What theoretical frameworks or models have been used to assess determinants of cancer screening?
A diverse range of theoretical frameworks and models have been used to assess determinants of cancer screening. These frameworks are critical for understanding the multifaceted psychosocial, behavioral, and contextual influences that drive or impede participation in cancer screening programs.
Health Belief Model (HBM):
The HBM is one of the most frequently applied theoretical frameworks for cancer screening. It emphasizes individuals’ perceptions of susceptibility, severity, benefits, barriers, cues to action, and self-efficacy related to health behavior. Numerous studies have used it to understand participation in breast, cervical, and colorectal cancer screening. HBM constructs such as perceived barriers, benefits, and susceptibility have shown strong associations with screening intentions and behaviors[1]. For instance, in the context of colorectal cancer screening, knowledge, perceived susceptibility, response efficacy, and self-efficacy, as defined in the HBM, significantly predicted participation rates[2]. Other research demonstrates the relevance of HBM in explaining gender differences and addressing context-specific barriers in colorectal cancer screening[3], as well as in breast cancer screening across different populations[4],[5].
Theory of Planned Behavior (TPB):
The TPB suggests that attitude toward the behavior, subjective norms, and perceived behavioral control jointly shape individuals’ intentions and actions. Research indicates that TPB is particularly strong in predicting intentions to participate in cancer screening, sometimes outperforming other models. Attitudes, subjective norms (perceived social pressure), and perceived behavioral control (confidence in ability to complete screening) have all been identified as significant predictors of screening intention and behavior for cervical, breast, and colorectal cancer[6]. Expanded TPB models often include additional constructs such as anticipated regret and self-identity, which further improve predictive power[7],[8],[9].
Transtheoretical Model (TTM) (Stages of Change):
The TTM focuses on the process and readiness to change, categorizing individuals into precontemplation, contemplation, preparation, action, and maintenance stages. This model has been used to analyze breast cancer screening behavior, where interventions tailored to a person’s stage of readiness significantly improve behavior adoption[10]. TTM helps in designing interventions by targeting individuals at different stages of screening behavior adoption.
Protection Motivation Theory (PMT):
PMT assesses how perceived severity, vulnerability, response efficacy, self-efficacy, and fear influence motivation to adopt protective behaviors like cancer screening. Recent studies on colorectal cancer screening found perceived severity and response efficacy strongly influence screening intentions, while self-efficacy and response costs were less predictive in some cases[11].
Social-Cognitive and Other Health Behavior Theories:
Complementing the above, models such as Social Cognitive Theory, which emphasizes observational learning, reinforcement, and self-efficacy, have also been applied, as have hybrid and integrated models that combine elements from several frameworks. For instance, the Integrated Behavioral Model (IBM) and constructs from the Social-Ecological Model (SEM) have been mapped to determinants of HPV vaccination and cancer screening behaviors on social media and in communities[12].
Consolidated Framework for Implementation Research (CFIR):
CFIR is a meta-theoretical framework that systematically identifies multilevel barriers and facilitators (inner/outer context, individuals, intervention characteristics, and implementation process) affecting cancer screening implementation[13]. This framework is often used for evaluation of interventions and identifying actionable strategies in health systems[14],[15].
Andersen and Newman Framework of Health Services Utilization:
This framework categorizes determinants of health service use into predisposing (e.g., demographics, beliefs), enabling (e.g., resources, accessibility), and need-related factors. Recent systematic reviews have employed this model to classify social, individual, and health system barriers and facilitators to cervical cancer screening in diverse regions[16].
Ecological and Multi-level Models:
Broader conceptual models such as ecological systems theory and multi-level logic models have also been used for integrating individual, social, environmental, and policy-level determinants. These approaches are especially common in studies targeting populations facing disparities in screening, such as racial/ethnic minorities and low-income groups[14],[17],[18].
Intervention Mapping and Logic Model Approaches:
Systematic frameworks like Intervention Mapping use theory and evidence to guide the development, implementation, and evaluation of interventions designed to increase screening uptake. These methods help connect behavioral and environmental determinants to specific change objectives in cancer screening programs[19],[20].
Other Models and Emerging Approaches:
- The Theory of Care-Seeking Behavior (TCSB) focuses specifically on attitudes, beliefs, and actions related to seeking preventive care[1].
- The Health Action Model (HAM), employed in some recent breast cancer screening studies, structures the educational interventions addressing personal, social, and environmental determinants[21].
- Machine learning models are increasingly used to predict screening uptake using features aligned with established theoretical frameworks, as seen in recent African studies for cervical cancer screening[22].
Integrated and Consolidated Models:
There is a marked trend toward integrating elements of multiple theories to better capture the complex web of factors affecting screening. For example, the Determinants Of Screening upTake (DOST) model integrates the HBM, TPB, and TCSB to provide a comprehensive, beneficiary-centered map of barriers and facilitators[1].
Summary Table (in Markdown):
| Model/Theory | Core Constructs | Screening Contexts |
|---|---|---|
| Health Belief Model (HBM) | Susceptibility, severity, benefits, barriers, self-efficacy | Breast, cervical, colorectal, lung |
| Theory of Planned Behavior (TPB) | Attitude, subjective norm, perceived behavioral control | Cervical, breast, colorectal |
| Transtheoretical Model (TTM) | Stage of change, processes, readiness | Breast, cervical, colorectal |
| Protection Motivation Theory (PMT) | Severity, vulnerability, efficacy, fear | Colorectal |
| Consolidated Framework (CFIR) | Multilevel domains (context, individuals, process) | Colorectal, lung, breast, cervical |
| Andersen & Newman Utilization | Predisposing, enabling, need | Cervical, diverse cancers |
| Social Cognitive Theory | Self-efficacy, modeling, reinforcement | Various, especially knowledge/attitude pathways |
| Intervention Mapping/Logic Model | Behavioral/environmental determinants, change objectives | Colorectal, breast, cervical |
| Multi-level/Ecological Models | Individual, social, environmental, policy | Breast, colorectal, cervical, Asian/immigrant populations |
| DOST/Integrated Models | Combined constructs from HBM, TPB, TCSB | General/various |
| Health Action Model (HAM) | Action-oriented structures | Breast |
In conclusion, there is no single framework universally applied. Rather, research integrates theoretical constructs suited to the population, context, cancer site, and behavioral target under investigation. Would you like an in-depth comparison of how different models perform or specific guidance on choosing a framework for a particular population or screening modality? I can also drill down into examples from particular cancer types or geographic/economic settings if needed.