Considerations of older adults with multimorbidity when facing healthcare choices: A qualitative systematic review
Bibliographic record
Abstract
OBJECTIVES: healthcare decision-making of older adults with multimorbidity is challenging and patient preferences regarding healthcare choices have been insufficiently studied. We aimed to explore what considerations older adults with multimorbidity take into account when facing choices in a healthcare context and what meaning these choices hold for them. METHODS: systematic review of literature from four databases up until November 2024 using a thematic synthesis of qualitative research (PROSPERO CRD42023477681). Peer-reviewed, empirical studies reporting on the considerations regarding healthcare choices of older people (aged ≥ 75) with multimorbidity in English were included. The JBI Critical Appraisal Checklist for Qualitative Research was used to appraise included studies. RESULTS: 20 articles relating to 19 studies with a total of 225 participants were included. Studies were mainly based on interviews (n = 12) or combined observational and interview data (n = 7) and reported on multiple types of healthcare choices. The synthesis showed a variety of patient considerations regarding engagement with decision-making delineating a spectrum of engagement and a diversity of drivers for healthcare choices. Contextual factors such as complexity, power dynamics, information provision, and relationships shaped patients' considerations. CONCLUSIONS AND PRACTICE IMPLICATIONS: The synthesis showed that considerations of older people with multimorbidity are diverse and considerably shaped by patient and decision context. Therefore, this context should be considered in decision-making, with specific attention to vulnerability to power dynamics, and room should be provided to attune decision-making to individual patient considerations. Interventions to improve integration of patient considerations in decision-making and patient engagement should not only focus on patients, but also target healthcare professionals and systems.
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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 | 0.042 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".