Human support for digital mental health interventions: a promising approach

Werntz, A., Amado, S., Jasman, M., Ervin, A, & Rhodes, J. (2023). Providing human support for the use of digital mental health interventions: Systematic meta-review. Journal of Medical Internet Research, 25.

Summarized by Megyn Jasman

Notes of Interest:

  • Digital mental health interventions (DMHIs) are popular because research has shown that many are effective.
  • However, many individuals who use DMHIs tend to stop using them and overall engagement is low, which makes them less effective overall.
      • One way of increasing engagement with DMHIs is by having another individual support their use, such as assisting with troubleshooting (i.e., for technical difficulties), providing encouragement, and answering questions.
    • Supportive accountability (first introduced by Mohr et al., 2011) is a technique in which supportive individuals can encourage an individual to meet their goals by nudging and reminding them to complete tasks.
  • This study systematically reviewed 31 meta-analyses (an analysis that combines the quantitative results of several studies to get an overall effect) to examine the mental health outcomes for individuals who receive human support for using a DMHI, versus those who did not have the added support.
  • Three main takeaways:
    • Human support has the potential to improve the effects of digital mental health interventions as a way of increasing access to evidence-based mental health tools. This is important because many DMHIs is free to use!
    • Results suggest that DMHIs do not need to be supported by individuals with extensive mental health training. This means that a loved one or trusted mentor can support their use.
    • Human support of DMHIs leads to stronger effects (compared to no support) among interventions targeted at individuals with elevated (or specific) mental health symptoms.
  • Overall, there may be opportunities for mentors and other paraprofessionals to support digital mental health intervention use to promote positive outcomes.

Introduction (Reprinted from the Abstract)

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.

Implications (Reprinted from the Discussion)

A systematic meta-review of meta-analyses was conducted that compared the effects of human support or DMHIs with no support on mental health symptoms. The effects of human support on treatment outcomes, participant samples, and types of support providers were examined. Results from 31 meta-analyses representing 505 unique primary studies have been reported. Almost half (22/45, 48%) of the effect sizes revealed that supported interventions had significantly stronger effects compared with unsupported interventions. Only 9% (4/45) of effect sizes described the significantly stronger effects of unsupported interventions. No clear pattern of results emerged in the outcome domain. Evidence for human-supported DMHIs was split for depression and PTSD symptoms; for anxiety symptoms, evidence suggested that there were largely no significant differences between human-supported and unsupported DMHIs. However, when multiple outcomes were assessed, human support for DMHIs appeared to be more effective than no support. Given the variable and number of studies across several outcomes and discrepant results, it would be premature to draw firm conclusions regarding the relative importance of human support for DMHIs across different outcome domains. Similarly, no clear pattern of results emerged for sample characteristics, with effect sizes largely split across those that did vs did not show the efficacy of added human support. The same was true regarding the quality of the meta-analysis.

Moreover, we did not find a clear pattern of results when comparing highly trained support providers (eg, clinicians) with paraprofessional-level support, suggesting that DMHIs do not need to be supported by individuals with extensive mental health training. This is promising for models of increasing access to mental health services and has implications for task-shifting mental health care as well as for therapeutic mentoring [74]. Unfortunately, 19 of the 45 effect sizes were from meta-analyses that did not define the training or background of the individuals providing support, greatly limiting our ability to draw strong conclusions about the role of background and training of support providers on the efficacy of human support. Although no clear patterns emerged in the outcome domain, sample characteristics, or provider background, we highlight a few promising trends that can guide future research and practice. Among DMHIs that target individuals with elevated mental health symptoms and specific mental health symptoms (depression, anxiety, and PTSD), human support appears to lead to stronger effects when compared with unsupported DMHIs. Future studies should explore this association

This article was published in JMIR, which is an open-access (free) journal. To access this article, click here.