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      Internet-delivered psychological treatments: from innovation to implementation : Internet-delivered psychological treatments: from innovation to implementation

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          Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-analysis.

          We studied to what extent internet-based cognitive behaviour therapy (CBT) programs for symptoms of depression and anxiety are effective. A meta-analysis of 12 randomized controlled trials. The effects of internet-based CBT were compared to control conditions in 13 contrast groups with a total number of 2334 participants. A meta-analysis on treatment contrasts resulted in a moderate to large mean effect size [fixed effects analysis (FEA) d=0.40, mixed effects analysis (MEA) d=0.60] and significant heterogeneity. Therefore, two sets of post hoc subgroup analyses were carried out. Analyses on the type of symptoms revealed that interventions for symptoms of depression had a small mean effect size (FEA d=0.27, MEA d=0.32) and significant heterogeneity. Further analyses showed that one study could be regarded as an outlier. Analyses without this study showed a small mean effect size and moderate, non-significant heterogeneity. Interventions for anxiety had a large mean effect size (FEA and MEA d=0.96) and very low heterogeneity. When examining the second set of subgroups, based on therapist assistance, no significant heterogeneity was found. Interventions with therapist support (n=5) had a large mean effect size, while interventions without therapist support (n=6) had a small mean effect size (FEA d=0.24, MEA d=0.26). In general, effect sizes of internet-based interventions for symptoms of anxiety were larger than effect sizes for depressive symptoms; however, this might be explained by differences in the amount of therapist support.
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            Internet-based and other computerized psychological treatments for adult depression: a meta-analysis.

            Computerized and, more recently, Internet-based treatments for depression have been developed and tested in controlled trials. The aim of this meta-analysis was to summarize the effects of these treatments and investigate characteristics of studies that may be related to the effects. In particular, the authors were interested in the role of personal support when completing a computerized treatment. Following a literature search and coding, the authors included 12 studies, with a total of 2446 participants. Ten of the 12 studies were delivered via the Internet. The mean effect size of the 15 comparisons between Internet-based and other computerized psychological treatments vs. control groups at posttest was d = 0.41 (95% confidence interval [CI]: 0.29-0.54). However, this estimate was moderated by a significant difference between supported (d = 0.61; 95% CI: 0.45-0.77) and unsupported (d = 0.25; 95% CI: 0.14-0.35) treatments. The authors conclude that although more studies are needed, Internet and other computerized treatments hold promise as potentially evidence-based treatments of depression.
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              Persuasive System Design Does Matter: A Systematic Review of Adherence to Web-Based Interventions

              Background Although web-based interventions for promoting health and health-related behavior can be effective, poor adherence is a common issue that needs to be addressed. Technology as a means to communicate the content in web-based interventions has been neglected in research. Indeed, technology is often seen as a black-box, a mere tool that has no effect or value and serves only as a vehicle to deliver intervention content. In this paper we examine technology from a holistic perspective. We see it as a vital and inseparable aspect of web-based interventions to help explain and understand adherence. Objective This study aims to review the literature on web-based health interventions to investigate whether intervention characteristics and persuasive design affect adherence to a web-based intervention. Methods We conducted a systematic review of studies into web-based health interventions. Per intervention, intervention characteristics, persuasive technology elements and adherence were coded. We performed a multiple regression analysis to investigate whether these variables could predict adherence. Results We included 101 articles on 83 interventions. The typical web-based intervention is meant to be used once a week, is modular in set-up, is updated once a week, lasts for 10 weeks, includes interaction with the system and a counselor and peers on the web, includes some persuasive technology elements, and about 50% of the participants adhere to the intervention. Regarding persuasive technology, we see that primary task support elements are most commonly employed (mean 2.9 out of a possible 7.0). Dialogue support and social support are less commonly employed (mean 1.5 and 1.2 out of a possible 7.0, respectively). When comparing the interventions of the different health care areas, we find significant differences in intended usage (p = .004), setup (p < .001), updates (p < .001), frequency of interaction with a counselor (p < .001), the system (p = .003) and peers (p = .017), duration (F = 6.068, p = .004), adherence (F = 4.833, p = .010) and the number of primary task support elements (F = 5.631, p = .005). Our final regression model explained 55% of the variance in adherence. In this model, a RCT study as opposed to an observational study, increased interaction with a counselor, more frequent intended usage, more frequent updates and more extensive employment of dialogue support significantly predicted better adherence. Conclusions Using intervention characteristics and persuasive technology elements, a substantial amount of variance in adherence can be explained. Although there are differences between health care areas on intervention characteristics, health care area per se does not predict adherence. Rather, the differences in technology and interaction predict adherence. The results of this study can be used to make an informed decision about how to design a web-based intervention to which patients are more likely to adhere.
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                Author and article information

                Journal
                World Psychiatry
                World Psychiatry
                Wiley
                17238617
                February 2019
                February 2019
                January 02 2019
                : 18
                : 1
                : 20-28
                Affiliations
                [1 ]Department of Behavioural Sciences and Learning; Linköping University; Linköping Sweden
                [2 ]Department of Clinical Neuroscience, Division of Psychiatry; Karolinska Institutet; Stockholm Sweden
                [3 ]MindSpot Clinic; Macquarie University; Sydney Australia
                [4 ]eCentreClinic, Department of Psychology; Macquarie University; Sydney Australia
                [5 ]Institute of Child Health, University College London; London UK
                [6 ]Department of Psychology; Stockholm University; Stockholm Sweden
                [7 ]Department of Psychology; University of Southern Denmark; Odense Denmark
                10.1002/wps.20610
                © 2019

                http://doi.wiley.com/10.1002/tdm_license_1.1

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