Experiences of community-dwelling older adults living with multiple chronic conditions: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to understand the experiences of living with multiple chronic conditions (MCC) from the perspective of community-living older adults with MCC. DESIGN: A qualitative study using an interpretive description approach. SETTING: Participants were recruited from southern Ontario, Canada. PARTICIPANTS: 21 community-living, older adults (≥65 years) with an average of 7.4 chronic conditions including one of diabetes, dementia or stroke. METHODS: Data were collected through digitally-recorded, in-depth, semi-structured in-person interviews. Interview transcripts were analysed and coded using Thorne's interpretive description approach. RESULTS: Five themes were identified representing older adults' experiences of living with MCC: (a) trying to stay healthy while living with MCC, (b) depending on family caregivers for support with just about everything, (c) paying the high costs of living with MCC, (d) making healthcare decisions by proxy and (e) receiving healthcare services that do not address the complex needs of persons living with MCC. CONCLUSIONS: The experience of living with MCC in the community was complex and multi-faceted. The need for a person-centred and family-centred approach to care in the community, which includes the coordination of health and social services that are tailored to the needs of older adults and their informal caregivers, was underscored. Such an approach would facilitate improved information-sharing and discussion of care management options between health professionals and their patients, enable older adults with MCC to actively engage in priority-setting and decision-making and may result in improved health and quality of life for older adults with MCC.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".