Effect of educational interventions on nutritional knowledge of cancer prevention based on health belief model: A systematic review
Bibliographic record
Abstract
This systematic review aimed to assess the impact of educational interventions on nutritional knowledge for cancer prevention using the health belief model. Comprehensive searches were conducted in international electronic databases, including Scopus, PubMed, and Web of Science, from their inception until June 16, 2024. Keywords derived from Medical Subject Headings such as "Nutrition Knowledge", "Education", "Health Belief Model", and "Cancer" were utilized. The quality of randomized controlled trials (RCTs) and quasi-experimental studies was assessed using the Joanna Briggs Institute's (JBI) critical assessment checklist. A total of 611 participants were enrolled in five studies, with 78.39% female and 76.76% in the intervention group. The mean age of participants was 42.12 years (SD=6.47). Of the included studies, one was an RCT, while the remaining four were quasi-experimental. Three studies included a control group, and four studies incorporated a follow-up. Regarding the assessment tools used, four studies employed researcher-developed questionnaires, and one study utilized the nutrition-related cancer prevention knowledge, attitude, and practice (NUTCANKAP) questionnaire for evaluating nutritional knowledge. The mean follow-up period was approximately 14 weeks, and the average duration of the intervention was 54 minutes. Across all studies, the interventions effectively increased nutritional knowledge of cancer prevention based on the health belief model. The findings indicated that education based on the health belief model effectively increased nutritional knowledge of cancer prevention. Health professionals like nurses can use this model to enhance nutritional knowledge. It is recommended that health managers and policymakers create environments that enable health professionals to employ educational strategies based on the health belief model, thereby improving nutritional knowledge.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".