Abstract
Background
Breast self-examination (BSE) is a simple, low-cost method for promoting breast awareness and early detection of breast abnormalities, particularly among young women. However, lack of confidence and perceived barriers often limit regular BSE practice. Educational interventions that combine theoretical knowledge with hands-on training may enhance self-efficacy and support sustainable behavioral change.
Objective
This study aimed to compare the effects of theoretical education alone versus theoretical plus hands-on BSE training on breast cancer knowledge, health beliefs, and BSE practice among female university students.
Methods
This randomized controlled study was conducted among 40 female university students residing in university dormitories. Participants were stratified based on pretest scores and randomly assigned to either a theoretical education–only group (n = 20) or a theoretical plus hands-on training group (n = 20). The primary outcomes were breast cancer knowledge, health beliefs, and BSE practice. Breast cancer knowledge was assessed at baseline, immediately after training, and at a 3-month follow-up using the Breast Cancer Knowledge Test (BCKT). Health beliefs were assessed at baseline and at the 3-month follow-up using the Champion Health Belief Model Scale. BSE practice frequency and perceived barriers were also recorded. Repeated-measures and mixed-design ANOVA and chi-square tests were used for data analysis.
Results
Breast cancer knowledge increased significantly in all participants from pretest to posttest (p < 0.001) and remained significantly higher than baseline at the 3-month follow-up, although a slight decline was observed. No significant Time × Group interaction was found for knowledge scores.
In contrast, significant Time × Group interactions were observed for health motivation (p = 0.001), perceived barriers to BSE (p < 0.001), and self-efficacy (p = 0.005), all favoring the theoretical plus hands-on training group. Regular BSE practice increased from 0% at baseline to 60% at follow-up across the cohort, with a significantly greater increase in the hands-on training group compared with the theoretical-only group (75% vs. 45%, p = 0.038).
Conclusion
While theoretical education effectively improves breast cancer knowledge, the addition of hands-on BSE training is critical for reducing perceived barriers, enhancing self-efficacy, and promoting regular BSE practice. Incorporating hands-on training into breast health education programs may substantially improve behavioral outcomes among young women.
Keywords: Breast self-examination, Breast cancer education, Self-efficacy, Health belief model, University students, Health behavior change
Introduction
Breast cancer is the most common cancer among women both in Türkiye and worldwide and remains a major public health concern due to its high morbidity and mortality rates [1]. According to the International Agency for Research on Cancer (IARC), breast cancer was the most frequently diagnosed cancer and the leading cause of cancer-related deaths among women globally in 2022 [2]. In Türkiye, GLOBOCAN 2022 data report an incidence of 46.8 per 100,000 and a mortality rate of 12.5 per 100,000 among women [3]. Early detection plays a critical role in improving treatment outcomes and reducing mortality [4].
Increasing awareness and promoting early detection behaviors are among the most effective strategies in breast cancer control. In Türkiye, national screening guidelines recommend monthly breast self-examination (BSE) starting at age 20, annual clinical breast examinations, and biennial mammography between the ages of 40 and 69 [5, 6]. However, despite these recommendations, regular BSE practice remains low among Turkish women. The most frequently reported reasons include lack of knowledge, forgetfulness, and insufficient confidence in performing the examination correctly [7–11].
Educational interventions have been shown to improve knowledge and BSE practices; however, most existing programs primarily rely on theoretical instruction [10, 12]. The effectiveness of incorporating practical, hands-on training methods—particularly using breast models—remains insufficiently explored.
Breast cancer screening has been shown to reduce mortality by up to 33% through early detection; however, participation rates remain highly variable and often suboptimal across populations. Screening behavior is a complex health-related process influenced by a wide range of psychological, social, and sociodemographic factors. Evidence suggests that lower levels of self-efficacy, life satisfaction, and perceived control are associated with reduced participation in screening, while communication and recommendations from healthcare providers play a crucial role in improving screening uptake [13].
From a conceptual perspective, health behavior theories—particularly the Health Belief Model—propose that engagement in preventive behaviors such as breast self-examination is shaped not only by knowledge but also by constructs such as perceived susceptibility, perceived benefits, perceived barriers, and self-efficacy. However, previous research indicates that these models explain only a limited proportion of variance in screening behaviors and may not fully capture the complexity of real-world decision-making [14].
In addition, contemporary behavior change research emphasizes that knowledge-based interventions alone are insufficient to produce sustained behavioral change. Instead, effective interventions operate through specific mechanisms of action, such as enhancing self-efficacy and reducing perceived barriers, which mediate the relationship between educational strategies and behavioral outcomes.
Therefore, this study aims to compare the effects of theoretical education alone versus combined theoretical and hands-on training on breast cancer knowledge, health beliefs (including perceived barriers, benefits, and self-efficacy), and BSE practice behaviors among female university students. By explicitly examining these dependent variables, the study seeks to provide evidence on whether hands-on training contributes to more effective and sustainable behavior change.
Materials and methods
Study design
This study is a randomized controlled trial conducted at Sivas Cumhuriyet University between March and June 2023. It has a two-arm, parallel-group design and includes pretest, posttest, and 3-month follow-up assessments. The participants were female university students residing in university dormitories of the Credit and Dormitories Institution (KYK) who agreed to participate in the study. The follow-up period was 3 months. The study design is shown in Fig. 1. This study was an educational intervention and was therefore not registered in a clinical trial registry. The study was conducted and reported in accordance with the CONSORT 2010 statement for randomized controlled trials.
Fig. 1.
CONSORT flow diagram showing participant progression through baseline assessment, common theoretical education, randomization, intervention allocation, follow-up, and analysis
Participants and sample size
Inclusion criteria were being 18 years of age or older, being a student at Sivas Cumhuriyet University, living in a KYK dormitory, having no previous hands-on training on BSE, and providing written informed consent.
Exclusion criteria were having a diagnosis of breast cancer, refusing to provide consent, or withdrawing from the study during the study period.
The primary hypothesis of this study was that the interaction between the type of training (theoretical education only vs. theoretical plus hands-on training) and time of measurement (pretest, posttest, and 3-month follow-up) would result in a significant difference in students’ knowledge and attitude scores.
An a priori power analysis was conducted using G*Power version 3.1.9.4 for a mixed-design ANOVA with a 2 (group) × 3 (time) design. A medium effect size (f = 0.25) was selected based on Cohen’s recommendations for behavioral research. Assuming a significance level of α = 0.05, statistical power (1–β) of 0.90, a correlation among repeated measures of 0.50, and ε = 1, the required total sample size was calculated as 36 participants (18 per group). To account for an anticipated attrition rate of 10%, the final target sample size was set at 40 participants (20 per group).
Allocation
After participants were taken into the training room, the pretest was administered. All participants received the theoretical education together in the same session prior to group allocation. They received a standardized 45-minute theoretical education covering breast anatomy and physiology, common breast pathologies, breast cancer, and the principles of breast self-examination. Group assignment was performed only after completion of the theoretical training. Therefore, no interaction between groups occurred during the intervention phase, and the risk of contamination between groups was minimized.
Following the theoretical session, participants were randomly assigned to either the theoretical education–only group or the theoretical education plus hands-on training group. Stratification was performed based on pretest knowledge scores to ensure balanced baseline distribution between groups. Participants were stratified according to their pretest scores prior to randomization. To minimize selection bias, pretest data were entered into an anonymized dataset during the theoretical session and sent to a co-author who was not involved in participant recruitment or intervention delivery and was located in a different city. This independent researcher generated the random allocation sequence using the RAND() function in Microsoft Excel and assigned participants in a 1:1 ratio to the study groups. The allocation list was then returned to the study team and implemented after completion of the theoretical training. Due to the nature of the intervention, blinding of participants and instructors was not feasible; however, data analysis was conducted by an independent evaluator blinded to group allocation. Outcome data were analyzed using anonymized participant and group codes to further reduce potential bias.
The educational content and hands-on training were structured in accordance with the Turkish Ministry of Health’s national breast cancer screening recommendations [5]. These recommendations include monthly BSE after 20 years, annual clinical breast examination, and biennial mammography for women aged 40–69 years. Educational brochures obtained from the Ministry of Health were distributed to all participants after the training.
In the theoretical education–only group, the posttest was administered immediately after the theoretical session. In the other group, participants received a structured hands-on training session in small groups using 3B Scientific® L50 breast models. The hands-on training lasted approximately 60 min and included instructor demonstration, guided practice, and supervised individual performance, with immediate personalized feedback. The posttest was administered immediately after completion of the hands-on training.
Due to the nature of the intervention, blinding of participants and instructors was not feasible; however, data analysis was conducted by an independent evaluator blinded to group allocation.
Retention of knowledge, as well as the sustainability of health beliefs and attitudes over time, was assessed at the 3-month follow-up using the same measurement instruments administered at baseline.
Instruments
Data collection was carried out at three different time points:
Pre-test: The pretest was administered before the education to assess participants’ baseline knowledge and attitudes. This assessment included a demographic information form and attitude questions, the Comprehensive Breast Cancer Knowledge Test, and the Champion’s Health Belief Model Scale.
Post-test: The posttest was administered immediately after the theoretical education in the theoretical education only group and immediately after completion of the hands-on training in the other group to evaluate the short-term effects of the education. The Breast Cancer Knowledge Test was used at this stage.
Follow-up test: The follow-up test was conducted three months after the education to assess knowledge retention and the sustainability of attitude changes. This assessment included the attitude questions, the Comprehensive Breast Cancer Knowledge Test, and the Champion’s Health Belief Model Scale.
No personal identifying information, such as names or surnames, was collected from participants. To allow matching of results across assessments (pretest, posttest, and follow-up test), each participant was assigned a unique study code used only for the research process.
Regular BSE practice was operationally defined as performing breast self-examination at least once per month, in line with national recommendations.
The Breast Cancer Knowledge Test used in this study was originally developed by Stager in 1993 and later adapted into Turkish by Başak [15, 16]. The test consists of 20 items, each answered as “true” or “false.” Eight items are correct statements and twelve are incorrect statements. Total scores range from 0 to 20. In the Turkish validity study, the internal consistency of the scale was reported as Cronbach’s alpha = 0.71.
The Champion’s Health Belief Model Scale was developed by Champion in 1984 and revised in 1993, 1997, and 1999. The Turkish validity and reliability study was conducted by Gözüm and Aydın in 2004 [17, 18]. The scale consists of 52 items and 8 subscales, scored using a 5-point Likert scale. Each subscale can be scored independently. Since the participants in this study were not in the age group for mammography, the “Mammography Benefits” and “Mammography Barriers” subscales were excluded. Thus, a total of six subscales were used: Susceptibility, Severity, Health Motivation, Benefits of BSE, Barriers to BSE, and Self-efficacy for BSE.
Statistical analysis
Statistical analyses were performed using IBM SPSS Statistics (version 23). Descriptive statistics were presented as mean ± standard deviation for continuous variables and as frequencies and percentages for categorical variables. Normality of continuous variables was assessed using skewness and kurtosis values.
Baseline comparisons between the theoretical education–only group and the theoretical plus hands-on training group were performed using independent-samples t tests for continuous variables and chi-square tests for categorical variables. Effect sizes were reported as Cohen’s d for t tests and Cramer’s V for chi-square tests.
Changes in Breast Cancer Knowledge Test scores over time (pretest, posttest, and 3-month follow-up) were analyzed using repeated-measures analysis of variance (ANOVA). Bonferroni-adjusted post hoc tests were applied for pairwise comparisons. To examine whether changes over time differed between groups, a mixed-design repeated-measures ANOVA was performed, with time as the within-subject factor and group as the between-subject factor. Effect sizes were reported as partial eta squared (η²p).
For the Champion Health Belief Model Scale subscales, changes from pretest to follow-up were analyzed using mixed-design repeated-measures ANOVA, with time as the within-subject factor and group as the between-subject factor. Main effects of time and Time × Group interaction effects were examined, and effect sizes were reported as partial eta squared.
Changes in BSE practice frequency and perceived barriers to BSE were analyzed using chi-square tests. All statistical analyses were conducted at a 95% confidence level, and a p value of < 0.05 was considered statistically significant.
Results
A total of 40 students participated in the study. The participants were allocated to the theoretical plus hands-on training group (n = 20) and the theoretical education–only group (n = 20). There were no statistically significant differences between the groups in terms of demographic characteristics (p > 0.05). The mean age was 21.50 ± 2.19 years in the theoretical education–only group and 21.05 ± 2.50 years in the theoretical plus hands-on training group, with no significant difference between groups (p = 0.550). There were no statistically significant differences between the groups with respect to year of university, faculty type, parental education level, family history of breast cancer, history of cancer in close relatives, or baseline frequency of breast self-examination practice (all p > 0.05). The demographic characteristics of the participants are presented in Table 1.
Table 1.
Baseline demographic characteristics of participants by study groups
| N = 40 | Theoretical education–only group (n = 20) | Theoretical + hands-on training group (n = 20) | Test | p | Effect Size |
|---|---|---|---|---|---|
| Age | 21.50 ± 2.19 | 21.05 ± 2.50 | t = 0.61 | 0.550 | d = 0.19 |
| Year of university | |||||
| First | 6 (30.0%) | 10 (50.0%) | χ² = 1.73 | 0.630 | V = 0.21 |
| Second | 7 (35.0%) | 5 (25.0%) | |||
| Third | 6 (30.0%) | 4 (20.0%) | |||
| Fourth | 1 (5.0%) | 1 (5.0%) | |||
| Faculty | |||||
| Health-related | 8 (40.0%) | 6 (30.0%) | χ² = 0.44 | 0.741 | V = 0.11 |
| Non-health | 12 (60.0%) | 14 (70.0%) | |||
| Mother’s education level | |||||
| Primary school | 14 (70.0%) | 13 (65.0%) | χ² = 2.86 | 0.267 | V = 0.14 |
| High school | 4 (20.0%) | 7 (35.0%) | |||
| University | 2 (10.0%) | 0 (0.0%) | |||
| Father’s education level | |||||
| Primary school | 8 (40.0%) | 5 (25.0%) | χ² = 2.58 | 0.270 | V = 0.25 |
| High school | 8 (40.0%) | 13 (65.0%) | |||
| University | 4 (20.0%) | 2 (10.0%) | |||
| Family history of breast cancer | |||||
| Yes | 4 (20.0%) | 4 (20.0%) | χ² = 0.00 | 1.000 | V = 0.00 |
| No | 16 (80.0%) | 16 (80.0%) | |||
| Frequency of performing BSE | |||||
| Never | 16 (80.0%) | 16 (80.0%) | χ² = 0.00 | 1.000 | V = 0.00 |
| Occasionally | 4 (20.0%) | 4 (20.0%) | |||
| Regularly | 0 (0%) | 0 (0%) | |||
BSE breast self-examination. Values are presented as mean ± SD or as n (%). Effect sizes were reported as Cohen’s d for t-tests and Cramer’s V for chi-square tests
The internal consistency of the measurement tools in the current sample was acceptable. The Cronbach’s alpha coefficient for the Breast Cancer Knowledge Test was α = 0.701. For the Champion’s Health Belief Model Scale, Cronbach’s alpha values for the subscales were as follows: susceptibility (α = 0.610), severity (α = 0.832), health motivation (α = 0.825), benefits of BSE (α = 0.675), barriers to BSE (α = 0.872), and self-efficacy (α = 0.862).
A repeated measures ANOVA revealed a significant effect of time on Breast Cancer Knowledge Test scores of all participants, F(2, 78) = 146.57, p < 0.001, partial η² = 0.79, indicating a large effect size. The mean pre-test score was 10.45 ± 2.50, the mean post-test score was 16.55 ± 2.12, and the mean follow-up test score was 14.00 ± 2.80. Pairwise post-hoc analyses using Bonferroni adjustment indicated that post-test scores were significantly higher than pre-test scores (mean difference = − 6.10, p < 0.001), and follow-up scores also remained significantly higher than pre-test (mean difference = − 3.55, p < 0.001). However, post-test scores were significantly higher than follow-up scores (mean difference = 2.55, p < 0.001), suggesting some decline in knowledge retention over time, although knowledge levels at follow-up remained well above baseline.
As shown in Table 2, the mixed repeated-measures ANOVA revealed no statistically significant Time × Group interaction (F(2, 76) = 1.34, p = 0.267, η²p = 0.034), indicating that the pattern of change across measurement times did not differ significantly between the groups.
Table 2.
Descriptive statistics of Breast Cancer Knowledge Test scores by group and results of mixed repeated-measures ANOVA (Time × Group interaction)
| N = 40 | Theoretical education–only group (n = 20) | Theoretical + hands-on training group (n = 20) | Time × Group (interaction) | ||
|---|---|---|---|---|---|
| F (df1, df2) | p | Partial η² | |||
| Pre-test | 10.10 ± 2.31 | 10.75 ± 2.15 | 1.34 (2, 76) | 0.267 | 0.034 |
| Post-test | 16.20 ± 2.17 | 16.90 ± 2.08 | |||
| Follow-up test | 13.15 ± 2.98 | 14.85 ± 2.39 | |||
Values are presented as Mean ± SD. Effect sizes are reported as partial η²
The subscales of the Champion Health Belief Model Scale were analyzed to examine changes over time (from pretest to follow-up) in the theoretical education–only group and the theoretical plus hands-on training group. Health motivation showed a significant Time × Group interaction (p = 0.001), with motivation increasing in the theoretical plus hands-on training group while showing a slight decrease in the theoretical education–only group. Perceived benefits of BSE increased significantly over time (p < 0.001), with no significant group interaction. Perceived barriers to BSE demonstrated both a significant main effect of time (p = 0.001) and a significant Time × Group interaction (p < 0.001), indicating a greater reduction in perceived barriers in the theoretical plus hands-on training group. Self-efficacy also showed a strong main effect of time (p < 0.001) and a significant interaction effect (p = 0.005), with a greater increase observed in the theoretical plus hands-on training group compared with the theoretical education–only group. Detailed descriptive statistics and mixed ANOVA results are presented in Table 3.
Table 3.
Descriptive statistics of Champion Health Belief Model Scale subscales by group and results of mixed repeated-measures ANOVA
| N = 40 | Theoretical education–only group (n = 20) | Theoretical + hands-on training group (n = 20) | Time | Time × Group (interaction) | ||||
|---|---|---|---|---|---|---|---|---|
| F (1, 38) | p | Partial η² | F (1, 38) | p | Partial η² | |||
| Perceived Susceptibility | ||||||||
| Pre-test | 8.25 ± 1.02 | 8.35 ± 1.56 | 2.988 | 0.092 | 0.073 | 0.49 | 0.486 | 0.013 |
| Follow-up test | 8.65 ± 1.84 | 9.30 ± 2.29 | ||||||
| Perceived Seriousness | ||||||||
| Pre-test | 18.40 ± 5.24 | 21.40 ± 5.63 | 0.059 | 0.809 | 0.002 | 0.59 | 0.188 | 0.045 |
| Follow-up test | 19.30 ± 3.79 | 20.10 ± 6.55 | ||||||
| Health Motivation | ||||||||
| Pre-test | 21.60 ± 2.03 | 20.60 ± 3.10 | 1.436 | 0.238 | 0.036 | 12.928 | 0.001 | 0.254 |
| Follow-up test | 20.65 ± 2.60 | 22.50 ± 1.96 | ||||||
| Perceived Benefits of BSE | ||||||||
| Pre-test | 15.45 ± 1.90 | 15.25 ± 2.19 | 34.273 | < 0.001 | 0.474 | 0.011 | 0.916 | 0.000 |
| Follow-up test | 18.15 ± 2.30 | 18.05 ± 2.03 | ||||||
| Perceived Barriers to BSE | ||||||||
| Pre-test | 16.00 ± 5.25 | 16.60 ± 4.27 | 14.035 | 0.001 | 0.270 | 19.891 | < 0.001 | 0.344 |
| Follow-up test | 16.20 ± 4.85 | 14.30 ± 4.52 | ||||||
| Self-Efficacy | ||||||||
| Pre-test | 23.65 ± 6.02 | 26.85 ± 8.06 | 70.440 | < 0.001 | 0.650 | 9.085 | 0.005 | 0.193 |
| Follow-up test | 31.10 ± 5.55 | 42.65 ± 6.43 | ||||||
BSE breast self-examination. Values are presented as Mean ± SD. Effect sizes are reported as partial η²
Before the educational intervention, 80% of the students (n = 32) reported that they had never performed BSE, while 20% (n = 8) stated that they performed it irregularly or rarely. After the educational interventions, the proportion of students who reported never performing BSE decreased to 17.5% (n = 7) across the entire cohort. Overall, 60% of the participants (n = 24) reported performing BSE regularly, whereas 22.5% (n = 9) indicated that they performed it irregularly or rarely.
When changes in BSE practice frequency were evaluated by group, 55% of participants in the theoretical education–only group (n = 11) and 95% of those in the theoretical plus hands-on training group (n = 19) reported performing BSE more frequently compared with the pre-education period (p = 0.004).
When the barriers to students’ BSE practices were questioned, the responses were categorized as “I do not think it will happen to me” and “I do not feel confident in my ability to perform BSE” Accordingly, Table 4 presents the frequencies of perceived barriers before and after the education, stratified by groups.
Table 4.
Distribution of perceived barriers to breast self-examination practice at baseline and 3-month follow-up by study groups
| Theoretical education–only group (n = 20) | Theoretical + hands-on training group (n = 20) |
p | |
|---|---|---|---|
| Baseline | |||
| Regular BSE practice | 0 (%0) | 0 (%0) | 0.172 |
| I do not think it will happen to me | 12 (%60) | 8 (%40) | |
| I do not feel confident in my ability to perform BSE | 8 (%40) | 12 (%60) | |
| 3 Months Follow-up | |||
| Regular BSE practice | 9 (%45) | 15 (%75) | 0.038 |
| I do not think it will happen to me | 2 (%10) | 3 (%15) | |
| I do not feel confident in my ability to perform BSE | 9 (%45) | 2 (%10) | |
BSE breast self-examination. Values are presented as n (%). p values were calculated using the chi-square test
Discussion
In Türkiye, the Ministry of Health recommends that women perform breast self-examination monthly, undergo a clinical breast examination annually, and have mammography screening every two years for women aged 40–69 [6]. Therefore, this study aimed to evaluate the effects of theoretical and hands-on breast self-examination education on knowledge levels and health beliefs among young female university students.
According to the findings of this study, Breast Cancer Knowledge Test scores increased significantly from pretest to posttest among all participants. Although a slight decline was observed at the 3-month follow-up, scores remained significantly higher than baseline levels. No significant difference was found between the groups in terms of changes in knowledge over time. However, within the Health Belief Model Scale, the group that received hands-on training in addition to theoretical education showed a significant increase in health motivation scores and a significant decrease in perceived barriers to BSE at the 3-month follow-up. Although self-efficacy scores increased in both groups, the increase was more pronounced in the group that received hands-on training. Similarly, BSE practice frequency increased in both groups compared with baseline, with a relatively greater increase observed in the group that received hands-on training.
WHO does not recommend BSE as a screening method but rather as a tool to promote awareness and personal empowerment among women at risk [19]. Some studies have reported that routine BSE increases the detection of benign breast conditions and biopsy rates without significantly reducing breast cancer–related mortality [20, 21]. Nevertheless, breast cancer remains the most common cancer worldwide and is a leading cause of cancer-related mortality among women, disproportionately affecting those in low- and middle-income countries. While five-year survival rates exceed 90% in high-income countries, they are approximately 66% in India and around 40% in South Africa. According to the WHO Global Breast Cancer Initiative report, these disparities are largely attributable to the lack of organized screening programs, delays in diagnosis, and limited access to basic treatment [22]. The recommendations of the Turkish Ministry of Health emphasize increasing women’s breast awareness, improving general knowledge about breast health, and educating women about the benefits and limitations of BSE, while encouraging prompt medical consultation in the presence of any breast abnormality [6]. In the present study, a large proportion of participants (80%) reported never performing BSE at baseline; following the educational intervention, this proportion decreased markedly to 17.5%. This pattern is in line with current recommendations emphasizing breast awareness and suggests that educational interventions may play a role in improving BSE-related behaviors.
At baseline, barriers to performing BSE were equally distributed, with 50% of participants reporting low perceived risk “I do not think it will happen to me” and 50% reporting low confidence in their ability to perform BSE. At the 3-month follow-up, distinct patterns emerged between the two educational approaches. In the theoretical education–only group, 45% of participants reported performing regular BSE; however, low self-efficacy remained common (45%), whereas low perceived risk markedly decreased (10%). In contrast, the theoretical plus hands-on training group demonstrated a higher rate of regular BSE practice (75%), accompanied by a reduction in low self-efficacy (10%), while low perceived risk remained low (15%). These findings suggest that while theoretical education may improve risk perception, the addition of hands-on training may contribute to improvements in self-efficacy and may support BSE practice. Also these results are consistent with previous studies from different cultural settings. In a study conducted among Korean women, 88.0% of participants reported being aware of breast self-examination. However, the most common sources of information were mass media, such as television, radio, and newspapers, while recommendations from healthcare professionals accounted for only 17.2%. Regular and irregular BSE practice rates were reported as 13.2% and 16.1%, respectively, and the most frequently cited reason for not performing BSE was lack of knowledge about how to perform the examination (31.7%) [23]. These findings are consistent with the present study, where lack of knowledge and low confidence were identified as key barriers, suggesting that educational interventions may help address this gap.
In a cross-sectional study conducted among Iranian women, barriers to breast self-examination, as well as knowledge and practice related to BSE, were investigated. The main barriers to performing BSE were reported as fear of detecting a breast lump (91.7%), lack of knowledge about how to perform BSE (90.4%), and insufficient education provided by healthcare professionals (89.6%) [24]. In the present study, lack of confidence in how to perform BSE was the most frequently reported barrier, followed by low perceived risk (“I do not think it will happen to me”). The differences observed between these two studies, conducted in countries with similar geographical and cultural characteristics, may be attributed to differences in the age profiles of the study populations. While the mean age of participants in the Iranian study was 42 years, the present study was conducted among young female university students with a mean age of 21 years. This age difference may influence both perceived risk and perceived barriers related to BSE practice. These results highlight the importance of tailoring educational interventions to the specific characteristics of the target population, particularly in younger women.
Scores on the perceived barriers to BSE subscale of the Champion Health Belief Model Scale decreased significantly in the group that received hands-on training. In parallel, BSE self-efficacy scores increased significantly in the same group. Although knowledge scores increased similarly in both groups compared with baseline, the reduction in perceived barriers to practice and the increase in self-efficacy observed in the hands-on training group may be considered key factors underlying the greater increase in BSE practice frequency in this group.
In a descriptive study conducted in Türkiye by Nahcivan and Seçginli, women who reported greater confidence in their ability to perform BSE, had health insurance, and possessed knowledge about breast cancer were more likely to perform BSE [25]. Similarly, a quasi-experimental study conducted in Bangladesh demonstrated that an educational intervention on breast cancer and BSE among female university students resulted in significant short-term improvements in both knowledge levels and BSE practices. In that study, knowledge related to breast cancer symptoms, risk factors, prevention, and screening increased significantly after the intervention, accompanied by higher rates of BSE practice. These findings are consistent with the results of the present study, in which a reduction in perceived barriers and an increase in self-efficacy following hands-on training were associated with increased frequency of BSE practice [26]. These findings suggest a potential link between self-efficacy, perceived barriers, and BSE practice in the context of educational interventions.
A hands-on educational intervention was implemented to support behavioral change in breast self-examination practice, in this study. Previous studies have demonstrated that educational interventions grounded in behavioral theories are effective in promoting BSE-related behaviors. Cheraghalizadeh et al. reported that both face-to-face and virtual education programs based on the Theory of Planned Behavior led to significant improvements in BSE practice and related theoretical constructs at one and three months after the intervention among Iranian women. In addition, early post-intervention knowledge levels were significantly associated with subsequent BSE practice, suggesting that initial learning plays a key role in sustaining behavior change. Similar findings have been reported for virtual education, where early gains in knowledge and practice were strongly correlated with outcomes observed at later follow-up periods [27].
Educational interventions that combine theoretical and hands-on training components may support the translation of knowledge into behavior. In another quasi-experimental study conducted in Iran, a four-week virtual education program delivered via messaging applications improved knowledge scores in both intervention and control groups; however, no significant differences were observed between groups, leading the authors to conclude that virtual education alone may be insufficient to enhance all dimensions of health-related skills. Nevertheless, the increase observed in both groups may be attributed to the high sociocultural background of the study population and increased self-directed information seeking among participants aware of being part of a research study [28]. Consistent with these findings, knowledge scores increased significantly in both groups in the present study following theoretical education. However, as reported in previous studies, lack of self-confidence remains a major barrier to translating knowledge into regular BSE practice. The hands-on skills training implemented in this study effectively addressed this barrier and was associated with a greater increase in BSE practice frequency, highlighting the potential role of hands-on training in supporting sustained behavioral change.
Limitation
This study has several limitations. First, the follow-up period was limited to three months, which represents a short- to medium-term evaluation. Longer follow-up periods, preferably six months or more, are required to determine whether a health behavior has been sustained and integrated into daily routines [29, 30]. Therefore, the findings of this study reflect short- to medium-term effects.
Second, the study was conducted among young female university students, which limits the generalizability of the findings to women of different age groups or sociocultural backgrounds. In particular, perceived risk and health-related behaviors may vary with age and life experience.
Third, the frequency of breast self-examination practice and perceived barriers were assessed using self-reported measures. This may have introduced social desirability bias or recall bias.
Fourth, there was a difference in post-test timing between the groups, as the intervention group completed the assessment after an additional hands-on training session. This may have introduced a timing-related bias, particularly for knowledge outcomes, and should be considered when interpreting intergroup comparisons. In addition, the unequal nature of the intervention and the lack of blinding of participants and instructors may have influenced participants’ responses and introduced potential bias, particularly in self-reported outcomes. Therefore, post-test comparisons between groups should be interpreted with caution.
Finally, the study was conducted at a single center with a relatively small sample size. Future studies with larger and multicenter samples are needed to enhance the generalizability of the findings.
Acknowledgements
The authors thank all students who participated in this study. The authors used ChatGPT (OpenAI) for language editing and grammatical improvement of the manuscript. The tool was not used for data analysis, study design, interpretation of results, or decision-making. All content was reviewed and approved by the authors, who take full responsibility for the manuscript.
Authors’ contributions
E.A. conceived and designed the study, supervised the research process, contributed to the interpretation of results, and drafted and critically revised the manuscript. T.E.A. and A.T.B. contributed to data collection, implementation of the educational intervention, and data entry. Ö.K.O., who was not involved in the intervention process and was external to the study institution, performed the blinded statistical analysis and contributed to the interpretation of the findings. N.K. provided methodological guidance and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript and agree to be accountable for all aspects of the work.
Funding
This study was supported by the TÜBİTAK 2209-A University Students Research Projects Support Program (1919B012215001). Preliminary findings of this study were presented as an abstract at the 21st National Family Medicine Research Days Congress (Online), held on May 2–6, 2023.
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Non-Interventional Clinical Research Ethics Committee of Sivas Cumhuriyet University (Approval No: 2023-01/11; Date: January 18, 2023). Written informed consent was obtained from all participants. Permission for the use of the Turkish versions of the scales was obtained from the original authors via email.
Consent publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.