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Background: Breast cancer (BC) is the most prevalent cancer among women. Teachers play a crucial role in promoting healthy behaviors, including breast cancer screening (BCS). This study aimed to assess the impact of an Health Belief Model (HBM)-based educational intervention on BCS uptake, knowledge, and beliefs among female Yemeni teachers in Klang Valley, Malaysia.
Methods: A cluster-randomized controlled trial was conducted with 180 participants from 12 schools, randomly assigned to intervention or control groups. The intervention group participated in a 90-minute educational session, with follow-up assessments at baseline, and at 1, 3, and 6 months' post-intervention, using validated Arabic questionnaires. Data analysis was performed using SPSS version 22.0, with Generalized Estimating Equations (GEE) applied to assess differences within and between groups over time. Statistical significance was set at P < 0.05.
Results: At baseline, there were no significant differences between groups. Post-intervention, the intervention group showed significantly higher rates of breast self-examination (BSE) and clinical breast examination (CBE) compared to the control group, with adjusted odds ratios (AOR) of 17.51 (CI: 8.22-37.29) for BSE and 2.75 (CI: 1.42-5.32) for CBE. Over six months, BSE performance in the intervention group increased, with AORs improving from 11.01 (CI: 5.05-24.04) to 18.55 (CI: 8.83-38.99). Similarly, CBE uptake rose from 1.60 (CI: 1.02-2.52) to 2.27 (CI: 1.44-3.58). Secondary outcomes revealed significant gains in knowledge and beliefs in the intervention group, including increased confidence in performing BSE and reduced perceived barriers.
Conclusions: The HBM-based educational intervention effectively enhanced BCS uptake, improved knowledge, and decreased barriers to BCS among Yemeni teachers in Malaysia, highlighting the potential of targeted educational programs to promote cancer screening behaviors in underserved populations.
Clinical Trial Registration: Retrospectively registered, ANZCTR (ACTRN12618000173291). Registered on February 02, 2018.
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http://dx.doi.org/10.1186/s12885-024-13214-5 | DOI Listing |
EBioMedicine
September 2025
Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, PR China; Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, PR China. Electronic address:
JMIR Cancer
September 2025
Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.
Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative.
View Article and Find Full Text PDFEpidemiol Serv Saude
September 2025
Universidade Estadual do Norte do Paraná, Programa de Pós-Graduação em Enfermagem em Atenção Primária à Saúde Bandeirantes, PR, Brazil.
Objectives: To analyze the temporal trend and identify spatial clusters of breast cancer mortality in Paraná state between 2012 and 2021.
Methods: This was a time series study, with spatial analysis of breast cancer mortality rates in the 399 municipalities of Paraná. Data were selected from the Mortality Information System.
Cien Saude Colet
August 2025
Faculdade de Medicina da Universidade Federal de Pelotas. Pelotas RS Brasil.
The objective of this study was to analyze the characteristics of avoidable mortality in the population aged five to 69 years living in the city of Pelotas/RS, comparing it with the rest of the state of Rio Grande do Sul, from 2000 to 2021. An ecological study was conducted analyzing avoidable mortality coefficients according to sex and age, from 2000 to 2021. The data source was the Mortality Information System, and the trend analysis was performed using Prais-Winsten regression, with standardization of coefficients.
View Article and Find Full Text PDFCien Saude Colet
August 2025
Programa de Pós-Graduação em Nutrição e Saúde, Universidade Estadual do Ceará. R. Betel 1958, Itaperi. 60714-230 Fortaleza CE Brasil.
This study aimed to evaluate mortality due to female breast cancer attributable to overweight and obesity and to estimate the number of preventable deaths with a reduction in the Body Mass Index in Brazil. An ecological study was carried out with investigation of information on overweight, obesity, sociodemographic characteristics based on a national survey carried out in 2013-14; breast cancer mortality rate in 2019 using the Online Atlas of Mortality and Relative Risk Meta-Analyses. The Potential Impact Fraction analysis was carried out, considering the following counterfactual scenarios related to the reduction in BMI: Scenario A - population contingent of women that make up the prevalence of overweight and obesity now composes the prevalence of eutrophy; Scenario B - population contingent of women that make up the prevalence of overweight starts to make up the prevalence of eutrophy; Scenario C - population contingent of women that make up the prevalence of obesity becomes part of the prevalence of overweight.
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