Predictors of primary health care utilization by former residents of institutions in Ontario
Bibliographic record
Abstract
For years institutionalization has been the primary method of service delivery for \npersons with developmental disabilities (DD). However, in Ontario the last institution \nwas closed on March 31, 2009 with former residents now residing in small, communitybased homes. This study investigated potential predictors of primary health care \nutilization by former residents. Several indirect measures were employed to gather \ninformation from 60 participants on their age, health status, adaptive functioning level, \nproblem behaviour, mental health status and, total psychotropic medication use. A direct \nmeasure was used to gather primary health care utilization information, which served as \nthe dependent variable. A stepwise linear regression failed to reveal significant predictors \nof health care utilization. The data were subsequently dichotomized and the outcomes of \na logistic regression analysis indicated that mental health status, psychotropic medication \nuse and, an interaction between mental health status and health status significantly \npredicted higher primary health care usage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".