‘Thinking you're old and frail’: a qualitative study of frailty in older adults
Bibliographic record
Abstract
ABSTRACT Many older adults experience what is clinically recognised as frailty but little is known about the perceptions of, and attitudes regarding, being frail. This qualitative study explored adults' perceptions of frailty and their beliefs concerning its progression and consequences. Twenty-nine participants aged 66–98 with varying degrees of frailty, residing either in their homes or institutional settings, participated in semi-structured interviews. Verbatim transcripts were analysed using a Grounded Theory approach. Self-identifying as ‘frail’ was perceived by participants to be strongly related to their own levels of health and engagement in social and physical activity. Being labelled by others as ‘old and frail’ contributed to the development of a frailty identity by encouraging attitudinal and behavioural confirmation of it, including a loss of interest in participating in social and physical activities, poor physical health and increased stigmatisation. Using both individual and social context, different strategies were used to resist self-identification. The study provides insights into older adults' perceptions and attitudes regarding frailty, including the development of a frailty identity and its relationship with activity levels and health. The implications of these findings for future research and practice are discussed.
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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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".