Cancer screening in the context of women's health: Perceptions of body and self among women of different ages in urban Sweden
Bibliographic record
Abstract
Most research on cervical cancer screening from the perspective of the involved women tends to focus on issues specifically related to screening participation, knowledge and information needs or experiences. Our previous research in this area indicated a need to investigate women's perspectives on cancer screening within a broader framework. Therefore, in this study, we aim to understand better, how women reason about health, ill health, health maintenance and disease prevention, in relation to cancer prevention and screening. We conducted twelve focus group discussions in Sweden with 49 women between the ages of 21 and 74 years. The findings indicate that women's reasoning about different aspects of “control”—physical, physiological, emotional and social—was central in understanding their view on cancer prevention and screening. The desire for and burden of maintaining control appeared to affect their decisions and attitudes toward cervical cancer screening, with health maintenance described as having a “high price”. Whereas some women motivated their screening attendance as a means of maintaining control, others described abstaining from screening which appeared to threaten their sense of control. It was also found that women reason differently about mammography and cervical cancer screening, which is contrary to assumptions guiding research in this area.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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; 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".