Desempenho ocupacional e aplicação da Classificação Internacional de Funcionalidade (CIF) em um serviço de reabilitação
Bibliographic record
Abstract
OBJECTIVE: To describe the socio-demographic profile and analyze the occupational performance of users of a specialized rehabilitation service according to the International Classification of Functioning, Disability, and Health (ICF) model. MATERIALS AND METHODS: Documentary and exploratory study, in which the medical records from 97 patients treated between 2013 and 2015, were assessed using the Canadian Occupational Performance Measure (COPM). RESULTS: The age range of the patients was 14-83 years (average of 48.4 years), the majority being women (57.7%), married (43.3%), and retired (39.2%). Most patients had less than eight years of schooling (42.3%); 80.4% were sedentary; 12.4% smokers and 19.6% regularly consumed alcoholic beverages. Rotator cuff syndrome, stroke, and upper limb fracture were the most frequent diagnoses. The mean of occupational performance was 4.28 points (SD=1.84), and performance satisfaction was 4.43 points (SD=2.41). There were difficulties in self-care activities, functional mobility, productive activities and leisure and recreational activities. Regarding the components of the ICF, the Mobility domain obtained the highest number of categories cited by the users. In contrast, the Personal Care domain received the highest number of complaints. CONCLUSION: The occupational performance of the patients presented more limitations in self-care and productive activities. The application of ICF to classify activities identified specific demands in five domains, Mobility, and Personal care being the most frequent. These results allow directing health actions towards the real needs of the patients and structuring professional practice.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".