Help seeking for cancer ‘alarm’ symptoms: a qualitative interview study of primary care patients in the UK
Bibliographic record
Abstract
BACKGROUND: Delay in help seeking for cancer 'alarm' symptoms has been identified as a contributor to delayed diagnosis. AIM: To understand people's help-seeking decision making for cancer alarm symptoms, without imposing a cancer context. DESIGN AND SETTING: Community-based, qualitative interview study in the UK, using purposive sampling by sex, socioeconomic status, and prior help seeking, with framework analysis of transcripts. METHOD: Interviewees (n = 48) were recruited from a community-based sample (n = 1724) of adults aged ≥50 years who completed a health survey that included a list of symptoms. Cancer was not mentioned. Participants reporting any of 10 cancer alarm symptoms (n = 915) and who had consented to contact (n = 482) formed the potential pool from which people were invited to an interview focusing on their symptom experiences. RESULTS: Reasons for help seeking included symptom persistence, social influence, awareness/fear of a link with cancer, and 'just instinct'. Perceiving the symptom as trivial or 'normal' was a deterrent, as was stoicism, adopting self-management strategies, and fear of investigations. Negative attitudes to help seeking were common. Participants did not want to be seen as making a fuss, did not want to waste the doctor's time, and were sometimes not confident that the GP could help. CONCLUSION: Decision making about cancer alarm symptoms was complex. Recognition of cancer risk almost always motivated help seeking (more so than the fear of cancer being a deterrent), assisted by recent public-awareness campaigns. As well as symptom persistence motivating help seeking, it could also have the reverse effect. Negative attitudes to help seeking were significant deterrents.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".