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      From black box to toolbox: Outlining device functionality, engagement activities, and the pervasive information architecture of mHealth interventions

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          Abstract

          mHealth interventions that deliver content via mobile phones represent a burgeoning area of health behavior change. The current paper examines two themes that can inform the underlying design of mHealth interventions: (1) mobile device functionality, which represents the technological toolbox available to intervention developers; and (2) the pervasive information architecture of mHealth interventions, which determines how intervention content can be delivered concurrently using mobile phones, personal computers, and other devices. We posit that developers of mHealth interventions will be better able to achieve the promise of this burgeoning arena by leveraging the toolbox and functionality of mobile devices in order to engage participants and encourage meaningful behavior change within the context of a carefully designed pervasive information architecture.

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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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            Health and the mobile phone.

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              The efficacy of internet interventions for depression and anxiety disorders: a review of randomised controlled trials.

              To review the outcomes, nature and quality of published randomised controlled trials of preventive and treatment internet interventions for depression and anxiety disorders, and to document the availability of effective interventions. Previous reviews of internet interventions for mental health and related conditions were updated using an extension of the original methodology. All studies included in the original reviews and more recent eligible trials (published before June 2009) were included, together with any trials identified from a search of the health intervention web portal Beacon and the Journal of Medical Internet Research. A total of 29 reports describing 26 trials satisfied the inclusion criteria. All trials employed a cognitive behaviour therapy intervention program. Of the 26 trials, 23 demonstrated some evidence of effectiveness relative to controls. Effect size differences ranged from 0.42 to 0.65 for depression interventions involving participants with clinically significant symptoms of depression, and 0.29 to 1.74 for anxiety interventions involving participants with a diagnosed anxiety disorder. Of the five effective English-language programs, three are available to the public without charge and two can be accessed at a small cost through health practitioner referral. Internet interventions for depression and anxiety disorders offer promise for use as self-help applications for consumers or as an adjunct to usual care.
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                Author and article information

                Journal
                101631612
                42488
                Internet Interv
                Internet Interv
                Internet interventions : the application of information technology in mental and behavioural health
                2214-7829
                10 February 2015
                1 March 2015
                01 March 2016
                : 2
                : 1
                : 91-101
                Affiliations
                [a ]Oregon Research Institute, Eugene OR, USA
                [b ]Norwegian Centre for Addiction Research, University of Oslo, Oslo, Norway
                [c ]IEQ Technology, Springfield OR, USA
                Article
                NIHMS662256
                10.1016/j.invent.2015.01.002
                4346786
                25750862
                9057842e-9eea-4278-a60d-8e035798ce3f
                © 2015 Published by Elsevier B.V.

                This manuscript version is made available under the CC BY-NC-ND 4.0 license.

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                mhealth,ehealth,toolbox,blackbox,internet interventions,pervasive information architecture

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