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      Effectiveness of Using Mental Health Mobile Apps as Digital Antidepressants for Reducing Anxiety and Depression: Protocol for a Multiple Baseline Across-Individuals Design

      , MClinPsych 1 , , , PhD 1 , , PhD 1
      (Reviewer), (Reviewer)
      JMIR Research Protocols
      JMIR Publications
      mHealth, eHealth, mobile apps, mobile phone, anxiety, depression, single-case study

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          The use of mental health mobile apps to treat anxiety and depression is widespread and growing. Several reviews have found that most of these apps do not have published evidence for their effectiveness, and existing research has primarily been undertaken by individuals and institutions that have an association with the app being tested. Another reason for the lack of research is that the execution of the traditional randomized controlled trial is time prohibitive in this profit-driven industry. Consequently, there have been calls for different methodologies to be considered. One such methodology is the single-case design, of which, to the best of our knowledge, no peer-reviewed published example with mental health apps for anxiety and/or depression could be located.


          The aim of this study is to examine the effectiveness of 5 apps ( Destressify, MoodMission, Smiling Mind, MindShift, and SuperBetter) in reducing symptoms of anxiety and/or depression. These apps were selected because they are publicly available, free to download, and have published evidence of efficacy.


          A multiple baseline across-individuals design will be employed. A total of 50 participants will be recruited (10 for each app) who will provide baseline data for 20 days. The sequential introduction of an intervention phase will commence once baseline readings have indicated stability in the measures of participants’ mental health and will proceed for 10 weeks. Postintervention measurements will continue for a further 20 days. Participants will be required to provide daily subjective units of distress (SUDS) ratings via SMS text messages and will complete other measures at 5 different time points, including at 6-month follow-up. SUDS data will be examined via a time series analysis across the experimental phases. Individual analyses of outcome measures will be conducted to detect clinically significant changes in symptoms using the statistical approach proposed by Jacobson and Truax. Participants will rate their app on several domains at the end of the intervention.


          Participant recruitment commenced in January 2020. The postintervention phase will be completed by June 2020. Data analysis will commence after this. A write-up for publication is expected to be completed after the follow-up phase is finalized in January 2021.


          If the apps prove to be effective as hypothesized, this will provide collateral evidence of their efficacy. It could also provide the benefits of (1) improved access to mental health services for people in rural areas, lower socioeconomic groups, and children and adolescents and (2) improved capacity to enhance face-to-face therapy through digital homework tasks that can be shared instantly with a therapist. It is also anticipated that this methodology could be used for other mental health apps to bolster the independent evidence base for this mode of treatment.

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          Most cited references45

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          The Use of Single-Subject Research to Identify Evidence-Based Practice in Special Education

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            The efficacy of smartphone-based mental health interventions for depressive symptoms: a meta-analysis of randomized controlled trials.

            The rapid advances and adoption of smartphone technology presents a novel opportunity for delivering mental health interventions on a population scale. Despite multi-sector investment along with wide-scale advertising and availability to the general population, the evidence supporting the use of smartphone apps in the treatment of depression has not been empirically evaluated. Thus, we conducted the first meta-analysis of smartphone apps for depressive symptoms. An electronic database search in May 2017 identified 18 eligible randomized controlled trials of 22 smartphone apps, with outcome data from 3,414 participants. Depressive symptoms were reduced significantly more from smartphone apps than control conditions (g=0.38, 95% CI: 0.24-0.52, p<0.001), with no evidence of publication bias. Smartphone interventions had a moderate positive effect in comparison to inactive controls (g=0.56, 95% CI: 0.38-0.74), but only a small effect in comparison to active control conditions (g=0.22, 95% CI: 0.10-0.33). Effects from smartphone-only interventions were greater than from interventions which incorporated other human/computerized aspects along the smartphone component, although the difference was not statistically significant. The studies of cognitive training apps had a significantly smaller effect size on depression outcomes (p=0.004) than those of apps focusing on mental health. The use of mood monitoring softwares, or interventions based on cognitive behavioral therapy, or apps incorporating aspects of mindfulness training, did not affect significantly study effect sizes. Overall, these results indicate that smartphone devices are a promising self-management tool for depression. Future research should aim to distil which aspects of these technologies produce beneficial effects, and for which populations.
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              The Depression Anxiety Stress Scales-21 (DASS-21): further examination of dimensions, scale reliability, and correlates.

              We conducted two studies to examine the dimensions, internal consistency reliability estimates, and potential correlates of the Depression Anxiety Stress Scales-21 (DASS-21; Lovibond & Lovibond, 1995). Participants in Study 1 included 887 undergraduate students (363 men and 524 women, aged 18 to 35 years; mean [M] age = 19.46, standard deviation [SD] = 2.17) recruited from two public universities to assess the specificity of the individual DASS-21 items and to evaluate estimates of internal consistency reliability. Participants in a follow-up study (Study 2) included 410 students (168 men and 242 women, aged 18 to 47 years; M age = 19.65, SD = 2.88) recruited from the same universities to further assess factorial validity and to evaluate potential correlates of the original DASS-21 total and scale scores. Item bifactor and confirmatory factor analyses revealed that a general factor accounted for the greatest proportion of common variance in the DASS-21 item scores (Study 1). In Study 2, the fit statistics showed good fit for the bifactor model. In addition, the DASS-21 total scale score correlated more highly with scores on a measure of mixed depression and anxiety than with scores on the proposed specific scales of depression or anxiety. Coefficient omega estimates for the DASS-21 scale scores were good. Further investigations of the bifactor structure and psychometric properties of the DASS-21, specifically its incremental and discriminant validity, using known clinical groups are needed. © 2012 Wiley Periodicals, Inc.

                Author and article information

                JMIR Res Protoc
                JMIR Res Protoc
                JMIR Research Protocols
                JMIR Publications (Toronto, Canada )
                July 2020
                5 July 2020
                : 9
                : 7
                : e17159
                [1 ] School of Psychology Faculty of Medicine and Health University of New England Armidale Australia
                Author notes
                Corresponding Author: Jamie M Marshall jmarsh21@ 123456une.edu.au
                Author information
                ©Jamie M Marshall, Debra A Dunstan, Warren Bartik. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 05.07.2020.

                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 JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.

                : 22 November 2019
                : 18 March 2020
                : 3 April 2020
                : 20 April 2020

                mhealth,ehealth,mobile apps,mobile phone,anxiety,depression,single-case study


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