THE CARE NAVIGATOR ROLE IN RURAL PRIMARY CARE MEMORY CLINICS
Bibliographic record
Abstract
Abstract Collaborative dementia care models that include a navigator role achieve better outcomes but little is known about impacts in rural settings. Rural primary healthcare memory clinic teams in Saskatchewan include Coordinators from the Alzheimer Society of Saskatchewan (ASOS) First Link Program, which aims to connect persons living with dementia (PLWD) and families with supports at diagnosis. We examined perceptions of First Link Coordinators (FLC) and memory clinic team members about the FLC role, and evaluated impact of the role within the memory clinic (compared to self- and direct-referrals from other healthcare providers) on timeliness, number of completed FLC-client contacts, topics discussed, duration, and contact method. The QUAL+QUAN design included: (1) semi-structured interviews with three FLC and six team members in four rural memory clinics, (2) routinely collected ASOS client data. Separate inductive thematic analyses with FLC and team interviews (Jan 2021-Apr 2023) identified two common themes: benefits for PLWD and families (eg, early and ongoing connection to emotional support) and benefits for team members (eg, can focus on their unique role). Face-to-face contact established a FLC-family relationship and facilitated follow-up contact. Longitudinal retrospective analysis of ASOS data found that between Dec 2017-Dec 2021, 139 clients (predominantly spouses, children) were referred. Compared to other referrals, statistically significant differences (p<.05) included: memory clinic clients contacted sooner after referral, longer duration of first contact, more completed contacts, more topics discussed. Findings demonstrate the added value of FLC in rural memory clinics. Future research should explore long-term outcomes for PLWD and families.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".