Key informants' perspectives on implementing caregiver programs in an organized system of stroke care
Bibliographic record
Abstract
PURPOSE: Family caregivers provide essential support to individuals recovering after experiencing a stroke. Although clinical guidelines recommend the provision of caregiver education and support, these guidelines have not been implemented into standard clinical practice. The objective of this study was to gain insight from key informants-affiliates of a regional stroke system-to identify organization and system level barriers and facilitators associated with implementing stroke caregiver programs. METHODS: Twelve key informants were interviewed. Informants discussed their experiences with and perceptions of caregiver programs. They also identified barriers and facilitators to implementing caregiver programs. Interview data were analyzed using inductive thematic analysis. RESULTS: Three themes were generated: (1) lack of consensus on the need for caregiver education and support programs as part of the health care system; (2) a collaborative process is needed to engage stakeholders and identify champions (3) stakeholders need different types of evidence in support of implementation. CONCLUSIONS: This study provides initial insight into the potential barriers and facilitators needed to develop and implement stroke caregiver programs. Further exploration of these topics can inform caregiver program development and their implementation into stroke systems of care.IMPLICATIONS FOR REHABILITATIONRehabilitation research needs to demonstrate that caregivers are a unique group in need of support from the health care system.Rehabilitation research needs to contribute to the evidence that caregiver programs can improve patient, caregiver, and health system outcomes.Researchers can enhance caregiver program implementation through collaboration between researchers, stakeholders, and system change champions starting with program development.
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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 | 0.021 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| 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".