Factors Determining Women’s Attitudes and Knowledge Toward Breast Cancer Screening: A Systematic Review
Bibliographic record
Abstract
Background/Objectives: Breast cancer (BCA) is one of the most common cancers affecting women worldwide. Screening has been linked to up to a 33% reduction in breast cancer-related deaths by helping detect tumors at an early stage. The successful implementation of community-based breast cancer screening programs depends on understanding the attitudes of women within the target community. This study aims to systematically review the literature to assess the association between women’s attitudes toward breast cancer screening and their life satisfaction and general attitudes toward life. We also aimed to examine women’s attitudes toward breast cancer screening recommendations and the factors that influence these attitudes. Methods: A systematic review of English-language literature was carried out. PubMed and Scopus were searched up to November 2024 for studies that met the predefined inclusion criteria. Methodologic quality was assessed using the adapted Newcastle–Ottawa Scale for cross-sectional studies and the corresponding scale for cohort studies. Results: Eleven studies met the inclusion criteria. The percentage of women who had undergone at least one breast cancer screening ranged from 8.3% to 94.5%. Women’s attitudes toward and participation in breast cancer screening were linked to psychological, social, and demographic factors. Lower levels of life satisfaction, self-efficacy, and perceived control or mastery in life, along with higher levels of non-work-related stress, and higher levels of optimism, were associated with a lower likelihood of participating in breast cancer screening.
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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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".