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      Digital Mental Health Interventions for Depression, Anxiety, and Enhancement of Psychological Well-Being Among College Students: Systematic Review

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          Abstract

          Background

          College students are increasingly reporting common mental health problems, such as depression and anxiety, and they frequently encounter barriers to seeking traditional mental health treatments. Digital mental health interventions, such as those delivered via the Web and apps, offer the potential to improve access to mental health treatment.

          Objective

          This study aimed to review the literature on digital mental health interventions focused on depression, anxiety, and enhancement of psychological well-being among samples of college students to identify the effectiveness, usability, acceptability, uptake, and adoption of such programs.

          Methods

          We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (registration number CRD42018092800), and the search strategy was conducted by a medical research librarian in the following databases: MEDLINE (Ovid), EMBASE (Elsevier), PsycINFO (EbscoHost), the Cochrane Library (Wiley), and Web of Science (Thomson Reuters) from the date of inception to April 2019. Data were synthesized using a systematic narrative synthesis framework, and formal quality assessments were conducted to address the risk of bias.

          Results

          A total of 89 studies met the inclusion criteria. The majority of interventions (71/89, 80%) were delivered via a website, and the most common intervention was internet-based cognitive behavioral therapy (28, 31%). Many programs (33, 37%) featured human support in the form of coaching. The majority of programs were either effective (42, 47%) or partially effective (30, 34%) in producing beneficial changes in the main psychological outcome variables. Approximately half of the studies (45, 51%) did not present any usability or acceptability outcomes, and few studies (4, 4%) examined a broad implementation of digital mental health interventions on college campuses. Quality assessments revealed a moderate-to-severe risk of bias in many of the studies.

          Conclusions

          Results suggest that digital mental health interventions can be effective for improving depression, anxiety, and psychological well-being among college students, but more rigorous studies are needed to ascertain the effective elements of these interventions. Continued research on improving the user experience of, and thus user engagement with, these programs appears vital for the sustainable implementation of digital mental health interventions on college campuses.

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          Most cited references 121

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          The client satisfaction questionnaire. Psychometric properties and correlations with service utilization and psychotherapy outcome.

          An 18-item version of the Client Satisfaction Questionnaire (CSQ-18) was included in an experimental study of the effects of pretherapy orientation on psychotherapy outcome. The psychometric properties of the CSQ-18 in this study were compared with earlier findings. In addition, the correlations of the CSQ-18 with service utilization and psychotherapy outcome measures were examined. Results indicated that the CSQ-18 had high internal consistency (coefficient alpha = .91) and was substantially correlated with remainer-terminator status (rs = .61) and with number of therapy sessions attended in one month (r = .54). The CSQ-18 was also correlated with change in client-reported symptoms (r = -.35), indicating that greater satisfaction was associated with greater symptom reduction. Results also demonstrated that a subset of items from the scale (the CSQ-8) performed as well as the CSQ-18 and often better. The excellent performance of the CSQ-8, coupled with its brevity, suggests that it may be especially useful as a brief global measure of client satisfaction.
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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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              Efficacy of Self-guided Internet-Based Cognitive Behavioral Therapy in the Treatment of Depressive Symptoms: A Meta-analysis of Individual Participant Data.

              Self-guided internet-based cognitive behavioral therapy (iCBT) has the potential to increase access and availability of evidence-based therapy and reduce the cost of depression treatment.
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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 (Toronto, Canada )
                1439-4456
                1438-8871
                July 2019
                22 July 2019
                : 21
                : 7
                Affiliations
                [1 ] Center for Behavioral Intervention Technologies Northwestern University Chicago, IL United States
                [2 ] Department of Psychiatry and Behavioral Sciences Rush University Medical Center Chicago, IL United States
                [3 ] Galter Health Sciences Library and Learning Center Northwestern University Chicago, IL United States
                Author notes
                Corresponding Author: Emily G Lattie emily.lattie@ 123456northwestern.edu
                Article
                v21i7e12869
                10.2196/12869
                6681642
                31333198
                ©Emily G Lattie, Elizabeth C Adkins, Nathan Winquist, Colleen Stiles-Shields, Q Eileen Wafford, Andrea K Graham. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.07.2019.

                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 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.

                Categories
                Original Paper
                Original Paper

                Medicine

                ehealth, mhealth, mental health, students, universities

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