AfriCAT: Protocol for a Computerised Adaptive Test to advance measurement-based mental healthcare for adolescents in Africa (Preprint)

BACKGROUND Adolescent mental health care is constrained not only by limited treatment capacity, but by the absence of precise and efficient tools to identify and triage those in need. Measurement-based mental healthcare (MBMH) relies on standardized assessments to guide identification, treatment selection, and ongoing monitoring of mental disorders. However, conventional assessments present a trade-off: diagnostic interviews lack feasibility at scale; while brief screening tools result in misclassification and suboptimal allocation of limited mental health resources. Computerized adaptive testing (CAT) addresses this trade-off by dynamically tailoring assessments to individuals, maximizing measurement precision while minimizing assessment burden. Despite these advances, no adaptive assessment for adolescent mental health has been developed or calibrated using African data. OBJECTIVE The AfriCAT study aims to develop and internally validate a precision computerized adaptive assessment of adolescent depression and anxiety to support measurement-based mental healthcare in African contexts. METHODS AfriCAT is a mixed-methods study integrating psychometric modeling, adaptive simulation, modular clinical decision support networks, participatory workshops, discrete choice experiments (DCEs), and stakeholder interviews. Diagnostic Interview Schedule for Children, version 5 (DISC-5) modules assessing major depressive disorder, generalized anxiety disorder, social phobia and post-traumatic stress disorder among adolescents aged 10-17 years from the Kenya-National Adolescent Mental Health Survey (N=5,155) will form the item bank. Adaptive engines will be developed using a bifactor multidimensional item response theory framework and a modular neural architecture. Simulation-based internal validation will evaluate precision, efficiency, and diagnostic classification relative to DISC-5 diagnoses. Participatory workshops in Kenya and South Africa, DCEs to quantify adolescent preferences, and stakeholder interviews will inform refinement of adolescent- and provider-facing prototypes. RESULTS Ethical approval has been obtained from the Human Research Ethics Committee (Medical) at the University of the Witwatersrand and the Aga Khan University Institutional Scientific and Ethics Review Committee (ISERC). Data preparation and model development are underway. Participatory workshops and DCEs are ongoing. Simulation-based validation and prototype refinement will follow. CONCLUSIONS AfriCAT aims to develop the first adaptive mental health assessment calibrated using nationally representative African adolescent data. By integrating precision psychometrics with participatory co-design, the study seeks to enable more accurate triage and support scalable, measurement-based adolescent mental healthcare in resource-constrained settings.