Potential Factors Influencing Adoption of a Primary Care Pathway to Prevent Functional Decline in Older Adults
Bibliographic record
Abstract
Introduction To help recognize and care for community-dwelling older adults living with frailty, we plan to implement a primary care pathway consisting of frailty screening, shared decision-making to select a preventive intervention, and facilitated referral to community-based services. In this study, we examined the potential factors influencing adoption of this pathway. Methods In this qualitative, descriptive study, we conducted semi-structured interviews and focus groups with patients aged 70 years and older, health professionals (HPs), and managers from four primary care practices in the province of Quebec, representatives of community-based services and geriatric clinics located near the practices. Two researchers conducted an inductive/deductive thematic analysis, by first drawing on the Consolidated Framework for Implementation Research and then adding emergent subthemes. Results We recruited 28 patients, 29 HPs, and 8 managers from four primary care practices, 16 representatives from community-based services, and 10 representatives from geriatric clinics. Participants identified several factors that could influence adoption of the pathway: the availability of electronic and printed versions of the decision aids; the complexity of including a screening form in the electronic health record; public policies that limit the capacity of community-based services; HPs’ positive attitudes toward shared decision-making and their work overload; and lack of funding. Conclusions These findings will inform the implementation of the care pathway, so that it meets the needs of key stakeholders and can be scaled up.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".