Top 10 Google Scholar Citations per Month JMIR Articles(All Time)

Medicine 2.0: Social Networking, Collaboration, Participation, Apomediation, and Openness

Mon, 25 Aug 2008 18:23:14 EDT

In a very significant development for eHealth, a broad adoption of Web 2.0 technologies and approaches coincides with the more recent emergence of Personal Health Application Platforms and Personally Controlled Health Records such as Google Health, Microsoft HealthVault, and Dossia. “Medicine 2.0” applications, services and tools are defined as Web-based services for health care consumers, caregivers, patients, health professionals, and biomedical researchers, that use Web 2.0 technologies and/or semantic web and virtual reality approaches to enable and facilitate specifically 1) social networking, 2) participation, 3) apomediation, 4) openness and 5) collaboration, within and between these user groups. The Journal of Medical Internet Research (JMIR) publishes a Medicine 2.0 theme issue and sponsors a conference on “How Social Networking and Web 2.0 changes Health, Health Care, Medicine and Biomedical Research”, to stimulate and encourage research in these five areas.

Google Scholar Citations Per Month: 5.43

Using the Internet to Promote Health Behavior Change: A Systematic Review and Meta-analysis of the Impact of Theoretical Basis, Use of Behavior Change Techniques, and Mode of Delivery on Efficacy

Wed, 17 Feb 2010 13:03:11 EST

Background: The Internet is increasingly used as a medium for the delivery of interventions designed to promote health behavior change. However, reviews of these interventions to date have not systematically identified intervention characteristics and linked these to effectiveness. Objectives: The present review sought to capitalize on recently published coding frames for assessing use of theory and behavior change techniques to investigate which characteristics of Internet-based interventions best promote health behavior change. In addition, we wanted to develop a novel coding scheme for assessing mode of delivery in Internet-based interventions and also to link different modes to effect sizes. Methods: We conducted a computerized search of the databases indexed by ISI Web of Knowledge (including BIOSIS Previews and Medline) between 2000 and 2008. Studies were included if (1) the primary components of the intervention were delivered via the Internet, (2) participants were randomly assigned to conditions, and (3) a measure of behavior related to health was taken after the intervention. Results: We found 85 studies that satisfied the inclusion criteria, providing a total sample size of 43,236 participants. On average, interventions had a statistically small but significant effect on health-related behavior (d+ = 0.16, 95% CI 0.09-0.23). More extensive use of theory was associated with increases in effect size (P = .049), and, in particular, interventions based on the theory of planned behavior tended to have substantial effects on behavior (d+ = 0.36, 95% CI 0.15-0.56). Interventions that incorporated more behavior change techniques also tended to have larger effects compared to interventions that incorporated fewer techniques (P < .001). Finally, the effectiveness of Internet-based interventions was enhanced by the use of additional methods of communicating with participants, especially the use of short message service (SMS), or text, messages. Conclusions: The review provides a framework for the development of a science of Internet-based interventions, and our findings provide a rationale for investing in more intensive theory-based interventions that incorporate multiple behavior change techniques and modes of delivery.

Google Scholar Citations Per Month: 4.22

Determinants of Engagement in Face-to-Face and Online Patient Support Groups

Wed, 07 Dec 2011 11:55:25 EST

Background: Although peer-to-peer contact might empower patients in various ways, studies show that only a few patients actually engage in support groups. Objective: The objective of our study was to explore factors that facilitate or impede engagement in face-to-face and online peer support, using the Theory of Planned Behavior. Methods: A questionnaire was completed by 679 patients being treated for arthritis, breast cancer, or fibromyalgia at two Dutch regional hospitals. Results: Our results showed that only a minority of the patients engaged in organized forms of peer support. In total 10% (65/679) of the respondents had engaged in face-to-face meetings for patients in the past year. Only 4% (30/679) of the respondents had contact with peers via the Internet in the past year. Patients were more positive about face-to-face peer support than about online peer support (P < .001). In accordance with the Theory of Planned Behavior, having a more positive attitude (P < .01) and feeling more supported by people in the social environment (P < .001) increased the intention to participate in both kinds of peer support. In addition, perceived behavioral control (P = .01) influenced the intention to participate in online peer support. Nevertheless, the intention to engage in face-to-face and online peer support was only modestly predicted by the Theory of Planned Behavior variables (R2 = .33 for face-to-face contact and R2 = .26 for online contact). Conclusion: Although Health 2.0 Internet technology has significantly increased opportunities for having contact with fellow patients, only a minority seem to be interested in organized forms of peer contact (either online or face-to-face). Patients seem somewhat more positive about face-to-face contact than about online contact.

Google Scholar Citations Per Month: 3.97

What is e-health?

Mon, 18 Jun 2001 00:00:00 EDT

No Abstract Available

Google Scholar Citations Per Month: 3.89

Online Communication Between Doctors and Patients in Europe: Status and Perspectives

Tue, 15 Jun 2010 11:23:34 EDT

Background: Use of the Internet for health purposes is steadily increasing in Europe, while the eHealth market is still a niche. Online communication between doctor and patient is one aspect of eHealth with potentially great impact on the use of health systems, patient-doctor roles and relations and individuals’ health. Monitoring and understanding practices, trends, and expectations in this area is important, as it may bring invaluable knowledge to all stakeholders, in the Health 2.0 era. Objective: Our two main goals were: (1) to investigate use of the Internet and changes in expectations about future use for particular aspects of communication with a known doctor (obtaining a prescription, scheduling an appointment, or asking a particular health question), and (2) to investigate how important the provision of email and Web services to communicate with the physician is when choosing a new doctor for a first time face-to-face appointment. The data come from the second survey of the eHealth Trends study, which addressed trends and perspectives of health-related Internet use in Europe. This study builds on previous work that established levels of generic use of the Internet for self-help activities, ordering medicine or other health products, interacting with a Web doctor/unknown health professional, and communicating with a family doctor or other known health professional. Methods: A representative sample of citizens from seven European countries was surveyed (n = 7022) in April and May of 2007 through computer-assisted telephone interviews (CATI). Respondents were questioned about their use of the Internet to obtain a prescription, schedule an appointment, or ask a health professional about a particular health question. They were also asked what their expectations were regarding future use of the Internet for health-related matters. In a more pragmatic approach to the subject, they were asked about the perceived importance when choosing a new doctor of the possibility of using email and the Web to communicate with that physician. Logistic regression analysis was used to draw the profiles of users of related eHealth services in Europe among the population in general and in the subgroup of those who use the Internet for health-related matters. Changes from 2005 to 2007 were computed using data from the first eHealth Trends survey (October and November 2005, n = 7934). Results: In 2007, an estimated 1.8% (95% confidence interval [CI], 1.5 - 2.1) of the population in these countries had used the Internet to request or renew a prescription; 3.2% (95% CI 2.8 - 3.6) had used the Internet to schedule an appointment; and 2.5% (95% CI 2.2 - 2.9) had used the Internet to ask a particular health question. This represents estimated increases of 0.9% (95% CI 0.5 - 1.3), 1.7% (95% CI 1.2 - 2.2), and 1.4% (95% CI 0.9 - 1.8). An estimated 18.0% (95% CI 17.1 - 18.9) of the populations of these countries expected that in the near future they would have consultations with health professionals online, and 25.4% (95% CI 24.4 - 26.3) expected that in the near future they would be able to schedule an appointment online. Among those using the Internet for health-related purposes, on average more than 4 in 10 people considered the provision of these eHealth services to be important when choosing a new doctor. Conclusions: Use of the Internet to communicate with a known health professional is still rare in Europe. Legal context, health policy issues, and technical conditions prevailing in different countries might be playing a major role in the situation. Interest in associated eHealth services is high among citizens and likely to increase.

Google Scholar Citations Per Month: 3.88

The Effectiveness of Web-Based vs. Non-Web-Based Interventions: A Meta-Analysis of Behavioral Change Outcomes

Wed, 10 Nov 2004 00:00:00 EST

BACKGROUND: A primary focus of self-care interventions for chronic illness is the encouragement of an individual's behavior change necessitating knowledge sharing, education, and understanding of the condition. The use of the Internet to deliver Web-based interventions to patients is increasing rapidly. In a 7-year period (1996 to 2003), there was a 12-fold increase in MEDLINE citations for “Web-based therapies.” The use and effectiveness of Web-based interventions to encourage an individual's change in behavior compared to non-Web-based interventions have not been substantially reviewed. OBJECTIVE: This meta-analysis was undertaken to provide further information on patient/client knowledge and behavioral change outcomes after Web-based interventions as compared to outcomes seen after implementation of non-Web-based interventions. METHODS: The MEDLINE, CINAHL, Cochrane Library, EMBASE, ERIC, and PSYCHInfo databases were searched for relevant citations between the years 1996 and 2003. Identified articles were retrieved, reviewed, and assessed according to established criteria for quality and inclusion/exclusion in the study. Twenty-two articles were deemed appropriate for the study and selected for analysis. Effect sizes were calculated to ascertain a standardized difference between the intervention (Web-based) and control (non-Web-based) groups by applying the appropriate meta-analytic technique. Homogeneity analysis, forest plot review, and sensitivity analyses were performed to ascertain the comparability of the studies. RESULTS: Aggregation of participant data revealed a total of 11,754 participants (5,841 women and 5,729 men). The average age of participants was 41.5 years. In those studies reporting attrition rates, the average drop out rate was 21% for both the intervention and control groups. For the five Web-based studies that reported usage statistics, time spent/session/person ranged from 4.5 to 45 minutes. Session logons/person/week ranged from 2.6 logons/person over 32 weeks to 1008 logons/person over 36 weeks. The intervention designs included one-time Web-participant health outcome studies compared to non-Web participant health outcomes, self-paced interventions, and longitudinal, repeated measure intervention studies. Longitudinal studies ranged from 3 weeks to 78 weeks in duration. The effect sizes for the studied outcomes ranged from -.01 to .75. Broad variability in the focus of the studied outcomes precluded the calculation of an overall effect size for the compared outcome variables in the Web-based compared to the non-Web-based interventions. Homogeneity statistic estimation also revealed widely differing study parameters (Qw16 = 49.993, P ≤ .001). There was no significant difference between study length and effect size. Sixteen of the 17 studied effect outcomes revealed improved knowledge and/or improved behavioral outcomes for participants using the Web-based interventions. Five studies provided group information to compare the validity of Web-based vs. non-Web-based instruments using one-time cross-sectional studies. These studies revealed effect sizes ranging from -.25 to +.29. Homogeneity statistic estimation again revealed widely differing study parameters (Qw4 = 18.238, P ≤ .001). CONCLUSIONS: The effect size comparisons in the use of Web-based interventions compared to non-Web-based interventions showed an improvement in outcomes for individuals using Web-based interventions to achieve the specified knowledge and/or behavior change for the studied outcome variables. These outcomes included increased exercise time, increased knowledge of nutritional status, increased knowledge of asthma treatment, increased participation in healthcare, slower health decline, improved body shape perception, and 18-month weight loss maintenance.

Google Scholar Citations Per Month: 3.83

The Law of Attrition

Thu, 31 Mar 2005 00:00:00 EST

In an ongoing effort of this Journal to develop and further the theories, models, and best practices around eHealth research, this paper argues for the need for a “science of attrition”, that is, a need to develop models for discontinuation of eHealth applications and the related phenomenon of participants dropping out of eHealth trials. What I call “law of attrition” here is the observation that in any eHealth trial a substantial proportion of users drop out before completion or stop using the appplication. This feature of eHealth trials is a distinct characteristic compared to, for example, drug trials. The traditional clinical trial and evidence-based medicine paradigm stipulates that high dropout rates make trials less believable. Consequently eHealth researchers tend to gloss over high dropout rates, or not to publish their study results at all, as they see their studies as failures. However, for many eHealth trials, in particular those conducted on the Internet and in particular with self-help applications, high dropout rates may be a natural and typical feature. Usage metrics and determinants of attrition should be highlighted, measured, analyzed, and discussed. This also includes analyzing and reporting the characteristics of the subpopulation for which the application eventually “works”, ie, those who stay in the trial and use it. For the question of what works and what does not, such attrition measures are as important to report as pure efficacy measures from intention-to-treat (ITT) analyses. In cases of high dropout rates efficacy measures underestimate the impact of an application on a population which continues to use it. Methods of analyzing attrition curves can be drawn from survival analysis methods, eg, the Kaplan-Meier analysis and proportional hazards regression analysis (Cox model). Measures to be reported include the relative risk of dropping out or of stopping the use of an application, as well as a “usage half-life”, and models reporting demographic and other factors predicting usage discontinuation in a population. Differential dropout or usage rates between two interventions could be a standard metric for the “usability efficacy” of a system. A “run-in and withdrawal” trial design is suggested as a methodological innovation for Internet-based trials with a high number of initial dropouts/nonusers and a stable group of hardcore users.

Google Scholar Citations Per Month: 3.36

Social Media Use in the United States: Implications for Health Communication

Fri, 27 Nov 2009 11:24:54 EST

Background: Given the rapid changes in the communication landscape brought about by participative Internet use and social media, it is important to develop a better understanding of these technologies and their impact on health communication. The first step in this effort is to identify the characteristics of current social media users. Up-to-date reporting of current social media use will help monitor the growth of social media and inform health promotion/communication efforts aiming to effectively utilize social media. Objective: The purpose of the study is to identify the sociodemographic and health-related factors associated with current adult social media users in the United States. Methods: Data came from the 2007 iteration of the Health Information National Trends Study (HINTS, N = 7674). HINTS is a nationally representative cross-sectional survey on health-related communication trends and practices. Survey respondents who reported having accessed the Internet (N = 5078) were asked whether, over the past year, they had (1) participated in an online support group, (2) written in a blog, (3) visited a social networking site. Bivariate and multivariate logistic regression analyses were conducted to identify predictors of each type of social media use. Results: Approximately 69% of US adults reported having access to the Internet in 2007. Among Internet users, 5% participated in an online support group, 7% reported blogging, and 23% used a social networking site. Multivariate analysis found that younger age was the only significant predictor of blogging and social networking site participation; a statistically significant linear relationship was observed, with younger categories reporting more frequent use. Younger age, poorer subjective health, and a personal cancer experience predicted support group participation. In general, social media are penetrating the US population independent of education, race/ethnicity, or health care access. Conclusions: Recent growth of social media is not uniformly distributed across age groups; therefore, health communication programs utilizing social media must first consider the age of the targeted population to help ensure that messages reach the intended audience. While racial/ethnic and health status–related disparities exist in Internet access, among those with Internet access, these characteristics do not affect social media use. This finding suggests that the new technologies, represented by social media, may be changing the communication pattern throughout the United States.

Google Scholar Citations Per Month: 2.55

eHealth Trends in Europe 2005-2007: A Population-Based Survey

Mon, 17 Nov 2008 08:57:12 EST

Background: In the last decade, the number of Internet users worldwide has dramatically increased. People are using the Internet for various health-related purposes. It is important to monitor such use as it may have an impact on the individual’s health and behavior, patient-practitioner roles, and on general health care provision. Objectives: This study investigates trends and patterns of European health-related Internet use over a period of 18 months. The main study objective was to estimate the change in the proportion of the population using the Internet for health purposes, and the importance of the Internet as a source of health information compared to more traditional sources. Methods: The survey data were collected through computer-assisted telephone interviews. A representative sample (N = 14,956) from seven European countries has been used: Denmark, Germany, Greece, Latvia, Norway, Poland, and Portugal. The European eHealth Consumer Trends Survey was first conducted in October-November 2005 and repeated in April-May 2007. In addition to providing background information, respondents were asked to rate the importance of various sources of health information. They were also queried as to the frequency of different online activities related to health and illness and the effects of such use on their disposition. Results: The percentage of the population that has used the Internet for health purposes increased from an estimated 42.3% (95% CI [Confidence Interval] 41.3 - 43.3) in 2005 to an estimated 52.2% (95% CI 51.3 - 53.2) in 2007. Significant growth in the use of the Internet for health purposes was found in all the seven countries. Young women are the most active Internet health users. The importance of the Internet as a source of health information has increased. In 2007, the Internet was perceived as an important source of health information by an estimated 46.8% (95% CI 45.7 - 47.9) of the population, a significant increase of 6.5 % (95% CI 4.9 - 8.1) from 2005. The importance of all the traditional health information channels has either decreased or remained the same. An estimated 22.7% (95% CI 21.7 - 23.6) are using it for more interactive services than just reading health information. Conclusion: The Internet is increasingly being used as a source of health information by the European population, and its perceived importance is rising. Use of the Internet for health purposes is growing in all age groups and for both men and women, with especially strong growth among young women. We see that experienced Internet health users are also using the Internet as an active communication channel, both for reaching health professionals and for communicating with peers.

Google Scholar Citations Per Month: 2.53

CONSORT-EHEALTH: Improving and Standardizing Evaluation Reports of Web-based and Mobile Health Interventions

Sat, 31 Dec 2011 23:59:39 EST

Background: Web-based and mobile health interventions (also called “Internet interventions” or "eHealth/mHealth interventions") are tools or treatments, typically behaviorally based, that are operationalized and transformed for delivery via the Internet or mobile platforms. These include electronic tools for patients, informal caregivers, healthy consumers, and health care providers. The Consolidated Standards of Reporting Trials (CONSORT) statement was developed to improve the suboptimal reporting of randomized controlled trials (RCTs). While the CONSORT statement can be applied to provide broad guidance on how eHealth and mHealth trials should be reported, RCTs of web-based interventions pose very specific issues and challenges, in particular related to reporting sufficient details of the intervention to allow replication and theory-building. Objective: To develop a checklist, dubbed CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile HEalth Applications and onLine TeleHealth), as an extension of the CONSORT statement that provides guidance for authors of eHealth and mHealth interventions. Methods: A literature review was conducted, followed by a survey among eHealth experts and a workshop. Results: A checklist instrument was constructed as an extension of the CONSORT statement. The instrument has been adopted by the Journal of Medical Internet Research (JMIR) and authors of eHealth RCTs are required to submit an electronic checklist explaining how they addressed each subitem. Conclusions: CONSORT-EHEALTH has the potential to improve reporting and provides a basis for evaluating the validity and applicability of eHealth trials. Subitems describing how the intervention should be reported can also be used for non-RCT evaluation reports. As part of the development process, an evaluation component is essential; therefore, feedback from authors will be solicited, and a before-after study will evaluate whether reporting has been improved.

Google Scholar Citations Per Month: 2.51