Abstract
Background:
Recent years have highlighted an increasing need to promote mental well-being in the general population. This has led to a rapidly growing market for fully automated digital mental well-being tools. Although many individuals have started using these tools in their daily lives, evidence on the overall effectiveness of digital mental well-being tools is currently lacking.
Objective:
This study aims to review the evidence on the effectiveness of fully automated digital interventions in promoting mental well-being in the general population.
Methods:
Following the preregistration of the systematic review protocol on PROSPERO, searches were carried out in MEDLINE, Web of Science, Cochrane, PsycINFO, PsycEXTRA, Scopus, and ACM Digital (initial searches in February 2022; updated in October 2022). Studies were included if they contained a general population sample and a fully automated digital intervention that exclusively used psychological mental well-being promotion activities. Two reviewers, blinded to each other’s decisions, conducted data selection, extraction, and quality assessment of the included studies. Narrative synthesis and a random-effects model of per-protocol data were adopted.
Results:
We included 19 studies that involved 7243 participants. These studies included 24 fully automated digital mental well-being interventions, of which 15 (63%) were included in the meta-analysis. Compared with no intervention, there was a significant small effect of fully automated digital mental well-being interventions on mental well-being in the general population (standardized mean difference 0.19, 95% CI 0.04-0.33; P=.02). Specifically, mindfulness-, acceptance-, commitment-, and compassion-based interventions significantly promoted mental well-being in the general population (P=.006); insufficient evidence was available for positive psychology and cognitive behavioral therapy–based interventions; and contraindications were found for integrative approaches. Overall, there was substantial heterogeneity, which could be partially explained by the intervention duration, comparator, and study outcomes. The risk of bias was high, and confidence in the quality of the evidence was very low (Grading of Recommendations, Assessment, Development, and Evaluations), primarily because of the high rates of study dropout (average 37%; range 0%-85%) and suboptimal intervention adherence (average 40%).
Conclusions:
This study provides a novel contribution to knowledge regarding the effectiveness, strengths, and weaknesses of fully automated digital mental well-being interventions in the general population. Future research and practice should consider these findings when developing fully automated digital mental well-being tools. In addition, research should aim to investigate positive psychology and cognitive behavioral therapy–based tools as well as develop further strategies to improve adherence and reduce dropout in fully automated digital mental well-being interventions. Finally, it should aim to understand when and for whom these interventions are particularly beneficial.
Recent years have highlighted an increasing need to promote mental well-being in the general population. This has led to a rapidly growing market for fully automated digital mental well-being tools. Although many individuals have started using these tools in their daily lives, evidence on the overall effectiveness of digital mental well-being tools is currently lacking.
Objective:
This study aims to review the evidence on the effectiveness of fully automated digital interventions in promoting mental well-being in the general population.
Methods:
Following the preregistration of the systematic review protocol on PROSPERO, searches were carried out in MEDLINE, Web of Science, Cochrane, PsycINFO, PsycEXTRA, Scopus, and ACM Digital (initial searches in February 2022; updated in October 2022). Studies were included if they contained a general population sample and a fully automated digital intervention that exclusively used psychological mental well-being promotion activities. Two reviewers, blinded to each other’s decisions, conducted data selection, extraction, and quality assessment of the included studies. Narrative synthesis and a random-effects model of per-protocol data were adopted.
Results:
We included 19 studies that involved 7243 participants. These studies included 24 fully automated digital mental well-being interventions, of which 15 (63%) were included in the meta-analysis. Compared with no intervention, there was a significant small effect of fully automated digital mental well-being interventions on mental well-being in the general population (standardized mean difference 0.19, 95% CI 0.04-0.33; P=.02). Specifically, mindfulness-, acceptance-, commitment-, and compassion-based interventions significantly promoted mental well-being in the general population (P=.006); insufficient evidence was available for positive psychology and cognitive behavioral therapy–based interventions; and contraindications were found for integrative approaches. Overall, there was substantial heterogeneity, which could be partially explained by the intervention duration, comparator, and study outcomes. The risk of bias was high, and confidence in the quality of the evidence was very low (Grading of Recommendations, Assessment, Development, and Evaluations), primarily because of the high rates of study dropout (average 37%; range 0%-85%) and suboptimal intervention adherence (average 40%).
Conclusions:
This study provides a novel contribution to knowledge regarding the effectiveness, strengths, and weaknesses of fully automated digital mental well-being interventions in the general population. Future research and practice should consider these findings when developing fully automated digital mental well-being tools. In addition, research should aim to investigate positive psychology and cognitive behavioral therapy–based tools as well as develop further strategies to improve adherence and reduce dropout in fully automated digital mental well-being interventions. Finally, it should aim to understand when and for whom these interventions are particularly beneficial.
| Original language | English |
|---|---|
| Article number | e44658 |
| Journal | JMIR mental health |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 19 Oct 2023 |
Bibliographical note
AcknowledgmentsThe authors are grateful for the support of the librarians at the University of Bath and advice from Emma Fisher in conducting the meta-analysis. This work was supported by the Economic and Social Research Council (grant 2572559) and Cyberlimbic Systems Ltd.
Data Availability
For the purpose of open access, the author has applied a Creative Commons Attribution (CC-BY) license. Data supporting this study are openly available from UK Data Service.
Funding
The authors are grateful for the support of the librarians at the University of Bath and advice from Emma Fisher in conducting the meta-analysis. This work was supported by the Economic and Social Research Council (grant 2572559) and Cyberlimbic Systems Ltd. JG received partial funding for this research project from Cyberlimbic Systems Ltd. TT is the chief executive officer and cofounder of Cyberlimbic Systems Ltd. BA received funding from the National Institute of Health Research and the UK Research and Innovation on the topic of digital health interventions. BA also sits on the scientific advisory board of the Medito Foundation and earGym. The remaining authors have no conflicts of interest to declare.
| Funders | Funder number |
|---|---|
| Cyberlimbic Systems Ltd | |
| UK Research and Innovation | |
| Economic and Social Research Council | 2572559 |
| National Institute for Health and Care Research |
Keywords
- apps
- digital
- intervention
- mental well-being
- mobile phone
- promotion
- web-based
ASJC Scopus subject areas
- Psychiatry and Mental health
