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 4.7 for 2013
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Promoting a hand hygiene program via social media

Background: Hand hygiene is an important component in infection control to protect patient safety and reduce healthcare associated infection. Objective: Evaluate the efficacy of different social media on promotion of a hand hygiene (HH) program. Methods: The observational study was conducted from May 5 to December 31, 2014 at a 2600-bed tertiary care hospital. A 3 min video of a HH campaign in 8 languages was posted to YouTube. The Chinese version was promoted through three platforms: the hospital website, the hospital group e-mail, and the Facebook site of a well-known internet illustrator. The video traffic was analyzed via Google Analytics. HH compliance was measured in November of 2013 and 2014. Results: There were 5,252 views of the video, mainly of the Chinese-language version (3,509/5,252, 66.8%). The NTUH web site had 24,000 subscribers and 151 of them viewed the video (connection rate: 0.6%, 151/24,000); There were 9,967 users of the hospital e-mail group and the connection rate was 0.9% (91/9,967). The connection rate was 6.2% (807/13,080) from Facebook, significantly higher than the other 2 venues (both p < 0.001). HH compliance sustained from 83.7% (473/565) in 2013 to 86.7% (589/679) in 2014 (p = 0.13) among all HCWs. Conclusions: Facebook had the highest connection rate in the HH video campaign. The use of novel social media such as Facebook should be considered for future programs that promote HH and other healthy behaviors.

2015-07-04

Thomson Reuters has published the Journal Citation Reports (JCR) with its Journal Impact Factors for 2015. The Journal Impact Factor 2015 is defined as the number of citations in 2014 to the citations to articles published in the previous 2 years (2012-2013), divided by the number of articles published during that time. The Journal Impact Factor is a metric of excellence for a journal, it is not an article-level metric.

The Impact Factor is an increasingly controversial metric due its frequent misuse, e.g. administrators comparing the "raw" impact factor score across disciplines. This disadvantages journals in smaller disciplines such as medical informatics, which traditionally have less citations than for example multidisciplinary or general medicine journals. As one innovation, Thomson Reuters is now ranking journals by quartile (Q1, Q2, Q3, Q4), within their discipline.

While we at JMIR discourage obsession over the journal impact factor (in particular if abused as proxy to assess the quality of individual articles), our ranking in the JCR is an important validation that even as small open access publisher we can compete with journals published by publishing giants.

JMIR continues to be ranked in the first quartile (Q1) in both of it's disciplines, medical informatics (Q1) and health services research (Q1).

However, even these category-specific rankings are sometimes questionable, in particular for multidisciplinary journals such as JMIR which fit into more than the categories selected by the JCR editors. Moreover, the current JCR categories sometimes lump together journals which do not belong together, for example statistics journals are part of the medical informatics category, and oddly enough, the journal Statistical Methods in Medical Research is now suddenly the top-ranked journal in the medical informatics category.

It may therefore make more sense to compare JMIR against other leading multidisciplinary open access journals, as shown below. However, once again, the impact factor should not be the only determining factor when submitting an article. The journal scope and audience (who reads the journal) are equally important if one wants to maximize impact and influence of an article on key stakeholders and researchers, which is not measurable by citations (perhaps better measured with social media uptake and altmetrics).

We continue to encourage our authors to consider the full range of JMIR journals when submitting an article and consider the scope of the journal and the topic of the article.

Quiz: Which of the following #openaccess journals has the highest impact factor:

1) PloS One,

2) PeerJ,

3) BMC MDM,

4) BMJ Open,

5) JMIR 

(scroll down for the answer)

Journal Quartile (in their category)   Impact Factor 2015
1. JMIR Q1, Q1 3.428
2. PloS One Q1 3.234
3. BMJ Open Q2 2.271
4. PeerJ Q1 2.112
5. BMC Med Inform Med Dec Mk Q2 1.830

Beyond the Journal Impact Factor

Authors care (and should care) about other metrics/ratings such as author satisfaction with reviews and turnaround times, as for example evaluated by SciRevJMIR is ranked highly here as well (compare for example against PlosOne ratings).

scirev ranking of JMIR vs PlosOne

Other metrics to look at are the twimpact factor (social media impact) as well as post-publication dissemination activies by the publisher (JMIR is using TrendMD to promote published articles across other publishers such as BMJ and the JAMA network).

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Recent Articles:

  • This is a screenshot from MoodGYM.

    Predictors of Response to Web-Based Cognitive Behavioral Therapy With High-Intensity Face-to-Face Therapist Guidance for Depression: A Bayesian Analysis

    Abstract:

    Background: Several studies have demonstrated the effect of guided Internet-based cognitive behavioral therapy (ICBT) for depression. However, ICBT is not suitable for all depressed patients and there is a considerable level of nonresponse. Research on predictors and moderators of outcome in ICBT is inconclusive. Objective: This paper explored predictors of response to an intervention combining the Web-based program MoodGYM and face-to-face therapist guidance in a sample of primary care patients with mild to moderate depressive symptoms. Methods: Participants (N=106) aged between 18 and 65 years were recruited from primary care and randomly allocated to a treatment condition or to a delayed treatment condition. The intervention included the Norwegian version of the MoodGYM program, face-to-face guidance from a psychologist, and reminder emails. In this paper, data from the treatment phase of the 2 groups was merged to increase the sample size (n=82). Outcome was improvement in depressive symptoms during treatment as assessed with the Beck Depression Inventory-II (BDI-II). Predictors included demographic variables, severity variables (eg, number of depressive episodes and pretreatment depression and anxiety severity), cognitive variables (eg, dysfunctional thinking), module completion, and treatment expectancy and motivation. Using Bayesian analysis, predictors of response were explored with a latent-class approach and by analyzing whether predictors affected the slope of response. Results: A 2-class model distinguished well between responders (74%, 61/82) and nonresponders (26%, 21/82). Our results indicate that having had more depressive episodes, being married or cohabiting, and scoring higher on a measure of life satisfaction had high odds for positively affecting the probability of response. Higher levels of dysfunctional thinking had high odds for a negative effect on the probability of responding. Prediction of the slope of response yielded largely similar results. Bayes factors indicated substantial evidence that being married or cohabiting predicted a more positive treatment response. The effects of life satisfaction and number of depressive episodes were more uncertain. There was substantial evidence that several variables were unrelated to treatment response, including gender, age, and pretreatment symptoms of depression and anxiety. Conclusions: Treatment response to ICBT with face-to-face guidance may be comparable across varying levels of depressive severity and irrespective of the presence and severity of comorbid anxiety. Being married or cohabiting, reporting higher life satisfaction, and having had more depressive episodes may predict a more favorable response, whereas higher levels of dysfunctional thinking may be a predictor of poorer response. More studies exploring predictors and moderators of Internet-based treatments are needed to inform for whom this treatment is most effective. Clinical Trial: Australian New Zealand Clinical Trials Registry number: ACTRN12610000257066; https://www.anzctr.org.au/trial_view.aspx?id=335255 (Archived by WebCite at http://www.webcitation.org/6GR48iZH4).

  • Swabbing participant. (cc) Platteau et al. CC-BY-SA 2.0, please cite as (http://www.jmir.org/article/viewFile/4384/1/63730).

    Swab2know: An HIV-Testing Strategy Using Oral Fluid Samples and Online Communication of Test Results for Men Who Have Sex With Men in Belgium

    Abstract:

    Background: As HIV remains a public health concern, increased testing among those at risk for HIV acquisition is important. Men who have sex with men (MSM) are the most important group for targeted HIV testing in Europe. Several new strategies have been developed and implemented to increase HIV-testing uptake in this group, among them the Swab2know project. Objective: In this project, we aim to assess the acceptability and feasibility of outreach and online HIV testing using oral fluid samples as well as Web-based delivery of test results. Methods: Sample collection happened between December 2012 and April 2014 via outreach and online sampling among MSM. Test results were communicated through a secured website. HIV tests were executed in the laboratory. Each reactive sample needed to be confirmed using state-of-the-art confirmation procedures on a blood sample. Close follow-up of participants who did not pick up their results, and those with reactive results, was included in the protocol. Participants were asked to provide feedback on the methodology using a short survey. Results: During 17 months, 1071 tests were conducted on samples collected from 898 men. Over half of the samples (553/1071, 51.63%) were collected during 23 outreach sessions. During an 8-month period, 430 samples out of 1071 (40.15%) were collected from online sampling. Additionally, 88 samples out of 1071 (8.22%) were collected by two partner organizations during face-to-face consultations with MSM and male sex workers. Results of 983 out of 1071 tests (91.78%) had been collected from the website. The pickup rate was higher among participants who ordered their kit online (421/430, 97.9%) compared to those participating during outreach activities (559/641, 87.2%; P<.001). MSM participating during outreach activities versus online participants were more likely to have never been tested before (17.3% vs 10.0%; P=.001) and reported more sexual partners in the 6 months prior to participation in the project (mean 7.18 vs 3.23; P<.001). A total of 20 participants out of 898 (2.2%) were confirmed HIV positive and were linked to care. Out of 1071 tests, 28 (2.61%) with a weak reactive result could not be confirmed, and were thereby classified as false reactive results. Most of the 388 participants who completed posttest surveys (388/983, 39.5%) were very positive about their experience. The vast majority (371/388, 95.6%) were very satisfied, while 17 out of 388 (4.4%) reported mixed feelings. Conclusions: Despite a high yield and a considerable number of false reactive results, satisfaction was high among participants. The project helped us to reach the target population, both in numbers of tests executed and in newly diagnosed HIV infections. Further optimization should be considered in the accuracy of the test, the functionalities of the website (including an online counseling tool), and in studying the cost effectiveness of the methodology.

  • Example failures that resulted from the application of MetaMap to process patient-generated text in an online health community (blue terms represent patient-generated text; black terms represent MetaMap’s interpretation; and red terms represent failure type).

    Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text

    Abstract:

    Background: The prevalence and value of patient-generated health text are increasing, but processing such text remains problematic. Although existing biomedical natural language processing (NLP) tools are appealing, most were developed to process clinician- or researcher-generated text, such as clinical notes or journal articles. In addition to being constructed for different types of text, other challenges of using existing NLP include constantly changing technologies, source vocabularies, and characteristics of text. These continuously evolving challenges warrant the need for applying low-cost systematic assessment. However, the primarily accepted evaluation method in NLP, manual annotation, requires tremendous effort and time. Objective: The primary objective of this study is to explore an alternative approach—using low-cost, automated methods to detect failures (eg, incorrect boundaries, missed terms, mismapped concepts) when processing patient-generated text with existing biomedical NLP tools. We first characterize common failures that NLP tools can make in processing online community text. We then demonstrate the feasibility of our automated approach in detecting these common failures using one of the most popular biomedical NLP tools, MetaMap. Methods: Using 9657 posts from an online cancer community, we explored our automated failure detection approach in two steps: (1) to characterize the failure types, we first manually reviewed MetaMap’s commonly occurring failures, grouped the inaccurate mappings into failure types, and then identified causes of the failures through iterative rounds of manual review using open coding, and (2) to automatically detect these failure types, we then explored combinations of existing NLP techniques and dictionary-based matching for each failure cause. Finally, we manually evaluated the automatically detected failures. Results: From our manual review, we characterized three types of failure: (1) boundary failures, (2) missed term failures, and (3) word ambiguity failures. Within these three failure types, we discovered 12 causes of inaccurate mappings of concepts. We used automated methods to detect almost half of 383,572 MetaMap’s mappings as problematic. Word sense ambiguity failure was the most widely occurring, comprising 82.22% of failures. Boundary failure was the second most frequent, amounting to 15.90% of failures, while missed term failures were the least common, making up 1.88% of failures. The automated failure detection achieved precision, recall, accuracy, and F1 score of 83.00%, 92.57%, 88.17%, and 87.52%, respectively. Conclusions: We illustrate the challenges of processing patient-generated online health community text and characterize failures of NLP tools on this patient-generated health text, demonstrating the feasibility of our low-cost approach to automatically detect those failures. Our approach shows the potential for scalable and effective solutions to automatically assess the constantly evolving NLP tools and source vocabularies to process patient-generated text.

  • Scale from (http://www.bing.com/images/search?pq=balance+scale&sc=8-12&sp=-1&sk=&sid=1373CFFC4B7B46F290C84C34D0591A45&q=balance+Scale&qft=+filterui:license-L2_L3&FORM=R5IR42); free to modify, share and used commercially. Pills are from Microsoft clipart.

    Assessment of Web-Based Consumer Reviews as a Resource for Drug Performance

    Abstract:

    Background: Some health websites provide a public forum for consumers to post ratings and reviews on drugs. Drug reviews are easily accessible and comprehensible, unlike clinical trials and published literature. Because the public increasingly uses the Internet as a source of medical information, it is important to know whether such information is reliable. Objective: We aim to examine whether Web-based consumer drug ratings and reviews can be used as a resource to compare drug performance. Methods: We analyzed 103,411 consumer-generated reviews on 615 drugs used to treat 249 disease conditions from the health website WebMD. Statistical analysis identified 427 drug pairs from 24 conditions for which two drugs treating the same condition had significantly and substantially different satisfaction ratings (with at least a half-point difference between Web-based ratings and P<.01). PubMed and Google Scholar were searched for publications that were assessed for concordance with findings online. Results: Scientific literature was found for 77 out of the 427 drug pairs and compared to findings online. Nearly two-thirds (48/77, 62%) of the online drug trends with at least a half-point difference in online ratings were supported by published literature (P=.02). For a 1-point online rating difference, the concordance rate increased to 68% (15/22) (P=.07). The discrepancies between scientific literature and findings online were further examined to obtain more insights into the usability of Web-based consumer-generated reviews. We discovered that (1) drugs with FDA black box warnings or used off-label were rated poorly in Web-based reviews, (2) drugs with addictive properties were rated higher than their counterparts in Web-based reviews, and (3) second-line or alternative drugs were rated higher. In addition, Web-based ratings indicated drug delivery problems. If FDA black box warning labels are used to resolve disagreements between publications and online trends, the concordance rate increases to 71% (55/77) (P<.001) for a half-point rating difference and 82% (18/22) for a 1-point rating difference (P=.002). Our results suggest that Web-based reviews can be used to inform patients’ drug choices, with certain caveats. Conclusions: Web-based reviews can be viewed as an orthogonal source of information for consumers, physicians, and drug manufacturers to assess the performance of a drug. However, one should be cautious to rely solely on consumer reviews as ratings can be strongly influenced by the consumer experience.

  • Zombies Run - (c) Six to Start (fair Use).

    Apps for IMproving FITness and Increasing Physical Activity Among Young People: The AIMFIT Pragmatic Randomized Controlled Trial

    Abstract:

    Background: Given the global prevalence of insufficient physical activity (PA), effective interventions that attenuate age-related decline in PA levels are needed. Mobile phone interventions that positively affect health (mHealth) show promise; however, their impact on PA levels and fitness in young people is unclear and little is known about what makes a good mHealth app. Objective: The aim was to determine the effects of two commercially available smartphone apps (Zombies, Run and Get Running) on cardiorespiratory fitness and PA levels in insufficiently active healthy young people. A second aim was to identify the features of the app design that may contribute to improved fitness and PA levels. Methods: Apps for IMproving FITness (AIMFIT) was a 3-arm, parallel, randomized controlled trial conducted in Auckland, New Zealand. Participants were recruited through advertisements in electronic mailing lists, local newspapers, flyers posted in community locations, and presentations at schools. Eligible young people aged 14-17 years were allocated at random to 1 of 3 conditions: (1) use of an immersive app (Zombies, Run), (2) use of a nonimmersive app (Get Running), or (3) usual behavior (control). Both smartphone apps consisted of a fully automated 8-week training program designed to improve fitness and ability to run 5 km; however, the immersive app featured a game-themed design and narrative. Intention-to-treat analysis was performed using data collected face-to-face at baseline and 8 weeks, and all regression models were adjusted for baseline outcome value and gender. The primary outcome was cardiorespiratory fitness, objectively assessed as time to complete the 1-mile run/walk test at 8 weeks. Secondary outcomes were PA levels (accelerometry and self-reported), enjoyment, psychological need satisfaction, self-efficacy, and acceptability and usability of the apps. Results: A total of 51 participants were randomized to the immersive app intervention (n=17), nonimmersive app intervention (n=16), or the control group (n=18). The mean age of participants was 15.7 (SD 1.2) years; participants were mostly NZ Europeans (61%, 31/51) and 57% (29/51) were female. Overall retention rate was 96% (49/51). There was no significant intervention effect on the primary outcome using either of the apps. Compared to the control, time to complete the fitness test was –28.4 seconds shorter (95% CI –66.5 to 9.82, P=.20) for the immersive app group and –24.7 seconds (95% CI –63.5 to 14.2, P=.32) for the nonimmersive app group. No significant intervention effects were found for secondary outcomes. Conclusions: Although apps have the ability to increase reach at a low cost, our pragmatic approach using readily available commercial apps as a stand-alone instrument did not have a significant effect on fitness. However, interest in future use of PA apps is promising and highlights a potentially important role of these tools in a multifaceted approach to increase fitness, promote PA, and consequently reduce the adverse health outcomes associated with insufficient activity. Trial Registration: Australian New Zealand Clinical Trials Registry: ACTRN12613001030763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12613001030763 (Archived by WebCite at http://www.webcitation.org/6aasfJVTJ).

  • Screenshot of http://www.gofor2and5.com.au.

    Who Uses the Internet as a Source of Nutrition and Dietary Information? An Australian Population Perspective

    Abstract:

    Background: The Internet contains a plethora of nutrition information. Health organizations are increasingly using the Internet to deliver population-wide health information and interventions. Effective interventions identify their target population and their needs; however, little is known about use of the Internet as a source of nutrition information. Objective: The aim was to assess the change in prevalence and demographic characteristics of Western Australian adults accessing the Internet as a source of nutrition information and identify specific information needs. Methods: Data were pooled from the Western Australian Department of Health’s 3-yearly Nutrition Monitoring Survey Series telephone survey between 1995 and 2012 of 7044 participants aged 18 to 64 years. Outcome variables were the main sources of nutrition information used in the last year and yes/no responses to 4 suggestions to what would make it easier to eat a healthy diet. Sociodemographic variables were collected. Results: The proportion of respondents using the Internet for nutrition information increased from <1% in 1995-2001 to 9.1% in 2004 and 33.7% in 2012. Compared to 2004, logistic regression showed that the odds of using the Internet for this information increased significantly in 2009 (OR 2.84, 95% CI 2.07-3.88) and 2012 (OR 5.20, 95% CI 3.86-7.02, P<.001). Respondents using the Internet as a source were more likely to be female (OR 1.30, 95% CI 1.05-1.60, P=.02), live in a metropolitan area (OR 1.26, 95% CI 1.03-1.54, P=.03), born in countries other than Australia/UK/Ireland (OR 1.41, 95% CI 1.07-1.85, P=.02), more educated (university: OR 2.46, 95% CI 1.77-3.42, P<.001), and were less likely to be older (55-64 years: OR 0.38, 95% CI 0.25-0.57, P<.001). The majority of respondents agreed the following information would assist them to make healthier choices: more ways to prepare healthy foods (72.0%, 95% CI 70.7-73.3), quicker ways to prepare healthy foods (79.0%, 95% CI 77.8-80.1), how to choose healthy foods (68.8%, 95% CI 67.5-70.1), and knowing more about cooking (54.7%, 95% CI 53.3-56.1). Those using the Internet for nutrition information were more likely than nonusers to want to know quicker ways to prepare healthy foods (83.0% vs 78.1%, P=.005) and information on choosing healthy foods (76.3% vs 67.3%, P<.001). Conclusions: Use of the Internet as a main source of nutrition information has grown rapidly since 2004; one-third of Western Australian adults reported using the Internet for this purpose in 2012. Information on preparing healthy foods (ideas, quicker ways), choosing ingredients, and knowing more about cooking would make it easier to eat a healthy diet. For Internet users, emphasis should be on quicker ways and choosing ingredients. These finding have implications for policy makers and practitioners and suggest that traditional health promotion tactics should continue to be used to reach the broader population.

  • Free for commercial use (http://iconbug.com/detail/icon/7705/folded-paper-twitter/).

    Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning

    Abstract:

    Background: Electronic cigarettes (e-cigarettes) continue to be a growing topic among social media users, especially on Twitter. The ability to analyze conversations about e-cigarettes in real-time can provide important insight into trends in the public’s knowledge, attitudes, and beliefs surrounding e-cigarettes, and subsequently guide public health interventions. Objective: Our aim was to establish a supervised machine learning algorithm to build predictive classification models that assess Twitter data for a range of factors related to e-cigarettes. Methods: Manual content analysis was conducted for 17,098 tweets. These tweets were coded for five categories: e-cigarette relevance, sentiment, user description, genre, and theme. Machine learning classification models were then built for each of these five categories, and word groupings (n-grams) were used to define the feature space for each classifier. Results: Predictive performance scores for classification models indicated that the models correctly labeled the tweets with the appropriate variables between 68.40% and 99.34% of the time, and the percentage of maximum possible improvement over a random baseline that was achieved by the classification models ranged from 41.59% to 80.62%. Classifiers with the highest performance scores that also achieved the highest percentage of the maximum possible improvement over a random baseline were Policy/Government (performance: 0.94; % improvement: 80.62%), Relevance (performance: 0.94; % improvement: 75.26%), Ad or Promotion (performance: 0.89; % improvement: 72.69%), and Marketing (performance: 0.91; % improvement: 72.56%). The most appropriate word-grouping unit (n-gram) was 1 for the majority of classifiers. Performance continued to marginally increase with the size of the training dataset of manually annotated data, but eventually leveled off. Even at low dataset sizes of 4000 observations, performance characteristics were fairly sound. Conclusions: Social media outlets like Twitter can uncover real-time snapshots of personal sentiment, knowledge, attitudes, and behavior that are not as accessible, at this scale, through any other offline platform. Using the vast data available through social media presents an opportunity for social science and public health methodologies to utilize computational methodologies to enhance and extend research and practice. This study was successful in automating a complex five-category manual content analysis of e-cigarette-related content on Twitter using machine learning techniques. The study details machine learning model specifications that provided the best accuracy for data related to e-cigarettes, as well as a replicable methodology to allow extension of these methods to additional topics.

  • Image source: Still image taken from video titled Lazy Girl No.6, by Maria Raquel Cochez. Licensed under cc-by-sa 3.0,  https://de.wikipedia.org/wiki/Datei:LazyGirl6.jpg.

    An Interactive Computer Session to Initiate Physical Activity in Sedentary Cardiac Patients: Randomized Controlled Trial

    Abstract:

    Background: Physical activity (PA) improves many facets of health. Despite this, the majority of American adults are insufficiently active. Adults who visit a physician complaining of chest pain and related cardiovascular symptoms are often referred for further testing. However, when this testing does not reveal an underlying disease or pathology, patients typically receive no additional standard care services. A PA intervention delivered within the clinic setting may be an effective strategy for improving the health of this population at a time when they may be motivated to take preventive action. Objective: Our aim was to determine the effectiveness of a tailored, computer-based, interactive personal action planning session to initiate PA among a group of sedentary cardiac patients following exercise treadmill testing (ETT). Methods: This study was part of a larger 2x2 randomized controlled trial to determine the impact of environmental and social-cognitive intervention approaches on the initiation and maintenance of weekly PA for patients post ETT. Participants who were referred to an ETT center but had a negative-test (ie, stress tests results indicated no apparent cardiac issues) were randomized to one of four treatment arms: (1) increased environmental accessibility to PA resources via the provision of a free voucher to a fitness facility in close proximity to their home or workplace (ENV), (2) a tailored social cognitive intervention (SC) using a “5 As”-based (ask, advise, assess, assist, and arrange) personal action planning tool, (3) combined intervention of both ENV and SC approaches (COMBO), or (4) a matched contact nutrition control (CON). Each intervention was delivered using a computer-based interactive session. A general linear model for repeated measures was conducted with change in PA behavior from baseline to 1-month post interactive computer session as the primary outcome. Results: Sedentary participants (n=452; 34.7% participation rate) without a gym membership (mean age 58.57 years; 59% female, 78% white, 12% black, 11% Hispanic) completed a baseline assessment and an interactive computer session. PA increased across the study sample (F1,441=30.03, P<.001). However, a time by condition interaction (F3,441=8.33, P<.001) followed by post hoc analyses indicated that SC participants exhibited a significant increase in weekly PA participation (mean 45.1, SD 10.2) compared to CON (mean -2.5, SD 10.8, P=.004) and ENV (mean 8.3, SD 8.1, P<.05). Additionally, COMBO participants exhibited a significant increase in weekly PA participation (mean 53.4, SD 8.9) compared to CON (P<.001) and ENV (P=.003) participants. There were no significant differences between ENV and CON or between SC and COMBO. Conclusions: A brief, computer-based, interactive personal action planning session may be an effective tool to initiate PA within a health care setting, in particular as part of the ETT system. Trial Registration: Clinicaltrials.gov NCT00432133, http://clinicaltrials.gov/ct2/show/NCT00432133 (Archived by WebCite at http://www.webcitation.org/6aa8X3mw1).

  • The FAMILY project.

    Using Information and Communication Technologies for Family Communication and Its Association With Family Well-Being in Hong Kong: FAMILY Project

    Abstract:

    Background: Family communication is central to the family and its functioning. It is a mutual process in which family members create, share, and regulate meaning. Advancement and proliferation of information and communication technologies (ICTs) continues to change methods of family communication. However, little is known about the use of different methods for family communication and the influence on family well-being. Objective: We investigated the sociodemographic factors associated with different methods of family communication and how they are associated with perceived family harmony, happiness, and health (3Hs) among Chinese adults in Hong Kong. Methods: Data came from a territory-wide probability-based telephone survey using the Family and Health Information Trend survey (FHInTs). Frequency of family communication using different methods (ie, face-to-face, phone, instant messaging [IM], social media sites, and email) were recoded and classified as frequent (always/sometimes) and nonfrequent (seldom/never) use. Family well-being was measured using 3 questions of perceived family harmony, happiness, and health with higher scores indicating better family well-being. Adjusted odds ratios for family communication methods by sociodemographic characteristics and adjusted beta coefficients for family well-being by communication methods were calculated. Results: A total of 1502 adults were surveyed. Face-to-face (94.85%, 1408/1484) was the most frequent means of communication followed by phone (78.08%, 796/1484), IM (53.64%, 796/1484), social media sites (17.60%, 261/1484), and email (13.39%, 198/1484). Younger age was associated with the use of phone, IM, and social media sites for family communication. Higher educational attainment was associated with more frequent use of all modes of communication, whereas higher family income was only significantly associated with more frequent use of IM and email (P=.001). Face-to-face (beta 0.65, 95% CI 0.33-0.97) and phone use (beta 0.20, 95% CI 0.02-0.38) for family communication were associated with significantly higher levels of perceived family well-being. Conclusions: Socioeconomic disparities in using these information and communication technologies (ICT) methods for family communication were observed. Although traditional methods remain as the main platform for family communication and were associated with better family well-being, a notable proportion of respondents are using new ICT methods, which were not associated with perceived family well-being. Because ICTs will continue to diversify modes of family communication, more research is needed to understand the impact of ICTs on family communication and well-being.

  • Contrast between paper and electronic diaty.

    More Than Telemonitoring: Health Provider Use and Nonuse of Life-Log Data in Irritable Bowel Syndrome and Weight Management

    Abstract:

    Background: The quantified self, self-monitoring or life-logging movement is a trend to incorporate technology into data acquisition on aspects of a person's daily life in terms of inputs (eg food consumed), states (eg mood), and performance (mental and physical). Consumer self-monitoring mobile phone apps have been widely studied and used to promote healthy behavior changes. Data collected through life-logging apps also have the potential to support clinical care. Objective: We sought to develop an in-depth understanding of providers’ facilitators and barriers to successfully integrating life-log data into their practices and creating better experiences. We specifically investigated three research questions: How do providers currently use patient-collected life-log data in clinical practice? What are provider concerns and needs with respect to this data? What are the constraints for providers to integrate this type of data into their workflows? Methods: We interviewed 21 health care providers—physicians, dietitians, a nurse practitioner, and a behavioral psychologist—who work with obese and irritable bowel syndrome patients. We transcribed and analyzed interviews according to thematic analysis and an affinity diagramming process. Results: Providers reported using self-monitoring data to enhance provider-patient communication, develop personalized treatment plans, and to motivate and educate patients, in addition to using them as diagnostic and adherence tools. However, limitations associated with current systems and workflows create barriers to regular and effective review of this data. These barriers include a lack of time to review detailed records, questions about providers' expertise to review it, and skepticism about additional benefits offered by reviewing data. Current self-monitoring tools also often lack flexibility, standardized formats, and mechanisms to share data with providers. Conclusions: Variations in provider needs affect tracking and reviewing needs. Systems to support diagnosis might require better reliability and resolution, while systems to support interaction should support collaborative reflection and communication. Automatic synthesis of data logs could help providers focus on educational goals while communication of contextual information might help providers better understand patient values. We also discuss how current mobile apps and provider systems do, and do not, support these goals, and future design opportunities to realize the potential benefits of using life-logging tools in clinical care.

  • Title image. Image credit: Shutterstock.

    Predictors of “Liking” Three Types of Health and Fitness-Related Content on Social Media: A Cross-Sectional Study

    Abstract:

    Background: Adolescence and young adulthood are key periods for developing norms related to health behaviors and body image, and social media can influence these norms. Social media is saturated with content related to dieting, fitness, and health. Health and fitness–related social media content has received significant media attention for often containing objectifying and inaccurate health messages. Limited research has identified problematic features of such content, including stigmatizing language around weight, portraying guilt-related messages regarding food, and praising thinness. However, no research has identified who is “liking” or “following” (ie, consuming) such content. Objective: This exploratory study aimed to identify demographics, mental health, and substance use–related behaviors that predicted consuming 3 types of health and fitness–related social media content—weight loss/fitness motivation pages (ie, “fitspiration”), detox/cleanse pages, and diet/fitness plan pages—among young social media users. Methods: Participants (N=1001; age: median 21.06, IQR 17.64-24.64; female: 723/1001, 72.23%) completed a cross-sectional 112-question online survey aimed at social media users aged between 15-29 years residing in Victoria, Australia. Logistic regression was used to determine which characteristics predicted consuming the 3 types of health and fitness–related social media content. Results: A total of 378 (37.76%) participants reported consuming at least 1 of the 3 types of health and fitness–related social media content: 308 (30.77%) fitspiration pages, 145 (14.49%) detox pages, and 235 (23.48%) diet/fitness plan pages. Of the health and fitness–related social media content consumers, 85.7% (324/378) identified as female and 44.8% (324/723) of all female participants consumed at least 1 type of health and fitness–related social media content. Predictors of consuming at least one type of health and fitness–related social media content in univariable analysis included female gender (OR 3.5, 95% CI 2.5-4.9, P<.001), being aged 15-17 years (OR 3.0, 95% CI 2.2-4.0, P<.001), residing outside a major city (OR 2.0, 95% CI 1.4-2.9, P<.001), having no post–high school education (OR 2.2, 95% CI 1.7-2.9, P<.001), being born in Australia (OR 2.0, 95% CI 1.2-3.2, P=.006), having a self-reported eating disorder (OR 2.4, 95% CI 1.5-3.9, P<.001), being a victim of bullying (OR 1.7, CI 1.3-2.3, P<.001), misusing detox/laxative teas or diet pills (OR 4.6, 95% CI 2.8-7.6, P<.001), never using illegal drugs (OR 1.6, 95% CI 1.2-2.0, P=.001), and not engaging in risky single occasion drinking on a weekly basis (OR 2.0, 95% CI 1.3-3.0, P=.003). Conclusions: Consumers of health and fitness–related social media content were predominantly teenaged girls. There is a need to ensure that this social media content portrays responsible health messages and to research further the role of fitspiration pages, detox pages, and diet/fitness plan pages in influencing body image and health behaviors.

  • Distribution of searches across organ systems. Each organ system name is followed by the percentage of queries related to that system. Each pie chart shows the distribution of searches for that organ system grouped by their term category, followed by the 10 most frequent and 10 least frequent terms searched for related to that system. Searches about diseases and symptoms (dark blue) dominated most systems. Searches about the endocrine system included a significant number of drug searches, followed by the cardiovascular system.

    Analyzing Information Seeking and Drug-Safety Alert Response by Health Care Professionals as New Methods for Surveillance

    Abstract:

    Background: Patterns in general consumer online search logs have been used to monitor health conditions and to predict health-related activities, but the multiple contexts within which consumers perform online searches make significant associations difficult to interpret. Physician information-seeking behavior has typically been analyzed through survey-based approaches and literature reviews. Activity logs from health care professionals using online medical information resources are thus a valuable yet relatively untapped resource for large-scale medical surveillance. Objective: To analyze health care professionals’ information-seeking behavior and assess the feasibility of measuring drug-safety alert response from the usage logs of an online medical information resource. Methods: Using two years (2011-2012) of usage logs from UpToDate, we measured the volume of searches related to medical conditions with significant burden in the United States, as well as the seasonal distribution of those searches. We quantified the relationship between searches and resulting page views. Using a large collection of online mainstream media articles and Web log posts we also characterized the uptake of a Food and Drug Administration (FDA) alert via changes in UpToDate search activity compared with general online media activity related to the subject of the alert. Results: Diseases and symptoms dominate UpToDate searches. Some searches result in page views of only short duration, while others consistently result in longer-than-average page views. The response to an FDA alert for Celexa, characterized by a change in UpToDate search activity, differed considerably from general online media activity. Changes in search activity appeared later and persisted longer in UpToDate logs. The volume of searches and page view durations related to Celexa before the alert also differed from those after the alert. Conclusions: Understanding the information-seeking behavior associated with online evidence sources can offer insight into the information needs of health professionals and enable large-scale medical surveillance. Our Web log mining approach has the potential to monitor responses to FDA alerts at a national level. Our findings can also inform the design and content of evidence-based medical information resources such as UpToDate.

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    Date Submitted: Sep 3, 2015

    Open Peer Review Period: Sep 3, 2015 - Oct 29, 2015

    Background: Hand hygiene is an important component in infection control to protect patient safety and reduce healthcare associated infection. Objective: Evaluate the efficacy of different social media...

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    Date Submitted: Aug 29, 2015

    Open Peer Review Period: Sep 3, 2015 - Oct 29, 2015

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    Date Submitted: Aug 26, 2015

    Open Peer Review Period: Sep 3, 2015 - Oct 29, 2015

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    Date Submitted: Aug 26, 2015

    Open Peer Review Period: Sep 3, 2015 - Oct 29, 2015

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    Date Submitted: Sep 3, 2015

    Open Peer Review Period: Sep 3, 2015 - Oct 29, 2015

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    Date Submitted: Sep 1, 2015

    Open Peer Review Period: Sep 2, 2015 - Sep 16, 2015

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