Building a Bridge to the Community: An Integrated Knowledge Translation Approach to Improving Participation in Community-Based Exercise for People After Stroke
Bibliographic record
Abstract
BACKGROUND: People who have had a stroke and are living in the community have low levels of physical activity, which reduces their functional capacity and increases risks of developing secondary comorbid conditions. Exercise delivered in community centers can address these low levels of physical activity; however, implementing evidence-based programs to meet the needs of all community stakeholders is challenging. OBJECTIVES: The objective of this study was to determine implementation factors to facilitate participation in relevant exercise and physical activity for people with chronic health conditions, like stroke. DESIGN: The design consisted of a qualitative observational study using an integrated knowledge translation approach. METHODS: Supported by an integrated knowledge translation approach, a series of focus groups-with stakeholder group representation that included people who had had a stroke and care partners, community organizations (ie, support groups, community center staff), health care providers, and exercise deliverers-was conducted. During the focus groups, participants provided perspectives on factors that could influence implementation effectiveness. Focus groups were recorded, transcribed, and thematically analyzed. RESULTS: Forty-eight stakeholders participated. Based on the themes, a new implementation model that describes the importance of relationships between community centers, clinicians, and people who have had a stroke is proposed. The development of partnerships facilitates the implementation and delivery of exercise programs for people with ongoing health needs. These partnerships address unmet needs articulated in the focus groups and could fill a gap in the continuity of care. CONCLUSIONS: Data from this study support the need for the community sector to offer a continuing service in partnership with the health system and people with chronic health needs. It indicates the potential of clinicians to partner with people with chronic health conditions and empower them to improve participation in relevant health behaviors, like community-based exercise.
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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 | 0.052 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".