Prediction of breast self-examination in a sample of Iranian women: an application of the Health Belief Model
Bibliographic record
Abstract
BACKGROUND: Iranian women, many of whom live in small cities, have limited access to mammography and clinical breast examinations. Thus, breast self examination (BSE) becomes an important and necessary approach to detecting this disease in its early stages in order to limit its resultant morbidity and mortality. This study examined constructs arising from the Health Belief Model as predictors of breast self examination behavior in a sample of women living in Bandar Abbas, Iran. METHODS: This study was conducted in eight health centers located in Bandar Abbas, Iran. The sample consisted of 240 eligible women who were selected from referrals to the centers. The inclusion criteria were as follows: aged 30 years and over; and able to read and write Farsi. Women with breast cancer, who were pregnant, or breast feeding, were excluded from the study. Data were collected by using a self administered questionnaire which included demographic characteristics and Champion's Health Belief Model Scale. This instrument measures the concepts of disease susceptibility (3 items), seriousness (6 items), benefits (4 items), barriers (8 items) and self-efficacy (10 items). RESULTS: The subjects' mean age was 37.2 (SD = 6.1) years. Just under a third of the subjects (31.7%) had performed BSE in the past and 7.1% of them performed it at least monthly. Perceived benefits and perceived self-efficacy of the women who performed BSE were significantly higher compared with women who did not practice BSE (p < 0.03). Furthermore, perceived barriers were lower among those who had performed BSE (p < 0.001). Logistic regression analysis indicated that women who perceived fewer barriers (OR: 0.70, 95% CI: 0.63-0.77, p < 0.001) and had higher self-efficacy (OR: 1.08, 95% CI: 1.02-1.13, p = 0.003) were more likely to perform BSE (R2 = 0.52). CONCLUSION: Findings from this study indicated that perceived barriers and perceived self-efficacy could be predictors of BSE behavior among the sample of women. Therefore, BSE training programs that emphasize self-efficacy and address perceived barriers are recommended.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".