JMIR Publications

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 4.5 for 2015

Recent Articles:

  • Twitter Discussions. Image sourced and copyright held by authors.

    Characterizing Twitter Discussions About HPV Vaccines Using Topic Modeling and Community Detection


    Background: In public health surveillance, measuring how information enters and spreads through online communities may help us understand geographical variation in decision making associated with poor health outcomes. Objective: Our aim was to evaluate the use of community structure and topic modeling methods as a process for characterizing the clustering of opinions about human papillomavirus (HPV) vaccines on Twitter. Methods: The study examined Twitter posts (tweets) collected between October 2013 and October 2015 about HPV vaccines. We tested Latent Dirichlet Allocation and Dirichlet Multinomial Mixture (DMM) models for inferring topics associated with tweets, and community agglomeration (Louvain) and the encoding of random walks (Infomap) methods to detect community structure of the users from their social connections. We examined the alignment between community structure and topics using several common clustering alignment measures and introduced a statistical measure of alignment based on the concentration of specific topics within a small number of communities. Visualizations of the topics and the alignment between topics and communities are presented to support the interpretation of the results in context of public health communication and identification of communities at risk of rejecting the safety and efficacy of HPV vaccines. Results: We analyzed 285,417 Twitter posts (tweets) about HPV vaccines from 101,519 users connected by 4,387,524 social connections. Examining the alignment between the community structure and the topics of tweets, the results indicated that the Louvain community detection algorithm together with DMM produced consistently higher alignment values and that alignments were generally higher when the number of topics was lower. After applying the Louvain method and DMM with 30 topics and grouping semantically similar topics in a hierarchy, we characterized 163,148 (57.16%) tweets as evidence and advocacy, and 6244 (2.19%) tweets describing personal experiences. Among the 4548 users who posted experiential tweets, 3449 users (75.84%) were found in communities where the majority of tweets were about evidence and advocacy. Conclusions: The use of community detection in concert with topic modeling appears to be a useful way to characterize Twitter communities for the purpose of opinion surveillance in public health applications. Our approach may help identify online communities at risk of being influenced by negative opinions about public health interventions such as HPV vaccines.

  • Table of contents image.

    The Top Chinese Mobile Health Apps: A Systematic Investigation


    Background: China’s mHealth market is on track to become a global leader by industry size. The Chinese mobile app market and health care system have peculiarities that distinguish them from other app markets. To date, Chinese mHealth apps have not been systematically investigated. Objective: The objective of this study was to provide an overview of Chinese mHealth apps as of December 2015. Methods: We identified and investigated the most downloaded apps from the iOS and Android platforms. For each app, we analyzed and recorded its main service offered, mHealth initiative, disease and specialty focus, app cost, target user, Web app availability, and emphasis on information security. Standard descriptive statistics were used. Results: A total of 234 apps met the inclusion criteria and were investigated. The apps targeting nonhealth care professionals focused on providing telemedicine and appointment-making services. The apps targeting health care professionals focused on education and peer reviewed articles. The most common disease-specific apps focused primarily on diabetes, hypertension, and hepatitis management. Most apps were free and available on both iOS and Android platforms. Conclusions: The primary mHealth initiatives targeted by the apps reflect Chinese patients’ demand for access to medical care. Disease-specific apps are also representative of disease prevalence in China. Government press releases suggest that new policies on the horizon may shift the industry.

  • Close-up of woman typing on keyboard of laptop. Source: Licensed under CC0 License.

    An Internet-Based Intervention for Depression in Primary Care in Spain: A Randomized Controlled Trial


    Background: Depression is the most prevalent cause of illness-induced disability worldwide. Face-to-face psychotherapeutic interventions for depression can be challenging, so there is a need for other alternatives that allow these interventions to be offered. One feasible alternative is Internet-based psychological interventions. This is the first randomized controlled trial (RCT) on the effectiveness of an Internet-based intervention on depression in primary health care in Spain. Objective: Our aim was to compare the effectiveness of a low-intensity therapist-guided (LITG) Internet-based program and a completely self-guided (CSG) Internet-based program with improved treatment as usual (iTAU) care for depression. Methods: Multicenter, three-arm, parallel, RCT design, carried out between November 2012 and January 2014, with a follow-up of 15 months. In total, 296 adults from primary care settings in four Spanish regions, with mild or moderate major depression, were randomized to LITG (n=96), CSG (n=98), or iTAU (n=102). Research completers at follow-up were 63.5%. The intervention was Smiling is Fun, an Internet program based on cognitive behavioral therapy. All patients received iTAU by their general practitioners. Moreover, LITG received Smiling is Fun and the possibility of psychotherapeutic support on request by email, whereas CSG received only Smiling is Fun. The main outcome was the Beck Depression Inventory-II at 3 months from baseline. Mixed-effects multilevel analysis for repeated measures were undertaken. Results: There was no benefit for either CSG [(B coefficient=-1.15; P=.444)] or LITG [(B=-0.71; P=.634)] compared to iTAU, at 3 months. There were differences at 6 months [iTAU vs CSG (B=-4.22; P=.007); iTAU vs LITG (B=-4.34; P=.005)] and 15 months [iTAU vs CSG (B=-5.10; P=.001); iTAU vs LITG (B=-4.62; P=.002)]. There were no differences between CSG and LITG at any time. Adjusted and intention-to-treat models confirmed these findings. Conclusions: An Internet-based intervention for depression combined with iTAU conferred a benefit over iTAU alone in the Spanish primary health care system. Trial Registration: NCT01611818; selectaction=Edit&uid=U0001NPQ&ts=2&cx=gctdh2&sid=S0003KJ6 (Archived by WebCite at

  • Image courtesy of Ambro at
Standard Licence.

    A Multirelational Social Network Analysis of an Online Health Community for Smoking Cessation


    Background: Online health communities (OHCs) provide a convenient and commonly used way for people to connect around shared health experiences, exchange information, and receive social support. Users often interact with peers via multiple communication methods, forming a multirelational social network. Use of OHCs is common among smokers, but to date, there have been no studies on users’ online interactions via different means of online communications and how such interactions are related to smoking cessation. Such information can be retrieved in multirelational social networks and could be useful in the design and management of OHCs. Objective: To examine the social network structure of an OHC for smoking cessation using a multirelational approach, and to explore links between subnetwork position (ie, centrality) and smoking abstinence. Methods: We used NetworkX to construct 4 subnetworks based on users’ interactions via blogs, group discussions, message boards, and private messages. We illustrated topological properties of each subnetwork, including its degree distribution, density, and connectedness, and compared similarities among these subnetworks by correlating node centrality and measuring edge overlap. We also investigated coevolution dynamics of this multirelational network by analyzing tie formation sequences across subnetworks. In a subset of users who participated in a randomized, smoking cessation treatment trial, we conducted user profiling based on users’ centralities in the 4 subnetworks and identified user groups using clustering techniques. We further examined 30-day smoking abstinence at 3 months postenrollment in relation to users’ centralities in the 4 subnetworks. Results: The 4 subnetworks have different topological characteristics, with message board having the most nodes (36,536) and group discussion having the highest network density (4.35×10−3). Blog and message board subnetworks had the most similar structures with an in-degree correlation of .45, out-degree correlation of .55, and Jaccard coefficient of .23 for edge overlap. A new tie in the group discussion subnetwork had the lowest probability of triggering subsequent ties among the same two users in other subnetworks: 6.33% (54,142/855,893) for 2-tie sequences and 2.13% (18,207/855,893) for 3-tie sequences. Users’ centralities varied across the 4 subnetworks. Among a subset of users enrolled in a randomized trial, those with higher centralities across subnetworks generally had higher abstinence rates, although high centrality in the group discussion subnetwork was not associated with higher abstinence rates. Conclusions: A multirelational approach revealed insights that could not be obtained by analyzing the aggregated network alone, such as the ineffectiveness of group discussions in triggering social ties of other types, the advantage of blogs, message boards, and private messages in leading to subsequent social ties of other types, and the weak connection between one’s centrality in the group discussion subnetwork and smoking abstinence. These insights have implications for the design and management of online social networks for smoking cessation.

  • Second international Critical Care Datathon. Image source: Copyright: MIT Critical Data and shared under a CC-BY license.

    Datathons and Software to Promote Reproducible Research


    Background: Datathons facilitate collaboration between clinicians, statisticians, and data scientists in order to answer important clinical questions. Previous datathons have resulted in numerous publications of interest to the critical care community and serve as a viable model for interdisciplinary collaboration. Objective: We report on an open-source software called Chatto that was created by members of our group, in the context of the second international Critical Care Datathon, held in September 2015. Methods: Datathon participants formed teams to discuss potential research questions and the methods required to address them. They were provided with the Chatto suite of tools to facilitate their teamwork. Each multidisciplinary team spent the next 2 days with clinicians working alongside data scientists to write code, extract and analyze data, and reformulate their queries in real time as needed. All projects were then presented on the last day of the datathon to a panel of judges that consisted of clinicians and scientists. Results: Use of Chatto was particularly effective in the datathon setting, enabling teams to reduce the time spent configuring their research environments to just a few minutes—a process that would normally take hours to days. Chatto continued to serve as a useful research tool after the conclusion of the datathon. Conclusions: This suite of tools fulfills two purposes: (1) facilitation of interdisciplinary teamwork through archiving and version control of datasets, analytical code, and team discussions, and (2) advancement of research reproducibility by functioning postpublication as an online environment in which independent investigators can rerun or modify analyses with relative ease. With the introduction of Chatto, we hope to solve a variety of challenges presented by collaborative data mining projects while improving research reproducibility.

  • Web based Well being interventions. Image taken by authors.

    Effectiveness of Web-Delivered Acceptance and Commitment Therapy in Relation to Mental Health and Well-Being: A Systematic Review and Meta-Analysis


    Background: The need for effective interventions to improve mental health and emotional well-being at a population level are gaining prominence both in the United Kingdom and globally. Advances in technology and widespread adoption of Internet capable devices have facilitated rapid development of Web-delivered psychological therapies. Interventions designed to manage a range of affective disorders by applying diverse therapeutic approaches are widely available. Objective: The main aim of this review was to evaluate the evidence base of acceptance and commitment therapy (ACT) in a Web-based delivery format. Method: A systematic review of the literature and meta-analysis was conducted. Two electronic databases were searched for Web-delivered interventions utilizing ACT for the management of affective disorders or well-being. Only Randomized Controlled Trials (RCTs) were included. Results: The search strategy identified 59 articles. Of these, 10 articles met the inclusion criteria specified. The range of conditions and outcome measures that were identified limited the ability to draw firm conclusions about the efficacy of Web-delivered ACT-based intervention for anxiety or well-being. Conclusions: ACT in a Web-based delivery format was found to be effective in the management of depression. Rates of adherence to study protocols and completion were high overall suggesting that this therapeutic approach is highly acceptable for patients and the general public.

  • Image Source: Thoughtful Walker, copyright Michael Coghlan,,
Licensed under Creative Commons Attribution cc-by 2.0

    Use and Appreciation of a Tailored Self-Management eHealth Intervention for Early Cancer Survivors: Process Evaluation of a Randomized Controlled Trial


    Background: A fully automated computer-tailored Web-based self-management intervention, Kanker Nazorg Wijzer (KNW [Cancer Aftercare Guide]), was developed to support early cancer survivors to adequately cope with psychosocial complaints and to promote a healthy lifestyle. The KNW self-management training modules target the following topics: return to work, fatigue, anxiety and depression, relationships, physical activity, diet, and smoking cessation. Participants were guided to relevant modules by personalized module referral advice that was based on participants’ current complaints and identified needs. Objective: The aim of this study was to evaluate the adherence to the module referral advice, examine the KNW module use and its predictors, and describe the appreciation of the KNW and its predictors. Additionally, we explored predictors of personal relevance. Methods: From the respondents (N=231; mean age 55.6, SD 11.5; 79.2% female [183/231]), 98.3% (227/231) were referred to one or more KNW modules (mean 2.9, SD 1.5), and 85.7% (198/231) of participants visited at least one module (mean 2.1, SD 1.6). Significant positive associations were found between the referral to specific modules (range 1-7) and the use of corresponding modules. The likelihoods of visiting modules were higher when respondents were referred to those modules by the module referral advice. Predictors of visiting a higher number of modules were a higher number of referrals by the module referral advice (β=.136, P=.009), and having a partner was significantly related with a lower number of modules used (β=-.256, P=.044). Overall appreciation was high (mean 7.5, SD 1.2; scale 1-10) and was significantly predicted by a higher perceived personal relevance (β=.623, P=.000). None of the demographic and cancer-related characteristics significantly predicted the perceived personal relevance. Results: The KNW in general and more specifically the KNW modules were well used and highly appreciated by early cancer survivors. Results indicated that the module referral advice might be a meaningful intervention component to guide the users in following a preferred selection of modules. These results indicate that the fully automated Web-based KNW provides personal relevant and valuable information and support for early cancer survivors. Therefore, this intervention can complement usual cancer aftercare and may serve as a first step in a stepped-care approach. Conclusions: The KNW in general and more specifically the KNW modules were well used and highly appreciated by early cancer survivors. Indications were found that the module referral advice might be a meaningful intervention component to guide the users in following a preferred selection of modules. These results indicate that the fully automated Web-based KNW provides personal relevant and valuable information and support for early cancer survivors. Therefore, this intervention can complement usual cancer aftercare and may serve as a first step in a stepped-care approach. Trial Registration: Nederlands Trial Register: NTR3375; (Archived by WebCite at

  • Image Source: Business Baby Pointing, copyright Paul Inkles,,
Licensed under Creative Commons Attribution cc-by 2.0

    An Evaluation and Ranking of Children’s Hospital Websites in the United States


    Background: Children’s hospitals are faced with the rising need for technological innovation. Their prospective health care consumers, who increasingly depend on the Web and social media for communication and consumer engagement, drive this need. As patients and family members navigate the Web presence of hospitals, it is important for these specialized organizations to present themselves and their services efficiently. Objective: The purpose of this study was to evaluate the website content of children’s hospitals in order to identify opportunities to improve website design and create benchmarks to judge improvement. Methods: All websites associated with a children’s hospital were identified using a census list of all children’s hospitals in the United States. In March of 2014, each website and its social media were evaluated using a Web crawler that provided a 5-dimensional assessment that included website accessibility, marketing, content, technology, and usability. The 5-dimensional assessment was scored on a scale ranging from 0 to 10 with positive findings rated higher on the scale. Websites were ranked by individual dimensions as well as according to their average ranking across all dimensions. Results: Mean scores of 153 websites ranged from 5.05 to 8.23 across all 5 dimensions. Results revealed that no website scored a perfect 10 on any dimension and that room exists for meaningful improvement. Conclusions: Study findings allow for the establishment of baseline benchmarks for tracking future website and social media improvements and display the need for enhanced Web-based consumer engagement for children’s hospitals.

  • Source:, CC Public Domain.

    Effectiveness of mHealth Interventions Targeting Health Care Workers to Improve Pregnancy Outcomes in Low- and Middle-Income Countries: A Systematic Review


    Background: Low- and middle-income countries (LMICs) face the highest burden of maternal and neonatal deaths. Concurrently, they have the lowest number of physicians. Innovative methods such as the exchange of health-related information using mobile devices (mHealth) may support health care workers in the provision of antenatal, delivery, and postnatal care to improve maternal and neonatal outcomes in LMICs. Objective: We conducted a systematic review evaluating the effectiveness of mHealth interventions targeting health care workers to improve maternal and neonatal outcomes in LMIC. Methods: The Cochrane Library, PubMed, EMBASE, Global Health Library, and Popline were searched using predetermined search and indexing terms. Quality assessment was performed using an adapted Cochrane Risk of Bias Tool. A strength, weakness, opportunity, and threat analysis was performed for each included paper. Results: A total of 19 studies were included for this systematic review, 10 intervention and 9 descriptive studies. mHealth interventions were used as communication, data collection, or educational tool by health care providers primarily at the community level in the provision of antenatal, delivery, and postnatal care. Interventions were used to track pregnant women to improve antenatal and delivery care, as well as facilitate referrals. None of the studies directly assessed the effect of mHealth on maternal and neonatal mortality. Challenges of mHealth interventions to assist health care workers consisted mainly of technical problems, such as mobile network coverage, internet access, electricity access, and maintenance of mobile phones. Conclusions: mHealth interventions targeting health care workers have the potential to improve maternal and neonatal health services in LMICs. However, there is a gap in the knowledge whether mHealth interventions directly affect maternal and neonatal outcomes and future research should employ experimental designs with relevant outcome measures to address this gap.

  • Image Source: Woman with laptop lying down in bed, copyright, Mecklenburg County., CC0 License.

    Evaluation of a Web-Based E-Learning Platform for Brief Motivational Interviewing by Nurses in Cardiovascular Care: A Pilot Study


    Background: Brief motivational interviewing (MI) can contribute to reductions in morbidity and mortality related to coronary artery disease, through health behavior change. Brief MI, unlike more intensive interventions, was proposed to meet the needs of clinicians with little spare time. While the provision of face-to-face brief MI training on a large scale is complicated, Web-based e-learning is promising because of the flexibility it offers. Objective: The primary objective of this pilot study was to examine the feasibility and acceptability of a Web-based e-learning platform for brief MI (MOTIV@CŒUR), which was evaluated by nurses in cardiovascular care. The secondary objective was to assess the preliminary effect of the training on nurses’ perceived brief MI skills and self-reported clinical use of brief MI. Methods: We conducted a single-group, pre-post pilot study involving nurses working in a coronary care unit to evaluate MOTIV@CŒUR, which is a Web-based e-learning platform for brief MI, consisting of two sessions lasting 30 and 20 minutes. MOTIV@CŒUR covers 4 real-life clinical situations through role-modeling videos showing nurse-client interactions. A brief introduction to MI is followed by role playing, during which a nurse practitioner evaluates clients’ motivation to change and intervenes according to the principles of brief MI. The clinical situations target smoking, medication adherence, physical activity, and diet. Nurses were asked to complete both Web-based training sessions asynchronously within 20 days, which allowed assessment of the feasibility of the intervention. Data regarding acceptability and preliminary effects (perceived skills in brief MI, and self-reported clinical use of conviction and confidence interventions) were self-assessed through Web-based questionnaires 30 days (±5 days) after the first session. Results: We enrolled 27 women and 4 men (mean age 37, SD 9 years) in March 2016. Of the 31 participants, 24 (77%, 95% CI 63%–91%) completed both sessions in ≤20 days. At 30 days, 28 of the 31 participants (90%) had completed at least one session. The training was rated as highly acceptable, with the highest scores observed for information quality (mean 6.26, SD 0.60; scale 0–7), perceived ease of use (mean 6.16, SD 0.78; scale 0–7), and system quality (mean 6.15, SD 0.58; scale 0–7). Posttraining scores for self-reported clinical use of confidence interventions were higher than pretraining scores (mean 34.72, SD 6.29 vs mean 31.48, SD 6.75, respectively; P=.03; scale 10–50). Other results were nonsignificant. Conclusions: Brief MI training using a Web-based e-learning platform including role-modeling videos is both feasible and acceptable according to cardiovascular care nurses. Further research is required to evaluate the e-learning platform in a randomized controlled trial. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): 16510888; (Archived by WebCite at

  • Image Source: Tablet love, copyright, Sascha Müsse., Licensed under Creative Commons Attribution cc-by 2.0

    Efficacy of Internet-Based Self-Monitoring Interventions on Maternal and Neonatal Outcomes in Perinatal Diabetic Women: A Systematic Review and Meta-Analysis


    Background: Self-monitoring using the Internet offers new opportunities to engage perinatal diabetic women in self-management to reduce maternal and neonatal complications. Objective: This review aims to synthesize the best available evidence to evaluate the efficacy of Internet-based self-monitoring interventions in improving maternal and neonatal outcomes among perinatal diabetic women. Methods: The review was conducted using Cochrane Central Register of Controlled Trials, PubMed, EMBASE, Cumulative Index to Nursing and Allied Health Literature, PsyINFO, Scopus, and ProQuest Dissertations and Theses to search for English-language research studies without any year limitation. A risk of bias table was used to assess methodological quality. Meta-analysis was performed with RevMan software. Cochran Q and I2 tests were used to assess heterogeneity. The overall effect was assessed using z tests at P<.05. Of the 438 studies identified through electronic searches and reference lists, nine experimental studies from 10 publications were selected. Results: Half of the selected studies showed low risk of bias and comprised 852 perinatal diabetic women in six countries. The meta-analysis revealed that Internet-based self-monitoring interventions significantly decreased the level of maternal glycated hemoglobin A1c (z=2.23, P=.03) compared to usual care among perinatal diabetic women at postintervention. Moreover, Internet-based self-monitoring interventions significantly decreased the cesarean delivery rate (z=2.23, P=.03) compared to usual care among the mixed group at postintervention. Conclusions: This review shows neonatal or other maternal outcomes are similar between Internet-based self-monitoring interventions and usual diabetes care among perinatal diabetic women. The long-term effects of the intervention must be confirmed in future studies using randomized controlled trials and follow-up data.

  • Image Source: Verona Cycling, copyright, Tejvan Pettinger., Licensed under Creative Commons Attribution cc-by 2.0

    Web-Based Video-Coaching to Assist an Automated Computer-Tailored Physical Activity Intervention for Inactive Adults: A Randomized Controlled Trial


    Background: Web-based physical activity interventions that apply computer tailoring have shown to improve engagement and behavioral outcomes but provide limited accountability and social support for participants. It is unknown how video calls with a behavioral expert in a Web-based intervention will be received and whether they improve the effectiveness of computer-tailored advice. Objective: The purpose of this study was to determine the feasibility and effectiveness of brief video-based coaching in addition to fully automated computer-tailored advice in a Web-based physical activity intervention for inactive adults. Methods: Participants were assigned to one of the three groups: (1) tailoring + video-coaching where participants received an 8-week computer-tailored Web-based physical activity intervention (“My Activity Coach”) including 4 10-minute coaching sessions with a behavioral expert using a Web-based video-calling program (eg, Skype; n=52); (2) tailoring-only where participants received the same intervention without the coaching sessions (n=54); and (3) a waitlist control group (n=45). Demographics were measured at baseline, intervention satisfaction at week 9, and physical activity at baseline, week 9, and 6 months by Web-based self-report surveys. Feasibility was analyzed by comparing intervention groups on retention, adherence, engagement, and satisfaction using t tests and chi-square tests. Effectiveness was assessed using linear mixed models to compare physical activity changes between groups. Results: A total of 23 tailoring + video-coaching participants, 30 tailoring-only participants, and 30 control participants completed the postintervention survey (83/151, 55.0% retention). A low percentage of tailoring + video-coaching completers participated in the coaching calls (11/23, 48%). However, the majority of those who participated in the video calls were satisfied with them (5/8, 71%) and had improved intervention adherence (9/11, 82% completed 3 or 4 modules vs 18/42, 43%, P=.01) and engagement (110 minutes spent on the website vs 78 minutes, P=.02) compared with other participants. There were no overall retention, adherence, engagement, and satisfaction differences between tailoring + video-coaching and tailoring-only participants. At 9 weeks, physical activity increased from baseline to postintervention in all groups (tailoring + video-coaching: +150 minutes/week; tailoring only: +123 minutes/week; waitlist control: +34 minutes/week). The increase was significantly higher in the tailoring + video-coaching group compared with the control group (P=.01). No significant difference was found between intervention groups and no significant between-group differences were found for physical activity change at 6 months. Conclusions: Only small improvements were observed when video-coaching was added to computer-tailored advice in a Web-based physical activity intervention. However, combined Web-based video-coaching and computer-tailored advice was effective in comparison with a control group. More research is needed to determine whether Web-based coaching is more effective than stand-alone computer-tailored advice. Trial Registration: Australian New Zealand Clinical Trials Registry (ACTRN): 12614000339651; (Archived by WebCite at

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  • An Online Group-based Self-tracking Program to Increase Fruit and Vegetable Consumption: The Effects of Demographic Similarity, Social Modeling and Performance Discrepancy

    Date Submitted: Aug 23, 2016

    Open Peer Review Period: Aug 24, 2016 - Oct 19, 2016

    Background: Self-tracking allows people to reflect on their health behaviors and make improvements accordingly to achieve a health goal. Web-based interventions with a self-tracking component have bee...

    Background: Self-tracking allows people to reflect on their health behaviors and make improvements accordingly to achieve a health goal. Web-based interventions with a self-tracking component have been found to be effective in promoting adults’ fruit and vegetable consumptions (FVC). However, these interventions primarily focus on individual- rather than group-based self-tracking. The rise of social media technologies enables sharing and comparing self-tracking records in a group context. Therefore, we develop an online group-based self-tracking program to promote FVC in early young adults, who are at an important stage of developing food patterns that will affect their future. Objective: This study aims to examine (1) the effectiveness of online group-based self-tracking on FVC, and (2) composition characteristics of online self-tracking groups that make the group more effective in promoting FVC in early young adults. Methods: During a 4-week web-based experiment, 113 college students self-tracked their FVC either individually (i.e., the control group) or in an online group characterized by a 2 (demographic similarity: demographically similar vs. demographically diverse) × 2 (social modeling: incremental-change vs. ideal-change) experimental design. Each online group consisted of one focal participant and three confederates as group members whose demographics and FVC were manipulated to create the four treatment groups. Self-reported FVC were assessed using the food frequency questionnaire at baseline and after the 4-week experiment, and were recorded using participants’ self-tracking messages during the 4-week experiment. Results: Participants who self-tracked their FVC collectively with other group members consumed more FV than participants who self-tracked their FVC individually, P = .02, η2 = .08, controlling for demographics, BMI, baseline FVC and meal plan enrollment. The results did not show significant main effects of demographic similarity (P = .47) or types of social modeling (P = .54) in making self-tracking groups more effective in promoting FVC. However, additional analyses revealed the main effect of performance discrepancy (i.e., difference in FVC between a focal participant and his/her group members during the 4-week experiment), such that participants who had a low performance discrepancy from other group members consumed greater FVC than participants who had a high performance discrepancy from other group members, P = .003, η2 = .16. A mediation test showed that low performance discrepancy led to greater downward contrast (b = -0.78, CI = [-2.44, -0.15]), which in turn, led to greater FVC. Conclusions: Online self-tracking groups with models consistently increasing their FVC were more effective than self-tracking alone in promoting FVC for early young adults. Low performance discrepancy from models would lead to downward contrast, which in turn, increased participants’ FVC over time. The study highlighted social comparison processes in online groups that allow for sharing personal health information.

  • Developing a Veterans’ Health Information Technology Systems Matrix Using Participatory Methods

    Date Submitted: Aug 24, 2016

    Open Peer Review Period: Aug 24, 2016 - Sep 2, 2016

    Background: The Department of Veterans Affairs (VA) has developed various health information technology (HIT) resources to provide accessible veteran-centered health care. Currently, the VA is undergo...

    Background: The Department of Veterans Affairs (VA) has developed various health information technology (HIT) resources to provide accessible veteran-centered health care. Currently, the VA is undergoing a major re-organization of VA HIT to develop a fully integrated system to meet consumer needs. While extensive system documentation exists for various VA HIT systems, a more centralized and integrated view across systems, with clear documentation, is needed in order to support effective analysis, strategy, planning, and use. Such a tool would enable a novel view of what is currently available and support identifying and effectively capturing the consumer’s vision for the future. Objective: The objective of this article is to present the VA HIT systems matrix (HITSM); a novel tool designed to describe the existing VA HIT system and identify consumers’ vision for the future of an integrated VA HIT system. Methods: This study utilized an expert panel and veteran focus groups with self-administered surveys. The study employed participatory research methods to define the current system and understand how stakeholders and veterans envision the future of VA HIT and interface design (e.g. look, feel, and function). Results: The HITSM was developed with input from 47 Veterans, an informal caregiver, and an expert panel to provide a descriptive inventory of existing and emerging VA HIT. There are four worksheets that present data, titled: (1) Access and Function; (2) Benefits and Barriers; (3) System Preferences; and (4) Tasks. Within each worksheet there is a two-axis inventory. The VA’s existing and emerging HIT platforms (e.g. My HealtheVet, Mobile Health, VetLink Kiosks, Telehealth); My HealtheVet features (e.g. Blue Button, Secure Messaging, Appointment Reminders, Prescription Refill, Vet Library, Spotlight, Vitals Tracker); and non-VA platforms (e.g. Phone/Smartphone, Texting, non-VA Mobile Applications, non-VA Mobile Electronic Devices, non-VA Websites) are organized by row. Columns are titled with thematic and functional domains (e.g. access, function, benefits, barriers, authentication, delegation, user tasks). Cells for each sheet include descriptions and details that reflect factors relevant to domains and the topic of each worksheet. Conclusions: The current work provides documentation of the current VA HIT system and efforts for consumers’ vision of an integrated system redesign. The HITSM provides a consumer preference blueprint to inform the current VA HIT system and the vision for future development.

  • Redirecting behavioural cues using technology: Is there a role for the use of social media in conjunction with activity trackers?

    Date Submitted: Aug 18, 2016

    Open Peer Review Period: Aug 23, 2016 - Oct 18, 2016

    Recent work by Cole-Lewis and colleagues explored the use of health promotion tools within social media to better understand complex network analyses. However, there is a lack of evidence on the use o...

    Recent work by Cole-Lewis and colleagues explored the use of health promotion tools within social media to better understand complex network analyses. However, there is a lack of evidence on the use of social media and activity trackers in conjunction to augment health behaviours. This is a novel strategy and we propose its use in combating the growing obesity epidemic.

  • Supervised machine learning algorithms can classify open-text feedback of doctor performance with human-level accuracy

    Date Submitted: Aug 23, 2016

    Open Peer Review Period: Aug 23, 2016 - Oct 18, 2016

    Background: Machine learning techniques may be an efficient and effective way to classify open text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing profess...

    Background: Machine learning techniques may be an efficient and effective way to classify open text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective: To evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to signal differences in doctors’ professional performance in the UK. Methods: We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinician’s colleagues using the GMC Colleague Questionnaire. We coded comments into five global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained machine learning algorithms to classify doctors and assessed their performance using several training samples. We evaluated doctor performance using the GMC Colleague Questionnaire (GMC-CQ) and compared scores between doctors with different classifications using t-tests. Results: Individual algorithm performance was high (range F=0.80 to 0.85). Inter-rater agreement between the algorithms and the human coder was highest for codes relating to ‘popular’ (recall =.97), ‘innovator’ (recall =.98), and ‘respected’ (recall =.87) codes and was lower for the ‘interpersonal’ (recall =.80) and ‘professional’ (recall =.82) codes. Four-fold cross-validation demonstrated similar performance in each analysis. When combined into an ensemble of multiple algorithms, mean human-computer inter-rater agreement was .87. Doctors who were classified as ‘respected’, ‘professional’, and ‘interpersonal’ had higher scores on the GMC Colleague Questionnaire compared to doctors who were not classified (P<.05). Scores did not vary between doctors who were rated as popular or innovative and those who were not rated at all (P>.05). Conclusions: Machine learning algorithms can classify open-text feedback of doctor performance into multiple themes derived by human raters with high performance. Colleague open-text comments that signal respect, professionalism, and being interpersonal may be key indicators of doctor’s performance.

  • A smarter pathway for delivering cue exposure therapy? The design and development of a smartphone application targeting alcohol use disorder.

    Date Submitted: Aug 19, 2016

    Open Peer Review Period: Aug 19, 2016 - Oct 14, 2016

    Background: While the number of alcohol-related treatments in app stores is proliferating, none of them are based on a psychological framework and supported by empirical evidence. Cue exposure treatme...

    Background: While the number of alcohol-related treatments in app stores is proliferating, none of them are based on a psychological framework and supported by empirical evidence. Cue exposure treatment (CET) with urge-specific coping skills (USCS) is often used in Danish treatment settings. It is an evidence-based psychological approach that focuses on promoting `confrontation with alcohol cues’ as a means of reducing urges and the likelihood of relapse. Objective: This paper describes the design and development of a CET-based smartphone application; an innovative delivery pathway for treating alcohol use disorder (AUD). Methods: The treatment is based on Monty and co-workers’ manual for CET with USCS (2002). It was created by a multidisciplinary team of psychiatrists, psychologists, engineers and graphic designers as well as patients with AUD. A database was developed for the purpose of registering and monitoring training activities. A final version of the CET app and database was developed after several user tests. Results: The final version of the CET app includes: an introduction, 4 sessions featuring USCS, 8 alcohol exposure videos promoting the use of one of the USCS, and a results component providing an overview of training activities and potential progress. Real-time urges are measured before, during and after exposure to alcohol cues and are registered in the app together with other training activity variables. Data packages are continuously sent in encrypted form to an external database, and will be merged with other data (in an internal database) in the future. Conclusions: The CET smartphone app is currently being tested in a large-scale, randomized controlled trial with the aim of clarifying whether it can be classified as an evidence-based treatment solution. The app has the potential to augment the reach of psychological treatment for AUD. Clinical Trial: ID: NCT02298751 Registration date: 6 November 2014

  • Disease monitoring and health campaign evaluation using Internet search activities for HIV/AIDS, stroke, colorectal cancer and marijuana use in Canada: A Retrospective Observational Study

    Date Submitted: Aug 16, 2016

    Open Peer Review Period: Aug 16, 2016 - Oct 11, 2016

    Background: Infodemiology can offer practical and feasible health research applications through the practice of studying information available on the Internet. Google Trends provides publically access...

    Background: Infodemiology can offer practical and feasible health research applications through the practice of studying information available on the Internet. Google Trends provides publically accessible information regarding search behaviours in a population, which may be studied and used for health campaign evaluation and disease monitoring. Additional studies examining the use and effectiveness of Google Trends for these purposes remain warranted. Objective: The study explored the use of infodemiology in the context of health campaign evaluation and chronic disease monitoring. It was hypothesized that following a launch of the campaign, there would be an increase in information seeking behaviour on the Internet. Secondly, increasing and decreasing disease patterns in a population would be associated with the Internet search activity trends. This study examined four different diseases: HIV, stroke, colorectal cancer and marijuana use. Methods: Using Google Trends, relative search volume data were collected throughout the period of February 2004 to January 2015. Campaign information and disease statistics were obtained from governmental publications. Search activity trends were graphed and assessed with disease trends and the campaign interval. Pearson product correlation statistics and joinpoint methodology analyses were used to determine significance. Results: Disease patterns and online activity across all four diseases were significantly correlated: HIV (r=0.36, p<0.001), stroke (r=0.40, p<0.001), colorectal cancer (r= -0.41, p<0.001) and substance use (r=0.64, p<0.001). Visual inspection and the joinpoint analysis showed significant correlations for the campaigns on colorectal cancer and substance use in stimulating online search activity. No significant correlations were observed for the campaigns on stroke and HIV regarding Internet search activity. Conclusions: The use of infoveillance shows promises as an alternative and inexpensive solution to disease surveillance and health campaign evaluation. Further research is needed to understand Google Trends as a valid and reliable tool for health research.