Implementation of Behavioural Supports Ontario (BSO): An Evaluation of Three Models of Care
Bibliographic record
Abstract
Behavioural Supports Ontario (BSO) was launched to enhance the healthcare services for Ontario's seniors, their caregivers and families living and coping with responsive behaviours associated with dementia and other neurological conditions. The implementation of the program varied across and within the local health integration networks (LHINs). By 2015, there were three BSO models operating within the long-term care (LTC) home sector: in-home BSO teams, a mobile team that serves multiple LTC homes within a sub-area of a LHIN and a LHIN-wide mobile team that provides services to all homes. A survey was undertaken to identify the differences among the BSO models of care in relation to care planning, collaboration and team building and home-level resident outcomes. We found that three years after implementation, LTC staff reported that the in-home BSO model out-performs the mobile team across all key measures. There is a role for mobile teams to provide expertise and sharing of best practices across the regions, but future policy and funding should focus on supporting the development of in-home BSO teams.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".