Coaching to Support Mental Health Apps: Exploratory Narrative Review

Meyer, Ashley; Wisniewski, Hannah; Torous, John

doi:10.2196/28301

Cited by 23 publications

(10 citation statements)

References 53 publications

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“…Along these lines, Mohr et al [ 35 ] set forth a range of testable hypotheses pertaining to client motivation, alliance, and communications media, each of which should be more explicitly defined, tested, and manualized. Similarly, there is a need to specify the type of human support provided, as it can vary and may include postsession feedback, regular calls, feedback on assignments, regular supportive text messages, asynchronous web-based messaging, personalized feedback, tailored emails, or even face-to-face meetings [ 75 ].…”

Section: Discussionmentioning

confidence: 99%

Providing Human Support for the Use of Digital Mental Health Interventions: Systematic Meta-review

Werntz¹,

Amado²,

Jasman³

et al. 2023

J Med Internet Res

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Background Digital mental health interventions (DMHIs) have been increasingly deployed to bridge gaps in mental health care, particularly given their promising efficacy. Nevertheless, attrition among DMHI users remains high. In response, human support has been studied as a means of improving retention to and outcomes of DMHIs. Although a growing number of studies and meta-analyses have investigated the effects of human support for DMHIs on mental health outcomes, systematic empirical evidence of its effectiveness across mental health domains remains scant. Objective We aimed to summarize the results of meta-analyses of human support versus no support for DMHI use across various outcome domains, participant samples, and support providers. Methods We conducted a systematic meta-review of meta-analyses, comparing the effects of human support with those of no support for DMHI use, with the goal of qualitatively summarizing data across various outcome domains, participant samples, and support providers. We used MEDLINE, PubMed, and PsycINFO electronic databases. Articles were included if the study had a quantitative meta-analysis study design; the intervention targeted mental health symptoms and was delivered via a technology platform (excluding person-delivered interventions mediated through telehealth, text messages, or social media); the outcome variables included mental health symptoms such as anxiety, depression, stress, posttraumatic stress disorder symptoms, or a number of these symptoms together; and the study included quantitative comparisons of outcomes in which human support versus those when no or minimal human support was provided. Results The results of 31 meta-analyses (505 unique primary studies) were analyzed. The meta-analyses reported 45 effect sizes; almost half (n=22, 48%) of them showed that human-supported DMHIs were significantly more effective than unsupported DMHIs. A total of 9% (4/45) of effect sizes showed that unsupported DMHIs were significantly more effective. No clear patterns of results emerged regarding the efficacy of human support for the outcomes assessed (including anxiety, depression, posttraumatic stress disorder, stress, and multiple outcomes). Human-supported DMHIs may be more effective than unsupported DMHIs for individuals with elevated mental health symptoms. There were no clear results regarding the type of training for those providing support. Conclusions Our findings highlight the potential of human support in improving the effects of DMHIs. Specifically, evidence emerged for stronger effects of human support for individuals with greater symptom severity. There was considerable heterogeneity across meta-analyses in the level of detail regarding the nature of the interventions, population served, and support delivered, making it difficult to draw strong conclusions regarding the circumstances under which human support is most effective. Future research should emphasize reporting detailed descriptions of sample and intervention characteristics and describe the mechanism through which they believe the coach will be most useful for the DMHI.

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Section: Discussionmentioning

confidence: 99%

Providing Human Support for the Use of Digital Mental Health Interventions: Systematic Meta-review

Werntz¹,

Amado²,

Jasman³

et al. 2023

J Med Internet Res

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show abstract

“…It would be beneficial to develop brief interventions intended to improve the eHealth literacy skills necessary for engaging in mHealth apps, to provide patients with the tools to engage with and apply the health information provided on such platforms. In addition, there is evidence that support from a coach or health navigator may help patients engage more effectively with mHealth interventions (38). These support efforts could emphasize ensuring patients are equipped with eHealth literacy skills, and thereby be another useful strategy for improving patient engagement with mHealth apps.…”

Section: Discussionmentioning

confidence: 99%

The Relationship Between Depressive Symptoms, eHealth Literacy, and Asthma Outcomes in the Context of a Mobile Health Intervention

et al. 2023

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Objective: The ASTHMAXcel PRO mobile app provides asthma education and collects asthma outcome data. The objective of this study was to evaluate the associations between health/electronic health literacy (eHealth literacy) and depressive symptoms with app usage and clinical outcomes. Methods: Adults with persistent asthma were recruited to use the app. Participants completed the Patient Health Questionnaire-9 to assess for depressive symptoms, Asthma Control Test, Mini Asthma Quality of Life (QOL) Questionnaire, and the Newest Vital Sign tool to measure health literacy. Data on a subset of participants were available on eHealth literacy (n = 24) and average number of app logins across 2 months (n = 40). Results: The total study sample included 96 participants (46% non-Hispanic Black, 44.4% Hispanic). The average participant age was 44.0 (standard deviation = 14.9) years, with 74% identifying as female. Increased depressive symptoms were associated with worse asthma control (β = −0.46, p < .001) and asthma QOL (β = −0.38, p < .001), but not eHealth literacy. Higher eHealth literacy was associated with worse asthma QOL (β = −0.48, p = .02) and more app logins (β = 0.59, p = .04). Newest Vital Sign scores were not associated with any of the other measures. Conclusions: Depressive symptoms were associated with worse asthma outcomes. eHealth literacy was associated with increased patient engagement with the app and worse asthma QOL, which may reflect patients with worse QOL seeking out health information on the Internet (although directionality could not be assessed). Digital health literacy may be key to increasing patient engagement with mobile health interventions. Trial Registration: National Clinical Trial No. 03847142, https://clinicaltrials.gov/ct2/show/NCT03847142.

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“…In fact, how to efficiently integrate coaching and messaging support to keep users engaged is an intense field of research 64,65 . We, as users of mobile technologies, get annoyed with frequent messages and suggestions from our smartphone.…”

Section: Opportunities and Recommendationsmentioning

confidence: 99%

“…In fact, how to efficiently integrate coaching and messaging support to keep users engaged is an intense field of research. 64,65 We, as users of mobile technologies, get annoyed with frequent messages and suggestions from our smartphone. For this reason, the topic of "receptivity" or how to understand when is the right time to send a notification to have full attention from the user is key to the success of DTx, and most of the current efforts in this area are concentrated around optimizing the features of the interventions to increase its chance to be "receptioned.…”

Section: Research Needed Beyond the Topics Of Engagement And Adherencementioning

confidence: 99%

Digital Therapeutics as a New Therapeutic Modality: A Review from the Perspective of Clinical Pharmacology

Ribba,

Peck,

Hutchinson

et al. 2023

Clin Pharma and Therapeutics

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The promise of transforming digital technologies into treatments is what drives the development of digital therapeutics (DTx), generally known as software applications embedded within accessible technologies—such as smartphones—to treat, manage, or prevent a pathological condition. Whereas DTx solutions that successfully demonstrate effectiveness and safety could drastically improve the life of patients in multiple therapeutic areas, there is a general consensus that generating therapeutic evidence for DTx presents challenges and open questions. We believe there are three main areas where the application of clinical pharmacology principles from the drug development field could benefit DTx development: the characterization of the mechanism of action, the optimization of the intervention, and, finally, its dosing. We reviewed DTx studies to explore how the field is approaching these topics and to better characterize the challenges associated with them. This leads us to emphasize the role that the application of clinical pharmacology principles could play in the development of DTx and to advocate for a development approach that merges such principles from development of traditional therapeutics with important considerations from the highly attractive and fast‐paced world of digital solutions.

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Coaching to Support Mental Health Apps: Exploratory Narrative Review

Cited by 23 publications

References 53 publications

Providing Human Support for the Use of Digital Mental Health Interventions: Systematic Meta-review

Providing Human Support for the Use of Digital Mental Health Interventions: Systematic Meta-review

The Relationship Between Depressive Symptoms, eHealth Literacy, and Asthma Outcomes in the Context of a Mobile Health Intervention

Digital Therapeutics as a New Therapeutic Modality: A Review from the Perspective of Clinical Pharmacology

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