What older adults want from their health care providers
Bibliographic record
Abstract
Changing demographic trends and population needs have increased demand for chronic complex care and contributed to rising health care costs. The study sought to identify unmet health care needs of older adults and opportunities for service improvement in a high need suburban neighborhood of a prairie province. The insights provided by older adults informed the service design for a new model of integrated care in community settings. Narrative inquiry methodology was used to understand care experiences through stories. Stories of older adults’ health care journeys were elicited with semi-structured interviews. A paradigmatic approach to analysis was applied with holistic coding, mapping of story elements followed by comparison and theming across participants’ stories. Older adults perceived that relationship and informational continuity fostered effective communication and supported coordination of care. Timely access to care was valued and flexibility in types of medical encounters was suggested as an option to improve provider responsiveness. Access to information about community resources was limited and older adults required support with navigation. Structural (e.g. availability of services and transportation), financial and personal barriers exist for older adults to access and use community health services. Health care transitions were inadequately supported by comprehensive discharge planning, timely communication and follow up post discharge. New models of care need to embrace person-centred and goal directed approaches to the delivery of care to improve patient experience. Older adults offer valuable perspectives as community partners and co-designers of systems change in efforts to re-engineer health services.
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 | 0.003 | 0.012 |
| 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 | 0.004 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".