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A research report is one big argument about how and why you came up with your conclusions. To make it a convincing argument, a typical guiding structure has developed. In the different chapters, there are distinct issues that need to be addressed to explain to the reader why your conclusions are valid. The governing principle for writing the report is full disclosure: to explain everything and ensure replicability by another researcher.
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Barros, L. O. (2016). The only academic phrasebook you’ll ever need . Createspace Independent Publishing Platform.
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Hunziker, S., Blankenagel, M. (2024). Writing up a Research Report. In: Research Design in Business and Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-42739-9_4
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Chapter 11: Presenting Your Research
Learning Objectives
In this section, we look at how to write an APA-style empirical research report , an article that presents the results of one or more new studies. Recall that the standard sections of an empirical research report provide a kind of outline. Here we consider each of these sections in detail, including what information it contains, how that information is formatted and organized, and tips for writing each section. At the end of this section is a sample APA-style research report that illustrates many of these principles.
Title page and abstract.
An APA-style research report begins with a title page . The title is centred in the upper half of the page, with each important word capitalized. The title should clearly and concisely (in about 12 words or fewer) communicate the primary variables and research questions. This sometimes requires a main title followed by a subtitle that elaborates on the main title, in which case the main title and subtitle are separated by a colon. Here are some titles from recent issues of professional journals published by the American Psychological Association.
Below the title are the authors’ names and, on the next line, their institutional affiliation—the university or other institution where the authors worked when they conducted the research. As we have already seen, the authors are listed in an order that reflects their contribution to the research. When multiple authors have made equal contributions to the research, they often list their names alphabetically or in a randomly determined order.
In some areas of psychology, the titles of many empirical research reports are informal in a way that is perhaps best described as “cute.” They usually take the form of a play on words or a well-known expression that relates to the topic under study. Here are some examples from recent issues of the Journal Psychological Science .
Individual researchers differ quite a bit in their preference for such titles. Some use them regularly, while others never use them. What might be some of the pros and cons of using cute article titles?
For articles that are being submitted for publication, the title page also includes an author note that lists the authors’ full institutional affiliations, any acknowledgments the authors wish to make to agencies that funded the research or to colleagues who commented on it, and contact information for the authors. For student papers that are not being submitted for publication—including theses—author notes are generally not necessary.
The abstract is a summary of the study. It is the second page of the manuscript and is headed with the word Abstract . The first line is not indented. The abstract presents the research question, a summary of the method, the basic results, and the most important conclusions. Because the abstract is usually limited to about 200 words, it can be a challenge to write a good one.
The introduction begins on the third page of the manuscript. The heading at the top of this page is the full title of the manuscript, with each important word capitalized as on the title page. The introduction includes three distinct subsections, although these are typically not identified by separate headings. The opening introduces the research question and explains why it is interesting, the literature review discusses relevant previous research, and the closing restates the research question and comments on the method used to answer it.
The opening , which is usually a paragraph or two in length, introduces the research question and explains why it is interesting. To capture the reader’s attention, researcher Daryl Bem recommends starting with general observations about the topic under study, expressed in ordinary language (not technical jargon)—observations that are about people and their behaviour (not about researchers or their research; Bem, 2003 [1] ). Concrete examples are often very useful here. According to Bem, this would be a poor way to begin a research report:
Festinger’s theory of cognitive dissonance received a great deal of attention during the latter part of the 20th century (p. 191)
The following would be much better:
The individual who holds two beliefs that are inconsistent with one another may feel uncomfortable. For example, the person who knows that he or she enjoys smoking but believes it to be unhealthy may experience discomfort arising from the inconsistency or disharmony between these two thoughts or cognitions. This feeling of discomfort was called cognitive dissonance by social psychologist Leon Festinger (1957), who suggested that individuals will be motivated to remove this dissonance in whatever way they can (p. 191).
After capturing the reader’s attention, the opening should go on to introduce the research question and explain why it is interesting. Will the answer fill a gap in the literature? Will it provide a test of an important theory? Does it have practical implications? Giving readers a clear sense of what the research is about and why they should care about it will motivate them to continue reading the literature review—and will help them make sense of it.
Breaking the Rules
Researcher Larry Jacoby reported several studies showing that a word that people see or hear repeatedly can seem more familiar even when they do not recall the repetitions—and that this tendency is especially pronounced among older adults. He opened his article with the following humourous anecdote:
A friend whose mother is suffering symptoms of Alzheimer’s disease (AD) tells the story of taking her mother to visit a nursing home, preliminary to her mother’s moving there. During an orientation meeting at the nursing home, the rules and regulations were explained, one of which regarded the dining room. The dining room was described as similar to a fine restaurant except that tipping was not required. The absence of tipping was a central theme in the orientation lecture, mentioned frequently to emphasize the quality of care along with the advantages of having paid in advance. At the end of the meeting, the friend’s mother was asked whether she had any questions. She replied that she only had one question: “Should I tip?” (Jacoby, 1999, p. 3)
Although both humour and personal anecdotes are generally discouraged in APA-style writing, this example is a highly effective way to start because it both engages the reader and provides an excellent real-world example of the topic under study.
Immediately after the opening comes the literature review , which describes relevant previous research on the topic and can be anywhere from several paragraphs to several pages in length. However, the literature review is not simply a list of past studies. Instead, it constitutes a kind of argument for why the research question is worth addressing. By the end of the literature review, readers should be convinced that the research question makes sense and that the present study is a logical next step in the ongoing research process.
Like any effective argument, the literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that demonstrate it, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or it might describe one phenomenon, then describe another phenomenon that seems inconsistent with the first one, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally suggest a way to test whether it does, in fact, apply to that situation.
Looking at the literature review in this way emphasizes a few things. First, it is extremely important to start with an outline of the main points that you want to make, organized in the order that you want to make them. The basic structure of your argument, then, should be apparent from the outline itself. Second, it is important to emphasize the structure of your argument in your writing. One way to do this is to begin the literature review by summarizing your argument even before you begin to make it. “In this article, I will describe two apparently contradictory phenomena, present a new theory that has the potential to resolve the apparent contradiction, and finally present a novel hypothesis to test the theory.” Another way is to open each paragraph with a sentence that summarizes the main point of the paragraph and links it to the preceding points. These opening sentences provide the “transitions” that many beginning researchers have difficulty with. Instead of beginning a paragraph by launching into a description of a previous study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:
Another example of this phenomenon comes from the work of Williams (2004).
Williams (2004) offers one explanation of this phenomenon.
An alternative perspective has been provided by Williams (2004).
We used a method based on the one used by Williams (2004).
Finally, remember that your goal is to construct an argument for why your research question is interesting and worth addressing—not necessarily why your favourite answer to it is correct. In other words, your literature review must be balanced. If you want to emphasize the generality of a phenomenon, then of course you should discuss various studies that have demonstrated it. However, if there are other studies that have failed to demonstrate it, you should discuss them too. Or if you are proposing a new theory, then of course you should discuss findings that are consistent with that theory. However, if there are other findings that are inconsistent with it, again, you should discuss them too. It is acceptable to argue that the balance of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in psychology can hope for), but it is not acceptable to ignore contradictory evidence. Besides, a large part of what makes a research question interesting is uncertainty about its answer.
The closing of the introduction—typically the final paragraph or two—usually includes two important elements. The first is a clear statement of the main research question or hypothesis. This statement tends to be more formal and precise than in the opening and is often expressed in terms of operational definitions of the key variables. The second is a brief overview of the method and some comment on its appropriateness. Here, for example, is how Darley and Latané (1968) [2] concluded the introduction to their classic article on the bystander effect:
These considerations lead to the hypothesis that the more bystanders to an emergency, the less likely, or the more slowly, any one bystander will intervene to provide aid. To test this proposition it would be necessary to create a situation in which a realistic “emergency” could plausibly occur. Each subject should also be blocked from communicating with others to prevent his getting information about their behaviour during the emergency. Finally, the experimental situation should allow for the assessment of the speed and frequency of the subjects’ reaction to the emergency. The experiment reported below attempted to fulfill these conditions. (p. 378)
Thus the introduction leads smoothly into the next major section of the article—the method section.
The method section is where you describe how you conducted your study. An important principle for writing a method section is that it should be clear and detailed enough that other researchers could replicate the study by following your “recipe.” This means that it must describe all the important elements of the study—basic demographic characteristics of the participants, how they were recruited, whether they were randomly assigned, how the variables were manipulated or measured, how counterbalancing was accomplished, and so on. At the same time, it should avoid irrelevant details such as the fact that the study was conducted in Classroom 37B of the Industrial Technology Building or that the questionnaire was double-sided and completed using pencils.
The method section begins immediately after the introduction ends with the heading “Method” (not “Methods”) centred on the page. Immediately after this is the subheading “Participants,” left justified and in italics. The participants subsection indicates how many participants there were, the number of women and men, some indication of their age, other demographics that may be relevant to the study, and how they were recruited, including any incentives given for participation.
After the participants section, the structure can vary a bit. Figure 11.1 shows three common approaches. In the first, the participants section is followed by a design and procedure subsection, which describes the rest of the method. This works well for methods that are relatively simple and can be described adequately in a few paragraphs. In the second approach, the participants section is followed by separate design and procedure subsections. This works well when both the design and the procedure are relatively complicated and each requires multiple paragraphs.
What is the difference between design and procedure? The design of a study is its overall structure. What were the independent and dependent variables? Was the independent variable manipulated, and if so, was it manipulated between or within subjects? How were the variables operationally defined? The procedure is how the study was carried out. It often works well to describe the procedure in terms of what the participants did rather than what the researchers did. For example, the participants gave their informed consent, read a set of instructions, completed a block of four practice trials, completed a block of 20 test trials, completed two questionnaires, and were debriefed and excused.
In the third basic way to organize a method section, the participants subsection is followed by a materials subsection before the design and procedure subsections. This works well when there are complicated materials to describe. This might mean multiple questionnaires, written vignettes that participants read and respond to, perceptual stimuli, and so on. The heading of this subsection can be modified to reflect its content. Instead of “Materials,” it can be “Questionnaires,” “Stimuli,” and so on.
The results section is where you present the main results of the study, including the results of the statistical analyses. Although it does not include the raw data—individual participants’ responses or scores—researchers should save their raw data and make them available to other researchers who request them. Several journals now encourage the open sharing of raw data online.
Although there are no standard subsections, it is still important for the results section to be logically organized. Typically it begins with certain preliminary issues. One is whether any participants or responses were excluded from the analyses and why. The rationale for excluding data should be described clearly so that other researchers can decide whether it is appropriate. A second preliminary issue is how multiple responses were combined to produce the primary variables in the analyses. For example, if participants rated the attractiveness of 20 stimulus people, you might have to explain that you began by computing the mean attractiveness rating for each participant. Or if they recalled as many items as they could from study list of 20 words, did you count the number correctly recalled, compute the percentage correctly recalled, or perhaps compute the number correct minus the number incorrect? A third preliminary issue is the reliability of the measures. This is where you would present test-retest correlations, Cronbach’s α, or other statistics to show that the measures are consistent across time and across items. A final preliminary issue is whether the manipulation was successful. This is where you would report the results of any manipulation checks.
The results section should then tackle the primary research questions, one at a time. Again, there should be a clear organization. One approach would be to answer the most general questions and then proceed to answer more specific ones. Another would be to answer the main question first and then to answer secondary ones. Regardless, Bem (2003) [3] suggests the following basic structure for discussing each new result:
Notice that only Step 3 necessarily involves numbers. The rest of the steps involve presenting the research question and the answer to it in words. In fact, the basic results should be clear even to a reader who skips over the numbers.
The discussion is the last major section of the research report. Discussions usually consist of some combination of the following elements:
The discussion typically begins with a summary of the study that provides a clear answer to the research question. In a short report with a single study, this might require no more than a sentence. In a longer report with multiple studies, it might require a paragraph or even two. The summary is often followed by a discussion of the theoretical implications of the research. Do the results provide support for any existing theories? If not, how can they be explained? Although you do not have to provide a definitive explanation or detailed theory for your results, you at least need to outline one or more possible explanations. In applied research—and often in basic research—there is also some discussion of the practical implications of the research. How can the results be used, and by whom, to accomplish some real-world goal?
The theoretical and practical implications are often followed by a discussion of the study’s limitations. Perhaps there are problems with its internal or external validity. Perhaps the manipulation was not very effective or the measures not very reliable. Perhaps there is some evidence that participants did not fully understand their task or that they were suspicious of the intent of the researchers. Now is the time to discuss these issues and how they might have affected the results. But do not overdo it. All studies have limitations, and most readers will understand that a different sample or different measures might have produced different results. Unless there is good reason to think they would have, however, there is no reason to mention these routine issues. Instead, pick two or three limitations that seem like they could have influenced the results, explain how they could have influenced the results, and suggest ways to deal with them.
Most discussions end with some suggestions for future research. If the study did not satisfactorily answer the original research question, what will it take to do so? What new research questions has the study raised? This part of the discussion, however, is not just a list of new questions. It is a discussion of two or three of the most important unresolved issues. This means identifying and clarifying each question, suggesting some alternative answers, and even suggesting ways they could be studied.
Finally, some researchers are quite good at ending their articles with a sweeping or thought-provoking conclusion. Darley and Latané (1968) [4] , for example, ended their article on the bystander effect by discussing the idea that whether people help others may depend more on the situation than on their personalities. Their final sentence is, “If people understand the situational forces that can make them hesitate to intervene, they may better overcome them” (p. 383). However, this kind of ending can be difficult to pull off. It can sound overreaching or just banal and end up detracting from the overall impact of the article. It is often better simply to end when you have made your final point (although you should avoid ending on a limitation).
The references section begins on a new page with the heading “References” centred at the top of the page. All references cited in the text are then listed in the format presented earlier. They are listed alphabetically by the last name of the first author. If two sources have the same first author, they are listed alphabetically by the last name of the second author. If all the authors are the same, then they are listed chronologically by the year of publication. Everything in the reference list is double-spaced both within and between references.
Appendices, tables, and figures come after the references. An appendix is appropriate for supplemental material that would interrupt the flow of the research report if it were presented within any of the major sections. An appendix could be used to present lists of stimulus words, questionnaire items, detailed descriptions of special equipment or unusual statistical analyses, or references to the studies that are included in a meta-analysis. Each appendix begins on a new page. If there is only one, the heading is “Appendix,” centred at the top of the page. If there is more than one, the headings are “Appendix A,” “Appendix B,” and so on, and they appear in the order they were first mentioned in the text of the report.
After any appendices come tables and then figures. Tables and figures are both used to present results. Figures can also be used to illustrate theories (e.g., in the form of a flowchart), display stimuli, outline procedures, and present many other kinds of information. Each table and figure appears on its own page. Tables are numbered in the order that they are first mentioned in the text (“Table 1,” “Table 2,” and so on). Figures are numbered the same way (“Figure 1,” “Figure 2,” and so on). A brief explanatory title, with the important words capitalized, appears above each table. Each figure is given a brief explanatory caption, where (aside from proper nouns or names) only the first word of each sentence is capitalized. More details on preparing APA-style tables and figures are presented later in the book.
Figures 11.2, 11.3, 11.4, and 11.5 show some sample pages from an APA-style empirical research report originally written by undergraduate student Tomoe Suyama at California State University, Fresno. The main purpose of these figures is to illustrate the basic organization and formatting of an APA-style empirical research report, although many high-level and low-level style conventions can be seen here too.
Key Takeaways
Figure 11.1 long description: Table showing three ways of organizing an APA-style method section.
In the simple method, there are two subheadings: “Participants” (which might begin “The participants were…”) and “Design and procedure” (which might begin “There were three conditions…”).
In the typical method, there are three subheadings: “Participants” (“The participants were…”), “Design” (“There were three conditions…”), and “Procedure” (“Participants viewed each stimulus on the computer screen…”).
In the complex method, there are four subheadings: “Participants” (“The participants were…”), “Materials” (“The stimuli were…”), “Design” (“There were three conditions…”), and “Procedure” (“Participants viewed each stimulus on the computer screen…”). [Return to Figure 11.1]
A type of research article which describes one or more new empirical studies conducted by the authors.
The page at the beginning of an APA-style research report containing the title of the article, the authors’ names, and their institutional affiliation.
A summary of a research study.
The third page of a manuscript containing the research question, the literature review, and comments about how to answer the research question.
An introduction to the research question and explanation for why this question is interesting.
A description of relevant previous research on the topic being discusses and an argument for why the research is worth addressing.
The end of the introduction, where the research question is reiterated and the method is commented upon.
The section of a research report where the method used to conduct the study is described.
The main results of the study, including the results from statistical analyses, are presented in a research article.
Section of a research report that summarizes the study's results and interprets them by referring back to the study's theoretical background.
Part of a research report which contains supplemental material.
Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.
The primary objective of a research report is to communicate the results of a research study to a wider audience, including other researchers, policymakers, and practitioners. Research reports play a crucial role in advancing knowledge and understanding in various fields of study. They provide a detailed and accurate account of the research process and outcomes, and they serve as a reference source for future research.
The structure of a research report typically follows a standard format. The introduction sets the context and background for the research and outlines the research questions or objectives. The literature review provides an overview of existing research on the topic and identifies gaps in the literature that the research aims to address. The methodology section describes the research design and methods used to collect and analyze data. The results section presents the findings of the study, often using tables, charts, and graphs. The discussion section interprets and contextualizes the findings and compares them to previous research. Finally, the conclusion summarizes the key findings and implications of the research, highlighting any limitations and recommendations for future research.
A research report can take various forms, depending on the field of study and the research question. For example, it may be a quantitative or qualitative report, a literature review report, or a case study report. A research report should be clear, concise, and objective regardless of the form.
Research reports are essential for various reasons. First, they provide a detailed and accurate account of the research process and outcomes, which can inform policy and practice in various settings. Second, research reports contribute to the development of knowledge and understanding in a particular field or discipline. They provide a reference source for other researchers in the field, and they can inspire new research questions and directions. Finally, research reports are a crucial component of academic and professional careers. They demonstrate research skills, expertise, and contributions to the field.
Writing a research report can be a challenging task, but it is a crucial component of academic and professional research. An excellent research report should be clear, concise, and well-structured, with a focus on presenting accurate and objective findings. Here are some tips for writing an excellent research report:
A research report is a vital tool in disseminating research results to academic, professional, and public audiences. It provides a detailed analysis of the research problem, research questions, methodology, findings, and conclusions. Research reports are crucial in advancing knowledge and understanding in various fields of study, informing policy and practice, and contributing to academic and professional careers.
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Scientific researches are studies that should be systematically planned before performing them. In this review, classification and description of scientific studies, planning stage randomisation and bias are explained.
Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new information is revealed with respect to diagnosis, treatment and reliability of applications. The purpose of this review is to provide information about the definition, classification and methodology of scientific research.
Before beginning the scientific research, the researcher should determine the subject, do planning and specify the methodology. In the Declaration of Helsinki, it is stated that ‘the primary purpose of medical researches on volunteers is to understand the reasons, development and effects of diseases and develop protective, diagnostic and therapeutic interventions (method, operation and therapies). Even the best proven interventions should be evaluated continuously by investigations with regard to reliability, effectiveness, efficiency, accessibility and quality’ ( 1 ).
The questions, methods of response to questions and difficulties in scientific research may vary, but the design and structure are generally the same ( 2 ).
Scientific research can be classified in several ways. Classification can be made according to the data collection techniques based on causality, relationship with time and the medium through which they are applied.
Another method is to classify the research according to its descriptive or analytical features. This review is written according to this classification method.
Moreover, some studies may be experimental. After the researcher intervenes, the researcher waits for the result, observes and obtains data. Experimental studies are, more often, in the form of clinical trials or laboratory animal trials ( 2 ).
Analytical observational research can be classified as cohort, case-control and cross-sectional studies.
Firstly, the participants are controlled with regard to the disease under investigation. Patients are excluded from the study. Healthy participants are evaluated with regard to the exposure to the effect. Then, the group (cohort) is followed-up for a sufficient period of time with respect to the occurrence of disease, and the progress of disease is studied. The risk of the healthy participants getting sick is considered an incident. In cohort studies, the risk of disease between the groups exposed and not exposed to the effect is calculated and rated. This rate is called relative risk. Relative risk indicates the strength of exposure to the effect on the disease.
Cohort research may be observational and experimental. The follow-up of patients prospectively is called a prospective cohort study . The results are obtained after the research starts. The researcher’s following-up of cohort subjects from a certain point towards the past is called a retrospective cohort study . Prospective cohort studies are more valuable than retrospective cohort studies: this is because in the former, the researcher observes and records the data. The researcher plans the study before the research and determines what data will be used. On the other hand, in retrospective studies, the research is made on recorded data: no new data can be added.
In fact, retrospective and prospective studies are not observational. They determine the relationship between the date on which the researcher has begun the study and the disease development period. The most critical disadvantage of this type of research is that if the follow-up period is long, participants may leave the study at their own behest or due to physical conditions. Cohort studies that begin after exposure and before disease development are called ambidirectional studies . Public healthcare studies generally fall within this group, e.g. lung cancer development in smokers.
Cross-sectional studies are advantageous since they can be concluded relatively quickly. It may be difficult to obtain a reliable result from such studies for rare diseases ( 2 ).
Cross-sectional studies are characterised by timing. In such studies, the exposure and result are simultaneously evaluated. While cross-sectional studies are restrictedly used in studies involving anaesthesia (since the process of exposure is limited), they can be used in studies conducted in intensive care units.
Clinical studies are conducted by a responsible researcher, generally a physician. In the research team, there may be other healthcare staff besides physicians. Clinical studies may be financed by healthcare institutes, drug companies, academic medical centres, volunteer groups, physicians, healthcare service providers and other individuals. They may be conducted in several places including hospitals, universities, physicians’ offices and community clinics based on the researcher’s requirements. The participants are made aware of the duration of the study before their inclusion. Clinical studies should include the evaluation of recommendations (drug, device and surgical) for the treatment of a disease, syndrome or a comparison of one or more applications; finding different ways for recognition of a disease or case and prevention of their recurrence ( 7 ).
In this review, clinical research is explained in more detail since it is the most valuable study in scientific research.
Clinical research starts with forming a hypothesis. A hypothesis can be defined as a claim put forward about the value of a population parameter based on sampling. There are two types of hypotheses in statistics.
The planning phase comes after the determination of a hypothesis. A clinical research plan is called a protocol . In a protocol, the reasons for research, number and qualities of participants, tests to be applied, study duration and what information to be gathered from the participants should be found and conformity criteria should be developed.
The selection of participant groups to be included in the study is important. Inclusion and exclusion criteria of the study for the participants should be determined. Inclusion criteria should be defined in the form of demographic characteristics (age, gender, etc.) of the participant group and the exclusion criteria as the diseases that may influence the study, age ranges, cases involving pregnancy and lactation, continuously used drugs and participants’ cooperation.
The next stage is methodology. Methodology can be grouped under subheadings, namely, the calculation of number of subjects, blinding (masking), randomisation, selection of operation to be applied, use of placebo and criteria for stopping and changing the treatment.
The entire source from which the data are obtained is called a universe or population . A small group selected from a certain universe based on certain rules and which is accepted to highly represent the universe from which it is selected is called a sample and the characteristics of the population from which the data are collected are called variables. If data is collected from the entire population, such an instance is called a parameter . Conducting a study on the sample rather than the entire population is easier and less costly. Many factors influence the determination of the sample size. Firstly, the type of variable should be determined. Variables are classified as categorical (qualitative, non-numerical) or numerical (quantitative). Individuals in categorical variables are classified according to their characteristics. Categorical variables are indicated as nominal and ordinal (ordered). In nominal variables, the application of a category depends on the researcher’s preference. For instance, a female participant can be considered first and then the male participant, or vice versa. An ordinal (ordered) variable is ordered from small to large or vice versa (e.g. ordering obese patients based on their weights-from the lightest to the heaviest or vice versa). A categorical variable may have more than one characteristic: such variables are called binary or dichotomous (e.g. a participant may be both female and obese).
If the variable has numerical (quantitative) characteristics and these characteristics cannot be categorised, then it is called a numerical variable. Numerical variables are either discrete or continuous. For example, the number of operations with spinal anaesthesia represents a discrete variable. The haemoglobin value or height represents a continuous variable.
Statistical analyses that need to be employed depend on the type of variable. The determination of variables is necessary for selecting the statistical method as well as software in SPSS. While categorical variables are presented as numbers and percentages, numerical variables are represented using measures such as mean and standard deviation. It may be necessary to use mean in categorising some cases such as the following: even though the variable is categorical (qualitative, non-numerical) when Visual Analogue Scale (VAS) is used (since a numerical value is obtained), it is classified as a numerical variable: such variables are averaged.
Clinical research is carried out on the sample and generalised to the population. Accordingly, the number of samples should be correctly determined. Different sample size formulas are used on the basis of the statistical method to be used. When the sample size increases, error probability decreases. The sample size is calculated based on the primary hypothesis. The determination of a sample size before beginning the research specifies the power of the study. Power analysis enables the acquisition of realistic results in the research, and it is used for comparing two or more clinical research methods.
Because of the difference in the formulas used in calculating power analysis and number of samples for clinical research, it facilitates the use of computer programs for making calculations.
It is necessary to know certain parameters in order to calculate the number of samples by power analysis.
Two types of errors can be made while accepting or rejecting H 0 hypothesis in a hypothesis test. Type-I error (α) level is the probability of finding a difference at the end of the research when there is no difference between the two applications. In other words, it is the rejection of the hypothesis when H 0 is actually correct and it is known as α error or p value. For instance, when the size is determined, type-I error level is accepted as 0.05 or 0.01.
Another error that can be made during a hypothesis test is a type-II error. It is the acceptance of a wrongly hypothesised H 0 hypothesis. In fact, it is the probability of failing to find a difference when there is a difference between the two applications. The power of a test is the ability of that test to find a difference that actually exists. Therefore, it is related to the type-II error level.
Since the type-II error risk is expressed as β, the power of the test is defined as 1–β. When a type-II error is 0.20, the power of the test is 0.80. Type-I (α) and type-II (β) errors can be intentional. The reason to intentionally make such an error is the necessity to look at the events from the opposite perspective.
ES is defined as the state in which statistical difference also has clinically significance: ES≥0.5 is desirable. The difference between groups is the absolute difference between the groups compared in clinical research.
The allocation ratio of groups is effective in determining the number of samples. If the number of samples is desired to be determined at the lowest level, the rate should be kept as 1/1.
The direction of hypothesis in clinical research may be one-sided or two-sided. While one-sided hypotheses hypothesis test differences in the direction of size, two-sided hypotheses hypothesis test differences without direction. The power of the test in two-sided hypotheses is lower than one-sided hypotheses.
After these four variables are determined, they are entered in the appropriate computer program and the number of samples is calculated. Statistical packaged software programs such as Statistica, NCSS and G-Power may be used for power analysis and calculating the number of samples. When the samples size is calculated, if there is a decrease in α, difference between groups, ES and number of samples, then the standard deviation increases and power decreases. The power in two-sided hypothesis is lower. It is ethically appropriate to consider the determination of sample size, particularly in animal experiments, at the beginning of the study. The phase of the study is also important in the determination of number of subjects to be included in drug studies. Usually, phase-I studies are used to determine the safety profile of a drug or product, and they are generally conducted on a few healthy volunteers. If no unacceptable toxicity is detected during phase-I studies, phase-II studies may be carried out. Phase-II studies are proof-of-concept studies conducted on a larger number (100–500) of volunteer patients. When the effectiveness of the drug or product is evident in phase-II studies, phase-III studies can be initiated. These are randomised, double-blinded, placebo or standard treatment-controlled studies. Volunteer patients are periodically followed-up with respect to the effectiveness and side effects of the drug. It can generally last 1–4 years and is valuable during licensing and releasing the drug to the general market. Then, phase-IV studies begin in which long-term safety is investigated (indication, dose, mode of application, safety, effectiveness, etc.) on thousands of volunteer patients.
When the methodology of clinical research is prepared, precautions should be taken to prevent taking sides. For this reason, techniques such as randomisation and blinding (masking) are used. Comparative studies are the most ideal ones in clinical research.
A case in which the treatments applied to participants of clinical research should be kept unknown is called the blinding method . If the participant does not know what it receives, it is called a single-blind study; if even the researcher does not know, it is called a double-blind study. When there is a probability of knowing which drug is given in the order of application, when uninformed staff administers the drug, it is called in-house blinding. In case the study drug is known in its pharmaceutical form, a double-dummy blinding test is conducted. Intravenous drug is given to one group and a placebo tablet is given to the comparison group; then, the placebo tablet is given to the group that received the intravenous drug and intravenous drug in addition to placebo tablet is given to the comparison group. In this manner, each group receives both the intravenous and tablet forms of the drug. In case a third party interested in the study is involved and it also does not know about the drug (along with the statistician), it is called third-party blinding.
The selection of patients for the study groups should be random. Randomisation methods are used for such selection, which prevent conscious or unconscious manipulations in the selection of patients ( 8 ).
No factor pertaining to the patient should provide preference of one treatment to the other during randomisation. This characteristic is the most important difference separating randomised clinical studies from prospective and synchronous studies with experimental groups. Randomisation strengthens the study design and enables the determination of reliable scientific knowledge ( 2 ).
The easiest method is simple randomisation, e.g. determination of the type of anaesthesia to be administered to a patient by tossing a coin. In this method, when the number of samples is kept high, a balanced distribution is created. When the number of samples is low, there will be an imbalance between the groups. In this case, stratification and blocking have to be added to randomisation. Stratification is the classification of patients one or more times according to prognostic features determined by the researcher and blocking is the selection of a certain number of patients for each stratification process. The number of stratification processes should be determined at the beginning of the study.
As the number of stratification processes increases, performing the study and balancing the groups become difficult. For this reason, stratification characteristics and limitations should be effectively determined at the beginning of the study. It is not mandatory for the stratifications to have equal intervals. Despite all the precautions, an imbalance might occur between the groups before beginning the research. In such circumstances, post-stratification or restandardisation may be conducted according to the prognostic factors.
The main characteristic of applying blinding (masking) and randomisation is the prevention of bias. Therefore, it is worthwhile to comprehensively examine bias at this stage.
While conducting clinical research, errors can be introduced voluntarily or involuntarily at a number of stages, such as design, population selection, calculating the number of samples, non-compliance with study protocol, data entry and selection of statistical method. Bias is taking sides of individuals in line with their own decisions, views and ideological preferences ( 9 ). In order for an error to lead to bias, it has to be a systematic error. Systematic errors in controlled studies generally cause the results of one group to move in a different direction as compared to the other. It has to be understood that scientific research is generally prone to errors. However, random errors (or, in other words, ‘the luck factor’-in which bias is unintended-do not lead to bias ( 10 ).
Another issue, which is different from bias, is chicanery. It is defined as voluntarily changing the interventions, results and data of patients in an unethical manner or copying data from other studies. Comparatively, bias may not be done consciously.
In case unexpected results or outliers are found while the study is analysed, if possible, such data should be re-included into the study since the complete exclusion of data from a study endangers its reliability. In such a case, evaluation needs to be made with and without outliers. It is insignificant if no difference is found. However, if there is a difference, the results with outliers are re-evaluated. If there is no error, then the outlier is included in the study (as the outlier may be a result). It should be noted that re-evaluation of data in anaesthesiology is not possible.
Statistical evaluation methods should be determined at the design stage so as not to encounter unexpected results in clinical research. The data should be evaluated before the end of the study and without entering into details in research that are time-consuming and involve several samples. This is called an interim analysis . The date of interim analysis should be determined at the beginning of the study. The purpose of making interim analysis is to prevent unnecessary cost and effort since it may be necessary to conclude the research after the interim analysis, e.g. studies in which there is no possibility to validate the hypothesis at the end or the occurrence of different side effects of the drug to be used. The accuracy of the hypothesis and number of samples are compared. Statistical significance levels in interim analysis are very important. If the data level is significant, the hypothesis is validated even if the result turns out to be insignificant after the date of the analysis.
Another important point to be considered is the necessity to conclude the participants’ treatment within the period specified in the study protocol. When the result of the study is achieved earlier and unexpected situations develop, the treatment is concluded earlier. Moreover, the participant may quit the study at its own behest, may die or unpredictable situations (e.g. pregnancy) may develop. The participant can also quit the study whenever it wants, even if the study has not ended ( 7 ).
In case the results of a study are contrary to already known or expected results, the expected quality level of the study suggesting the contradiction may be higher than the studies supporting what is known in that subject. This type of bias is called confirmation bias. The presence of well-known mechanisms and logical inference from them may create problems in the evaluation of data. This is called plausibility bias.
Another type of bias is expectation bias. If a result different from the known results has been achieved and it is against the editor’s will, it can be challenged. Bias may be introduced during the publication of studies, such as publishing only positive results, selection of study results in a way to support a view or prevention of their publication. Some editors may only publish research that extols only the positive results or results that they desire.
Bias may be introduced for advertisement or economic reasons. Economic pressure may be applied on the editor, particularly in the cases of studies involving drugs and new medical devices. This is called commercial bias.
In recent years, before beginning a study, it has been recommended to record it on the Web site www.clinicaltrials.gov for the purpose of facilitating systematic interpretation and analysis in scientific research, informing other researchers, preventing bias, provision of writing in a standard format, enhancing contribution of research results to the general literature and enabling early intervention of an institution for support. This Web site is a service of the US National Institutes of Health.
The last stage in the methodology of clinical studies is the selection of intervention to be conducted. Placebo use assumes an important place in interventions. In Latin, placebo means ‘I will be fine’. In medical literature, it refers to substances that are not curative, do not have active ingredients and have various pharmaceutical forms. Although placebos do not have active drug characteristic, they have shown effective analgesic characteristics, particularly in algology applications; further, its use prevents bias in comparative studies. If a placebo has a positive impact on a participant, it is called the placebo effect ; on the contrary, if it has a negative impact, it is called the nocebo effect . Another type of therapy that can be used in clinical research is sham application. Although a researcher does not cure the patient, the researcher may compare those who receive therapy and undergo sham. It has been seen that sham therapies also exhibit a placebo effect. In particular, sham therapies are used in acupuncture applications ( 11 ). While placebo is a substance, sham is a type of clinical application.
Ethically, the patient has to receive appropriate therapy. For this reason, if its use prevents effective treatment, it causes great problem with regard to patient health and legalities.
Before medical research is conducted with human subjects, predictable risks, drawbacks and benefits must be evaluated for individuals or groups participating in the study. Precautions must be taken for reducing the risk to a minimum level. The risks during the study should be followed, evaluated and recorded by the researcher ( 1 ).
After the methodology for a clinical study is determined, dealing with the ‘Ethics Committee’ forms the next stage. The purpose of the ethics committee is to protect the rights, safety and well-being of volunteers taking part in the clinical research, considering the scientific method and concerns of society. The ethics committee examines the studies presented in time, comprehensively and independently, with regard to ethics and science; in line with the Declaration of Helsinki and following national and international standards concerning ‘Good Clinical Practice’. The method to be followed in the formation of the ethics committee should be developed without any kind of prejudice and to examine the applications with regard to ethics and science within the framework of the ethics committee, Regulation on Clinical Trials and Good Clinical Practice ( www.iku.com ). The necessary documents to be presented to the ethics committee are research protocol, volunteer consent form, budget contract, Declaration of Helsinki, curriculum vitae of researchers, similar or explanatory literature samples, supporting institution approval certificate and patient follow-up form.
Only one sister/brother, mother, father, son/daughter and wife/husband can take charge in the same ethics committee. A rector, vice rector, dean, deputy dean, provincial healthcare director and chief physician cannot be members of the ethics committee.
Members of the ethics committee can work as researchers or coordinators in clinical research. However, during research meetings in which members of the ethics committee are researchers or coordinators, they must leave the session and they cannot sign-off on decisions. If the number of members in the ethics committee for a particular research is so high that it is impossible to take a decision, the clinical research is presented to another ethics committee in the same province. If there is no ethics committee in the same province, an ethics committee in the closest settlement is found.
Thereafter, researchers need to inform the participants using an informed consent form. This form should explain the content of clinical study, potential benefits of the study, alternatives and risks (if any). It should be easy, comprehensible, conforming to spelling rules and written in plain language understandable by the participant.
This form assists the participants in taking a decision regarding participation in the study. It should aim to protect the participants. The participant should be included in the study only after it signs the informed consent form; the participant can quit the study whenever required, even when the study has not ended ( 7 ).
Peer-review: Externally peer-reviewed.
Author Contributions: Concept - C.Ö.Ç., A.D.; Design - C.Ö.Ç.; Supervision - A.D.; Resource - C.Ö.Ç., A.D.; Materials - C.Ö.Ç., A.D.; Analysis and/or Interpretation - C.Ö.Ç., A.D.; Literature Search - C.Ö.Ç.; Writing Manuscript - C.Ö.Ç.; Critical Review - A.D.; Other - C.Ö.Ç., A.D.
Conflict of Interest: No conflict of interest was declared by the authors.
Financial Disclosure: The authors declared that this study has received no financial support.
The title summarizes the main idea or ideas of your study. A good title contains the fewest possible words needed to adequately describe the content and/or purpose of your research paper.
The title is the part of a paper that is read the most, and it is usually read first . It is, therefore, the most important element that defines the research study. With this in mind, avoid the following when creating a title:
Appiah, Kingsley Richard et al. “Structural Organisation of Research Article Titles: A Comparative Study of Titles of Business, Gynaecology and Law.” Advances in Language and Literary Studies 10 (2019); Hartley James. “To Attract or to Inform: What are Titles for?” Journal of Technical Writing and Communication 35 (2005): 203-213; Jaakkola, Maarit. “Journalistic Writing and Style.” In Oxford Research Encyclopedia of Communication . Jon F. Nussbaum, editor. (New York: Oxford University Press, 2018): https://oxfordre.com/communication.
The following parameters can be used to help you formulate a suitable research paper title:
The initial aim of a title is to capture the reader’s attention and to highlight the research problem under investigation.
Create a Working Title Typically, the final title you submit to your professor is created after the research is complete so that the title accurately captures what has been done . The working title should be developed early in the research process because it can help anchor the focus of the study in much the same way the research problem does. Referring back to the working title can help you reorient yourself back to the main purpose of the study if you find yourself drifting off on a tangent while writing. The Final Title Effective titles in research papers have several characteristics that reflect general principles of academic writing.
The Subtitle Subtitles are frequently used in social sciences research papers because it helps the reader understand the scope of the study in relation to how it was designed to address the research problem. Think about what type of subtitle listed below reflects the overall approach to your study and whether you believe a subtitle is needed to emphasize the investigative parameters of your research.
1. Explains or provides additional context , e.g., "Linguistic Ethnography and the Study of Welfare Institutions as a Flow of Social Practices: The Case of Residential Child Care Institutions as Paradoxical Institutions." [Palomares, Manuel and David Poveda. Text & Talk: An Interdisciplinary Journal of Language, Discourse and Communication Studies 30 (January 2010): 193-212]
2. Adds substance to a literary, provocative, or imaginative title or quote , e.g., "Listen to What I Say, Not How I Vote": Congressional Support for the President in Washington and at Home." [Grose, Christian R. and Keesha M. Middlemass. Social Science Quarterly 91 (March 2010): 143-167]
3. Qualifies the geographic scope of the research , e.g., "The Geopolitics of the Eastern Border of the European Union: The Case of Romania-Moldova-Ukraine." [Marcu, Silvia. Geopolitics 14 (August 2009): 409-432]
4. Qualifies the temporal scope of the research , e.g., "A Comparison of the Progressive Era and the Depression Years: Societal Influences on Predictions of the Future of the Library, 1895-1940." [Grossman, Hal B. Libraries & the Cultural Record 46 (2011): 102-128]
5. Focuses on investigating the ideas, theories, or work of a particular individual , e.g., "A Deliberative Conception of Politics: How Francesco Saverio Merlino Related Anarchy and Democracy." [La Torre, Massimo. Sociologia del Diritto 28 (January 2001): 75 - 98]
6. Identifies the methodology used , e.g. "Student Activism of the 1960s Revisited: A Multivariate Analysis Research Note." [Aron, William S. Social Forces 52 (March 1974): 408-414]
7. Defines the overarching technique for analyzing the research problem , e.g., "Explaining Territorial Change in Federal Democracies: A Comparative Historical Institutionalist Approach." [ Tillin, Louise. Political Studies 63 (August 2015): 626-641.
With these examples in mind, think about what type of subtitle reflects the overall approach to your study. This will help the reader understand the scope of the study in relation to how it was designed to address the research problem.
Anstey, A. “Writing Style: What's in a Title?” British Journal of Dermatology 170 (May 2014): 1003-1004; Balch, Tucker. How to Compose a Title for Your Research Paper. Augmented Trader blog. School of Interactive Computing, Georgia Tech University; Bavdekar, Sandeep B. “Formulating the Right Title for a Research Article.” Journal of Association of Physicians of India 64 (February 2016); Choosing the Proper Research Paper Titles. AplusReports.com, 2007-2012; Eva, Kevin W. “Titles, Abstracts, and Authors.” In How to Write a Paper . George M. Hall, editor. 5th edition. (Oxford: John Wiley and Sons, 2013), pp. 33-41; Hartley James. “To Attract or to Inform: What are Titles for?” Journal of Technical Writing and Communication 35 (2005): 203-213; General Format. The Writing Lab and The OWL. Purdue University; Kerkut G.A. “Choosing a Title for a Paper.” Comparative Biochemistry and Physiology Part A: Physiology 74 (1983): 1; “Tempting Titles.” In Stylish Academic Writing . Helen Sword, editor. (Cambridge, MA: Harvard University Press, 2012), pp. 63-75; Nundy, Samiran, et al. “How to Choose a Title?” In How to Practice Academic Medicine and Publish from Developing Countries? A Practical Guide . Edited by Samiran Nundy, Atul Kakar, and Zulfiqar A. Bhutta. (Springer Singapore, 2022), pp. 185-192.
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This report examines key changes in the economic status of the American middle class from 1970 to 2023 and its demographic attributes in 2022. The historical analysis is based on U.S. Census Bureau data from the Annual Social and Economic Supplements (ASEC) of the Current Population Survey (CPS). The demographic analysis is based on data from the American Community Survey (ACS). The data is sourced from IPUMS CPS and IPUMS USA , respectively.
The CPS, a survey of about 60,000 households, is the U.S. government’s official source for monthly estimates of unemployment . The CPS ASEC, conducted in March each year, is the official source of U.S. government estimates of income and poverty . Our analysis of CPS data starts with the 1971 CPS ASEC, which records the incomes of households in 1970. It is also the first year for which data on race and ethnicity is available. The latest available CPS ASEC file is for 2023, which reports on household incomes in 2022.
The public-use version of the ACS is a 1% sample of the U.S. population, or more than 3 million people. This allows for a detailed study of the demographic characteristics of the middle class, including its status in U.S. metropolitan areas. But ACS data is available only from 2005 onward and is less suitable for long-term historical analyses. The latest available ACS data is for 2022.
Middle-income households are defined as those with an income that is two-thirds to double that of the U.S. median household income, after incomes have been adjusted for household size. Lower-income households have incomes less than two-thirds of the median, and upper-income households have incomes that are more than double the median. When using American Community Survey (ACS) data, incomes are also adjusted for cost of living in the areas in which households are located.
Estimates of household income are scaled to reflect a household size of three and expressed in 2023 dollars. In the Current Population Survey (CPS), household income refers to the calendar year prior to the survey year. Thus, the income data in the report refers to the 1970-2022 period, and the share of Americans in each income tier from the CPS refers to the 1971-2023 period.
The demographic attributes of Americans living in lower-, middle- or upper-income tiers are derived from ACS data. Except as noted, estimates pertain to the U.S. household population, excluding people living in group quarters.
The terms middle class and middle income are used interchangeably in this report.
White, Black, Asian, American Indian or Alaska Native, and Native Hawaiian or Pacific Islander include people who identified with a single major racial group and who are not Hispanic. Multiracial includes people who identified with more than one major racial group and are not Hispanic. Hispanics are of any race.
U.S. born refers to individuals who are U.S. citizens at birth, including people born in the 50 U.S. states, the District of Columbia, Puerto Rico or other U.S. territories, as well as those born elsewhere to at least one parent who is a U.S. citizen. The terms foreign born and immigrant are used interchangeably in this report. They refer to people who are not U.S. citizens at birth.
Occupations describe the broad kinds of work people do on their job. For example, health care occupations include doctors, nurses, pharmacists and others who are directly engaged in the provision of health care. Industries describe the broad type of products companies produce. Each industry encompasses a variety of occupations. For example, the health care and social assistance industry provides services that are produced by a combination of doctors, managers, technology and administrative staff, food preparation workers, and workers in other occupations.
The share of Americans who are in the middle class is smaller than it used to be. In 1971, 61% of Americans lived in middle-class households. By 2023, the share had fallen to 51%, according to a new Pew Research Center analysis of government data.
As a result, Americans are more apart than before financially. From 1971 to 2023, the share of Americans who live in lower-income households increased from 27% to 30%, and the share in upper-income households increased from 11% to 19%.
Notably, the increase in the share who are upper income was greater than the increase in the share who are lower income. In that sense, these changes are also a sign of economic progress overall.
But the middle class has fallen behind on two key counts. The growth in income for the middle class since 1970 has not kept pace with the growth in income for the upper-income tier. And the share of total U.S. household income held by the middle class has plunged.
Moreover, many groups still lag in their presence in the middle- and upper-income tiers. For instance, American Indians or Alaska Natives, Black and Hispanic Americans, and people who are not married are more likely than average to be in the lower-income tier. Several metro areas in the U.S. Southwest also have high shares of residents who are in the lower-income tier, after adjusting for differences in cost of living across areas.
Our report focuses on the current state of the American middle class. First, we examine changes in the financial well-being of the middle class and other income tiers since 1970. This is based on data from the Annual Social and Economic Supplements (ASEC) of the Current Population Survey (CPS), conducted from 1971 to 2023.
Then, we report on the attributes of people who were more or less likely to be middle class in 2022. Our focus is on their race and ethnicity , age , gender, marital and veteran status , place of birth , ancestry , education , occupation , industry , and metropolitan area of residence . These estimates are derived from American Community Survey (ACS) data and differ slightly from the CPS-based estimates. In part, that is because incomes can be adjusted for the local area cost of living only with the ACS data. (Refer to the methodology for details on these two data sources.)
This analysis and an accompanying report on the Asian American middle class are part of a series on the status of America’s racial and ethnic groups in the U.S. middle class and other income tiers. Forthcoming analyses will focus on White, Black, Hispanic, American Indian or Alaska Native, Native Hawaiian or Pacific Islander and multiracial Americans, including subgroups within these populations. These reports are, in part, updates of previous work by the Center . But they offer much greater detail on the demographic attributes of the American middle class.
Following are some key facts about the state of the American middle class:
In our analysis, “middle-income” Americans are those living in households with an annual income that is two-thirds to double the national median household income. The income it takes to be middle income varies by household size, with smaller households requiring less to support the same lifestyle as larger households. It also varies by the local cost of living, with households in a more expensive area, such as Honolulu, needing a higher income than those in a less expensive area, such as Wichita, Kansas.
We don’t always know the area in which a household is located. In our two data sources – the Current Population Survey, Annual Social and Economic Supplement (CPS ASEC) and the American Community Survey (ACS) – only the latter provides that information, specifically the metropolitan area of a household. Thus, we aren’t able to adjust for the local cost of living when using the CPS to track changes in the status of the middle class over time. But we do adjust for the metropolitan area cost of living when using the ACS to determine the demographic attributes of the middle class in 2022.
In the 2023 CPS ASEC data , which reports income for 2022, middle-income households with three people have incomes ranging from about $61,000 to $183,000 annually. “Lower-income” households have incomes less than $61,000, and “upper-income” households have incomes greater than $183,000.
In the 2022 ACS data , middle-income households with three people have incomes ranging from about $62,000 to $187,000 annually, with incomes also adjusted for the local area cost of living. (Incomes are expressed in 2023 dollars.)
The boundaries of the income tiers also vary across years as the national median income changes.
The terms “middle income” and “middle class” are used interchangeably in this report for the sake of exposition. But being middle class can refer to more than just income , be it education level, type of profession, economic security, home ownership or social and political values. Class also could simply be a matter of self-identification .
Households in all income tiers had much higher incomes in 2022 than in 1970, after adjusting for inflation. But the gains for middle- and lower-income households were less than the gains for upper-income households .
The median income of middle-class households increased from about $66,400 in 1970 to $106,100 in 2022, or 60%. Over this period, the median income of upper-income households increased 78%, from about $144,100 to $256,900. (Incomes are scaled to a three-person household and expressed in 2023 dollars.)
The median income of lower-income households grew more slowly than that of other households, increasing from about $22,800 in 1970 to $35,300 in 2022, or 55%.
Consequently, there is now a larger gap between the incomes of upper-income households and other households. In 2022, the median income of upper-income households was 7.3 times that of lower-income households, up from 6.3 in 1970. It was 2.4 times the median income of middle-income households in 2022, up from 2.2 in 1970.
The share of total U.S. household income held by the middle class has fallen almost without fail in each decade since 1970 . In that year, middle-income households accounted for 62% of the aggregate income of all U.S. households, about the same as the share of people who lived in middle-class households.
By 2022, the middle-class share in overall household income had fallen to 43%, less than the share of the population in middle-class households (51%). Not only do a smaller share of people live in the middle class today, the incomes of middle-class households have also not risen as quickly as the incomes of upper-income households.
Over the same period, the share of total U.S. household income held by upper-income households increased from 29% in 1970 to 48% in 2022. In part, this is because of the increase in the share of people who are in the upper-income tier.
The share of overall income held by lower-income households edged down from 10% in 1970 to 8% in 2022. This happened even though the share of people living in lower-income households increased over this period.
The share of people in the U.S. middle class varied from 46% to 55% across racial and ethnic groups in 2022. Black and Hispanic Americans, Native Hawaiians or Pacific Islanders, and American Indians or Alaska Natives were more likely than others to be in lower-income households .
In 2022, 39% to 47% of Americans in these four groups lived in lower-income households. In contrast, only 24% of White and Asian Americans and 31% of multiracial Americans were in the lower-income tier.
At the other end of the economic spectrum, 27% of Asian and 21% of White Americans lived in upper-income households in 2022, compared with about 10% or less of Black and Hispanic Americans, Native Hawaiians or Pacific Islanders, and American Indians or Alaska Natives.
Not surprisingly, lower-income status is correlated with the likelihood of living in poverty. According to the Census Bureau , the poverty rate among Black (17.1%) and Hispanic (16.9%) Americans and American Indians or Alaska Natives (25%) was greater than the rate among White and Asian Americans (8.6% for each). (The Census Bureau did not report the poverty rate for Native Hawaiians or Pacific Islanders.)
Children and adults 65 and older were more likely to live in lower-income households in 2022. Adults in the peak of their working years – ages 30 to 64 – were more likely to be upper income. In 2022, 38% of children (including teens) and 35% of adults 65 and older were lower income, compared with 26% of adults ages 30 to 44 and 23% of adults 45 to 64.
The share of people living in upper-income households ranged from 13% among children and young adults (up to age 29) to 24% among those 45 to 64. In each age group, about half or a little more were middle class in 2022.
Men were slightly more likely than women to live in middle-income households in 2022 , 53% vs. 51%. Their share in upper-income households (18%) was also somewhat greater than the share of women (16%) in upper-income households.
Marriage appears to boost the economic status of Americans. Among those who were married in 2022, eight-in-ten lived either in middle-income households (56%) or upper-income households (24%). In contrast, only about six-in-ten of those who were separated, divorced, widowed or never married were either middle class or upper income, while 37% lived in lower-income households.
Veterans were more likely than nonveterans to be middle income in 2022, 57% vs. 53%. Conversely, a higher share of nonveterans (29%) than veterans (24%) lived in lower-income households.
Immigrants – about 14% of the U.S. population in 2022 – were less likely than the U.S. born to be in the middle class and more likely to live in lower-income households. In 2022, more than a third of immigrants (36%) lived in lower-income households, compared with 29% of the U.S. born. Immigrants also trailed the U.S. born in the shares who were in the middle class, 48% vs. 53%.
There are large gaps in the economic status of American residents by their region of birth. Among people born in Asia, Europe or Oceania, 25% lived in upper-income households in 2022. People from these regions represented 7% of the U.S. population.
By comparison, only 14% of people born in Africa or South America and 6% of those born in Central America and the Caribbean were in the upper-income tier in 2022. Together they accounted for 8% of the U.S. population.
The likelihood of being in the middle class or the upper-income tier varies considerably with the ancestry of Americans. In 2022, Americans reporting South Asian ancestry were about as likely to be upper income (38%) as they were to be middle income (42%). Only 20% of Americans of South Asian origin lived in lower-income households. South Asians accounted for about 2% of the U.S. population of known origin groups in 2022.
At least with respect to the share who were lower income, this was about matched by those with Soviet, Eastern European, other Asian or Western European origins. These groups represented the majority (54%) of the population of Americans whose ancestry was known in 2022.
On the other hand, only 7% of Americans with Central and South American or other Hispanic ancestry were in the upper-income tier, and 44% were lower income. The economic statuses of Americans with Caribbean, sub-Saharan African or North American ancestry were not very different from this.
Education matters for moving into the middle class and beyond, and so do jobs. Among Americans ages 25 and older in 2022, 52% of those with a bachelor’s degree or higher level of education lived in middle-class households and another 35% lived in upper-income households.
In sharp contrast, 42% of Americans who did not graduate from high school were in the middle class, and only 5% were in the upper-income tier. Further, only 12% of college graduates were lower income, compared with 54% of those who did not complete high school.
Not surprisingly, having a job is strongly linked to movement from the lower-income tier to the middle- and upper-income tiers. Among employed American workers ages 16 and older, 58% were in the middle-income tier in 2022 and 23% were in the upper-income tier. Only 19% of employed workers were lower income, compared with 49% of unemployed Americans.
In some occupations, about nine-in-ten U.S. workers are either in the middle class or in the upper-income tier, but in some other occupations almost four-in-ten workers are lower income. More than a third (36% to 39%) of workers in computer, science and engineering, management, and business and finance occupations lived in upper-income households in 2022. About half or more were in the middle class.
But many workers – about one-third or more – in construction, transportation, food preparation and serving, and personal care and other services were in the lower-income tier in 2022.
About six-in-ten workers or more in education; protective and building maintenance services; office and administrative support; the armed forces; and maintenance, repair and production were in the middle class.
Depending on the industrial sector, anywhere from half to two-thirds of U.S. workers were in the middle class, and the share who are upper income or lower income varied greatly.
About a third of workers in the finance, insurance and real estate, information, and professional services sectors were in the upper-income tier in 2022. Nearly nine-in-ten workers (87%) in public administration – largely filling legislative functions and providing federal, state or local government services – were either in the middle class or the upper-income tier.
But nearly four-in-ten workers (38%) in accommodation and food services were lower income in 2022, along with three-in-ten workers in the retail trade and other services sectors.
The share of Americans who are in the middle class or in the upper- or lower-income tier differs across U.S. metropolitan areas. But a pattern emerges when it comes to which metro areas have the highest shares of people living in lower-, middle- or upper-income households. (We first adjust household incomes for differences in the cost of living across areas.)
The 10 metropolitan areas with the greatest shares of middle-income residents are small to midsize in population and are located mostly in the northern half of the U.S. About six-in-ten residents in these metro areas were in the middle class.
Several of these areas are in the so-called Rust Belt , namely, Wausau and Oshkosh-Neenah, both in Wisconsin; Grand Rapids-Wyoming, Michigan; and Lancaster, Pennsylvania. Two others – Dover and Olympia-Tumwater – include state capitals (Delaware and Washington, respectively).
In four of these areas – Bismarck, North Dakota, Ogden-Clearfield, Utah, Lancaster and Wausau – the share of residents in the upper-income tier ranged from 18% to 20%, about on par with the share nationally.
The 10 U.S. metropolitan areas with the highest shares of residents in the upper-income tier are mostly large, coastal communities. Topping the list is San Jose-Sunnyvale-Santa Clara, California, a technology-driven economy, in which 40% of the population lived in upper-income households in 2022. Other tech-focused areas on this list include San Francisco-Oakland-Hayward; Seattle-Tacoma-Bellevue; and Raleigh, North Carolina.
Bridgeport-Stamford-Norwalk, Connecticut, is a financial hub. Several areas, including Washington, D.C.-Arlington-Alexandria and Boston-Cambridge-Newton, are home to major universities, leading research facilities and the government sector.
Notably, many of these metro areas also have sizable lower-income populations. For instance, about a quarter of the populations in Bridgeport-Stamford-Norwalk; Trenton, New Jersey; Boston-Cambridge-Newton; and Santa Cruz-Watsonville, California, were in the lower-income tier in 2022.
Most of the 10 U.S. metropolitan areas with the highest shares of residents in the lower-income tier are in the Southwest, either on the southern border of Texas or in California’s Central Valley. The shares of people living in lower-income residents were largely similar across these areas, ranging from about 45% to 50%.
About 40% to 50% of residents in these metro areas were in the middle class, and only about one-in-ten or fewer lived in upper-income households.
Compared with the nation overall, the lower-income metro areas in Texas and California have disproportionately large Hispanic populations. The two metro areas in Louisiana – Monroe and Shreveport-Bossier City – have disproportionately large Black populations.
Note: For details on how this analysis was conducted, refer to the methodology .
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What would you do if you had a copy of yourself? A digital doppelgänger, identical to you in every way, in an accurate digital rendering of your home, workplace, neighborhood, or city? Even better: What if the digital version of you—your digital twin—was impervious to injury, pain, or embarrassment? The mind boggles at the possibilities. Suffice it to say, you’d probably be able to make decisions for yourself with a lot more certainty of the outcome.
Kimberly Borden is a senior partner in McKinsey’s Chicago office. Anna Herlt is a senior partner in the Munich office. Tomás Lajous , Kayvaun Rowshankish , and Rodney W. Zemmel are senior partners in the New York office.
In business, this heightened degree of certainty is extremely valuable—and emerging digital twins may help deliver it.
Put simply, a digital twin is a virtual replica of a physical object, person, or process that can be used to simulate its behavior to better understand how it works in real life. Digital twins are linked to real data sources from the environment, which means that the twin updates in real time to reflect the original version. Digital twins also comprise a layer of behavioral insights and visualizations derived from data. When interconnected within one system, digital twins can form what’s known as an enterprise metaverse : a digital and often immersive environment that replicates and connects every aspect of an organization to optimize simulations, scenario planning, and decision making .
There are a few different types of digital twins. First, there’s a product twin, which is a representation of a product . This digital twin can include products at various stages of the life cycle, from initial concept design and engineering through to full functionality—meaning you get live, real-time data on a product as if it’s in service. One great example of a product twin is something you probably already have in your pocket: Google Maps is a digital twin of the Earth’s surface. It links real-time data on traffic to help optimize your commute.
Other types of twins include production plant twins, which represent an entire manufacturing facility, or procurement and supply chain twins, also called network twins. And finally, infrastructure twins represent physical infrastructure such as a highway, a building, or even a stadium.
Digital twins have the potential to deliver more agile and resilient operations. And their potential isn’t lost on CEOs: McKinsey research indicates that 70 percent of C-suite technology executives at large enterprises are already exploring and investing in digital twins.
Read on to learn more about the value of digital twins and how to put them to use.
Learn more about McKinsey Digital and McKinsey’s Operations Practice .
One of the areas where digital twins can bring the most value is the reduction in time to market. Digital twins can allow for rapid iterations and optimizations of product designs—far faster than physically testing every single prototype. What’s more, digital twins can result in significant improvements in product quality. By simulating the product throughout the manufacturing process, it’s possible to identify flaws in the design much earlier. (“The companies that harness this first,” says McKinsey senior adviser Will Roper, referring to digital-manufacturing twins, “will really shake up the markets they’re in.”) And finally, by mirroring a product in service, it’s possible to create a single source of truth for how the design is functioning, allowing for real-time adjustment or redesign.
McKinsey has seen organizations post revenue increases of as much as 10 percent by developing digital twins of their customers, allowing those customers to fully interact and immerse themselves within a company’s product. Daimler, for example, has developed customer twins that allow customers to “test drive” a vehicle without ever getting behind the wheel.
Product digital twins can be particularly helpful in improving sustainability efforts. These digital twins can help organizations reduce the material used in a product’s design, as well as improve the traceability of a product to reduce environmental waste. Consumer electronics manufacturers have made significant improvements to sustainability by using digital twins, reducing scrap waste by roughly 20 percent .
Learn more about McKinsey’s Operations Practice .
A key element an organization needs for implementing digital twins is digital maturity . This essentially means data: a high-quality data infrastructure that delivers reliable data from both testing and live environments, as well as the talent needed to build and maintain that infrastructure.
But that doesn’t have to mean that organizations need a complex or dynamic environment to benefit from a digital twin. Some companies are seeing success twinning products as simple as toothbrushes to gain real-time customer feedback. Then, once the initial use case is established, organizations can add more layers of information and real-time feedback to further improve the twin.
Building and scaling a digital twin requires a three-step approach:
Companies can start their journey to an enterprise metaverse with one digital twin, modeled after one data product. A data product delivers a high-quality, ready-to-use data set that people across an organization can easily access and apply. It should be a single, reusable source of truth, enhanced over time, that can serve as the basis for future use cases. Eventually, a first digital twin can evolve based on learnings from behavioral data, ultimately providing increasingly powerful predictive capabilities.
From there, an organization can create multiple interconnected digital twins to simulate the complex relationships between different entities. This can generate richer behavior insights for even more sophisticated use cases—and greater value. For example, an organization might connect a digital twin of its customers with retail stores, inventory, sales, and customer process flows. In doing this, the organization could carry out the following:
Finally, an organization with a healthy digital-twin network can layer on additional technologies required to create an enterprise metaverse. A retailer could, for instance, connect the digital twin of its retail store to digital twins of its warehouses, supply chain, call center, and more until every part of the organization has been replicated.
Interest in digital twins, combined with rapidly advancing supportive technologies, is spurring market estimates for digital-twin investments of more than $48 billion by 2026 . We’re already seeing some advanced implementations:
Learn more about McKinsey Digital and McKinsey’s Operations Practice , and explore digital-operations-related job opportunities if you’re interested in working at McKinsey.
Articles referenced:
Related articles.
The so-called “creator economy” has mushroomed and is expected to grow even more in the coming years, according to Goldman Sachs Research.
As the ecosystem grows, the total addressable market of the creator economy could roughly double in size over the next five years to $480 billion by 2027 from $250 billion today, Sheridan writes. That growth is roughly in line with the team’s estimates for growth in global digital advertising spend over that period. The analysts expect spending on influencer marketing and platform payouts fueled by the monetization of short-form video platforms via advertising to be the primary growth drivers of the creator economy.
Goldman Sachs Research expects the 50 million global creators to grow at a 10-20% compound annual growth rate during the next five years. Creators earn income primarily through direct branding deals to pitch products as an influencer; via a share of advertising revenues with the host platform; and through subscriptions, donations and other forms of direct payment from followers. Brand deals are the main source of revenue at about 70%, according to survey data.
Only about 4% of global creators are deemed professionals, meaning they pull in more than $100,000 a year. Goldman Sachs Research expects their share of the creator universe to stay steady even as the overall ecosystem expands.
Which companies will benefit the most from the ongoing growth of the creator economy? The platforms that are best positioned to attract both influential creators and a larger share of the total spending are those that will offer multiple forms of monetization, according to Goldman Sachs Research. But the analysts also cite six key enablers for creating a “flywheel effect” in which small gains build on each other over time and create further growth momentum:
1. Scale: a large, global user base with diversified interests
2. Capital: access to large pools of capital to fund monetization, either through a diversified revenue base and/or as part of a larger parent company
3. Strong AI-powered recommendation engines: for surfacing relevant content and matching creators with interested users
4. Effective monetization tools: a variety of product offerings/payout structures for creators to diversify their income streams
5. Robust data and analytics: for providing transparency on engagement, retention, conversion and other metrics
6. E-commerce options: the ability to shop is integrated into the core user experience
At least at this point, the report points to the large incumbent platforms as being in the driver’s seat. Goldman Sachs Research sees more creators moving to these platforms as competition heats up for their content and audiences, particularly as macroeconomic uncertainty impacts brand spending and as rising interest rates pressure funding for emerging platforms. “As a result, we expect some element of a ‘flight to quality’ whereby creators will prioritize platforms with stability, scale and monetization potential,” Sheridan writes.
This article is being provided for educational purposes only. The information contained in this article does not constitute a recommendation from any Goldman Sachs entity to the recipient, and Goldman Sachs is not providing any financial, economic, legal, investment, accounting, or tax advice through this article or to its recipient. Neither Goldman Sachs nor any of its affiliates makes any representation or warranty, express or implied, as to the accuracy or completeness of the statements or any information contained in this article and any liability therefore (including in respect of direct, indirect, or consequential loss or damage) is expressly disclaimed.
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Premo97 is waiting for your help., ai-generated answer.
Explanation:
a detailed and careful study of something to find out more information about it
किसी विषय में या पर अनुसंधान या शोधकार्य (किसी विषय के ज्ञान में वृद्धि के लिए उसका विस्तृत और सुविचारित अध्ययन)
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Research reports are recorded data prepared by researchers or statisticians after analyzing the information gathered by conducting organized research, typically in the form of surveys or qualitative methods. A research report is a reliable source to recount details about a conducted research. It is most often considered to be a true testimony ...
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A research report is normally organized into three broad sections. First, an introduction provides a brief background on the topic and introduces the reader to your perspective. The second section is the body of the report, which should include the research findings and supporting evidence.
Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new ...
A research report is a publication that reports on the findings of a research project or alternatively scientific observations on or about a subject. The introductory part of research report should not only contain purpose of the study, statement of the problem, hypothesis and operational definition of the concepts, but should also contain a ...
What is the best definition of a research report? A. Expository writing that seems to persuade readers B. An essay that explores similarities and differences between topics C. A piece of writing that reflects personal experience D. A piece of writing that explores a topic by gathering and analyzing information
The Subtitle Subtitles are frequently used in social sciences research papers because it helps the reader understand the scope of the study in relation to how it was designed to address the research problem. Think about what type of subtitle listed below reflects the overall approach to your study and whether you believe a subtitle is needed to emphasize the investigative parameters of your ...
Research is the process to acquire knowledge about something, to also know facts about the matter.
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The median income of middle-class households increased from about $66,400 in 1970 to $106,100 in 2022, or 60%. Over this period, the median income of upper-income households increased 78%, from about $144,100 to $256,900. (Incomes are scaled to a three-person household and expressed in 2023 dollars.)
The new report says that some health effects of Long COVID, including chronic fatigue and post-exertional malaise, cognitive impairment (sometimes referred to as "brain fog"), and autonomic dysfunction, can impair an individual's ability to work or attend school for six months to two years or more after COVID-19 infection.
Put simply, a digital twin is a virtual replica of a physical object, person, or process that can be used to simulate its behavior to better understand how it works in real life. Digital twins are linked to real data sources from the environment, which means that the twin updates in real time to reflect the original version.
Goldman Sachs Research expects the 50 million global creators to grow at a 10-20% compound annual growth rate during the next five years. Creators earn income primarily through direct branding deals to pitch products as an influencer; via a share of advertising revenues with the host platform; and through subscriptions, donations and other forms of direct payment from followers.
the investigation into and study of materials and sources in order to establish facts and reach new conclusions
you are writing a five-paragraph research paper. You find articles on ur topic in academic journals. You copy and paste the most interesting parts of the article into your research paper without putting those parts in quotations or giving biblio graphical information, but you do list the articles in ur own works cited at the end of the paper. which best explains the scenario?
Explanation: a detailed and careful study of something to find out more information about it. किसी विषय में या पर अनुसंधान या शोधकार्य (किसी विषय के ज्ञान में वृद्धि के लिए उसका विस्तृत और सुविचारित अध्ययन)