research paper about mobile phones

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• 29 May 2023

Episode 27: Our mobile world: How the cell phone is changing science and research

• Subhra Priyadarshini

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A researcher documenting ant colonies. Credit: Subhra Priyadarshini

Does the mobile phone have a place in the lab?

The smartphone is a great example of technology leapfrog in countries like India, where a vast majority of phone users never had a landline. The increasing penetration of affordable mobile phones in developing countries is now making it possible for scientists to conduct meaningful and timely research, in the lab, field or while working from home.

Nature India's 'Our mobile world' podcast series will look at the many ways in which the smartphone has changed India’s science-society dynamics and the way researchers work. We will look at themes ranging from smartphones as enablers of science and research in India, to digital health, digital illiteracy, research around mobile phone e-waste, the gender digital divide and innovations in healthcare, medicine, agriculture and governance. We've chosen stories predominantly from India but also have examples from other counties in the global south.

Host: Subhra Priyadarshini, production and script: Aroma Warsi, sound editing: Prince George.

doi: https://doi.org/10.1038/d44151-023-00061-9

(Lightly edited for readability)

Speakers : Subhajit Bandyopadhyay, Preethi Jyothi, Jayashree Balasubramaniam, Subhra Priyadarshini

00:02 Support announcement : This episode is produced with support from DBT Wellcome Trust India Alliance.

00:30 Subhra Priyadarshini : The mobile phone. Yes, that’s the subject of our new podcast season. It’s ubiquitous, its indispensable, it’s almost like an extension of your hand. In many countries of the global south, such as India, the smartphone is a great example of technology leapfrog, as a vast majority of phone users never had a landline and were introduced to phones with the handheld phone.

And, of course, the increasing penetration of affordable mobile phones in developing countries is also making it possible for scientists to conduct meaningful and timely research, in the lab, in the field or while working from home, especially what we saw during the COVID-19 pandemic.

I am your host Subhra Priyadarshini, and in this new season of the Nature India podcast, I will explore how the mobile phone has changed India’s science-society dynamics as well as the way scientists, researchers and policy makers work. In today’s episode we will specifically look at smartphones as enablers of science and research. We will talk about the use of mobile phones for research and data collection, crowdsourcing and science education.

In short, does the lab have a place for the mobile phone? Let’s find out.

Up first, we talk of the use of mobile phones in a science laboratory setting. Convenient, right? When you don’t have a laptop handy. But can they also replace bulky, expensive scientific instruments in the lab or help set up labs, for instance, in remote places? We ask Subhajit Bandyopadhyay, a professor in the Department of Chemical Sciences at the Indian Institute of Science, Education and Research, Kolkata.

2:37 Subhajit Bandyopadhyay : Oh, yes, of course. A mobile phone can be used as a great tool, because it has so many features. I teach chemistry, and we deal with a lot of problems that are associated with chemistry. So quite often, you use instruments called spectrophotometers. And what it does is, it would tell you, very simplistically, a lot about the intensity of light and how it various wavelengths and so on. Typical spectrophotometric would be quite expensive. So if in village schools where you don't really have a stable power supply, and if the funding situation is not that great. We have developed programs, which could be used by schoolchildren, to supplement spectrophotometers. And they can do certain experiments like chemical kinetics and stuff with these cell phones. So it's basically free. And it's really easy to use. And, you know, the precision would not be as good as the spectrophotometer. But it's pretty good.

3:38 Subhra Priyadarshini : Right. And while mobile apps can provide easy access to scientific information, analysis, or simulations, or making learning and experimentation more engaging and accessible, imagine if you are colour blind or have impaired vision and can’t differentiate between all the colourful liquids in a chemistry lab. Subhajit and his team developed a smartphone app that helps colour-blind and visually impaired students detect colour change in a routine lab experiment, thereby ensuring their active participation and independence in the lab.

6:11 Subhajit Bandyopadhyay : We developed this a few years ago. About 8% of the male population of the world is colour blind. And about 0.5% of the female population of the world is colour blind. Now that's, that's really a big number. I'm thinking of a classroom of 80 students or, or sometimes in big colleges, it's over 100 students, you have a large number of students who are colour blind. Now, these students cannot really perform the chemistry experiments, because very often this chemistry experiments would involve colours. For example, the basic experiment of titration, acid base titration, or redox titration would involve colours. So what we did was we basically use this mobile phone camera and translated the colour data to something which was easy for a student with color blindness to perceive. For example, when the there is a change in the colour from colourless to red, the screen would indicate the colour change. At the same time, there will be other indicators like beeping sound, or it would vibrate.

Really was a very rewarding experience for me. So a few years ago, I went to Vietnam and one of the students told me that he was colour blind. And he said, he uses a particular programme that helps him greatly, and he takes out the phone and shows me my programme. So it was really a wonderful experience for me.

The application records the colour information. Hue Saturation and Value colour space and when there is a change in colour, it basically says there is a colour change by various means like beep sounds or vibration pulses.

6:11 Subhra Priyadarshini : One of Subhajit’s students Balraj Rathod, now a PhD scholar at the University of British Columbia in Canada, helped the team make this app.

Now, mobile phones have also emerged as supplementary teaching methods by providing access to educational resources, remote communication and multimedia learning. Preethi Jyothi, a faculty member in the Department of Computer Science at IIT Bombay uses it as a teaching aid.

6:53 Preethi Jyothi : So to give an example, smartphones now have lots of these built-in sensors. And using the sensors, you could teach fundamental concepts in physics, like, motion, and pressure, and so on. Typically abstract concepts, but using smartphones to make lab lessons applications involving these concepts would really reinforce the student's interest in learning,specific concepts. and also language learning. when you're trying to speak a new language, how to pronounce words, and so on, if you have apps on your smartphones, which will record what you're saying, and then give you instant feedback about how you're pronouncing certain words. That's a very powerful kind of tool. So I think science education, certainly mobile phones have a place.

7:35 Subhra Priyadarshini : And Preethi tell us a bit about the crowd sourced research, which has been your forte, along with your colleague Kameswari Chebrolu.

7:45 Preethi Jyothi : These days smartphones can also be used to gather data from people. And this could be because smartphones have GPS systems enabled, you could use it to gather data from people for various applications, like say traffic forecasting, or route planning and so on. I work on applying machine learning techniques for speech and language. And I'm specifically interested in building technologies for Indian languages. And so this app that we built that it's called clap, it's available on the Google Play Store. So this is an app via which you can be collected speech data from anyone who downloads this app. the volunteers would be asked to just read out these prompts. what we get immediately is parallel text with the corresponding speech from different speakers. unlike maybe other crowdsourcing platforms, which are very well known like Amazon's Mechanical Turk, and so on, which actually have many users from India, what we have found is that platforms like Mechanical Turk, most of the users are urban users, this automatically excludes a large fraction of users. Smartphones, now the reach is so much wider. And so our idea was to be able to reach users across a very broad spectrum, spanning multiple demographics they're all already very comfortable with using mobile phones. And this is currently a big area of interest across kind of machine learning technologies that you don't want to be catering just to very small sections of users. And if you're building machine learning applications, it all everything that is driving the accuracy of the such applications is the data that is being used to train these applications.That was the motivation behind building such an app on a smartphone so that we could get data from diverse users, and then use that to train speech recognition and language technologies.

9:40 Subhra Priyadarshini : Certainly, phones are the new trainers and teachers. They also play a crucial role in disseminating scientific knowledge for various end users. Take the instance of farmers as consumers of scientific knowledge. Jayashree Balasubramaniam, who works in the business of communication at Reliance Foundation tells us more.

10:06 Jayashree Balasubramaniam : The whole context of using mobile phones to bridge a number of gaps, I think that's something that's really picked up, especially post-COVID, where people have not only broken down their own personal barriers, but I think technology has grown immensely. What has also happened is that we see a large number of people, especially from communities, like small and marginal farmers, looking at ways in which they can explore this, take, for instance, you know, something that's related to crop practices, or, you know, pests and disease or a package of practices that developed by agricultural research institutions, and that's actually to be used by farmers. So what's been happening is that the typical agricultural extension services has managed to reach out to farmers through physical modes, but given the limitations that, you know, situations, such as the COVID pandemic brought in, what happened was that farmers also had to kind of look at other ways to gather the same information. During, you know, the 2020, I think this was the only sector in India that actually kind of had a positive growth. And this was primarily thanks to the way that they had, you know, kind of leveraged their knowledge.

11:27 Subhra Priyadarshini : Agriculture sciences have been a great beneficiary of mobile phone use for data collection and surveys, crowdsourcing, education and dissemination. We’ll, of course, dedicate a full episode to talk about this unique use case. But Jayashree, do talk us through a few of these use cases in this field as you have been at the forefront of this use.

11:53 Jayashree Balasubramaniam : Take for instance, you know, access to mobile-based advisories. Now, one of the biggest barriers in actually reaching information to a community like a small and marginal farmer has been internet connectivity or mobile connectivity, or actually just the use of technology, the ability to use technology,we work with millions of farmers across the country, when we actually need to send out a message, it's not just given to them in a simple localized context and format, it's also given in multiple languages. So, I think breaking the language barrier has been like one of you know, the most important steps in reaching this information, besides of course, the penetration in internet connectivity, The second is actually looking at ways in which with low mobile connectivity or low internet connectivity areas, you can use simple methods, these could be you know, chatbots this could be voice messages, this could also be some sort of audio conferencing that happens, where with a limited bandwidth and with a limited physical presence, you can still kind of get your message across, what we found through you know, our work in in a number of locations is that not only is the knowledge used, but you know, 75% or most of the farmers who have actually received these you know, pieces of information at different points of time have reported that they have actually improved their livelihoods.

13:18 Subhra Priyadarshini : And you see an easy uptake of this scientific information by people who may not have been exposed to science at all?

13:27 Jayashree Balasubramaniam : The second part of this whole process is adding to the scientific information with some sort of, you know, physical demonstration, new seed varieties, crop practices,water efficient , climate resilient, practices that can help rural communities.For instance, we're looking at something like Go. And DVIR are like a normalized difference vegetation index, which is you using, you know, satellite imagery.How it can predict something like drought or other crop stresses, even before that, it actually happens, it makes a big difference in actually transmitting this information. So this information is not just, you know, looked at, as somebody who's watching it, observing it, and recording it in a lab with the use of satellite imagery, this is actually getting translated through mobile or messaging or through, you know, mobile platforms, it's also like, you know, rural communities, we're using it for micro entrepreneurship and other things, but here translating the scientific information in simple, digestible nuggets, that has made a big difference to the way they actually adapt it on the field.

Now, we look at how integrated information like, weather, there is some sort of an impending natural disaster, you know, floods or cyclones, for instance, there are fishing communities who are actually exposing themselves to risk on a day to day basis,we found that 97% of the fishing communities were who actually received preventive information about the weather, said that actually, they not just, you know, minimize their losses, but actually, a lot of them were able to take preventive action to save their livelihood.

15:07 Subhra Priyadarshini : 10 years back Abhijit Pakhare, a community medicine specialist at the All India Institute of Medical Sciences at Bhopal and his colleagues analysed the use of mobile phones as research instruments for data collection in household surveys, clinical trials, surveillance and spatial data in global south countries. They inferred that mobile phones enabled economical, environment-friendly, faster and more accurate data collection for research. The limitations, however, were data entry errors, connectivity issues and of course the digital divide – all of which we will have a closer look at in our next episodes.

Ten years later, due to their widespread availability, affordability and connectivity, mobile phones are becoming extremely important to the process of science as much as science’s connect to society, as we have just heard through examples in the lab, in classrooms, in farming, fishing, rural communities. While urban users have to actually use apps for digital detox to keep away from potential negative effects of mobile use, science certainly benefits from these tiny devices. We will hear more on various aspects of scientific research benefitting from during this season.

Stay tuned, and give us a listen at your favourite podcast platform. This is Subhra Priyadarshini signing off from the Nature India podcast.

16:56 Support announcement : This episode was brought to you with support from DBT Wellcome Trust India Alliance.

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Mobile User Experience from the Lens of Project-Based Learning

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• Maria Spichkova   ORCID: orcid.org/0000-0001-6882-1444 20  

Part of the book series: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ((LNICST,volume 594))

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This paper presents an overview of mobile application projects conducted at the RMIT University as a part of the Learning and Teaching activities within Bachelor and Master programs, in collaboration with industrial partners. We discuss the lessons learned over eight years of teaching the corresponding courses and compare the results of our student project to the trends summarised in the recently published approached from other universities and countries.

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Acknowledgement

We would like to thank Shine Solutions Group Pty Ltd and Spatial Vision for supporting the projects. We also would like to thank students who participated in the discussed projects: Callum Pearse, Baoyun Chen, Shiran Ekanayake, Lijith Win Vijay, Harish Narayanasamy, Ashish Bhardwaj, Johan van Zyl, Lavanya Krishnamurthy, Nirav Desai, and Siddharth Sachdeva.

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Deakin University, Melbourne, VIC, Australia

Arkady Zaslavsky

Chongqing University of Posts and Telecommunications, Chongqing, China

Zhaolong Ning

Athens University of Economics and Business, Athens, Greece

Vana Kalogeraki

Swinburne University of Technology, Melbourne, VIC, Australia

Dimitrios Georgakopoulos

University of Pittsburgh, Pittsburgh, PA, USA

Panos K. Chrysanthis

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Spichkova, M. (2024). Mobile User Experience from the Lens of Project-Based Learning. In: Zaslavsky, A., Ning, Z., Kalogeraki, V., Georgakopoulos, D., Chrysanthis, P.K. (eds) Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-031-63992-0_30

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• v.7(3); Jul-Sep 2017

Smartphone usage and increased risk of mobile phone addiction: A concurrent study

Subramani parasuraman.

Unit of Pharmacology, AIMST University, Kedah, Malaysia

Aaseer Thamby Sam

1 Unit of Pharmacy Practice, Faculty of Pharmacy, AIMST University, Kedah, Malaysia

Stephanie Wong Kah Yee

Bobby lau chik chuon.

This study aimed to study the mobile phone addiction behavior and awareness on electromagnetic radiation (EMR) among a sample of Malaysian population.

This online study was conducted between December 2015 and 2016. The study instrument comprised eight segments, namely, informed consent form, demographic details, habituation, mobile phone fact and EMR details, mobile phone awareness education, psychomotor (anxious behavior) analysis, and health issues. Frequency of the data was calculated and summarized in the results.

Totally, 409 respondents participated in the study. The mean age of the study participants was 22.88 (standard error = 0.24) years. Most of the study participants developed dependency with smartphone usage and had awareness (level 6) on EMR. No significant changes were found on mobile phone addiction behavior between the participants having accommodation on home and hostel.

Conclusion:

The study participants were aware about mobile phone/radiation hazards and many of them were extremely dependent on smartphones. One-fourth of the study population were found having feeling of wrist and hand pain because of smartphone use which may lead to further physiological and physiological complication.

INTRODUCTION

Mobile/hand phones are powerful communication devices, first demonstrated by Motorola in 1973, and made commercially available from 1984.[ 1 ] In the last few years, hand phones have become an integral part of our lives. The number of mobile cellular subscriptions is constantly increasing every year. In 2016, there were more than seven billion users worldwide. The percentage of internet usage also increased globally 7-fold from 6.5% to 43% between 2000 and 2015. The percentage of households with internet access also increased from 18% in 2005 to 46% in 2015.[ 2 ] Parlay, the addiction behavior to mobile phone is also increasing. In 2012, new Time Mobility Poll reported that 84% people “couldn't go a single day without their mobile devices.”[ 3 ] Around 206 published survey reports suggest that 50% of teens and 27% of parents feel that they are addicted to mobiles.[ 4 ] The recent studies also reported the increase of mobile phone dependence, and this could increase internet addiction.[ 5 ] Overusage of mobile phones may cause psychological illness such as dry eyes, computer vision syndrome, weakness of thumb and wrist, neck pain and rigidity, increased frequency of De Quervain's tenosynovitis, tactile hallucinations, nomophobia, insecurity, delusions, auditory sleep disturbances, insomnia, hallucinations, lower self-confidence, and mobile phone addiction disorders.[ 6 ] In animals, chronic exposure to Wi-Fi radiation caused behavioral alterations, liver enzyme impairment, pyknotic nucleus, and apoptosis in brain cortex.[ 7 ] Kesari et al . concluded that the mobile phone radiation may increase the reactive oxygen species, which plays an important role in the development of metabolic and neurodegenerative diseases.[ 8 ]

In recent years, most of the global populations (especially college and university students), use smartphones, due to its wide range of applications. While beneficial in numerous ways, smartphones have disadvantages such as reduction in work efficacy, personal attention social nuisance, and psychological addiction. Currently, the addiction to smartphones among students is 24.8%–27.8%, and it is progressively increasing every year.[ 9 ] Mobile phone is becoming an integral part to students with regard to managing critical situations and maintaining social relationships.[ 10 ] This behavior may reduce thinking capabilities, affect cognitive functions, and induce dependency. The signs of smartphone addiction are constantly checking the phone for no reason, feeling anxious or restless without the phone, waking up in the middle of night to check the mobile and communication updates, delay in professional performance as a result of prolonged phone activities, and distracted with smartphone applications.[ 11 ]

Mobile phone is the most dominant portal of information and communication technology. A mental impairment resulting from modern technology has come to the attention of sociologists, psychologists, and scholars of education on mobile addiction.[ 12 ] Mobile phone addiction and withdrawal from mobile network may increase anger, tension, depression, irritability, and restlessness which may alter the physiological behavior and reduce work efficacy. Hence, the present study was planned to study the addiction behavior of mobile phone usage using an online survey.

This study was approved by Human and Animal Ethics Committee of AIMST University (AUHAEC/FOP/2016/05) and conducted according to the Declaration of Helsinki. The study was conducted among a sample of Malaysian adults. The study participants were invited through personal communications to fill the online survey form. The study was conducted between December 2015 and 2016. The study instrument comprised eight segments, namely, informed consent information, consent acceptance page, demographic details, habituation, mobile phone fact and electromagnetic radiation (EMR) details, mobile phone awareness education, psychomotor (anxious behavior) analysis, and health issues. If any of the participants were not willing to continue in the study, they could decline as per their discretion.

Totally, 450 participants were informed about the study and 409 participated in the study. The demographic details of the study participants are summarized in Table 1 . The incomplete forms were excluded from the study. The participants' details were maintained confidentially.

Demographic details of the study participants

Statistical analysis

Frequency of the data was calculated and the data were analyzed using two-sided Chi-square test with Yate's continuity correction.

Totally, 409 individuals participated in the study, of which 42.3% were males and 57.7% were females, between the age group of 18 and 55 years. Nearly 75.6% of the respondents were between the age group of 21 and 25 years. The mean age of the study participants was 22.88 (standard error = 0.24) years. The study participants' demographic details are summarized in Table 1 .

About 95% of the study participants were using smart phones, with 81.7% of them having at least one mobile phone. Most of the study participants used mobile phone for more than 5 years. Around 64.3% of the study participants use mobile phone for an hour (approximately) and remaining use it for more than an hour. Nearly 36.7% of the study participants have the habit of checking mobile phones in between sleep, while 27.1% felt inconvenience with mobile phone use. Majority of the respondents were using mobile phone for communication purposes (87.8%), photo shooting (59.7%), entertainment (58.2%), and educational/academic purposes (43.8%). Habits of mobile phone usage among the study participants are summarized in Table 2 .

Habituation analysis of mobile phone usage

The study results indicate that 86.8% of the participants are aware about EMR and 82.6% of the study participants are aware about the dangers of EMR. The prolonged use/exposure to EMR may cause De Quervain's syndrome, pain on wrist and hand, and ear discomfort. Among the study participants, 46.2% were having awareness on De Quervain's syndrome, 53.8% were feeling ear discomfort, and 25.9% were having mild-to-moderate wrist/hand pain. Almost 34.5% of the study participants felt pain in the wrist or at the back of the neck while utilizing smartphones [ Table 3a ]. Many of the study participants also agreed that mobile phone usage causes fatigue (12% agreed; 67.5% strongly agreed), sleep disturbance (16.9% agreed; 57.7% strongly agreed), and psychological disturbance (10.8% agreed; 54.8% strongly agreed) [ Table 3b ]. The study participants were having level 6 of awareness on mobile phone usage and EMR.

Analysis of awareness of mobile phone hazards

The behavioral analysis of the smartphone usage revealed that 70.4% of the study participants use smartphone longer than intended and 66.5% of the study participants are engaged for longer duration with smartphone. Nearly 57.7% of the study participants exercise control using their phones only for specific important functions. More number of study participants (58.2%) felt uncomfortable without mobile and were not able to withstand not having a smartphone, feeling discomfort with running out of battery (73.8%), felt anxious if not browsing through their favorite smartphone application (41.1%), and 50.4% of the study participants declared that they would never quit using smartphones even though their daily lifestyles were being affected by it. The study also revealed another important finding that 74.3% of smartphone users are feeling dependency on the use of smartphone. The addiction behavior analysis data of mobile phone are summarized in Table 4 .

Addiction behavior analysis of mobile phone

The study results also suggest that female participants were having more awareness than male participants ( P < 0.001) [ Table 5a ] and were more dependent on smartphones than male participants ( P < 0.05) [ Table 5b ]. Female participants were ready to quit using smartphones, if it affected daily lifestyle compared with male participants ( P < 0.05) [ Table 5b ]. Habituation of mobile phone use and addiction behavior were compared between both genders of the study participants and are summarized in Table 5a and ​ andb, b , respectively.

Comparison of habituation of mobile phone usage between genders

Comparison of addiction behavior between genders

A total of 297 participants were having accommodation in hostel, among them 39.6% of the study participants checked their mobile phone on an average of 21–30 times, a day, and 11.7% of the study participants checked their mobile phone more than 30 times a day. A total of 112 participants have accommodation in home, among them 28.6% of the study participants checked their mobile phone 21–30 times a day, and 13.4% of the study participants checked their mobile phone more than 30 times a day.

A total of 66.1% of participants having accommodation in home use their phones longer than intended, whereas 71.8% of participants having accommodation in hostel are using phone longer than intended. Forty-one (36.6%) and 109 (36.6%) participants from home and hotel checked mobile phone in-between sleep, respectively. About 67.9% of participants having accommodation in home felt dependent on mobile and it was the same for participants having accommodation in hostel (76.5%).

The study results suggest that a significant number of the participants had addiction to mobile phone usage, but were not aware on it, as mobile phones have become an integral part of life. No significant differences were found on addiction behavior between the participants residing in hostel and homes. Mobile phone abuse is rising as an important issue among the world population including physical problems such as eye problems, muscular pain, and psychological problem such as tactile and auditory delusions.[ 13 ] Along with mobile phone, availability of Wi-Fi facility in residence place and work premises also increases mobile phone dependence. The continuous and constant usage of mobile phone reduces intellectual capabilities and work efficacy. A study conducted in Chinese population (160 million out of the total 1.3 billion people) showed that people affected by mobile phone dependence have difficulty in focusing on work and are unsociable, eccentric, and use phones in spite of facing hazards or having knowledge of harmful effects of this form of electromagnetic pollution.[ 14 ]

The statement “I will never quit using my smartphone even though my daily lifestyles are affected by it” was statistically significant ( P = 0.0229). This points to a trend of mobile phone addiction among the respondents. This finding was discussed by Salehan and Negahban. They stated that this trend is due to the fast growth in the use of online social networking services (SNS). Extensive use of technology can lead to addiction. The use of SNS mobile applications is a significant predictor of mobile addiction. Their result showed that the use of SNS mobile applications is affected by both SNS network size and SNS intensity of the user. It has implications for academia as well as governmental and non-for-profit organizations regarding the effect of mobile phones on individual's and public health.[ 15 ] The health risks associated with mobile phones include increased chances of low self-esteem, anxiety or depression, bullying, eye strain and “digital or mobile phone thumb,” motor vehicle accidents, nosocomial infections, lack of sleep, brain tumors and low sperm counts, headache, hearing loss, expense, and dishonesty. The prevalence of cell phone dependence is unknown, but it is prevalent in all cultures and societies and is rapidly rising.[ 16 ] Relapse rate with mobile phone addiction is also high, which may also increase the health risk and affect cognitive function. Sahin et al . studied mobile phone addiction level and sleep quality in 576 university students and found that sleep quality worsens with increasing addiction level.[ 17 ]

The statement “Feeling dependent on the use of smartphone” was also statistically significant ( P = 0.0373). This was also explored by Richard et al . among 404 university students regarding their addiction to smartphones. Half of the respondents were overtly addicted to their phones, while one in five rated themselves totally dependent on their smartphones. Interestingly, higher number of participants felt more secure with their phones than without. Using their phones as an escapism was reported by more than half of the respondents. This study revealed an important fact that people are not actually addicted to their smartphones per se ; however, it is to the entertainment, information, and personal connections that majority of the respondents were addicted to.[ 18 ]

The 2015 statistical report from the British Chiropractic Association concluded that 45% of young people aged 16–24 years suffered with back pain. Long-term usage of smart phone may also cause incurable occipital neuralgia, anxiety and depression, nomophobia, stress, eyesight problem, hearing problems, and many other health issues.[ 19 ]

A study conducted among university students of Shahrekord, Iran, revealed that 21.49% of the participants were addicted to mobile phones, 17.30% participants had depressive disorder, 14.20% participants had obsessive-compulsive disorder, and 13.80% had interpersonal sensitivity.[ 12 ] Nearly 72% of South Korean children aged 11–12 years spend 5.4 h a day on mobile phones, 25% of those children were considered addicts to smartphones.[ 20 ] Thomée et al . collected data from 4156 adults aged between 20 and 24 years and observed no clear association between availability demands or being awakened at night and the mental health outcomes.[ 21 ] Overuse of mobile phone can lead to reduced quality of interpersonal relationships and lack of productivity in daily life. The study outcome from different studies showed variable results on addictive behavior on mobile phone usage. The fact is over-/long-time usage of mobile phone may cause behavioral alteration and induce addictive behavior.

This study suggests that most of the study participants are aware about mobile phone/radiation hazards and many of them developed dependent behavior with smartphone. No significant changes were found on mobile phone dependency behavior between participants having accommodation in house and hostel. One-fourth of the study population is having a feeling of wrist and hand because of smartphone usage which may lead to further physiological and physiological complications.

Limitations

• Cluster sampling from a wider population base could have provided a more clear idea regarding the topic of interest
• Increasing the time frame and number of study phases was not possible due to logistical issues
• Impact of smartphone addiction on sleep pattern could have been studied in-depth.

Financial support and sponsorship

Conflicts of interest.

There are no conflflicts of interest.

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• Teens and Mobile Phones
• Introduction: Why study mobile phones?

Table of Contents

• Acknowledgements
• Chapter One: The basics of how teens acquire and use mobile phones
• Chapter Two: How phones are used with friends – What they can do and how teens use them
• Chapter Three: Attitudes towards cell phones
• Chapter Four: How parents and schools regulate teens’ mobile phones

Introduction and background

Wireless communication has emerged as one of the fastest diffusing mediums on the planet, fueling an emergent “mobile youth culture”[6.numoffset=”6” Castells, M., Fernandez-Ardevol, M., Qiu, J., & Sey, A. (2007). Mobile communication and society: A global perspective . Cambridge, MA: MIT Press.] that speaks as much with thumbs as it does with tongues. At one of our focus groups a teen boy gushed, “I have unlimited texts . . . which is like the greatest invention of mankind.” His enthusiasm was hardly unique. Cell phone use and, in particular, the rise of texting has become a central part of teens’ lives. They are using their phones to stay in touch with friends and parents. They are using them to share stories and photos. They are using them to entertain themselves when they are bored. They are using them to micro-coordinate their schedules and face-to-face gatherings. And some are using their phones to go online to browse, to participate in social networks, and check their emails. This is the sunny side of the story. Teens are also using mobile phones to cheat on tests and to skirt rules at school and with their parents. Some are using their phones to send sexts, others are sleeping with buzzing phones under their pillows, and some are using their phones to place calls and text while driving.

While a small number of children get a cell phone in elementary school, the real tipping point for ownership is in middle school. About six in ten (66%) of all children in our sample had a cell phone before they turned 14. Slightly less than 75% of all high school students had a cell phone.

This report particularly highlights the rapid rise of text messaging in recent months. Some 72% of all US teens are now text message users, 1 up from 51% in 2006. Among them, the typical texter sends and receives 50 texts a day, or 1500 per month. By way of comparison a Korean, Danish or a Norwegian teen might send 15 – 20 a day and receives as many. Changes in subscription packages have encouraged widespread texting among US teens and has made them into world class texters. As a result, teens in America have integrated texting into their everyday routines. It is a way to keep in touch with peers even while they are engaged in other social activities. Often this is done discreetly and with little fuss. In other cases, it interrupts in-person encounters or can cause dangerous situations.

To understand the role that cell phones play in teens’ lives, the Pew Research Center’s Internet & American Life Project and Michigan’s Department of Communication Studies conducted a survey and focus groups in the latter part of 2009. The phone survey was conducted on landline and cell phones and included 800 youth ages 12-17 and one of their parents. It was administered from June 26-September 24, 2009. The overall survey has a margin of error of 4 percentage points; the portion dealing with teen cell owners involved 625 teens in the sample and has a margin of error of 4 percentage points; the portion dealing with teen texters involved 552 teens in the sample and has a margin of error of 5 percentage points.

A brief history of the mobile phone as a technology

The idea for cellular telephony originated in the US. The first cellular call and the first call from a hand held cellular device also were placed in the US.

The cell phone merges the landline telephony system with wireless communication. The landline telephone was first patented in 1876. Mobile radio systems have been used since the early 1900’s in the form of ship to shore radio, and were installed in some police cars in Detroit starting in 1921. The blending of landline telephone and radio communication came after the Second World War. The first commercially available “mobile radiophone service” that allowed calls from fixed to mobile telephones was offered in St. Louis in 1946. By 1964 there were 1.5 million mobile phone users in the US. 2 This was a non-cellular system that made relatively inefficient use of the radio bandwidth. In addition, the telephones were large, energy intensive car-mounted devices. According to communications scholar Thomas Farley, the headlights of a car would noticeably dim when the user was transmitting a call. 3

In the drive to produce a more efficient mobile telephone system, researchers W. Rae Young and Douglas Ring of Bell Labs developed the idea of cellular telephony, in which geographical areas are divided into a mesh of cells, each with its own cell tower. 4 This allowed a far more efficient use of the radio spectrum and the “cell” phones needed less power to send and receive a signal. The first installation was in 1969 on the Amtrak Metroliner that traveled between New York City and Washington. Four years later Martin Cooper of Motorola made the first cellular call from a prototype handheld cell phone.

Regulation around mobile phones

After the inauguration of mobile phone service in the US, a regulatory environment that allowed multiple mobile-calling standards stifled mobile communication development and expansion in the US for several years. Indeed, the growth of the GSM standard in Europe and the rise of DoCoMo in Japan meant that the dramatic developments in the cell phone industry were taking place abroad. In the US, small license areas for mobile phone companies meant that users were constantly roaming outside their core area. A user in Denver would have to pay roaming charges if he or she made or received a call in Ft. Collins, Colorado Springs or Vail. To the degree that texting was available, users could only text to users in their home network.

In the late 1980’s industry consolidation eliminated the small local areas and by the turn of the millennium, interoperability between operators became standard, and the cost of calling plans and the price of handsets fell. Rather than being a yuppie accessory, the cell phone became widely-used by everyone from the captains of industry and finance to the people who shined their shoes and walked their dogs.

As cell phones have become more available, they are increasingly owned and used by children and teens. Further, as handsets become more loaded with capabilities ranging from video recording and sharing, to music playing and internet access, teens and young adults have an ever-increasing repertoire of use. Indeed, we are moving into an era when mobile devices are not just for talking and texting, but can also access the internet and all it has to offer. This connectivity with others and with content has directed the regulator’s lens onto mobile safety practices. It has also prompted the beginning of a cultural conversation about how to ensure that parents have the tools to regulate their child’s mobile use, should they choose to. Understanding how youth use mobile phones is vital to creating effective policy based on the reality of how the technology is used. It is also important to understand how telecommunications company policies and pricing affect how teens and parents use their phones.

Previous research on cell phones and teens

This report tries to expand a tradition of cell phone research that extends into the early 1990s, 5 and work on landline telephony as far back as the 1970s. 6 The first studies to examine the social consequences of the mobile phone came in the early 1990s when researchers examined its impact on residential markets. 7 One of the earliest papers on cell phones examined it through the lens of gender; in 1993, Lana Rakow and Vija Navarro wrote about the cell phone and what they called “remote mothering.” 8 Starting in the mid 1990s in Europe there was the beginning of more extended scholarship on cellular communication, 9 and by 2000 work was being done in the US that evolved from a small number of articles to edited books and eventually to both popular and more scholarly books on mobile communication. 10

Several themes have been central in these analyses. One is the use of cell phones in the “micro-coordination” of daily interaction. 11 As the name implies, this line of research examines how the cell phone allows for a more nuanced form of coordination. Instead of having to agree on a time and place beforehand, individuals can negotiate the location and the timing of meetings as a situation clarifies itself. Micro-coordination can be used to organize get-togethers and it can be used to sort out the logistics of daily life (e.g. sending reminders to one another or exchanging information on the fly). Extending this concept further, the cell phone can be used to coordinate so called “flash mobs” as well as different kinds of protests. 12

While micro-coordination describes an instrumental type of interaction, another line of research has examined how the cell phone can be used for expressive interaction. Since the device provides us direct access to one another, it allows us to maintain ongoing interaction with family and friends. 13 This, in turn provides the basis for the enhancement of social cohesion. 14 In this vein, some researchers have examined how the cell phone affects our sense of safety and security. 15 The cell phone can be used to summon help when accidents have happened and they can be seen as a type of insurance in case something bad occurs. Others have examined how teens, as well as others, see the mobile phone as a form of self-expression. Having a cell phone is a status symbol and having a particularly sought after model can enhance our standing among peers. 16

Finally, focusing directly on teens, there has been considerable research on the role of the cell phone as part of the emancipation process. 17 Up to this point, however, there has been little quantitative analysis of teens in the US on this topic. 18 Indeed this is one of the main questions considered in this report. Before the cell phone, there were often discussions in the home as to whether a teen could have a landline extension in her room. Teens’ push to have their own landline phone underscored their drive to control contact with their peers. The rise of the cell phone has changed the dimensions of this discussion. The cell phone has provided teens with their own communication channel. This access can be used to plan and to organize daily life and it can be used to exchange jokes and endearments. It can also be used to plan mischief of varying caliber, and it can be used to exchange photos that are – literally – the picture of innocence or of depravity.

The organization of the report

This report is the fruit of a collaboration between the University of Michigan and the Pew Research Center’s Internet & American Life Project in an attempt to broadly capture the current state of mobile phone ownership and use among American youth and their families today. From June through September 2009, the Pew Internet Project fielded a random digit-dial telephone survey among a nationally representative sample of 800 teens ages 12-17 and one of their parents or a guardian (the teen and their parent/guardian were interviewed independently). In addition to the telephone survey, the University of Michigan fielded 9 focus groups among teens ages 12-18 in four cities in June and October of 2009. The focus groups queried teens more deeply about attitudes toward and practices around their mobile phone.

The study has been guided by a desire to measure the state of affairs around mobile phones and youth in the US – how many, how much, how often, with whom? – and to better understand how mobile phones fit into and enhance (or detract from) friendships and family relationships.

The report is organized into five chapters. The first chapter covers many of the basic measurements around mobile phones, the demographic variations around their use, and different models of phone ownership. This chapter also explores the economics of teens’ phone use, including payments, and calling and texting plan structures.

The second chapter of the report looks in depth at text messaging and voice calling, and compares the two modes of communication. It then places both of those activities in the broader context of teens’ overall communications practices as well as in the context of all the activities that teens can and do engage in on their mobile phone handsets, such as listening to music, sending email, looking up websites online and taking and sharing photos and videos.

The third chapter examines parents’ and teens’ attitudes towards their cell phones, and the ways the devices enhance and disrupt their lives. It details how families and teens feel about safety and the phone, and the ways in which the phone has become a social and entertainment hub. This chapter also explores how the phone has become an electronic tether between parents and children, and teens and friends, one so potent that teens frequently sleep with their phone under their pillows.

Chapter four examines the ways in which parents and schools regulate and monitor teens’ mobile phone use and how those actions may relate to teen cell phone-related behaviors.

The fifth chapter looks at teens, cell phones and “adverse behaviors.” It recaps some of our previous research on sexting and distracted driving, and presents new research on harassment through the mobile phone, as well as teens’ experiences with spam and the sending of regrettable text messages.

The last section of the report details the full set of methods that we used to conduct the research that undergirds this report.

• Castells, M., Fernandez-Ardevol, M., Qiu, J., & Sey, A. (2007). Mobile communication and society: A global perspective . Cambridge, MA: MIT Press. ↩
• This 72% of teens who text figure is slightly different than previous teens who text numbers that we have released. The difference lies in the question wording. For this question, we asked about teens texting friends, but we did not specify the platform (computer, cell phone) on which the texting was taking place. Our other teen texting number (66%) reflects teens who text on their own cell phone, and does not constrain who the teen may be texting with. Please see K9c and K20a in our questionnaire for exact question wording. ↩
• Goggin, G. 2006. Cell phone culture: Mobile technology in everyday life. London: Routledge. ↩
• Farley, T. 2005. “Mobile telephone history.” Telektronikk 3/4:22 – 34. ↩
• Lindmark, S. 2002. “Evolution of techno-economic systems: An investigation of the history of mobile communications.” Doctoral Dissertation Thesis, Department of industrial management and economics, Chalmers University of Technology, Gothenberg, Sweden. ↩
• Thanks to Fred Stutzman for his excellent literature review of this area. ↩
• de Sola Pool, I. (Ed.). (1971). The social impact of the telephone. Cambridge: MIT press. Fischer, C. S. (1992). America Calling: A Social History of the Telephone to 1940. Berkeley, CA: University of California Press. ↩
• Jarrat, J  and Coates, J.F. (1990). ‘Future Use of Cellular Technology: Some Social Implications’, Telecommunications Policy, February 1990, pp 78–84. Lange, K. (1993). Some concerns about the future of mobile communications in residential markets. In M Christofferson (Ed.), Telecommunication: Limits to deregulation (pp. 197 – 210). Amsterdam: IOS Press. ↩
• Rakow, L.F., & Navarro, V. (1993). Remote mothering and the parallel shift: Women meet the cellular telephone. Critical studies in mass communication , 10, 144-157. ↩
• Haddon, L. (1996, 11.4.96). Mobile telephony issues: discussion paper for COST 248, Mobile sub-group. Paper presented at the COST 248 meeting, University of Sussex, Brighton, UK. Haddon, L. (1997). “Communications on the move: The Experience of Mobile Telephony in the 1990s.” Farsta:Telia. Ling, Rich. (1997). “One can talk about common manners!”: the use of mobile telephones in inappropriate situations. In Leslie Haddon (Ed.), Themes in mobile telephony: Final Report of the COST 248 Home and Work group . Stockholm: Telia. Ling, Rich, Julsrud, Tom and Krogh, Erling. (1998). The Goretex Principle: The Hytte and Mobile Telephones in Norway. In L. Haddon (Ed.), Communications on the Move: The Experience of Mobile Telephony in the 1990s ( COST248 Report). Farsta: Telia. ↩
• Grinter, R. E. and Eldridge, M. A. (2001). y do tngrs luv 2 txt msg?. In ECSCW’01: Proceedings of the seventh conference on European Conference on Computer Supported Cooperative Work , Norwell, MA, USA, 2001 (pp. 219-238). Kluwer Academic Publishers. Katz, J. and Aakhus, M. (Eds.), 2002. Perpetual contact: Mobile communication, private talk, public performance. Cambridge: Cambridge University Press. ↩
• Ling, R. and Yttri, B. (2002). Micro and hyper-coordination through the use of the mobile telephone. In Katz, J. and Aakhus, M. (Eds.), Perpetual contact: Mobile communication, private talk, public performance . Cambridge: Cambridge University Press. ↩
• Rheingold, Howard. (2002) Smart Mobs: The Next Social Revolution . Perseus Publishing, Cambridge, MA. ↩
• Licoppe, Christian. (2004). ‘Connected presence: the emergence of a new repertoire for managing social relationships in a changing communications technoscape.’ Environment and planning: Society and space, 22, 135 – 156. Christensen, T. H. (2009). ‘Connected presence’ in distributed family life. New Media & Society, 11(3), 433–451. ↩
• Miyata, Kakuko, Boase, Jeffrey and Wellman, Barry. (2008). The Social Effects of Keitai and Personal Computer E-Mail in Japan. In Katz, J.E., Handbook of Mobile Communication Studies . Cambridge, MA: MIT Press. Ling, Rich. (2008). New Tech, New Ties: How mobile communication is reshaping social cohesion. Cambridge: MIT Press. ↩
• Ling, R. (2007). Children, youth, and mobile communication. Journal of Children and Media, 1(1), 60–67. Palfrey, J. and et. al. (December 31, 2008). Enhancing Child Safety and Online Technologies. Internet Safety Task Force. Retrieved January 10, 2009 from http://cyber.law.harvard.edu/pubrelease/isttf/ . Harris Interactive. (2008) A Generation Unplugged – Research Report. Harris Interactive. Accessed from http://files.ctia.org/pdf/HI_TeenMobileStudy_ResearchReport.pdf on January 10, 2009. Cox Communications (2009) Cox Communications Teen Online & Wireless Safety Survey, in Partnership with the National Center for Missing & Exploited Children® (NCMEC) and John Walsh. ↩
• Fortunati, L. (2005). Mobile telephone and the presentation of self. In R. Ling & P. Pedersen (Eds.), Mobile Communications: Re-negotiation of the Social Sphere (pp. 203 – 218). London: Springer. Ito, M., Okabe, D., and Matsuda, M. 2005. Personal, portable, pedestrian: Mobile phones in Japanese life . Cambridge, MA: The MIT Press. Portus, Lourdes, 2008 How the Urban Poor Acquire and Give Meaning to the Mobile Phone in Katz, J.E. Handbook of Mobile Communication Studies . Cambridge, MA: MIT Press. Katz, James E., Lever, Katie M., and Chen, Yi-Fan. 2008. Mobile Music as Environmental Control and Prosocial Entertainment. in Katz, J.E. Handbook of Mobile Communication Studies . Cambridge, MA: MIT Press. Harris Interactive. (2008) A Generation Unplugged – Research Report. Harris Interactive. Accessed from http://files.ctia.org/pdf/HI_TeenMobileStudy_ResearchReport.pdf on January 10, 2009. ↩
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• On the Move: The Role of Cellular Communications in American Life. (2006). University of Michigan: Ann Arbor, MI. Accessed from http://itudcmc.files.wordpress.com/2010/03/onthemove1.pdf on March 24, 2010 ↩

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Characterizing physician directory data quality: variation by specialty, state, and insurer

• Neel M. Butala 1 , 2 ,
• Kuldeep Jiwani 3 &
• Emily M. Bucholz 2 , 4  

BMC Health Services Research volume  24 , Article number:  808 ( 2024 ) Cite this article

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As U.S. legislators are urged to combat ghost networks in behavioral health and address the provider data quality issue, it becomes important to better characterize the variation in data quality of provider directories to understand root causes and devise solutions. Therefore, this manuscript examines consistency of address, phone number, and specialty information for physician entries from 5 national health plan provider directories by insurer, physician specialty, and state.

We included all physicians in the Medicare Provider Enrollment, Chain, and Ownership System (PECOS) found in ≥ 2 health insurer physician directories across 5 large national U.S. health insurers. We examined variation in consistency of address, phone number, and specialty information among physicians by insurer, physician specialty, and state.

Of 634,914 unique physicians in the PECOS database, 449,282 were found in ≥ 2 directories and included in our sample. Across insurers, consistency of address information varied from 16.5 to 27.9%, consistency of phone number information varied from 16.0 to 27.4%, and consistency of specialty information varied from 64.2 to 68.0%. General practice, family medicine, plastic surgery, and dermatology physicians had the highest consistency of addresses (37-42%) and phone numbers (37-43%), whereas anesthesiology, nuclear medicine, radiology, and emergency medicine had the lowest consistency of addresses (11-21%) and phone numbers (9-14%) across health insurer directories. There was marked variation in consistency of address, phone number, and specialty information by state.

Conclusions

In evaluating a large national sample of U.S. physicians, we found minimal variation in provider directory consistency by insurer, suggesting that this is a systemic problem that insurers have not solved, and considerable variation by physician specialty with higher quality data among more patient-facing specialties, suggesting that physicians may respond to incentives to improve data quality. These data highlight the importance of novel policy solutions that leverage technology targeting data quality to centralize provider directories so as not to not reinforce existing data quality issues or policy solutions to create national and state-level standards that target both insurers and physician groups to maximize quality of provider information.

Peer Review reports

Introduction

Patients rely on health insurer provider directories to find physicians and access the care they need, but these directories have a high rate of inaccuracies [ 1 , 2 , 3 , 4 , 5 ]. Poor quality data in provider directories can lead to difficulties in accessing care since patients may be directed to incorrect phone numbers and addresses. Additionally, health insurer provider directory inaccuracies can lead to surprise bills if patients visit a provider that they believe is covered in their network based on inaccurate directory information, but the provider is not actually covered. More broadly, inaccurate provider directories lead to misrepresentation of network breadth and depth for consumers as they choose health plans.

Inaccurate provider directories can also lead to adverse effects at a health system level. In countries with large private healthcare systems in which many individuals depend on commercial health insurance, governments rely on provider directories to ensure that health insurers have contracted with an adequate number of providers to provide their members the option of receiving comprehensive care [ 6 ]. In countries with large public healthcare systems, governments can rely on provider directory information to engage in healthcare workforce planning across multiple health disciplines. Current data on physicians, nurses, dentists, and other health professionals from provider directories with information on the range of services offered are a crucial input to health workforce planning frameworks, regardless of the methodology chosen [ 7 ]. As such, high-quality provider directory data are necessary to enhance health workforce planning and make decisions regarding the targeted number and mix of professions and skillsets.

A U.S. recent study found that address and specialty information was inconsistent for over 80% of physicians across directories of 5 large national health insurers [ 8 ]. In the U.S., health policy solutions to improve provider directory accuracy have been attempted, but they have largely been unsuccessful in achieving their aim. Most states have laws requiring health plans to keep their directories updated [ 9 ]. Additionally, the No Surprises Act, as a part of the 2021 Consolidated Appropriations Act, created specific requirements for health plans regarding accuracy and timely updating of provider directories. However, enforcement of these regulations has been minimal [ 9 ].

In the U.S. Congress, there have been renewed calls by legislators to address provider directory data quality, particularly as it relates to ‘ghost networks’ [ 10 ]. Notably, the U.S. Senate Finance Committee recently passed the Requiring Enhanced and Accurate Lists of (REAL) Health Providers Act, which aims to ensure that Medicare Advantage plans maintain accurate directories of providers, with bipartisan support [ 11 ]. Ghost networks are physicians listed in provider directories but, in reality, are not accepting new patients or are unavailable for other reasons [ 12 ]. The presence of ghost physician entries is a byproduct of provider directory inaccuracies and can complicate access to physicians for the most vulnerable patients.

As U.S. legislators are urged to combat ghost networks and address the provider data quality issue, it becomes important to better characterize the variation in consistency of provider directories to understand root causes and inform solutions. The aim of this manuscript was to examine variation in consistency of address, phone number, and specialty information for physician entries from 5 national health plan provider directories by insurer, physician specialty, and state. These results can inform the development of novel federal and state-specific policies and guide insurers’ efforts to update provider directories.

We searched the Medicare Provider Enrollment, Chain, and Ownership System (PECOS) database for all physicians who were included in the online provider directories of 5 large national health insurers: UnitedHealth, Elevance (formerly Anthem), Cigna, Aetna, and Humana, based on physician name and zip code in September 2022. Once identified in insurer directories, we used the National Provider Identifier number to distinguish between different physicians with the same name in the same zip code. This study was not considered human subjects research as all data were available in publicly accessible health insurer provider directories and therefore there was no interaction or interventions with any individuals or use of any private information. Therefore, the need for ethics approval and informed consent to participate was waived from Colorado Multiple Institutional Review Board review. All methods were performed in accordance with the relevant guidelines and regulations.

Among physicians with address information found in ≥ 2 health insurer directories, we compared consistency of physician practice street address across health insurer directories using an approximate matching algorithm, as previously described [ 8 ]. Specifically, this algorithm was validated internally through iterative manual review of 200 entries and externally through contacting a sample of 600 entries directly with correct classification in 99%. In evaluating consistency of physician address information across health insurer directories, we did not penalize for differences in abbreviations or punctuation or evaluate secondary unit identifiers, such as suite number.

Among physicians with phone number information found in ≥ 2 health insurer directories, we evaluated consistency of physician phone number information across health plan directories. All digits of a phone number had to match exactly to be considered consistent.

Among physicians with specialty information found in ≥ 2 health insurer directories, we evaluated consistency of physician specialty information across health plan directories according to the 2021 National Uniform Claim Committee taxonomy, as previously described [ 8 ]. We categorized specialty information into 31 classifications according to the 2021 National Uniform Claim Committee taxonomy to account for differences in presence of specialty or subspecialty information across health insurer directories [ 13 ].

A physician’s information was deemed to be consistent if it was the same among all locations, phone numbers, or specialties across all health insurer directories in which the physician’s information was found. A physician’s information was considered inconsistent if physician address, phone number, or specialty differed across directories or if a physician was found in a directory but an address, phone number, or specialty present in other directories was missing from that directory.

Consistency of address, phone number, and specialty for each physician was computed independently and were not conditional on consistency of other variables.

Statistical analysis

For each insurer, we calculated the percentage of physicians in that insurer’s directory with consistent address, phone number, or specialty information when including only physicians found in that specific insurer’s physician directory. In order to evaluate consistency of physician information by physician specialty, we calculated the percentage of physicians with consistent address and phone number information by specialty among physicians with consistent specialty information only.

For each state, we calculated the percentage of physicians with consistent address, phone number, or specialty information. We attributed physicians with addresses in multiple states to the most frequent state (mode state) that appeared across all addresses for that physician. Since the presence of insurers in each state may vary, and the consistency of physician information decreases as a physician is found in more directories, we repeated this state-level analysis stratifying by the number of directories in which a physician appeared to account for potential differential ascertainment of consistency information based on the presence of number of insurers in each state.

In supplemental analysis, we additionally evaluated pair-wise consistency of physician directory address, phone number, and specialty information between each individual insurer and PECOS directly.

All analyses were conducted using Python version 3.4 (Python Software Foundation) and SAS version 9.4 (SAS Institute, Cary, NC).

Of 634,914 unique physicians in the PECOS database, 449,282 were found in ≥ 2 directories and included in our sample. Consistency of address information varied from 16.5 to 27.9% across insurers, consistency of phone number information varied from 16.0 to 27.4%, and consistency of specialty information varied from 64.2 to 68.0% across insurers (Fig.  1 ). Similar patterns were observed when each individual insurer was compared to PECOS directly, though address consistency was higher (ranging from 41 to 50% across insurers), phone number consistency was lower (ranging from 14 to 32% across insurers), and specialty consistency was higher (ranging from 80 to 87% across insurers; Supplemental Fig.  1 ).

Consistency of physician address, phone number, and specialty information by insurer compared to other insurer directories

Among physicians with consistent specialty information, address and phone number consistency varied considerably by physician specialty (Table  1 ). General practice, family medicine, plastic surgery, and dermatology physicians had the highest consistency of addresses (37-42%) and phone numbers (37-43%), whereas anesthesiology, nuclear medicine, radiology, and emergency medicine had the lowest consistency of address (11–21%) and phone number (9–14%) information across health insurer directories. Physicians in specialties that deliver primary care (general practice, family medicine, preventive medicine, pediatrics, internal medicine, and obstetrics & gynecology) had consistency of addresses 31% of the time and phone numbers 30% of the time in aggregate.

There was marked variation in consistency of address information by state (Fig.  2 A), with only 13% of physicians having consistent addresses in Minnesota and 47% of physicians having consistent addresses in Washington, D.C. Similarly, there was marked variation in consistency of phone number information by state (Fig.  2 B), with only 6% of physicians having consistent phone numbers in North Dakota and 39% of physicians having consistent phone numbers in Florida. There was less variation in consistency of specialty information by state (Fig.  2 C), though this still ranged from 54% of physicians having consistent specialty information in Minnesota to 82% of physicians having consistent specialty information in Alaska. Similar patterns across states were observed when stratifying by number of directories in which a physician was found (Supplemental Figs.  2 – 4 ).

Variation in physician information by state (heat map)

In evaluating a large national sample of U.S. physicians, we found considerable variation in consistency of health plan directory information by specialty and state, but less variation by insurer.

The low variation in physician data consistency by insurer is suggestive of the systemic nature of the provider data quality problem across insurers, irrespective of individual insurer processes. All physician directory information originates from physician practices, which face tremendous administrative burden to send physician information to insurers in distinct formats via disparate mechanisms on different schedules [ 14 ]. Prior U.S. legislation, as well as the REAL Health Providers Act bill that is currently under consideration, has primarily targeted insurers to maintain accurate directories; however, newer policy solutions may be more successful if they incorporate provider groups as well to address another source of the provider data quality problem.

The magnitude of inconsistency of address and phone number information for physicians in all specialties was high. All specialties had < 50% consistency of physician addresses and phone numbers across health insurer directories examined. Reassuringly, primary care physicians and those that receive many direct patient referrals (plastic surgery and dermatology) had the greatest consistency across addresses and phone numbers, despite often practicing in multiple locations. In contrast, physicians with the lowest consistency across addresses and phone numbers were those that rarely had direct patient referrals (anesthesiology, nuclear medicine, radiology, emergency medicine), for which a health plan provider directory may be less important to ensure access to care. These data suggest that physician practices may be responsive to incentives to improve provider directory accuracy, given that specialties with a higher degree of interface with patients often had better provider data quality. Future policy solutions could leverage physician incentives further to improve directory quality.

We found considerable variation in address, phone number, and specialty data quality by state. However, the key drivers of this variation are unclear. States vary in their enforcement strategy for national laws pertaining to provider directory accuracy that target insurers [ 15 ]. Additionally, many states have specific laws on health plan provider directory quality targeting insurers, but they are variably enforced [ 9 ]. Notably, California has had several documented enforcements of state laws regarding provider directories in recent years [ 1 ]. but it remains near the median nationally in terms of provider data quality. Future research into the drivers of state variation in provider directory quality remains a rich area for further inquiry.

In the United States, the Centers for Medicare and Medicaid Services has proposed the creation of a National Directory of Healthcare Providers and Services, which would be a single, centralized system that would aim to reduce the burden for insurers and physicians while promoting real-time accuracy for patients [ 16 ]. This unified solution would engage both insurers and physician groups, though would require a radical shift in the way physician data is transmitted between entities. Notably, the PECOS directory is currently meant to be a national “gold standard” source of provider information for physicians who treat Medicare patients, but repeated Office of Inspector General investigations have found this to have substantial inaccuracies [ 17 ]. These findings are consistent with the results from the pairwise comparisons between individual insurers and PECOS in our study, which reaffirm the large magnitude of inconsistencies in this existing U.S. national government-run provider directory. An alternative, less-disruptive policy solution that may be easier to implement would be to create a national standard by which to exchange provider directory information, similar to administrative claims.

Internationally, many government agencies maintain centralized provider directories, in part by necessity as a function of operating public healthcare delivery systems, such as the National Health Service in the United Kingdom. In such contexts, accurate provider directory information is a key input to health workforce planning, which has implications for the short-term allocation of the healthcare workforce as well as the long-term development of the healthcare workforce through targeted investment in training programs. Some evidence suggests that inaccuracies are also present in high magnitude in such government-maintained directories [ 18 , 19 ], though a thorough evaluation of provider directory accuracy in most countries is lacking. Recognizing the need to streamline and improve provider data, in early 2023, the Australian Digital Health Agency launched Provider Connect Australia (PCA) [ 20 ], which is a unified database that streamlines access to provider information for patients and other healthcare entities. Given many parallels between the healthcare systems of Australia and the United States, it will be important to gauge the success of PCA in enrolling provider groups and the accuracy of its information as the world looks to PCA as a model for forward-thinking technology-enabled national provider directory.

In this report evaluating health plan physician directory consistency for over 40% of all US physicians, we found minimal variation by insurer and considerable variation by physician specialty and state. These data highlight the importance of novel policy solutions to centralize provider directories or create national and state-level standards. Future legislation should engage both insurers and physician groups to maximize quality of provider information.

Data availability

Deidentified participant data can be made available at time of publication upon reasonable request to researchers for analyses pertaining to physician directory data quality by contacting the corresponding author.

Abbreviations

Provider Enrollment, Chain, and Ownership System

Requiring Enhanced and Accurate Lists of Health Providers Act

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Acknowledgements

NB is supported by grants from the Boettcher Foundation and the American Heart Association.

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Contributions

NB contributed to idea generation, analysis and interpretation of results, and writing of manuscript. KJ contributed to data aggregation and analysis and critical revision of manuscript. EB contributed to analysis and interpretation of results and critical revision of manuscript. NB and EB had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

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Correspondence to Neel M. Butala .

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Ethics approval and consent to participate.

This study was not considered human subjects research as all data were available in publicly accessible health insurer provider directories and therefore there was no interaction or interventions with any individuals or use of any private information. Therefore, this was deemed exempt from Colorado Multiple Institutional Review Board review. All methods were performed in accordance with the relevant guidelines and regulations.

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NB and KJ report personal fees from HiLabs outside the submitted work. EB reports that her spouse has received personal fees from HiLabs outside the submitted work. This analysis was initiated independent of any of HiLabs products or financial interests. HiLabs did not have any direct input into the analysis or interpretation of the data. HiLabs had no role in the design and conduct of the study, preparation, review, or approval of the manuscript, or the decision to submit the manuscript for publication.

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Butala, N.M., Jiwani, K. & Bucholz, E.M. Characterizing physician directory data quality: variation by specialty, state, and insurer. BMC Health Serv Res 24 , 808 (2024). https://doi.org/10.1186/s12913-024-11269-5

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Nursing aide turned sniper: Thomas Crooks' mysterious plot to kill Trump

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Attack planned well in advance

Investigators are still seeking Crooks' motive – despite his Republican leanings, he had donated recently to a progressive voter-turnout campaign in 2021 – but indicated he'd planned the attack well in advance.

The shooting marks the first assassination attempt against a former or current U.S. president since President Ronald Reagan was injured in a March 1981 shooting at a Washington, D.C., hotel. 

There are many questions about why Crooks turned into a would-be presidential assassin, firing indiscriminately into hordes of political supporters.

FBI special agent Kevin Rojek said on a call with media that law enforcement located "a suspicious device" when they searched Crooks' vehicle and that it's being analyzed at the FBI crime lab.

"As far as the actions of the shooter immediately prior to the event and any interaction that he may have had with law enforcement, we're still trying to flesh out those details now," Rojek said.

None of Crooks' shocked neighbors or high school classmates described him as violent or that he in any way signaled he was intent on harming Trump. Sunday morning, reporters and curious locals swarmed the leafy streets of the home where Crooks lived with his parents in Bethel Park, about 50 miles from the shooting scene.

Those who knew him described a quiet young man who often walked to work at a nearby nursing home. One classmate said he was bullied and often ate alone in high school.

Sunday morning, neighbor Cathy Caplan, 45, extended her morning walk about a quarter mile to glimpse what was happening outside Crooks’ home.“It came on the morning news and I was like ‘I know that street,’” said Caplan, who works for the local school district. "It feels like something out of a movie.”

Dietary aide turned deadly killer

Authorities say they are examining Crooks' phone, social media and online activity for motivation. They said he carried no identification and his body had to be identified via DNA and biometric confirmation.

Although no possible motive has yet been released, Crooks nevertheless embodies the achingly familiar profile of an American mass shooter: a young white man, isolated from peers and armed with a high-powered rifle. His attack was one of at least 59 shootings in the United States on Saturday, according to the Gun Violence Archive.

According to records and online posts of the ceremony, Crooks graduated from Bethel Park High School, about 42 miles from Butler County, on June 3, 2022. That same day, Trump met briefly with investigators at his Mar-a-Lago club in Florida as they examined whether he improperly took classified documents with him when he left the White House.

A classmate remembered Crooks as a frequent target of bullies. Kids picked on him for wearing camouflage to class and his quiet demeanor, Jason Kohler, 21, said. Crooks usually ate lunch alone, Kohler said.

Crooks worked as a dietary aide at the Bethel Park Skilled Nursing and Rehabilitation, less than a mile from his home. In a statement provided to USA TODAY on Sunday, Marcie Grimm, the facility's administrator, said she was "shocked and saddened to learn of his involvement."

Neighbor Dean Sierka, 52, has known Crooks and his parents for years. The families live a few doors apart on a winding suburban street, and Sierka’s daughter, who attended elementary, middle and high school with Crooks, remembers him as quiet and shy. Sierka said they saw Crooks at least once a week, often when he was walking to the nursing home from his parents' three-bedroom brick house.

"You wouldn’t have expected this," Sierka said. "The parents and the family are all really nice people."

"It's crazy," he added.

Secret Service role: Did they do enough?

Founded in 1865, the Secret Service is supposed to stop this kind of attack, and dozens of agents were present Saturday. As the former president and presumptive Republican presidential nominee, Trump's public appearances are managed by the Secret Service, which works with local law enforcement to develop security plans and crowd-management protocols.

In the days before the event, the agency's experts would have scouted the location, identified security vulnerabilities, and designed a perimeter to keep Trump and rally attendees safe. Congress and the Secret Service are now investigating how Crooks was able to get so close to the former president, and several witnesses reported seeing him in the area with the gun before Trump took the stage.

As the event doors opened at 1 p.m., the temperature was already pushing close to 90, and ticketed attendees oozed through metal detectors run by members of the Secret Service's uniformed division. Similar to airport security screenings, rallygoers emptied their pockets to prove they weren't carrying guns or other weapons.

Media reports indicate the Secret Service had in place, as usual, a counter-sniper team scanning the surrounding area for threats.

In an exclusive interview, former Secret Service Director Julia Pierson told USA TODAY that maintaining such a sniper security perimeter is part of the agency's responsibility for safeguarding protectees like Trump from harm. She said agents typically consider 1,000 yards to be the minimum safe distance for sniper attacks.

The Secret Service has confirmed that it is investigating how Crooks got so close to Trump, who took the stage shortly after 6 p.m. Officials say Crooks' rifle was legally obtained but have not yet released specifics.

Outside the venue at that time, Greg Smith says he tried desperately to get the attention of police. He told the BBC that he and his friends saw a man crawling along a roof overlooking the rally. Other witnesses said they also saw a man atop the American Glass Research building outside the official event security perimeter, well within the range of a 5.56 rifle bullet.

"We noticed the guy bear-crawling up the roof of the building beside us, 50 feet away from us," Smith told the BBC. "He had a rifle, we could clearly see him with a rifle."

Smith told the BBC that the Secret Service eventually saw him and his friends pointing at the man on the roof.

"I'm thinking to myself, why is Trump still speaking, why have they not pulled him off the stage?" Smith said. "Next thing you know, five shots rang out."

From his nearby deck, Trump supporter Pat English watched as the former president took the stage to Lee Greenwood's "God Bless the U.S.A.," and attendees raised their cell phones to record.

English had taken his grandson to see the rally earlier but left when it got too hot. From his deck, they listened as Trump began speaking at 6:05 p.m., backed by a crown of red-hatted MAGA supporters waving "fire Joe Biden" signs.

And then gunfire began.

Boom, boom, boom

"I heard a 'boom, boom, boom' and then screams,” English said Sunday. "I could see people running and the police run in."

Trump was saying the word "happened" as the first pop rang out. He reached up to grab his ear as two more shots echoed, and the crowd behind him – and Trump himself – ducked. Plainclothes Secret Service agents piled atop the president as a fusillade of shots rang out, apparently the Secret Service killing Crooks.

The crowd screamed, and the venue's sound system picked up the agents atop Trump planning to move the former president to safety. One yelled, "shooter's down. Let's move, let's move."

The agents then helped Trump back to his feet as they shielded him on all sides.

The sound system then picked up Trump's voice: "Wait, wait," he said, before turning to the audience and triumphantly raising his fist to yell "fight, fight" as the crowd cheered, blood streaming down his face.

By 6:14 p.m. Trump's motorcade was racing from the scene, and in a later statement, Trump's campaign said he was checked out at a local medical facility.

"I was shot with a bullet that pierced the upper part of my right ear," Trump said in a statement. "I knew immediately that something was wrong in that I heard a whizzing sound, shots, and immediately felt the bullet ripping through the skin. Much bleeding took place, so I realized then what was happening."

Firefighter 'hero' gunned down

Outside of the Butler Township Administration Office Sunday afternoon, Pennsylvania Gov. Josh Shapiro identified the rally attendee killed by Crooks as Corey Comperatore, a firefighter, father of two and longtime Trump supporter.

“Corey died a hero,” Shapiro said. “Corey dove on his family to protect them last night at this rally. Corey was the very best of us. May his memory be a blessing.”

Two other Pennsylvanians are still undergoing treatment for their injuries, Shapiro said.

Pennsylvania State Police identified two wounded attendees David Dutch, 57, of New Kensington, and James Copenhaver, 74, of Moon Township. Both are hospitalized and listed in stable condition. Shapiro said he spoke with the family of one victim and received a message from the other.

Biden spoke briefly with Trump on Saturday night, and the president condemned the assassination attempt as “sick.” He said there’s no place for political violence in the U.S. and called on Americans to unite together to condemn it.

But earlier in the week, Biden told campaign donors in a private phone call it was time to stop talking about his own disastrous presidential debate performance and start targeting Trump instead.

"I have one job and that's to beat Donald Trump," Biden said. "We're done talking about the (June 27) debate. It's time to put Trump in the bullseye."

Republicans across the country have used similar language to attack their opponents over the years, and political scientists say violent rhetoric used worldwide almost invariably leads to physical violence.

On Sunday, someone parked a truck-mounted electronic billboard at the gates to the Butler Farm Show grounds reading "Democrats attempted assassination," along with a picture of Trump clutching an American flag, his face overlaid with a bullseye crosshairs.

Authorities say they have not yet determined a motive for Crooks' attack. But in a statement, Trump declared the shooting an act of evil and thanked God for preventing the unthinkable.

"We will fear not, but instead remain resilient in our faith and defiant in the face of wickedness," Trump said.

And he said he'd be back on the campaign trail for the Republican National Convention in Milwaukee, which starts Monday.

"Based on yesterday’s terrible events, I was going to delay my trip to Wisconsin, and the Republican National Convention, by two days," Trump said on his Truth Social account Sunday, "but have just decided that I cannot allow a 'shooter,' or potential assassin, to force change to scheduling, or anything else."

Contributing: David Jackson, Aysha Bagchi, Christopher Cann, Bryce Buyakie, Emily Le Coz, Josh Meyer, USA TODAY Network

How the assassination attempt unfolded : Graphics, maps, audio analysis show what happened