Determinants of mammography screening uptake among women attending family health centers in Ankara, Türkiye: a cross-sectional study

Abstract

Objective

This study aimed to assess sociodemographic characteristics, health-seeking behaviors, and breast cancer screening beliefs among women aged 18–69 years attending Family Health Centers (FHCs) in Ankara, Türkiye, and to determine predictors of participation in mammography screening. It is design as a descriptive, cross-sectional study.

Methods

Between April 2024 and January 2025, data were collected from 718 women using a sociodemographic questionnaire and the Turkish-adapted Breast Cancer Screening Beliefs Scale (originally developed by Kwok et al., validated by Türkoğlu et al.). Descriptive analyses, Chi-square tests, and binary logistic regression were performed with IBM SPSS 25.0. Variables with p < 0.20 in univariate analyses were entered into multivariate modeling, and statistical significance was defined as p < 0.05.

Results

Statistically significant differences were found between age groups in terms of marital status, education level, housing situation, presence of chronic disease, general health perception, and history of non-breast cancer screening (p < 0.001). According to the logistic regression analysis, women who are aware of screening programs are 8.50 times more likely to have a mammogram, those who have undergone non-breast cancer screening are 5.52 times more likely, those with chronic diseases are 1.98 times more likely, and those who describe their health perception as “good/very good” are 1.90 times more likely. (Nagelkerke R² = 0.465).

Conclusion

Mammography participation is influenced by both structural and personal determinants. Enhancing awareness, strengthening primary-care education, and addressing financial barriers could substantially improve screening uptake and facilitate earlier breast cancer diagnosis among Turkish women.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-026-15334-z.

Introduction

Cancer is one of the leading causes of death in every country in the world and one of the biggest obstacles to increasing life expectancy. According to 2020 data, 2.3 million new cases and 685,000 deaths were reported worldwide due to cancer [1]. Breast cancer patients account for 36% of all patients receiving oncology treatment. The incidence of breast cancer is increasing worldwide, but it is most common in industrialized countries [2]. The incidence and mortality rates of breast cancer have increased over the past thirty years [3]. In Türkiye, the incidence of breast cancer is also rapidly increasing, reaching 43.4 per 100,000 women [4].

Early detection and screening programs are critical in reducing mortality in the fight against breast cancer. Methods such as mammography, clinical breast examination, and breast self-examination are among the screening strategies recommended in national and international guidelines [5].For many years, self-examination of the breasts or clinical breast examination by a doctor or nurse has been recommended as screening methods to detect breast cancer in its early stages, starting at age 20 and done monthly [6].Mammographic screening is considered the gold standard screening method and reduces mortality by 23% [7]. Most guidelines recommend annual or biennial mammography screening for average-risk populations aged 40 to 74. For high-risk populations, early annual mammography or annual MRI screening is recommended [8].

Individual and societal factors influencing women’s participation in screening include their roles within the family, their knowledge and awareness of breast cancer and screening, fear of cancer, anxiety about mammography, need for spousal/family support, and concerns about privacy [9]. Positive health beliefs, having private health insurance, having undergone cervical cancer screening, and having motivation, are significantly associated with higher participation rates in breast cancer screening [10]. In addition, a family history of breast cancer, the presence of chronic diseases, and the proportion of healthcare expenditures in the budget also shape screening decisions [11]. According to a study conducted in Malaysia, health beliefs such as health motivation for breast cancer screening, perceived benefit of mammography, perceived barriers to mammography, readiness for mammography, and action cues for mammography were found to be diminished by undergoing mammography [12].

Breast cancer screening beliefs and mammography compliance are structurally shaped by collective expectations stemming from deep-seated cultural norms, beyond individual attitudes [13]. Theoretical frameworks such as the Health Belief Model offer a critical foundation for explaining how these cultural values structure an individual’s perceived susceptibility and self-efficacy toward screening behavior [14].

Awareness of breast cancer screening is not exclusive to women aged 40 and over; it is also prevalent among younger adults. A study conducted in Canada included 661 women under the age of 40 who visited family health centers; it was determined that 50% of these women underwent breast examinations by physicians. Although this age group is not included in cancer screening programs, it was observed that younger age groups perform self-breast examinations [15].

In Türkiye, mammography for breast cancer screening is performed at Cancer Early Detection, Screening and Education Centers (KETEM). Cancer screening, counseling and education activities are carried out taking into account the size and equipment of the centers [16]. According to a study conducted in family health centers in Turkey, it has been suggested that overcoming barriers to breast cancer screening – defined as fear of cancer, anxiety about pain, lack of information, difficulty accessing hospitals, and time constraints – can be achieved through one-on-one training, motivation, and access to KETEM (Cancer Early Detection and Screening Centers) at family health centers [17].

A study conducted in Turkey, using KETEM centres (Cancer Early Detection and Screening Centres) found that women who were invited to KETEM but did not attend were less likely to engage with the healthcare system than those who participated in the screening. In other words, even if women know that screening is free, their participation in screening programs decreases if the system does not actively engage them [18].

Family Health Centers, which provide primary healthcare services, are an important point of contact for women regarding their health-related questions. Assessing the healthcare utilization behaviors of women visiting Family Health Centers and their beliefs about breast cancer screening plays a critical role in strengthening community-based early detection programs [19].

The aim of this study is to evaluate the sociodemographic characteristics, healthcare utilization behaviors, and beliefs about breast cancer screening of women aged 18–69 who visit primary healthcare centers.

Methods

Study design and sampling

The population of the above cross-sectional descriptive study was women from 18 to 69 years who submitted an application to the chosen Family Health Centers of the Etimesgut, Gölbaşı, Sincan, and Yenimahalle districts in Ankara Province between January 21 and 24, 2025. Population figures of the said districts and the average annual number of primary healthcare visits per capita provided within the Turkish Ministry of Health’s Health Statistics Yearbook were utilized in order to estimate the number of weekly primary care applications per district.

The sample size needed was calculated using EpiInfo software (Epi Info™ (Version 7.2.5.0). At a 95% confidence level, α = 0.05, margin of error (d) of 3%, design effect of 1.0, and hypothesized prevalence of 50%, the sample size needed was 660 respondents. In anticipation of losing 10% data, surveys were planned to be collected from 726 individuals. Questionnaires were completed by 726 participants. No missing data imputation methods were utilized; instead, missing data were handled using listwise deletion. Following the exclusion of 8 incomplete responses, data from 718 women were analyzed in the final model (Fig. 1) Participants from a single Family Health Center were estimated by applying stratified sampling followed by simple random sampling. Women aged 18 to 69 who applied to selected Family Health Centers located in the Etimesgut, Gölbaşı, Sincan, and Yenimahalle districts and voluntarily agreed to complete the questionnaire were included in the study. Participants did not receive any financial or non-financial incentives for their participation in the study.

Fig. 1.

Flow chart of the sampling procedure

Data collection and ethics

This study was approved by the Gazi University Faculty of Medicine Ethics Committee [Approval No: 2025 − 612]. This study was conducted in accordance with the Declaration of Helsinki. The necessary permissions for data collection were obtained from the Ministry of Health. The study questionnaire was structured, self-applied, and known to be valid and reliable. The scale, originally called the “Breast Cancer Screening Beliefs Questionnaire,” was developed in English by Kwok et al. [20]. in 2010 to assess women’s beliefs regarding breast cancer screening. The validity and reliability study in Turkish was conducted by Türkoğlu et al. [21]. in 2018. Written and verbal informed consent was obtained from all participants after briefly explaining the purpose of the study and its contribution to women’s health. The selected Family Health Centers were visited, and all the participants completed the questionnaires themselves, which took approximately 15 min. The study was conducted by the principal researcher under the supervision of an academic supervisor. The questionnaires were administered in the style of personal interviews, and the data were subsequently uploaded to an online survey using Google Forms. To ensure data confidentiality, all digital data were stored on a secure, password-protected local computer accessible only to the personal laptop of corresponding author.

Socio-demographic characteristics questionnaire

This survey was specifically designed for the current study and has never been used elsewhere. It contained 28 questions relating to the age, gender, marital status, household population number of inhabitants in it, educational level, work status, type of occupation, adequacy of household income to meet needs, health insurance coverage status, whether or not there are chronic diseases, how well the subject feels, and what portion of the household budget is used for health care costs.

In the questionnaire’s first part, participants were asked a series of questions to ascertain their history and behaviors of, and exposure to, breast cancer and other cancer screenings. These included whether they had ever been diagnosed with breast cancer, whether they had any breast cancer history in their family, and whether they knew anyone in their close social network who had been diagnosed with breast cancer. They were also questioned whether they ever underwent breast cancer screening and, if so, whether they would be amenable to undergoing the screening again, and when the next due date would be. They were asked the same questions regarding any other cancer screenings, including whether they ever underwent any non-breast cancer screening and whether they would be willing to participate in these screenings again in the future. These items were constructed to measure both vicarious and direct exposure to breast cancer as well as attitudes toward future and past participation in cancer screening programs.

Kwok’s health belief model scale for breast cancer screening

The scale was originally developed in English by Kwok et al. [20]. in 2010 to assess women’s beliefs about breast cancer screening. Türkoğlu et al. [21]. conducted a validity and reliability study of the scale in Turkish in 2018. While the original form contains 20 items, the Turkish-adapted version consists of 13 items. All the items on the original scale are scored on a 5-point Likert scale ranging from “strongly agree” (1 point) to “strongly disagree” (5 points). The scale consists of three subdimensions: Attitudes toward health screening: items 1, 2, 3, and 4; Knowledge and perceptions about breast cancer: items 5, 6, 7, and 8; Barriers to mammography screening: items 9, 10, 11, 12, and 13.

In order to compute scores, the original scores are recoded as follows: 1 = 0, 2 = 25, 3 = 50, 4 = 75, and 5 = 100. After this conversion, the mean score of each subdimension is calculated by summing the item scores and dividing by the number of items. The scale has no reverse-coded items. In the internal consistency analyses of the scale, item-total score correlation values ranged from 0.37 to 0.90, and no items were extracted from the scale. The minimum score that can be achieved from the scale is 0, and the maximum score is 100. Mean subdimension scores of 65 or higher indicate more positive screening beliefs, greater knowledge, and fewer perceived barriers to mammography screening.

Statistics

Descriptive and inferential statistical analyses were carried out to determine the relationship between participants’ sociodemographic, health-related, and cancer awareness variables and their uptake of breast cancer screening (dependent variable: having undergone breast screening: yes/no). Categorical variables were expressed as frequency (n) and percentage (%). The association between the categorical variables and the status of breast cancer screening was established by using the Chi-square (χ²) test. Where required, Fisher’s exact test was used for cells with an expected frequency of fewer than five. A binary logistic regression was used to establish independent predictors of participation in breast cancer screening (dependent variable: having undergone breast screening: yes/no). Variables that were significant in the univariate analysis (p < 0.20) were entered into the multivariate model. The backward likelihood ratio (LR) method was employed to select the most parsimonious model. Independent variables that were entered into the model were: Age group (18–39 years as the reference), Presence of chronic illness (yes/no), Perception of general health (poor/very poor/fair vs. good/very good), Family history of breast cancer (yes/no), Whether having heard of breast cancer screening (yes/no), and Previous history of non-breast cancer screening (yes/no). The results were expressed as unstandardized regression coefficients (B), standard errors (S.E.), Wald χ² statistics, p-values, and odds ratios (OR) with 95% confidence intervals (CI). Nagelkerke R² statistic was applied to test the overall model fit. Statistical significance was at p < 0.05. All analyses were conducted using IBM SPSS Statistics for Windows, version 25.0 (IBM Corp., NY, USA).

Results

Of the 718 women included in the study, 46.2% (n = 332) were aged 18–39 and 53.8% (n = 386) were aged 40–69. The distribution of participants’ sociodemographic and health characteristics according to age groups is presented in Table 1. According to the analysis results, statistically significant differences were found between age groups in terms of marital status, education level, housing status, presence of chronic disease, general health perception, and history of non-breast cancer screening (p < 0.001). The 40–69 age group showed a higher rate of being married, owning a home, and having a chronic disease. In contrast, awareness of the national screening program was similar and statistically indistinguishable between the 18–39 (94.9%) and 40–69 (94.0%) age groups (p = 0.745).

Table 1.

Distribution of participants’ sociodemographic and health characteristics by age groups (N = 718)

Variable	Total (N = 718) n (%)	18–39Age (n = 332) n (%)	40–69Age (n = 386) n (%)	p
Marital status				< 0.001
Married	473 (65.9)	159 (47.9)	314 (81.3)
Single / Divorced / Widowed	245 (34.1)	173 (52.1)	72 (18.7)
Education Level				< 0.001
High school and above	547 (76.2)	320 (96.4)	227 (58.8)
Below high school	171 (23.8)	12 (3.6)	159 (41.2)
Housing Situation				< 0.001
Owner	386 (53.8)	136 (41.0)	250 (64.8)
Tenant / Other	332 (46.2)	196 (59.0)	136 (35.2)
Chronic Disease				< 0.001
Exist	355 (49.4)	95 (28.6)	260 (67.4)
None	363 (50.6)	237 (71.4)	126 (32.6)
General Perception of Health				< 0.001
Good / Very good	447 (62.3)	262 (78.9)	185 (47.9)
Poor / Average / Weak	271 (37.7)	70 (21.1)	201 (52.1)
Screening Program Awareness				0.745
Heard/Knows	678 (94.4)	315 (94.9)	363 (94.0)
Didn’t Hear/Doesn’t Know	40 (5.6)	17 (5.1)	23 (6.0)
Non-Breast Cancer Screening				< 0.001
Done	222 (30.9)	69 (20.8)	153 (39.6)
None	496 (69.1)	263 (79.2)	233 (60.4)

Table 2 compares the mean subscale and total scores of the Breast Cancer Screening Beliefs Scale (BCSBQ) according to age groups. The analysis revealed no statistically significant differences between age groups in terms of attitudes towards health screening (F1), knowledge about breast cancer (F2), and barriers to mammography screening (F3) (p > 0.05). The mean total scale score was 48.14 ± 7.17 in the 18–39 age group and 48.02 ± 7.24 in the 40–69 age group (p = 0.826).

Table 2.

Relationship of breast cancer screening belief scale scores by age groups (N = 718)

Scale Sub-Dimensions	18–39 Age (n = 332) (Med ± SS)	40–69 Age (n = 386) (Med ± SS)	p
Attitudes toward health screening	11.58 ± 2.55	11.64 ± 2.50	0.738
Information about breast cancer	15.89 ± 3.47	15.95 ± 3.27	0.807
Barriers to mammography screening	20.66 ± 3.55	20.42 ± 3.74	0.374
Scale Total Score	48.14 ± 7.17	48.02 ± 7.24	0.826

Factors influencing screening behavior in women aged 40–69 years (n = 386) participating in routine mammography screening are presented in Table 3. In univariate analyses, awareness of the screening program, history of non-breast screening, general health perception, family history of breast cancer, housing status, and education level were found to be associated with mammography participation (p ≤ 0.05).

Table 3.

Analysis of factors predicting participation in mammography screening among women aged 40–69 (n = 386)

Variables and Categories	Scanning (+) (n = 242) n (%)/x̄±SD	Scanning (-) (n = 144) n (%)/x̄±SD	p (univariate)	Model 1 (Enter) aOR (%95 GA)	p (M1)	Model 2 (Backward) aOR (%95 GA)	p (M2)
Screening Program Awareness			< 0.001		0.001		< 0.001
Yes	238 (98.3)	125 (86.8)		7.75 (2.30–26.09)		8.50 (2.62–27.61)
No	4 (1.7)	19 (13.2)		1.00 (Ref)		1.00 (Ref)
Extramammary Screening			< 0.001		< 0.001		< 0.001
Yes	130 (53.7)	23 (16.0)		5.22 (3.05–8.92)		5.52 (3.25–9.36)
No	112 (46.3)	121 (84.0)		1.00 (Ref)		1.00 (Ref)
Chronic Disease			0.145		0.022		0.010
Yes	170 (70.2)	90 (62.5)		1.88 (1.10–3.23)		1.98 (1.17–3.34)
No	72 (29.8)	54 (37.5)		1.00 (Ref)		1.00 (Ref)
General Perception of Health			0.008		0.020		0.012
Good / Very Good	129 (53.3)	56 (38.9)		1.86 (1.10–3.13)		1.90 (1.15–3.13)
Poor / Average / Weak	113 (46.7)	88 (61.1)		1.00 (Ref)		1.00 (Ref)
Family History of Breast Cancer			0.012		0.032
Yes	69 (28.5)	24 (16.7)		1.91 (1.06–3.46)		-	-
No	173 (71.5)	120 (83.3)		1.00 (Ref)
Housing Situation			0.01		0.066
Owner	169 (69.8)	81 (56.2)		1.59 (0.97–2.59)		-	-
Tenant / Other	73 (30.2)	63 (43.8)		1.00 (Ref)
Education Level			0.05		0.976
High School and Above	152 (62.8)	75 (52.1)		0.99 (0.58–1.69)		-	-
Below High School	90 (37.2)	69 (47.9)		1.00 (Ref)
Employment Status			0.136		0.250
Working	81 (33.5)	37 (25.7)		1.38 (0.80–2.41)		-	-
Not working / Other	161 (66.5)	107 (74.3)		1.00 (Ref)
BCSBQ
Attitude Towards Health Screening	11.57 ± 2.52	11.77 ± 2.48	0.457	-	-	-	-
Breast Cancer Information	15.91 ± 3.32	16.02 ± 3.20	0.764	-	-	-	-
Mammography Barriers	20.32 ± 3.86	20.58 ± 3.53	0.514	-	-	-	-
Nagelkerke R2				0.288		0.266

Variables serving as potential confounders—specifically awareness of screening programs, history of non-breast screening, general perception of health, presence of chronic disease, family history of breast cancer, housing situation, education level, and employment status—that showed significance (p < 0.200) in the univariate analysis were included in the Model 1 (Enter) logistic regression analysis. Subsequently, in Model 2, obtained from the backward stepwise analysis, awareness of screening programs, history of non-breast screening, presence of chronic disease, and positive health perception were identified as the strongest independent predictors of mammography participation. According to the final model (Model 2); Women who are aware of screening programs are 8.50 times more likely to have a mammogram (aOR: 8.50; 95% CI: 2.62–27.61). Those who have undergone non-breast cancer screening are 5.52 times more likely to have a mammogram (aOR: 5.52; 95% CI: 3.25–9.36). Those with chronic diseases are 1.98 times more likely to have a mammogram (aOR: 1.98; 95% CI: 1.17–3.34),and those who describe their perceived health as ‘good/very good’ are 1.90 times more likely to have a mammogram (aOR: 1.90; 95% CI: 1.15–3.13).

The effect of BCSBQ scale sub-dimensions on screening behavior was tested in Model 1, but no statistically significant contribution was found (p > 0.05). The Nagelkerke R² value of the final model (Model 2) was calculated as 0.266.

Discussion

This study examined the relationship between mammography and breast examination awareness and related factors among women seeking primary health care.

This study found that individuals with higher levels of education were more likely to undergo mammography than those with lower levels of education. Similarly, a meta- analysis by Damiani et al. [22]. found a positive correlation between increasing levels of education and adherence to mammography screening. A study conducted on Bangladeshi women showed that women with 12 or more years of education were more likely to have knowledge about mammography and self-examination compared to those with lower levels of education [23]. This suggests that education plays a role in increasing women’s capacity to acquire health information, their level of understanding of risks, and their ability to communicate with health institutions.

The findings of this study show that individuals with good or better health perception participated more in mammography screening programs than those with moderate, poor, or very poor health perception. The findings of the study by Onyenemezu et al. [24]. which evaluated participation in colorectal cancer screening, were found to be similar to our findings; it was observed that individuals who described themselves as having good/very good health participated more in cancer screening. In this context, developing specific communication strategies for women with low general health perception, integrating counseling to improve health status perception and motivational approaches in breast cancer screening programs to be conducted in ASM’s may be an effective method to increase screening participation.

It has been observed that individuals who undergo other cancer screenings have a high level of participation in breast cancer screening programs. Specifically, in the 40 years and older age group, those who participated in other cancer screening programs were found to be 5.52 times more likely to participate in breast cancer screening programs compared to those who did not. According to a study conducted in France to evaluate participation in breast and cervical cancer screening, the main factor associated with more frequent participation in one or both cancer screenings is having recently undergone the other screening [25]. A study conducted in the United States was carried out by 90 primary care physicians and included 33,137 patients. Patients who underwent colorectal cancer screening were also found to have higher rates of breast cancer screening [26]. While this suggests that preventive health practices reinforce each other, these findings also indicate that multiple screening opportunities within the health system could increase awareness and participation in breast cancer screening.

This study found that women over 40 years of age were more likely to be married, own a home, and have a chronic illness compared to the group under 40. This situation generally represents a higher level of contact with the healthcare system, as described in the literature [27]. In this context, it is expected that individuals with chronic illnesses will visit healthcare facilities more frequently and have greater awareness of national screening programs [28]. However, the study’s findings showed no statistically significant difference between age groups in terms of awareness of the national screening program (KETEM). This raises the issue of the quality of contact with the health system. Although women over 40 visit the health system more frequently due to chronic illnesses, their visits are often limited to managing their existing chronic diseases [29]. Indeed, the literature emphasizes that unless physicians make screening recommendations for asymptomatic patients a part of routine examinations, the frequency of a patient’s contact with the system does not translate into awareness [30]. The younger age group’s access to information about national programs through digital literacy may be equalized with the older age group’s knowledge gained from physical contact with the system. This awareness match demonstrates that the messages of organized screening programs (KETEM) have a heterogeneous impact on all age groups, but do not provide a real behavioral advantage [19]. In conclusion, the increased burden of chronic diseases among women over 40, leading to more frequent contact with the health system, has not directly translated into increased screening awareness. This finding suggests that screening policies should focus not only on disseminating information but also on active clinical integration models that create age-specific awareness in every patient who interacts with the system.

In this study, when women under and over 40 were examined in two separate groups, no significant relationship was found between breast cancer screening belief scale scores and knowledge about breast cancer, attitudes towards health screening, and barriers to mammography screening. The lack of a significant difference between the two groups in terms of attitudes towards health screening indicates that women, regardless of age, have similar motivation regarding the necessity of screening and general health awareness. A systematic review emphasizes that education level and socioeconomic status are more decisive than age in influencing screening attitudes [31]. Another study in the literature, conducted on African women over 18 living in Australia, found no significant results when all age groups were evaluated for all three parameters [32]. Although similar results were obtained regarding screening beliefs across all age groups, it is predicted that the increase in screening participation with age does not correlate with belief, and that factors other than belief, such as chronic illness and home ownership, influence the behavioral action. This shows us that the primary determinant of screening behavior is not actually belief or education level, but rather the contact that can be established with the health system. Seeking healthcare due to a specific illness or having less socioeconomic concern can increase the financial resources available to the health system, thus increasing the likelihood of seeking screening. While financial capacity plays a significant role in individuals’ motivation to seek healthcare, in the Turkish context, providing breast cancer screenings as a completely free and accessible public service minimizes the restrictive effect of socioeconomic level as a financial barrier on screening behavior.

In this study, although no significant findings were found when comparing age groups with breast cancer screening belief scale scores according to the results of the analyses, a strong relationship was observed between breast cancer awareness and awareness of screening programs in women aged 40 and over. It was observed that knowing about the existence of a screening program increased participation in screening by 8.5 times in women aged 40 and over. This shows that women are more involved in the screening process when they are not only aware of the risks of the disease but also aware of the existence of institutional mechanisms to combat these risks. A study conducted in the United Arab Emirates showed that 63% of women who did not participate in a breast cancer screening program had never heard of it before, while approximately 80% of women who performed self-examinations and underwent mammography stated that this recommendation had been made by a healthcare provider previously [33]. A study conducted in Ethiopia on awareness of breast cancer screening among women showed that 35% of all women were aware of at least one screening program, and approximately 88% of those who were aware participated in the screening program [34]. It can be argued that awareness campaigns targeting the over-40 age group should focus not only on disease risk but also directly on the accessibility and ease of implementation of the screening program.

This study found that women aged 40 and over with a family history of breast cancer participated significantly more in screening programs compared to those without a family history. Similarly, a study in the literature involving 1039 first-degree relatives of women with a family history of breast cancer reported that, particularly among those aged 40–49, the likelihood of undergoing screening mammography was approximately 2.8 times higher compared to those without a family history [35]. Another study showed that women with a positive family history were more likely to have mammograms [36]. This can be explained by the fact that women with a first-degree relative diagnosed with breast cancer feel they are at higher risk and, due to perceived sensitivity, tend to adopt preventive health behaviors earlier.

This study found that women aged 40 and over who owned their homes had a higher participation rate in mammography screening programs, and this difference was statistically significant. Homeownership is also one of the structural barriers of this study. The literature also supports our findings. A study involving over 2.5 million American veterans evaluated colonoscopy and mammography screening rates between homeowners and non-homeowners. While 70% of homeowner veterans had mammograms, this figure was 63% for non-homeowner veterans [37]. This positive relationship between homeownership and screening compliance can be explained, from a social determinant perspective, by the fact that reduced financial stress can increase individuals’ ability to allocate funds for preventive health services.

This study found that women over 40 who perceived their health as good had a higher participation rate in breast cancer screening programs than those who perceived their health as poor. This finding is consistent with many studies in the literature. Rakowski et al. showed that women who perceived their health positively had higher rates of undergoing mammography [38]. Similarly, a comprehensive study conducted in 2004 found that subjective health perception was a significant predictor of participation in breast cancer screening, with women who rated their health status as poor benefiting less from screening programs [39]. These findings highlight the need to develop specific intervention strategies for women who perceive their health status as poor when planning breast cancer screening programs.

The finding that the primary determinant in breast cancer screening is contact with the healthcare system rather than individual beliefs necessitates a shift in focus from awareness training to structural system improvements. In this context, strengthening systemic conveniences such as presumed appointments in patient-provider communication and improving primary healthcare services stands out as the most effective policy change for behavioral alteration. To prove the causality of the current findings and maximize their reliability, a critical next step is to replicate the study with a longitudinal design to track the sustainable impact of system contact over time.

This article has several limitations. As the study is cross-sectional, it does not allow for establishing cause-and-effect relationships. Since the data is based on self-reporting, there is a possibility of misremembering. There is no documented and proven level of health. Since the study only included women who applied to ASMs, it is limited in terms of reflecting awareness in the general population. The survey included in the study gave limited space to the psychosocial, religious, and cultural aspects of the individuals, so it was not possible to examine the effect of such factors as independent variables on the study. A limitation of this study is that it did not assess participants’ family history of cancer, which may influence cancer risk perceptions and screening beliefs. The inclusion of a large group of 718 individuals in the study is important in terms of its generalizability to the population. The study collected information across a wide range of topics, including sociodemographic data, health perception, income level, and household health expenditures, thus enabling multidimensional analysis. The primary care-focused approach, being the most accessible and available part of healthcare services, is important in terms of accessibility to the population. The joint evaluation of variables such as education, income, marital status, and health insurance allows for multidimensional inferences related to screening behaviors. Questioning the individual, their family, and their close circle about their cancer history is also one of the strengths of our study in terms of assessing cancer awareness.

Conclusion

These data obtained indicate that strategies to increase breast cancer screening rates should focus on programs such as active in-system reminders and multiple screening packages. Family health center visits can be considered as screening opportunities, and patients can be informed about this. Service providers can offer multiple screening packages such as cervical, breast, and colon cancer. Health system follow-up modules can include reminder screens for relevant physicians and healthcare personnel for individuals with chronic diseases, tailored to their screening age.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

All authors contributed substantially to the work’s conception or design. Responsibilities include acquisition (FBT, SPÇ, and KNT), analysis (SPÇ, CB, and SÖ), or interpretation of data (all authors) for the work drafting (FBT and SPÇ)/revising (all authors) for intellectual content. Final approval of the version to be published (all authors): agreement to be accountable (all authors). FBT is responsible for the overall content as the guarantor.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Data availability

Data are available upon reasonable request.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was granted by the Gazi University Human Research Ethics Committee (approval no: 2025 − 612), and written informed consent was obtained from all individual participants included in the study.

Consent for publication

Informed consent was obtained from all participants for the publication of their individual details and accompanying images in this manuscript.

Patient and public involvement

Patients and/or the public were not involved in the design, conduct, reporting, or dissemination plans of this research.

Patient consent for publication

Not applicable.

Provenance and peer review

Not commissioned; externally peer reviewed.

Competing interests

The authors declare no competing interests.