Resilience in Relation to Multimorbidity in Older Adults: A Scoping Review
Bibliographic record
Abstract
Abstract Multimorbidity is widespread, costly, and associated with a range of deleterious symptoms, affecting 70-80 % of older adults. Resilience in late life has been the focus of considerable research to understand differences in vulnerabilities and recovery from stressors relevant to multimorbidity. Despite this, previous reviews have not focused on resilience in relation to multimorbidity in older adults; therefore, this study synthesized relevant literature. The study design was a scoping review following JBI methodology. Searched electronic databases included PubMed, Embase, CINAHL, and PsycINFO. Data were extracted by two independent reviewers and charted using Garrard’s review matrix method. Gough’s weight of evidence criteria were used to appraise quality. Of 468 retrieved studies, 14 met inclusion criteria, primarily from the US, UK, and Canada. Most resilience in multimorbidity frameworks operationalize resilience as dependent on the socio-environmental context of older adults. Resilience was commonly considered a dynamic process, but only one study was longitudinal. Measures were primarily psychological or psycho-social in nature and did not include biological or physical measures of resilience. Quality of life and quality of care were common outcomes; resilience significantly related to these outcomes. Findings indicate both the important relationships of resilience with outcomes of multimorbidity, as well as multiple gaps in our current understanding of resilience in relation to multimorbidity. Results highlight the need for studies with diverse populations across diverse cultures, studies that incorporate multidimensional measures, with attention to physiological or physical properties of resilience, and longitudinal studies that capture the dynamic process of resilience in multimorbidity.
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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 | 0.012 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".