Data-driven supervision to optimize the effectiveness of proactive case detection for mental health care among children: a proof-of-concept study

Data-driven supervision to optimize the effectiveness of proactive case detection for mental health care among children: a proof-of-concept study

This proof-of-concept study evaluated an optimization strategy for the Community Case Detection Tool (CCDT) aimed at improving community-level mental health detection and help-seeking among children aged 6–18 years. The optimization strategy, CCDT+, combined data-driven supervision with motivational...

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Bibliographic Details
Main Authors: Myrthe van den Broek, M. Claire Greene, Anthony F. Guevara, Sandra Agondeze, Erimiah Kyanjo, Olivier Irakoze, Rosco Kasujja, Brandon A. Kohrt, Mark J. D. Jordans
Format: Article
Language:English
Published: Cambridge University Press 2025-01-01
Series:Cambridge Prisms: Global Mental Health
Subjects:
proof-of-concept
proactive case detection
optimization strategy
dashboard
sub-Saharan Africa
child and adolescent mental health
Online Access:https://www.cambridge.org/core/product/identifier/S205442512400150X/type/journal_article
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Summary:This proof-of-concept study evaluated an optimization strategy for the Community Case Detection Tool (CCDT) aimed at improving community-level mental health detection and help-seeking among children aged 6–18 years. The optimization strategy, CCDT+, combined data-driven supervision with motivational interviewing techniques and behavioural nudges for community gatekeepers using the CCDT. This mixed-methods study was conducted from January to May 2023 in Palorinya refugee settlement in Uganda. We evaluated (1) the added value of the CCDT+ in improving the accuracy of detection and mental health service utilization compared to standard CCDT, and (2) implementation outcomes of the CCDT+. Of the 1026 children detected, 801 (78%) sought help, with 656 needing mental health care (PPV = 0.82; 95% CI: 0.79, 0.84). The CCDT+ significantly increased detection accuracy, with 2.34 times higher odds compared to standard CCDT (95% CI: 1.41, 3.83). Additionally, areas using the CCDT+ had a 2.05-fold increase in mental health service utilization (95% CI: 1.09, 3.83). The CCDT+ shows promise as an embedded quality-optimization process for the detection of mental health problems among children and enhance help-seeking, potentially leading to more efficient use of mental health care resources.
ISSN:2054-4251

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