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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Apr 16, 2026
Date Accepted: Jun 20, 2026

The final, peer-reviewed published version of this preprint can be found here:

Measurement-Based Mental Health Care for Adolescents in Africa: Protocol for a Computerized Adaptive Test

Moffett B, Bitta M, Williams D, Doenz J, Erskine H, Mabia C, Nkuna T, Gomes S, van Heerden A, Marlow M, Maravilla J, Tomlinson M, Craske MG, Hartley MA, Gibbons RD

Measurement-Based Mental Health Care for Adolescents in Africa: Protocol for a Computerized Adaptive Test

JMIR Res Protoc 2026;15:e98369

DOI: 10.2196/98369

PMID: 42710021

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

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

  • Bianca Moffett; 
  • Mary Bitta; 
  • Darryn Williams; 
  • Jonathan Doenz; 
  • Holly Erskine; 
  • Constance Mabia; 
  • Tamera Nkuna; 
  • Stash Gomes; 
  • Alastair van Heerden; 
  • Marguerite Marlow; 
  • Joemer Maravilla; 
  • Mark Tomlinson; 
  • Michelle G. Craske; 
  • Mary-Anne Hartley; 
  • Robert D. Gibbons

ABSTRACT

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.


 Citation

Please cite as:

Moffett B, Bitta M, Williams D, Doenz J, Erskine H, Mabia C, Nkuna T, Gomes S, van Heerden A, Marlow M, Maravilla J, Tomlinson M, Craske MG, Hartley MA, Gibbons RD

Measurement-Based Mental Health Care for Adolescents in Africa: Protocol for a Computerized Adaptive Test

JMIR Res Protoc 2026;15:e98369

DOI: 10.2196/98369

PMID: 42710021

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