%0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 6 %P e146 %T Adherence to Internet-Based Mobile-Supported Stress Management: A Pooled Analysis of Individual Participant Data From Three Randomized Controlled Trials %A Zarski,Anna-Carlotta %A Lehr,Dirk %A Berking,Matthias %A Riper,Heleen %A Cuijpers,Pim %A Ebert,David Daniel %+ Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander University Erlangen-Nuremberg, Nägelsbachstr. 25a, Erlangen, 91052, Germany, 49 9131 85 67570, Anna-Carlotta.Zarski@fau.de %K guidance %K treatment adherence %K predictors %K Internet intervention %K work-related stress %K stress management %D 2016 %7 29.06.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Nonadherence to treatment is a prevalent issue in Internet interventions. Guidance from health care professionals has been found to increase treatment adherence rates in Internet interventions for a range of physical and mental disorders. Evaluating different guidance formats of varying intensity is important, particularly with respect to improvement of effectiveness and cost-effectiveness. Identifying predictors of nonadherence allows for the opportunity to better adapt Internet interventions to the needs of participants especially at risk for discontinuing treatment. Objective: The goal of this study was to investigate the influence of different guidance formats (content-focused guidance, adherence-focused guidance, and administrative guidance) on adherence and to identify predictors of nonadherence in an Internet-based mobile-supported stress management intervention (ie, GET.ON Stress) for employees. Methods: The data from the groups who received the intervention were pooled from three randomized controlled trials (RCTs) that evaluated the efficacy of the same Internet-based mobile-supported stress management intervention (N=395). The RCTs only differed in terms of the guidance format (content-focused guidance vs waitlist control, adherence-focused guidance vs waitlist control, administrative guidance vs waitlist control). Adherence was defined by the number of completed treatment modules (0-7). An ANOVA was performed to compare the adherence rates from the different guidance formats. Multiple hierarchical linear regression analysis was conducted to evaluate predictors of nonadherence, which included gender, age, education, symptom-related factors, and hope for improvement. Results: In all, 70.5% (93/132) of the content-focused guidance sample, 68.9% (91/132) of the adherence-focused guidance sample, and 42.0% (55/131) of the participants in the administrative guidance sample completed all treatment modules. Guidance had a significant effect on treatment adherence (F2,392=11.64, P<.001; ω2=.05). Participants in the content-focused guidance (mean 5.70, SD 2.32) and adherence-focused guidance samples (mean 5.58, SD 2.33) completed significantly more modules than participants in the administrative guidance sample (mean 4.36, SD 2.78; t223=4.53, P<.001; r=.29). Content-focused guidance was not significantly associated with higher adherence compared to adherence-focused guidance (t262=0.42, P=.67; r=.03). The effect size of r=.03 (95% CI –0.09 to 0.15) did not pass the equivalence margin of r=.20 and the upper bound of the 95% CI lay below the predefined margin, indicating equivalence between adherence-focused guidance and content-focused guidance. Beyond the influence of guidance, none of the predictors significantly predicted nonadherence. Conclusions: Guidance has been shown to be an influential factor in promoting adherence to an Internet-based mobile-supported stress management intervention. Adherence-focused guidance, which included email reminders and feedback on demand, was equivalent to content-focused guidance with regular feedback while requiring only approximately a quarter of the coaching resources. This could be a promising discovery in terms of cost-effectiveness. However, even after considering guidance, sociodemographic, and symptom-related characteristics, most interindividual differences in nonadherence remain unexplained. Clinical Trial: DRKS00004749; http://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL _ID=DRKS00004749 (Archived by WebCite at http://www.webcitation.org/6QiDk9Zn8); DRKS00005112; http://drks-neu.uniklinik-freiburg. de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00005112 (Archived by WebCite at http://www.webcitation.org/6QiDysvev); DRKS00005384; http://drks-neu.uniklinik-freiburg.de/ drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00005384 (Archived by WebCite at http://www.webcitation.org/6QiE0xcpE) %M 27357528 %R 10.2196/jmir.4493 %U http://www.jmir.org/2016/6/e146/ %U https://doi.org/10.2196/jmir.4493 %U http://www.ncbi.nlm.nih.gov/pubmed/27357528 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 4 %N 2 %P e18 %T Impact of Implementing a Wiki to Develop Structured Electronic Order Sets on Physicians' Intention to Use Wiki-Based Order Sets %A Archambault,Patrick Michel %A Beaupré,Pierre %A Bégin,Laura %A Dupuis,Audrey %A Côté,Mario %A Légaré,France %+ Centre intégré de santé et services sociaux de Chaudière-Appalaches, 143 rue Wolfe, Lévis, QC, G6V 3Z1, Canada, 1 418 835 7121 ext 3905, patrick.m.archambault@gmail.com %K knowledge translation %K wiki %K collaborative writing applications %K decision support tools %K health informatics %K Theory of Planned Behavior %K emergency medicine %K computer physician order entry %D 2016 %7 17.05.2016 %9 Original Paper %J JMIR Med Inform %G English %X Background: Wikis have the potential to promote best practices in health systems by sharing order sets with a broad community of stakeholders. However, little is known about the impact of using a wiki on clinicians’ intention to use wiki-based order sets. Objective: The aims of this study were: (1) to describe the use of a wiki to create structured order sets for a single emergency department; (2) to evaluate whether the use of this wiki changed emergency physicians’ future intention to use wiki-based order sets; and (3) to understand the impact of using the wiki on the behavioral determinants for using wiki-based order sets. Methods: This was a pre/post-intervention mixed-methods study conducted in one hospital in Lévis, Quebec. The intervention was comprised of receiving access to and being motivated by the department head to use a wiki for 6 months to create electronic order sets designed to be used in a computer physician order entry system. Before and after our intervention, we asked participants to complete a previously validated questionnaire based on the Theory of Planned Behavior. Our primary outcome was the intention to use wiki-based order sets in clinical practice. We also assessed participants’ attitude, perceived behavioral control, and subjective norm to use wiki-based order sets. Paired pre- and post-Likert scores were compared using Wilcoxon signed-rank tests. The post-questionnaire also included open-ended questions concerning participants’ comments about the wiki, which were then classified into themes using an existing taxonomy. Results: Twenty-eight emergency physicians were enrolled in the study (response rate: 100%). Physicians’ mean intention to use a wiki-based reminder was 5.42 (SD 1.04) before the intervention, and increased to 5.81 (SD 1.25) on a 7-point Likert scale (P=.03) after the intervention. Participants’ attitude towards using a wiki-based order set also increased from 5.07 (SD 0.90) to 5.57 (SD 0.88) (P=.003). Perceived behavioral control and subjective norm did not change. Easier information sharing was the most frequently positive impact raised. In order of frequency, the three most important facilitators reported were: ease of use, support from colleagues, and promotion by the departmental head. Although participants did not mention any perceived negative impacts, they raised the following barriers in order of frequency: poor organization of information, slow computers, and difficult wiki access. Conclusions: Emergency physicians’ intention and attitude to use wiki-based order sets increased after having access to and being motivated to use a wiki for 6 months. Future studies need to explore if this increased intention will translate into sustained actual use and improve patient care. Certain barriers need to be addressed before implementing a wiki for use on a larger scale. %M 27189046 %R 10.2196/medinform.4852 %U http://medinform.jmir.org/2016/2/e18/ %U https://doi.org/10.2196/medinform.4852 %U http://www.ncbi.nlm.nih.gov/pubmed/27189046 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 2 %N 1 %P e11 %T Development of the Health Atlas of Jalisco: A New Web-Based Service for the Ministry of Health and the Community in Mexico %A Ramos Herrera,Igor Martin %A Gonzalez Castañeda,Miguel %A Robles,Juan %A Fonseca León,Joel %+ Center of Research on Geographic Information Systems and Management in Health, Department of Public Health, University of Guadalajara, N Bldg, 2nd Fl., 950 Sierra Mojada, Guadalajara, 44340, Mexico, 52 331 058 5200 ext 33900, iramos@cucs.udg.mx %K Public health %K health atlas %K geographic information systems %K geographic mapping %K online systems %K health information systems %D 2016 %7 16.03.2016 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Maps have been widely used to provide a visual representation of information of a geographic area. Health atlases are collections of maps related to conditions, infrastructure or services provided. Various countries have put resources towards producing health atlases that support health decision makers to enhance their services to the communities. Latin America, as well as Spain, have produced several atlases of importance such as the interactive mortality atlas of Andalucía, which is very similar to the one that is presented in this paper. In Mexico, the National Institute of Public Health produced the only health atlas found that is of relevance. It was published online in 2003 and is currently still active. Objective: The objective of this work is to describe the methods used to develop the Health Atlas of Jalisco (HAJ), and show its characteristics and how it interactively works with the user as a Web-based service. Methods: This work has an ecological design in which the analysis units are the 125 municipalities (counties) of the state of Jalisco, Mexico. We created and published online a geographic health atlas displaying a system based on input from official health database of the Health Ministry of Jalisco (HMJ), and some databases from the National Institute of Statistics and Geography (NISGI). The atlas displays 256 different variables as health-direct or health-related indicators. Instant Atlas software was used to generate the online application. The atlas was developed using these procedures: (1) datasheet processing and base maps generation, (2) software arrangements, and (3) website creation. Results: The HAJ is a Web-based service that allows users to interact with health and general data, regions, and categories according to their information needs and generates thematic maps (eg, the total population of the state or of a single municipality grouped by age or sex). The atlas is capable of displaying more than 32,000 different maps by combining categories, indicators, municipalities, and regions. Users can select the entire province, one or several municipalities, and the indicator they require. The atlas then generates and displays the requested map. Conclusions: This atlas is a Web-based service that interactively allows users to review health indicators such as structure, supplies, processes, and the impact on public health and related sectors in Jalisco, Mexico. One of the main interests is to reduce the number of information requests that the Ministry of Health receives every week from the general public, media reporters, and other government sectors. The atlas will support transparency, information diffusion, health decision-making, and the formulation of new public policies. Furthermore, the research team intends to promote research and education in public health. %M 27227146 %R 10.2196/publichealth.5255 %U http://publichealth.jmir.org/2016/1/e11/ %U https://doi.org/10.2196/publichealth.5255 %U http://www.ncbi.nlm.nih.gov/pubmed/27227146 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 18 %N 2 %P e32 %T What Predicts Patients’ Willingness to Undergo Online Treatment and Pay for Online Treatment? Results from a Web-Based Survey to Investigate the Changing Patient-Physician Relationship %A Roettl,Johanna %A Bidmon,Sonja %A Terlutter,Ralf %+ Alpen-Adria Universitaet Klagenfurt, Department of Marketing and International Management, Universitaetsstrasse 65-67, Klagenfurt, 9020, Austria, 43 463 2700 4046, johanna.roettl@aau.at %K physician-patient relationship, online treatment %K general practitioners %K willingness to pay %D 2016 %7 04.02.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Substantial research has focused on patients’ health information–seeking behavior on the Internet, but little is known about the variables that may predict patients’ willingness to undergo online treatment and willingness to pay additionally for online treatment. Objective: This study analyzed sociodemographic variables, psychosocial variables, and variables of Internet usage to predict willingness to undergo online treatment and willingness to pay additionally for online treatment offered by the general practitioner (GP). Methods: An online survey of 1006 randomly selected German patients was conducted. The sample was drawn from an e-panel maintained by GfK HealthCare. Missing values were imputed; 958 usable questionnaires were analyzed. Variables with multi-item measurement were factor analyzed. Willingness to undergo online treatment and willingness to pay additionally for online treatment offered by the GP were predicted using 2 multiple regression models. Results: Exploratory factor analyses revealed that the disposition of patients’ personality to engage in information-searching behavior on the Internet was unidimensional. Exploratory factor analysis with the variables measuring the motives for Internet usage led to 2 separate factors: perceived usefulness (PU) of the Internet for health-related information searching and social motives for information searching on the Internet. Sociodemographic variables did not serve as significant predictors for willingness to undergo online treatment offered by the GP, whereas PU (B=.092, P=.08), willingness to communicate with the GP more often in the future (B=.495, P<.001), health-related information–seeking personality (B=.369, P<.001), actual use of online communication with the GP (B=.198, P<.001), and social motive (B=.178, P=.002) were significant predictors. Age, gender, satisfaction with the GP, social motive, and trust in the GP had no significant impact on the willingness to pay additionally for online treatment, but it was predicted by health-related information–seeking personality (B=.127, P=.07), PU (B=–.098, P=.09), willingness to undergo online treatment (B=.391, P<.001), actual use of online communication with the GP (B=.192, P=.001), highest education level (B=.178, P<.001), monthly household net income (B=.115, P=.01), and willingness to communicate with the GP online more often in the future (B=.076, P=.03). Conclusions: Age, gender, and trust in the GP were not significant predictors for either willingness to undergo online treatment or to pay additionally for online treatment. Willingness to undergo online treatment was partly determined by the actual use of online communication with the GP, willingness to communicate online with the GP, health information–seeking personality, and social motivation for such behavior. Willingness to pay extra for online treatment was influenced by the monthly household net income category and education level. The results of this study are useful for online health care providers and physicians who are considering offering online treatments as a viable number of patients would appreciate the possibility of undergoing an online treatment offered by their GP. %M 26846162 %R 10.2196/jmir.5244 %U http://www.jmir.org/2016/2/e32/ %U https://doi.org/10.2196/jmir.5244 %U http://www.ncbi.nlm.nih.gov/pubmed/26846162 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 18 %N 2 %P e28 %T In Pursuit of Theoretical Ground in Behavior Change Support Systems: Analysis of Peer-to-Peer Communication in a Health-Related Online Community %A Myneni,Sahiti %A Cobb,Nathan %A Cohen,Trevor %+ School of Biomedical Informatics, University of Texas Health Science Center at Houston, 7000 Fannin, Suite 165, Houston, TX, 77030, United States, 1 713 486 0115, sahiti.myneni@uth.tmc.edu %K behavior change %K online social media %K web interventions %K smoking cessation %D 2016 %7 02.02.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Research studies involving health-related online communities have focused on examining network structure to understand mechanisms underlying behavior change. Content analysis of the messages exchanged in these communities has been limited to the “social support” perspective. However, existing behavior change theories suggest that message content plays a prominent role reflecting several sociocognitive factors that affect an individual’s efforts to make a lifestyle change. An understanding of these factors is imperative to identify and harness the mechanisms of behavior change in the Health 2.0 era. Objective: The objective of this work is two-fold: (1) to harness digital communication data to capture essential meaning of communication and factors affecting a desired behavior change, and (2) to understand the applicability of existing behavior change theories to characterize peer-to-peer communication in online platforms. Methods: In this paper, we describe grounded theory–based qualitative analysis of digital communication in QuitNet, an online community promoting smoking cessation. A database of 16,492 de-identified public messages from 1456 users from March 1-April 30, 2007, was used in our study. We analyzed 795 messages using grounded theory techniques to ensure thematic saturation. This analysis enabled identification of key concepts contained in the messages exchanged by QuitNet members, allowing us to understand the sociobehavioral intricacies underlying an individual’s efforts to cease smoking in a group setting. We further ascertained the relevance of the identified themes to theoretical constructs in existing behavior change theories (eg, Health Belief Model) and theoretically linked techniques of behavior change taxonomy. Results: We identified 43 different concepts, which were then grouped under 12 themes based on analysis of 795 messages. Examples of concepts include “sleepiness,” “pledge,” “patch,” “spouse,” and “slip.” Examples of themes include “traditions,” “social support,” “obstacles,” “relapse,” and “cravings.” Results indicate that themes consisting of member-generated strategies such as “virtual bonfires” and “pledges” were related to the highest number of theoretical constructs from the existing behavior change theories. In addition, results indicate that the member-generated communication content supports sociocognitive constructs from more than one behavior change model, unlike the majority of the existing theory-driven interventions. Conclusions: With the onset of mobile phones and ubiquitous Internet connectivity, online social network data reflect the intricacies of human health behavior as experienced by health consumers in real time. This study offers methodological insights for qualitative investigations that examine the various kinds of behavioral constructs prevalent in the messages exchanged among users of online communities. Theoretically, this study establishes the manifestation of existing behavior change theories in QuitNet-like online health communities. Pragmatically, it sets the stage for real-time, data-driven sociobehavioral interventions promoting healthy lifestyle modifications by allowing us to understand the emergent user needs to sustain a desired behavior change. %M 26839162 %R 10.2196/jmir.4671 %U http://www.jmir.org/2016/2/e28/ %U https://doi.org/10.2196/jmir.4671 %U http://www.ncbi.nlm.nih.gov/pubmed/26839162 %0 Journal Article %@ 1923-2195 %I Gunther Eysenbach %V 4 %N 2 %P e5 %T Harnessing the Web: How E-Health and E-Health Literacy Impact Young Adults’ Perceptions of Online Health Information %A Briones,Rowena %+ Virginia Commonwealth University, Richard T. Robertson School of Media & Culture, 901 W. Main St., Richmond, VA, 23284, United States, 1 804 827 2048, rlbriones@vcu.edu %K e-health literacy %K young adults %K online information seeking %K online health information %D 2015 %7 31.12.2015 %9 Original Paper %J Med 2.0 %G English %X Background: The rise of technology has changed how people take control of their health, enabling individuals to choose to live healthier lives and make better treatment decisions. With this said, the Internet has emerged as the channel used by individuals for actively seeking or passively receiving health information. Objective: To explore how young adults assess the quality of health information, and how they construct meaning of online health information in general. Through 50 in-depth interviews, this study aims to examine how and why young adults turn to the Web for health information, and what strategies they employ to ensure that they are getting credible information. Methods: A total of 50 in-depth interviews were conducted with young adults to explore how they make meaning of online health information. Depending on the geographic area of the participant, the interview took place face-to-face at a location convenient for them, over Skype, or over the telephone and lasted on average 40 minutes. The interviews were transcribed verbatim, fully retaining the speech style of the moderator and the participants. Data were analyzed using techniques from the grounded theory approach, using a constant comparative method to allow for themes to emerge from the transcripts. Results: The participants shared several benefits to this mode of health information seeking, claiming that it made for more productive visits with doctors and made health information more readily accessible through a variety of different formats. Additionally, the participants demonstrated their e-health literacy levels by discussing how they assessed online health information, engaging in a series of strategies that encompassed different aspects of e-health literacy. Social media channels were brought up by the participants as relatively new tools that can be used to assist in the seeking, understanding, and sharing of health information. However, participants also cautioned about the use of social media in regards to its informal nature, warning users to evaluate sources accordingly and to use these channels as supplementary outlets of information for more traditional channels. Conclusions: The use of the Internet and technology for health purposes is a growing area for both scholarship and practice that has strong implications for health consumers, medical professionals, and communicators alike. The findings that emerged from this research demonstrated that the online space is an acceptable channel through which young adults can find and share information. However, in spite of the rising usage of social media by this particular group, the findings showed that they were hesitant and wary of the channel, not seeing it as a resource for health information but more of a channel for networking and entertainment. In spite of this, this study shows that the online health information seeking behaviors is an area that warrants further exploration. %M 26721292 %R 10.2196/med20.4327 %U http://www.medicine20.com/2015/2/e5/ %U https://doi.org/10.2196/med20.4327 %U http://www.ncbi.nlm.nih.gov/pubmed/26721292 %0 Journal Article %@ 1923-2195 %I Gunther Eysenbach %V 4 %N 2 %P e4 %T mHealth: Don’t Forget All the Stakeholders in the Business Case %A Petersen,Carolyn %A Adams,Samantha A %A DeMuro,Paul R %+ Mayo Clinic, Global Business Solutions, 200 First St. SW, Rochester, MN, 55905, United States, 1 507 284 2511, petersen.carolyn@mayo.edu %K Internet %K mobile %K mobile health %K app %K social media %K health care market %D 2015 %7 31.12.2015 %9 Short Paper %J Med 2.0 %G English %X Mobile health (mHealth) facilitates linking patient-generated data with electronic health records with clinical decision support systems. mHealth can transform health care, but to realize this potential it is important to identify the relevant stakeholders and how they might be affected. Such stakeholders include primary stakeholders, such as patients, families and caregivers, clinicians, health care facilities, researchers, payors and purchasers, employers, and miscellaneous secondary stakeholders, such as vendors, suppliers, distributors, and consultants, policy makers and legislators. The breadth and depth of the mHealth market make it possible for mHealth to have a considerable effect on people’s health. However, many concerns exist, including privacy, data security, funding, and the lack of case studies demonstrating efficacy and cost-effectiveness. Many American and European initiatives to address these concerns are afoot. %M 26720310 %R 10.2196/med20.4349 %U http://www.medicine20.com/2015/2/e4/ %U https://doi.org/10.2196/med20.4349 %U http://www.ncbi.nlm.nih.gov/pubmed/26720310 %0 Journal Article %@ 1923-2195 %I Gunther Eysenbach %V 4 %N 2 %P e3 %T Using the Internet to Support Exercise and Diet: A Stratified Norwegian Survey %A Wangberg,Silje C %A Sørensen,Tove %A Andreassen,Hege K %+ Department of Health and Society, Narvik University College, Lodve Langes gt. 2, P.O. Box 385, Narvik, 8505, Norway, 47 76 96 60 00, siljecw@gmail.com %K Internet %K Health Behaviors %K Social Disparities %K Health Literacy %D 2015 %7 26.08.2015 %9 Original Paper %J Med 2.0 %G English %X Background: Internet is used for a variety of health related purposes. Use differs and has differential effects on health according to socioeconomic status. Objective: We investigated to what extent the Norwegian population use the Internet to support exercise and diet, what kind of services they use, and whether there are social disparities in use. We expected to find differences according to educational attainment. Methods: In November 2013 we surveyed a stratified sample of 2196 persons drawn from a Web panel of about 50,000 Norwegians over 15 years of age. The questionnaire included questions about using the Internet, including social network sites (SNS), or mobile apps in relation to exercise or diet, as well as background information about education, body image, and health. The survey email was opened by 1187 respondents (54%). Of these, 89 did not click on the survey hyperlink (declined to participate), while another 70 did not complete the survey. The final sample size is thus 1028 (87% response rate). Compared to the Norwegian census the sample had a slight under-representation of respondents under the age of 30 and with low education. The data was weighted accordingly before analyses. Results: Sixty-nine percent of women and 53% of men had read about exercise or diet on the Internet (χ2= 25.6, P<.001). More people with higher education (71%, χ2=19.1, P<.001), reported this. The same gender difference was found for using Internet-based interventions with 20% of women compared to14% of men reporting having used these interventions (χ2=7.9, P= .005), for having posted a status about exercise or diet on Facebook or other SNS (23% vs 12%, χ2=18.8, P<.001), and for having kept an online exercise or diet journal (21% vs 15%, χ2=7.0, P=.008). Evaluations of own physical appearance accounted for some of the gender differences in using online exercise or diet journals. Seven percent of the total sample reported having used electronic communication to ask professionals about exercise or diet, while a few more had discussed online with peers (10%). Asking professionals online was more common amongst those with only primary education (13%, χ2<10.5, P=.005).  Conclusions: Gender and education are related to how the Internet is used to support health behaviors. We should be aware of the potential role of the Internet in accelerating social disparities in health, and continue to monitor population use. For Internet- and mobile-based interventions to support health behaviors, this study provides information relevant to tailoring of delivery media and components to user. %M 26310277 %R 10.2196/med20.4116 %U http://www.medicine20.com/2015/2/e3/ %U https://doi.org/10.2196/med20.4116 %U http://www.ncbi.nlm.nih.gov/pubmed/26310277 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 2 %P e71 %T Doctors and the Etiquette of Mobile Device Use in Trauma and Orthopedics %A Blocker,Oliver %A Hayden,Lydia %A Bullock,Alison %+ The Cardiff Unit for Research and Evaluation in Medical and Dental Education (CUREMeDE), Cardiff University, Cardiff University School of Social Sciences, Glamorgan Building, King Edward VII Avenue, Cardiff, CF10 3WT, United Kingdom, 44 2920870780, drblocker@gmail.com %K education, medical %K cell phones %K patient-physician relationship %D 2015 %7 26.6.2015 %9 Original Paper %J JMIR mHealth uHealth %G English %X Background: The etiquette surrounding the use of mobile devices, so-called "mobiquette," has been previously identified as a barrier to use in an educational context. Objective: To investigate the influence of mobile device use on patient and staff opinions in the trauma and orthopedics department at a teaching hospital in Wales. Methods: A survey of patients at the bedside and staff in their work environment was undertaken. Data included age, frequency of observed use, suspected main reason for use, and whether doctors’ use of a mobile device positively or negatively influenced participants' opinions of them as a professional and as a person. Results: A total of 59 patients and 35 staff responded. The modal age range was 40 to 54 years old. Most patients (78%) never see doctors using mobile devices in the workplace, compared with 3% of staff. The main reason for use was thought to be "communicating with colleagues" (48%) followed by "Internet use/applications for work reasons" (40%). Approximately 40% of patients' opinions of doctors were positively influenced by device use, compared with 82% of staff. This difference between patient and staff opinions was statistically significant for both professional (P<.001) and personal (P=.002) opinions. Conclusions: Patients are likely to have a negative opinion of doctors using mobile devices in the workplace. This can be balanced by the more positive opinions of colleagues. We advise doctors to remember "mobiquette" around patients. %M 26116061 %R 10.2196/mhealth.4122 %U http://mhealth.jmir.org/2015/2/e71/ %U https://doi.org/10.2196/mhealth.4122 %U http://www.ncbi.nlm.nih.gov/pubmed/26116061 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 6 %P e156 %T Gender Differences in Searching for Health Information on the Internet and the Virtual Patient-Physician Relationship in Germany: Exploratory Results on How Men and Women Differ and Why %A Bidmon,Sonja %A Terlutter,Ralf %+ Department of Marketing and International Management, Alpen-Adria-Universitaet Klagenfurt, Universitaetsstrasse 65-67, Klagenfurt am Woerthersee, 9020, Austria, 43 463 2700 ext 4048, sonja.bidmon@aau.at %K gender differences %K physician-patient relations %K information seeking behavior %K general practitioners %K statistical factor analysis %D 2015 %7 22.06.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: Many studies have shown that women use the Internet more often for health-related information searches than men, but we have limited knowledge about the underlying reasons. We also do not know whether and how women and men differ in their current use of the Internet for communicating with their general practitioner (GP) and in their future intention to do so (virtual patient-physician relationship). Objective: This study investigates (1) gender differences in health-related information search behavior by exploring underlying emotional, motivational, attitudinal as well as cognitive variables, situational involvement, and normative influences, and different personal involvement regarding health-related information searching and (2) gender differences in the virtual patient-physician relationship. Methods: Gender differences were analyzed based on an empirical online survey of 1006 randomly selected German patients. The sample was drawn from an e-panel maintained by GfK HealthCare. A total of 958 usable questionnaires were analyzed. Principal component analyses were carried out for some variables. Differences between men (517/958) and women (441/958) were analyzed using t tests and Kendall’s tau-b tests. The survey instrument was guided by several research questions and was based on existing literature. Results: Women were more engaged in using the Internet for health-related information searching. Gender differences were found for the frequency of usage of various Internet channels for health-related information searches. Women used the Internet for health-related information searches to a higher degree for social motives and enjoyment and they judged the usability of the Internet medium and of the information gained by health information searches higher than men did. Women had a more positive attitude toward Web 2.0 than men did, but perceived themselves as less digitally competent. Women had a higher health and nutrition awareness and a greater reluctance to make use of medical support, as well as a higher personal disposition of being well-informed as a patient. Men may be more open toward the virtual patient-physician relationship. Conclusions: Women have a stronger social motive for and experience greater enjoyment in health-related information searches, explained by social role interpretations, suggesting these needs should be met when offering health-related information on the Internet. This may be interesting for governmental bodies as well as for the insurance and the pharmaceutical industries. Furthermore, women may be more easily convinced by health awareness campaigns and are, therefore, the primary target group for them. Men are more open to engaging in a virtual relationship with the GP; therefore, they could be the primary target group for additional online services offered by GPs. There were several areas for GPs to reinforce the virtual patient-physician relationship: the fixing of personal appointments, referral to other doctors, writing prescriptions, and discussions of normal test results and doctor’s notes/certificates of health. %M 26099325 %R 10.2196/jmir.4127 %U http://www.jmir.org/2015/6/e156/ %U https://doi.org/10.2196/jmir.4127 %U http://www.ncbi.nlm.nih.gov/pubmed/26099325 %0 Journal Article %@ 2369-3762 %I JMIR Publications %V 1 %N 1 %P e3 %T Global Outreach of a Locally-Developed Mobile Phone App for Undergraduate Psychiatry Education %A Zhang,Melvyn WB %A Cheok,Christopher CS %A Ho,Roger CM %+ National Healthcare Group, Level 9, Department of Psychological Medicine, National University Healthcare Systems (NUHS) Tower Block 5 Lower Kent Ridge Road, Singapore, 119054, Singapore, 65 7725555, melvynzhangweibin@gmail.com %K psychiatry %K education %K eLearning %K mobile phone apps %K mobile phones %K feasibility %K proof of concept %D 2015 %7 08.06.2015 %9 Original Paper %J JMIR Medical Education %G English %X Background: Over the past decade, there have been massive developments in both Web-based and mobile phone technologies. Mobile phones are well accepted by students, trainees, and doctors. A review of the current literature has identified the following specialties that have used mobile phones in education: pediatrics, ophthalmology, nephrology, plastic surgery, orthopedics, pharmacology, and urology. However, to date, there are no published papers examining the application of the latest mobile phone technologies for psychiatry education internationally. Objectives: The main objectives of this study are (1) to determine the feasibility and receptiveness of a locally-developed psychiatry mobile phone app and user perspectives (both quantitative and qualitative) towards it, and (2) to determine the receptiveness of a locally-developed app for psychiatry education internationally. Methods: A Web-based app that contained textbook contents, videos, and quizzes was developed using HTML5 technologies in 2012. Native apps were subsequently developed in 2013. Information about the apps was disseminated locally to Singaporean medical students, but the respective native apps were made available on the app stores. A user perspective survey was conducted locally to determine student’s perception of the app. Results: From the inception of the app until the time of preparation of this manuscript, there have been a cumulative total of 28,500 unique visits of the responsive HTML5 Web-based mobile phone app. There have been a cumulative total of 2200 downloads of the Mastering Psychiatry app from the Apple app store and 7000 downloads of the same app from the Android app store. The initial user perspective survey conducted locally highlighted that approximately a total of 95.2% (177/186) of students felt that having a psychiatry mobile phone app was deemed to be useful. Further chi-squared analysis demonstrated that there was a significant difference between males and females in their perception of having textbook contents in the mobile phone app (χ24=12.9, P=.0012). Conclusions: To the best of our knowledge, this is the first study to demonstrate the feasibility and global acceptance of a local, self-designed educational app for psychiatry education. Whilst the current research has managed to demonstrate the feasibility and acceptance of such an app, future studies would be warranted to look, in-depth, into whether there are cultural differences in terms of perceptions towards having such an app in psychiatry and what contents different cultures and cohorts of students might want within an app. %M 27731838 %R 10.2196/mededu.4179 %U https://medinform.jmir.org/2015/1/e3/ %U https://doi.org/10.2196/mededu.4179 %U http://www.ncbi.nlm.nih.gov/pubmed/27731838 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 2 %P e46 %T A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT) %A Eckhoff,Randall Peter %A Kizakevich,Paul Nicholas %A Bakalov,Vesselina %A Zhang,Yuying %A Bryant,Stephanie Patrice %A Hobbs,Maria Ann %+ RTI International, 3040 E. Cornwallis Rd., Research Triangle Park, NC, , United States, 1 919 541 7158, reckhoff@rti.org %K intervention studies %K mHealth %K mobile apps %K platform %K software engineering %K telemedicine %K tool %K toolkit %D 2015 %7 01.06.2015 %9 Tutorial %J JMIR mHealth uHealth %G English %X Personal Health Intervention Toolkit (PHIT) is an advanced cross-platform software framework targeted at personal self-help research on mobile devices. Following the subjective and objective measurement, assessment, and plan methodology for health assessment and intervention recommendations, the PHIT platform lets researchers quickly build mobile health research Android and iOS apps. They can (1) create complex data-collection instruments using a simple extensible markup language (XML) schema; (2) use Bluetooth wireless sensors; (3) create targeted self-help interventions based on collected data via XML-coded logic; (4) facilitate cross-study reuse from the library of existing instruments and interventions such as stress, anxiety, sleep quality, and substance abuse; and (5) monitor longitudinal intervention studies via daily upload to a Web-based dashboard portal. For physiological data, Bluetooth sensors collect real-time data with on-device processing. For example, using the BinarHeartSensor, the PHIT platform processes the heart rate data into heart rate variability measures, and plots these data as time-series waveforms. Subjective data instruments are user data-entry screens, comprising a series of forms with validation and processing logic. The PHIT instrument library consists of over 70 reusable instruments for various domains including cognitive, environmental, psychiatric, psychosocial, and substance abuse. Many are standardized instruments, such as the Alcohol Use Disorder Identification Test, Patient Health Questionnaire-8, and Post-Traumatic Stress Disorder Checklist. Autonomous instruments such as battery and global positioning system location support continuous background data collection. All data are acquired using a schedule appropriate to the app’s deployment. The PHIT intelligent virtual advisor (iVA) is an expert system logic layer, which analyzes the data in real time on the device. This data analysis results in a tailored app of interventions and other data-collection instruments. For example, if a user anxiety score exceeds a threshold, the iVA might add a meditation intervention to the task list in order to teach the user how to relax, and schedule a reassessment using the anxiety instrument 2 weeks later to re-evaluate. If the anxiety score exceeds a higher threshold, then an advisory to seek professional help would be displayed. Using the easy-to-use PHIT scripting language, the researcher can program new instruments, the iVA, and interventions to their domain-specific needs. The iVA, instruments, and interventions are defined via XML files, which facilities rapid app development and deployment. The PHIT Web-based dashboard portal provides the researcher access to all the uploaded data. After a secure login, the data can be filtered by criteria such as study, protocol, domain, and user. Data can also be exported into a comma-delimited file for further processing. The PHIT framework has proven to be an extensible, reconfigurable technology that facilitates mobile data collection and health intervention research. Additional plans include instrument development in other domains, additional health sensors, and a text messaging notification system. %M 26033047 %R 10.2196/mhealth.4202 %U http://mhealth.jmir.org/2015/2/e46/ %U https://doi.org/10.2196/mhealth.4202 %U http://www.ncbi.nlm.nih.gov/pubmed/26033047 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 2 %P e43 %T Public Health Guidelines for Physical Activity: Is There an App for That? A Review of Android and Apple App Stores %A Knight,Emily %A Stuckey,Melanie I %A Prapavessis,Harry %A Petrella,Robert J %+ University of Western Ontario, Centre for Studies in Family Medicine, 1151 Richmond Street, Rm 2117, London, ON, N6A 3K7, Canada, 1 519 933 8455, petrella@uwo.ca %K Mobile applications %K Exercise %K Public Health %D 2015 %7 21.05.2015 %9 Review %J JMIR mHealth uHealth %G English %X Background: Physical activity participation is an important behavior for modifying lifestyle-related disease risk. Mobile health apps for chronic disease management and prevention are being developed at a rapid rate. However, it is unclear whether these apps are evidence-based. Current public health recommendations for physical activity participation for adults highlight the importance of engaging in 150 minutes weekly of purposeful exercise, and muscle strengthening activities on at least 2 days of the week. Objective: The aims of the present review were to (1) identify available evidence-based physical activity apps, and (2) identify technological features that could be leveraged to improve health outcomes. Methods: iTunes and Google Play mobile app stores were searched using keyword and category searching during a single day (February 18, 2014) for physical activity apps available in English. The description pages of eligible apps were reviewed by 4 independent reviewers for evidence-based content, technological, and descriptive features. An a priori subset of apps was downloaded for further review (n=6 affiliated with a non-commercial agency; n=10 top rated; n=10 random selection), and developers were contacted for information regarding evidence-informed content. Results: The initial search yielded 2400 apps, of which 379 apps (n=206 iTunes; n=173 Google Play) were eligible. Primary results demonstrated no apps (n=0) adhering to evidence-based guidelines for aerobic physical activity, and 7 out of 379 implementing evidence-based guidelines for resistance training physical activity. Technological features of apps included social networking (n=207), pairing with a peripheral health device (n=61), and measuring additional health parameters (n=139). Secondary results revealed 1 app that referenced physical activity guidelines (150 minutes/weekly of exercise), and demonstrated that apps were based on various physical activity reports (n=4) or personal expertise (n=2). Conclusions: The present study demonstrated a shortage of evidence-based physical activity apps. This gap underscores the need for development of evidence-informed mobile apps. Results highlight the opportunity to develop evidence-informed mobile apps that can be used clinically to enhance health outcomes. %M 25998158 %R 10.2196/mhealth.4003 %U http://mhealth.jmir.org/2015/2/e43/ %U https://doi.org/10.2196/mhealth.4003 %U http://www.ncbi.nlm.nih.gov/pubmed/25998158 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 5 %P e112 %T Low Health Literacy and Evaluation of Online Health Information: A Systematic Review of the Literature %A Diviani,Nicola %A van den Putte,Bas %A Giani,Stefano %A van Weert,Julia CM %+ Amsterdam School of Communication Research / ASCoR, Department of Communication Science, University of Amsterdam, P.O. Box 15791, Amsterdam, 1001 NG, Netherlands, 31 6 15254105, N.Diviani@uva.nl %K health information seeking %K online health information %K information quality %K health literacy %D 2015 %7 07.05.2015 %9 Review %J J Med Internet Res %G English %X Background: Recent years have witnessed a dramatic increase in consumer online health information seeking. The quality of online health information, however, remains questionable. The issue of information evaluation has become a hot topic, leading to the development of guidelines and checklists to design high-quality online health information. However, little attention has been devoted to how consumers, in particular people with low health literacy, evaluate online health information. Objective: The main aim of this study was to review existing evidence on the association between low health literacy and (1) people’s ability to evaluate online health information, (2) perceived quality of online health information, (3) trust in online health information, and (4) use of evaluation criteria for online health information. Methods: Five academic databases (MEDLINE, PsycINFO, Web of Science, CINAHL, and Communication and Mass-media Complete) were systematically searched. We included peer-reviewed publications investigating differences in the evaluation of online information between people with different health literacy levels. Results: After abstract and full-text screening, 38 articles were included in the review. Only four studies investigated the specific role of low health literacy in the evaluation of online health information. The other studies examined the association between educational level or other skills-based proxies for health literacy, such as general literacy, and outcomes. Results indicate that low health literacy (and related skills) are negatively related to the ability to evaluate online health information and trust in online health information. Evidence on the association with perceived quality of online health information and use of evaluation criteria is inconclusive. Conclusions: The findings indicate that low health literacy (and related skills) play a role in the evaluation of online health information. This topic is therefore worth more scholarly attention. Based on the results of this review, future research in this field should (1) specifically focus on health literacy, (2) devote more attention to the identification of the different criteria people use to evaluate online health information, (3) develop shared definitions and measures for the most commonly used outcomes in the field of evaluation of online health information, and (4) assess the relationship between the different evaluative dimensions and the role played by health literacy in shaping their interplay. %M 25953147 %R 10.2196/jmir.4018 %U http://www.jmir.org/2015/5/e112/ %U https://doi.org/10.2196/jmir.4018 %U http://www.ncbi.nlm.nih.gov/pubmed/25953147 %0 Journal Article %@ 1923-2195 %I Gunther Eysenbach %V 4 %N 1 %P e2 %T Web 2.0 Applications in Medicine: Trends and Topics in the Literature %A Boudry,Christophe %+ Media Normandie, Normandy University, University of Caen Basse-Normandie, Esplanade de la Paix, Caen Cedex, 14032, France, 33 231565160, boudry@enc.sorbonne.fr %K Social media %K Internet %K Health information management %K bibliometrics %K Medline %K Blogging %K Medical Informatics %D 2015 %7 01.04.2015 %9 Original Paper %J Med 2.0 %G English %X Background: The World Wide Web has changed research habits, and these changes were further expanded when “Web 2.0” became popular in 2005. Bibliometrics is a helpful tool used for describing patterns of publication, for interpreting progression over time, and the geographical distribution of research in a given field. Few studies employing bibliometrics, however, have been carried out on the correlative nature of scientific literature and Web 2.0. Objective: The aim of this bibliometric analysis was to provide an overview of Web 2.0 implications in the biomedical literature. The objectives were to assess the growth rate of literature, key journals, authors, and country contributions, and to evaluate whether the various Web 2.0 applications were expressed within this biomedical literature, and if so, how. Methods: A specific query with keywords chosen to be representative of Web 2.0 applications was built for the PubMed database. Articles related to Web 2.0 were downloaded in Extensible Markup Language (XML) and were processed through developed hypertext preprocessor (PHP) scripts, then imported to Microsoft Excel 2010 for data processing. Results: A total of 1347 articles were included in this study. The number of articles related to Web 2.0 has been increasing from 2002 to 2012 (average annual growth rate was 106.3% with a maximum of 333% in 2005). The United States was by far the predominant country for authors, with 514 articles (54.0%; 514/952). The second and third most productive countries were the United Kingdom and Australia, with 87 (9.1%; 87/952) and 44 articles (4.6%; 44/952), respectively. Distribution of number of articles per author showed that the core population of researchers working on Web 2.0 in the medical field could be estimated at approximately 75. In total, 614 journals were identified during this analysis. Using Bradford’s law, 27 core journals were identified, among which three (Studies in Health Technology and Informatics, Journal of Medical Internet Research, and Nucleic Acids Research) produced more than 35 articles related to Web 2.0 over the period studied. A total of 274 words in the field of Web 2.0 were found after manual sorting of the 15,878 words appearing in title and abstract fields for articles. Word frequency analysis reveals “blog” as the most recurrent, followed by “wiki”, “Web 2.0”, ”social media”, “Facebook”, “social networks”, “blogger”, “cloud computing”, “Twitter”, and “blogging”. All categories of Web 2.0 applications were found, indicating the successful integration of Web 2.0 into the biomedical field. Conclusions: This study shows that the biomedical community is engaged in the use of Web 2.0 and confirms its high level of interest in these tools. Therefore, changes in the ways researchers use information seem to be far from over. %M 25842175 %R 10.2196/med20.3628 %U http://www.medicine20.com/2015/1/e2/ %U https://doi.org/10.2196/med20.3628 %U http://www.ncbi.nlm.nih.gov/pubmed/25842175 %0 Journal Article %@ 1929-0748 %I JMIR Publications Inc. %V 4 %N 1 %P e33 %T Clinical Effect Size of an Educational Intervention in the Home and Compliance With Mobile Phone-Based Reminders for People Who Suffer From Stroke: Protocol of a Randomized Controlled Trial %A Merchán-Baeza,Jose Antonio %A Gonzalez-Sanchez,Manuel %A Cuesta-Vargas,Antonio %+ Universidad de Malaga, C/ Arquitecto Francisco Peñalosa, Ampliación Campus Teatinos, Malaga, 29071, Spain, Malaga, 29071, Spain, 34 951 952 823, acuesta.var@gmail.com %K stroke %K ADL %K environment %K patient adherence %K mobile apps %K mobile health %D 2015 %7 10.03.2015 %9 Protocol %J JMIR Res Protoc %G English %X Background: Stroke is the third-leading cause of death and the leading cause of long-term neurological disability in the world. Cognitive, communication, and physical weakness combined with environmental changes frequently cause changes in the roles, routines, and daily occupations of stroke sufferers. Educational intervention combines didactic and interactive intervention, which combines the best choices for teaching new behaviors since it involves the active participation of the patient in learning. Nowadays, there are many types of interventions or means to increase adherence to treatment. Objective: The aim of this study is to enable patients who have suffered stroke and been discharged to their homes to improve the performance of the activities of daily living (ADL) in their home environment, based on advice given by the therapist. A secondary aim is that these patients continue the treatment through a reminder app installed on their mobile phones. Methods: This study is a clinical randomized controlled trial. The total sample will consist of 80 adults who have suffered a stroke with moderate severity and who have been discharged to their homes in the 3 months prior to recruitment to the study. The following tests and scales will be used to measure the outcome variables: Barthel Index, the Functional Independence Measure, the Mini-Mental State Examination, the Canadian Neurological Scale, the Stroke Impact Scale-16, the Trunk Control Test, the Modified Rankin Scale, the Multidimensional Scale of Perceived Social Support, the Quality of Life Scale for Stroke, the Functional Reach Test, the Romberg Test, the Time Up and Go test, the Timed-Stands Test, a portable dynamometer, and a sociodemographic questionnaire. Descriptive analyses will include mean, standard deviation, and 95% confidence intervals of the values for each variable. The Kolmogov-Smirnov (KS) test and a 2x2 mixed-model analysis of variance (ANOVA) will be used. Intergroup effect sizes will be calculated (Cohen’s d). Results: Currently, the study is in the recruitment phase and implementation of the intervention has begun. The authors anticipate that during 2015 the following processes should be completed: recruitment, intervention, and data collection. It is expected that the analysis of all data and the first results should be available in early-to-mid 2016. Conclusions: An educational intervention based on therapeutic home advice and a reminder app has been developed by the authors with the intention that patients who have suffered stroke perform the ADL more easily and use their affected limbs more actively in the ADL. The use of reminders via mobile phone is proposed as an innovative tool to increase treatment adherence in this population. Trial Registration: ClinicalTrials.gov NCT01980641; https://clinicaltrials.gov/ct2/show/NCT01980641 (Archived by WebCite at http://www.webcitation.org/6WRWFmY6U). %M 25757808 %R 10.2196/resprot.4034 %U http://www.researchprotocols.org/2015/1/e33/ %U https://doi.org/10.2196/resprot.4034 %U http://www.ncbi.nlm.nih.gov/pubmed/25757808 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 3 %P e62 %T Wikipedia and Medicine: Quantifying Readership, Editors, and the Significance of Natural Language %A Heilman,James M %A West,Andrew G %+ Faculty of Medicine, Department of Emergency Medicine, University of British Columbia, 2194 Health Sciences Mall, Unit 317, Vancouver, BC, V6T1Z3, Canada, 1 4158306381, jmh649@gmail.com %K health information systems %K consumer health information %K information sharing %K information networks %K information science %K Internet %K Web 2.0 %K cooperative behavior %D 2015 %7 04.03.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: Wikipedia is a collaboratively edited encyclopedia. One of the most popular websites on the Internet, it is known to be a frequently used source of health care information by both professionals and the lay public. Objective: This paper quantifies the production and consumption of Wikipedia’s medical content along 4 dimensions. First, we measured the amount of medical content in both articles and bytes and, second, the citations that supported that content. Third, we analyzed the medical readership against that of other health care websites between Wikipedia’s natural language editions and its relationship with disease prevalence. Fourth, we surveyed the quantity/characteristics of Wikipedia’s medical contributors, including year-over-year participation trends and editor demographics. Methods: Using a well-defined categorization infrastructure, we identified medically pertinent English-language Wikipedia articles and links to their foreign language equivalents. With these, Wikipedia can be queried to produce metadata and full texts for entire article histories. Wikipedia also makes available hourly reports that aggregate reader traffic at per-article granularity. An online survey was used to determine the background of contributors. Standard mining and visualization techniques (eg, aggregation queries, cumulative distribution functions, and/or correlation metrics) were applied to each of these datasets. Analysis focused on year-end 2013, but historical data permitted some longitudinal analysis. Results: Wikipedia’s medical content (at the end of 2013) was made up of more than 155,000 articles and 1 billion bytes of text across more than 255 languages. This content was supported by more than 950,000 references. Content was viewed more than 4.88 billion times in 2013. This makes it one of if not the most viewed medical resource(s) globally. The core editor community numbered less than 300 and declined over the past 5 years. The members of this community were half health care providers and 85.5% (100/117) had a university education. Conclusions: Although Wikipedia has a considerable volume of multilingual medical content that is extensively read and well-referenced, the core group of editors that contribute and maintain that content is small and shrinking in size. %M 25739399 %R 10.2196/jmir.4069 %U http://www.jmir.org/2015/3/e62/ %U https://doi.org/10.2196/jmir.4069 %U http://www.ncbi.nlm.nih.gov/pubmed/25739399 %0 Journal Article %@ 1923-2195 %I Gunther Eysenbach %V 4 %N 1 %P e1 %T Acceptance Factors of Mobile Apps for Diabetes by Patients Aged 50 or Older: A Qualitative Study %A Scheibe,Madlen %A Reichelt,Julius %A Bellmann,Maike %A Kirch,Wilhelm %+ Technische Universität Dresden, Medizinische Fakultät Carl Gustav Carus, Research Association Public Health Saxony and Saxony-Anhalt, Fiedlerstraße 33, Dresden, 01307, Germany, 49 351 458 6499, Madlen.Scheibe@uniklinikum-dresden.de %K mobile apps %K mobile health %K elderly %K diabetes mellitus %K blood sugar self-monitoring %K patient acceptance of health care %K qualitative research %K guided interviews %D 2015 %7 02.03.2015 %9 Original Paper %J Med 2.0 %G English %X Background: Mobile apps for people with diabetes offer great potential to support therapy management, increase therapy adherence, and reduce the probability of the occurrence of accompanying and secondary diseases. However, they are rarely used by elderly patients due to a lack of acceptance. Objective: We investigated the question “Which factors influence the acceptance of diabetes apps among patients aged 50 or older?” Particular emphasis was placed on the current use of mobile devices/apps, acceptance-promoting/-inhibiting factors, features of a helpful diabetes app, and contact persons for technical questions. This qualitative study was the third of three substudies investigating factors influencing acceptance of diabetes apps among patients aged 50 or older. Methods: Guided interviews were chosen in order to get a comprehensive insight into the subjective perspective of elderly diabetes patients. At the end of each interview, the patients tested two existing diabetes apps to reveal obstacles in (first) use. Results: Altogether, 32 patients with diabetes were interviewed. The mean age was 68.8 years (SD 8.2). Of 32 participants, 15 (47%) knew apps, however only 2 (6%) had already used a diabetes app within their therapy. The reasons reported for being against the use of apps were a lack of additional benefits (4/8, 50%) compared to current therapy management, a lack of interoperability with other devices/apps (1/8, 12%), and no joy of use (1/8, 12%). The app test revealed the following main difficulties in use: nonintuitive understanding of the functionality of the apps (26/29, 90%), nonintuitive understanding of the menu navigation/labeling (19/29, 66%), font sizes and representations that were too small (14/29, 48%), and difficulties in recognizing and pressing touch-sensitive areas (14/29, 48%). Furthermore, the patients felt the apps lacked individually important functions (11/29, 38%), or felt the functions that were offered were unnecessary for their own therapy needs (10/29, 34%). The most important contents of a helpful diabetes app were reported as the ability to add remarks to measured values (9/28, 32%), the definition of thresholds for blood glucose values and highlighting deviating values (7/28, 25%), and a reminder feature for measurement/medication (7/28, 25%). The most important contact persons for technical questions were family members (19/31, 61%). Conclusions: A lack of additional benefits and ease of use emerged as the key factors for the acceptance of diabetes apps among patients aged 50 or older. Furthermore, it has been shown that the needs of the investigated target group are highly heterogeneous due to varying previous knowledge, age, type of diabetes, and therapy. Therefore, a helpful diabetes app should be individually adaptable. Personal contact persons, especially during the initial phase of use, are of utmost importance to reduce the fear of data loss or erroneous data input, and to raise acceptance among this target group. %R 10.2196/med20.3912 %U http://www.medicine20.com/2015/1/e1/ %U https://doi.org/10.2196/med20.3912