Piloting a Points-Based Caseload Measure for Community Based Paediatric Occupational and Physiotherapists
Bibliographic record
Abstract
BACKGROUND: Caseload guidelines and workload management are important issues in recruitment and retention of paediatric rehabilitation therapists. PURPOSE: This study developed and piloted a points-based caseload questionnaire for paediatric occupational and physiotherapists. METHODS: Therapists completed the pilot caseload measure and participated in teleconference focus groups to share their experiences and opinions. Analysis was through descriptive statistics and qualitative analysis. FINDINGS: The data suggested links between caseload point size and various factors such as years of experience, manageability, and client maturity. Focus group feedback supported the use of points rather than numbers as a caseload measure. Participants suggested various uses for the measure and changes to improve ease and consistency in completion. IMPLICATIONS: This caseload measure holds promise, following ongoing research, as a method to standardize caseloads across paediatric settings. As is, it can be used within agencies or by individual therapists seeking a tool of self-reflection and of workload measure.
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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 | 0.028 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".