Dementia Care Evidence: Contextual Dimensions that Influence Use in Northern Home Care Centres
Bibliographic record
Abstract
Living and working in isolated northern communities pose challenges in using evidence to inform dementia care. Purpose : To better understand the contextual dimensions of two home care centres in two Canadian northern, rural communities that influence the use of evidence from the perspectives of home care providers (HCPs). Sample: All clinical leaders, managers, and home care providers (n=48 FTE) in the two home care centres were sent an information letter outlining the study’s purpose, expectations, and benefits and invited to participate in focus groups conducted in two home care centres. Fourteen staff participated in the two focus groups. Method: A qualitative interpretive descriptive approach was used. Semi-structured questions were used to guide the audiotape recorded focus groups. Transcripts were coded using Lubrosky’s thematic analysis. Findings: Our findings are described in broad contextual themes (e.g., challenges in using the RAI-HC, availability of resources, relationships in a rural community, leadership, and evaluation) that included both positive and negative contextual dimensions that influenced the use of evidence. Conclusions: Most importantly, reallocated resources are needed in northern home care settings. Challenges in exchanging evidence related to difficult relationships with physicians, clients, and their family caregivers. Leadership and collaboration dimensions were fundamental to establishing a vibrant workplace in which HCPs provided and exchanged evidence-based dementia care. Keywords: Evidence-based dementia care, northern home care, home care contextual dimensions, knowledge exchange. DOI: http://dx.doi.org/ 10.14574/ojrnhc.v15i1.344
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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 | 0.120 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.012 |
| 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".