SUSTAINING COMMUNITY-BASED HEALTH INITIATIVES FOR ADULTS AGING WITH INTELLECTUAL DISABILITIES
Bibliographic record
Abstract
Community-based intellectual disabilities (ID) agencies provide services and supports to people aging with ID, offering these individuals opportunities to participate in their community and engage in health promoting behaviors. However, little is known about the factors involved with sustaining community-based health initiatives (CBHI) among ID agencies. The purpose of the current study was to explore the facilitators and barriers of sustaining CBHI for people aging with ID living in group homes managed by ID agencies. Two non-profit ID agencies participated in the study. Nineteen semi-structured interviews were conducted with directors, managers, and direct support staff. Interviews conducted with directors and regional managers provided a broader systemic perspective, whereas interviews with support staff provided a front line perspective of the factors that may be effecting CBHI sustainability within group home settings. Grounded theory methods, including constant comparison, were used for analysis. Findings show that although ID agencies understand the importance of health and community participation for their clients and support such initiatives, agencies lack policies, resources, and ID and health education to sustain CBHI for their clients aging with ID over time. It is important to gain a better understanding of the influencing factors involved in sustaining CBHI that are being implemented by these agencies to enable individuals with ID to experience the many positive physical, psychological, and social health outcomes as they age and to potentially decrease their risk of institutionalization due to poor health.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".