ReviewNature human behaviour2024
A collaborative realist review of remote measurement technologies for depression in young people.
Review in Nature human behaviour, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Remote Measurement-Based Care Interventions for Mental Health: Systematic Review and Meta-Analysis.JMIR mental health · 2026Pooled it
- Child and adolescent psychiatry: challenges, solutions, opportunities, and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026Article
- Smartphone gaze-tracking for accessible psychiatric assessment.Npj mental health research · 2026Article
- Effects of the SES NXT intervention on mental health and well-being for children of divorce.NPJ digital medicine · 2026Article
- Promoting Rehabilitation Using a Multimodal Internet of Things-Based Patient Monitoring System in a Smart Hospital.IEEE journal of translational engineering in health and medicine · 2026Article
- Characterizing heterogeneity in emotional and behavioral problems: Latent class analysis with 507,188 children and adolescents and associations with mobile gaming addiction behavior.Psychological medicine · 2025Article
- Can Artificial Intelligence Enhance European Emerging Adults' Psychological Adjustment? A Scoping Review.Behavioral sciences (Basel, Switzerland) · 2025Review
- Requirements and Concerns of Individuals Remitted From Depression for an Early Relapse Detection mHealth App: Focus Group Study.JMIR mHealth and uHealth · 2025Article
- A systematic review of strategies in digital technologies for motivating adherence to chronic illness self-care.npj health systems · 2025Article
- How to integrate physiological data from wearables in treatment of personality disorders: a narrative review.Frontiers in psychiatry · 2025Review
- A literature review of remote mental health screening: barriers, potential solutions, and tools.Frontiers in digital health · 2025Review
- Development of the psychopathological vulnerability index for screening at-risk youths: a Rasch model approach.Npj mental health research · 2024Article
- Accurately predicting mood episodes in mood disorder patients using wearable sleep and circadian rhythm features.NPJ digital medicine · 2024Article
- The behavioral and physiological correlates of affective mood switching in premenstrual dysphoric disorder.Frontiers in psychiatry · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
Digital mental health is becoming increasingly common. This includes use of smartphones and wearables to collect data in real time during day-to-day life (remote measurement technologies, RMT). Such data could capture changes relevant to depression for use in objective screening, symptom management and relapse prevention. This approach may be particularly accessible to young people of today as the smartphone generation. However, there is limited research on how such a complex intervention would work in the real world. We conducted a collaborative realist review of RMT for depression in young people. Here we describe how, why, for whom and in what contexts RMT appear to work or not work for depression in young people and make recommendations for future research and practice. Ethical, data protection and methodological issues need to be resolved and standardized; without this, RMT may be currently best used for self-monitoring and feedback to the healthcare professional where possible, to increase emotional self-awareness, enhance the therapeutic relationship and monitor the effectiveness of other interventions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.