Medication Management Support Needs in Dementia Care: Caregiver and Healthcare Provider Perspectives
Bibliographic record
Abstract
Medication management represents one of the most frequent and challenging tasks assumed by unpaid family caregivers of people living with dementia (PLWD), yet existing supports often fall short of caregivers’ needs. This dissertation explores how medication management is experienced and supported in dementia caregiving contexts, addressing four research questions: 1) What are the experiences of caregivers managing medications for PLWD? 2) What are the needs and preferences regarding resources that support medication management for caregivers of PLWD? 3) What do healthcare providers (HCPs) perceive to be the needs of caregivers of PLWD regarding resources and support for medication management? and 4) How do HCPs contribute to supporting the medication management activities of caregivers for PLWD? A concurrent embedded mixed methods approach was used to answer the first two research questions, where the experiences of 13 caregivers in Ontario were examined through a quantitative survey with embedded semi-structured interviews. Quantitative data were analyzed descriptively and using non-parametric tests, while qualitative data were analyzed through content analysis. A qualitative descriptive approach using semi-structured interviews with seven Ontario HCPs was used to answer the third and fourth research questions. Data were analyzed through reflexive thematic analysis. Caregivers’ experiences with medication management varied, reflecting individual circumstances, dementia progression, and available supports, encompassing both practical challenges and adaptive strategies. They emphasized the need for dementia-specific resources that are practical, anticipatory, and accessible across digital and print formats, with preference for opportunities to learn from peers and facilitation from HCPs. Five key caregiver needs were identified through the HCP interviews, where access to medication information and education, adherence support, tracking tools, optimized prescribing practice, and referral to formal services were emphasized. HCPs showed commitment to supporting caregivers through education and routine support, though systemic barriers limited consistency. Through integration of these findings, this dissertation contributes four themes that advance understanding of medication management in dementia caregiving. The themes emphasize support for caregivers related to dementia stage-specific medication information; policy and practice advancements to improve shared decision-making; systemic changes to expand adoption of digital tools for medication tracking and adherence; and structured approaches to assess caregiver capacity.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".