A systematic review and psychometric evaluation of resilience measurement scales for people living with dementia and their carers
Bibliographic record
Abstract
Psychometrically sound resilience outcome measures are essential to establish how health and care services or interventions can enhance the resilience of people living with dementia (PLWD) and their carers. This paper systematically reviews the literature to identify studies that administered a resilience measurement scale with PLWD and/or their carers and examines the psychometric properties of these measures. Electronic abstract databases and the internet were searched, and an international network contacted to identify peer-reviewed journal articles. Two authors independently extracted data. They critically reviewed the measurement properties from the available psychometric data in the studies, using a standardised checklist adapted for purpose. Fifty-one studies were included in the final review, which applied nine different resilience measures, eight developed in other populations and one developed for dementia carers in Thailand. None of the measures were developed for use with people living with dementia. The majority of studies (N = 47) focussed on dementia carers, three studies focussed on people living with dementia and one study measured both carers and the person with dementia. All the studies had missing information regarding the psychometric properties of the measures as applied in these two populations. Nineteen studies presented internal consistency data, suggesting seven of the nine measures demonstrate acceptable reliability in these new populations. There was some evidence of construct validity, and twenty-eight studies hypothesised effects a priori (associations with other outcome measure/demographic data/differences in scores between relevant groups) which were partially supported. The other studies were either exploratory or did not specify hypotheses. This limited evidence does not necessarily mean the resilience measure is not suitable, and we encourage future users of resilience measures in these populations to report information to advance knowledge and inform further reviews. All the measures require further psychometric evaluation in both these populations. The conceptual adequacy of the measures as applied in these new populations was questionable. Further research to understand the experience of resilience for people living with dementia and carers could establish the extent current measures -which tend to measure personal strengths -are relevant and comprehensive, or whether further work is required to establish a new resilience outcome measure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.180 | 0.092 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".