essay on harms of smoking

Essay on Smoking

500 words essay on  smoking.

One of the most common problems we are facing in today’s world which is killing people is smoking. A lot of people pick up this habit because of stress , personal issues and more. In fact, some even begin showing it off. When someone smokes a cigarette, they not only hurt themselves but everyone around them. It has many ill-effects on the human body which we will go through in the essay on smoking.

Ill-Effects of Smoking

Tobacco can have a disastrous impact on our health. Nonetheless, people consume it daily for a long period of time till it’s too late. Nearly one billion people in the whole world smoke. It is a shocking figure as that 1 billion puts millions of people at risk along with themselves.

Cigarettes have a major impact on the lungs. Around a third of all cancer cases happen due to smoking. For instance, it can affect breathing and causes shortness of breath and coughing. Further, it also increases the risk of respiratory tract infection which ultimately reduces the quality of life.

In addition to these serious health consequences, smoking impacts the well-being of a person as well. It alters the sense of smell and taste. Further, it also reduces the ability to perform physical exercises.

It also hampers your physical appearances like giving yellow teeth and aged skin. You also get a greater risk of depression or anxiety . Smoking also affects our relationship with our family, friends and colleagues.

Most importantly, it is also an expensive habit. In other words, it entails heavy financial costs. Even though some people don’t have money to get by, they waste it on cigarettes because of their addiction.

How to Quit Smoking?

There are many ways through which one can quit smoking. The first one is preparing for the day when you will quit. It is not easy to quit a habit abruptly, so set a date to give yourself time to prepare mentally.

Further, you can also use NRTs for your nicotine dependence. They can reduce your craving and withdrawal symptoms. NRTs like skin patches, chewing gums, lozenges, nasal spray and inhalers can help greatly.

Moreover, you can also consider non-nicotine medications. They require a prescription so it is essential to talk to your doctor to get access to it. Most importantly, seek behavioural support. To tackle your dependence on nicotine, it is essential to get counselling services, self-materials or more to get through this phase.

One can also try alternative therapies if they want to try them. There is no harm in trying as long as you are determined to quit smoking. For instance, filters, smoking deterrents, e-cigarettes, acupuncture, cold laser therapy, yoga and more can work for some people.

Always remember that you cannot quit smoking instantly as it will be bad for you as well. Try cutting down on it and then slowly and steadily give it up altogether.

Get the huge list of more than 500 Essay Topics and Ideas

Conclusion of the Essay on Smoking

Thus, if anyone is a slave to cigarettes, it is essential for them to understand that it is never too late to stop smoking. With the help and a good action plan, anyone can quit it for good. Moreover, the benefits will be evident within a few days of quitting.

FAQ of Essay on Smoking

Question 1: What are the effects of smoking?

Answer 1: Smoking has major effects like cancer, heart disease, stroke, lung diseases, diabetes, and more. It also increases the risk for tuberculosis, certain eye diseases, and problems with the immune system .

Question 2: Why should we avoid smoking?

Answer 2: We must avoid smoking as it can lengthen your life expectancy. Moreover, by not smoking, you decrease your risk of disease which includes lung cancer, throat cancer, heart disease, high blood pressure, and more.

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Health Effects of Smoking

Smoking is the number one cause of preventable disease and death worldwide. Smoking-related diseases claim more than 480,000 lives in the U.S. each year. Smoking costs the U.S. at least $289 billion each year, including at least $151 billion in lost productivity and $130 billion in direct healthcare expenditures. 1

Key Facts about Smoking

• Cigarette smoke contains more than 7,000 chemicals, at least 69 of which are known to cause cancer. 2 Smoking is directly responsible for approximately 90 percent of lung cancer deaths and approximately 80 percent of deaths caused by chronic obstructive pulmonary disease (COPD), including emphysema and chronic bronchitis. 1
• Among adults who have ever smoked daily, 78% had smoked their first cigarette by the time they were 18 years of age, and 94% had by age 21. 3
• Among current smokers, 73% of their diagnosed smoking-related conditions are chronic lung diseases. Even among smokers who have quit, chronic lung disease still accounts for 50% of smoking-related conditions. 4
• Smoking harms nearly every organ in the body, and is a main cause of lung cancer and COPD. It also is a cause of coronary heart disease, stroke and a host of other cancers and diseases. 1 See more of the health effects caused by smoking.

Smoking Rates among Adults & Youth

• In 2017, an estimated 34.3 million, or 14.0% of adults 18 years of age and older were current cigarette smokers. 5
• Men tend to smoke more than women. In 2017, 15.8% of men currently smoked cigarettes daily compared to 12.2% of women. 5 
• Prevalence of current cigarette smoking in 2017 was highest among American Indians/Alaska Natives (24.6%), non-Hispanic whites (15.3%) and non-Hispanic blacks (15.1%), and was lowest among Hispanics (9.9%) and Asian-Americans (7.0%). 5
• In 2017, 7.6 % of high school students and 2.1% of middle school students were current cigarette users. 6

Facts about Quitting Smoking

• Nicotine is the chemical in cigarettes that causes addiction. Smokers not only become physically addicted to nicotine; they also link smoking with many social activities, making smoking an extremely difficult addiction to break. 7
• In 2017, an estimated 55.2 million adults were former smokers. Of the 34.3 million current adult smokers, 48.4% stopped smoking for a day or more in the preceding year because they were trying to quit smoking completely. 5
• Quitting smoking for good often requires multiple attempts. Using counseling or medication alone increases the chance of a quit attempt being successful; the combination of both is even more effective. 8
• There are seven medications approved by the U.S. Food and Drug Administration to aid in quitting smoking. Nicotine patches, nicotine gum and nicotine lozenges are available over the counter, and a nicotine nasal spray and inhaler are currently available by prescription. Bupropion SR (Zyban®) and varenicline (Chantix®) are non-nicotine pills. 8
• Individual, group and telephone counseling are effective. Telephone quitline counseling is available in all 50 states and is effective for many different groups of smokers. 8

Learn about the American Lung Association’s programs to help you or a loved one quit smoking , and join our advocacy efforts to reduce tobacco use and exposure to secondhand smoke. Visit Lung.org or call the Lung HelpLine at 1-800-LUNGUSA (1-800-586-4872).

The Health Effects of Smoking

U.S. Department of Health and Human Services. The Health Consequences of Smoking - 50 Years of Progress: A Report of the Surgeon General. 2014.

U.S. Department of Health and Human Services. How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease A Report of the Surgeon General. 2010.

Substance Abuse and Mental Health Services Administration. National Survey on Drug Use and Health, 2017. Analysis by the American Lung Association Epidemiology and Statistics Unit using SPSS software.

U.S. Department of Health and Human Services. The Health Consequences of Smoking: A Report of the Surgeon General, 2004.

Centers for Disease Control and Prevention. National Center for Health Statistics. National Health Interview Survey, 2015. Analysis performed by the American Lung Association Epidemiology and Statistics Unit using SPSS software.

Centers for Disease Control and Prevention. National Youth Tobacco Survey, 2017. Analysis by the American Lung Association Epidemiology and Statistics Unit using SPSS software.

National Institute on Drug Abuse. Tobacco/Nicotine Research Report: Is Nicotine Addictive? January 2018.

Fiore M, Jaen C, Baker T, et al. Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice Guideline. Vol 35. Rockville, MD; 2008.

Page last updated: May 2, 2024

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Cause and Effects of Smoking Cigarettes, Essay Example

Pages: 3

Words: 914

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Smoking cigarettes has historically been a leisurely and highly popular social activity that a litany of people turn to as a way to assuage daily stress, lose weight, and feel socially accepted in a constantly evolving social world. Tobacco, the main ingredient in cigarettes, has high levels of nicotine, which is a highly addictive ingredient that makes it hard for people to quit smoking if nicotine is ingested on a quotidian basis (Woolbright, 1994, p. 337). According to the CDC (2014), cigarette smoking causes over 480,000 deaths annually in the United States alone, which translates into one out of every five people extirpating due to the ingestion of tobacco. A preventable cause of death, cigarette smoking kills more persons than accidents caused due motor vehicle accidents, alcohol consumption, illegal drug use, deaths involving firearms, and the HIV/AIDS virus altogether (Center For Disease Control and Prevention, 2014). Women who smoke tobacco disproportionately suffer from even more health problems as it directly harms not only their reproductive health but also their mortality and morbidity rates of their progeny or future children (American Lung Association, n.d.). People should not smoke because it not only spawns negative health effects but also because it is not economically useful. If people stopped smoking, many lives would be both indirectly and directly saved from premature and preventative deaths as a result.

Doctors and other medical experts pinpoint the various health hazards caused by smoking, especially to the statistics pertaining to the nexus between smoking cigarettes and premature death, in order to convince people to quit smoking. In the past five decades, the risk of premature death in both female and male smokers has profoundly increased (Centers for Disease Control and Prevention, 2014). According to the CDC (2014), smoking cigarettes causes a handful of diseases because it adversely impacts almost all bodily organs and detracts from the general health of enthusiastic smokers. The risk of developing coronary heart disease (COPD), various cardiovascular maladies, and stroke–the leading cause of death in the United States alone–increases two to four times as much due to the damage it spawns to blood vessels because tobacco narrows and thickens them. These ramifications cause rapid heartbeat, which results in higher blood pressure levels which renders smokers vulnerable to blood clots. If blood clots prevent blood from reaching the heart, people put themselves  at risk for heart attack due to the fact that the heart does not get enough oxygen and thus kills the heart muscle. In addition, blood clots can also cause a stroke because they can hinder blood flow to the brain. Shockingly, quitting smoking even after just one year drastically enhances an individual’s risk of incurring poor cardiovascular health. Moreover, smoking is directly connected to various respiratory diseases due to the fact that it harms both airways and alveoli, or the minute air vacs, that are in the lungs. Chronic Obstructive Pulmonary Disease (COPD), emphysema, and bronchitis are common forms of lung disease that chronic smokers often develop. In addition, medical experts correlate cigarette smoking with a litany of cancers, which have been pinpointed as the primary cause of lung cancer in individuals who smoke for a protracted period of time. Smoking cigarettes can also spawn various other types of cancer, including cancer in the stomach, liver, kidneys, bladders, pancreas, and oropharynx. Smoking not only puts smokers at risk for these often fatal types of cancer but also to those around smokes as a result of second-hand smoking. Second-hand smoke, according to the CDC (2014), causes an estimated 34,000 deaths per year in non-smokers because they too develop various cardiovascular diseases while an estimated 8,000 persons prematurely dying as a result of stroke (CDC, 2014). They also are put at risk for developing lung cancer by approximately thirty percent, and their risk for heart attack is also amplified. Physicians estimate that if nobody smoked cigarettes around the world, an estimated one out of every three deaths caused by cancer would not manifest (1).

More poignantly, smoking cigarettes negatively impacts women’s reproductive health, and children who are exposed to cigarette smoke suffer from often fatal effects. Many studies have analyzed and outlined the negative ramifications of maternal smoking on both the mother and the baby and/or infant ( Hofhuis, de Jongste, & Merkus, 2003 & Woolbright, 1994). Many states require documentation on birth certificates of maternal tobacco consumption (Woolbright, 1994). Despite the Surgeon General’s stern warning that maternal smoking has been linked to fetal injury, premature birth, and/or low birth rate, 15-37% of pregnant women still smoke cigarettes while pregnant (Hofhuis, de Jongste, & Merkus, 2003). Mothers who smoke also frequently participate in other high-risk behaviors that also negatively impacts the health of their progeny. Additionally, factors including marital and socio-economic status in addition education level affect the outcome of pregnancies due to increased vulnerability to cigarette smoking (Woolbright, 1994, p. 330). Low birth weight is the main impact of maternal smoking, although the existing literature pinpoints infant death and premature birth as major ramifications of it as well. Infant exposure to tobacco after they are born puts him or her at risk of premature death if they develop respiratory diseases in addition to Sudden Infant Death Syndrome (Woolbright, 1994). Hofhuis, de Jongste, and Merkus (2003) assessed how smoking cigarettes during pregnancy in addition to passive smoking thereafter affects both the mortality and morbidity rates in children. Statistics show that other obstetric complications directly linked to smoking, including spontaneous abortions, premature rupture of membranes, ectopic pregnancies, and complications related to the placenta. Smoking also stunts the lung growth that fetuses need in utero, which results in the child suffering from weakened lungs after birth while also exponentially increases the child’s chance of suffering from asthma and a vast array of other crippling  respiratory diseases. In addition, it stunts brain development and detracts from the child’s mental acuity.

Health Effects of Cigarette Smoking. (2014, February 6).  Centers for Disease Control and Prevention . Retrieved November 21, 2015 from http://www.cdc.gov/tobacco/data_statistics/fact_sheets/health_effects/effects_ cig_smoking/

American Lung Association. (n.d.). Women and tobacco use.  American Lung Association . Retrieved November 21, 2015 from http://www.lung.org/stop- smoking/about-smoking/facts- figures/women-and-tobacco-use.html

Ault, R. W., Jr., R. E., Jackson, J. D., Saba, R. S., & Saurman, D. S. (1991). Smoking and Absenteeism. Applied Economics ,  23 , 743-754.

Hodgson TA. Cigarette Smoking and Lifetime Medical Expenditures.  Millbank Q  1992, 70, 81-125.

Hofhuis, W., de Jongste, J. C., & Merkus, P. J. (2003). Adverse Health Effects of Prenatal and Postnatal Tobacco Smoke Exposure on Children.  Arch Dis Child ,  88 , 1086-1090.

Woolbright, L. A. (1994). The effects of maternal smoking on infant health. Population Research and Policy Review ,  13 (3), 327-339.

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Essay on Smoking 250 & 500 Words-Causes, Effects & Quitting

This article is on Smoking essay. I have included two essays 500 words and 250 words in the article.

I have also included the causes, health benefits and side effects of smoking. There is also a paragraph on how to quit smoking. So let’s begin.

Table of Contents

What is Smoking?

Smoking refers to the inhalation and exhalation of smoke, typically from burning tobacco in cigarettes, cigars or pipes. This action introduces various harmful substances, including nicotine, tar, and carbon monoxide, into the body, leading to adverse health effects such as cancer, heart disease, and respiratory issues.

Essay on Smoking 500 Words.

Smoking, a practice deeply entrenched in history, has transcended generations and cultures, becoming an enduring habit within societies worldwide. However, its enduring prevalence belies a harsh reality — smoking is a perilous habit that not only imperils individual health but also casts a long shadow on societal well-being.

Origin of Smoking

The origins of smoking trace back centuries, intertwined with cultural practices, social rituals, and even medicinal applications. Tobacco, introduced to the Western world in the 16th century, swiftly captivated societies and, over time, became a pervasive habit ingrained in various social contexts. However, the appealing and often glamorous depiction of smoking in media and popular culture overshadowed its underlying health risks, contributing to its widespread acceptance.

Health Hazards Linked to Smoking

The grim truth lies in the severe health hazards linked to smoking. Countless studies affirm the deleterious impact of smoking on physical health, with lung cancer standing as one of its most notorious consequences. Beyond cancer, cardiovascular diseases, chronic obstructive pulmonary disease (COPD), and a myriad of other respiratory illnesses afflict those who succumb to this addictive habit. Moreover, the insidious nature of secondhand smoke further endangers non-smokers, amplifying health risks and affecting the wider community.

Social and Economic Impacts

Not confined solely to individual health, smoking exerts a profound societal and economic toll. Socially, smokers often face stigma and discrimination, influencing personal relationships, employment opportunities, and societal perceptions. Moreover, the economic burden of smoking cannot be overlooked, with substantial healthcare costs and decreased productivity due to illness directly related to smoking.

Regulations and Anti-Smoking Campaign

Despite these grim realities, efforts to curb smoking have been ongoing. Government policies and regulations, such as increased taxes on tobacco products and stringent smoking bans, aim to deter smoking and protect public health. Additionally, anti-smoking campaigns and educational programs seek to raise awareness about the hazards of smoking and encourage cessation.

Smoking Cessation and Support Systems

Smoking cessation programs and support systems play a pivotal role in helping individuals break free from the clutches of this addictive habit. Counselling, nicotine replacement therapies, and support groups have shown promise in assisting individuals in their journey toward a smoke-free life. However, the challenges in achieving high cessation rates persist, underlining the complexity of combating this pervasive habit.

Opposing views often arise, advocating for personal freedoms and questioning the efficacy of stringent regulations. Nevertheless, the overwhelming body of evidence supports the dire need for comprehensive measures to reduce smoking rates, safeguard public health, and alleviate the associated societal burdens.

In conclusion, smoking stands as a pressing public health concern with far-reaching repercussions. Its detrimental impact on individual health, society, and the economy necessitates a unified effort to combat its prevalence. Through stringent policies, robust cessation programs, and continued awareness campaigns, a concerted approach is essential to mitigate the devastating effects of smoking. As a society, it’s crucial to recognize the urgency of this issue and work collectively to create a healthier, smoke-free future for generations to come.

This essay aims to shed light on the multifaceted repercussions of smoking, emphasizing the imperative for comprehensive measures to address this pressing public health concern.

Write a paragraph on how Smoking is dangerous- 250 Words Essay

Smoking, in all its forms, represents a multifaceted danger that permeates far beyond the individual act of lighting a cigarette. At its core, smoking is a perilous habit that encompasses a multitude of health risks, causing irreparable harm to the human body.

The most widely recognized consequence is its link to various forms of cancer, particularly lung cancer, which stands as one of the deadliest outcomes of prolonged tobacco use.

However, the perils of smoking extend well beyond cancer, affecting almost every organ in the body. Cardiovascular diseases, respiratory ailments and compromised immune systems are just a few examples of the numerous health risks associated with smoking.

Equally concerning is the impact of secondhand smoke, which imperils the health of those in the vicinity of a smoker. This involuntary exposure significantly heightens health risks, emphasizing the danger not only to the smoker but also to those in their proximity.

Moreover, the addictive nature of nicotine in tobacco further entrenches this perilous habit, making it arduous for individuals to break free from its grasp. The societal and economic repercussions also cannot be understated, as smoking places a heavy burden on healthcare systems, decreases workforce productivity and fosters a climate of social disparity.

Collectively, smoking emerges not merely as an individual habit but as a complex, interconnected issue that imperils the well-being of individuals and societies alike, emphasizing the critical need for comprehensive measures to address and mitigate its dire consequences.

what are the causes of smoking

There are many causes of smoking and can be attributed to a variety of factors, including:

• Social and Cultural Influences: Social norms and cultural perceptions play a significant role in smoking initiation. In some societies, smoking is seen as a symbol of status, rebellion or a social activity, leading individuals, especially adolescents to take up smoking to conform or rebel against social norms.
• Peer Pressure: The influence of friends, peers and social circles can heavily impact an individual’s decision to smoke. People, especially in their formative years, may start smoking to fit in with certain groups or to be accepted by their peers.
• Family Influence: Family environment and exposure to smoking behaviours within the family can greatly influence one’s likelihood to smoke. Children growing up in households with smokers may view smoking as normal behaviour and may be more inclined to start smoking themselves.
• Psychological Factors: Stress, anxiety, depression or other psychological factors can lead individuals to use smoking as a coping mechanism. The addictive nature of nicotine in cigarettes provides temporary relief from stress or emotional turmoil, leading to continued use.
• Marketing and Advertising: Aggressive marketing and advertising by tobacco companies have historically played a significant role in enticing people to start smoking. Colourful packaging, appealing advertisements and endorsements by celebrities have been used to glamorize smoking.
• Addictive Nature of Nicotine: Nicotine, a highly addictive substance in tobacco, makes it challenging for individuals to quit once they start smoking. The physical and psychological dependence on nicotine makes it harder for individuals to break the habit.
• Accessibility and Availability: The easy access and availability of tobacco products, combined with relatively low legal age restrictions in some areas, contribute to the ease of starting and continuing smoking.

good side effects of smoking cigarettes

It’s crucial to note that smoking cigarettes poses a significant health risk and the negative effects of smoking far outweigh any potential positives. However, for the sake of providing a comprehensive view, some individuals might claim certain perceived “benefits” or effects of smoking, though these should not be interpreted as justifications for smoking due to the overwhelming negative health consequences. Here are a few perceptions that some individuals might assert as positive side effects of smoking, though they are not endorsed as valid benefits due to the associated health risks: see also- National Library of Medicine

• Weight Control: Some individuals believe that smoking suppresses appetite and helps in weight management. Nicotine is known to act as an appetite suppressant, leading to potential weight loss or control. However, any weight management effects come with the substantial health risks of smoking, far outweighing any potential benefit.
• Stress Relief: Certain smokers perceive that smoking provides stress relief or relaxation. They may feel a temporary sense of relaxation or relief due to the immediate impact of nicotine on the brain. However, the relief is short-term and is often overshadowed by the long-term negative health consequences of smoking.
• Improved Concentration: Some individuals report that smoking helps in concentration or focus. This might be due to the stimulating effect of nicotine, which can temporarily enhance cognitive function. Nonetheless, the health risks associated with smoking significantly outweigh any potential cognitive benefits.

It’s essential to emphasize that any perceived “benefits” of smoking are greatly outweighed by the severe and well-documented health risks. The detrimental effects of smoking on health, including its contribution to various life-threatening diseases like cancer, heart disease, respiratory ailments, and numerous other health complications, far eclipse any temporary or perceived advantages. Encouraging a smoke-free lifestyle remains the most important message to promote overall health and well-being.

harmful effects of smoking

The harmful effects of smoking are extensive and well-documented, impacting nearly every organ and system in the body. Here are some of the primary detrimental health consequences associated with smoking:

• Respiratory Issues: Smoking is a leading cause of various respiratory problems, including chronic obstructive pulmonary disease (COPD), chronic bronchitis and emphysema. It damages the airways and alveoli in the lungs, leading to breathing difficulties and decreased lung function.
• Cancer: Smoking is the primary cause of various types of cancer, particularly lung cancer. It is also associated with cancers of the mouth, throat, oesophagus, bladder, pancreas, kidney and cervix, among others.
• Cardiovascular Disease: Smoking significantly increases the risk of heart disease, leading to conditions such as coronary artery disease, heart attack, stroke and peripheral arterial disease. It contributes to the narrowing of blood vessels and increases blood clotting, elevating the risk of cardiovascular issues.
• Compromised Immune System: Smoking weakens the immune system, making individuals more susceptible to infections and illnesses. It reduces the body’s ability to fight off diseases and impedes the healing process.
• Reproductive Health Issues: Both male and female reproductive systems are adversely affected by smoking. In men, it can lead to reduced sperm count and erectile dysfunction. In women, smoking can affect fertility, increase the risk of miscarriage and lead to complications during pregnancy.
• Damage to Skin and Appearance: Smoking accelerates skin ageing, causes wrinkles, and leads to a dull complexion. It also increases the risk of developing skin conditions like psoriasis.
• Oral Health Problems: Smoking causes various oral health issues, including gum disease, tooth decay, tooth loss and an increased risk of oral cancers.
• Secondhand Smoke Effects: Non-smokers exposed to secondhand smoke are also at risk. They can experience similar health issues, including respiratory problems, heart disease and an increased risk of certain cancers.
• Economic and Social Implications: Smoking leads to significant economic burdens due to healthcare costs, loss of productivity, and absenteeism. It also contributes to social disparities and creates a burden on public health systems.

The harmful effects of smoking are both immediate and long-term, affecting not only the individual who smokes but also those exposed to secondhand smoke. It’s vital to understand and communicate the grave health risks associated with smoking to promote awareness and encourage smoking cessation for overall health and well-being.

Here are some statistics, you may like to read-

How to Quit Smoking

Quitting smoking is a challenging but incredibly rewarding endeavour. Here are some steps and strategies to help in the process of quitting:

• Set a Quit Date: Choose a specific date to quit smoking. Having a clear goal in mind can help mentally prepare for the change.
• Identify Triggers: Recognize the situations, feelings or habits that trigger the urge to smoke. These triggers could be stress, certain social settings or specific times of the day.
• Create a Support System: Inform friends, family and colleagues about your decision to quit. Having a support network can provide encouragement, understanding and accountability.
• Seek Professional Help: Consider consulting a healthcare professional. They can provide guidance, recommend cessation aids and create a tailored plan to quit smoking.
• Explore Nicotine Replacement Therapy (NRT): NRT, such as patches, gum, lozenges, inhalers or nasal sprays, can help manage withdrawal symptoms by providing controlled doses of nicotine without the harmful effects of smoking.
• Consider Prescription Medications: Certain prescription medications, like bupropion or varenicline, may be recommended by healthcare providers to help reduce cravings and withdrawal symptoms.
• Behavioural Support and Counseling : Behavioral therapy or counselling sessions, whether one-on-one or in group settings, can provide coping strategies, address triggers, and offer emotional support during the quitting process.
• Stay Active and Busy: Engage in physical activities or hobbies that keep your mind and body occupied. Exercise can help reduce stress and improve mood.
• Change Habits and Routines: Identify and modify routines or habits associated with smoking. For example, if you usually smoke after meals, find an alternative activity to replace this habit.
• Stay Persistent and Positive: Quitting smoking might not be easy and setbacks might occur. Stay positive and persistent. Even if there are relapses, use them as learning experiences to continue the journey toward being smoke-free.
• Celebrate Milestones: Acknowledge and celebrate each small success along the way. Whether it’s a day, a week or a month without smoking, it’s a significant achievement worth recognizing.
• Avoid Triggers and Temptations: Steer clear of situations or environments that may tempt you to smoke. This could mean avoiding places or people that encourage the habit.

Quitting smoking is a process that differs for each individual. Finding the right combination of strategies and support is crucial. Remember, the benefits of a smoke-free life – improved health, better quality of life, and saving money – are worthwhile and serve as strong motivators.

Thank you for reading the essay on smoking. I hope you have now clear knowledge about the causes of smoking, the good and the bad effects of smoking and how to quit smoking.

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• Speech on Pollution

Smoking, a prevalent habit, poses severe health risks. It’s a leading cause of preventable deaths worldwide, linked to cancer, heart disease, and respiratory issues. Nicotine addiction compounds its challenges. Efforts to curb smoking include public awareness campaigns, cessation programs, and stricter regulations to promote healthier lifestyles and reduce its detrimental impact.

Smoking involves inhaling smoke, usually from burning tobacco, introducing harmful substances into the body. Nicotine, an addictive component in tobacco, reinforces the habit. Smoking is linked to severe health risks, including cancer and cardiovascular diseases. It poses dangers to both smokers and non-smokers, impacting public health, society, and the environment.

Smoking is harmful due to its association with severe health risks, including cancer, respiratory diseases, and cardiovascular problems. Nicotine addiction compounds the issue, making cessation challenging. Secondhand smoke poses dangers to non-smokers. Social stigma, economic burdens and environmental pollution further emphasize the detrimental impact of smoking on both individual health and society at large.

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Smoking and Its Effects on Human Body Essay

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Introduction

Works cited.

Smoking is one of the oldest traditions followed by millions of people in the world. Despite pleasure and positive feelings, smoking is dangerous as it harms the human body and tissues. Smoking is dangerous as it leads to health-related problems including cardiovascular disease. According to Carr (22), one-third of all deaths in America are caused by coronary heart disease, and at least 30 percent of these deaths are related to smoking. Smoking affects the lungs and respiratory organs causing such terrible diseases as cancer. Among the most wider spread diseases are peptic ulcers, cancer of the larynx, kidney, pancreas, and other major organs. The resins from the smoke enter the blood and ruin cells. This process is inevitable if a person smokes for years. Also, smoking harms the fetus, increasing the risk of spontaneous abortion and low birth weight.

The investigators explain the effects of smoking on the breath as follows: the rapid pulse rate of smokers decreases the stroke volume during rest since the venous return is not affected and the ventricles lose the habit and ability to make large strokes. Similar conditions arise during strenuous exercise, that is, with the rapid heart rate, the diastolic filling is incomplete and the stroke output remains small. This results in a relatively small unit circulation and oxygen supply to the tissues with the result that an oxygen debt must be incurred. This ends in breathlessness and dyspnœa. Just giving the facts is not enough. Attitudes and behaviors need to be addressed (Rabin and Sugarman, p. 43).

Students want behavioral tips on how to maintain peer acceptability while avoiding the pressure to show how cool they are b smoking. While cigarette ads on television and radio are forbidden, “gifts” of cigarettes to minors (particularly in minority communities) are not discouraged as an advertisement ploy. Moreover, the interlacing of beer ads with sports events and wine cooler ads with upscale women’s television programming sends strong messages to young people about how society views substance use. Role-plays, debates, “raps,” and antismoking jingles allow students an active exploration of their motivation for wanting or not wanting to smoke. These techniques encourage youngsters to think for themselves, to develop their judgments and attitudes (Carr, p. 87). Recently, studies by Rabin and Sugarman (2003) have demonstrated an increased cancer risk in adulthood among children who were exposed to parental smoking in their early years. An overview of the health effects of passive smoking on children and adults is the same as on active smokers. Smoking has direct physiological effects on the body, and the cumulative wear and tear on the system caused by recurring stress can eventually cause damage to the system. Indeed, there is abundant evidence that stress can cause several physiological and biochemical changes (Cnossen, p. 31).

In sum, smoking harms the human body ruining healthy cells and tissues. Smoking is dangerous as it leads to inevitable changes in blood and tissues of the heart and lungs. Smoking can cause neural and endocrine change that alters the normal functioning of the organism (e.g., change in cardiovascular activity or immune system functioning). This physiological stress response is accompanied by behavioral responses as well. Smoking and the subsequent behavioral response to it can affect health and facilitate, if not cause, some illnesses.

• Carr, A. The Easy Way to Stop Smoking: Join the Millions Who Have Become Non-Smokers Using Allen Carr’s Easyway Method. Sterling; 1 edition, 2005.
• Cnossen, S. Theory and Practice of Excise Taxation: Smoking, Drinking, Gambling, Polluting, and Driving. Oxford University Press, 2005.
• Rabin, R. L., Sugarman, S.D. Regulating Tobacco. Oxford University Press, 2001.
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• Advertising and Child Obesity: Content Analysis of Food Commercial on Saturday Morning Television
• You Can’t Smoke Before 18
• Language in “The Wanting Seed” and “1985” by Anthony Burgess
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Student Essays

Essay on Smoking [ Causes & Harms of Smoking ]

This simple essay talks about Smoking, Why people Smoke, how smoking is harmful for us in life, how to avoid smoking in life etc. This essay is written in simple English with easy to understand words for children and students.

Essay on Smoking | Causes of Smoking | Harms Caused by Smoking, How to Avoid Smoking

Smoking is dangerous habit. People who smoke cigarettes can get addicted to it very easily. It is hard to quit smoking once you have started because nicotine is present in cigarettes which is a very addictive substance. Cigarette smoking not only harms the smoker, but also the people around him or her.

Smoking is a bad habit. People who smoke know it is harmful to them and yet they continue smoking. It is an addiction like any other drug addiction such as alcoholism or drug abuse. Smokers become addicted to the nicotine in cigarettes. Nicotine is a drug that is found in tobacco leaves. It is this drug that makes smoking so addictive. Smoking is harmful to our health in many ways. It can cause lung cancer, heart disease, and other health problems.

Secondhand smoke is also harmful. Secondhand smoke is the smoke that comes from the burning end of a cigarette, pipe, or cigar. It is also the smoke exhaled by a smoker. Secondhand smoke is dangerous because it contains the same harmful chemicals that smokers breathe in.

>>>> Read Also: ”  Speech on Noise Pollution “

Causes of smoking addiction:

Few of the most common causes of getting people addicted to smoking are;

1) Curiosity: Most of the time, people start smoking just out of curiosity. They want to know what it feels like or they see their friends smoking and they want to try it.

2) Peer Pressure: Another reason why people start smoking is because of peer pressure. Their friends or people they admire smoke and they want to be like them.

3) Stress: Some people start smoking to relieve stress. They think it relaxes them, but it actually doesn’t.

4) Depression: People who are depressed sometimes start smoking because they think it will make them feel better.

These are some of the reasons why people start smoking. Once they start, it’s hard to stop.

Smoking is harmful to our health:

Like we said before, smoking is very harmful to our health. Smoking cigarettes can cause lung cancer, throat cancer, and mouth cancer. It also can cause heart disease, strokes, and other health problems. Smoking is also terrible for the environment. Cigarette butts are the most littered item in the world. They pollute our water and land.

Ways to Avoid Smoking:

There are many ways to avoid smoking. The best way is to never start smoking. If you are a smoker, you can quit smoking by slowly reducing the number of cigarettes you smoke each day. You can also try using nicotine gum or patches to help you quit smoking. However, following are the most effective ways to quit smoking for good.

Disassociate yourself from Smoking Company: The majority of smokers usually smoke with the same group of people. These people can be friends, family members, or colleagues. If you want to quit smoking, it is important that you disassociate yourself from these people. This means avoiding places where these people usually smoke, such as bars or clubs. It is also important to avoid social situations where smoking is likely to take place, such as parties.

Identify Your Triggers: Another way to avoid smoking is to identify your triggers. A trigger is anything that makes you want to smoke. Common triggers include drinking alcohol, coffee, or tea; being around other smokers; and feeling stressed. Once you know what your triggers are, you can avoid them.

Use a Nicotine Replacement Therapy: Nicotine replacement therapy is a great way to help you quit smoking. This therapy involves using products that contain nicotine, such as gum, patches, or lozenges. These products help to ease withdrawal symptoms and cravings.

Get Support: Quitting smoking is not easy. It is important to get support from family and friends. You can also join a support group. These groups can provide you with helpful information and support. Smoking is a bad habit that is harmful to our health. There are many ways to avoid smoking, such as disassociating yourself from smokers, identifying your triggers, Quitting smoking is not easy.

It takes a lot of willpower and effort. But it can be done. And, it is worth it because quitting smoking will improve your health and the health of those around you.

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• Open access
• Published: 12 July 2024

Effectiveness of smoking cessation interventions among adults: an overview of systematic reviews

• Mona Hersi 1 ,
• Andrew Beck 2 ,
• Candyce Hamel 1 ,
• Leila Esmaeilisaraji 1 ,
• Kusala Pussegoda 1 ,
• Bradley Austin 3 ,
• Nadera Ahmadzai 1 ,
• Misty Pratt 1 ,
• Micere Thuku 3 ,
• Fatemeh Yazdi 1 ,
• Alexandria Bennett   ORCID: orcid.org/0000-0002-5977-2094 2 ,
• Nicole Shaver 2 ,
• Niyati Vyas 2 ,
• Becky Skidmore 4 ,
• Brian Hutton 1 , 3 ,
• Douglas Manuel 3 , 5 , 6 , 7 , 8 ,
• Matt Morrow 9 ,
• Smita Pakhale 3 , 6 , 8 ,
• Justin Presseau 3 , 8 , 10 ,
• Beverley J. Shea 1 , 3 ,
• Julian Little 8 ,
• David Moher 8 &
• Adrienne Stevens 1  

Systematic Reviews volume  13 , Article number:  179 ( 2024 ) Cite this article

754 Accesses

Metrics details

This overview of reviews aims to identify evidence on the benefits (i.e. tobacco use abstinence and reduction in smoking frequency) and harms (i.e. possible adverse events/outcomes) of smoking cessation interventions among adults aged 18 years and older.

We searched Medline, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, the CADTH Health Technology Assessment Database and several other websites for grey literature. Searches were conducted on November 12, 2018, updated on September 24, 2020, with publication years 2008 to 2020. Two reviewers independently performed title-abstract and full-text screening considering pre-determined inclusion criteria. Data extraction and quality assessments were initially completed by two reviewers independently (i.e. 73% of included studies ( n = 22)) using A Measurement Tool to Assess Systematic Reviews-2 (AMSTAR 2), and the remainder done by one reviewer and verified by another due to resources and feasibility. The application of Grading of Recommendations Assessment, Development and Evaluation (GRADE) was performed by one independent reviewer and verified by another.

A total of 22 Cochrane systematic reviews evaluating the impact of smoking cessation interventions on outcomes such as tobacco use abstinence, reduction in smoking frequency, quality of life and possible adverse events were included. Pharmaceutical (i.e. varenicline, cytisine, nicotine replacement therapy (NRT), bupropion) and behavioural interventions (i.e. physician advice, non-tailored print-based self-help materials, stage-based individual counselling, etc.) showed to have increased smoking cessation; whereas, data for mobile phone-based interventions including text messaging, hypnotherapy, acupuncture, continuous auricular stimulation, laser therapy, electrostimulation, acupressure, St John’s wort, S-adenosyl-L-methionine (SAMe), interactive voice response systems and other combination treatments were unclear. Considering harms related to smoking cessation interventions, small/mild harms (i.e. increased palpitations, chest pain, nausea, insomnia, headache) were observed following NRT, varenicline and cytisine use. There were no data on harms related to behavioural therapies (i.e. individual or group counselling self-help materials, internet interventions), combination therapies or other therapies (i.e. laser therapy, electrostimulation, acupressure, St John’s wort, SAMe).

Results suggest that pharmacological and behavioural interventions may help the general smoking population quit smoking with observed small/mild harms following NRT or varenicline. Consequently, evidence regarding ideal intervention strategies and the long-term impact of these interventions for preventing smoking was unclear.

Systematic review registration

PROSPERO CRD42018099691

Peer Review reports

Prevalence and burden of tobacco smoking

The World Health Organization (WHO), under their 2013 Framework Convention on Tobacco Control, was able to commit 194 countries to a global target reduction in smoking rates of 30% by 2025 [ 1 , 2 ]. In 2010, the global prevalence of current smokers was 22.1% and estimated to decrease to 18.9% in 2025 [ 2 ]. In Canada, between 1999 and 2020, there has been an overall reduction in the prevalence of current smokers (i.e. defined as those being daily and non-daily smokers) [ 3 , 4 ]. According to the 2022 Canadian Tobacco and Nicotine Survey (CTNS), the prevalence of current cigarette smoking among adults aged 25 years and older was 11.7% (95% CI: 10.8 to 12.7), unchanged from 2021; however, the prevalence was higher among adult men compared to adult women (13.8% versus 9.8%) [ 5 ]. The prevalence of past-30-day use of at least one tobacco product was 10.7% (95% CI: 9.3 to 12.1) among young adults aged 20 to 24 years and 13.6% (95% CI: 12.6 to 14.6) among adults aged 25 years and older, all unchanged from 2021 [ 5 ]. The health economic burden due to the prevalence of smoking was approximately $16.2 billion Canadian dollars in 2012, comprising $9.5 billion in indirect costs (e.g. economic costs associated with increased morbidity and mortality) and $6.5 billion in direct costs (e.g. hospital expenditures, physician care, medications) [ 6 ].

Smoking continues to be one of the leading causes of preventable deaths globally [ 7 ]. In 2012, 45,464 deaths in Canada were attributable to smoking (approximately 599,390 potential years of life lost) and 993 deaths were due to secondhand smoke exposure [ 6 ]. In addition to various cancers (e.g. mouth, lung, bladder, cervix, colon, rectum) and cardiovascular disease (e.g. coronary heart disease, stroke, atherosclerosis, aortic aneurysm, peripheral heart disease), smoking can cause reproductive issues (e.g. infertility, spontaneous abortion, premature birth, low birth weight), neonatal death, sudden infant death syndrome, early menopause and osteoporosis, among other conditions like lung diseases (e.g. emphysema, chronic bronchitis, etc.) [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ].

Smoking cessation, the act of discontinuing the use of tobacco smoking, has been shown to improve general, mental and physical health aspects of quality of life within a week of quitting and these improvements are maintained over time [ 7 , 16 , 17 , 18 ]. A Canadian study found that men who had quit for 20 years had the same quality of life as those who had never smoked; this observation was even more beneficial for females, who only had to quit for 10 years [ 19 ]. Quitting smoking is beneficial at any age and reduces the excess morbidity risk experienced by smokers for a multitude of cancers, as well as outcomes related to cardiovascular disease, chronic respiratory disease/COPD, asthma and reproductive health [ 20 ].

As per the 2022 CTNS survey, the prevalence of former smoking was 23.2% among Canadians aged 15 years and older, unchanged from 2021 (22.7%) [ 5 ]. Among those reporting as former smoker, 4.2% had quit less than one year ago, 5.6% had quit between 1 and 2 years ago, 9.8% between 3 and 5 years ago and 80.4% had quit over 5 years ago [ 5 ]. About 62.4% of respondents reported independently quitting smoking as one of the cessation methods, whereas 39.5% reported reducing the number of cigarettes smoked, 28.2% reported switching to vaping and 26.3% reported using nicotine replacement products within the past 12 months [ 5 ]. Information on various smoking cessation interventions, including pharmacotherapies, behavioural therapies, exercise and other interventions can be found in Additional file 1. Different stop smoking interventions have been offered in randomized trials; however, the outcome criteria (e.g. measuring smoking abstinence, point prevalence abstinence, or continuous abstinence) and aspects of follow-up and analysis vary across trials leading to difficulties in interpretation [ 21 ]. West et al. proposed standardization based on six criteria (duration of abstinence of 6 or 12 months, self-report of abstinence, biochemical verification, following up with protocol violators, collecting follow-up data blind to specific allocation groups, using intention-to-treat (ITT) approach in analysis) to define smoking abstinence and provide guidance for analysis and trial data reporting, to address this issue arising from such variation between trials [ 21 ]. These have become known as the Russell Standard criteria enabling a meaningful comparison across trial results assessing smoking cessation interventions [ 21 ].

Current guideline recommendations

Canadian guidelines.

In 2011, the Canadian Action Network for the Advancement, Dissemination and Adoption of Practice-informed Tobacco Treatment (CAN-ADAPTT) released its guidelines for smoking cessation [ 22 ]. For guideline development, CAN-ADAPTT adopted the ADAPTE process consisting of three phases: planning and set-up, adaptation and development of the final product [ 23 ]. The guideline development group reviewed the extracted evidence from relevant pre-existing high-quality clinical practice guidelines (CPGs) and developed summary statements based on clarity of risk, benefits and quality of the supporting evidence. The grades of recommendations and levels of evidence were assigned using a modified GRADE approach [ 22 ], using the GRADE guiding table compiled by UpToDate [ 24 ]. Briefly, the guideline was separated into two cessation methods: (a) counselling and psychosocial approaches and (b) pharmacotherapy [ 22 ]. CAN-ADAPTT recommends combining counselling (i.e. self-help, individual/group, telephone quitline, web-based) or motivational interviewing and pharmacotherapy, when feasible. Counselling should be provided for a minimum of four sessions with incorporated problem-solving, skills training and providing support. Follow-up by healthcare professionals is recommended [ 22 ]. CAN-ADAPTT also provided separate guideline recommendations for specific sub-group populations: pregnant and breastfeeding individuals, youth, indigenous communities, hospitalized patients, people living with mental health conditions and people with addictions other than to tobacco [ 22 ].

The 2017 Registered Nurses Association of Ontario based their guideline recommendations from a systematic review capturing evidence from 6 international clinical practice guidelines and 53 peer-reviewed articles [ 25 ]. Briefly, the guidelines advocate for recommendations based on the level of evidence separated into the following areas: assessment (screen smoking patients), planning (develop intervention plan), implementation (provide intensive intervention and counselling on the use of pharmacotherapies and for pregnant individuals to provide intensive interventions in conjunction with NRT), evaluation (evaluate effectiveness until goals are attained) and education (continually updating education for health care professionals) [ 25 ]. The Association considered evidence for the effectiveness of e-cigarettes, hypnotherapy, laser therapy, electrostimulation, acupressure and acupuncture to be insufficient [ 25 ].

Guidelines from international organizations

Various international guidelines have been published, all of which generally recommend behavioural interventions either alone or in combination with pharmacotherapies, such as NRT, bupropion and varenicline. The United Kingdom (UK) National Institute for Health and Care Excellence (NICE, 2023) recommends very brief advice, individual or group behavioural support, bupropion, short- and long-acting NRT, varenicline, nicotine containing e-cigarettes and/or in-person group seminar [ 26 ]. New Zealand’s Ministry of Health (2021) recommends the combination use of behavioural interventions and pharmacotherapies. It also stipulates that brief advice (approximately 30 s), behavioural support, NRT, bupropion, varenicline and nortriptyline are the most effective cessation aids [ 27 ]. The Scottish Intercollegiate Guidelines Network (2017) recommends varenicline or combination NRT alone or as part of a behavioural intervention and bupropion combined with a single NRT [ 28 ]. The United States Preventive Services Task Force (USPSTF) released their 2021 guideline, which recommends alone or the combined use of behavioural interventions and FDA-approved pharmacotherapies for tobacco cessation with high certainty of evidence [ 29 ]. The Royal Australian College of General Practitioners (RACGP) recommends brief smoking cessation advice and pharmacotherapies (NRT, varenicline, bupropion) accompanied by behavioural support based on efficacy, clinical suitability and patient preference [ 30 ]. The American Thoracic Society Clinical Practice Guideline (2020) also recommends pharmacotherapy choices to improve patient-centred care of tobacco dependence [ 31 ].

To address smoking cessation strategies relevant to the Canadian context and given a large amount of rapidly accumulating evidence, an approach capitalizing on available systematic review evidence was developed.

The aim of this overview of reviews is to inform the development of the Canadian Task Force on Preventive Health Care’s (CTFPHC) clinical practice guideline on smoking cessation interventions in adults. This overview of reviews addresses the following key question (KQ): what are the benefits and harms of interventions to promote cessation of tobacco smoking in adults?

We conducted an evidence review that occurred in two stages. First, the subject of this paper is an overview of systematic reviews that aims to evaluate the benefits and harms of various smoking cessation interventions for adults. Second is a systematic review update that aims to synthesize recent evidence on the benefits and harms of e-cigarettes as a smoking cessation intervention. The results of the present review were used to identify the candidate systematic review for the second stage and the results of stage two are reported elsewhere. For the purposes of this evidence review, tobacco smoking refers to any form of smoked tobacco (e.g. cigarettes, pipes, cigars, cigarillos, via water pipe or hookah) but excludes tobacco use for traditional or ceremonial purposes. We used the Preferred Reporting Items for Overviews of systematic reviews (PRIOR) (Additional file 2) as a guide for reporting, where relevant [ 32 ], and other reports to help us make informed decisions while conducting overview of reviews of healthcare interventions [ 33 , 34 , 35 ].

Literature sources and search strategy

The search strategy was developed through an iterative process by an experienced medical information specialist in consultation with the review team. The MEDLINE search strategy was peer-reviewed prior to execution using the Peer Review of Electronic Search Strategies Checklist (Additional file 3) [ 36 ]. Using the multifile option and deduplication tool on Ovid, we searched Ovid MEDLINE® ALL, Embase Classic + Embase, PsycINFO, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects and the Health Technology Assessment database (Additional file 4) on November 13, 2018. We updated the search on September 24, 2020. The strategies used a combination of controlled vocabulary (e.g. ‘Smoking Cessation’, ‘Tobacco Use Disorder/drug therapy’, ‘Tobacco Use Cessation Products’) and free-text terms (e.g. quit smoking, nicotine replacement, vaping). The results were limited to the publication years 2008 to 2020 and, where possible, animal-only and opinion pieces were removed.

We searched for unpublished English or French language literature and reports using the Canadian Agency for Drugs and Technologies in Health (CADTH) Grey Matters checklist [ 37 ]. The list of websites searched for grey literature are included in Additional file 5. We also scanned reference lists of relevant systematic reviews and overviews for grey literature sources as well as references not captured by the electronic database search.

Eligibility criteria

Cochrane systematic reviews with or without meta-analysis were selected for inclusion according to criteria specified in Additional file 6. Briefly, the overview focuses on general populations, those either specifically motivated or not motivated to quit or those living with mental illness in whom various interventions are compared with an inactive, minimally active or usual care control. To determine eligibility of comparators for a given analysis, we relied on information reported at face value by review authors. For example, we included comparators explicitly reported as ‘placebo’ by review authors even if it was apparent from review evidence tables that some trials in the analysis used a control condition other than placebo, including active controls (e.g. smoking cessation advice).We excluded analyses if authors explicitly signalled that trials with varying control conditions were included in the analysis (e.g. comparators identified as ‘placebo or no NRT’ where the latter could include various control conditions such as advice or counselling). Where comparators were not clearly reported by review authors (e.g. labelled only as ‘control’), we scrutinized review evidence tables to determine control conditions across trials; we excluded analyses where all trials had an active control condition or if there was a mix of both active and inactive control conditions across trials. Analyses that combined trials of various interventions, such that the effect of each cannot be isolated, were excluded post hoc due to limited utility of these data. For example, we would exclude analyses of ‘smoking cessation pharmacotherapies versus placebo’ where individual trials of different pharmacotherapy interventions (e.g. NRT, varenicline, bupropion) are combined in a meta-analysis. This is distinct from combination interventions where the intent is to test the synergistic effect of interventions; these interventions were relevant for inclusion as we restricted inclusion to Cochrane reviews, and the potential for overlapping outcome data was minimized [ 33 ]. Therefore, the extent of primary study overlap across reviews was not assessed and no attempt was made to assess the extent of concordance or discordance across potentially overlapping reviews. However, any instances of duplicate analyses across reviews are noted in the results section. To align with other smoking outcomes, we only included smoking reduction data if reported a minimum of 6 months from quit date or intervention initiation. To be consistent with included reviews, we considered smoking reduction data reported from quit date or intervention initiation between 24 and 26 weeks to match the 6-month criterion as the timing of outcome assessment.

Study selection

Literature search results were downloaded and deduplicated in a reference manager (Reference Manager 12, Thomson Reuters, New York, USA) [ 38 ]. Remaining citations were uploaded to an online systematic review management software (DistillerSR, Evidence Partners, Ottawa, Canada) for study selection [ 39 ]. Two reviewers independently screened titles and abstracts of records according to the liberal accelerated method whereby a second reviewer only verifies records excluded by the first reviewer. References were randomized to ensure that one reviewer could not determine whether a given reference was excluded by another reviewer. Full-text screening was conducted by two reviewers independently. Disagreements were resolved by consensus or third-party arbitration.

Screening forms were piloted by all reviewers prior to screening commencement. Where necessary, articles were ordered via interlibrary loan and included if received within 30 days. The exclusion of records due to unavailability is noted in Additional file 7.

Data extraction

Data extraction was conducted using DistillerSR following a calibration exercise. Data extraction items in detail are available in Additional file 8. Of the reviews included ( n = 22), data were extracted independently by two reviewers for 73% of reviews. For the remainder of reviews, data were extracted by one reviewer and verified by a second reviewer due to resources and feasibility. For both procedures, disagreements were resolved by consensus or third-party arbitration.

We collected review characteristics and outcome data as reported by review authors. For meta-analyses, we reported the pooled effect estimates along with corresponding confidence intervals and heterogeneity statistics (e.g. I 2 ). We also redrew forest plots for all relevant analyses (Additional file 9) using the Cochrane Review Manager software [ 40 ]. Where a meta-analysis was not performed, we collected outcome data as reported by review authors (e.g. vote count, narrative synthesis). Data were collected for all relevant timepoints of follow-up. We did not consult primary studies for the purposes of data extraction, risk of bias assessments or for checking the accuracy of data reported within a review.

Primary study characteristics were nearly always reported in aggregate at the review level (i.e. across all included studies) rather than at the analysis level, impeding their utility for this overview. Using data reported in review evidence tables, we looked across studies to produce analysis-specific aggregate information on populations and outcome measurement methods including biochemical validation of smoking outcomes, use of co-interventions, proportion of participants receiving specialized behavioural counselling, as well as any sources of indirectness which was used to inform assessment of the GRADE indirectness domain. As risk of bias information was also typically reported in aggregate across all studies rather than for each analysis, we developed risk of bias figures for each according to review authors’ assessments (Additional file 10). These figures were used to inform rating of the GRADE risk of bias domain.

Populations were coded as ‘general/mixed’ if all included studies recruited an unrestricted population of smokers or where populations across trials varied with no specific subpopulation forming a majority. If most trials were of a specific subpopulation of smokers (e.g. smokers motivated to quit), we coded accordingly. Where review authors made explicit statements regarding the applicability of the evidence to a specific subpopulation of smokers or where they restricted inclusion to a subpopulation, we coded the population in accordance with this information even if it was not made explicit in review evidence tables. Population details for each analysis are outlined in the GRADE tables (Additional file 11).

Quality assessment

Quality assessment of reviews was assessed using the 16-item AMSTAR 2 instrument [ 41 ] (Additional file 12). Overall rating of quality was determined according to the fulfilment of critical and non-critical items, as either high (no critical flaws and a maximum of one non-critical weakness), moderate (no critical flaws and more than one non-critical weakness), low (one critical flaw with/without non-critical weaknesses) or critically low (more than one critical flaw with/without non-critical weaknesses). Quality assessment was conducted independently by two reviewers for 73% of included reviews ( n = 22). For the remainder, assessments were made by one reviewer and verified by another due to resources and feasibility. For both procedures, disagreements were resolved by consensus or third-party arbitration.

Subgroup analysis

Subgroup analyses have been reported in Additional file 13 and variables of interest for data extraction are listed in Table 1 .

Evidence synthesis

We describe the results for each included analysis, along with reasons for downrating the certainty of evidence, narratively and within GRADE tables (Additional file 11). Given that we did not consult primary studies and relied solely on data as reported by review authors, indirect comparisons of treatments using simple (e.g. comparing 95% confidence intervals) or complex (e.g. network meta-analysis) methods were not performed, as stated in our protocol. As aforementioned, no attempt was made to assess concordance or discordance across reviews with similar scope.

For binary data meta-analyses, review authors typically reported relative effects (i.e. risk or odds ratios) which were used to calculate the absolute measure of intervention effects based on control event rates presented in the reviews. In the narrative summary of results, we report absolute effects as number per 1000 patients. Corresponding relative measures of effect are reported in GRADE tables (Additional file 11). Where there was insufficient information to calculate absolute effects, we relied on the reported relative effect and did not seek additional sources to inform baseline risks.

We followed authors’ main analyses or subgroups in lieu of main analyses. Further, where review authors performed GRADE assessments for subgroups in lieu of the main analysis, we followed suit. Credibility of subgroup assessments were guided by the GRADE working paper on inconsistency and criteria developed by Sun and colleagues (2010 and 2014) [ 42 , 43 , 44 ]. Credibility was only performed for subgroups that served as the main analysis (i.e. those for which we performed GRADE assessments). Results of subgroup credibility assessments are reported in GRADE Summary of Findings tables (Additional file 11).

Grading the certainty of the evidence

We operationalized GRADE methods to determine the certainty of evidence in light of how information was presented in the Cochrane reviews (e.g. risk of bias ratings) and incorporating guidance for overviews made available by Cochrane in 2019 [ 45 ]. Assessments were performed by one person and verified by a second person; any remaining discrepancies were discussed for consensus. GRADE guidance for footnotes was consulted and implemented [ 46 ]; a detailed approach was used to elaborate on assessments and for additional information such as whether co-interventions were provided. Maximum downrating for a given domain was two levels, considering partial demerit where warranted, except for publication bias which was downrated by a maximum of one level.

For risk of bias, we used authors’ ratings for individual domains at face value to inform our assessments and any additional information provided by authors in the text of their review. For example, if performance bias was not assessed but authors state that it was not possible due to the nature of the intervention, we interpreted this as high risk for that domain. Where not already incorporated by review authors, we included an assessment of whether biochemical validation was used for smoking outcomes. For domains not assessed by authors, excluding selective reporting bias, we interpreted these as an unclear risk. Typically, most biases outlined in the Cochrane risk of bias tool [ 47 ] were considered to inform the rating with the exception of selective reporting (considered only if issues were identified by authors) and the ‘other’ bias domain (typically only considered issues of baseline imbalance to reduce variability across reviews, except where noted).

Eligibility criteria were used to guide our rating of indirectness except for specialized behavioural interventions which were considered direct evidence because the mix of specialized and general interventions were considered by the guideline Working Group as either reflective of practice or referral to counselling; as this information was not provided in aggregate, we extracted it from reviews. The proportion of indirectness of a given analysis, along a continuum, was used to inform the rating.

To assess imprecision and to establish the target of certainty ratings, extracted outcome data (i.e. including relative and absolute effects) were provided to the guideline Working Group to make their partially contextualized judgements on effect sizes (i.e. trivial, small, moderate, or large) for a given intervention or comparator and considering other contextual factors as necessary. Information on the procedure of effect size ratings and final effect size judgements can be found in Additional file 14.

For syntheses without meta-analysis, additional guidance made available by GRADE was used [ 48 ]. Guidance typically used for inconsistency and publication bias were followed without special considerations [ 44 ].

If information was missing to facilitate the rating of a particular domain, we provided a rating range, which was also reflected in the overall certainty rating. If authors performed a GRADE assessment, we recorded that rating and any accompanying footnote information for downrating in the Summary of Findings (SoF) table (Additional file 11) for readers’ comparison.

Changes from protocol

Considering the substantial amount of evidence that was encountered during the conduct of the overview and potential for several hundred GRADE analyses, several protocol amendments were made in consultation with the guideline Working Group, for feasibility. First, we limited inclusion to Cochrane systematic reviews as evidence suggests that review findings from this source are more likely to have GRADE ratings than non-Cochrane reviews [ 49 ]. Given the substantial number of analyses reported within relevant Cochrane reviews, we further limited to comparisons and populations of greatest relevance to the Working Group and their recommendations on the suite of effective and suitable interventions available to physicians and patients. We further excluded comparative effectiveness data as well as data for specific subpopulations (e.g. pregnant smokers, smokers defined by demographic factors, smokers with co-morbidities other than those living with mental illness) as mentioned under the key questions 1b and 1c of the protocol [ 50 ].

Search results

We identified 4436 citations from database searches and an additional 43 from the grey literature following the previous search (i.e. until November 2018) and updated search (i.e. until September 2020). We screened the titles and abstracts of 4276 unique records. In total, 2244 records advanced to full-text screening including 1 newly published citation brought forth by the guideline Working Group. We excluded 1890 citations at full-text screening; a list of excluded citations with reason for exclusion is provided in Additional file 7.

Following protocol amendments, we excluded an additional 333 citations (Fig.  1 , bottom right). Of these, 290 were non-Cochrane systematic reviews. Some excluded reviews ( n = 23) were Cochrane systematic reviews that only reported comparative effectiveness data or examined subpopulations of smokers excluded by the guideline Working Group (e.g. smokers with COPD, pregnant/postpartum smokers). From the overview, we also excluded the candidate Cochrane electronic cigarette review as it was updated in the second part of this report [ 51 ]. A Cochrane overview of reviews and network meta-analysis, which would have contributed solely placebo-controlled analyses, was also excluded as it was superseded by updated versions of the included reviews of the pairwise placebo-controlled comparisons [ 52 ]. Reasons for exclusion of the remaining nine reviews are outlined in Fig.  1 . Twenty-two Cochrane systematic reviews were included (i.e. inclusive of four Cochrane systematic reviews identified through an updated search) in the overview.

PRISMA flow diagram

Characteristics of included reviews

Twenty-two systematic reviews reporting 131 relevant analyses involving pharmacotherapies, behavioural interventions, other therapies and combination interventions were included. Reviews were published between 2010 and 2020 and the number of included studies ranged from none to 136. Of the 13 reviews reporting the total number of participants across included studies, the range of participants was 1120 to approximately 4.7 million. The largest review of 4.7 million participants examined the effects of automated telephone communication systems for prevention and management of various conditions, only one of which was smoking cessation; therefore, only a subset of studies (i.e. 10 of 132) was relevant to this overview. Review characteristics are summarized in Additional file 15.

A majority (68%) of systematic reviews typically included general (i.e. unrestricted) smokers as well as specific smoking subpopulations, as per eligibility. Three reviews sought studies of smokers motivated or wishing to quit [ 53 , 54 , 55 ]. One review of harm reduction strategies included studies of smokers with no immediate intention to quit [ 56 ]. Another review intended to examine the effect of advice in smokers with severe mental illness but found no studies [ 57 ]. Remaining reviews included studies of smokers with current and past depression [ 58 ] and schizophrenia or schizoaffective disorder [ 59 ]. Four (18%) reviews excluded studies of adolescents and five (23%) excluded studies of pregnant smokers. None of the reviews restricted inclusion to studies conducted in a specific setting; they typically included studies from various settings including workplaces, schools, primary care, smoking cessation clinics, medical specialist settings, and in-patient settings including hospital and substance use treatment facilities.

Of the 22 reviews reporting outcome data, all but one review [ 60 ] reported on smoking abstinence. Three reviews (14%, n = 3) reported data on smoking reduction, nine (41%, n = 9) on adverse events [ 53 , 54 , 56 , 59 , 61 , 62 , 63 , 64 , 65 ], two (9%, n = 2) on weight gain [ 56 , 60 ] and three (14%, n = 3) on changes in emotional or mental state [ 59 , 66 , 67 ]. None of the reviews reported on quality of life or loss of social group.

AMSTAR 2 rating

Most reviews (i.e. 12 studies; (54%)) were rated as having critically low quality. The remainder were of low (i.e. 5 studies; 23%) or moderate (i.e. 5 studies; 23%) quality. Regarding the critical domains, deficiencies were primarily observed with item 11 with only 24% of reviews reported using appropriate methods for meta-analysis of randomized controlled trials (RCTs) and non-randomized studies. Two (10%) reviews had inadequate search strategies, seven (33%) failed to use adequate methods for assessing risk of bias for RCTs and/or non-randomized studies, eight (38%) did not consider risk of bias in the interpretation of results and eight (38%) did not investigate publication bias or at least the intention to do so (Additional file 16).

Risk of bias of primary studies

All reviews assessed the risk of bias of included studies using the Cochrane risk of bias tool [ 47 ]. However, there was variation in terms of which domains of the tool were assessed as well as how the domains were operationalized across reviews. For example, some but not all reviews assessed attrition and selective reporting biases. There was variation across reviews in the assessment of blinding with some combining performance and detection bias and others assessing them as separate domains. Some reviews added domains in relation to special considerations; for example, Farley [ 60 ] examined post-cessation weight gain in abstinent smokers and evaluated the definition of abstinence as part of the risk of bias assessment. Use of biochemical validation for smoking outcomes was inconsistently accounted for in risk of bias assessments across reviews.

As mentioned above, risk of bias figures was re-drawn for each analysis to inform GRADE assessments (Additional file 10). The risk of bias across studies for each analysis is specified in the GRADE table footnotes (Additional file 11).

Included analyses

Pharmacotherapies were examined in 71 analyses from seven reviews. Data were available for all pharmacotherapies of interest, namely, varenicline, cytisine, bupropion and nicotine replacement therapy (NRT), all of which were compared to placebo (Fig 2a). Twenty-two (31%) analyses covered smoking abstinence, 9 (13%) smoking reduction, 22 (31%) adverse events, 10 (14%) post-cessation weight gain and eight (11%) changes in emotional or mental state.

Thirty-one analyses from eleven reviews compared a behavioural intervention to no intervention, assessment only, usual care or a minimal intervention. Behavioural interventions included self-help materials, physician advice, individual counselling, group therapy, internet interventions, telephone-based interventions (e.g. telephone counselling, interactive voice response systems, short messaging service) and various stage-based interventions including expert systems, interactive computer programmes, advice and counselling (Additional file 17: Figure 2b). A majority (87%) of the analyses were specific to smoking abstinence; three analyses were of adverse events and one of change in emotional state.

Three reviews, contributing eight analyses, examined the effect of other therapies on smoking abstinence (Fig 2c). Interventions included hypnotherapy, acupuncture, continuous auricular stimulation, laser therapy, electrostimulation, St. John’s wort and S-adenosyl-L-methionine (SAMe). Inactive control conditions included placebo, sham and wait-list or no intervention. The effect of e-cigarettes on smoking abstinence, reduction, adverse events and weight gain in smokers not interested in quitting was examined in one review contributing seven analyses [ 56 ].

Combination interventions were from 6 reviews covered 14 analyses and included combination behavioural interventions (e.g. telephone counselling plus self-help materials, internet interventions plus behavioural support) or a combination of behavioural and pharmacotherapy interventions (e.g. behavioural support and phone calls plus NRT) (Additional file 17: Figure 2d). These interventions were compared to no intervention, usual care or a minimal intervention. Eight analyses (57%) were of smoking abstinence and six (43%) of smoking reduction. Information on included analyses for different smoking interventions can be found in Additional file 17.

• Pharmacotherapies

Varenicline versus placebo

Varenicline—abstinence/cessation in general/mixed population of smokers

Most trials reported biochemically validated continuous/sustained abstinence and provided behavioural co-interventions to both trial arms. Except where noted, varenicline was typically provided as 2 mg/day for 12 weeks.

At longest follow-up of 6 or more months, 138 more people per 1000 (95% CI: 118 to 159 more per 1000; 27 trials, 12,625 participants; I 2 = 60%) on varenicline compared with placebo stopped smoking (rating down once for inconsistency). The certainty of the evidence was rated as moderate. Effectiveness was also shown with the 6-month follow-up results and the certainty of the evidence was also rated as moderate (Additional file 11: Table 9; Figure 2a (Additional file 17)).

For extended (long-term) varenicline treatment (2 mg/day for 6–12 months) compared to placebo, 177 more per 1000 (95% CI: 121 to 249 more; 4 trials, 2170 participants; I 2 = 78%) stopped smoking (rating down twice for inconsistency and once for indirectness, the latter mainly from specialized medical settings). The certainty of evidence was rated as very low. Also, for the low (<2 mg/day) dose of varenicline compared to placebo at 12 months follow-up, 111 more per 1000 (95% CI: 57 to 182 more; n = 4, 1266 participants; I 2 = 68%) stopped smoking (rating down for risk of bias, and/or inconsistency, and imprecision). The certainty of evidence was rated as very low. At 12 months follow-up, variable dose varenicline compared to placebo resulted in 125 more people per 1000 abstinent (95% CI: 78 to 183 more; trials 6, 1789 participants) being (rating down for inconsistency and imprecision). The certainty of evidence was low (Additional file 11: Table 10, 11, and 12; Figure 2a (Additional file 17)).

Varenicline—abstinence/cessation in smokers reducing to quit

With an approach to reduce-to-quit, 179 more per 1000 participants (95% CI: 116 to 266 more; n = 1, 1510 participants) taking varenicline for 6 months were abstinent at 12 months compared to placebo (rating down once for imprecision). Participants in both study arms received behavioural co-interventions [ 62 ]. The certainty of the evidence was rated as moderate (Additional file 11: Table 13; Figure 2a (Additional file 17)).

Varenicline—abstinence/cessation in smokers not motivated to quit

Among smokers with no immediate intention to quit all tobacco use, 68 more participants per 1000 (95% CI: 10 fewer to 245 more; n = 1, 218 participants) taking varenicline (2 mg/day for 2–8 weeks) were point prevalence abstinent at 6-month follow-up as compared to placebo (rating down once for risk of bias and twice for imprecision; very low certainty). Participants in both groups received a behavioural co-intervention (Additional file 11: Table 32; Figure 2a (Additional file 17)) [ 56 ].

Varenicline—abstinence/cessation in smokers with schizophrenia, bipolar or other psychiatric disorder

At 6-month follow-up, 104 more people per 1000 (95% CI: 67 to 152 more; 4 trials, 2332 participants; I 2 = 0%) quit smoking on varenicline (2 mg/day). Behavioural co-intervention(s) were provided in all studies and all but one trial reported continuous/sustained abstinence [ 62 ]. The certainty of the evidence was rated as high (Additional file 11: Table 14; Figure 2a (Additional file 17)).

Among smokers with schizophrenia or schizoaffective disorder who were interested in quitting, 94 more participants per 1000 on varenicline (2 mg/day for about 12 weeks) (95% CI: 8 fewer to 866 more; single trial, 128 participants) were point prevalence abstinent at 6-month follow-up (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 55; Figure 2a (Additional file 17)) [ 59 ]. The certainty of the evidence was rated as very low.

Varenicline—abstinence/cessation in smokers with depression who were motivated/wishing to quit

More participants receiving varenicline (2 mg/day), 101 more per 1000 participants (95% CI: 29 to 209 more; single trial, 523 participants) were abstinent at 12 months follow-up (rating down once for imprecision). All participants received a behavioural co-intervention [ 62 ]. The certainty of the evidence was rated as moderate (Additional file 11: Table 15; Figure 2a (Additional file 17)).

Varenicline—abstinence/cessation in smokers who previously failed to quit on varenicline but are motivated/wishing to try quitting again

At 12 months follow-up in smokers who previously failed to quit on varenicline, 168 more per 1000 (95% CI: 65 to 382 more; single trial, 494 participants) remained abstinent (rating down once for risk of bias and imprecision). Participants in both arms received a behavioural co-intervention [ 62 ]. The certainty of the evidence was rated as low (Additional file 11: Table 16; Figure 2a (Additional file 17)).

Varenicline—reduction in number of cigarettes/day from baseline in smokers with schizophrenia or schizoaffective disorder

Among continued smokers with schizophrenia or schizoaffective disorder who were interested in quitting, review authors report no statistically significant difference between groups at 6 months regarding reduction in number of cigarettes per day from baseline. It is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that there may be little to no difference between groups (rating down once for risk of bias) (Additional file 11: Table 55; Figure 2a (Additional file 17)) [ 59 ]. We were unable to assess imprecision and provide an overall certainty rating due to missing information (i.e. number of events or sample size).

Varenicline—weight gain in smokers motivated/wishing to quit

Across analyses, weight gain was assessed in biochemically validated abstinent smokers. Most trials provided behavioural co-intervention(s) to both study groups.

Compared to placebo, varenicline (2 mg/day) likely results in little to no difference in post-cessation weight gain at end of treatment (MD −0.41 kg, 95% CI: 0.63 to 0.19 lower; 11 trials, 2008 participants; I 2 = 42%) (rating down once for risk of bias to also reflect concerns with inconsistency) in smokers motivated to quit. The certainty of the evidence was rated as moderate. These effects were sustained at 6 or 12 months follow-up (Additional file 11: Table 20; Figure 2a (Additional file 17)) [ 60 ]. The certainty of the evidence was rated as low (rating down once for risk of bias and imprecision) and moderate (rating down once for imprecision).

Low-dose varenicline (1 mg/day) may result in little to no difference in post-cessation weight gain by 0.12 kg at end of treatment (MD 0.12 kg, 95% CI: 0.68 lower to 0.43 higher; 3 trials, 254 participants; I 2 = 60%) (rating down once for inconsistency and imprecision). The certainty of the evidence was rated as low (Additional file 11: Table 21; Figure 2a (Additional file 17)) [ 60 ].

Varenicline—change in mental state in smokers with schizophrenia or schizoaffective disorder

Most trials examined varenicline 2 mg/day for about 8 to 12 weeks and behavioural co-interventions were provided to both groups in most trials. Change in mental state outcomes included positive (e.g. hallucinations, delusions), negative (e.g. anhedonia, avolition), depressive and general symptoms of schizophrenia. Various outcome measurement tools were used including, but not limited to, the Positive and Negative Syndrome Scale (PANSS), Hamilton Depression Rating Scale (HAM-D) and Brief Psychiatric Rating Scale. Participants were interested in quitting in a few of the trials. Review authors analysed studies according to the primary study objective.

In trials with a primary aim of smoking cessation ( n = 2), two reported on positive symptoms and one trial each on negative and depressive symptoms. Review authors report that there was no significant difference between groups at end of treatment for all symptoms, but it is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that there may be little to no difference between groups [ 59 ]. We were unable to assess imprecision and provide an overall certainty rating due to missing information (i.e. number of events or sample size).

Three trials had a primary aim other than smoking cessation, reduction or relapse. These trials examined the effect of varenicline on cognitive function ( n = 2) or alcohol dependence ( n = 1). A single trial included both smokers and non-smokers; whereas the other trials either only recruited smokers or reported symptom data for smokers only. One trial had a small sample size (ten participants) due to recruitment issues. For all symptoms (i.e. positive, negative, depressive and general symptoms of schizophrenia), review authors reported either no significant changes during varenicline treatment or no significant difference between groups. Regarding the latter, it is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that the confidence interval around the best estimate of effect includes the possibility of little to no difference between groups and more participants experiencing symptoms in one group over another (rating down once for risk of bias) (Additional file 11: Table 55; Figure 2a (Additional file 17)) [ 59 ]. We were unable to assess imprecision and provide an overall certainty rating due to unclear reporting of the sample size.

Varenicline—adverse events in general/mixed population of smokers

Most trials examined varenicline 2 mg/day for 12 weeks, provided both study groups with behavioural co-intervention and measured the outcome over a range of timepoints.

Nausea, insomnia, abnormal dreams, headache and serious adverse events occurred more frequently in those taking varenicline. Compared to placebo:

192 more per 1000 people on varenicline experienced nausea (95% CI: 169 to 216 more; n = 32, 14,963 participants; I 2 = 22%). The certainty of the evidence was rated as high.

41 more per 1000 experienced insomnia (95% CI: 29 to 54 more; n = 29, 14,447 participants; I 2 = 0%). The certainty of the evidence was rated as high.

64 more per 1000 had abnormal dreams (95% CI: 50 to 79 more; n = 26, 13,682 participants; I 2 = 62%). The certainty of the evidence was rated as moderate (rating down once for inconsistency).

17 more per 1000 experienced headaches (95% CI: 7 to 30 more; n = 25, 13,835 participants; 27%). The certainty of the evidence was rated as high.

7 more per 1000 had at least one serious adverse event (defined as ‘any untoward medical occurrence that resulted in death, was life-threatening, required inpatient hospitalization or prolongation of existing hospitalization, resulted in persistent or significant disability or incapacity, or resulted in a congenital anomaly or birth defect’) (95% CI: 1 to 13 more; n = 29, 15,370 participants; I 2 = 0%). The certainty of the evidence was rated as high.

Compared to placebo, 3 more people per 1000 (95% CI: ,1 fewer to 9 more; 21 trials, 8587 participants; I 2 = 0%) taking varenicline had a cardiac adverse event including death (rating down once for risk of bias and once for indirectness due to setting and inclusion of quitters) as one of the serious adverse events. The certainty of the evidence was rated as low. Six more participants per 1000 (95% CI: 0 fewer to 12 more; 26 trials, 15,000 participants; I 2 = 0%) taking varenicline experienced at least one serious adverse event during or immediately after treatment. The certainty of the evidence was rated as high (Additional file 11: Table 17; Figure 2a (Additional file 17)) [ 62 ].

One fewer participant per 1000 (95% CI: 6 fewer to 3 more; n = 36, 16,189 participants; I 2 = 0%) taking varenicline experienced depression compared to placebo. The certainty of the evidence was rated as high. Two fewer participants per 1000 (95% CI: 4 fewer to 0 fewer; n = 24, 11,193 participants; I 2 = 0%) on varenicline had suicidal ideation. The certainty of the evidence was rated as high (Additional file 11: Table 17; Figure 2a (Additional file 17)) [ 62 ].

Four studies reported discontinuation data narratively. Across three studies, treatment discontinuation ranged from 9.5 to 28% with varenicline and from 8 to 10% in the placebo group. In the fourth study, where study discontinuation was assessed during the 12-week varenicline open label phase, 32% exited the study because of discontinuation, non-adherence to protocol and relapse. We were unable to assess imprecision and provide an overall certainty rating due to missing information (i.e. number of events or sample size) (Additional file 11: Table 17; Figure 2a (Additional file 17)).

Varenicline—adverse events in smokers not motivated to quit

Review authors indicate that there was no difference between groups regarding treatment discontinuation due to adverse events, but it is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that the confidence interval around the best estimate of effect includes the possibility of little to no difference between groups and more participants experiencing the outcome in one group over another (Additional file 11: Table 32; Figure 2a (Additional file 17)) (rating down once for risk of bias and once or twice for imprecision). We were unable to assess imprecision definitively because the sample size was unclear. Participants in both groups received a behavioural co-intervention [ 56 ].

Varenicline—adverse events in smokers with schizophrenia or schizoaffective disorder

Most trials examined varenicline 2 mg/day for about 8 to 12 weeks and behavioural co-interventions were provided to both groups in most trials. Participants were interested in quitting in a few of the trials. Review authors analysed studies according to the primary study objective.

Two trials had a primary aim of smoking cessation. One trial reported no suicidal ideation. This study reported exacerbation of side effects in the varenicline arm, namely, constipation, insomnia and nausea. In the second trial, two participants with a history of suicide attempts assigned to varenicline were hospitalized; one of the participants overdosed and had a seizure resulting in hospitalization. In total, the trial reported 13 serious adverse events occurring in 9 participants assigned to varenicline and 1 participant assigned to placebo (2 varenicline participants experienced 3 serious adverse events related to treatment). One death from accidental drowning occurred in the varenicline arm during the long-term follow-up period (off-treatment); the event was not related to treatment according to authors. No treatment-related adverse events occurred in placebo arm. This second trial also reported no difference between groups regarding other adverse events including neuropsychiatric serious adverse events and study discontinuation. The most common adverse events occurring in the varenicline arm were nausea (23.8%), headache (10.7%) and vomiting (10.7%) (Additional file 11: Table 55; Figure 2a (Additional file 17)) (rating down once for risk of bias and once or twice for imprecision) [ 59 ]. We were unable to assess imprecision definitively because the sample size was unclear.

Three trials had a primary aim other than smoking cessation, reduction or relapse. These trials examined the effect of varenicline on cognitive function ( n = 2) or alcohol dependence ( n = 1). Adverse events data from two trials included both smokers and non-smokers; the remaining trial recruited smokers with alcohol dependence and had a small sample size (ten participants) due to recruitment issues). In one trial recruiting participants with both smoking and alcohol dependence, one participant assigned to varenicline withdrew from the trial due to passive suicidal ideation (7 days after starting varenicline), vomiting and irritability. The other two trials reported that among smokers and non-smokers, no participants had suicidal ideation and no increase in suicidal ideation occurred in those assigned varenicline, respectively. One trial reported a trend toward reduced psychosis in the varenicline arm compared to placebo; both smokers and non-smokers were included in this analysis, but study authors report no difference in treatment effect related to smoking status. In the second trial of smokers and non-smokers, two participants in each study arm withdrew due to exacerbation of psychotic symptoms. One trial reported that among smokers and non-smokers, there was no difference between varenicline and placebo groups regarding common side effects of varenicline. However, the two other trials reported higher rates of common side effects in the varenicline arm (e.g. nausea, headache, vomiting, abdominal pain). In one of these studies, one patient withdrew due to nausea and vomiting. Given what was reported, the one trial in smokers with alcohol dependence raised concerns for review authors regarding the safety and tolerability of varenicline in schizophrenic patients (rating down once for risk of bias, once for inconsistency ) (Additional file 11: Table 55; Figure 2a (Additional file 17)) [ 59 ]. We were unable to assess imprecision or provide an overall certainty rating because the sample size was unclear.

Review authors note that across all varenicline trials in the review, 2 of 144 participants on varenicline experienced suicidal ideation or behaviour. This includes one participant who overdosed in a smoking cessation trial as well as one participant with passive suicidal ideation in a trial examining varenicline for purposes other than smoking cessation [ 59 ].

Cytisine versus placebo

Cytisine—abstinence/cessation in general/mixed population of smokers

At 2 years of follow-up, 79 more participants per 1000 taking cytisine (1.5 mg tablets for 25 days with variability in daily dose) were abstinent compared to placebo (95% CI: 31 to 141 more; n = 1, 1214 participants) (rating down twice for risk of bias and once for imprecision). The certainty of the evidence was rated as very low. Abstinence was not biochemically validated and review authors state that behavioural support was kept to a minimum (Additional file 11: Table 8; Figure 2a (Additional file 17)) [ 62 ].

Cytisine—abstinence/cessation in smokers motivated/wishing to quit

Two trials reported biochemically validated continuous/sustained abstinence in participants receiving cytisine (1.5 mg tablets for 25 days with variability in daily dose) compared to placebo. While review authors state that behavioural support was kept to a minimum, counselling or support was provided to both groups in both trials. Compared to placebo, 64 more participants per 1000 (95% CI: 22 to 147 more; n = 2, 937 participants; I 2 = 0%) on cytisine were abstinent at 6 or more months follow-up (rating down once for imprecision). The certainty of the evidence was rated as moderate (Additional file 11: Table 7; Figure 2a (Additional file 17)) [ 62 ].

Cytisine—adverse events in general/mixed population of smokers

Adverse events were largely similar between cytisine and placebo groups across studies ( n = 3). At 4 weeks, there were similar rates of mild adverse events (nausea, restlessness, insomnia, irritability) between groups in abstinent smokers (23.4% versus 20%); longer term information was not reported. A total of 10 events (e.g. dyspepsia, nausea and headache) from 4 people in each group were reported in a second study. The third study reported higher rates of gastrointestinal disorders with cytisine (13.8% versus 8.1%, p = 0.02) (Additional file 11: Table 8; Figure 2a (Additional file 17)) [ 62 ]. We were unable to assess imprecision or provide an overall certainty rating because the sample size was not reported.

Nicotine replacement therapy (NRT) versus placebo

NRT—abstinence/cessation in relapsed smokers motivated to quit

Nicotine patch (decreasing dose over 12 weeks: 21 mg/24 h to 7 mg/24 h) or placebo was provided to participants along with minimal additional support in one trial. Included participants had relapsed after transdermal patch and behavioural counselling in an earlier phase of the trial but were motivated to make a second attempt. Absolute effects could not be calculated for this study. Compared to placebo, NRT patch increased continuous abstinence by 25% but the confidence interval included possibility of a potential larger increase or large decrease in cessation (RR 1.25, 95% CI: 0.34 to 4.60; n = 1, 629 participants) (rating down 0.5 for risk of bias and twice for imprecision). The certainty of the evidence was rated as very low. Review authors indicate that there was a greater relative effect in 28-day point prevalence abstinence with NRT (RR 2.49, 95% CI: 1.11 to 5.57) although quit rates were low irrespective of the definition of abstinence used (Additional file 11: Table 22; Figure 2a (Additional file 17)) [ 54 ].

NRT—abstinence/cessation in smokers not motivated/wishing to quit

Lindson-Hawley [ 56 ] included studies of smokers who have no immediate intention to quit all tobacco use. Type of NRT varied across trials; studies examined inhaler ( n = 2), gum ( n = 4) or offered participants a choice of NRT type ( n = 2). Dosing and treatment duration varied across studies within each NRT type (Additional file 11: Table 30). Most studies provided behavioural co-intervention to each group and biochemically validated smoking abstinence. For smoking cessation, authors preferred point prevalence over sustained/continuous abstinence as participants were not expected to quit at start of intervention.

Compared to placebo, 44 more participants per 1000 taking NRT were abstinent at 12 to 24 months follow-up (95% CI: 22 to 73 more; n = 8, 3081 participants; I 2 = 30%) (rating down once for risk of bias). The certainty of the evidence was rated as moderate. Subgroup differences by NRT type was not detected (test for subgroup differences: p = 0.42, I 2 = 0.0%) (Additional file 13) [ 56 ].

NRT—reduction in cigarettes per day of >50% of baseline or cessation in smokers not motivated/wishing to quit

Again in the review of Lindson-Hawley [ 56 ], studies of smokers who have no immediate intention to quit all tobacco use were included. NRT type, dose and treatment duration varied across studies (Additional file 11: Table 30). For smoking reduction, review authors preferred sustained/continuous rates over point prevalence.

At longest follow-up (12+ months), 60 more participants per 1000 (95% CI: 35 to 91 more; n = 8, 3081 participants; I 2 = 45%) (rating down once for risk of bias) on NRT reduced the number of cigarettes smoked per day by more than 50% of baseline or quit entirely as compared to placebo. The certainty of the evidence was rated as moderate. Subgroup analysis indicated that compared to placebo, more participants reduced smoking with gum and inhaler than with choice of NRT (test for subgroup differences: p = 0.01, I 2 = 79%) (Additional file 13) [ 56 ].

NRT—abstinence/cessation in smokers with current depression

A single study reporting post hoc subgroup data for smokers with current depression was identified by van der Meer [ 58 ]. Participants received NRT gum (2 or 4 mg with recommendation of 9 to 15 pieces per day for 2 months followed by weaning) or placebo plus a behavioural co-intervention provided to all participants. Abstinence was biochemically verified and measured continuously. Compared to placebo, 94 more participants per 1000 (95% CI: 4 fewer to 369 more; n = 1, 196 participants) receiving NRT gum were abstinent at 12 months follow-up (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 60; Figure 2a (Additional file 17)) [ 58 ]. The certainty of the evidence was rated as very low.

NRT—abstinence/cessation in smokers with past depression

Three studies recruited general smokers but reported pre-stated or post hoc subgroup data for smokers with past depression. One study each examined NRT gum (2 mg for 8 weeks and tapering to week 11) and patch (21, 14 and 7 mg titrated down during 8 weeks after quit date). The remaining study examined patch (21, 14 and 7 mg titrated down during 8 weeks after quit date), lozenge (2 or 4 mg according to dependence for 12 weeks) and patch plus lozenge with each of the treatment arms entered separately in the meta-analysis. All studies provided behavioural co-intervention to both arms; one four arm trial also provided bupropion or placebo tablets. Abstinence was biochemically validated in all studies, but measures varied with most reporting point prevalence.

Compared to placebo, 42 more participants per 1000 (95% CI: 38 fewer to 150 more; n = 3, 432 participants; I 2 = 0%) on NRT were abstinent at longest follow-up (6+ months) (rating down twice for imprecision) (Additional file 11: Table 61; Figure 2a (Additional file 17)) [ 58 ]. The certainty of the evidence was rated as low.

NRT—abstinence/cessation in smokers with schizophrenia or schizoaffective disorder

No studies were found [ 59 ].

NRT—reduction in smokers with schizophrenia or schizoaffective disorder

NRT—weight gain in smokers motivated/wishing to quit

Across analyses, weight gain was assessed in biochemically validated abstinent smokers. Type of NRT varied across studies and included patch, gum, inhaler, sublingual tablet and intranasal spray. Within each type, there was variation across trials with respect to dose and treatment duration. Control groups received placebo in all but two trials; one provided group therapy while the control condition was described as ‘no gum’ in the second. Most trials provided behavioural co-intervention to both study groups.

Compared to placebo, participants on NRT had 0.69 kg fewer kg gained post-cessation (95% CI: 0.88 to 0.51 lower; n = 19, 2600 participants; I 2 = 82%) (rating down once for risk of bias and twice for inconsistency) at the end of treatment. The certainty of the evidence was rated as very low. There was little to no change in weight gain at 6 months (−0.37 kg; 95% CI: 0.88 lower to 0.14 higher; n = 9; 771 participants, I 2 = 0%) and at 12 months of follow-up (−0.42 kg; CI: 0.92 lower to 0.08 higher; n = 15, 1334 participants, I 2 = 0%) (Additional file 11: Table 19; Figure 2a (Additional file 17)). The certainty of the evidence was rated as moderate for both (rating down once for risk of bias). Subgroup differences by NRT type were not detected for all timepoints of follow-up (test for subgroup differences: end of treatment p = 0.38, I 2 = 5%; 6 months p = 0.89, I 2 = 0%; 12 months p = 0.34, I 2 = 12%) (Additional file 13) [ 60 ].

NRT—change in mental state in smokers with schizophrenia or schizoaffective disorder

Two trials reported a change in mental state following NRT use, with the treatment duration of 7 h (8 mg/day) in one RCT and 32 h (22mg/day) in the second trial. One trial reported no difference in psychiatric symptoms between NRT patch and placebo phases. In the second trial, no participant experienced a change in subjective experience or mental status (rating down once for risk of bias and once or twice for imprecision) (Additional file 11: Table 56) [ 59 ]. We were unable to assess imprecision or provide an overall certainty rating lack of clarity regarding because the sample size was unclear.

NRT—adverse events in smokers with schizophrenia or schizoaffective disorder

One cross-over trial reported that 60% of participants experienced an increase in abnormal involuntary movement when using NRT patch (22 mg/day for 32 h). Review authors report the increase as statistically significant when participants were smoking and using NRT patch; it is unclear whether this is based on p -values or confidence intervals (rating down twice for risk of bias and once or twice for imprecision) (Additional file 11: Table 56) [ 59 ]. The certainty of the evidence was rated as very low.

NRT—adverse events in smokers motivated/wishing to quit

The type and dosing of NRT varied across studies or was not reported. Some studies provided either high- or low-intensity behavioural support to both study arms.

Compared to placebo, 12 more participants per 1000 (95% CI: 5 to 21 more; n = 15, 11,074 participants; I 2 = 10%) taking NRT experienced palpitations/chest pains (rating down once for risk of bias). The certainty of the evidence was rated as moderate.

By type of formulation, the most common adverse events were as follows:

Nicotine gum: hiccups gastrointestinal disturbances, jaw pain and orodental problems

Nicotine patch: mild skin sensitivity and local skin irritation in up to 54% of patch users

Nicotine inhalator: throat irritation, coughing and oral burning

Nicotine nasal spray: irritation and runny nose

Nicotine oral spray: hiccoughs and throat irritation

Nicotine sublingual tablets: hiccoughs, burning and smarting sensation in the mouth, sore throat, coughing, dry lips and mouth ulcers

Review authors reported that reactions to NRT were usually not severe enough to prompt discontinuation of treatment. Trials could not be pooled due to heterogeneity with respect to the nature, timing and duration of symptoms.

Authors considered attrition as an adverse event in the review. They reported that attrition rates in NRT groups were generally similar to or lower than in control groups among included studies (Additional file 11: Table 23) [ 54 ].

Bupropion versus placebo

Bupropion—abstinence/cessation in smokers not motivated/wishing to quit

There was overlap across two reviews which included the same trial of smokers who were interested in reducing smoking but not quitting and who had at least two failed quit attempts, one of which was with NRT (Howes 2020 [ 67 ], Lindson-Hawley 2016 [ 56 ]). In the trial, those who became willing to quit entered the cessation phase of the trial, which included weekly counselling for seven weeks and then 19 weeks of follow-up. Both study arms received behavioural co-interventions and abstinence was biochemically confirmed.

Compared to placebo, 14 more participants per 1000 (95% CI: 18 fewer to 75 more; n = 1, 594 participants) on bupropion (300 mg/day for 26 weeks) were abstinent at 6 months follow-up, although there is uncertainty. Reviews differed in their rating of the attrition bias domain for this evidence; one review rated the trial as being at high risk while the other rated it at low risk of bias. As such, our GRADE assessments differed across reviews for this same evidence; we downrated once due to risk of bias and twice for imprecision for one review and twice for risk of bias and twice for imprecision for the other (Additional file 11: Tables 25 and 31) [ 56 , 67 ]. The certainty of the evidence was rated as very low for both reviews.

Bupropion—abstinence/cessation in smokers with current depression

Five studies reported pre-stated or post hoc subgroup data for smokers with current depression. Abstinence was biochemically validated in all trials with most reporting continuous/sustained rates. Dosing of bupropion treatment was 300 mg/day for 7 weeks to 6 months across trials. All studies provided both arms with behavioural co-intervention and one also provided NRT patch.

At longest follow-up (6 to 12 months), 41 more participants per 1000 (95% CI: 19 fewer to 142 more; n = 5, 410 participants, I 2 = 29%) were abstinent compared to placebo. We rated down once for risk of bias to also reflect concerns with indirectness and twice for imprecision (Additional file 11: Table 58; Figure 2a (Additional file 17)). The certainty of the evidence was rated as very low.

Review authors performed subgroup analysis by sole use of bupropion or bupropion used in adjunct to NRT; subgroup differences were not detected (test for subgroup differences: p = 0.66, I 2 = 0%) (Additional file 13) [ 58 ].

Bupropion—abstinence/cessation in smokers with past depression

Four studies recruited general smokers but reported post hoc subgroup data for smokers with past depression. Bupropion treatment was 300 mg/day for 7 to 12 weeks across trials. All studies provided behavioural co-intervention to both arms; one four arm trial also provided NRT or placebo patch. The outcome was biochemically validated in all trials and most reported point prevalence abstinence.

Compared to placebo, 128 more participants per 1000 (95% CI: 38 to 268 more; n = 4, 404 participants; I 2 = 44%) on bupropion stopped smoking at longest follow-up of 6 to 12 months (rating down once for risk of bias to also reflect concerns with inconsistency and once for imprecision) (Additional file 11: Table 59; Figure 2a (Additional file 17)). The certainty of the evidence was rated as low. Review authors signal the need for caution in interpreting these results as data for participants with past depression were derived from post-hoc subgroup analyses in all studies. Review authors performed subgroup analysis by sole use of bupropion or bupropion used in adjunct to NRT; they report no strong evidence of a difference between subgroups (test for subgroup differences: p = 0.05, I 2 = 73.3%) (Additional file 13) [ 58 ].

Bupropion—abstinence/cessation in smokers with schizophrenia or schizoaffective disorder

Most trials examined the effect of offering 300 mg/day for about 10 or 12 weeks; 1 trial offered 150 mg/day for 12 weeks. Behavioural co-interventions were provided to both study groups in all trials; co-interventions included specialized behavioural counselling which was received by about 70% of participants in each study arm, across trials. Participants in two trials also received NRT patch with or without NRT gum. Abstinence was biochemically validated in all trials with most reporting continuous/sustained rates. Participants in all trials were interested in quitting.

At 6-month follow-up, 66 more participants per 1000 (95% CI: 1 to 244 more; n = 5, 214 participants; I 2 = 0%) on bupropion were abstinent (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 54; Figure 2a (Additional file 17)). The certainty of the evidence was rated as very low. Review authors performed subgroup analysis by sole use of bupropion or bupropion used in adjunct to NRT; subgroup differences were not detected (test for subgroup differences: p = 0.67, I 2 = 0%) (Additional file 13). Review authors also report data at longer follow-up. In one trial, three additional participants were abstinent at 2 years; of the four total participants that quit, three received bupropion during the trial or during the follow-up period. One other study reported that of the five bupropion participants that were abstinent at 6 months, two relapsed at 12-month follow-up. Including this 12-month follow-up data would reduce the effect estimate and the confidence interval would suggest little to no difference between groups or fewer events with bupropion [ 59 ].

Bupropion—reduction in number of cigarettes per day in smokers not motivated/wishing to quit

Participants were interested in reducing smoking but not quitting and had at least two failed quit attempts, one of which was with NRT ( n = 1; 594 participants). At 12-month follow-up, 1 more participant per 1000 (95% CI: 36 fewer to 63 more; n = 1, 594 participants) on bupropion (300 mg/day for 26 weeks) quit or reduced the number of cigarettes smoked per day by more than 50% (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 31; Figure 2a (Additional file 17)) [ 56 ]. The certainty of the evidence was rated as very low.

Based on data from the same trial, Howes [ 67 ] reported no significant difference between groups in reduction of cigarettes per day at 12-month follow-up. It is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that the confidence interval around the best estimate of effect includes the possibility of little to no difference between groups and greater reduction in one group over another (rating down twice for risk of bias) (Additional file 11: Table 25) [ 67 ]. We were unable to assess imprecision and provide an overall certainty rating due to missing information (i.e. number of events or sample size).

Bupropion—reduction in cotinine in smokers not motivated/wishing to quit

Two reviews reported data from the same single trial of the effects of bupropion compared with placebo on concentrations of biomarkers, like nicotine and its metabolites (i.e. cotinine), tobacco-specific nitrosamines, carbon monoxide (CO) and tobacco alkaloids (i.e. anabasine) [ 68 , 69 ] assessed as their exposure in fluids , i.e. plasma, saliva and urine to determine approaches bound to achieve smoking cessation. Among participants who were interested in reducing but not quitting smoking and with at least two failed quit attempts ( n = 1, 327 participants), 26 fewer participants per 1000 (95% CI: 40 fewer to 27 more; n = 1, 327 participants) on bupropion (300 mg/day for 26 weeks) had reduction in cotinine levels greater than 50%. Reviews differed in their rating of attrition bias for the same evidence resulting in different GRADE ratings across reviews; we downrated once due to risk of bias and twice for imprecision for one review and twice due to risk of bias and twice for imprecision for the other (Additional file 11: Tables 25 and 31) [ 56 , 67 ]. The certainty of the evidence was rated as very low for both reviews.

Lindson-Hawley [ 56 ] also report no statistically significant difference between groups in mean urinary cotinine decrease from baseline at 12-month follow-up (mean decrease: bupropion 82 ng/mL versus placebo 28 ng/mL, p = 0.25) (rating down once for risk of bias and once or twice for imprecision). We were unable to rate the certainty of the evidence due to sample size analysed not being reported, and so the imprecision domain could not be assessed.

Bupropion—reduction in number of cigarettes per day in smokers with schizophrenia or schizoaffective disorder

Participants in all trials were interested in quitting and specialized behavioural counselling was provided to both groups. In one trial, participants in both groups also received NRT patch and NRT gum.

At 6-month follow-up, those on bupropion (300 mg/day for about 12 weeks) reduced their smoking by 0.4 cigarettes per day compared to those on placebo*(95% CI: 5.72 lower to 6.53 higher; n = 2, 104 participants; I 2 = 0%) (rating down once for risk of bias and once for imprecision) (Additional file 11: Table 54; Figure 2a (Additional file 17)) [ 59 ]. The certainty of the evidence was rated as low.

Bupropion—expired carbon monoxide levels in smokers with schizophrenia or schizoaffective disorder

Participants in all trials were interested in quitting and specialized behavioural counselling was provided to both groups. In one trial, participants in both groups also received NRT patch with or without NRT gum.

Compared to placebo, expired CO mean was 5.55 ppm lower with bupropion (150 or 300 mg/day for about 12 weeks) at 6 months follow-up (95% CI: 17.89 lower to 6.78 higher; n = 3, 123 participants, I 2 = 83%) (rating down once for risk of bias, twice for inconsistency and once for imprecision) (Additional file 11: Table 54; Figure 2a (Additional file 17)) [ 59 ]. The certainty of the evidence was rated as very low.

Bupropion—weight gain in smokers motivated/wishing to quit

Across analyses, weight gain was assessed in biochemically validated abstinent smokers. All trials examined bupropion 300 mg/day for 7 to 12 weeks and provided behavioural co-intervention to both study arms. Control groups received placebo in all but one trial in which participants received advice.

Compared to placebo, bupropion reduced post-cessation weight gain by 1.12 kg at end of treatment (95% CI: 1.47 to 0.77 lower; n = 7, 869 participants; I 2 = 0%) (rating down once for risk of bias). The certainty of the evidence was rated as moderate. There was a little to no change in weight gain at 6 months of follow-up (0.87 kg lower; 95% CI: 2.21 lower to 0.47 higher, n = 4, 218 participants, I 2 = 0%) and at 12 months of follow-up (0.38 kg lower; 95% CI: 2 lower to 1.24 higher, n = 4, 252 participants, I 2 = 0%) (Additional file 11: Table 18; Figure 2a (Additional file 17)) [ 60 ]. The certainty of evidence was rated as low at both the follow-ups (rating down once for risk of bias and once for imprecision at both the follow-ups).

Bupropion—change in emotional state (depressive symptoms) in general/mixed population of smokers

A single trial included by Howes [ 67 ] reported on depressive symptoms. During treatment, most participants in both arms experienced reduction in depressive symptoms and this was sustained at follow-up. A between-group difference was observed for highly dependent smokers with greater reduction in the bupropion arm (300 mg/day for 10 weeks), but the reduction was not sustained at follow-up (Additional file 11: Table 26; Figure 2a (Additional file 17)). Behavioural co-interventions were provided to both study groups. We were unable to rate the certainty of the evidence due to sample size analysed not being reported for imprecision domain.

Bupropion—change in mental state in smokers with schizophrenia or schizoaffective disorder

Change in mental state outcomes included positive (e.g. hallucinations, delusions), negative (e.g. anhedonia, avolition), depressive and psychiatric symptoms. Various outcome measurement tools were used including, but not limited to, the PANSS, HAM-D and Beck Depression Inventory (BDI) [ 70 , 71 , 72 ]. Participants were interested in quitting in most trials. Review authors analysed studies according to the primary study objective.

Among studies with a primary aim of cessation, bupropion dosing was 300 mg/day for about 10 to 12 weeks and specialized behavioural counselling was provided to both groups in all trials. In one trial, participants in both arms also received NRT patch and NRT gum as a co-intervention. The positive symptoms score was 0.24 lower in those with bupropion at the end of treatment (95% CI: 0.66 lower to 0.19 higher; n = 2, 85 participants, I 2 = 0%) (rating down once for risk of bias and once for imprecision) compared to placebo. The negative symptoms score was 0.12 lower in those with bupropion at the end of treatment (95% CI: 0.46 lower to 0.22 higher; n = 3, 136 participants, I 2 = 0%) (rating down once for risk of bias and twice for imprecision) compared to placebo. Lastly, the depressive symptoms score was 0.16 lower in those with bupropion at the end of treatment (95% CI: 0.5 lower to 0.18 higher; n = 3, 136 participants, I 2 = 0%) (Additional file 11: Table 54; Figure 2a (Additional file 17)) compared to placebo. The certainty of the evidence was rated as low or very low. Review authors indicate that three additional trials provided corroborating evidence of no significant difference between groups in symptoms, but data were incompletely reported. One trial not included in the meta-analysis reported improvement in negative symptoms and greater stability of psychotic and depressive symptoms in the bupropion arm during quit attempt. Three additional studies reported no effect of smoking abstinence on symptoms [ 59 ].

Three studies had a primary aim of smoking reduction. Intervention participants received bupropion 300 mg/day for about 22 days to 14 weeks across two studies; dosing and treatment duration was unclear for one study. One trial each provided specialized behavioural counselling and non-contingent reinforcement as co-interventions to both study groups. As reported by review authors, one study reported no worsening of positive and negative symptoms in the bupropion arm, a second study reported no significant difference between groups regarding change in positive and negative symptoms, and the third study reported no increase in psychiatric symptoms in the bupropion arm (rating down twice for risk of bias and once or twice for imprecision) (Additional file 11: Table 54; Figure 2a (Additional file 17)) [ 59 ]. The certainty of the evidence was rated as very low.

Bupropion—adverse events in smokers motivated/wishing to quit

Among participants who were interested in reducing but not quitting smoking and with at least two failed quit attempts ( n = 1, 594 participants), 17 more participants per 1000 (95% CI: 3 fewer to 91 more; n = 1, 594 participants) on bupropion (300 mg/day for 26 weeks) experienced a serious adverse event (rating down once for risk of bias and twice for imprecision). The certainty of the evidence was rated as very low. Review authors state that one of the events was potentially attributed to bupropion treatment (Additional file 11: Table 31; Figure 2a (Additional file 17)) [ 56 ].

Bupropion—adverse events in smokers with schizophrenia or schizoaffective disorder

In nearly all studies, participants were interested in quitting or reducing smoking and received either placebo or bupropion 300 mg/day for 22 days to 14 weeks, across studies. Behavioural co-interventions were provided to both study groups in most studies; in a few trials, all participants also received pharmacotherapy (NRT patch with or without NRT gum). Review authors analysed studies according to the primary study objective.

Seven studies with a primary aim of smoking cessation reported adverse events. In one study, a participant who took bupropion had a seizure; authors reported that this was likely unrelated to bupropion treatment. No seizures were reported in remaining trials.

One study reported that one participant receiving bupropion (3%) and two receiving placebo (7%) experienced a psychotic breakdown; authors did not consider this related to study treatment. Another study reported recurrence of psychotic symptoms in two participants, but results were not reported by study arm. One study reported no serious adverse events.

One trial reported higher rates of dry mouth in the bupropion arm compared to placebo and another study reported that significantly more bupropion participants (also receiving NRT) experienced poor concentration, jitteriness, light-headedness, muscle stiffness and frequent nocturnal awakening. A third study reported that, compared to placebo, the bupropion arm had higher rates of insomnia, dry mouth and sweatiness. A fourth study reported an allergic reaction in one participant receiving bupropion. A fifth study reported no significant differences in major adverse events measured by the Side Effect Checklist (e.g. restlessness, insomnia, dry mouth, sedation); however, five participants on bupropion withdrew from the trial due to side effects, including rash ( n = 1), restlessness and increased anxiety ( n = 2), worsening of psychosis ( n = 1) and the aforementioned seizure. The sixth study reported two participant withdrawals in the bupropion arm (also receiving NRT) due to insomnia and dizziness (rating down once for risk of bias ) (Additional file 11: Table 54; Figure 2a (Additional file 17)) [ 59 ]. We were unable to rate the certainty of the evidence due to sample size analysed not being reported for imprecision domain.

Among studies with a primary aim of smoking reduction ( n = 3), two reported no adverse events related to bupropion. The remaining study reported no significant difference between groups in adverse events and no seizures or suicidal behaviour in the bupropion arm (rating down once for risk of bias, once for indirectness and once or twice for imprecision) (Additional file 11: Table 54) [ 59 ]. The certainty of the evidence was rated as very low.

Behavioural interventions

Stage-based expert systems or tailored self-help materials versus assessment only

Abstinence/cessation in general/mixed population of smokers

Stage-based expert systems are personalized reports or letters, often produced electronically according to questionnaires or interviews, that are matched to a participant’s stage of change [ 73 ]. In one trial, a behavioural co-intervention was provided only to those receiving the intervention. In another, 25% of participants in the intervention arm and 21% in the control arm used NRT by 2-year follow-up. Most trials reported either prolonged or point prevalence abstinence; none biochemically validated smoking abstinence.

At longest follow-up (6+ months), 22 more people per 1000 (95% CI: 12 to 33 more; n = 10, 13,597 participants; I 2 = 46%) given stage-based expert systems or tailored self-help materials compared with assessment only stopped smoking (rating down twice for risk of bias and once for inconsistency) (Additional file 11: Table 2; Figure 2b (Additional file 17)) [ 73 ]. The certainty of the evidence was rated as very low.

One trial examined the effect of a computer-generated tailored letter addressing outcomes of smoking and quitting, self-efficacy, active skills to quit, boosting confidence and coping skills; control participants received a letter confirming no self-help intervention would be sent. Review authors state that there was a significant difference between groups at 14 months with more continuous/sustained abstainers in the intervention arm (OR 3.74, 95% CI: NR) (rating down twice for risk of bias) (Additional file 11: Table 2; Figure 2b (Additional file 17)) [ 73 ]. The certainty of the evidence was rated as very low.

Stage-based interactive computer programmes compared to usual care

Two cluster randomized trials, one in students 13 to 14 years of age and another in pregnant individuals, examined the effect of stage-based interactive computer programmes. One trial each reported point prevalence abstinence and continuous/sustained abstinence; neither used biochemical confirmation.

At longest follow-up (12+ months), 10 more people per 1000 (95% CI: 13 fewer to 41 more; n = 2, 1702 participants, I 2 = 0%) given stage-based interactive computer programmes stopped smoking in comparison to usual care (rating down twice for risk of bias, once for indirectness and twice for imprecision) (Additional file 11: Table 3; Figure 2b (Additional file 17)) [ 73 ]. The certainty of the evidence was rated as very low.

Stage-based telephone counselling compared to usual care

One trial of stage-based telephone counselling based on specialized approaches (5As, motivational interviewing, 5Rs) reported that at 12 months follow-up, 16 more people per 1000 (95% CI: 27 fewer to 114 more; n = 1, 318 participants) given stage-based telephone counselling compared to usual care were point prevalent abstinent (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 4; Figure 2b (Additional file 17)). The certainty of the evidence was rated as very low. The intervention group received additional co-interventions depending on readiness to quit [ 73 ].

Stage-based individual counselling and/or advice compared to usual care

One trial provided both stage-based counselling and advice; other trials offered either counselling or advice tailored to stage of change. About half of the studies provided a behavioural co-intervention to those in the active arm with a few also recommending pharmacotherapy. Usual care varied across studies with some trials providing active smoking cessation interventions in conjunction with usual care. Trials varied with respect to how abstinence was measured. Biochemical confirmation of abstinence was conducted in less than half of trials.

Compared to usual care, 21 more people per 1000 (95% CI: 1 fewer to 46 more; n = 7, 3293 participants, I 2 = 36%) receiving stage-based individual counselling and/or advice were abstinent at longest follow-up (6+ months) (rating down once for risk of bias) (Additional file 11: Table 5; Figure 2b (Additional file 17)) [ 73 ]. The certainty of the evidence was rated as moderate.

Stage-based individual counselling or advice compared to assessment only

Compared to receiving assessment only (i.e. no intervention), 12 more people per 1000 (95% CI: 2 fewer to 31 more; n = 3, 3056 participants, I 2 = 80%) receiving stage-based individual counselling or advice were abstinent at 6 or more months (rating down once for risk of bias and twice for inconsistency) (Additional file 11: Table 6; Figure 2b (Additional file 17)). The certainty of the evidence was rated as very low. Behavioural co-interventions were provided to intervention participants in all trials; no co-interventions were provided to the control groups. Measures of abstinence and use of biochemical validation varied across trials [ 73 ].

Interventions to increase adherence to medications for tobacco dependence compared to usual or standard care

Abstinence/cessation in smokers motivated/wishing to quit or reduce smoking

Four trials reported on the effects of interventions aimed to increase adherence to tobacco cessation medications. All trials provided some behavioural support to those receiving usual care. Relative to usual care, the intervention typically included an additional component focused on medication adherence with additional contact time. In most studies, the intervention involved specialized behavioural counselling (e.g. counselling based on motivational interviewing techniques and 4R approach). All participants in each of the trials were receiving NRT. Biochemical verification was used in most trials and most reported point prevalence rates.

Compared to usual care, 33 more people per 1000 (95% CI: 8 fewer to 81 more; n = 5, 3593 participants; I 2 = 72%) receiving interventions to increase adherence to tobacco cessation medications were abstinent at 6-month follow-up (rating down twice for risk of bias and once for inconsistency) (Additional file 11: Table 24; Figure 2b (Additional file 17)) [ 66 ]. The certainty of the evidence was rated as very low.

Adverse events in smokers motivated/wishing to quit or reduce smoking

One study each reported no serious adverse events, or no treatment related adverse events. The third study reported no difference in adverse events between groups, but it is unclear whether this is based on confidence intervals or p -values (rating down once for risk of bias and once or twice for imprecision) (Additional file 11: Table 24; Figure 2b (Additional file 17)) [ 66 ]. We were unable to rate the certainty of the evidence due to sample size analysed not being reported for imprecision domain.

Change in emotional state—anxiety in smokers motivated/wishing to quit or reduce smoking

One trial reported no difference between groups regarding levels of anxiety at 1 week and 6 months, but it is unclear whether this is based on confidence intervals or p -values; (Additional file 11: Table 24; Figure 2b (Additional file 17)) [ 66 ]. We were unable to rate the certainty of the evidence due to sample size not being reported for imprecision domain.

Individual counselling (no systematic pharmacotherapy) compared to minimal contact control (no systematic pharmacotherapy)

Twenty-seven studies examined the effect of individual counselling delivered by a smoking cessation specialist outside of routine clinical care. Additional behavioural and/or other (e.g. computer-guided nicotine fading with contingent contract, cigarette substitute) co-interventions were provided in the majority of studies. Review authors state that no systematic pharmacotherapy was provided; however, a few trials did offer NRT or a prescription for NRT to those receiving counselling. Minimal contact control was usual care or brief advice (up to 15 min) with or without self-help materials. Some trials provided additional behavioural or other (e.g. monetary rewards for cessation) co-interventions to control participants; NRT was made available in three trials. Trials varied with respect to how abstinence was measured and whether biochemical validation was conducted.

At follow-up of 6 or more months, 40 more people per 1000 (95% CI: 28 to 54 more; n = 27, 11,100 participants; I 2 = 50%) receiving individual counselling compared to minimal contact were abstinent (rating down once for inconsistency and twice for indirectness) (Additional file 11: Table 29; Figure 2b (Additional file 17)). This was performed as a subgroup analysis by review authors; our assessment of subgroup credibility suggests that the subgroup analysis is plausible [ 74 ]. However, the certainty of the evidence was rated as very low.

Non-tailored print-based self-help materials (no face-to-face contact) versus no materials/no intervention

All trials in this analysis sent non-tailored materials to participants without personal contact. Control conditions varied across trials and included no intervention, usual care, wait-list and a letter apologizing for shortage of smoking cessation kits. Trials varied with respect to how abstinence was measured, and it was unclear or not reported in almost half of the studies. Biochemical validation was used in nearly half of studies. Behavioural co-interventions were provided to intervention participants in one trial.

Compared to control, 10 more people per 1000 (95% CI: 2 to 19 more; n = 11, 13,241 participants; I 2 = 0%) receiving non-tailored print-based self-help materials (with no face-to-face contact) were abstinent at 6+ month follow-up (Additional file 11: Table 36; Figure 2b (Additional file 17)). The certainty of the evidence was rated as high. This was performed as a subgroup analysis by review authors; our assessment of credibility suggests that the subgroup analysis is plausible. Review authors indicate that one trial not included in the meta-analysis due to inadequate reporting found no difference between groups [ 75 ].

Abstinence/cessation in smokers motivated to quit/wishing to quit

Two studies of treatment-seeking smokers examined the effect of non-tailored print-based materials without face-to-face contact. One trial each reported point prevalence and continuous/sustained abstinence. Only one of the trials biochemically validated abstinence. No co-interventions were provided.

At 6 months follow-up, 174 more people per 1000 (95% CI: 71 to 398 more; n = 2, 924 participants; I 2 = 0%) receiving non-tailored print-based self-help materials (no face-to-face contact) were abstinent compared to those receiving no materials/no intervention (rating down twice for risk of bias and once for imprecision) (Additional file 11: Table 37; Figure 2b (Additional file 17)) [ 75 ]. The certainty of the evidence was rated as very low.

Non-tailored print-based self-help materials (no face-to-face contact) compared to brief leaflet

All trials in this analysis sent non-tailored materials to participants without personal contact. Control participants received a brief leaflet which was considered a minimal print-based intervention by review authors. Additional behavioural co-interventions were provided to control participants in all studies. No additional co-interventions were given to active arms. Half of the studies reported continuous/sustained abstinence rates. Very few studies biochemically confirmed abstinence.

Compared with a brief leaflet control, 10 fewer people per 1000 (95% CI: from 23 fewer to 5 more; n = 6, 7023 participants, I 2 = 21%) given non-tailored print-based self-help materials (no face-to-face) were abstinent at 6+ months follow-up (rating down once for risk of bias) (Additional file 11: Table 38; Figure 2b (Additional file 17)). This was performed as a subgroup analysis by review authors; our assessment of credibility suggests that the subgroup analysis is plausible [ 75 ]. The certainty of the evidence was rated as moderate.

Non-tailored print-based self-help materials (with face-to-face contact) compared to no intervention or leaflet only

Materials were given to participants in-person, but investigators did not provide advice to smoking cessation. Most studies provided additional behavioural co-interventions to those in the active arm. No intervention was provided to control participants in most studies; in one study, participants received materials and a video not specific to smoking. Trials varied with respect to how abstinence was measured. Only one study used biochemical validation.

At longest follow-up (6+ months), 18 more people per 1000 (95% CI: 1 to 41 more; n = 4, 2822 participants; I 2 = 21%) receiving non-tailored print-based self-help materials (with face-to-face contact) were abstinent compared to those receiving no intervention or leaflet only (rating down twice for risk of bias) (Additional file 11: Table 39; Figure 2b (Additional file 17)). The certainty of the evidence was rated as low. Subgroup differences by control condition (no intervention or leaflet only) was not detected (test for subgroup differences: p = 0.88, I 2 = 0%) [ 75 ].

Individually tailored print-based self-help materials (no face-to-face contact) compared to no materials/no intervention

Materials were tailored to the individual’s characteristics; several trials used computerized expert systems with tailoring according to baseline data. In all trials, materials were sent to participants without personal contact. Control conditions varied across studies and included assessment only, thank you letters only, and no intervention or information. No co-interventions were provided to either arm in all trials. Majority of studies reported continuous/sustained abstinence rates. No studies used biochemical validation.

Compared to those receiving no materials/no intervention, 20 more people per 1000 (95% CI: 11 to 31 more; n = 10, 14,359 participants; I 2 = 0%) receiving individually tailored print-based self-help materials (no face-to-face contact) were abstinent at longest follow-up (6+ months) (rating down twice for risk of bias) (Additional file 11: Table 40; Figure 2b (Additional file 17)) [ 75 ]. The certainty of the evidence was rated as low.

Intensive telephone counselling compared to minimal telephone counselling

Three trials compared intensive telephone counselling, defined as three to five calls, to minimal telephone counselling consisting of a single call. Two trials provided a behavioural co-intervention to both arms, and one of these trials also provided pharmacotherapy to all study participants including those receiving control. Most trials reported point prevalence rates. Only one trial biochemically validated smoking abstinence.

At 6 months or more follow-up, 64 more people per 1000 (95% CI: 28 to 104 more; n = 3, 2602 participants; I 2 = 0%) receiving intensive telephone counselling were abstinent compared to those receiving minimal telephone counselling (rating down twice for risk of bias and half for each indirectness and imprecision) (Additional file 11: Table 42; Figure 2b (Additional file 17)) [ 76 ]. The certainty of the evidence was rated as very low.

Brief motivational telephone counselling compared to usual care telephone call

One trial compared brief motivational telephone counselling (three 15-min calls) to a usual care telephone call (one 5-min call). No co-interventions were provided to either arm.

At 12 months follow-up, 60 more people per 1000 (95% CI: 4 to 190 more; n = 1, 374 participants) receiving brief motivational telephone counselling were point prevalence abstinent compared to those receiving usual care telephone call (rating down twice for risk of bias and twice for imprecision) (Additional file 11: Table 43; Figure 2b (Additional file 17)) [ 76 ]. The certainty of the evidence was rated as very low.

Telephone counselling for smoking reduction compared to usual care telephone call

Compared to a usual care telephone call (1 5-min call), 49 more people per 1000 (95% CI: 1 fewer to 167 more; n = 1, 375 participants) receiving telephone counselling (3 15-min calls) for smoking reduction were point prevalence abstinent at 12-month follow-up (rating down twice for risk of bias and twice for imprecision) (Additional file 11: Table 44; Figure 2b (Additional file 17)) [ 76 ]. The certainty of the evidence was rated as very low.

Interactive voice response (IVR) systems compared to no intervention

One trial compared IVR to no intervention. Prior to randomization, all participants received varenicline for 12 weeks and IVR. After randomization, the control group no longer received IVR. Review authors reported little to no difference between groups at 24 months follow-up (21.7% of intervention group versus 42.9% of control group; p = 0.13) (rating down once for risk of bias) (Additional file 11: Table 45; Figure 2b (Additional file 17)) [ 77 ]. We were unable to rate the certainty of the evidence due to sample size analysed not being reported for imprecision domain.

Physician advice (minimal or intensive interventions) compared to no advice (or usual care)

Physician advice involved a ‘stop smoking’ message. Interventions were defined as minimal if delivered during a single session of less than 20-min duration plus up to 1 follow-up visit with or without a leaflet. Intensive interventions involved a longer initial consultation, use of additional materials other than a leaflet, or more than one follow-up visit. Pharmacotherapy co-intervention was provided to intervention participants in some of the studies. Additional behavioural and/or pharmacotherapy co-interventions were provided to control participants in some studies. Trials varied with respect to how abstinence was measured and only a few biochemically confirmed smoking abstinence.

At longest follow-up, 36 more people per 1000 (95% CI: 28 to 46 more; n = 26, 22,239 participants; I 2 = 40%) receiving physician advice were abstinent in comparison to those receiving no advice (or usual care) (rating down twice for risk of bias) (Additional file 11: Table 46; Figure 2b (Additional file 17)). The certainty of the evidence was rated as low. Subgroup differences by advice intensity (minimal or intensive) was not detected (test for subgroup differences: p = 0.31, I 2 = 3%) (Additional file 13). Review authors state that indirect comparisons across subgroups defined by number of advice sessions was suggestive of greater effects with multiple visits compared to a single visit. Authors indicate no important differences between subgroups according to use of aids [ 78 ].

Physician advice with follow-up compared to minimal intervention/advice with single visit

Five studies compared physician advice with follow-up to a minimal intervention/advice with a single visit. Most studies reported continuous/sustained abstinence. Abstinence was biochemically confirmed in 60% of studies. One study provided a pharmacotherapy co-intervention to both arms.

Compared to control, 47 more people per 1000 (95% CI: 7 to 103 more; n = 5, 1254 participants; I 2 = 0%) receiving physician advice with follow-up were abstinent at 6+ months (rating down twice for risk of bias and once for imprecision) (Additional file 11: Table 47; Figure 2b (Additional file 17)) [ 78 ]. The certainty of the evidence was rated as very low.

Intensive advice compared to minimal advice

Intensive interventions involved a longer initial consultation, use of additional materials other than a leaflet or more than one follow-up visit. Trials varied with respect to how abstinence was measured; nearly half reported point prevalence rates and the reminder continuous/sustained rates. Biochemical validation was used in 60% of studies. One study provided a pharmacotherapy co-intervention to both arms.

Compared to minimal advice, 28 more people per 1000 (95% CI: 15 to 42 more; n = 15, 9775 participants; I 2 = 32%) receiving intensive advice were abstinent at longest follow-up (6+ months) (rating down twice for risk of bias and once for indirectness) (Additional file 11: Table 48; Figure 2b (Additional file 17)). The certainty of the evidence was rated as very low. The effect estimate was larger for the subgroup of participants at high risk of smoking-related diseases as compared to unselected smokers, but confidence intervals overlapped (test for subgroup differences: p = 0.02, I 2 = 82%) (Additional file 13) [ 78 ].

Group behaviour therapy compared to no intervention

Group therapy was delivered over at least two sessions. Measures of abstinence were unclear or not reported for two-thirds of trials. Some studies provided both groups with co-interventions including pharmacotherapy; however, provision of co-interventions was unclear for most studies.

Compared to those receiving no intervention, 108 more people per 1000 (95% CI: 54 to 186 more; n = 9, 1098 participants; I 2 = 55%) given group behaviour therapy were abstinent at 6+ months follow-up (rating down twice for risk of bias, once for inconsistency, once for imprecision) (Additional file 11: Table 51; Figure 2b (Additional file 17)) [ 79 ]. The certainty of the evidence was rated as very low.

Interactive and tailored internet interventions compared to non-active controls

Interactive interventions ‘involved a two-way flow of information between the internet and the participant’ and programmes were tailored to a participant's characteristics [ 61 ]. Across studies, control conditions consisted of printed self-help guides or usual care. One study provided NRT as an adjunct to the internet intervention. Another study offered free nicotine patches and bupropion to all participants, including those receiving control, and their partners who wanted to quit. Trials varied with respect to how abstinence was measured and only 25% used biochemical validation.

At longest follow-up (6 to 12 months), 19 more people per 1000 (95% CI: 1 to 39 more; n = 8, 6786 participants; I 2 = 58%) receiving interactive and tailored internet interventions were abstinent compared to non-active controls (rating down twice for risk of bias, once for indirectness and inconsistency) (Additional file 11: Table 52; Figure 2b (Additional file 17)) [ 61 ]. The certainty of the evidence was rated as very low.

Mobile phone short message service compared to control

Abstinence/cessation in smokers motivated/wishing to quit

One trial examined the effect of personalized text messaging with smoking cessation advice, support and distraction sent between a health care provide or buddy (i.e. lay health worker or peer support) and the participant. The control group received biweekly text messages thanking them for their involvement and reminder of a free month of text messaging should they complete the study. The trial used various measures of abstinence.

Compared to control, 17 more people per 1000 (95% CI: 21 fewer to 62 more; n = 1, 1705 participants) receiving the active text messaging intervention were point prevalent abstinent at 6-month follow-up (rating down once for risk of bias and twice for imprecision). The certainty of the evidence was rated as very low. However, when point prevalence using last outcome carried forward, 76 more people per 1000 receiving the active intervention were point prevalent abstinent in comparison to controls (95% CI: 30 to 131 more; n = 1, 1705 participants) (rating down once for risk of bias and once for imprecision). The certainty of the evidence was rated as low.

When allowing for three or fewer lapses of two or fewer cigarettes per lapse, 29 more people per 1000 (95% CI: 5 to 65 more; n = 1, 1705 participants) receiving the active text messaging intervention were continuously abstinent compared to controls (rating down once for risk of bias and once for imprecision). The certainty of the evidence was rated as low. These effects were not sustained when allowing for no lapses (Additional file 11: Table 63; Figure 2b (Additional file 17)) [ 65 ].

Adverse events in smokers motivated/wishing to quit

Compared to control, six fewer people per 1000 receiving the active text messaging intervention had been in a car crash during the 6-month follow-up period (rating down twice for imprecision). The certainty of the evidence was rated as low. However, it is possible that there is little to no difference between groups or that more participants receiving the intervention were in a car crash (Additional file 11: Table 63; Figure 2b (Additional file 17)) [ 65 ].

Compared to control, 5 more people per 1000 (95% CI: 15 fewer to 33 more; n = 1, 1705 participants) receiving the active text messaging intervention experienced pain in their thumb/finger joints during the 6-month follow-up (rating down twice for imprecision). The certainty of the evidence was rated as low (Additional file 11: Table 63; Figure 2b (Additional file 17)) [ 65 ].

Mobile phone-based interventions compared to usual care

Nearly all studies had text messaging (SMS) as the main component of the intervention; however, one trial differed in that participants received mobile phone-based counselling (cognitive behavioural therapy (CBT) and motivational). In-person visits or assessments were provided in addition to SMS in five studies. Control conditions varied across studies and included no intervention, text messages, written/internet untailored materials, untailored messages and standard cessation advice and treatment. Trials varied with respect to how abstinence was measured with slightly more reporting point prevalence rates. Abstinence was biochemically confirmed in half of the studies.

At longest follow-up (6+ months), 37 more people per 1000 (95% CI: 26 to 50 more; n = 12, 11,885 participants; I 2 = 59%) receiving mobile phone-based interventions were abstinent in comparison to those receiving usual care (rating down once for risk of bias and once for inconsistency) (Additional file 11: Table 69; Figure 2b (Additional file 17)). The certainty of the evidence was rated as low. Sensitivity analyses according to abstinence definition, biochemical validation and intervention characteristics showed no appreciable change in the relative effect estimate (Additional file 13) [ 80 ].

Other therapy interventions

Hypnotherapy compared to placebo drug alone

Intervention details, including the number and duration of sessions, was not reported in the only included trial. At 12 months follow-up, 18 fewer people per 1000 (95% CI: 77 fewer to 166 more; n = 1, 114 participants) receiving hypnotherapy were point prevalent abstinent compared to those receiving the placebo drug (rating down twice for risk of bias and twice for imprecision) (Additional file 11: Table 1 ; Figure 2c (Additional file 17)) [ 53 ]. The certainty of the evidence was rated as very low.

Acupuncture compared to sham acupuncture

All trials selected acupuncture points (i.e. anatomic sites) for smoking cessation. Two studies used facial acupuncture, five used auricular acupuncture alone with/without continuous stimulation (i.e. needle or pressure device) and four used combined body and auricular acupuncture with/without continuous stimulation (i.e. indwelling needle or seed). Two trials, representing 4% of the evidence, used potentially active acupuncture points for the sham arm. Behavioural co-interventions were provided to both study arms in some trials and pharmacotherapy to all participants in one study. Trials varied with respect to how abstinence was measured. Few studies used biochemical validation.

At longest follow-up (6–12 months), 11 more people per 1000 (95% CI: 15 fewer to 43 more; n = 11, 1892 participants, I 2 = 23%) who received acupuncture were abstinent compared to those receiving sham (rating down twice for risk of bias and twice for imprecision) (Additional file 11: Table 64; Figure 2c (Additional file 17)). The certainty of the evidence was rated as low. Sensitivity analysis excluding studies which used potentially active acupuncture points for the sham arm yielded similar results [ 55 ].

Acupuncture compared to waiting list/no intervention

All trials selected acupuncture points (i.e. anatomic sites) for smoking cessation. One study used facial acupuncture and two used auricular acupuncture alone with or without continuous stimulation (i.e. needle or pressure device). One study provided a behavioural co-intervention to both study arms, with no co-interventions in the remaining studies. No studies biochemically verified abstinence.

At 6 to 12 months follow-up, 60 more people per 1000 (95% CI: 2 fewer to 174 more; n = 2, 393 participants, I 2 = 57%) reported being smoking abstinent compared to those in the waitlist/no intervention group. We rated down twice for risk of bias, once for inconsistency and twice for imprecision (Additional file 11: Table 65; Figure 2c (Additional file 17)) [ 55 ]. The certainty of the evidence was rated as very low.

Continuous auricular stimulation compared to sham stimulation

Four studies used indwelling needles and the remainder used continuous acupressure. One trial, representing 5% of the evidence, used potentially active acupuncture points for the sham arm. Two studies provided behavioural co-intervention to both groups. Half of the studies reported use of biochemical confirmation for smoking abstinence. The measure of smoking abstinence was unclear or not reported for half of the studies.

At 6 to 12 months follow-up, 26 more people per 1000 (95% CI: 12 fewer to 98 more; n = 6, 570 participants, I 2 = 22%) given continuous auricular stimulation compared to sham stimulation stopped smoking (rating down twice for risk of bias to also reflect concerns with publication bias and twice for imprecision) (Additional file 11: Table 66; Figure 2c (Additional file 17)). The certainty of the evidence was rated as very low. Subgroup differences by type of stimulation (indwelling needles or continuous acupressure) was not detected (test for subgroup differences: p = 0.06, I 2 = 72%) (Additional file 13) [ 55 ].

Laser therapy compared to sham laser

Only one of the two studies reported the dose of laser used which was 50 mW for 14 min. One study provided behavioural co-intervention to both arms. Abstinence measures were unclear or not reported for both studies.

Studies were heterogeneous and could not be quantitatively synthesized ( I 2 = 97%). Review authors report that heterogeneity was possibly attributable to populations recruited and dose of laser administered. Results from one study were null-inclusive (RD 3 more per 1000, 95% CI: 45 fewer to 94 more). The other study reported results favouring the intervention (RD 515 more per 1000, 95% CI: 192 to 1000 more) (rating down once for risk of bias, twice for inconsistency and twice for imprecision) (Additional file 11: Table 67; Figure 2c (Additional file 17)) [ 55 ]. However, the certainty of the evidence was rated as very low.

Electrostimulation compared to sham electrostimulation

Electrostimulation was administered through surface electrodes over the mastoid bone in one study and to the ear in the other. No co-interventions were provided to either arm in both studies. Abstinence measures were unclear or not reported for both studies. Biochemical validation was used in one study.

Compared to sham electrostimulation, 34 fewer people per 1000 (95% CI: 102 fewer to 60 more; n = 2, 405 participants, I 2 = 46%) receiving electrostimulation were abstinent at longest follow-up (6 to 12 months) (rating down twice for risk of bias and twice for imprecision) (Additional file 11: Table 68; Figure 2c (Additional file 17)) [ 55 ]. The certainty of the evidence was rated as very low.

Acupressure versus sham

No studies were found [ 55 ].

Laser therapy versus wait-list/no intervention

Electrostimulation versus wait-list/no intervention

St John’s wort versus placebo

One trial examined 900 mg/day of St John’s wort for 14 weeks and the other examined both 900 and 1800 mg/day for 12 weeks; treatment arms in the latter study were combined in the analysis. Behavioural co-interventions were provided to all groups in both studies. The studies reported biochemically confirmed prolonged abstinence.

Compared to placebo, 10 fewer participants per 1000 (95% CI: 40 fewer to 83 more; n = 2, 261 participants, I 2 = 29%) on St. John’s wort were abstinent at 6-month follow-up (rating down twice for imprecision) (Additional file 11: Table 27; Figure 2c (Additional file 17)) [ 67 ]. The certainty of the evidence was rated as low.

S-Adenosyl-L-methionine (SAMe) versus placebo

A single study reported on 800 and 1600 mg/day SAMe; doses were combined in analysis by review authors. All study groups received a behavioural co-intervention.

Compared to placebo, 38 fewer participants per 1000 (95% CI: 95 fewer to 134 more; n = 1, 120 participants) receiving SAMe were point prevalence abstinent at 6 months follow-up (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 28; Figure 2c (Additional file 17)) [ 67 ]. The certainty of the evidence was rated as very low.

Exercise interventions versus no intervention

No studies were found [ 60 ].

Combination interventions

Behavioural support (advice) plus NRT plus phone calls versus no intervention

Abstinence/cessation in smokers not motivated/wishing to quit

In one trial, participants received an initial advice intervention aimed at encouraging reduction. Participants were also advised to quit; those who agreed received the cessation intervention. Intervention participants were offered a choice of NRT gum or patch. Control participants received assessment calls only. Co-interventions were not provided to either group. Smoking cessation was not biochemically verified.

Review authors report that point prevalence abstinence rates were significantly higher in the intervention group as compared to control at 6 months follow-up (rating down twice for risk of bias and once or twice for imprecision) (Additional file 11: Table 34; Figure 2d (Additional file 17)) [ 56 ]. The certainty of the evidence was rated as very low.

Reduction in the number of cigarettes/day in smokers not motivated/wishing to quit

The same trial also reported on smoking reduction. Review authors indicate that the reduction rate was significantly higher in the intervention group compared to those in the control arm (rating down twice for risk of bias and once or twice for imprecision) (Additional file 11: Table 34; Figure 2d (Additional file 17)) [ 56 ]. The certainty of the evidence was rated as very low.

Telephone counselling plus self-help materials versus usual care

Participants were instructed to reduce smoking by 50% or more; cessation was subsequently encouraged. Self-help materials were individually tailored newsletter and a targeted newsletter. Usual care consisted of usual care plus generic health mailings. Co-interventions were not provided to either group. Smoking abstinence was biochemically verified.

At 12-month follow-up, 22 more people per 1000 (95% CI: 18 fewer to 124 more; n = 1, 320 participants) receiving telephone counselling plus self-help were point prevalence abstinent as compared to those receiving usual care (rating down twice for imprecision) (Additional file 11: Table 33; Figure 2d (Additional file 17)) [ 56 ]. The certainty of the evidence was rated as low.

Reduction in cigarettes/day of >50% of baseline or cessation

In the same trial, 63 more people per 1000 (95% CI: 22 fewer to 195 more; n = 1, 320 participants) receiving telephone counselling plus self-help were abstinent or reduced the number of cigarettes smoked by more than 50% at 12 months compared to usual care (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 33; Figure 2d (Additional file 17)) [ 56 ]. The certainty of the evidence was rated as very low.

Reduction in carbon monoxide >50%

At 12 months, 1 fewer person per 1000 (95% CI: 59 fewer to 100 more; n = 1, 320 participants) receiving telephone counselling plus self-help reduced their carbon monoxide levels by more than 50% as compared to those receiving usual care (rating down twice for imprecision) (Additional file 11: Table 33; Figure 2d (Additional file 17)) [ 56 ]. The certainty of the evidence was rated as low.

Reduction in number of cigarettes per day from baseline

Review authors state that the number of cigarettes per day decreased from baseline in both groups (mean change from baseline (SD): intervention: 21.2 (9.4) and usual care: 20.1 (8.9). There was no difference between groups at 12 months follow-up (mean (SD): intervention, 15.8 (10. 3) and usual care, 15.3 (9.2) (rating down once for risk of bias) (Additional file 11: Table 33; Figure 2d (Additional file 17)) [ 56 ]. Unable to assess the certainty of the evidence and imprecision domain based on information reported.

Reduction in carbon monoxide from baseline

Carbon monoxide levels decreased from baseline in both groups. Review authors state that there was no significant between-group difference in the change from baseline but it is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that the confidence interval around the best estimate of effect includes the possibility of little to no difference between groups and greater reduction in one group over another (Additional file 11: Table 33; Figure 2d (Additional file 17)) [ 56 ]. Unable to assess the certainty of the evidence and imprecision domain based on information reported.

Hotline and self-help materials versus minimal intervention

Two trials examined the effects of telephone hotline and self-help materials. One study promoted a 24-h hotline, daytime access to counsellors and use of the American Lung Association self-help manual. The second trial consisted of a Quitline proactive contract, quit kits (national Quitline printed resources), individual counselling with a practice nurse (face-to-face) and three proactive telephone calls from counsellors. Control participants received a minimal intervention; this was usual care delivered by a primary care provider (i.e. advice, referral to Quitline, or both) in one study and a self-help manual in the second (American Lung Association). One study offered pharmacotherapy co-intervention (NRT patch) to both arms. Both trials reported continuous/sustained abstinence rates. Only one used biochemical validation.

At longest follow-up (12 to 18 months), 21 more people per 1000 (95% CI: 5 more to 42 more; n = 2, 3327 participants; I 2 = 0%) receiving hotline and self-help materials were abstinent compared to those receiving minimal intervention (rating down by 1.5 for risk of bias and 0.5 for imprecision) (Additional file 11: Table 41; Figure 2d (Additional file 17)) [ 76 ]. The certainty of the evidence was rated as low.

Internet intervention plus behavioural support versus non-internet-based non-active control

Participants in five trials received an internet intervention plus behavioural support which was provided by nurses, peer coaches or tobacco treatment specialists. Control participants received a non-active control condition which varied across trials (usual care, printed self-help guides, standard smoking cessation advice). In two trials, all participants (including controls) were using or offered pharmacotherapy. Trials varied with respect to how smoking abstinence was measured, most reported prolonged rates. Biochemical validation was used in 40% of studies.

Compared to non-active controls, 54 more people per 1000 (95% CI: 23 more to 92 more; n = 5, 2334 participants; I 2 = 60%) receiving an internet intervention plus behavioural support were abstinent at longest follow-up of 6 to 12 months (rating down one to two times for risk of bias, once for inconsistency and 0.5 for imprecision) (Additional file 11: Table 53; Figure 2d (Additional file 17)) [ 61 ]. The certainty of the evidence was rated as very low.

Individual smoking cessation intervention based on cognitive behavioural therapy and motivational interviewing plus NRT patch compared to routine care

Abstinence/cessation in smokers with schizophrenia or schizoaffective disorder

A single trial reported on the effects of a combination intervention which involved 8 h of individual contact for 8 weeks and NRT patch for about 10 weeks (21 mg, 14 mg, 7 mg titrated down). Participants in both study groups received booklets on smoking cessation as a co-intervention. Review authors report no statistically significant difference between groups in biochemically validated point prevalence or continuous abstinence rates at 6 months, 12 months, or 4 years (threshold for statistical significance was p < 0.01) (rating down once for risk of bias) (Additional file 11: Table 57) [ 59 ]. We were unable to assess imprecision and provide an overall certainty rating due to missing information.

Reduction in cigarettes per day of >50% of baseline in smokers with schizophrenia or schizoaffective disorder

Review authors report no statistically significant difference between groups in smoking reduction at 6 months, 12 months, or 4 years (rating down once for risk of bias) (Additional file 11: Table 57) [ 59 ]. We were unable to assess imprecision and provide an overall certainty rating due to missing information.

Standard treatment plus extended NRT and extended CBT compared to standard treatment in smokers with past depression

Abstinence/cessation in smokers with past depression

The only trial in this analysis recruited general smokers but provided pre-stated subgroup data for participants with past depression. Standard treatment consisted of sustained release bupropion (300 mg/day) for 12 weeks, nicotine gum (2 mg and 4 mg) for 10 weeks, 5 group counselling sessions from a counsellor and a self-help manual; no further treatment was provided after week 12. In addition to standard treatment, those in the active arm received extended NRT (i.e. until week 52) and extended CBT (i.e. 11 individual CBT sessions from week 10 to 52).

Compared to standard treatment, 259 more people per 1000 (95% CI: 6 fewer to 786 more; n = 1, 57 participants) receiving standard treatment plus extended NRT and extended CBT were point prevalence abstinent (follow-up timepoint unclear) (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 62; Figure 2d (Additional file 17)) [ 58 ]. The certainty of the evidence was rated as very low.

Combined pharmacotherapy and behavioural interventions compared to usual care or minimal intervention

The typical intervention involved multiple contacts with a specialist cessation counsellor combined with pharmacotherapy. Review authors reported that most of the trials offered one or more types of NRT or bupropion. Usual care or minimal intervention was typically brief advice and self-help materials. Additional co-intervention (behavioural with or without pharmacotherapy) was provided to intervention participants in a few trials. Some trials provided behavioural and/or pharmacotherapy co-interventions to control participants. Trials varied with respect to how abstinence was measured but most used point prevalence. Biochemical confirmation of abstinence was used in 65% of the studies.

At longest follow-up (6+ months), 71 more people per 1000 (95% CI: 58 more to 84 more; n = 52, 19,488 participants; I 2 = 36%) receiving combination pharmacotherapy and behavioural support were abstinent in comparison to those receiving usual care or minimal intervention (rating down twice for risk of bias to also reflect concerns for indirectness) (Additional file 11: Table 49; Figure 2d (Additional file 17)). The certainty of the evidence was rated as low. Review authors reported a larger effect in the subgroup of trials recruiting participants from health care settings (Additional file 13). Other variables tested in subgroup and meta-regression analyses did not modify the effect; this included participants’ motivation to quit and intensity of behavioural support [ 81 ].

Combined pharmacotherapy and intensive behavioural interventions compared to usual care or no intervention

Review authors excluded one study with a more intensive intervention from the main analysis presented above [ 81 ]. The study intervention consisted of 12 group sessions over 10 weeks, with advice from physician on risk for COPD, and 2 mg of nicotine gum for 6 months. Intervention participants were also randomized to bronchodilator or placebo. The control group received no intervention or usual care. No co-interventions were provided to either arm. The study reported biochemically confirmed point prevalence rates.

Compared to usual care or no intervention, 260 more people per 1000 (95% CI: 212 more to 315 more; n = 1, 5887 participants) receiving the combination intervention were abstinent at 12-month follow-up (rating down once for indirectness) (Additional file 11: Table 50) [ 81 ]. The certainty of the evidence was rated as moderate.

Electronic cigarette intervention

E-cigarette versus placebo

Although the stage II of this evidence review aims at synthesizing evidence on the harms and benefits of e-cigs, we have included results from the Lindson-Hawley systematic review [ 56 ] in this overview of reviews for completeness. In the single trial identified by Lindson-Hawley [ 56 ], participants in the active treatment group received e-cigarettes containing either 7.2 or 5.4 mg of nicotine for 12 weeks to assist smoking reduction; active arms were combined in analyses. Control participants received e-cigarettes without nicotine. Neither group received co-interventions.

The trial reported biochemically validated abstinence defined as ‘not even a puff’ since the previous visit. At 12 months follow-up, 70 more people per 1000 (95% CI: 1 fewer to 270 more; n = 1, 300 participants) using e-cigarette with nicotine were abstinent in comparison to those receiving e-cigarettes without nicotine, but it is possible that there is little to no difference between groups or that more participants in the active treatment arm stopped smoking (rating down twice for imprecision) (Additional file 11: Table 35; Figure 2e (Additional file 17)) [ 56 ]. The certainty of the evidence was rated as low.

Reduction in cigarettes/day of >50% of baseline or cessation in smokers not motivated/wishing to quit

At 12 months follow-up, 45 more people per 1000 (95% CI: 38 fewer to 187 more; n = 1, 300 participants) using e-cigarette with nicotine reduced the number of cigarettes per day by more than 50% (including those who quit) (rating down once for risk of bias and twice for imprecision) (Additional file 11: Table 35; Figure 2e (Additional file 17)) [ 56 ]. The certainty of the evidence was rated as very low.

Reduction in number cigarettes/day

Review authors indicate that there was no statistically significant difference between groups (median cigarettes per day = 12–14 in all groups), but it is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that the confidence interval around the best estimate of effect includes the possibility of little to no difference between groups and a greater reduction in one group over another (rating down once for risk of bias) (Additional file 11: Table 35; Figure 2e (Additional file 17)) [ 56 ]. Unable to assess the certainty of the evidence because number of participants included in analysis not reported for imprecision domain.

Reduction in carbon monoxide

Authors indicate that there was no significant difference between groups (median CO = 15–17 ppm in all groups), but it is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that the confidence interval around the best estimate of effect includes the possibility of little to no difference between groups and greater reduction in one group over another (Additional file 11: Table 35; Figure 2e (Additional file 17)) [ 56 ]. Unable to assess the certainty of the evidence because number of participants included in analysis not reported for imprecision domain.

Adverse events in smokers not motivated/wishing to quit

Review authors indicate that the frequency of adverse events was similar across groups at baseline, 12 weeks and 52 weeks. There was a reduction in reported symptoms from baseline to 12-month follow-up across groups ( p < 0.001). Rates of shortness of breath were reduced from 20 to 4% from baseline to 2 weeks (Additional file 11: Table 35; Figure 2e (Additional file 17)) [ 56 ]. We were unable to assess imprecision and provide an overall certainty rating due to missing information (i.e. number of participants included in the analysis). Authors stated that no serious adverse events occurred [ 56 ].

Weight gain in smokers not motivated/wishing to quit

Review authors indicate that there was no significant difference in weight change within or between groups. Regarding the latter, it is unclear whether this is based on confidence intervals or p -values; we interpret this to mean that the confidence interval around the best estimate of effect includes the possibility of little to no difference between groups and more weight gain in one group over another (Additional file 11: Table 35; Figure 2e (Additional file 17)) [ 56 ]. Unable to assess the certainty of the evidence because number of participants included in analysis not reported for imprecision domain. Based on reporting, it is uncertain but unlikely that the outcome is post-cessation weight gain (i.e. does not appear to be assessed in only abstinent smokers).

Several stop-smoking interventions were identified that demonstrated an effect on sustained abstinence from tobacco smoking. Varenicline increased the chances of successful smoking cessation between two- and threefold compared with placebo in the general population of smokers and smokers with depression. The effect sizes included a large benefit for sustained abstinence for 6 or more months. There was a notable benefit for using varenicline in smokers with schizophrenia, bipolar disorder or other psychiatric disorders, given the high certainty of evidence based on four RCTs. Similarly, there is likely a benefit of cytisine over placebo in smokers motivated to quit; however, the estimates for benefit ranged from small but important to a large benefit with relatively low quit rates (9% in those receiving cytisine and 2% for placebo) at 1 year follow-up. NRT also demonstrated a twofold moderate benefit in smokers not motivated to quit, with 44 more per 1000 individuals more likely to stop smoking after following up for 1 to 2 years. Despite an observed benefit in smokers motivated to quit, the evidence in smokers with depression or past depression was less clear. The effect estimates for NRT gum versus placebo in smokers with depression encompassed little to no difference to a large benefit and was based on low certainty evidence, while the effect estimates for smokers with past depression encompassed both harm and benefit and was also based on low evidence. Lastly, evidence on bupropion suggested that it may increase smoking cessation among smokers with depression; however, we are very uncertain about the evidence as the effect estimates encompassed both benefits and harms. Although benefits were observed for smoking cessation with bupropion, varenicline and NRT, it is important to note little to no difference on long-term post-cessation weight gain. We also observed small harms like increased palpitations/chest pain with NRT, increased adverse events with varenicline (i.e. nausea, insomnia, abnormal dreams, headache) and mild harms (i.e. nausea, insomnia, irritability, headache, etc.) with cytisine compared to placebo. Lastly, bupropion showed little to no harm between groups due to insufficient information and low evidence certainty. The results from our review aligned with a 2023 systematic review and network meta-analysis (NMA) where high certainty evidence surrounding varenicline and cytisine as pharmacotherapy treatments showed higher smoking cessation rates compared to no pharmacotherapy. The NMA results also showed high-certainty evidence that nicotine patches, fast-acting nicotine and bupropion were more effective than control. For harm, low certainty evidence showed no difference between comparator groups [ 82 ]. The results also aligned with the review; an evidence update for the U.S. Preventive Services Task Force (USPSTF) having a very similar methodology showed strong evidence that a range of pharmacological and behavioural interventions offered individually or in combination can effectively increase smoking cessation in adults [ 83 ].

Other interventions that also showed a benefit on smoking cessation include physician advice, non-tailored print-based self-help materials, stage-based individual counselling, stage-based expert systems, individual counselling and group therapy. There was high certainty in the evidence for non-tailored print-based self-help materials (not face-to-face) compared to no materials in the general population of smokers suggesting a small but important benefit in smoking cessation; however, the effect was unclear in smokers motivated/wishing to quit. The effect of physician advice suggested moderate benefit; however, the certainty of the evidence was low due to very serious risk of bias. The effect of stage-based individual counselling and/or advice versus usual care in the general population of smokers had little to no difference on smoking cessation with moderate certainty of evidence. Lastly, stage-based expert systems, individual counselling versus minimal contact control and group therapy all showed a small but important benefit in smoking cessation; however, the certainty of evidence was very low.

The effects of some interventions on smoking cessation were unclear which included interventions to increase adherence to medications, telephone counselling plus self-help materials, interactive and tailored internet interventions, mobile phone-based interventions including text messaging, hypnotherapy, acupuncture, continuous auricular stimulation, laser therapy, electrostimulation, acupressure, St John’s wort, SAMe, electronic cigarettes, interactive voice response systems, standard treatment plus extended NRT plus extended CBT, individual counselling plus self-help and other combinations of interventions (Figure 2e). Unclear effects of interventions encompassed both a benefit and a harm and were usually based on low or very low certainty of evidence. For electronic cigarettes, the NMA results differed from our review results as there was a high certainty of evidence showing higher smoking abstinence rates in the nicotine e-cigs group than in the control group [ 82 ].

There are some important limitations to consider in our overview. For feasibility, we limited our study inclusion to Cochrane systematic reviews. Doing so may have resulted in a loss of outcome data as a more up-to-date non-Cochrane review with overlapping scope may have been available [ 33 ]. We also relied solely on information reported in the reviews (e.g. outcome measures, risk of bias assessments) and did not consult primary studies. This may have resulted in conflicting information reported within the text of reviews and the review evidence tables risk the possibility of propagating errors by carrying-over those extractions (i.e. two systematic reviews that had reported different GRADE ratings while assessing the same evidence from a single trial [ 56 , 67 ]). Additionally, reporting across reviews varied. For example, assessment of co-interventions was a function of review authors’ reporting and presentation of the information. The reporting of usual care also varied and often included smoking cessation interventions; this could attenuate the effect of the intervention. Whether authors across reviews would have assessed and presented the same information in the same manner is unknown. There were also differences among reviews in whether or how they used GRADE methods. For example, variation in whether biochemical validation was considered in the assessment. Many reviews considered both performance and detection bias together, which would be reflective of early Cochrane standards. Determining indirectness was an arduous task as individual study information had to be extracted and collated to determine the weighted aggregate. This is an important aspect of feasibility that others should consider when considering an overview for clinical practice guidelines. Another limitation to note is that our exclusion of data combining placebo and non-placebo controls may have led to a few potentially useful analyses being excluded. For example, we did not include the main analyses from the reviews focusing on bupropion and NRT, which are the main analyses used in the USPSTF tobacco cessation guideline, due to the comparator being labelled as placebo and ‘other’ controls. One last limitation to consider is related to the timeframe of the searches of the included reviews and the updates. There has been a search update for three of the included Cochrane reviews (i.e. Cahill 2016 [ 84 ], Farley 2012 [ 85 ], and Howes 2020 [ 86 ]) with the inclusion of new studies; however, the main conclusions remained unchanged for two of the reviews (i.e. Farley 2012 and Howes 2020). For Cahill, conclusions were updated in terms of high evidence certainty surrounding varenicline and moderate evidence certainty surrounding cytisine helping more people quit smoking in comparison to placebo at 6 months plus follow-up. For the results on SAEs, there was no difference in the number of individuals reporting SAEs in the cytisine groups compared to placebo; however, there was moderate evidence certainty that those in the varenicline group are more likely to report SAE than those not taking it [ 84 ].

Overall, the evidence included in this overview of systematic reviews was based on systematic reviews rated low or very low AMSTAR 2 quality. AMSTAR 2 was used to measure quality, but low ratings may be reflective of poor reporting. Most of the reviews were rated as critically low. For critical domains like the risk of bias, there may be some studies where they were unassessed; however, we considered the authors’ statements within the text of their review to help fill gaps. For some domains, we determined as ‘unclear risk of bias’ by default when information was missing. For the 38% of reviews that did not consider the risk of bias in the interpretation of results, this would not strongly influence the understanding of the evidence here as we undertook GRADE assessments (that include an assessment of the risk of bias for the body of evidence of an analysis) as part of our process.

Conclusions

This overview of reviews provides a comprehensive synthesis of the current evidence on the interventions helping adults aged 18 years and older to quit smoking. Results of this review, which included low, moderate and high-quality evidence, suggest that pharmacological (i.e. varenicline, NRT, cytisine, bupropion) and behavioural interventions (i.e. physician advice, non-tailored print-based self-help materials, stage-based individual counselling, stage-based expert systems, individual counselling and group therapy) can help the general smoking population quit smoking, however, with some small or mild harms to consider following NRT or varenicline use and will need to be assessed in the context of continued smoking. It is also important to note that the evidence examined does not provide clarity regarding ideal intervention strategies, nor the long-term impact of these interventions for preventing smoking. We also caution readers to avoid indirect comparisons across the analyses reported within this document, whether across categories or within a category where differences in dose and duration of treatment may be reported.

Availability of data and materials

All data generated or analysed during this study are included in this published article (and its supplementary information files).

Abbreviations

A MeaSurement Tool to Assess Systematic Reviews

Cognitive behavioural therapy

Confidence interval

Carbon monoxide

Exhaled carbon monoxide

Grading of Recommendations, Assessment, Development and Evaluation

Hamilton Depression Rating Scale

Interactive voice response

Mean difference

Nicotine replacement therapy

Positive and Negative Syndrome Scale

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Randomized controlled trial

Risk difference

Serious adverse event

S-Adenosyl-L-methionine

Standard deviation

Standardized mean difference

Short messaging service

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Acknowledgements

We would like to acknowledge the contribution of Raymond Daniel who helped with managing citations. The authors also acknowledge Greg Traversy from the Public Health Agency of Canada for his input and direction during project scoping and refinement. Lastly, we acknowledge Fatemeh Yazdi and Nadera Ahmadzai for their support during the conduct of the systematic review.

Funding for this evidence review was provided by the Public Health Agency of Canada and supported all phases of conduct of the evidence review. Staff of the Global Health and Guidelines Division at the Public Health Agency of Canada reviewed and provided input during the protocol and manuscript development but were not involved in study selection or interpretation of the findings. Final decisions were made by the review team. The views expressed herein do not necessarily represent the views of the Government of Canada.

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MH contributed to the conception and design of the work, participated in all aspects of the overview of review and drafted the original version of the manuscript. ABeck performed the study selection, data extraction, quality assessments, certainty of evidence appraisals, the updated overview of review and revisions to the manuscript. PB performed quality assessments, certainty of evidence appraisals and drafted the original version of the manuscript. CH performed data extraction and certainty of evidence appraisals. LE and KP performed study selection and data extraction. BA performed data extraction. NA, MP, MT and FY performed study selection. ABennett and NS performed the updated overview of review and manuscript revisions. NV performed manuscript revisions. BS developed the search strategy and provided text for the manuscript. BH, DManuel, MM, SP, JP, BJS and VW provided methodological and clinical expertise. DM and JL contributed to the conception and design of the work and provided methodological input at all phases. AS contributed to the conception and design of the work, oversaw all aspects of the review, provided methodological expertise at all phases, performed data extraction, quality assessments and certainty of evidence appraisals and drafted the original version of the manuscript.

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Additional file 1. various smoking cessation interventions., additional file 2. preferred reporting items for overview of reviews (prior) checklist., additional file 3. press –peer review assessment of search strategy., additional file 4. database search strategy., additional file 5. grey literature sources., additional file 6. eligibility criteria (pico criteria)., additional file 7. reasons for exclusion at full-text and post-hoc exclusions., additional file 8. overview of reviews data extraction items., additional file 9. forest plots for included analyses., additional file 10. risk of bias figures for included analyses., 13643_2024_2570_moesm11_esm.docx.

Additional file 11. Grading of Recommendations, Assessment, Development and Evaluation (GRADE) Evidence Profile and Summary of Findings (SoF) tables.

Additional file 12. AMSTAR 2 instrument.

Additional file 13. subgroup data for included analyses., additional file 14. tobacco effect judgements., additional file 15. review characteristics., additional file 16. amstar 2 rating of included reviews., additional file 17. included analyses and results., additional file 18. stakeholders’ feedback., rights and permissions.

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Hersi, M., Beck, A., Hamel, C. et al. Effectiveness of smoking cessation interventions among adults: an overview of systematic reviews. Syst Rev 13 , 179 (2024). https://doi.org/10.1186/s13643-024-02570-9

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Panel A shows unadjusted weighted proportions aggregated by quarter (Q). Panel B shows modeled monthly time trends: lines represent modeled weighted prevalence by monthly survey wave (modeled nonlinearly using restricted cubic splines, 5 knots), shaded bands represent SEs, and points represent observed weighted prevalence by quarter. Vertical lines indicate the timing of the start of the e-cigarette, or vaping product, use-associated lung injury (EVALI) outbreak (March 2019), 9 COVID-19 pandemic (March 2020), and the rapid increase in prevalence of disposable vaping among young people in England (June 2021). 14 Corresponding figures excluding don’t know responses are provided in eFigure 1 in Supplement 1 .

a Quarter 4 2014 includes data from November to December only.

Graphs show data by age (A), occupational social grade (B; ABC1 refers to managerial, professional, or intermediate workers, and C2DE refers to skilled manual workers, semiskilled and unskilled manual workers, state pensioners, casual and lowest grade workers, and those who are unemployed with state benefits only), and vaping status (C). Lines represent point estimates from logistic regression allowing an interaction between age and survey wave, modeled nonlinearly using restricted cubic splines (5 knots). Shaded bands represent SEs. Points represent observed weighted prevalence by quarter. From left to right, vertical lines indicate the timing of the start of the e-cigarette, or vaping product, use-associated lung injury outbreak (March 2019), 9 COVID-19 pandemic (March 2020), and the rapid increase in prevalence of disposable vaping among young people in England (June 2021). 14 Figures for trends in the perception of e-cigarettes as equally harmful, more harmful, or don’t know are shown in eFigure 2 in Supplement 1 . Corresponding figures excluding those who responded “don’t know” from the sample are shown in eFigure 3 in Supplement 1 .

eAppendix. Literature Review

eReferences

eTable 1. Harm Perceptions, Aggregated Across Survey Waves, Excluding Don’t Know Responses (Unweighted n=24,088)

eFigure 1. Harm Perceptions of e-Cigarettes Compared With Cigarettes Among Adults Who Smoke in England, November 2014 to June 2023, Excluding Don’t Know Responses (n=24,088)

eTable 2. Changes in Harm Perceptions From the Start to the End of the Study, Excluding Don’t Know Responses

eFigure 2. Trends in Harm Perceptions of e-Cigarettes Compared With Cigarettes Among Adults Who Smoke in England, by Age (A-C), Occupational Social Grade (D-F), and Vaping Status (G-I), November 2014 to June 2023: Equally Harmful, More Harmful, and Don’t Know

eFigure 3. Trends in Harm Perceptions of e-Cigarettes Compared With Cigarettes Among Adults Who Smoke in England, by Age (A-C), Occupational Social Grade (D-F), and Vaping Status (G-I), November 2014 to June 2023, Excluding Don’t Know Responses

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Jackson SE , Tattan-Birch H , East K , Cox S , Shahab L , Brown J. Trends in Harm Perceptions of E-Cigarettes vs Cigarettes Among Adults Who Smoke in England, 2014-2023. JAMA Netw Open. 2024;7(2):e240582. doi:10.1001/jamanetworkopen.2024.0582

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Trends in Harm Perceptions of E-Cigarettes vs Cigarettes Among Adults Who Smoke in England, 2014-2023

• 1 Department of Behavioural Science and Health, University College London, London, United Kingdom
• 2 SPECTRUM Consortium, Edinburgh, United Kingdom
• 3 Department of Addictions, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom

Question   How have harm perceptions of electronic cigarettes (e-cigarettes) compared with combustible cigarettes changed since 2014 among adults who smoke in England?

Findings   This survey study of 28 393 adults who smoke found that harm perceptions of e-cigarettes have worsened substantially over the last decade, such that in 2023, most (57.0%) believed e-cigarettes to be equally (33.7%) or more (23.3%) harmful than cigarettes. The timing of the 2 most notable changes in harm perceptions coincided with the e-cigarette, or vaping product, use-associated lung injury outbreak in 2019 and the recent increase in youth vaping in England since 2021.

Meaning   These findings provide evidence of substantial misperceptions about the harms of vaping compared with smoking and underscore the need to clearly communicate the risks so that adults who smoke can make informed choices about the nicotine products they use.

Importance   Electronic cigarettes (e-cigarettes) are less harmful to users than combustible cigarettes. However, public health and media reporting have often overstated the potential risks of e-cigarettes, and inaccurate perceptions of the harms of vaping relative to smoking are pervasive.

Objective   To examine time trends in harm perceptions of e-cigarettes compared with combustible cigarettes among adults who smoke.

Design, Setting, and Participants   This nationally representative monthly cross-sectional survey study was conducted from November 2014 to June 2023 in England. Participants were adults who currently smoke.

Main Outcomes and Measures   Participants were asked whether they thought e-cigarettes were less harmful, equally harmful, or more harmful than cigarettes, or did not know, with the proportion responding less harmful (vs all other responses) as the primary outcome. Logistic regression was used to test associations between survey wave and participants’ perceptions of the harms of e-cigarettes.

Results   Data were collected from 28 393 adults who smoke (mean [SD] age, 43.5 [17.3] years; 13 253 [46.7%] women). In November 2014, 44.4% (95% CI, 42.0%-46.8%) thought e-cigarettes were less harmful than cigarettes, 30.3% (95% CI, 28.2%-32.6%) thought e-cigarettes were equally harmful, 10.8% (95% CI, 9.4%-12.3%) thought they were more harmful, and 14.5% (95% CI, 12.9%-16.4%) did not know. However, by June 2023, the proportion who thought e-cigarettes were less harmful had decreased by 40% (prevalence ratio, 0.60; 95% CI, 0.55-0.66), and the proportion who thought e-cigarettes were more harmful had more than doubled (prevalence ratio, 2.16; 95% CI, 1.84-2.54). Changes over time were nonlinear: late 2019 saw a sharp decline in the proportion who thought e-cigarettes were less harmful and increases in the proportions who thought they were equally or more harmful. These changes were short-lived, returning to pre-2019 levels by the end of 2020. However, perceptions worsened again from 2021 up to the end of the study period: the proportion who thought e-cigarettes were more harmful increased to a new high, and the proportion who thought e-cigarettes were less harmful decreased to levels comparable to those in late 2019. As a result, in June 2023, the perception that e-cigarettes were equally as harmful as cigarettes was the most commonly held view among adults who smoke (33.7%; 95% CI, 31.4%-36.1%), with roughly similar proportions perceiving e-cigarettes to be less (26.7%; 95% CI, 24.6%-28.9%) and more (23.3%; 95% CI, 21.1%-25.7%) harmful.

Conclusions and Relevance   This survey study of adults who smoke in England found that harm perceptions of e-cigarettes have worsened substantially over the last decade, such that most adults who smoked in 2023 believed e-cigarettes to be at least as harmful as cigarettes. The timing of the 2 most notable changes in harm perceptions coincided with the e-cigarette, or vaping product, use-associated lung injury outbreak in 2019 and the recent increase in youth vaping in England since 2021.

Electronic cigarettes (e-cigarettes) are effective for helping people to stop smoking 1 and are less harmful than combustible cigarettes (referred to hereafter as cigarettes). 2 However, many adults who smoke in England (as in many other countries) believe that e-cigarettes are at least as harmful to health as cigarettes, 2 - 4 which can dissuade adults who smoke from switching to e-cigarettes (and thus reducing their exposure to harmful toxicants). 2 Several factors may have contributed to increased confusion about the harms of e-cigarettes relative to cigarettes over recent years (see the eAppendix in Supplement 1 for a full literature review). Media reporting often has overstated the risks of e-cigarettes, 5 , 6 and evidence suggests that this could exacerbate misperceptions. 2 , 7 There has been comparatively little reporting on the deaths caused by smoking; for example, smoking kills approximately 75 000 people each year in England. 8 Risk messages such as those provided by public health organizations can also change harm perceptions of e-cigarettes. 2 , 7 For example, in 2019, there was an outbreak of acute lung injuries that were primarily attributable to vaping contaminated tetrahydrocannabinol products; yet, before the cause was identified, the Centers for Disease Control and Prevention misattributed this to vaping generally and labeled the disease e-cigarette, or vaping product, use-associated lung injury (EVALI). 9 The following year, COVID-19, a disease that primarily impairs the respiratory system, prompted concerns that e-cigarette use may increase infection risk and disease severity 10 - 12 ; however, there is little evidence this was true. 11 , 13 Several studies documented short-term increases in the harm perceptions of e-cigarettes following the EVALI outbreak. 2 How harm perceptions of e-cigarettes have continued to change beyond 2020, in the context of the COVID-19 pandemic (since March 2020) and the growing concern about youth vaping (use of disposable e-cigarettes among young people in England has grown rapidly since June 2021, 14 leading to calls for a ban on disposable vapes 15 and widespread news coverage stating potential risks to youth), and the extent to which changes differ between key population subgroups, is not known.

It is important to understand whether there have been changes over time in perceptions of the relative harms of different nicotine products among adults who smoke, because this will have implications for accurate messaging and support. Identifying groups with particularly poor or worsening harm perceptions can inform targeted campaigns to address misperceptions, particularly because campaigns are perceived to negatively portray vaping. 16 Using data from a nationally representative survey in England, this study aimed to examine how harm perceptions of e-cigarettes compared with cigarettes have changed over time among adults who currently smoke, and the extent to which changes have differed by age, socioeconomic position, and vaping status (variables known to be associated with smoking, vaping, and harm perceptions of e-cigarettes vs cigarettes). 17 - 20

The study protocol and analysis plan for this survey study were preregistered on Open Science Framework 21 and were followed without amendment. Ethical approval for the Smoking and Alcohol Toolkit Study was granted originally by the University College London ethics committee. The data are collected by Ipsos Mori and are anonymized when received by University College London. All participants provided informed verbal consent. The study conformed to the American Association for Public Opinion Research ( AAPOR ) reporting guidelines for survey research.

Data were drawn from the ongoing Smoking Toolkit Study, a monthly cross-sectional survey of a representative sample of adults in England. 22 The study uses a hybrid of random probability and simple quota sampling to select a new sample of approximately 1700 adults each month. Comparisons with other national surveys and sales data indicate that sociodemographic characteristics, smoking prevalence, and cigarette consumption are nationally representative. 22 , 23

Data were initially collected through face-to-face computer-assisted interviews. However, social distancing restrictions under the COVID-19 pandemic meant that no data were collected in March 2020, and data from April 2020 onward were collected via telephone. The telephone-based data collection uses sampling and weighting approaches similar to the face-to-face interviews, and comparisons of the 2 data collection modalities indicate good comparability. 24 - 26

For the present study, we used data from survey respondents between November 2014 (the first wave to assess harm perceptions of e-cigarettes) and June 2023 (the most recent data available at the time of analysis). We restricted our sample to those aged 18 years or older who reported current smoking (see the Measures section), because the item assessing harm perceptions of e-cigarettes was only asked to those who smoke.

Smoking status was assessed with the question, “Which of the following best applies to you? Please note we are referring to cigarettes and other kinds of tobacco that you set light to and NOT electronic or ‘heat-not-burn’ cigarettes?: (a) I smoke cigarettes (including hand-rolled) every day; (b) I smoke cigarettes (including hand-rolled), but not every day; (c) I do not smoke cigarettes at all, but I do smoke tobacco of some kind (eg, pipe, cigar, or shisha); (d) I have stopped smoking completely in the last year; (e) I stopped smoking completely more than a year ago; (f) I have never been a smoker (ie, smoked for a year or more).” Responses a, b, and c were considered current smoking. Those who responded d, e, or f were excluded from the sample.

Harm perceptions of e-cigarettes was assessed with the question, “Compared to regular cigarettes, do you think electronic cigarettes are more, less, or equally harmful to health?” Response options were “more harmful,” “less harmful,” “equally harmful,” or “don’t know.” We analyzed the proportion responding less harmful (vs all other responses) as our primary outcome, consistent with current evidence that e-cigarettes are less harmful than cigarettes, 2 and the proportions responding equally harmful (vs all other), more harmful (vs all other), and don’t know (vs all other) as secondary outcomes. We conducted sensitivity analyses with don’t know responses excluded.

Age was categorized as 18 to 34 years, 35 to 64 years, and 65 years or older. Occupational social grade was categorized as ABC1 (managerial, professional, or intermediate) and C2DE (skilled manual workers, semiskilled and unskilled manual workers, state pensioners, casual and lowest grade workers, and unemployed with state benefits only).

Vaping status was assessed with a series of questions that ask participants whether they are using an e-cigarette or vaping device to help them stop smoking, cut down the amount smoked, in situations when smoking is not permitted, or for any other reason at all. Those who reported e-cigarette use in response to any of these questions were considered current vapers.

Data were analyzed using R statistical software version 4.2.2 (R Project for Statistical Computing). We excluded participants with missing data on harm perceptions.

The Smoking Toolkit Study uses raking to weight the sample to match the population in England on age, social grade, region, housing tenure, ethnicity, and working status within sex. This profile is determined monthly by combining data from the UK Census, the Office for National Statistics midyear estimates, and the annual National Readership Survey. 22 The following analyses used weighted data.

We used logistic regression to test associations between survey wave and perception of e-cigarettes as (a) less harmful than cigarettes (primary outcome), and (b) equally harmful, (c) more harmful, and (d) don’t know (secondary outcomes). Survey wave was modeled using restricted cubic splines with 5 knots, to allow relationships with time to be flexible and nonlinear.

To explore moderation by age, occupational social grade, and vaping status, we repeated the models including the interaction between the moderator of interest and survey wave, thus allowing time trends to differ across subgroups. Each interaction was tested in a separate model. Two-sided P  < .05 was considered statistically significant.

We used estimates from our models to plot the estimated prevalence of each harm perception over the study period (overall and by moderating variables), alongside unmodeled observed (weighted) data aggregated by quarter (to increase sample size contributing to each data point and reduce noise). We also used our modeled estimates to derive prevalence ratios (PRs) for the change in prevalence across the whole time series (June 2023 vs November 2014) alongside 95% CIs calculated using bootstrapping.

Of 169 433 participants surveyed in eligible waves, 28 393 (16.8%) reported current smoking. There were no missing data on e-cigarette harm perceptions (or age, occupational social grade, or vaping status), leaving a final sample for analysis of 28 393 adults who smoke (mean [SD] age, 43.5 [17.3] years; 13 253 [46.7%] women; 15 415 [54.3%] social grades C2DE; 5879 [20.7%] reported current vaping).

Table 1 shows descriptive data on harm perceptions, aggregated across survey waves (corresponding estimates excluding those who responded don’t know from the sample are shown in eTable 1 in Supplement 1 ). Overall, 35.2% (95% CI, 34.6%-35.8%) of adults who smoke perceived e-cigarettes to be less harmful than cigarettes, 36.7% (95% CI, 36.0%-37.3%) said it was equally harmful, 13.4% (95% CI, 12.9%-13.8%) said it was more harmful, and 14.8% (95% CI, 14.3%-15.2%) did not know. The proportion who thought e-cigarettes were less harmful was higher among those who currently vaped (56.7% [95% CI, 55.4%-58.1%] vs 29.4% [95% CI, 28.8%-30.1%] among those who did not currently vape), those from more advantaged social grades ABC1 (41.9% [95% CI, 41.0%-42.9%] vs 30.7% [95% CI, 29.9%-31.5%] among social grades C2DE), and those aged 35 to 64 years (37.6% [95% CI, 36.7%-38.5%] vs 34.1% [95% CI, 33.1%-35.0%] among those aged 18-34 years and 29.2% [95% CI, 95% CI, 27.7%-30.7%] among those aged ≥65 years). Younger participants (18-34 years) were more likely than middle-aged (35-64 years) and older (≥65 years) participants to perceive e-cigarettes as equally or more harmful than cigarettes, whereas older participants (≥65 years) were more likely to say they did not know. Approximately one-third (34.9% [95% CI, 33.6%-36.2%]) of dual users (who both smoked and vaped) reported perceiving that e-cigarettes were equally or more harmful than cigarettes.

Figure 1 A shows descriptive data on e-cigarette harm perceptions across the study period, aggregated by quarter (corresponding figures excluding don’t know responses are provided in eFigure 1 in Supplement 1 ). Models revealed significant changes in harm perceptions between the start and end of the study period ( Table 2 and Table 3 ) (corresponding estimates excluding those who responded don’t know from the sample are shown in eTable 2 in Supplement 1 ). In November 2014, when e-cigarette harm perceptions were first assessed, the most common perception among adults who smoke was that e-cigarettes were less harmful than cigarettes (44.4%; 95% CI, 42.0%-46.8%), similar to the proportions perceiving e-cigarettes to be equally harmful (30.3%; 95% CI, 28.2%-32.6%) or more harmful (10.8%; 95% CI, 9.4%-12.3%) combined, with 14.5% (95% CI, 12.9%-16.4%) saying they did not know. However, by June 2023, the proportion who thought e-cigarettes were less harmful had decreased by 40% (PR, 0.60; 95% CI, 0.55-0.66) and the proportion who thought they were more harmful had more than doubled (PR, 2.16; 95% CI, 1.84-2.54). Hence, in June 2023, the perception that e-cigarettes were equally as harmful as cigarettes was the most commonly held view among adults who smoke (33.7%; 95% CI, 31.4%-36.1%), with roughly similar proportions perceiving e-cigarettes to be less (26.7%; 95% CI, 24.6%-28.9%) and more (23.3%; 95% CI, 21.1%-25.7%) harmful.

Changes in harm perceptions over time were nonlinear ( Figure 1 B). From November 2014 to July 2019, the proportion of adults who smoke who thought e-cigarettes were less harmful than cigarettes declined steadily to 33.2% (95% CI, 32.0%-34.5%) and the proportion who thought they were equally harmful increased to 42.5% (95% CI, 41.1%-43.8%). The proportions who thought they were more harmful or who did not know were relatively stable up to the end of 2016; the former increased over subsequent years to a high of 14.1% (95% CI, 13.1%-15.1%) in April 2019, and the latter decreased to a low of 8.9% (95% CI, 8.3%-9.7%) in October 2018.

Inspection of the unmodeled data points (ie, observed weighted prevalence by quarter, shown as points in Figure 1 and Figure 2 ) suggests there was then a marked shift in perceptions in late 2019: a sharp decline in the proportion who thought e-cigarettes were less harmful than cigarettes to a low of 25.1% (95% CI, 21.0%-29.3%) in quarter 1 of 2020 and increases in the proportions who thought they were equally or more harmful, reaching highs of 50.6% (95% CI, 45.7%-55.5%) in quarter 1 of 2020 and 19.7% (95% CI, 16.6%-22.9%) in quarter 4 of 2019 ( Figure 1 B). Changes in the proportions who thought e-cigarettes were less or more harmful were short-lived, returning to pre-2019 levels by the end of 2020. However, the proportion who thought e-cigarettes were equally harmful decreased to below 2018 levels and remained lower, offset by an increase in the proportion who did not know how the harms of e-cigarettes compared with cigarettes in quarter 2 of 2020 ( Figure 1 B). From 2021 to the end of the study period in mid-2023, the proportion who thought e-cigarettes were more harmful than cigarettes increased to a new high (surpassing the previous peak in the unmodeled data points in late 2019), the proportion who thought they were less harmful decreased to levels comparable to those in late 2019, the proportion who thought they were equally harmful was stable, and the proportion who did not know declined ( Figure 1 B).

The decline over the study period in the proportion who thought e-cigarettes were less harmful than cigarettes was similar across age groups ( Figure 2 A). The decline in the proportion who thought e-cigarettes were equally harmful since 2019 was most pronounced among the oldest group (≥65 years) and least pronounced among the youngest group (18-34 years; P  for interaction = .001) (eFigure 2A in Supplement 1 ). The increase in the proportion who thought e-cigarettes were more harmful since 2021 was most pronounced among the youngest group and was absent in the oldest group ( P  for interaction = .001) (eFigure 2B in Supplement 1 ).

The decline in the proportion who thought e-cigarettes were less harmful than cigarettes since 2021 was more pronounced among social grades ABC1, with less change observed for C2DE ( P  for interaction = .005) ( Figure 2 B). Over the same period, there was also an increase in the proportion who thought e-cigarettes were equally harmful among social grades ABC1 but not C2DE ( P  for interaction = .003) (eFigure 2D in Supplement 1 ). By the end of the study period, the inequality gap in harm perceptions had closed, such that those from social grades ABC1 had perceptions similar to those from C2DE.

There were similar declines in the proportion who thought e-cigarettes were less harmful by vaping status across the period ( Figure 2 C). Notably, the proportion who believed e-cigarettes were less harmful was consistently lower among those who did not vape, and only 19.0% (95% CI, 17.0%-21.3%) of this group thought this by June 2023. There was an increase in the proportion who thought e-cigarettes were equally harmful since 2021 among those who currently vaped but no change among those who smoked but did not vape (eFigure 2G in Supplement 1 ). As a result, in June 2023, 33.4% (95% CI, 30.7%-36.3%) of participants who smoked but did not vape thought e-cigarettes were equally harmful as cigarettes, 27.7% (95% CI, 24.9%-30.6%) thought they were more harmful, and 19.9% (95% CI, 17.7%-22.3%) were unsure. Corresponding figures excluding those who responded don’t know from the sample are shown in eFigure 3 in Supplement 1 .

This survey study found that among adults who smoke in England, harm perceptions of e-cigarettes compared with cigarettes have worsened considerably over the past decade. In 2014, the most common perception was that e-cigarettes were less harmful than cigarettes. However, by June 2023, the proportion who thought e-cigarettes were less harmful had decreased by 40% and the proportion who thought they were more harmful had more than doubled. Although perceptions were generally more positive among those aged 35 to 64 years, those from more advantaged social grades, and those who currently vaped, deterioration was observed across all subgroups. As a result, only a minority (26.7%) of adults who smoke now think e-cigarettes are less harmful than cigarettes, including only 19.0% of smokers who do not vape, who would most benefit from switching to a reduced harm product. More than one-half (57.0%) of all adults surveyed think e-cigarettes are equally (33.7%) or more (23.3%) harmful than cigarettes. Among those who did not vape, 61.1% overall think e-cigarettes are equally (33.4%) or more (27.7%) harmful than cigarettes, and 19.9% are unsure.

Changes over time were nonlinear. Consistent with previous studies, 2 , 27 , 28 including from the same data set up to 2019, 4 we observed a sharp decline in late 2019 in the proportion who thought e-cigarettes were less harmful than cigarettes and increases in the proportions who thought e-cigarettes were equally or more harmful. This coincided with the timing of the EVALI outbreak, which was at its peak in September 2019. 9 EVALI cases declined to virtually zero by February 2020, at which point the Centers for Disease Control and Prevention stopped publishing updates on case numbers. 9 Likewise, changes in the proportions who thought e-cigarettes were less or more harmful were short-lived, returning to pre-2019 levels by the end of 2020. 27 Interestingly, changes in harm perceptions around the timing of EVALI appeared similar across age groups, despite EVALI predominantly affecting young people 9 and this being highlighted in media coverage at the time. 5

Following EVALI, the COVID-19 pandemic did not coincide with substantial changes in harm perceptions of e-cigarettes, with the only notable change being an increase in don’t know responses. This may be linked to an increase in confusion about public health risks resulting from misinformation transmitted during the pandemic. 29 However, perceptions worsened again from 2021 to the end of the study period. The proportion who thought e-cigarettes were more harmful increased to a new high (surpassing the previous peak in late 2019), and the proportion who thought they were less harmful decreased to levels comparable to those from late 2019. These changes coincided with the timing of concerns about an increase in youth vaping in England 30 since new disposable e-cigarettes have become popular. 14 This trend has been widely reported in the media (with a substantial increase in news reporting of vaping in 2022 and 2023) 31 and is a priority issue for policymakers 32 and practitioners. 15 We observed a clear age gradient in changing harm perceptions since 2021, with the increase in the proportion who thought e-cigarettes were more harmful than cigarettes most pronounced among those younger than 35 years and absent in those older than 65 years. This aligns with the emphasis on risks to young people in reports on youth vaping. 15 It suggests there is a disconnect between young people’s risk perceptions of e-cigarettes and their behavior (ie, that use of e-cigarettes is more common among younger age groups, despite a larger proportion thinking they are at least as harmful as smoking).

The deterioration in evidence-based harm perceptions since 2021 was also much more prominent among those from more advantaged social grades, with little change among less advantaged social grades. Overall, the more advantaged social grades held more positive views of e-cigarettes’ relative harms. However, the decline since 2021 closed the inequality gap, bringing their perceptions in line with the (more negative) views of those from less advantaged social grades. Although reducing inequalities is important, it does not improve public health unless it is achieved by correcting misperceptions in the less advantaged group, rather than worsening in the more advantaged group.

These findings have important implications for public health. Misperceptions about the risks of e-cigarettes compared with cigarettes are a health risk in and of themselves. If people who smoke think vaping is equally or more harmful than smoking, they may be less inclined to try and switch to vaping, leaving them using a more harmful product. 2 In April 2023, the English government announced a national swap to stop campaign, which aims to offer 1 million people a free vaping starter kit with behavioral support, to help them quit smoking. 33 Strategies such as these could be undermined if people who smoke are unwilling to try vaping because of safety concerns. In addition, if people who both smoke and vape (dual users) think the risks are similar, they may not see any benefit of stopping smoking and instead continue both behaviors. Our data suggest that 1 in 2 dual users now think e-cigarettes are equally or more harmful than cigarettes, so there is substantial opportunity to correct misperceptions. Similarly, if young vapers who have never smoked think the risks are similar, they may be equally likely to start smoking as to start vaping. To date, smoking prevalence among young people in England has remained low despite an increase in vaping prevalence, 2 although there are warning signs that the decline in smoking may have leveled off or reversed in recent years. 2 , 34 There is a need to clearly communicate the risks of vaping compared with smoking to ensure this pattern does not change.

This study had several limitations. Only adults who currently smoke were asked about harm perceptions of e-cigarettes, so we were unable to explore changes among nonsmokers or youth. We included all adults who reported current smoking but did not separate noncigarette tobacco (eg, cigars and pipes) users, who may hold different harm perceptions compared with those who smoke cigarettes, because of their small sample size. In addition, findings are unlikely to generalize beyond England; cross-national comparisons could help to understand potential factors contributing to changing vaping perceptions. Although we speculated on the potential causes of the changes in harm perceptions we observed, further research (eg, qualitative) is required to provide deeper insight into the factors that have caused people’s perceptions of e-cigarettes to change and why changes have been different across population subgroups. Further research could explore differences in intersectional subgroups (eg, age by socioeconomic position) to gain more nuanced insights into unequal harm perceptions.

Harm perceptions of e-cigarettes have worsened substantially over the last decade, such that the vast majority of adults who smoke and do not vape in England do not believe e-cigarettes are less harmful than cigarettes. The timing of the most notable changes in harm perceptions coincided with the EVALI outbreak and the recent increase in youth vaping.

Accepted for Publication: January 7, 2024.

Published: February 28, 2024. doi:10.1001/jamanetworkopen.2024.0582

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Jackson SE et al. JAMA Network Open .

Corresponding Author: Sarah E. Jackson, PhD, Department of Behavioural Science and Health, University College London, 1-19 Torrington Pl, London WC1E 7HB, United Kingdom ( [email protected] ).

Author Contributions: Dr Jackson had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Jackson, Tattan-Birch, Cox, Shahab, Brown.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Jackson, Shahab.

Critical review of the manuscript for important intellectual content: Tattan-Birch, East, Cox, Shahab, Brown.

Statistical analysis: Jackson .

Obtained funding: Shahab, Brown.

Supervision: Brown.

Conflict of Interest Disclosures: Dr Shahab reported being a Higher Education Funding Council for England–funded member of staff at University College London; receiving honoraria for talks, an unrestricted research grant, and travel expenses to attend meetings and workshops from Pfizer; receiving an honorarium to sit on advisory panel from Johnson & Johnson; acting as paid reviewer for grant awarding bodies and as a paid consultant for health care companies; and receiving research funding from the government, a community-interested company (National Centre for Smoking Cessation), and other charitable sources outside the submitted work. Dr Brown reported receiving grants from Johnson & Johnson and Pfizer outside the submitted work. No other disclosures were reported.

Funding/Support: Cancer Research UK (PRCRPG-Nov21\100002) funded the Smoking Toolkit Study data collection and the salaries of Drs Jackson, Tattan-Birch, and Cox. Dr East is supported by a fellowship from the Society for the Study of Addiction.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

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Home — Essay Samples — Nursing & Health — Smoking — How smoking can ruin your health

How Smoking Can Ruin Your Health

• Categories: Smoking Tobacco

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Words: 789 |

Published: Jan 15, 2019

Words: 789 | Pages: 2 | 4 min read

Works Cited

• BeTobaccoFree.gov. (n.d.). Health effects of cigarette smoking. U.S. Department of Health and Human Services.
• ISEEK Education. (n.d.). Smoking. University of Minnesota.
• MedlinePlus. (2022, January 25). Smoking and your health. U.S. National Library of Medicine.
• Smokefree. (n.d.). How smoking affects your body. National Health Service. https://www.nhs.uk/smokefree/why-quit/how-smoking-affects-your-body
• American Cancer Society. (2022, March 15). Health risks of smoking tobacco. https://www.cancer.org/cancer/cancer-causes/tobacco-and-cancer/health-risks-of-smoking-tobacco.html
• American Dental Association. (n.d.). Tobacco.
• Centers for Disease Control and Prevention. (2021, December 9). Secondhand smoke facts.
• Higginson, A., & Benowitz, N. L. (2019). Secondhand smoke and nicotine exposure. Medical Clinics, 103(5), 835-846.
• National Cancer Institute. (2022, March 29). Harms of smoking and health benefits of quitting. U.S. Department of Health and Human Services. https://www.cancer.gov/quit-smoking/guide/harms-health-benefits
• U.S. Department of Health and Human Services. (2014). The health consequences of smoking - 50 years of progress: A report of the Surgeon General. Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health.

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Paragraph on Dangers Of Smoking

Students are often asked to write a paragraph on Dangers Of Smoking in their schools. And if you’re also looking for the same, we have created 100-word, 200-word, and 250-word paragraphs on the topic.

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Smoking is very bad for our health. It can make us sick and feel unwell. When people smoke, they breathe in smoke that can hurt their lungs. This can make it hard for them to breathe and run fast. Smoking can also make teeth yellow and cause bad breath. It can hurt our heart, too. Some people who smoke get very sick and can even die. It’s important to stay away from smoke and say no to cigarettes. Always choose to play and eat healthy food instead. This helps us grow strong and stay happy.

Paragraph on Dangers Of Smoking in 200 Words

Smoking is very bad for our health. When we smoke, we breathe in a harmful thing called smoke. This smoke has many dangerous things inside it, like nicotine and tar. These harm our lungs, the part of our body that helps us breathe. If our lungs get sick, we may cough a lot, find it hard to breathe, or even get a very serious disease called lung cancer. Also, smoking can make our heart work harder, which can lead to heart disease. Not only that, but smoking can spoil our teeth and give us bad breath. This is not nice for the people around us. It is important to remember that smoking is not only bad for the people who smoke but also for the people who are around them. This is because when we smoke, we let out smoke into the air, and other people can breathe it in. This is called secondhand smoke, and it is also very harmful. So, for our own health and the health of the people around us, it’s best to stay away from smoking.

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Paragraph on Dangers Of Smoking in 250 Words

Smoking is a harmful habit that can lead to severe health problems. It’s like inviting trouble as it harms almost all parts of your body. When you smoke, you breathe in harmful chemicals which can damage your lungs, leading to diseases like bronchitis and lung cancer. These diseases make it hard for you to breathe and can make you feel sick a lot. Smoking also hurts your heart, making it work too hard. This can cause heart disease and can even lead to a heart attack. It can also stain your teeth yellow and give you bad breath, which nobody likes. Smoking is also bad for your skin. It can cause wrinkles and make you look older than you are. It is also very addictive because cigarettes contain nicotine, a drug that your body can start to need. Once you start smoking, it can be very hard to stop. You can become dependent on cigarettes, spending lots of money on them, and it can control your life. Second-hand smoke from cigarettes is also dangerous. It means the smoke that other people breathe out, which you can breathe in. This can also harm your health and the health of people around you. So, saying no to smoking is like saying yes to a healthy, happy life. It’s important to remember that the dangers of smoking are real and can affect you and the people you care about.

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Yes, the Enrollment Management Industry Is Harming Higher Ed

Financial aid leveraging leaves low-income students and their families with heavy debt loads, Stephen J. Burd writes.

By  Stephen J. Burd

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Harvard Education Press

In an opinion essay they wrote for this publication recently, Robert Massa and Bill Conley gently took issue with my book Lifting the Veil on Enrollment Management: How a Powerful Industry Is Limiting Social Mobility in American Higher Education ( Harvard Education Press ), arguing that my critique of the institutional financial aid strategies that the enrollment management industry promotes “is somewhat overstated.” More cutting was the headline of their column: “Is Enrollment Management Really Ruining Higher Ed?”

It is standard practice in Washington, D.C., public policy debates for supporters of the status quo to portray themselves as realists and reformers as naïve or conspiracy theorists. This approach echoes the infamous attack line that Ronald Reagan leveled at President Carter during the presidential debates of 1980: cocking his head toward Carter and chuckling, he said, “There you go again.”

It is important to say up front that I truly like and admire Robert Massa (I don’t know Bill Conley). By all accounts, he was an exemplary enrollment manager at Dickinson College, where he was dedicated to making the college more racially diverse. As Massa and Conley write, they had the good fortune of working at selective private colleges that were committed to meeting their students’ full financial need. They write that in their experience at such institutions, financial aid leveraging —an enrollment management practice in which colleges determine the precise price points, or tuition discounts, needed to enroll different groups of students, without spending a dollar more than necessary— was “primarily aimed” at just a subset of students with low or no need, and was “typically not used to determine the amount of institutional grants awarded to individual students with need.”

Unfortunately, their experiences aren’t typical. In fact, fewer than two dozen selective private colleges leverage their aid and meet 100 percent of their students’ financial need.

In reality the vast majority of colleges that engage in student aid leveraging do not meet the full financial need of their students. And many, if not most, of these colleges leave low- and lower-middle-income students with substantial amounts of unmet need, requiring these individuals and their families to take on heavy debt loads to enroll.

In an analysis I conducted for the book of institutional financial aid data at 575 selective private and public colleges and universities, I found that these institutions’ use of non-need-based aid skyrocketed from $2 billion annually in 2000 to more than $8 billion by 2020, after adjusting for inflation. Breaking these figures down by sector, I found the following:

• The 307 selective private colleges examined increased the annual amount they spent on non-need-based aid to $4.9 billion, from about $1.4 billion.
• The 268 selective public universities examined increased the yearly amount they spent on non-need-based aid to $3.3 billion, from $931 million.

At the same time that these selective colleges accelerated their spending on non-need-based aid, they left low-income and other financially needy students with larger funding gaps. Between 2000 and 2020, the average amount of financial need these colleges covered of their freshman student aid recipients dropped substantially: from 90 to 85 percent at private colleges and from 74 percent to 65 percent at public universities. A deeper dive into the data revealed that over this time period:

• Nearly two-thirds of the selective public universities examined decreased the amount of financial need they covered by an average of 18 percentage points.
• Nearly three-fifths of the selective private colleges examined decreased the amount of financial need they covered by an average of 11 percentage points.

Rather than pushing colleges to limit their use of financial aid leveraging to a subset of students, the country’s largest enrollment management firms are aggressively marketing financial aid leveraging (also called “optimization”) products that are designed to help colleges use all their aid strategically to pursue the students they most desire: the best applicants, who can help them rise up the rankings, and the wealthiest, who can help them increase their revenues.

EAB, one of the giants of the enrollment management industry, boasts to colleges that its “Financial Aid Optimization program ensures that every dollar you commit to aid is used to further your enrollment and net tuition revenue goals.” Instead of using student aid to meet financial need, the main goal of financial aid leveraging is to boost the institution’s bottom line. But don’t take it from me. Here’s what Nathan Mueller, a leader of EAB’s financial aid optimization team, recently told Higher Ed Dive : “The concept is to award financial aid in a way that results in the maximum total amount of net tuition revenue for the institution.” What this means in practice is that institutional financial aid dollars that used to go to financially needy students are now being used to provide discounts to entice affluent ones to enroll.

Joanne Bresilien learned that lesson the hard way, as the author Beth Zasloff writes in a chapter in my book. Raised by a single mother, who supported her two children on a monthly disability check, Joanne decided that she wanted to attend Ithaca College to pursue her goal of becoming a physical education teacher. While Ithaca provides generous discounts to affluent students, the college left Joanne, a low-income, first-generation student, with a substantial funding gap for her first year that could only be filled by having her mother take out a $14,000 federal Parent PLUS Loan.

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Joanne is not alone. For colleges that leverage a substantial portion of their aid, PLUS loans are easy credit they can offer low-income families who are left with large funding gaps. Unlike federal student loans, which have strict borrowing limits, parents can borrow PLUS loans up to a college’s full cost of attendance (minus the cost of any aid awarded), regardless of their income. To obtain the loans, parents need only pass a lax adverse credit-history check that does not assess whether the borrower will be able to repay the debt. And because colleges are not held accountable if borrowers do default on this debt, the institutions don’t have to worry about how hazardous these loans may be for students’ families. As a 2019 Urban Institute report stated, the PLUS loan program is “a no-strings-attached revenue source for colleges and universities, with the risk shared only by parents and the government,” which loses money if borrowers default.

It would be one thing if selective colleges left students like Joanne with large funding gaps because of limited resources. Joanne believed that was the case at Ithaca until one who day when she ran into an affluent friend outside her dorm who complained about having to go to the financial aid office. “I don’t know why they’re giving me an extra $14,000, and I don’t need it,” her friend said. For Joanne, “hearing this number, the same amount as her gap, felt like a punch to the gut,” Zasloff writes.

The fact that families like Joanne’s need to take on such an extraordinary risk to attend colleges that are showering wealthy students with more money than they know what to do with should raise alarms. Policy makers need to take a good, hard look at the financial aid leveraging products, strategies and algorithms that the giant enrollment firms are marketing to determine whether they are putting low-income and other financially needy students in harm’s way.

Massa and Conley conclude their column by writing that “enrollment management provides an easy target to blame” and suggesting that little would change for low-income students “if enrollment management consulting firms and current practices were banned from college campuses tomorrow.” These longtime enrollment managers have a right to their opinion, but it seems premature to reach that conclusion until we have a much better idea of what these firms are selling.

Stephen J. Burd is a senior writer and editor with the education policy program at New America. He is editor of Lifting the Veil on Enrollment Management: How a Powerful Industry Is Limiting Social Mobility in American Higher Education ( Harvard Education Press, 2024 ).

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How Trump Supercharged Project 2025—Whether He Wanted To or Not

F rom running a business into the ground to doing the same with our country, Donald Trump does a lot of things wrong . But, if we’re being honest, his instincts in marketing are usually pretty darn good. In recent weeks, though, he’s made a colossal marketing mistake.

On July 5, Donald Trump took to his social media platform Truth Social to declare that he “knows nothing” about Project 2025, a 920-page guidebook for a second Trump presidency, put together by right-wing think tank Heritage Foundation. And he tried it again this week. He thought he could distance himself from the backlash to his blueprint. But, Donald Trump claiming to not know Project 2025 would be like Jeffrey Dahmer claiming to be an introvert who has never met people before.

More than simply not being believed, though, Trump did something that he never expected: He supercharged interest in Project 2025. On Jun 24, the pollsters at Navigator Research found Project 2025's favorability underwater by 9-points (10-19%) with most people unaware of the plan altogether. Less than one month later, the favorability had plummeted to negative 32-points (11-43%) after Trump made it a bigger subject of conversation. When people learn about it, they react like they would watching a horror movie: They hate each minute of it but they can’t stop themselves from watching what comes next.

In fact, by July 11, more people were searching for information about Project 2025 than were searching for Taylor Swift or the NFL. People ranging from John Oliver to Taraji P. Henson have brought attention to it. Vice President Harris even referenced it in the announcement that she was running for President last weekend.

Project 2025 outlines how a second Trump administration would take over the government and give the MAGA movement more power than any president has had in the history of the United States The detailed plan meticulously lays out all the freedoms the Trump administration plans to take away from the American people and the threat they pose to working families and seniors, including letting government monitor women’s pregnancies while they pass a national ban on abortion; overturning health care protections for people with pre-existing conditions while removing the $35 cap on the price of insulin; and eliminating the Department of Education, Head Start, clean energy and the National Weather Service.

Read More: Project 2025’s Plan to Eliminate Public Schools Has Already Started

There is real power in having a national conversation about Project 2025. As people hear more about the plan, they shift from opposing it by 13-points to opposing it by 48-points. The biggest growth comes from non-MAGA affiliated Republicans and independents, especially non-college educated women under 55. All of these are key to building an electoral coalition in 2024 and beyond.

There are three main things people need to know when it comes to communicating about Project 2025.

It’s not your typical political BS

Most voters think a “plan” or an “agenda” from a politician is meaningless and largely disconnected from what will really happen. While that is sometimes true, Project 2025 isn’t like that. Twelve years ago, Republicans were caught on defense because they actually passed a budget (the Ryan budget) that would privatize Medicare. For the last two years, they’ve had to defend the actual overturning of Roe v. Wade. It wasn’t theoretical. It was real. People will know that this 920-page meticulous blueprint to takeover government is just as real and as present a danger. 

It confirms people's worst fears about Republicans, especially Trump

People are fearful of what another Trump presidency would mean—the chaos, the criminality, and shredding the Constitution. Americans start with a pre-existing belief that Trump and the MAGA allies are power-hungry, but Project 2025 proves they intended to do it and shows how. For example, they will take away the Department of Justice and replace it with hand-picked loyalists who report to them. It’s clear this is exactly what people featured—them pursuing absolute power. 

It’s mysterious and sinister

If you look at the massive uptick in the online conversation about Project 2025, one theme emerges consistently: curiosity. People see a 920-document written in secret by a bunch of Trump’s agents as mysterious and probably sinister. So they want to read it. They want to understand it. They want to reveal it. It plays into the conspiratorial notion of how people think and the conspiracy-theory attributes that drive many of the algorithms that dominate social media. In fact, as Trump found out starting with his July 5th tweet, the more that his team denies ownership of the plan, the more convinced people are that they own it.

But Democrats can’t just name drop the plan and expect that to evoke its intended impact. We have to frame the plan as the extreme blueprint it is and explain its consequences. We need to tell a common story, not just use a common set of magic words.

Project 2025 is more than a white paper, a policy proposal, or an agenda. It’s an instruction manual for a takeover—eliminating the protections for people and strengthening their ways to control people. We have to treat it as such.

The Trump team made the mistake of writing down their manual, giving everyone a chance to see what the future would look like under their administration. Then, they told everyone not to look at it. Predictably, now everyone wants a peek.

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