Development and evaluation of a social inclusion framework for a comprehensive hospital-based elder abuse intervention
Bibliographic record
Abstract
A framework of social inclusion can promote equity and aid in preventing and addressing the abuse of older adults. Our objective was to build a social inclusion framework for a comprehensive hospital-based elder abuse intervention being developed. Potential components of such a framework, namely, health determinants and guiding principles, were extracted from a systematic scoping review of existing responses (e.g., interventions, protocols) to elder abuse and collated. These were subsequently rated for their importance to the elder abuse intervention by a panel of violence experts and further evaluated by a panel of elder abuse experts. The final social inclusion framework comprised 12 health determinants each representing factors underpinning susceptibility for abuse in aging populations: history of trauma/abuse, communication needs, disability, health status, mental capacity, social support, culture, language, sexuality, religion, gender identity, and socioeconomic status. The framework also comprised 19 guiding principles each encompassing considerations for equitable engagement with older adults (e.g., All older adults have the right to self-determination, All older adults have the right to be safe, All older adults are assumed competent unless determined otherwise). Integrating this social inclusion framework into the design and delivery of an elder abuse intervention could empower older adults, while at the same time ensuring that practices and policies are tailored to meet their unique and varying needs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".