ReviewDigital health
Critical design decisions and user demographics in enhancing real-time digital mental health interventions: A systematic review.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Therapeutic Interaction Features of AI Chatbots in Depression Interventions: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Optimizing Usability of Digital Health Interventions for Nondigitally Native Adults: A Framework-Based Approach to Develop Just-in-Time Adaptive Interventions (JITAIs) and Other Adaptations.JMIR human factors · 2026Article
- Service quality optimization of online mental health communities: A KANO-IPA model approach.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Real-time digital mental health interventions, primarily enabled by smartphone technology offer continuous, personalised support, that adapts in response to the changing needs of individuals. Despite being prominently explored in populations with psychiatric disorders, there remains a notable gap in the systematic analysis of demographic characteristics, as well as the foundational design decisions or rules that underpin the personalisation of these interventions. Objectives: (a) Identifying the prevalent design decisions to enable personalisation within real-time digital mental health interventions, (b) the influence of these design decisions on the clinical outcomes of the interventions, and (c) the demographic characteristics of populations with psychiatric disorders targeted by real-time digital health interventions. Methods: Following PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines, a systematic literature review was conducted of peer-reviewed literature focusing on real-time digital interventions in populations with clinically diagnosed psychiatric disorders. We undertook a narrative synthesis to derive the demographics and personalisation design decisions of the interventions and conducted a pooled meta-analysis to evaluate clinical outcomes. Results: Interventions predominantly targeted female and Caucasian demographics, yielding modest clinical improvements. Our analysis identified nine critical personalisation design decisions concerning measurement, intervention, and interactions with health professional with varying influence on clinical outcomes. Conclusion: Understanding the complex nuances of design decisions that shape real-time digital health interventions, as well as identifying which patient demographics benefit most, is fundamental for their effective clinical impact and safe use. Prospero Registration: PROSPERO CRD42020161663.
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