When Pap Testing Fails to Prevent Cervix Cancer: A Qualitative Study of the Experience of Screened Women Under 50 with Advanced Cervix Cancer in Canada
Bibliographic record
Abstract
INTRODUCTION: While Papanicolaou (Pap) smears have resulted in a significant decline in cervical cancer incidence and mortality, our clinical experience indicates some women still present with locally advanced cervical cancer (LACC) despite having received Pap smear screening. Recent guidelines have decreased the recommended frequency of Pap smears to every three years. Our study sought to investigate the experiences of young women compliant with cervical screening who presented with LACC. METHODS: Women under 50 with LACC, FIGO (International Federation of Gynecology and Obstetrics) stage IB1 to IVA who underwent a Pap smear within two years of diagnosis and received curative intent chemoradiotherapy between September 2010 and December 2012 were included. Participants were treated at a tertiary academic cancer centre and invited for a semi-structured, in-person interview, which was analysed qualitatively using thematic analysis. RESULTS: Thirteen out of 38 women had Pap screening two or less years before diagnosis. Ten consented to participate in an interview. Several key themes emerged: I) Belief that LACC does not occur in those who undergo screening; II) Lack of understanding about LACC symptoms/diagnosis of cervix cancer; III) Reluctance from health care providers to perform a detailed pelvic examination in the presence of symptoms; IV) Negative emotions including anger, shame, regret, mistrust; V) Changes in quality of life from treatment; VI) Advice for other women. CONCLUSIONS: One-third of women presenting with LACC had appropriate Pap screening prior to diagnosis. Patients believe delays in their diagnosis resulted in detrimental quality of life. There is a need to educate physicians and the public about the symptoms of cervix cancer and to consider this diagnosis even when Pap screening has occurred.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| 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".