Assessing Functioning across Common Mental Disorders in Psychiatric Emergency Patients: Results from the WHODAS-2
Bibliographic record
Abstract
OBJECTIVE: Assessing global functioning in psychiatric emergency settings is important for clinicians to estimate severity of mental disorders, devise a treatment plan, and assess the evolution of their patients' progression over time. The World Health Organization Disability Assessment Schedule-2.0 (WHODAS-2) measures psychological, social, and professional functioning and is recommended as a standardized instrument of choice for use in psychiatric settings. Yet, studies investigating disability profiles of mental disorders using the WHODAS-2 are scarce, and psychometric properties have not been evaluated in a psychiatric emergency context. We describe and compare WHODAS-2 (12-item version) scores across mental disorders (anxiety, mood, psychotic, personality, and substance abuse) in adults admitted to psychiatric emergency. METHODS: = 1,125). Mental disorders were evaluated by psychiatrists, and WHODAS-2 scores were compared across groups. Psychometric properties were evaluated using confirmatory factor analysis (CFA). RESULTS: < 0.001) compared to other psychopathologies. The measure showed good internal consistency (global score α = 0.88; domain subscores α = 0.59 to 0.85) and acceptable goodness of fit indices in CFA confirming the original structure of WHODAS-2. CONCLUSIONS: Findings from this large-scale study could assist clinicians in interpreting WHODAS-2 scores in psychiatric populations and provide a more detailed portrait of disability profiles associated with different clinical diagnoses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".