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      Effectiveness of Social Media Interventions for People With Schizophrenia: A Systematic Review and Meta-Analysis

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          Abstract

          Background

          Recent studies have shown that people with serious mental disorders spend time online for the purposes of disclosure, information gathering, or gaming. However, coherent information on the effects of social media on treatment for people with schizophrenia is still lacking.

          Objective

          Our aim was to determine the effects of social media interventions for supporting mental health and well-being among people with schizophrenia.

          Methods

          A systematic review and meta-analysis were undertaken to determine the effects of social media interventions for supporting mental health and well-being among people with schizophrenia. Ten databases were searched, while search parameters included English-only manuscripts published prior to June 25, 2015. Study appraisals were made independently by 2 reviewers, and qualitative and quantitative syntheses of data were conducted.

          Results

          Out of 1043 identified records, only two randomized studies of moderate quality (three records, total N=331, duration 12 months) met the inclusion criteria. Participants were people with schizophrenia spectrum or an affective disorder. Social media was used as part of Web-based psychoeducation, or as online peer support (listserv and bulletin board). Outcome measures included perceived stress, social support, and disease-related distress. At 3 months, participants with schizophrenia in the intervention group reported lower perceived stress levels ( P=.04) and showed a trend for a higher perceived level of social support ( P=.06). However, those who reported more positive experiences with the peer support group also reported higher levels of psychological distress ( P=.01).

          Conclusions

          Despite using comprehensive searches from 10 databases, we found only two studies, whereas numerous reports have been published citing the benefits of social media in mental health. Findings suggest the effects of social media interventions are largely unknown. More research is needed to understand the effects of social media, for users with and without mental illness, in order to determine the impact on mental well-being ofsocial media use as well as its risks.

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          Most cited references37

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          The MOS social support survey.

          This paper describes the development and evaluation of a brief, multidimensional, self-administered, social support survey that was developed for patients in the Medical Outcomes Study (MOS), a two-year study of patients with chronic conditions. This survey was designed to be comprehensive in terms of recent thinking about the various dimensions of social support. In addition, it was designed to be distinct from other related measures. We present a summary of the major conceptual issues considered when choosing items for the social support battery, describe the items, and present findings based on data from 2987 patients (ages 18 and older). Multitrait scaling analyses supported the dimensionality of four functional support scales (emotional/informational, tangible, affectionate, and positive social interaction) and the construction of an overall functional social support index. These support measures are distinct from structural measures of social support and from related health measures. They are reliable (all Alphas greater than 0.91), and are fairly stable over time. Selected construct validity hypotheses were supported.
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            The interpretation of random-effects meta-analysis in decision models.

            This article shows that the interpretation of the random-effects models used in meta-analysis to summarize heterogeneous treatment effects can have a marked effect on the results from decision models. Sources of variation in meta-analysis include the following: random variation in outcome definition (amounting to a form of measurement error), variation between the patient groups in different trials, variation between protocols, and variation in the way a given protocol is implemented. Each of these alternatives leads to a different model for how the heterogeneity in the effect sizes previously observed might relate to the effect size(s) in a future implementation. Furthermore, these alternative models require different computations and, when the net benefits are nonlinear in the efficacy parameters, result in different expected net benefits. The authors' analysis suggests that the mean treatment effect from a random-effects meta-analysis will only seldom be an appropriate representation of the efficacy expected in a future implementation. Instead, modelers should consider either the predictive distribution of a future treatment effect, or they should assume that the future implementation will result in a distribution of treatment effects. A worked example, in a probabilistic, Bayesian posterior framework, is used to illustrate the alternative computations and to show how parameter uncertainty can be combined with variation between individuals and heterogeneity in meta-analysis.
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              Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide.

              Without a complete published description of interventions, clinicians and patients cannot reliably implement interventions that are shown to be useful, and other researchers cannot replicate or build on research findings. The quality of description of interventions in publications, however, is remarkably poor. To improve the completeness of reporting, and ultimately the replicability, of interventions, an international group of experts and stakeholders developed the Template for Intervention Description and Replication (TIDieR) checklist and guide. The process involved a literature review for relevant checklists and research, a Delphi survey of an international panel of experts to guide item selection, and a face to face panel meeting. The resultant 12 item TIDieR checklist (brief name, why, what (materials), what (procedure), who provided, how, where, when and how much, tailoring, modifications, how well (planned), how well (actual)) is an extension of the CONSORT 2010 statement (item 5) and the SPIRIT 2013 statement (item 11). While the emphasis of the checklist is on trials, the guidance is intended to apply across all evaluative study designs. This paper presents the TIDieR checklist and guide, with an explanation and elaboration for each item, and examples of good reporting. The TIDieR checklist and guide should improve the reporting of interventions and make it easier for authors to structure accounts of their interventions, reviewers and editors to assess the descriptions, and readers to use the information.
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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 Inc. (Toronto, Canada )
                1439-4456
                1438-8871
                April 2016
                22 April 2016
                : 18
                : 4
                : e92
                Affiliations
                [1] 1Department of Nursing Science University of Turku TurkuFinland
                [2] 2Turku University Ηospital TurkuFinland
                [3] 3Faculty of Health and Well-being Turku University of Applied Sciences TurkuFinland
                [4] 4Institute of Mental Health Division of Psychiatry University of Nottingham NottinghamUnited Kingdom
                Author notes
                Corresponding Author: Maritta Välimäki mava@ 123456utu.fi
                Author information
                http://orcid.org/0000-0003-3124-9290
                http://orcid.org/0000-0001-5577-1193
                http://orcid.org/0000-0002-3403-5418
                http://orcid.org/0000-0003-1628-4020
                Article
                v18i4e92
                10.2196/jmir.5385
                4859871
                27105939
                ee7f5dad-4493-4824-9997-a24c0887eee5
                ©Maritta Välimäki, Christina Athanasopoulou, Mari Lahti, Clive E Adams. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.04.2016.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), 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
                : 1 December 2015
                : 30 December 2015
                : 1 February 2016
                Categories
                Original Paper
                Original Paper

                Medicine
                social media,effectiveness,technology,internet,web 2.0,schizophrenia,mental health
                Medicine
                social media, effectiveness, technology, internet, web 2.0, schizophrenia, mental health

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