Acceptability of a mental health care pathway to address dementia risk factors in primary care settings: A qualitative study
Bibliographic record
Abstract
Abstract Background Given the projected increases in dementia prevalence across the world, it is imperative that we identify and mitigate the potential impacts of reversible risk factors for developing dementia. Depression, anxiety and mild cognitive impairment (MCI) are examples of such risk factors. However, despite their relatively high prevalence rates among those age 60 and over, these conditions often go unrecognized and untreated. A growing body of evidence suggests that evidence‐based interventions in primary care can increase detection and treatment rates of these conditions, and may help to prevent or prolong the development of dementia. This presentation reports on qualitative data collected as part of a longitudinal cohort study examining the implementation and effectiveness of an Integrative Care Pathway (ICP) for depression, anxiety and MCI in primary care settings. Method A qualitative descriptive design was used to examine the acceptability of the ICP by primary care providers. Two sets of focus groups were conducted with five participating primary care practices during the study. Participants varied by practice and included family physicians, nurses, allied health professionals, and administrative staff. Focus groups were audio‐recorded, transcribed verbatim, and analyzed using conventional content analysis. Result The findings indicate that providers had mixed reactions in terms of the acceptability of the ICP. The fact that the ICP was evidence‐based was a strength of the pathway and gave providers and patients reassurance regarding the management of depression, anxiety and MCI. However, the realities of primary care practice, particularly in terms of time constraints, indicated the need for flexibility in how the ICP is applied. Conclusion Having access to evidence‐based resources can support primary care providers in managing mental health risk factors for dementia. However, resources need to reflect the culture and practices of primary care settings in order for them to be acceptable to providers.
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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 | 0.037 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".