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      Exploring the Role of In-Person Components for Online Health Behavior Change Interventions: Can a Digital Person-to-Person Component Suffice?

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          Abstract

          The growth of the digital environment provides tremendous opportunities to revolutionize health behavior change efforts. This paper explores the use of Web-based, mobile, and social media health behavior change interventions and determines whether there is a need for a face-to-face or an in-person component. It is further argued that that although in-person components can be beneficial for online interventions, a digital person-to-person component can foster similar results while dealing with challenges faced by traditional intervention approaches. Using a digital person-to-person component is rooted in social and behavioral theories such as the theory of reasoned action, and the social cognitive theory, and further justified by the human support constructs of the model of supportive accountability. Overall, face-to-face and online behavior change interventions have their respective advantages and disadvantages and functions, yet both serve important roles. It appears that it is in fact human support that is the most important component in the effectiveness and adherence of both face-to-face and online behavior change interventions, and thoughtfully introducing a digital person-to-person component, to replace face-to-face interactions, can provide the needed human support while diminishing the barriers of in-person meetings. The digital person-to-person component must create accountability, generate opportunities for tailored feedback, and create social support to successfully create health behavior change. As the popularity of the online world grows, and the interest in using the digital environment for health behavior change interventions continues to be embraced, further research into not only the use of online interventions, but the use of a digital person-to-person component, must be explored.

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

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

            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.
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              The influence of social networking sites on health behavior change: a systematic review and meta-analysis.

              Our aim was to evaluate the use and effectiveness of interventions using social networking sites (SNSs) to change health behaviors.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                April 2018
                11 April 2018
                : 20
                : 4
                : e144
                Affiliations
                [1] 1 Department of Kinesiology University of Windsor Windsor, ON Canada
                [2] 2 Faculty of Nursing University of Windsor Windsor, ON Canada
                [3] 3 Department of Psychology University of Windsor Windsor, ON Canada
                [4] 4 Department of Women’s and Gender Studies University of Windsor Windsor, ON Canada
                Author notes
                Corresponding Author: Sara Santarossa santaros@ 123456uwindsor.ca
                Author information
                http://orcid.org/0000-0003-3038-4976
                http://orcid.org/0000-0002-9727-8126
                http://orcid.org/0000-0002-3463-5704
                http://orcid.org/0000-0002-8199-2982
                Article
                v20i4e144
                10.2196/jmir.8480
                5917076
                29643048
                aad691d8-7894-416a-9718-f45b72a153a7
                ©Sara Santarossa, Deborah Kane, Charlene Y Senn, Sarah J Woodruff. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 11.04.2018.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 14 July 2017
                : 16 January 2018
                : 23 February 2018
                : 25 February 2018
                Categories
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                Medicine
                digital person-to-person,in-person,online intervention,behavior change,health, digital media,health care

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