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      Smartphone-Supported versus Full Behavioural Activation for Depression: A Randomised Controlled Trial

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          Abstract

          Background

          There is need for more cost and time effective treatments for depression. This is the first randomised controlled trial in which a blended treatment - including four face-to-face sessions and a smartphone application - was compared against a full behavioural treatment. Hence, the aim of the current paper was to examine whether a blended smartphone treatment was non-inferior to a full behavioural activation treatment for depression.

          Methods

          This was a randomised controlled non-inferiority trial (NCT01819025) comparing a blended treatment ( n=46) against a full ten-session treatment ( n=47) for people suffering from major depression. Primary outcome measure was the BDI-II, that was administered at pre- and post-treatment, as well as six months after the treatment.

          Results

          Results showed significant improvements in both groups across time on the primary outcome measure (within-group Cohen’s d=1.35; CI [−0.82, 3.52] to d=1.47; CI [−0.41, 3.35]; between group d=−0.13 CI [−2.37, 2.09] and d=−0.10 CI [−2.53, 2.33]). At the same time, the blended treatment reduced the therapist time with an average of 47%.

          Conclusions

          We could not establish whether the blended treatment was non-inferior to a full BA treatment. Nevertheless, this study points to that the blended treatment approach could possibly treat nearly twice as many patients suffering from depression by using a smartphone applica¬tion as add-on. More studies are needed before we can suggest that the blended treatment method is a promising cost-effective alternative to regular face-to-face treatment for depression.

          Trial Registration

          Cognitive Behavioral Therapy Treatment of Depression With Smartphone Support NCT01819025

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          Most cited references16

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          Advantages and limitations of Internet-based interventions for common mental disorders.

          Several Internet interventions have been developed and tested for common mental disorders, and the evidence to date shows that these treatments often result in similar outcomes as in face-to-face psychotherapy and that they are cost-effective. In this paper, we first review the pros and cons of how participants in Internet treatment trials have been recruited. We then comment on the assessment procedures often involved in Internet interventions and conclude that, while online questionnaires yield robust results, diagnoses cannot be determined without any contact with the patient. We then review the role of the therapist and conclude that, although treatments including guidance seem to lead to better outcomes than unguided treatments, this guidance can be mainly practical and supportive rather than explicitly therapeutic in orientation. Then we briefly describe the advantages and disadvantages of treatments for mood and anxiety disorders and comment on ways to handle comorbidity often associated with these disorders. Finally we discuss challenges when disseminating Internet interventions. In conclusion, there is now a large body of evidence suggesting that Internet interventions work. Several research questions remain open, including how Internet interventions can be blended with traditional forms of care. Copyright © 2014 World Psychiatric Association.
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            Move over ANOVA: progress in analyzing repeated-measures data and its reflection in papers published in the Archives of General Psychiatry.

            The analysis of repeated-measures data presents challenges to investigators and is a topic for ongoing discussion in the Archives of General Psychiatry. Traditional methods of statistical analysis (end-point analysis and univariate and multivariate repeated-measures analysis of variance [rANOVA and rMANOVA, respectively]) have known disadvantages. More sophisticated mixed-effects models provide flexibility, and recently developed software makes them available to researchers. To review methods for repeated-measures analysis and discuss advantages and potential misuses of mixed-effects models. Also, to assess the extent of the shift from traditional to mixed-effects approaches in published reports in the Archives of General Psychiatry. The Archives of General Psychiatry from 1989 through 2001, and the Department of Veterans Affairs Cooperative Study 425. Studies with a repeated-measures design, at least 2 groups, and a continuous response variable. The first author ranked the studies according to the most advanced statistical method used in the following order: mixed-effects model, rMANOVA, rANOVA, and end-point analysis. The use of mixed-effects models has substantially increased during the last 10 years. In 2001, 30% of clinical trials reported in the Archives of General Psychiatry used mixed-effects analysis. Repeated-measures ANOVAs continue to be used widely for the analysis of repeated-measures data, despite risks to interpretation. Mixed-effects models use all available data, can properly account for correlation between repeated measurements on the same subject, have greater flexibility to model time effects, and can handle missing data more appropriately. Their flexibility makes them the preferred choice for the analysis of repeated-measures data.
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              Credibility of analogue therapy rationales

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                26 May 2015
                2015
                : 10
                : 5
                : e0126559
                Affiliations
                [1 ]Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden
                [2 ]Department of Psychology, Stockholm University, Stockholm, Sweden
                [3 ]Wemind Psykiatri Stockholm, Stockholm, Sweden
                [4 ]Department of Clinical Neuroscience, Center for Psychiatry Research, Karolinska Institute, Stockholm, Sweden
                University of Groningen, Faculty of Social and Behavioral Sciences, NETHERLANDS
                Author notes

                Competing Interests: KHL develops a related version of the smartphone application for the open market. OM is an employee of Wemind Psykiatri Stockholm. There are no further patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: KHL GA. Performed the experiments: KHL NT HC AW. Analyzed the data: KHL GA. Contributed reagents/materials/analysis tools: KHL GA. Wrote the paper: KHL GA PC. Provided continuous supervision during the entire study: GA JB OM.

                Article
                PONE-D-14-40400
                10.1371/journal.pone.0126559
                4444307
                26010890
                7e92a093-325e-4f84-a890-f3888de57219
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 9 September 2014
                : 2 April 2015
                Page count
                Figures: 4, Tables: 3, Pages: 16
                Funding
                This paper was supported by the Swedish Research Council: 2011-2476 ( http://www.vr.se/), as well as by the European Community’s Seventh Framework Programme (FP7): 603098 ( http://www.e-compared.eu/). Wemind Psykiatri Stockholm provided support in the form of salaries for author OM, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of the authors are articulated in the author contributions’ section.
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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