Exploring caregiver perspectives on health service delivery priorities for individuals with complex care needs: a qualitative descriptive study
Bibliographic record
Abstract
BACKGROUND: Health research in Canada is progressively moving towards engaging patients and their caregivers in projects where they can positively contribute to the improvement of healthcare systems and practices. One aspect of patient-oriented research (POR) focuses on identifying patient priorities for health research. Relative to their population size, patients with complex care needs (CCN) account for disproportionately high health services usage. Therefore, these patients and their caregivers are well-positioned to offer informed perspectives on health service delivery improvements. METHODS: Using a cross-sectional qualitative descriptive design, we explored health service delivery research priorities for two patient populations: children/youth with CCN and older adults with CCN, in New Brunswick, Canada. Despite concerted efforts to recruit patients directly, only caregivers responded to the recruitment materials. Qualitative data was collected using semi-structured interviews, focus groups, and self-report surveys. Data were analyzed using qualitative content analysis. RESULTS: Thirty-seven caregivers of children/youth and 35 caregivers of older adults took part in the study. While the study initially aimed to identify research priorities, participants primarily emphasized service gaps and made concrete recommendations for health system improvements. The top five priority areas for improving health service delivery for caregivers of children/youth with CCN were: (1) access to appropriate health care supports and services; (2) care continuity and coordination; (3) transitions to adulthood; (4) school and daycare system barriers; and (5) caregiver support. The top five priority areas for improving health service delivery for older adults with CCN according to their caregivers were: (1) access to appropriate health care supports and services; (2) home care issues and barriers; (3) care navigation and coordination; (4) impact of COVID-19 on care; and (5) caregiver support. CONCLUSION: This study highlights the multifaceted nature of caring for individuals with CCN. Our findings provide direction for future health research projects and offer practical guidance for health system decision-makers in the effort to improve health service delivery, particularly for our most vulnerable populations.
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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".