ArticleFrontiers in psychiatry2023
Congruency of multimodal data-driven personalization with shared decision-making for StayFine: individualized app-based relapse prevention for anxiety and depression in young people.
Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05551468 (StayFine), which is not on this map. Cited by 5 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.
StayFine: a Personalized Monitoring and Intervention App to Prevent Relapse of Anxiety and Mood Disorders in Youth and Young Adults
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Personalization variables in digital mental health interventions for depression and anxiety in adolescents and youth: a scoping review.Frontiers in digital health · 2025Pooled it
- Uncovering the heterogeneity in young adult anxiety: subtypes predict outcomes of a CBT mobile app.Molecular psychiatry · 2026Article
- Effectiveness of digital and mobile-based interventions on sleep quality among nurses: a systematic review and meta-analysis.Frontiers in digital health · 2026Review
- Examining varying number of intervention-modules and change in individual networks in young people remitted from depression or anxiety: Exploratory outcomes of the StayFine randomized clinical trial.Neuroscience applied · 2026Article
- Randomized controlled study of a digital data driven intervention for depressive and generalized anxiety symptoms.NPJ digital medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tailoring interventions to the individual has been hypothesized to improve treatment efficacy. Personalization of target-specific underlying mechanisms might improve treatment effects as well as adherence. Data-driven personalization of treatment, however, is still in its infancy, especially concerning the integration of multiple sources of data-driven advice with shared decision-making. This study describes an innovative type of data-driven personalization in the context of StayFine, a guided app-based relapse prevention intervention for 13- to 21-year-olds in remission of anxiety or depressive disorders (
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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.