Journal of Medical Internet Research

The leading peer-reviewed journal for health and healthcare in the Internet age.

JMIR's Thomson Reuter Impact Factor of 4.7 for 2013

Prevalence of Depression in Medical Students at the Lebanese University and its Correlation with Facebook Relevance:

Background: The prevalence of major depression is particularly high in medical students affecting around one third of this population. Moreover, online social media and in particular Facebook (fb) is becoming an intrinsic part in the life of a growing proportion of individuals worldwide. Objective: Our primary objective is to identify the prevalence of depression in medical students at the Lebanese University Faculty of Medicine (unique state university in Lebanon) and its correlation with the utilization of the interactive features of fb. Methods: Students of the Lebanese University Faculty of Medicine were assessed for: (1) depression and (2) fb activity. To screen for major depression we used the PHQ-9 scale. As for fb activity we developed the Facebook Resorting Questionnaire (FbRQ), which measures the degree of fb resorting. Results: Three hundred and sixty five (76%) out of 480 students participated in the survey. Twenty four were excluded hence 341 students were finally included. Current depression was reported in 117 students (34.31%) with a (2.25:1) female to male ratio; 81 out of 195 females (41.5%) versus 36 out of 146 males (24.6%). Moreover, 41 depressed students resorted to fb (35%) compared to 73 non-depressed students (32.5%). There was a strong correlation between depression and fb- resorting (P= .001) and depressed users resorted more to fb than the non- depressed. Conclusions: This study showed that depression was highly prevalent among students of the Faculty of Medicine at the Lebanese University. Moreover fb may be a promising helpful psychological tool for optimizing the management of depression. Our study brought to bear further questions that now prompt further observation and scrutiny to know more about the high rates of depression in this student population more so in this part of the world and to the growing role of social media.

2015-04-01


Call for Abstracts is Now Open. Submission Deadline: May 14 at 6pm EST

APRIL 1, 2015, BOSTON, MA -- The Connected Health Symposium, hosted annually by Partners HealthCare, today announced it has established a joint program with JMIR Publications to feature up to 50 poster presentations at this year's Symposium. JMIR Publications is the leading ehealth publisher, with over ten academic journals covering digital health, technology and innovation in health. Its flagship journal, the Journal of Medical Internet Research (JMIR), is the leading publication in the fields of medical informatics, health sciences and services research.

"There is important research being conducted throughout the connected health ecosystem that we can learn from and which deserves recognition. Academics, startups and other innovators will now have a stage to showcase their work at our annual Connected Health Symposium," said Kamal Jethwani, MD, MPH, Senior Director of Connected Health Innovation at Partners HealthCare. "We are very pleased to be working with JMIR Publications, publisher of the largest and most cited journals in ehealth."

As part of this new joint program, JMIR, along with members of the Partners Connected Health Innovation team, will review and select abstracts to be featured in a new poster session at the upcoming Connected Health Symposium. Poster presenters will receive complimentary registration to the Connected Health Symposium. Authors of accepted abstracts will also have an opportunity to submit papers for review and possible publication in JMIR and its sister journals (e.g. JMIR Medical Informatics, JMIR mHealth, JMIR Serious Games, JMIR Rehab, JMIR Mental Health, JMIR Public Health, JMIR Research Protocols and others) at a highly discounted rate.

"The Connected Health Symposium is a destination for discussion, learnings and innovation to advance the adoption and integration of connected health strategies," added Susan Lane, RN, MSN, MBA, Senior Director, Connected Health Operations, Partners HealthCare. "With the addition of this poster session, we are furthering our mission to highlight cutting-edge, novel and scalable programs to over 1,000 attendees at our Symposium, including clinicians, investors, innovators and academicians."

Abstracts must be submitted by May 14, 2015  (6pm EST) at http://iproc.org/author. An extended abstract (up to 5 pages) must be also be submitted (template at http://tinyurl.com/xabstract).

For full submission details, please see the call for papers at http://www.jmir.org/content/chs2015.

“We are thrilled to be involved in selecting the best research submissions for the Connected Health Symposium and to be the official publisher of this conference,” said Gunther Eysenbach, MD, MPH, FACMI, Publisher and Editor-in-Chief of the Journal of Medical Internet Research and its ten sister journals. “The partnership with the Connected Health Symposium is a logical extension of our strategy to partner with the leading knowledge translation initiatives in this field with the ultimate goal to advance ehealth and to expand our unique network of leading researchers in this field.”  

The 12th Annual Connected Health Symposium, being held October 29-30 in Boston, is a change-agent conference that promotes innovative thinking and the application of personal consumer health technologies, with a  focus on trends at the intersection of technology and new models of health care delivery.  Over 1,200 technology leaders, industry execs, Fortune 500 employers, policymakers, clinicians and health plan execs will come together to define the future of care delivery and impact the day-to-day lives of patients.


JMIR Publications
JMIR Publications is the leading ehealth publisher, advancing progress in the health, engineering and social sciences to ultimately help people to live happier and healthier lives using technology. JMIR Publications helps innovators in the health technology space to collaborate and disseminate their innovations, ideas, and research results to the widest possible audience, in a timely manner, adding value to the quality of the work and adhering to the highest ethical and quality standards. We achieve this by using the Internet and the latest available technologies as well as by producing conferences and social media, and other innovative knowledge translation products. We also innovate in the scholarly communication space itself, experimenting with new business models, new models of peer-review and dissemination, and new technologies. Visit http://www.jmir.org

Partners HealthCare Connected Health
Partners is leveraging information technology – cell phones, computers, wearables, sensors and remote health monitoring tools – to deliver quality patient care outside of traditional medical settings. Partners Connected Health programs are also helping providers and patients better manage chronic conditions, maintain health and wellness and improve adherence, engagement and clinical outcomes. The Connected Health team creates and deploys mobile technologies in a number of patient populations and care settings, and is conducting innovative clinical studies to test the effectiveness of mobile health technologies in various clinical applications, including medication adherence, care coordination, chronic disease management, and prevention and wellness. Visitwww.partners.org/connectedhealth

Partners HealthCare
Partners HealthCare is an integrated health system founded by Brigham and Women’s Hospital and Massachusetts General Hospital.  In addition to its two academic medical centers, the Partners system includes community and specialty hospitals, a managed care organization, community health centers, a physician network, home health and long-term care services, and other health care entities. Partners HealthCare is committed to patient care, research, teaching, and service to the community. Partners is one of the nation’s leading biomedical research organizations and a principal teaching affiliate of Harvard Medical School.  Partners HealthCare is a non-profit organization. Visit www.partners.org.

 

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Recent Articles:

  • Screenshot of the audiovisual material in which an older patient is presenting information in conversational style.

    The Effect of Modality and Narration Style on Recall of Online Health Information: Results From a Web-Based Experiment

    Abstract:

    Background: Older adults are increasingly using the Internet for health information; however, they are often not able to correctly recall Web-based information (eHealth information). Recall of information is crucial for optimal health outcomes, such as adequate disease management and adherence to medical regimes. Combining effective message strategies may help to improve recall of eHealth information among older adults. Presenting information in an audiovisual format using conversational narration style is expected to optimize recall of information compared to other combinations of modality and narration style. Objective: The aim of this paper is to investigate the effect of modality and narration style on recall of health information, and whether there are differences between younger and older adults. Methods: We conducted a Web-based experiment using a 2 (modality: written vs audiovisual information) by 2 (narration style: formal vs conversational style) between-subjects design (N=440). Age was assessed in the questionnaire and included as a factor: younger (<65 years) versus older (≥65 years) age. Participants were randomly assigned to one of four experimental webpages where information about lung cancer treatment was presented. A Web-based questionnaire assessed recall of eHealth information. Results: Audiovisual modality (vs written modality) was found to increase recall of information in both younger and older adults (P=.04). Although conversational narration style (vs formal narration style) did not increase recall of information (P=.17), a synergistic effect between modality and narration style was revealed: combining audiovisual information with conversational style outperformed combining written information with formal style (P=.01), as well as written information with conversational style (P=.045). This finding suggests that conversational style especially increases recall of information when presented audiovisually. This combination of modality and narration style improved recall of information among both younger and older adults. Conclusions: We conclude that combining audiovisual information with conversational style is the best way to present eHealth information to younger and older adults. Even though older adults did not proportionally recall more when audiovisual information was combined with conversational style than younger adults, this study reveals interesting implications for improving eHealth information that is effective for both younger and older adults.

  • Screenshot of @iurojc Twitter page, as an example of a Twitter-based journal club.

    Globalization of Continuing Professional Development by Journal Clubs via Microblogging: A Systematic Review

    Abstract:

    Background: Journal clubs are an essential tool in promoting clinical evidence-based medical education to all medical and allied health professionals. Twitter represents a public, microblogging forum that can facilitate traditional journal club requirements, while also reaching a global audience, and participation for discussion with study authors and colleagues. Objective: The aim of the current study was to evaluate the current state of social media–facilitated journal clubs, specifically Twitter, as an example of continuing professional development. Methods: A systematic review of literature databases (Medline, Embase, CINAHL, Web of Science, ERIC via ProQuest) was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic search of Twitter, the followers of identified journal clubs, and Symplur was also performed. Demographic and monthly tweet data were extracted from Twitter and Symplur. All manuscripts related to Twitter-based journal clubs were included. Statistical analyses were performed in MS Excel and STATA. Results: From a total of 469 citations, 11 manuscripts were included and referred to five Twitter-based journal clubs (#ALiEMJC, #BlueJC, #ebnjc, #urojc, #meded). A Twitter-based journal club search yielded 34 potential hashtags/accounts, of which 24 were included in the final analysis. The median duration of activity was 11.75 (interquartile range [IQR] 19.9, SD 10.9) months, with 7 now inactive. The median number of followers and participants was 374 (IQR 574) and 157 (IQR 272), respectively. An overall increasing establishment of active Twitter-based journal clubs was observed, resulting in an exponential increase in total cumulative tweets (R2=.98), and tweets per month (R2=.72). Cumulative tweets for specific journal clubs increased linearly, with @ADC_JC, @EBNursingBMJ, @igsjc, @iurojc, and @NephJC, and showing greatest rate of change, as well as total impressions per month since establishment. An average of two tweets per month was estimated for the majority of participants, while the “Top 10” tweeters for @iurojc showed a significantly lower contribution to overall tweets for each month (P<.005). A linearly increasing impression:tweet ratio was observed for the top five journal clubs. Conclusions: Twitter-based journal clubs are free, time-efficient, and publicly accessible means to facilitate international discussions regarding clinically important evidence-based research.

  • Connected Cardiac Care Program. (cc) Agboola et al, CC-BY-SA-2.0, please cite as (http://www.jmir.org/article/viewFile/4417/1/55086).

    Heart Failure Remote Monitoring: Evidence From the Retrospective Evaluation of a Real-World Remote Monitoring Program

    Abstract:

    Background: Given the magnitude of increasing heart failure mortality, multidisciplinary approaches, in the form of disease management programs and other integrative models of care, are recommended to optimize treatment outcomes. Remote monitoring, either as structured telephone support or telemonitoring or a combination of both, is fast becoming an integral part of many disease management programs. However, studies reporting on the evaluation of real-world heart failure remote monitoring programs are scarce. Objective: This study aims to evaluate the effect of a heart failure telemonitoring program, Connected Cardiac Care Program (CCCP), on hospitalization and mortality in a retrospective database review of medical records of patients with heart failure receiving care at the Massachusetts General Hospital. Methods: Patients enrolled in the CCCP heart failure monitoring program at the Massachusetts General Hospital were matched 1:1 with usual care patients. Control patients received care from similar clinical settings as CCCP patients and were identified from a large clinical data registry. The primary endpoint was all-cause mortality and hospitalizations assessed during the 4-month program duration. Secondary outcomes included hospitalization and mortality rates (obtained by following up on patients over an additional 8 months after program completion for a total duration of 1 year), risk for multiple hospitalizations and length of stay. The Cox proportional hazard model, stratified on the matched pairs, was used to assess primary outcomes. Results: A total of 348 patients were included in the time-to-event analyses. The baseline rates of hospitalizations prior to program enrollment did not differ significantly by group. Compared with controls, hospitalization rates decreased within the first 30 days of program enrollment: hazard ratio (HR)=0.52, 95% CI 0.31-0.86, P=.01). The differential effect on hospitalization rates remained consistent until the end of the 4-month program (HR=0.74, 95% CI 0.54-1.02, P=.06). The program was also associated with lower mortality rates at the end of the 4-month program: relative risk (RR)=0.33, 95% 0.11-0.97, P=.04). Additional 8-months follow-up following program completion did not show residual beneficial effects of the CCCP program on mortality (HR=0.64, 95% 0.34-1.21, P=.17) or hospitalizations (HR=1.12, 95% 0.90-1.41, P=.31). Conclusions: CCCP was associated with significantly lower hospitalization rates up to 90 days and significantly lower mortality rates over 120 days of the program. However, these effects did not persist beyond the 120-day program duration.

  • Screenshot of the Survey banner advertisement.

    A Mixed-Methods Study on the Acceptability of Using eHealth for HIV Prevention and Sexual Health Care Among Men Who Have Sex With Men in China

    Abstract:

    Background: Human immunodeficiency virus (HIV) infection disproportionately affects men who have sex with men (MSM). Over half of all HIV-positive MSM in China may not know their HIV status. Mobile phones and Web interventions (eHealth) are underutilized resources that show promise for supporting HIV education, testing, and linkage to care. Objective: This mixed-methods study among MSM in China assessed technology utilization and eHealth acceptability for sexual health care. Methods: We conducted in-depth interviews and an online survey. Qualitative analyses informed the development of the Internet survey, which was administered through two popular MSM websites. Bivariate and multivariate analysis assessed characteristics of MSM interested in eHealth for sexual health care. Results: The qualitative sample included MSM across a range of ages, education, marital status, sexuality, and HIV testing experience. Qualitative findings included the importance of the Internet as the primary source of information about sexual health, HIV and other sexually transmitted diseases (STDs), use of the Internet to enable HIV testing opportunities by facilitating connections with both the gay community and health care providers, and mixed perceptions regarding the confidentiality of eHealth tools for sexual health. Among the Internet sample (N=1342), the average age was 30.6 years old, 82.81% (1098/1342) were single, and 53.42% (711/1331) had completed college. In the past 3 months, 38.66% (382/988) had condomless sex and 60.53% (805/1330) self-reported having ever tested for HIV. The majority of men owned computers (94.14%, 1220/1296) and mobile phones (92.32%, 1239/1342), which many had used to search for HIV/STD information and testing sites. In multivariate analysis, interest in using computers or mobile phones to support their sexual health care was associated with being a student, prior use of computers or mobile phones to search for general health information, prior use of computers or mobile phones to search for HIV/STD information, and confidentiality concerns. Conclusions: MSM in this sample had high utilization of technology and interest in eHealth despite confidentiality concerns. Future eHealth interventions can thoughtfully and creatively address these concerns as a priority for successful implementation.

  • Word cloud generated from a sample of posts that are high on informational or emotional support or both.

    Eliciting and Receiving Online Support: Using Computer-Aided Content Analysis to Examine the Dynamics of Online Social Support

    Abstract:

    Background: Although many people with serious diseases participate in online support communities, little research has investigated how participants elicit and provide social support on these sites. Objective: The first goal was to propose and test a model of the dynamic process through which participants in online support communities elicit and provide emotional and informational support. The second was to demonstrate the value of computer coding of conversational data using machine learning techniques (1) by replicating results derived from human-coded data about how people elicit support and (2) by answering questions that are intractable with small samples of human-coded data, namely how exposure to different types of social support predicts continued participation in online support communities. The third was to provide a detailed description of these machine learning techniques to enable other researchers to perform large-scale data analysis in these communities. Methods: Communication among approximately 90,000 registered users of an online cancer support community was analyzed. The corpus comprised 1,562,459 messages organized into 68,158 discussion threads. Amazon Mechanical Turk workers coded (1) 1000 thread-starting messages on 5 attributes (positive and negative emotional self-disclosure, positive and negative informational self-disclosure, questions) and (2) 1000 replies on emotional and informational support. Their judgments were used to train machine learning models that automatically estimated the amount of these 7 attributes in the messages. Across attributes, the average Pearson correlation between human-based judgments and computer-based judgments was .65. Results: Part 1 used human-coded data to investigate relationships between (1) 4 kinds of self-disclosure and question asking in thread-starting posts and (2) the amount of emotional and informational support in the first reply. Self-disclosure about negative emotions (beta=.24, P<.001), negative events (beta=.25, P<.001), and positive events (beta=.10, P=.02) increased emotional support. However, asking questions depressed emotional support (beta=–.21, P<.001). In contrast, asking questions increased informational support (beta=.38, P<.001), whereas positive informational self-disclosure depressed it (beta=–.09, P=.003). Self-disclosure led to the perception of emotional needs, which elicited emotional support, whereas asking questions led to the perception of informational needs, which elicited informational support. Part 2 used machine-coded data to replicate these results. Part 3 analyzed the machine-coded data and showed that exposure to more emotional support predicted staying in the group longer 33% (hazard ratio=0.67, P<.001), whereas exposure to more informational support predicted leaving the group sooner (hazard ratio=1.05, P<.001). Conclusions: Self-disclosure is effective in eliciting emotional support, whereas question asking is effective in eliciting informational support. Moreover, perceptions that people desire particular kinds of support influence the support they receive. Finally, the type of support people receive affects the likelihood of their staying in or leaving the group. These results demonstrate the utility of machine learning methods for investigating the dynamics of social support exchange in online support communities.

  • Actual statistics compared with predicted values for obesity, 2010 BRFSS. Darker colors represent higher prevalence. Light gray indicates missing data. (cc-by) the authors.

    A New Source of Data for Public Health Surveillance: Facebook Likes

    Abstract:

    Background: Investigation into personal health has become focused on conditions at an increasingly local level, while response rates have declined and complicated the process of collecting data at an individual level. Simultaneously, social media data have exploded in availability and have been shown to correlate with the prevalence of certain health conditions. Objective: Facebook likes may be a source of digital data that can complement traditional public health surveillance systems and provide data at a local level. We explored the use of Facebook likes as potential predictors of health outcomes and their behavioral determinants. Methods: We performed principal components and regression analyses to examine the predictive qualities of Facebook likes with regard to mortality, diseases, and lifestyle behaviors in 214 counties across the United States and 61 of 67 counties in Florida. These results were compared with those obtainable from a demographic model. Health data were obtained from both the 2010 and 2011 Behavioral Risk Factor Surveillance System (BRFSS) and mortality data were obtained from the National Vital Statistics System. Results: Facebook likes added significant value in predicting most examined health outcomes and behaviors even when controlling for age, race, and socioeconomic status, with model fit improvements (adjusted R2) of an average of 58% across models for 13 different health-related metrics over basic sociodemographic models. Small area data were not available in sufficient abundance to test the accuracy of the model in estimating health conditions in less populated markets, but initial analysis using data from Florida showed a strong model fit for obesity data (adjusted R2=.77). Conclusions: Facebook likes provide estimates for examined health outcomes and health behaviors that are comparable to those obtained from the BRFSS. Online sources may provide more reliable, timely, and cost-effective county-level data than that obtainable from traditional public health surveillance systems as well as serve as an adjunct to those systems.

  • Screenshot from http://learnonline.health.nz/.

    Review and Evaluation of Online Tobacco Dependence Treatment Training Programs for Health Care Practitioners

    Abstract:

    Background: Training health care professionals is associated with increased capacity to deliver evidence-based smoking cessation interventions and increased quit rates among their patients. Online training programs hold promise to provide training but questions remain regarding the quality and usability of available programs. Objective: The aim was to assess the quality of English-language online courses in tobacco dependence treatment using a validated instrument. Methods: An environmental scan was conducted using the Google search engine to identify available online tobacco dependence treatment courses. The identified courses were then evaluated using the Peer Review Rubric for Online Learning, which was selected based on its ability to evaluate instructional design. It also has clear and concise criteria descriptions to ensure uniformity of evaluations by trained experts. Results: A total of 39 courses were identified, of which 24 unique courses were assessed based on their accessibility and functionality during the period of evaluation. Overall, the course ratings indicated that 17 of 24 courses evaluated failed to meet minimal quality standards and none of the courses evaluated could be ranked as superior. However, many excelled in providing effective navigation, course rationale, and content. Many were weak in the use of instructional design elements, such as teaching effectiveness, learning strategies, instructor’s role, and assessment and evaluation. Evaluation results and suggestions for improvement were shared with course administrators. Conclusions: Based on the courses evaluated in this review, course developers are encouraged to employ best practices in instructional design, such as cohesiveness of material, linearity of design, practice exercises, problem solving, and ongoing evaluation to improve existing courses and in the design of new online learning opportunities.

  • Possible thumbnail image for journal's table of contents.
Author Dr. CR Neary
Copyright Dr. CR Neary
No URL as photographer is family member so it's kindly reproduced with his permission.

    Validity of Internet-Based Longitudinal Study Data: The Elephant in the Virtual Room

    Abstract:

    Background: Internet-based data collection relies on well-designed and validated questionnaires. The theory behind designing and validating questionnaires is well described, but few practical examples of how to approach validation are available in the literature. Objective: We aimed to validate data collected in an ongoing Internet-based longitudinal health study through direct visits to participants and recall of their health records. We demonstrate that despite extensive pre-planning, social desirability can still affect data in unexpected ways and that anticipation of poor quality data may be confounded by positive validation. Methods: Dogslife is a large-scale, Web-based longitudinal study of canine health, in which owners of Labrador Retrievers were recruited and questioned at regular intervals about the lifestyle and health of their dogs using an Internet-based questionnaire. The Dogslife questionnaire predominantly consists of closed-answer questions. In our work, two separate validation methodologies were used: (1) direct interviews with 43 participants during visits to their households and (2) comparison of owner-entered health reports with 139 historical health records. Results: Our results indicate that user-derived measures should not be regarded as a single category; instead, each measurement should be considered separately as each presents its own challenge to participants. We recommend trying to ascertain the extent of recall decay within a study and, if necessary, using this to guide data collection timepoints and analyses. Finally, we recommend that multiple methods of communication facilitate validation studies and aid cohort engagement. Conclusions: Our study highlighted how the theory underpinning online questionnaire design and validation translates into practical data issues when applied to Internet-based studies. Validation should be regarded as an extension of questionnaire design, and that validation work should commence as soon as sufficient data are available. We believe that validation is a crucial step and hope our suggested guidelines will help facilitate validation of other Internet-based cohort studies.

  • Purchased

    A New Method for Assessing Content Validity in Model-Based Creation and Iteration of eHealth Interventions

    Abstract:

    Background: The advent of eHealth interventions to address psychological concerns and health behaviors has created new opportunities, including the ability to optimize the effectiveness of intervention activities and then deliver these activities consistently to a large number of individuals in need. Given that eHealth interventions grounded in a well-delineated theoretical model for change are more likely to be effective and that eHealth interventions can be costly to develop, assuring the match of final intervention content and activities to the underlying model is a key step. We propose to apply the concept of “content validity” as a crucial checkpoint to evaluate the extent to which proposed intervention activities in an eHealth intervention program are valid (eg, relevant and likely to be effective) for the specific mechanism of change that each is intended to target and the intended target population for the intervention. Objective: The aims of this paper are to define content validity as it applies to model-based eHealth intervention development, to present a feasible method for assessing content validity in this context, and to describe the implementation of this new method during the development of a Web-based intervention for children. Methods: We designed a practical 5-step method for assessing content validity in eHealth interventions that includes defining key intervention targets, delineating intervention activity-target pairings, identifying experts and using a survey tool to gather expert ratings of the relevance of each activity to its intended target, its likely effectiveness in achieving the intended target, and its appropriateness with a specific intended audience, and then using quantitative and qualitative results to identify intervention activities that may need modification. We applied this method during our development of the Coping Coach Web-based intervention for school-age children. Results: In the evaluation of Coping Coach content validity, 15 experts from five countries rated each of 15 intervention activity-target pairings. Based on quantitative indices, content validity was excellent for relevance and good for likely effectiveness and age-appropriateness. Two intervention activities had item-level indicators that suggested the need for further review and potential revision by the development team. Conclusions: This project demonstrated that assessment of content validity can be straightforward and feasible to implement and that results of this assessment provide useful information for ongoing development and iterations of new eHealth interventions, complementing other sources of information (eg, user feedback, effectiveness evaluations). This approach can be utilized at one or more points during the development process to guide ongoing optimization of eHealth interventions.

  • (cc) Domnich et al. CC-BY-SA-2.0, please cite as (http://www.jmir.org/article/viewFile/3734/1/56730).

    Uncontrolled Web-Based Administration of Surveys on Factual Health-Related Knowledge: A Randomized Study of Untimed Versus Timed Quizzing

    Abstract:

    Background: Health knowledge and literacy are among the main determinants of health. Assessment of these issues via Web-based surveys is growing continuously. Research has suggested that approximately one-fifth of respondents submit cribbed answers, or cheat, on factual knowledge items, which may lead to measurement error. However, little is known about methods of discouraging cheating in Web-based surveys on health knowledge. Objective: This study aimed at exploring the usefulness of imposing a survey time limit to prevent help-seeking and cheating. Methods: On the basis of sample size estimation, 94 undergraduate students were randomly assigned in a 1:1 ratio to complete a Web-based survey on nutrition knowledge, with or without a time limit of 15 minutes (30 seconds per item); the topic of nutrition was chosen because of its particular relevance to public health. The questionnaire consisted of two parts. The first was the validated consumer-oriented nutrition knowledge scale (CoNKS) consisting of 20 true/false items; the second was an ad hoc questionnaire (AHQ) containing 10 questions that would be very difficult for people without health care qualifications to answer correctly. It therefore aimed at measuring cribbing and not nutrition knowledge. AHQ items were somewhat encyclopedic and amenable to Web searching, while CoNKS items had more complex wording, so that simple copying/pasting of a question in a search string would not produce an immediate correct answer. Results: A total of 72 of the 94 subjects started the survey. Dropout rates were similar in both groups (11%, 4/35 and 14%, 5/37 in the untimed and timed groups, respectively). Most participants completed the survey from portable devices, such as mobile phones and tablets. To complete the survey, participants in the untimed group took a median 2.3 minutes longer than those in the timed group; the effect size was small (Cohen’s r=.29). Subjects in the untimed group scored significantly higher on CoNKS (mean difference of 1.2 points, P=.008) and the effect size was medium (Cohen’s d=0.67). By contrast, no significant between-group difference in AHQ scores was documented. Unexpectedly high AHQ scores were recorded in 23% (7/31) and 19% (6/32) untimed and timed respondents, respectively, very probably owing to “e-cheating”. Conclusions: Cribbing answers to health knowledge items in researcher-uncontrolled conditions is likely to lead to overestimation of people’s knowledge; this should be considered during the design and implementation of Web-based surveys. Setting a time limit alone may not completely prevent cheating, as some cheats may be very fast in Web searching. More complex and contextualized wording of items and checking for the “findability” properties of items before implementing a Web-based health knowledge survey may discourage help-seeking, thus reducing measurement error. Studies with larger sample sizes and diverse populations are needed to confirm our results.

  • The Prevent Online Diabetes Prevention Program.
(c) Sepah et al.

    Long-Term Outcomes of a Web-Based Diabetes Prevention Program: 2-Year Results of a Single-Arm Longitudinal Study

    Abstract:

    Background: Digital therapeutics are evidence-based behavioral treatments delivered online that can increase accessibility and effectiveness of health care. However, few studies have examined long-term clinical outcomes of digital therapeutics. Objective: The objective of this study was to conduct a 2-year follow-up on participants in the Internet-based Prevent diabetes prevention program pilot study, specifically examining the effects on body weight and A1c, which are risk factors for diabetes development. Methods: A quasi-experimental research design was used, including a single-arm pre- and post-intervention assessment of outcomes. Participants underwent a 16-week weight loss intervention and an ongoing weight maintenance intervention. As part of the program, participants received a wireless scale, which was used to collect body weight data on an ongoing basis. Participants also received A1c test kits at baseline, 0.5 year, 1 year, and 2-year time points. Results: Participants previously diagnosed with prediabetes (n=220) were originally enrolled in the pilot study. A subset of participants (n=187) met Centers for Disease Control and Prevention (CDC) criteria for starting the program (starters), and a further subset (n=155) met CDC criteria for completing the program (completers) and were both included in analyses. Program starters lost an average of 4.7% (SD 0.4) of baseline body weight after 1 year and 4.2% (SD 0.8) after 2 years, and reduced A1c by mean 0.38% (SD 0.07) after 1 year and 0.43% (SD 0.08) after 2 years. Program completers lost mean 4.9% (SD 0.5) of baseline body weight after 1 year and 4.3% (SD 0.8) after 2 years, and reduced A1c by 0.40% (SD 0.07) after 1 year and 0.46% (SD 0.08) after 2 years. For both groups, neither 2-year weight loss nor A1c results were significantly different from 1-year results. Conclusions: Users of the Prevent program experienced significant reductions in body weight and A1c that are maintained after 2 years. Contrary to the expected progression from prediabetes to diabetes over time, average A1c levels continued to show an average regression from within the prediabetic range (5.7%-6.4%) initially to the normal range (<5.7%) after 2 years. Further investigation is warranted to test digital therapeutics as a scalable solution to address national diabetes and cardiovascular disease prevention efforts.

  • This is a royalty free image by basketman (http://www.freedigitalphotos.net/images/Other_business_conce_g200-Finger_Pressing_Evaluation_Form_p68039.html).

    Insights Into the Impact of Online Physician Reviews on Patients’ Decision Making: Randomized Experiment

    Abstract:

    Background: Physician-rating websites combine public reporting with social networking and offer an attractive means by which users can provide feedback on their physician and obtain information about other patients’ satisfaction and experiences. However, research on how users evaluate information on these portals is still scarce and only little knowledge is available about the potential influence of physician reviews on a patient’s choice. Objective: Starting from the perspective of prospective patients, this paper sets out to explore how certain characteristics of physician reviews affect the evaluation of the review and users’ attitudes toward the rated physician. We propose a model that relates review style and review number to constructs of review acceptance and check it with a Web-based experiment. Methods: We employed a randomized 2x2 between-subject, factorial experiment manipulating the style of a physician review (factual vs emotional) and the number of reviews for a certain physician (low vs high) to test our hypotheses. A total of 168 participants were presented with a Web-based questionnaire containing a short description of a dentist search scenario and the manipulated reviews for a fictitious dental physician. To investigate the proposed hypotheses, we carried out moderated regression analyses and a moderated mediation analysis using the PROCESS macro 2.11 for SPSS version 22. Results: Our analyses indicated that a higher number of reviews resulted in a more positive attitude toward the rated physician. The results of the regression model for attitude toward the physician suggest a positive main effect of the number of reviews (mean [low] 3.73, standard error [SE] 0.13, mean [high] 4.15, SE 0.13). We also observed an interaction effect with the style of the review—if the physician received only a few reviews, fact-oriented reviews (mean 4.09, SE 0.19) induced a more favorable attitude toward the physician compared to emotional reviews (mean 3.44, SE 0.19), but there was no such effect when the physician received many reviews. Furthermore, we found that review style also affected the perceived expertise of the reviewer. Fact-oriented reviews (mean 3.90, SE 0.13) lead to a higher perception of reviewer expertise compared to emotional reviews (mean 3.19, SE 0.13). However, this did not transfer to the attitude toward the physician. A similar effect of review style and number on the perceived credibility of the review was observed. While no differences between emotional and factual style were found if the physician received many reviews, a low number of reviews received lead to a significant difference in the perceived credibility, indicating that emotional reviews were rated less positively (mean 3.52, SE 0.18) compared to fact-oriented reviews (mean 4.15, SE 0.17). Our analyses also showed that perceived credibility of the review fully mediated the observed interaction effect on attitude toward the physician. Conclusions: Physician-rating websites are an interesting new source of information about the quality of health care from the patient’s perspective. This paper makes a unique contribution to an understudied area of research by providing some insights into how people evaluate online reviews of individual doctors. Information attributes, such as review style and review number, have an impact on the evaluation of the review and on the patient’s attitude toward the rated doctor. Further research is necessary to improve our understanding of the influence of such rating sites on the patient's choice of a physician.

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