B-55An Examination of the World Health Organization Disability Assessment Schedule 2.0 with an Inpatient Rehabilitation Population
Bibliographic record
Abstract
Objective: The International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) advocates the use of the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) as a measure of health disability across cognition, mobility, self-care, interacting with others, life activities, and participation in community activities. However, research on the use of the WHODAS 2.0 with a rehabilitation population is limited. Study purpose: examine the relationship of demographic variables and a measure of cognitive impairment with the WHODAS 2.0. It was hypothesized that older age and higher scores of cognitive impairment would be predictive of greater disability. Method: Archival data was utilized to conduct a regression analysis examining the relationship between age, education, cognitive impairment as assessed by the Montreal Cognitive Assessment (MoCA), and disability as assessed by the WHODAS 2.0. The sample was comprised of 43 individuals with a mean age of 65 (SD = 14.51) years and 12.71 (SD = 2.63) years of education. The sample mean for the MoCA was 20.44 (SD = 4.70) and 80.86 (SD = 25.53) for the WHODAS 2.0. Results: The correlation coefficients between age, education, cognitive impairment and the WHODAS 2.0 are -.14, .26, and -.22, respectively. The variables in the regression analysis did not predict disability as assessed by the WHODAS 2.0 F(3, 39) = .87, p = .47. Conclusion: Disability and social impairment should not be inferred from data alone but rely upon multiple forms of information from outside sources. Results stress the importance of seeking input on adaptive functioning from family and multidisciplinary team members.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".