Does social disadvantage affect the validity of self-report for cervical cancer screening?
Bibliographic record
Abstract
OBJECTIVE: The aim was to review the international literature on the validity of self-report of cervical cancer screening, specifically of studies that made direct comparisons among women with and without social disadvantage, based on race/ethnicity, foreign-born status, language ability, income, or education. METHOD: The databases of Medline, EBM Reviews, and CINAHL from 1990 to 2011 were searched using relevant search terms. Articles eligible for data extraction documented the prevalence of cervical cancer screening based on both self-report and an objective measure for women both with and without at least one measure of social disadvantage. The report-to-record ratio, the ratio of the proportion of study subjects who report at least one screening test within a particular time frame to the proportion of study subjects who have a record of the same test within that time frame, was calculated for each subgroup. RESULTS: Five studies met the extraction criteria. Subgroups were based on race/ethnicity, education, and income. In all studies, and across all subgroups, report-to-record ratios were greater than one, indicative of pervasive over-reporting. CONCLUSION: The findings suggest that objective measures should be used by policymakers, researchers, and public-health practitioners in place of self-report to accurately determine cervical cancer screening rates.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".