Ageism, negative attitudes, and competing co-morbidities – why older adults may not seek care for restricting back pain: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Back pain, the most common type of pain reported by older adults, is often undertreated for reasons that are poorly understood, especially in minority populations. The objective of this study was to understand older adults' beliefs and perspectives regarding care-seeking for restricting back pain (back pain that restricts activity). METHODS: We used data from a diverse sample of 93 older adults (median age 83) who reported restricting back pain during the past 3 months. A semi-structured discussion guide was used in 23 individual interviews and 16 focus groups to prompt participants to share experiences, beliefs, and attitudes about managing restricting back pain. Transcripts were analyzed in an iterative process to develop thematic categories. RESULTS: Three themes for why older adults may not seek care for restricting back pain were identified: (1) beliefs about the age-related inevitability of restricting back pain, (2) negative attitudes toward medication and/or surgery, and (3) perceived importance of restricting back pain relative to other comorbidities. No new themes emerged in the more diverse focus groups. CONCLUSIONS: Illness perceptions (including pain-related beliefs), and interactions with providers may influence older adults' willingness to seek care for restricting back pain. These results highlight opportunities to improve the care for older adults with restricting back pain.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".