Common themes and emerging trends for the use of technology to support mental health and psychosocial well-being in limited resource settings: A review of the literature

“…Cognitive Behavioral Therapy (CBT) is a form of psychotherapy which seeks to employ its user to challenge negative thought patterns in order to reduce negative behavioral patterns and address or treat specific psychiatric symptoms or disorders such as depression and/or generalized anxiety disorder (29). In reflection of its use without necessity for an in-person professional counselor, the use of cognitive behavioral therapy (CBT) has been explored via text-messaging as an intervention tool, with interest in elevating an individual's mood, and were found to be effective (30)(31)(32)(33)(34)(35)(36).…”

Section: Introductionmentioning

confidence: 99%

Text4Support Mobile-Based Programming for Individuals Accessing Addictions and Mental Health Services—Retroactive Program Analysis at Baseline, 12 Weeks, and 6 Months

et al. 2021

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Objective: Where traditional approaches fall short, widely accessible and accepted, yet under leveraged, digital technologies such as text messaging present novel opportunities to solve a range of health care solutions. The following provides a preliminary analysis of the Text4Support program, a text-messaging intervention using the principles of cognitive behavioral therapy, which seeks to support the health and well-being of individuals seeking support for addiction or mental health concerns. The goal of this study was to assess whether the Text4Support program improved the perceived overall mental well-being of participants.Methods: The evaluation analyzes survey responses of individuals who were enrolled in the Text4Support program beginning in July 2019, who had completed the 6-months program by May 2020. Participants were asked to provide responses to three surveys during their time in the program—at baseline, 12-weeks and 6-months, which included questions documenting demographic information, general satisfaction with the program, and a participants' level of “global distress” through use of the Clinical Outcomes Routine Evaluation System (CORE-10)—a validated brief 10-item assessment and outcome measurement tool used to assess conditions including anxiety, depression, physical problems, and risk to self.Results and Conclusions: This data set did not include a large enough sample of participants to reach statistical significance. Nevertheless, the study provides some preliminary analysis, and identifies opportunities for the future analysis and research.

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“…Technological advances since this time include improvements in interface design and user experience features, such as chatbots, gamification, and virtual reality [15,16]. However, these relatively more high-tech solutions have yet to be fully integrated into the digital mental health landscape [16]. Thus, we believe that the general knowledge and discussion derived from this analysis, which inspected usage behaviors along common metrics such as logins, module usage, and mood monitoring, still bears relevance today.…”

Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 99%

e-Mental Health Program Usage Patterns in Randomized Controlled Trials and in the General Public to Inform External Validity Considerations: Sample Groupings Using Cluster Analyses

Sanatkar¹,

Baldwin²,

Huckvale³

et al. 2021

J Med Internet Res

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Background Randomized controlled trials (RCTs) with vigorous study designs are vital for determining the efficacy of treatments. Despite the high internal validity attributed to RCTs, external validity concerns limit the generalizability of results to the general population. Bias can be introduced, for example, when study participants who self-select into a trial are more motivated to comply with study conditions than are other individuals. These external validity considerations extend to e-mental health (eMH) research, especially when eMH tools are designed for public access and provide minimal or no supervision. Objective Clustering techniques were employed to identify engagement profiles of RCT participants and community users of a self-guided eMH program. This exploratory approach inspected actual, not theorized, RCT participant and community user engagement patterns. Both samples had access to the eMH program over the same time period and received identical usage recommendations on the eMH program website. The aim of this study is to help gauge expectations of similarities and differences in usage behaviors of an eMH tool across evaluation and naturalistic contexts. Methods Australian adults signed up to myCompass, a self-guided online treatment program created to reduce mild to moderate symptoms of negative emotions. They did so either by being part of an RCT onboarding (160/231, 69.6% female) or by accessing the program freely on the internet (5563/8391, 66.30% female) between October 2011 and October 2012. During registration, RCT participants and community users provided basic demographic information. Usage metrics (number of logins, trackings, and learning activities) were recorded by the system. Results Samples at sign-up differed significantly in age (P=.003), with community users being on average 3 years older (mean 41.78, SD 13.64) than RCT participants (mean 38.79, SD 10.73). Furthermore, frequency of program use was higher for RCT participants on all usage metrics compared to community users through the first 49 days after registration (all P values <.001). Two-step cluster analyses revealed 3 user groups in the RCT sample (Nonstarters, 10-Timers, and 30+-Timers) and 2 user groups in the community samples (2-Timers and 20-Timers). Groups seemed comparable in patterns of use but differed in magnitude, with RCT participant usage groups showing more frequent engagement than community usage groups. Only the high-usage group among RCT participants approached myCompass usage recommendations. Conclusions Findings suggested that external validity concerns of RCT designs may arise with regards to the predicted magnitude of eMH program use rather than overall usage styles. Following up RCT nonstarters may help provide unique insights into why individuals choose not to engage with an eMH program despite generally being willing to participate in an eMH evaluation study. Overestimating frequency of engagement with eMH tools may have theoretical implications and potentially impact economic considerations for plans to disseminate these tools to the general public.

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Common themes and emerging trends for the use of technology to support mental health and psychosocial well-being in limited resource settings: A review of the literature

Cited by 46 publications

References 78 publications

COVID‐19 and Autism Research: Perspectives from Around the Globe

COVID‐19 and Autism Research: Perspectives from Around the Globe

Text4Support Mobile-Based Programming for Individuals Accessing Addictions and Mental Health Services—Retroactive Program Analysis at Baseline, 12 Weeks, and 6 Months

e-Mental Health Program Usage Patterns in Randomized Controlled Trials and in the General Public to Inform External Validity Considerations: Sample Groupings Using Cluster Analyses

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