# Computer‐Assisted Performance‐Based Assessment for Mental Health: A Scoping Review

**Authors:** Hanya Li, Shuang Li

PMC · DOI: 10.1002/pchj.70086 · PsyCh Journal · 2026-02-27

## TL;DR

This paper reviews how computer-assisted tools can improve mental health assessments for adolescents by making them more objective and adaptable.

## Contribution

The study maps current CAT applications in PBAs and highlights under-researched areas like social-emotional domains.

## Key findings

- CATs enhance PBAs through data analysis, acquisition, and scenario creation.
- PBA scenarios show adaptability for multidimensional mental health assessment.
- Integrating validated scales into PBAs could improve assessment reliability.

## Abstract

Adolescent mental health is foundational to personal development, yet it faces escalating challenges globally. While traditional assessment methods lack objectivity and ecological validity, integrating computer‐assisted technology (CAT) into performance‐based assessments (PBAs) offers a promising pathway. This review, following the PRISMA‐ScR reporting standard, analyzed 89 articles (2015–2025) to map the assessed components, CAT applications, and scenario diversity in mental health PBAs. Analysis revealed a research emphasis on mental disorders, with critical domains for adolescent development remaining significantly understudied. CATs significantly enhanced PBAs through data analysis, data acquisition, scenario creation, and tool digitization. PBA scenarios are diverse, demonstrating the adaptability of PBAs for multidimensional mental health assessment. Prioritizing the design of PBAs for social–emotional and adaptive assessment is critical for the early identification of adolescent mental health issues. Furthermore, advancing predictive analytics and leveraging large language models for feedback generation are promising ways to unlock CAT's potential in enhancing PBAs. Importantly, integrating and adapting scenarios from validated scales by CATs into PBAs could further enhance assessment typicality and reliability.

## Full-text entities

- **Genes:** CAT [NCBI Gene 101093891]
- **Diseases:** suicidal ideation (MESH:D001072), mood (MESH:D019964), LLMs (MESH:D007806), DL (MESH:D007859), CATs (MESH:D002371), binge eating disorder (MESH:D056912), ASD (MESH:D000067877), internet addiction (MESH:D019966), Mental Disorders (MESH:D001523), Alzheimer's disease (MESH:D000544), anxiety (MESH:D001007), Schizophrenia (MESH:D012559), social anxiety (MESH:D000072861), depression (MESH:D003866), bipolar disorder (MESH:D001714), eating disorders (MESH:D001068), food addiction (MESH:D000073932), Cognitive impairments (MESH:D003072), internalizing disorders (MESH:D000082122), Idiopathic Arthritis (MESH:D001168), MH (MESH:C535694), ADHD (MESH:D001289), psychoses (MESH:D011618), Mental Health (OMIM:603663)
- **Chemicals:** PBA (-)
- **Species:** Mus musculus (house mouse, species) [taxon 10090], Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12946823/full.md

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12946823/full.md

## References

227 references — full list in the complete paper: https://tomesphere.com/paper/PMC12946823/full.md

---
Source: https://tomesphere.com/paper/PMC12946823