Women's perspectives on illness when being screened for cervical cancer
Bibliographic record
Abstract
BACKGROUND: In Greenland, the incidence of cervical cancer caused by human papillomavirus (HPV) is 25 per 100,000 women; 2.5 times the Danish rate. In Greenland, the disease is most frequent among women aged 30-40. Systematic screening can identify women with cervical cell changes, which if untreated may cause cervical cancer. In 2007, less than 40% of eligible women in Greenland participated in screening. OBJECTIVE: To examine Greenlandic women's perception of disease, their understanding of the connection between HPV and cervical cancer, and the knowledge that they deem necessary to decide whether to participate in cervical cancer screening. STUDY DESIGN: The methods used to perform this research were 2 focus-group interviews with 5 Danish-speaking women and 2 individual interviews with Greenlandic-speaking women. The analysis involved a phenomenological-hermeneutic approach with 3 levels of analysis: naive reading, structural analysis and critical interpretation. RESULTS: These revealed that women were unprepared for screening results showing cervical cell changes, since they had no symptoms. When diagnosed, participants believed that they had early-stage cancer, leading to feelings of vulnerability and an increased need to care for themselves. Later on, an understanding of HPV as the basis for diagnosis and the realization that disease might not be accompanied by symptoms developed. The outcome for participants was a life experience, which they used to encourage others to participate in screening and to suggest ways that information about screening and HPV might reach a wider Greenlandic population. CONCLUSION: Women living through the process of cervical disease, treatment and follow-up develop knowledge about HPV, cervical cell changes, cervical disease and their connection, which, if used to inform cervical screening programmes, will improve the quality of information about HPV, cervical cancer and screening participation. This includes that verbal and written information given at the point of screening and diagnosis needs to be complemented by visual imagery.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".