DOST: A consolidated health behavior model that maps factors influencing cancer screening uptake

Abstract

Background

Cancer is a leading cause of death worldwide, particularly in low- and middle-income countries (LMICs), where preventive interventions like screening and vaccination face challenges due to limited resources. Despite the availability of user-friendly screening methods, uptake remains poor. Psychological theories are recommended to identify and address determinants of screening participation; however, existing models often focus on a limited range of domains and overlook critical belief-related factors needed to encourage screening uptake. A comprehensive, integrated model addressing these gaps could significantly improve the identification of barriers to screening.

Methods

This conceptual paper proposes a model that maps potential barriers to cancer screening uptake through the lens of beneficiaries. The ‘Determinants Of Screening upTake’ (DOST) model was systematically developed through a series of steps integrating three existing health behavior theories that have been successfully used previously to improve screening uptake: the Health Belief Model (HBM), the Theory of Planned Behavior (TPB), and the Theory of Care-Seeking Behavior (TCSB).

Results

The DOST model integrates dimensions represented in existing health behavior models, presenting a detailed map of potential barriers in real world, faced by beneficiaries of screening. These barriers are categorized systematically to enhance understanding and facilitate its use among non-experts in empirical research.

Conclusion

By integrating multiple models, the DOST model offers a comprehensive framework that combines theoretical robustness with practical guidelines. It highlights psychosocial barriers that influence screening attitudes, intentions, and uptake. The model can guide the assessment of screening determinants in populations and support the design of educational messages or interventions aimed at increasing screening uptake.

Text box 1. Contributions to the literature
• Bridging theory and practice: This study introduces a conceptual model that integrates behavioral theories into a comprehensive framework to explain barriers to cancer screening. It makes complex theoretical constructs accessible for practical use in empirical research.
• Identification of Root causes: The model identifies underlying reasons for the non-uptake of cancer screening. It serves as a foundation for creating survey tools that connect psychological theories with real-world barriers.
• Contextual insights: The research highlights the vast range of psychosocial barriers that are theoretically categorized, offering valuable insights into the prioritization of the modifiable ones. The model presented here allows universal applicability and contextual adaptability, crucial for tailoring tools and interventions to specific populations.
• Contribution to Cancer Screening Research: The DOST model (Determinants Of Screening upTake) was developed using cervical cancer screening as a reference, given its well-documented barriers and significant public health impact. We propose that the DOST model is adaptable to other cancer screening programs, including breast, colorectal cancer, and prostate cancer which offer similar challenges. However, its application requires careful validation to ensure construct validity in assessment tools. Ongoing research is currently testing this model in a multi-contextual study, including the development of a questionnaire and an educational tool designed around its framework. To prevent misapplication, we recommend awaiting the preliminary validated draft of these tools, which are undergoing testing to ensure they accurately capture the domains the model intends to measure.

Background

Cervical cancer is the fourth leading cause of cancer among women worldwide. In 2022, nearly 0.5 million women were diagnosed with this disease, and 0.3 million died from cervical cancer. However, early detection of human papillomavirus (HPV) and treatment of patients with precancerous lesions can prevent its progression to cancer. The World Health Organization (WHO) therefore recommends that women undergo tests to screen for precancerous lesions at least once if not regularly every five years [1]. The WHO also recommends specific strategies to improve screening and follow-up, such as the ‘screen and treat’ approach, which is tailored to the context of implementation, particularly in areas where issues related to geographical accessibility persist [2]. The ‘screen and treat’ approach involves immediate treatment following positive screening results to prevent disease progression, making it especially suitable for resource-constrained settings.

Despite these recommendations, the uptake of screening for cervical cancer remains low, particularly in low- and middle-income countries (LMICs), where the disease burden is significant [3]. This issue can partially be attributed to organizational limitations within the health system—in resource-poor settings—which pose substantial challenges to providing organized cervical cancer screening. Moreover, even when well-tested strategies are implemented, they do not always result in successful utilization of screening services because of barriers directly experienced by women. While ensuring the availability, affordability, and accessibility of screening services is critical, poor acceptability or utilization can lead to program failure. Therefore, it is crucial to identify and mitigate the barriers to enhancing women’s use of available screening services.

An individual’s decision to undergo screening, when screening is available, depends on various factors or determinants. These determinants vary by age, culture, time, geography, and physical, psychological, social, and spiritual conditions. Each of these domains includes factors that may either facilitate screening uptake or represent a barrier to uptake by the individuals or beneficiaries (i.e., individuals who are targeted for screening programs based on specific criteria such as age, risk factors, or potential benefits from early detection and preventive care). Because any of these factors could influence a woman’s decision to undergo screening, it is important to account for all of them. To that effect it is useful to utilize a model that captures all determinants and classifies them logically for easy application, thus capturing a large range of determinants. Yet, while numerous studies have used existing models to explore or address cervical screening uptake [4,5,6,7,8,9], no single model has emerged as one that is simplified for practical use and encompasses all potential reasons for the non-uptake of screening. The proposed DOST model, developed with cervical cancer screening as a reference, provides a comprehensive framework to identify barriers across individual, interpersonal, societal, and organizational levels, and is applicable in diverse screening contexts and populations.

Unveiling determinants of screening uptake– modifiable and nonmodifiable barriers

The socioecological model developed on Bronfenbrenner ‘Ecologic Systems Theory’ [10] provides a structured framework to provide an overview of various determinants of screening uptake by categorizing them across different levels of social interaction: individual, interpersonal, sociocultural, health system, and political. It allows us to differentiate between external factors that constitute the health system and political factors (those that exist outside of the individual or the beneficiary) and those that are related to beneficiaries themselves (Beneficiary: Individuals targeted by screening programs based on specific criteria such as age, risk factors, or potential benefits from early detection and preventive care).

Before exploring the reasons for the non-uptake of cancer screening, it is essential to recognize that each individual may face unique barriers and facilitators influencing their decision to engage in screening. Effectively addressing these issues requires categorizing and simplifying them to focus on those particularly susceptible to change, which could significantly improve ‘attitudes’ toward screening and eventually action, i.e., screening. Psychosocial barriers are crucial in this context, as they directly inform the decision-making process and utilization of screening services. These barriers are of particular interest in research because of their modifiable nature. ‘Modifiable factors’ include beliefs such as sociocultural beliefs, individual perceptions, beliefs influenced by partners or family members, and spiritual influences. These factors are considered modifiable because they can be altered. For example, in the context of applying theories to enhance or promote screening uptake, substantial opportunities exist to mitigate these ‘modifiable barriers’ through intervention design or educational messages during health programs, awareness campaigns, or implementation studies, as opposed to ‘nonmodifiable’ factors such as age or financial status, making it especially relevant in public health research and programs. Given the variability in the importance of each factor among individuals, it is prudent to anticipate and comprehensively address all modifiable factors to increase screening uptake. Therefore, a model that addresses all modifiable factors, both at the individual and contextual levels, is essential. A holistic approach that considers and tackles both psychosocial and logistical barriers is critical for developing interventions that are meaningful and effective in enhancing screening uptake.

Having established the importance of addressing modifiable factors, health behavior theory-based research has extensively utilized theoretical models for three primary purposes: (a) exploring determinants, including barriers and facilitators, of screening uptake [4, 11,12,13] or ‘exploratory purpose’; (b) understanding the mechanisms of behavior change and the interrelationships among determinants [14]; and (c) informing interventions designed to promote screening uptake [15, 16] or ‘intervention purpose’ [17,18,19]. Health behavior models are particularly suitable for explaining the psychological processes involved in decision-making related to screening, which are based on beliefs, perceptions, and emotions [20]. Since these theories are broadly applicable, they have been widely utilized and recommended for translational implementation research. Most importantly, these models are effectively used to investigate or address psychosocial determinants influencing screening uptake [15]. This paper introduces a conceptual model, the DOST (determinants of screening uptake) model, that maps the psychosocial determinants of screening uptake, which is grounded in health behavior theories. Additionally, recognizing the importance of external factors, i.e., the health system and policy factors, this model provides a clear distinction of barriers across the domains of the socioecological model.

Existing models and frameworks

The development of health behavior models has significantly shaped our understanding of barriers and facilitators to cancer screening uptake. Traditional models, such as the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB), have guided research and interventions aimed at understanding and improving screening behaviors [12, 15, 21], but also show a number of important limitations.

Traditional Health Behavior models

The Health Belief Model (HBM) [45] was created by the social scientists in the early 1950s to understand why people did not use screening tests for early disease diagnosis. According to the HBM, a person’s likelihood of adopting a health behavior can be predicted by how they perceive the disease severity, their risk of contracting an illness or disease, how much they believe the recommended health behavior or activity works and the confidence in their ability to perfrom the behavior despite potential barriers.

The Theory of Planned Behavior (TPB) [46] is an adaptation and extension of the (older) theory of reasoned action and is often used in health research to explain intentions to perform health behavior, which is assumed to be the main predictor of actual behavior. It suggests that an individual is likely to exhibit a certain behavior if they have positive intentions to do so, and the intention depends on their belief that the behavior will give a positive outcome; they have the ability to do it, whereas a significant other will support them in the adoption of this behavior that they perceive to be doable.

The HBM and TPB have been instrumental in identifying individual-level determinants, such as perceived susceptibility, self-efficacy, and health motivation. These models offer valuable insights into understanding why individuals may or may not engage in cancer screening. However, their contributions are primarily limited to explaining behavioral intentions, leaving a significant portion of variance unexplained. They fail to address systemic and contextual factors, such as affordability and accessibility, which are critical in low- and middle-income contexts. Among the main criticisms and limitations of these models are: (1) the fact that they focus narrowly on psychological determinants without considering the interplay between individual and external factors (e.g., cultural norms, health system constraints, etc.); and (2) the fact that although each model explains part of the variance in behavioral intentions and, to a lesser extent, behavior, a significant portion of the variance remains unexplained [22].

Integrated models

The limitations of traditional models to address multifaceted barriers, particularly in complex settings, has prompted researchers to integrate theoretical domains into more comprehensive frameworks [23]. These integrated frameworks combine theoretical domains to provide a more complete and holistic understanding of health behavior. For examples, the psychosocial determinants of socioeconomic inequalities in the cancer screening participation framework [24] looks at the interaction between psychological and structural barriers and explain why individuals from poor socioeconomic backgrounds perceive greater barriers to screening uptake than do those living in less deprived situations. Similarly, the Integrative Model [13] assesses factors affecting HPV vaccine acceptance [25] by integrating the domains of the HBM and TPB theoretical models. The Integrated Behavioral Model (IBM) [26] combines constructs such as knowledge, salience, and environmental constraints with existing theoretical domains to provide a more comprehensive understanding of screening behavior determinants and has been used to explore cervical screening barriers [27] or reduce cancer screening delay [28]. The COM-B Model [29] and the Behavior Change Wheel (BCW) [30] combine capability, opportunity, and motivation with intervention strategies and policy considerations, addressing behavioral and contextual barriers in a systematic way. The Theoretical Domains Framework (TDF) [31] further expands on the psychological and organizational determinants of behavior, and can be used in combination to facilitate a systematic exploration of barriers to and facilitators of health behaviors such as cervical screening [32]. Finally, the Integrated Screening Action Model (I-SAM) [33] amalgamates pertinent health behavior theories to elucidate cancer screening behavior, with a primary emphasis on stages of behavior change and the influence of individual and interpersonal levels across these stages. It integrates these factors to provide a comprehensive framework for understanding the end variables that explain cancer screening uptake.

For a detailed review of these traditional and integrated models, their theoretical underpinnings, their applications to cervical cancer screening, their contributions to improving cancer screening uptake, and their limitations, the reader is referred to the author’s chapter on application of health behavior theories [34]. There are indeed various challenges to developing or applying these models [35]. According to Hein, ‘Integration is more than simply combining theories. Combining theories implies the use of a simple additive model, while integration implies critical testing of these constructs, and constructs will be added only if they have supplementary value theoretically and empirically and will lead to the development and testing of new hypotheses’ [35]. In the domain of understanding cancer screening, the integration or combination of health behavior theories for both research and practical applications has provided significant insights into how models can be combined or integrated for various purposes.

Addressing the theoretical and practical gaps

While traditional models such as the HBM and the TPB often fail to incorporate a number of important behavioral, particularly external factors such as health system or political factors, integrated models such as the capability, opportunity, motivation, and behavior (COM-B) model, the behavior change wheel (BCW), and integrated screening action model (I-SAM) include both psychosocial and external factors and are widely cited. However, the use of these models to map, explore, or identify determinants of cancer screening uptake remains problematic because they do not provide an exhaustive list of the root causes, such as poor knowledge and false beliefs existing in real-world phenomena. While more detailed exploration of the underlying knowledge, awareness and beliefs is typically relegated to empirical research involving qualitative interviews or focus groups that offer rich insights into their lived experiences, this method can be time-consuming, and data may not be representative owing to its small sample size. In such a case, a top-down approach can be useful and a model mapping these factors can guide systematic exploration or mitigation. Such a model will extend the traditional and integrated models by systematically addressing these root causes, or the ‘belief-related factors’ that needs to be mitigated to influence perception and motivation to undergo screening.

While a theory-informed approach can be helpful to explore determinants of screening uptake, a comprehensive model that can serve as a guide or checklist for designing questionnaires to explore them or inform educational messages for awareness campaigns to screen uptake is thus far lacking, which makes it challenging to assess or mitigate these factors comprehensively. A lack of clarity on the underlying factors due to a lack of a comprehensive model can also lead to inconsistent findings in the exploration of these belief-related barriers. Most studies utilize the domains of existing traditional models to select or develop tools, questionnaires, or educational interventions, but there is often ambiguity in how these elements should be developed. This raises questions as to which model should be used, how many items are needed, which specific domains should be prioritized, and how questions should be worded to operationalize the psycho-social barriers. For example, domains such as the ‘Perceived Severity’ or ‘Perceived Benefit’ of the HBM, have been measured in various ways using different assessment tools [15]. This ambiguity among researchers who try to apply such models can stem from a lack of understanding of the models or their limitation to bring types of barriers into broader categories. Therefore, a model with a simplified list of belief-related barriers or determinants can make it less ambiguous to formulate questionnaires to explore them in formative research.

This problem can also affect translational intervention studies aiming to promote or improve screening uptake. If the root causes (e.g., beliefs) are not all targeted by educational or informative interventions, the outcomes may be less effective because certain determinants remain unaddressed.

The complexity and interdependence of barriers to screening uptake mean that if any single barrier is overlooked, the intervention may inadvertently yield poor outcomes or no improvement in screening attitudes or beliefs, despite the educational program. This can result in a Type III error [36] in intervention studies trying to improve screening uptake. A Type III error occurs when the intervention is deemed ineffective in improving screening uptake, not because it addresses the wrong problem but because it misses a critical component of the correct problem. It thus might appear ineffective or even counterproductive because it failed to address a significant aspect that was not considered. To avoid this, applying the ‘universal precautions’ principle is ideal, although challenging. This principle, originally from healthcare [37], when applied in this context, suggests that we should assume all potential barriers are present and take comprehensive steps to address them. This approach ensures a thorough and holistic intervention strategy, enhancing the likelihood of improving knowledge in all areas related to disease and screening. Therefore, a model that highlights belief-related barriers could guide educational interventions to formulate messages necessary to target these barriers.

Comprehensive models such as TDF comprehensively capture several domains of determinants, and can thus be relevant for categorizing barriers and facilitators for screening [38] across broad categories. But they can be operationally difficult to explore specific belief-related factors [39, 40]. As they contain many constructs, some of which overlap, it can be challenging to select relevant domains and constructs for the purpose of mapping determinants of screening, making the framework less user friendly for implementers who don’t have a good theoretical background [41].

There is a pressing need for simplified yet comprehensive models that not only encompass a broad range of determinants but also facilitate the creation of tools or questionnaires to assess beliefs directly and easily. Such model could not only explore beliefs preventing screening uptake but also inform development of educational messages to enhance knowledge, target or modify the deep-rooted beliefs, and motivate the individual to uptake screening. These integrative efforts are vital for advancing public health strategies, especially for nonexperts, to improve outcomes in preventable cancers like cervical cancer screening and others.

Bridging gaps with the DOST model: enhancing practicality and theoretical depth to map determinants of screening uptake

A recommended approach to modifying screening beliefs involves the use of psychological health behavior theories to elucidate these beliefs. A more effective strategy is to integrate the traditional health behavior theories [35, 42], considering the broad range of social determinants i.e., influence of family, society, etc [43], that influence these beliefs.

The DOST (Determinants Of Screening upTake) model builds on and extends existing health behavior theories by focusing on and simplifying belief-related factors, representing real-life barriers to screening acceptance, making it easier to explore these barriers. Educational interventions play a vital role in addressing these barriers by framing specific informative messages to mitigate knowledge- and belief-related obstacles. The DOST model complements existing theoretical models by providing a practical framework that targets these belief-related barriers, ensuring that educational interventions are well-targeted and successful.

Brief overview-DOST

The ‘DOST-Determinants Of Screening upTake’ model was developed to build on the strengths of both traditional and integrated models while addressing their limitations and represents an innovative approach in cancer prevention health behavior research and is uniquely designed to extend and bridge both theoretical and practical gaps in existing models. It can be used to explore reasons for the non-uptake of cancer screening or to promote screening via educational messages. By building on and synergistically combining traditional theories such as the HBM, the TPB, and the Theory of Care Seeking Behavior (TCSB) [44], it accommodates a full spectrum of psychosocial determinants across meaningful theoretical domains because psychosocial barriers play a significant role in decision making in screening utilization. The combinations of the variables from different models are tested primarily to understand the explained variance of integration on screening intention. Additionally, DOST employs socio-ecological model categories to systematically map and display determinants of screening uptake. These include individual-related factors and external influences, such as interpersonal and sociocultural beliefs (e.g., opinions of loved ones that impact individual decisions). Structural barriers, including limited screening facilities, insufficient manpower, inadequate policies, and high screening costs, are also considered.

A detailed explanation of these factors is provided in the description of the model. Crucially, the model is grounded in empirical evidence, ensuring that its subdomains accurately reflect the actual psycho-social determinants, or ‘beliefs,’ that explain its domains. These subdomains, representative of real-life barriers, facilitate the development of targeted questions for empirical research, thereby simplifying the application of the model for implementers and program managers who may not be psychology experts. By categorizing these barriers under traditional model domains and including external factors, the DOST model complements and enhances existing health behavior theories and socio-ecological model, offering a holistic view of the determinants influencing cancer screening behavior, and deeper focus on belief related factors influencing screening acceptability relevant for studies focusing on these factors.

Method

To develop a consolidated model, we followed a systematic stepwise approach consisting of four consecutive steps: (1) Step 1: A systematic review to identify the health behavior theories that explain screening behavior (2). Step 2: Evaluating Predictive Strength of Health Behavior Models for Cervical Cancer Screening Intention (3). Step 3: Integration of the identified health behavior theories and domains into a conceptual model and testing its ability to predict cervical cancer screening intention (4). Step 4: Mapping the domains that may influence screening uptake or intention (components from the integrated health behavior model) across the levels of the socioecological model, comparing them with real-world barriers identified through emperical qualitative and quantitative studies.

Setting

Empirical research related to model testing was conducted in a low-middle-income country (India) selected to represent a setting characterized by significant challenges faced by women and the healthcare system. This choice aimed to address cultural and belief barriers, which are presumed to be pronounced in such contexts.

Step 1: A systematic review to identify the health behavior theories that explain screening behavior and intention

The initial step in our approach to developing the integrated DOST model was a systematic review, the results of which have been published elsewhere [15]. The objective of this review was to evaluate existing health behavior theories or models that are extensively employed to assess or predict barriers to cervical cancer screening or those utilized to inform educational interventions. This was done to ensure that the final model was built upon relevant and empirically supported theoretical foundations. The results of the study aided in pinpointing the most pertinent and effective frameworks and strategies, guiding the development and refinement of the DOST model.

Many studies have also explored the utilization of health behavior theories to explain breast cancer screening behavior [12]. Our review enabled to extract data on health behavior models used in assessing cervical cancer screening barriers and in interventions that could mitigate barriers to screening uptake and promote screening. It confirmed that health behavior theories are crucial in clarifying intentions and behaviors related to cervical cancer screening and in developing interventions to enhance screening uptake, and that interventions that encompass all theoretical constructs display superior effectiveness in transforming perceptions and amplifying the adoption of cervical cancer screening. However, it also revealed that the application of health behavior theories, though advantageous, has been inconsistent, in that the HBM was primarily used to interpret behaviors, whereas the TPB was more effective in explaining screening intentions.

Step 2: Evaluating predictive strength of health behavior models for cervical cancer screening intention

Systematic reviews of existing health behavior models have revealed that two methods have been widely applied to cancer screening (i.e., the HBM and the TPB). A third model, the theory of care-seeking behavior(TCSB) [44], is less widely used but has components that significantly influence screening behavior. Lauver’s Theory of Care-Seeking Behavior (TCSB), developed in 1993 and based on Triandis’ theory of general behavior, posits that individuals are more likely to engage in a behavior if they adhere to healthy practices, experience positive emotions, and perceive support from significant others, alongside favorable sociodemographic conditions. In the context of cancer screening behavior, the inclusion of the “Affect” domain within the conceptual model is pivotal because of its significant influence on various other domains, such as perceived susceptibility and perceived benefits.

In cervical cancer screening, for example, the domain of “Affect” is important because it encapsulates emotions such as fear, anxiety, or embarrassment. These emotional responses can significantly impact other domains within the model; for instance, poor knowledge and false beliefs can directly lead to fear or anxiety, which may lead to heightened perceived susceptibility or diminished perceived benefits. Such emotional responses often stem from inadequate knowledge, awareness, false beliefs or even a lack of social support, necessitating specialized attention and empathy toward individuals experiencing these emotions. Consequently, addressing these emotional factors becomes imperative in designing effective interventions to promote cancer screening. The incorporation of the ‘affect’ domain into the conceptual model enhances our ability to understand cancer screening behavior from an emotional perspective. By including emotions such as fear, anxiety, and embarrassment, the model acknowledges the significant role these feelings play alongside cognitive determinants. This comprehensive approach allows us to understand the reasons for the non-uptake of screening not only through a cognitive lens but also through the emotional experiences of individuals. Furthermore, to promote screening uptake, interventions can be designed to alleviate fear and anxiety by providing clear, empathetic communication and supportive counseling. This dual focus on emotions and cognition makes the model more effective and applicable.

Step 3: Combine the domains or components of the most predictive health behavior models into a conceptual model and test the ability of the integrated model to predict cervical cancer screening intention

To identify which model can predict screening intention better, a questionnaire study, which is published elsewhere, was undertaken to test the ability of each of these models to explain screening intention [47]. While it was found that the TPB and the HBM could significantly predict screening intention, certain components of the theory of care seeking behavior, such as ‘habits’, were significantly associated with the intention to be screened [47]. Therefore, the components of these three models were combined and tested for their combined validity to explain ‘screening intention’ which is considered a universal predictor of screening behavior. The integrated model performed better in explaining screening intentions than each of the individual models did [14].

Step 4: Mapping the factors that may influence screening uptake (components from the integrated health behavior model) across the levels of the socioecological model

To map the potential factors that explain screening uptake, the domains or constructs of the TPB, the HBM and the TCSB were integrated into a consolidated model that includes all potential psychological factors that significantly influence cancer screening intention.

The systems model of behavior change suggests the consideration of external factors that influence behavior [48]. To employ the systems approach, we used the socioecological model proposed by Bronfenbrenner [49], which shows that factors at various levels of social interaction can act as facilitators or barriers to behavior. When applied to health behavior, various levels of an individual’s social interaction factors can influence a person’s decision to participate in screening: individual factors (e.g., sociodemographic profile, knowledge and awareness, beliefs, self-perceptions), interpersonal factors (e.g., significant others that might influence one’s beliefs), sociocultural factors (e.g., influences of the community, culture), and organizational factors (e.g., availability of screening services, health programs, health coverage). The factors that may influence cervical cancer screening could be displayed across the socioecological model, as shown in Fig. 1, which is published elsewhere [50]. While the initial mapping and validation were focused on cervical cancer screening, the socioecological structure ensures broader applicability. For instance, similar psychosocial barriers—such as fear of invasive procedures, embarrassment, or cultural sensitivities—are also observed in breast and colorectal cancer screening. This gives the model scope to be applied or adapted for identifying determinants in other cancer screenings, such as breast, colorectal, or even prostate cancer.

Fig. 1

Barriers to screening uptake across socioecological levels [50]

We added the domain of ‘health literacy’ to our model (seen under the ‘individual factor’ in Fig. 2) because it is a critical concept in public health [51], and several studies have shown its significance in screening behavior [52]. Health literacy (HL), is a person’s ability to obtain, understand, appraise and apply information that is needed to make informed health decisions and low health literacy, is associated with poor self-care, poor adherence to medication, less uptake of preventive or health promotional services, and high expenditure on medications [51, 53, 54]. There is evidence in the literature that individuals with low health literacy are more likely to hold fatalistic cancer prevention beliefs [55, 56] or not seek medical care despite experiencing cancer-related symptoms [57] than those with higher health literacy. Our test of the relationship between HL and cervical cancer screening behavior confirmed the importance of HL for cervical cancer screening intentions [14, 58].

Fig. 2

‘DOST’– ‘Determinants Of Screening upTake’ model

In the context of the DOST model, health literacy (HL) plays a crucial role in promoting cervical cancer screening. Although health literacy cannot be directly modified to improve screening, it can be improved from a young age [59], which is why it overlaps with the modifiable and nonmodifiable barriers in our DOST model. Importantly, one’s health literacy level should be considered during screening promotion, and certain considerations can be made during the development of these educational interventions to ensure that individuals with lower health literacy levels are effectively reached and engaged. Additionally, with health psychology expert opinions, we retained the ‘Affect’ domain from the TCSB in the model to be integrated into DOST to highlight the importance of emotional factors that significantly influence the decision to screen.

Reporting standards

This manuscript adheres to the TIDieR (Template for Intervention Description and Replication) checklist for transparent and comprehensive reporting of the DOST model.

Results

The ‘DOST’- determinants of screening-uptake model

Model overview: The DOST model categorizes the factors that may influence screening participation across domains and their components for the ease of understanding and use of its users, who could be program implementers, researchers, etc. The DOST model and domains are displayed in Fig. 2, and their components are displayed in Table 1.

Table 1 ‘DOST’ model domains and components

In the model, barriers to screening are broadly classified as ‘health system-related barriers’, which are challenges faced by the health system to provide screening services (in green), and ‘beneficiary-related barriers’, which are the barriers faced by beneficiaries to utilize the services (in yellow). Theoretically, all the barriers need to be mitigated to promote decision making, which could be a challenging task in practice. However, when broken down into components, it becomes easier to address these separately, especially those that can be mitigated (modifiable barriers).

Domains and components of the DOST model

Health system factors

Cancer screening services or programs may not be implemented systematically leading to inequities. These inequities are due to a vast array of factors influencing implementation of cancer screening programs, which can be categorized as ‘health system-related factors’ (Displayed in green box in the model-Fig. 2). Screening utilization depends on the assurance of screening availability; addressing psychological barriers alone may not be impactful if screening services are not available or accessible, and hence, they must also be considered. Technically, it is essential to preliminarily assess the availability of screening when designing interventions to promote screening uptake. Neglecting to ensure the availability, affordability, accessibility and acceptability (Components ‘q’, ‘r’, ‘s’ and ‘t’ in DOST model) of screening could lead to incongruous and counterproductive interventions. The ‘health system barriers’ must be addressed foremost. This will enable a focus on beneficiary-related barriers to screening uptake. Typically, health system factors listed in Table 1, are more pronounced in LMICs because of limited health system resources [60]. While frameworks exist for health system assessment [61], numerous strategies, such as the incorporation of low-cost HPV testing, the development of context-relevant screening and management algorithms for population-based cervical cancer screening, the utilization of existing programs and human resources by task shifting, and the enhancement of competencies of current human resources through thorough training, can help mitigate these barriers to some extent. Gupta et al. emphasized that strong political will, judicious financial allocation, and strategic communication are indispensable for the effective implementation of cancer prevention programs in settings with limited resources [62]. Since the DOST model is designed to map all potential determinants of screening uptake, it plots health system-related factors alongside beneficiary barriers, providing a holistic view, capturing both ‘beneficiary-related’ and ‘health system’ determinants.

Beneficiary-related factors

All factors related to the beneficiary—such as sociodemographic profile, literacy, health literacy, and individual beliefs, as well as the beliefs of significant others (e.g., partner, family)—that influence the decision to undergo screening are categorized under ‘beneficiary-related factors’ in the DOST model (displayed in the yellow box in Fig. 2). These factors may include individual non-modifiable characteristics, such as sociodemographic profile, or modifiable attributes, such as beliefs and perceptions. Overall, they highlight the barriers beneficiaries face when attempting to utilize existing screening services and are a central focus of the model.

To provide clarity, beneficiary-related factors are sub-categorized as follows:

• 1. Individual Factors (Factors A, B, C, D): These factors represent the individual’s attributes and beliefs, encompassing both non-modifiable and modifiable characteristics mentioned earlier. These intrinsic factors directly shape the individual’s decision-making process regarding screening.

• 2. External Factors (Factor E): These factors encompass influences from the individual’s social context, such as family, community, or societal norms. For example, poor knowledge or negative beliefs held by a significant person (e.g., a partner or friend) may influence an individual’s beliefs, leading to a negative attitude toward screening.

This distinction between individual and external factors ensures that the model captures both internal and contextual determinants of screening behavior. By explicitly mapping these interactions, the DOST model allows implementers to target both individual barriers (e.g., knowledge gaps, false beliefs) and external influences (e.g., social support or community norms) in their interventions.

Factor A

INDIVIDUAL NON-MODIFIABLE FACTORS

Individual non-modifiable factorsepresent the (a) sociodemographic profile, such as age, financial status, and health insurance status; (b) social identity (role in family or community as a social or financial provider, decision maker, etc.); (c) health-seeking behavior of individuals [44] (routine response to symptoms, routine asymptomatic health check-up); and (d) health literacy, such as an individual’s ability to access, understand, appraise, and apply the information during the life course for health care, disease prevention or health promotion [63]. These factors are known to significantly influence the decision to undergo screening.

Factor B

KNOWLEDGE AND AWARENESS

The knowledge and awareness that individuals possess about the (e) disease and screening and (f) information about an existing screening program or services can influence their decission to undergo screening.

Specific aspects such as knowledge and awareness about disease (awareness of the disease, etiology, risk factors, nature/characteristics, warning signs, awareness of need of screening irrespective of symptoms), knowledge and awareness about screening (e.g., screening tests, methods, immediate consequences of screening both physical and screening reports) and awareness of existing screening services/programs (awareness that the test is available, where it is available, the cost of the test, the time required to undergo the test or obtain results) are vital for decision making. The individuals can obtain this information from various sources. Passive information can be obtained from general health awareness, such as media, government health education materials, friends, etc., or it can be actively sought by individuals from health practitioners or from various sources due resulting from increased interest on the topic due to presence of similar symptoms in them or among their significant relatives. The ‘knowledge and awareness’ factor is separated from others to list vital reasons for false beliefs and because they are or can usually be focused on in intervention studies.

Factor C

PERCEIVED FACTORS

Perceived factors are the beliefs and perceptions of individuals. They are concerned with various aspects, including (g) perceived susceptibility to the disease (i.e., beliefs about the likelihood of developing a disease or condition) [45]; for example, a woman must believe that there is a possibility of developing breast or cervical cancer before she will be interested in obtaining a mammogram. (h) Perceived disease severity, i.e., feelings about the seriousness of contracting an illness or of leaving it untreated, includes evaluations of both medical and clinical consequences [45]. (i) Affect (feelings of fear, embarrassment, anxiety related to the disease and its outcome; feelings of fear, embarrassment, anxiety related to screening process or the screening test and its outcome). (j) Perceived benefits, i.e., the benefit of screening/early detection and treatment (physical benefits such as improved survival rate compared with non-screening if detected), psychological benefits (peace of mind), social benefits (improved interpersonal relations), spiritual benefits (influence on spiritual beliefs), and financial benefits (prevents treatment costs of late detection of cancer).

Perceived barriers include those beliefs that act as barriers (k) Perceived barriers can be false or incorrect thoughts that are the result of incomplete ‘knowledge and awareness’, the factor mentioned (i.e., false thoughts/cognition related to the etiology of the disease, risk factors, nature/characteristics, warning signs, management, and treatment, etc.), false thoughts/cognition related to the outcome/impact of disease on one’s physical health, mental health, social relations, and spiritual or financial well-being; false thoughts/cognition related to the outcome/impact of screening on one’s physical health, mental health, social, spiritual or financial condition. These perceived barriers are highly modifiable through educational interventions, which aim to address and correct the underlying misconceptions.

On the other hand, perceived barriers can also be concerned with ‘real harms’ associated with screening (e.g., discomfort during procedures, minor risks, or anxiety). These are acknowledged in the DOST model under systemic acceptability factors, within health system-related factors, and can be addressed by ensuring minimally invasive and painless procedures, offering support for managing anxiety, and providing clear communication about both benefits and risks to facilitate informed decision-making.

(l) perceived self-efficacy (i.e., the belief that one is capable of seeking and undergoing screening tests despite existing difficulties or challenges) [64].

Factor D

PERCEIVED STRUCTURAL AND COGNITIVE HEALTH SYSTEM-RELATED FACTORS

The Factor D includes (m) perceived structural barriers such as distance, time and cost involved in obtaining a screen test. For example, an individual thinking of such a screening test perceives a long distance to the hospital, the unavailability of transport, inconvenient screening hours, expensive screening, etc., as barriers. It also includes(n) cognitive barriers related to health system services (e.g., beliefs about provider attitudes or quality of care; lack of faith in the system due to a bad experience or information obtained; or even emotions such as fear, embarrassment, or anxiety caused by false beliefs about the health system).

Although perceived structural and health system-related barriers may appear to overlap, they are distinct in this model. Perceived structural barriers are subjective obstacles that individuals believe prevent them from accessing screening, regardless of whether these barriers exist in reality. For example, a woman may perceive that the hospital is too far away or believe that no transportation is available without actually knowing if transport services exist. In contrast, health system barriers refer to actual obstacles within the healthcare system, such as a lack of screening services at health centers due to staff shortages, inadequate infrastructure, or poor service quality, which result from systemic resource constraints or organizational inefficiencies. Although there is no universally defined cutoff guidelines for human resource or distance for determining screening accessibility, its feasibility depends on the specific implementation context. For example geopgraphical accessibility can depend on terrain, transport availability, and population distribution.

Factor E

SOCIAL FACTORS

Social factors in an individual’s context can influence the decision to undergo screening. These include (o) the social influence of significant people (knowledge, awareness, beliefs of partners, family and friends) and (p) social influences from communities and groups (e.g., norms or beliefs of the local community, culture, or tradition).

All the above factors (‘A,’ ‘B,’ ‘C,’ ‘D,’ and ‘E’) can shape ‘attitude’ (feeling that screening is not required or unnecessary) [65], ‘motivation’ (acting as facilitators), or ‘self-efficacy’-a perceived sense of ability to undergo screening.

‘Systemic Acceptability’ vs ‘Individual Acceptability’: In the DOST model, acceptability is conceptualized in terms of two dimensions: systemic acceptability and individual acceptability. Factors categorized under C (Perceived Factors), D (Perceived Structural and Cognitive Health System-Related Factors), and E (Social Factors) influence an individual’s decision to accept screening, and can influence individual acceptability. Individual acceptability is shaped by Knowledge and Awareness, Social Influences, Beliefs, and Emotions. This aligns with Sekhon’s Theoretical Framework of Acceptability (TFA), which conceptualizes acceptability primarily as an individual factor, influenced by affect, self-efficacy, knowledge, and beliefs. In contrast, ‘Acceptability’ categorized under ‘Health System-Related Factors’ represents systemic acceptability. Systemic acceptability refers to the logistical and operational design of screening programs and includes factors such as user-friendliness, painless procedures, and convenient access. These are elements that implementers must address to make screening programs both attractive and accessible to beneficiaries. Conceptualizing acceptability as two dimensions reflects the interplay between how a screening program is organized (system-level) and how it is perceived (individual-level). This dual perspective provides implementers with actionable insights to design user-friendly screening procedures and programs while simultaneously addressing individual-level factors such as beliefs through educational campaigns and community engagement initiatives.

Discussion

Previous research has extensively investigated a variety of factors that influence screening uptake. Evaluating all potential impediments in a specific context can be intricate, but employing a consolidated model that methodically categorizes these barriers simplifies the process, providing implementation researchers and program managers with a more comprehensive understanding of these barriers and the underlying beliefs that give rise to them.

While traditional models highlight broader domains such as susceptibility, severity, and motivation, they primarily reflect mediating variables [33] that influence the decision to undergo screening. Poor knowledge and awareness can lead to false beliefs, which in turn evoke emotions such as fear or confidenc, anxiety or reassurance. These emotions impact perceived susceptibility and severity. For example, fear and anxiety can negatively impact perceived susceptibility or perceived severity leading to a diminished perception of benefits and, consequently, poor motivation and attitudes toward screening. Therefore, to effectively address screening uptake, it is essential to target these root causes—beliefs and knowledge—to mitigate the emotional and cognitive barriers influencing the decision to undergo screening.

Identifying and mitigating poor knowledge or awareness and false beliefs arising from inadequate knowledge can enhance motivation and capabilities or alleviate barriers to improve screening uptake. In the context of formative research, tools such as the Cancer Awareness Measure (CAM) [66] or the ABC measure of cancer awareness and beliefs [67] have been used to assess awareness of cancer risk factors and warning signs, which can help assess knowledge that leads to beliefs. However, they do not explain the role of awareness about screening benefits or explore the general care-seeking attitudes or behaviors of participants, which can significantly explain screening uptake and studies have shown that the BCAM-Breast Cancer Awareness Measure tool is basic and rudimentary [66, 67].

In intervention research, Hungerford’s behavior change theory [68] emphasizes that modifying beliefs through education can significantly improve attitudes toward screening uptake. To address psychosocial barriers effectively, it is crucial to provide clear and comprehensive information, which can be termed ‘necessary information’ and is essential for instilling correct beliefs, potentially leading to enriched emotional responses that influence an individual’s decision to undergo screening. The DOST model, with its extensive mapping of psycho-social determinants, not only highlights topics to explore for false beliefs but also serves as a practical guide for formulating ‘necessary information’ required to educate and correct misconceptions. This approach ensures a thorough understanding and addresses all relevant barriers, making it highly actionable for designing interventions.

The DOST model domains are built upon traditional health behavior models, adopting a socioecological approach to categorize these domains effectively. It also categorizes the domains into simpler subdomains that were compared with barriers identified through empirical research that reflect real-world barriers, which makes it easy to understand for implementers and program managers, even those without an extensive background in health behavior theory. While primarily focused on psychosocial factors, DOST employs a socioecological model to incorporate a ‘systems approach,’ effectively including health system and external factors. This ensures a holistic view, integrating influences at multiple levels—individual, interpersonal, societal, and organizational while also offering an easy-to-understand, actionable framework that guides investigators and implementers in instilling accurate beliefs.

The DOST model is an amalgamation of traditional health behavior models and the socioecological model, enhancing their utility by combining complementary elements. This integrative approach provides both theoretical depth and practical insights for effectively addressing barriers to cancer screening uptake. By combining complementary elements, it explains a larger portion of the variance in screening intentions compared to using individual models alone. Additionally, integrating theoretical insights with empirical observations provides a nuanced understanding of barriers to cancer screening uptake and offers practical solutions for addressing these barriers in real-world settings.

Although the DOST model was developed with cervical cancer screening as a reference, its comprehensive framework enables broader application to other cancer screening programs. Screening uptake for breast, prostate or colorectal cancer screening, for instance, are also affected by psychosocial and cultural barriers such as fear, embarrassment, and misinformation. The socio-ecological categorization of barriers in the DOST model ensures that it is versatile enough to address these challenges while remaining adaptable to specific contextual differences. By providing a systematic mapping of barriers, the DOST model supports the design of targeted interventions, educational programs, and policy measures aimed at improving screening uptake across a range of cancers.

Future research will need to establish the DOST model as a robust enhancement tool, effectively bridging theoretical insights with practical applications in the design of barrier assessments and educational interventions. By tailoring the framework to specific cultural contexts, we can move from theoretical evidence to real-world implementation to address the'Health system factors' and'Beneficiary related-factors' that act as barriers.

Implications

Considering the diverse needs and barriers faced by different stakeholders, the DOST model can serve specific purposes to effectively enhance cancer screening uptake. The Table 2 provides tailored implications for researchers, program managers, and policymakers, illustrating how the DOST model can be effectively utilized to enhance screening uptake.

Table 2 Implications of DOST model

The foundational premise of the DOST model is the fact that individuals often do not perceive the necessity for screening in the absence of symptoms. They operate under the assumption that no apparent ailment means no need for action, unlike when symptoms manifest which trigger a response. Additionally, screening procedures, particularly those involving private body areas, may deviate from common practice and can evoke physical or psychological discomfort. These factors can render the idea of screening unfavorable unless the perceived benefits significantly outweigh the discomforts and risks. This highlights the critical need for heightened awareness and understanding of the benefits of screening, emphasizing the importance of educational interventions to address these misconceptions. The DOST comprehensive framework enables a broader application to other cancer screening programs. This gives the model scope to be applied or adapted for identifying determinants in other cancer screenings.

It is crucial to recognize that the barriers and determinants identified are not exhaustive. To ensure a thorough understanding and effective application of the model, specific considerations and limitations of model use are outlined in Table 3. These considerations are vital for maximizing the impact and effective application of the model.

Table 3 Key considerations for applying the ‘DOST’ model

Limitations

Beneficiary-related factors to screening uptake: The model is centered explicitly on the barriers faced by or perceived by beneficiaries impeding screening uptake and does not dive deeper into the challenges related to screening implementation within the health system or the determinants of intervention implementation. For application of the model to inform interventions, one must remember that the ‘health system barrier’ is delineated as a determinant of screening uptake. That is, the model can be effectively applied when health system barriers have been addressed or when a screening program is well established and when utilization remains suboptimal.

Conclusion

Developing barrier assessment tools remains a significant challenge for implementers due to the limitations of both top-down and bottom-up approaches. While health behavior theories show promise in designing these tools and formulating educational interventions, operational complexities often hinder their real-world application. The DOST model addresses these issues by integrating a comprehensive range of potential barriers, providing a more complete understanding of the determinants of cancer screening uptake. It facilitates the theoretical application in empirical research and encourages users to consider all possible barriers within a given context.

Future research should focus on tool development and practical applications to fully reveal the model’s potential to explore screening barriers. It is recommended that, during the development of such tools, particular attention be given to assessing their construct validity to ensure they accurately measure the theoretical domains outlined in the model. The barrier assessment questionnaire currently being developed based on the DOST model may serve as a useful reference for ensuring content validity, although further validation and refinement are ongoing. While utilizing the model to mitigate the barriers, studies should focus on its utility in patient-centered care, where addressing individual and systemic barriers ensures individuals are empowered to make autonomous, informed decisions about screening participation. Such work will ultimately enhance health behavior outcomes and public health interventions. Ongoing refinement and validation of the DOST model through empirical studies will be pivotal in adapting and implementing it across diverse health contexts and domains.