SynthesisInternational journal of environmental research and public health2021
A Model-Based Meta-Analysis of Willingness to Participate in Cancer Screening.
Synthesis in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Barriers and Facilitators to Participation in Health Screening: an Umbrella Review Across Conditions.Prevention science : the official journal of the Society for Prevention Research · 2022Pooled it
- Article
- The public's irrational use of antibiotics for upper respiratory tract infections: a cross-sectional study based on the health belief model.Scientific reports · 2025Observational
- Methylated Reprimo Cell-Free DNA as a Non-Invasive Biomarker for Gastric Cancer.International journal of molecular sciences · 2025Article
- Knowledge and attitudes toward human papillomavirus and cervical cancer prevention among women in the Asir Region, Saudi Arabia: a cross-sectional study.Frontiers in oncology · 2025Article
- Predictors of cancer screening behavior of the working population in China based on the information-motivation-behavioral skills model.Frontiers in public health · 2023Article
- A cross-sectional study on assessment of perceived threat to cervical cancer using health belief model among women in a slum area of Kolkata.Journal of education and health promotion · 2022Article
- Systematic Construction and Validation of an Immune-Related Gene-Based Model to Predict Prognosis for Ovarian Cancer.BioMed research international · 2022Article
- Willingness to Receive Periodic Health Examination Based on the Health Belief Model Among the Elderly in Rural China: A Cross-Sectional Study.Patient preference and adherence · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although early screening tests are beneficial for the detection and treatment of cancers, many people have failed to participate in screening tests. The present study aims to explore the theoretical underpinning of low participation in screening programs using the method of meta-analytic structural equation modeling. It was found that the health belief model is the most adopted theoretical framework. Moreover, the intended uptake of screening was positively predicted only by cues to action, health literacy, and perceived susceptibility. As a result, a health intention model, including the three significant variables, is proposed. The practical implications of the findings are that health communication campaigns should focus on enlightening and engaging the public through all necessary means to raise awareness and transfer knowledge in relation to screening procedures as well as cancers per se.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.