Introduction

Skin cancer has become one of the most common types of cancer globally (WHO 2017, 2020); the most prevalent cause of morbidity and mortality in industrialized countries (Pearlman et al. 2021; Sotoudeh et al. 2019) and the second most frequent cancer among adolescents and young adults aged 15–29 years (Wu et al. 2018). Excessive UV exposure during adolescence and early youth has caused much of the affected population to receive damage to their skin (Tabbakh et al. 2019). Preventive behaviors (Tizek et al. 2019) can significantly slow its spread (Krstić and Ćorić 2021), with effective strategies including protection against UV radiation (Davati et al. 2013; Thoonen et al. 2020).

Spain is among the European countries with the highest exposure to UV radiation, and an increase in this type of cancer is expected if sun protection habits are not improved (Tejera-Vaquerizo et al. 2016). Given that epidemiological studies indicate young college students as a higher risk group (Blázquez-Sánchez et al. 2020; Cambil-Martín et al. 2023; García-Montero et al. 2020), corroborating research from other countries (Cambil-Martín et al. 2023; Davis et al. 2015; Julian et al. 2020; Trad and Estaville 2017), it is necessary to identify the factors that influence the adoption of healthy behaviors for skin cancer prevention in this population sector.

The health belief model has proved to be a valuable tool for understanding the adoption of sun prevention behavior in skin cancer, even though it has been less commonly used in relation to this area (Carpenter 2010; Pearlman et al. 2021; Støle et al. 2019). The adoption of health behavior change is influenced by several factors such as avoiding negative health outcomes, perceiving positive effects by adopting a recommended action, and believing in one’s individual capacity to successfully carry out the recommended action (Tang and Park 2017). In this sense, the HBM is considered useful for understanding perceptions of skin cancer threat, benefits of the effectiveness of preventive measures, and the individual and socio-contextual factors that influence the adoption of sun protection behaviors. Thus, this paper focuses on the analysis of HBM constructs on skin cancer prevention among young college students in Spain, a high-risk population for this disease. The high-risk designation is based on evidence showing that college students exhibit higher levels of sun exposure and lower rates of effective sun protection compared to other groups (Blázquez-Sánchez et al. 2020; Cambil-Martín et al. 2023; García-Montero et al. 2020).

Studies on college students have produced varied results regarding HBM constructs. For instance, a US study indicated that beliefs about sun exposure, regional climate, and sunscreen safety influence skin cancer risk (Julian et al. 2020). Meanwhile, Pearlman et al. (2021) found that among 186 medical students, perceived benefits outweighed perceived barriers, suggesting strong preventive action and self-efficacy, with susceptibility, benefits minus barriers, and self-efficacy as key predictors of behavior; however, social support did not significantly impact sun protection behavior. In Spain, research is limited on how beliefs and sun protection habits affect primary prevention behavior. Notably, studies using the CHACES questionnaire have identified factors such as age, gender, education, and skin phototype as predictors of sunburn, highlighting young adults with higher education levels as a high-risk group (Cambil-Martín et al. 2023; De Troya-Martín et al. 2018; De Troya-Martín et al. 2009; Blázquez-Sánchez et al. 2020, 2021; De Castro Maqueda et al. 2022; García-Montero et al. 2020).

The only study that has examined the HBM in relation to attitudes and behaviors toward sun protection (Cercato et al. 2015) was conducted during the summer of 2009 on Spanish beachgoers with an average age of 30 years. The results showed a high level of knowledge and a fairly positive attitude towards sun protection but also identified physical and motivational barriers. No subsequent studies have updated or tested the HBM dimensions in other Spanish contexts and population groups. Therefore, the research question guiding this study is:

What factors influence the adoption of skin cancer prevention behaviors among the at-risk population of young college students in Spain, and how can the constructs of the HBM explain these behaviors?

The primary contribution of this research lies in the incorporation of the sunburn measurement unit from the CHACES questionnaire within the framework of the HBM, and in the development of a statistical model that explains health behaviours related to solar photoprotection and skin cancer. This innovation provides a robust tool for better understanding the factors that influence the prevention of sun damage and the development of skin cancer.

Methods

The health belief model

The application of the HBM was developed in the 1950s by a group of psychologists — Irwin Rosenstock, Mayhew Derryberry, and Barbara Carriger — belonging to the Public Health Service of the United States (Green et al. 2020). This model has been extensively tested to explain adherence to health recommendations (Green et al. 2020; Moreno San Pedro & Gil Roales-Nieto 2003), and has recently gained renewed attention (Zewdie et al. 2022). The primary aim of this model is to understand why individuals often resist engaging in preventive behaviors (Moreno San Pedro and Gil Roales-Nieto 2003). It is grounded in the premise that individual health beliefs influence their behaviors (Champion and Skinner 2008; Janz and Becker 1984).

The original model contemplates four main dimensions: perceived susceptibility, perceived severity, perceived benefits, and perceived barriers (Champion and Skinner 2008; Moreno San Pedro & Gil Roales-Nieto 2003; Rosenstock 1966). This model has been expanded to include two additional dimensions: cues to action and self-efficacy (Bandura 1997; Champion & Skinner 2008; Green et al. 2020; Rosenstock et al. 1988). Susceptibility pertains to an individual's subjective perception of the risk of contracting diseases. The model posits that people are more motivated to take health-conscious actions if they believe they are susceptible to certain negative health outcomes (Rosenstock 1966). Severity encompasses beliefs about the seriousness of a given disease or the consequence of not treating it. This dimension includes assessments of medical–clinical consequences and possible social repercussions. The model predicts that the greater people's perception of the severity of negative health outcomes, the more motivated they are to act to take steps to avoid those outcomes. Benefits refer to the perceived effectiveness and efficacy of recommended actions or behaviors to reduce the risk or impact of the disease, while barriers relate to beliefs about the tangible and psychological costs of the recommended actions. Thus, the model suggests that if individuals perceive that a particular behavior will yield strong positive benefits, they are more likely to adopt it. Conversely, if individuals perceive barriers preventing them from engaging in preventive behavior, they are less likely to do so (Rosenstock 1966).

Cues to action refer to both internal factors (i.e., physical symptoms or bodily events) and external factors (i.e., advice from others, recommendations through the media or health services) that can trigger action. According to Hochbaum (1958), the activation of cues to action depends of perceived levels of susceptibility and severity. Therefore, this dimension has received limited attention in surveys (more so in content analysis, e.g., Tang and Park 2017) due to its challenging application in explanatory surveys (Champion and Skinner 2008). Self-efficacy refers to an individual’s confidence in their ability to perform a specific behavior and achieve certain results, and it is grounded in the concept of self-conviction in executing a behavior and attaining specific outcomes (Bandura 1997).

Through the use of quantitative methodological approaches, several studies have shown that HBM constructs can predict cancer detection behavior in certain groups within the population (Burak & Meyer 1997; Darvishpour et al. 2018; Lau et al. 2020). Research has shown that perceived barriers and severity of skin cancer (Støle et al. 2019) are significant, as reducing barriers and increasing perceived benefits enhances sun protection behaviors (Pearlman et al. 2021). However, factors such as the time between belief measurement and behavior, as well as types of behaviors, can moderate the predictive power of independent variables (Carpenter 2010). Thus, while the HBM may be useful in predicting cancer prevention behavior in certain populations, its predictive ability should be evaluated based on the specific health behavior context in which it is applied.

Age is considered a crucial factor in skin cancer prevention behavior (Çelik & Koç 2023), as the history of sunburns performs an influential role in the development of skin cancer (Cercato et al. 2015), particularly during the period of highest risk behaviors that could drive to the development of this disease — adolescence and young adulthood (Wu et al. 2018). Nevertheless, perceived susceptibility is inversely proportional to age (Çelik & Koç 2023; Grubbs & Tabano 2000). Although young people have knowledge about the risks of sun exposure and skin cancer, their perception of immortality (Davis et al. 2015) and perceived social norms (Glanz et al. 1999) act as barriers to preventive behavior (Carmel et al. 1994; Davati et al. 2013).

Critics of the HBM have noted several limitations, particularly with regard to its ability to predict actual behavior. While the model is useful for determining the intention of preventive behavior, it pays little attention to the individual variables that influence actual behavior (Janz & Becker 1984; Moreno San Pedro and Gil Roales-Nieto 2003). Furthermore, the absence of an individual experience focus has been considered another limitation of the model. As Davidhizar (1983) agues, a clear understanding of the cause of behavior is necessary for predicting change. Lastly, the model's significant emphasis on the risk and severity of the condition is another critical aspect to consider, as it may provide a simplistic view of health-related decision-making (Carpenter 2010).

Participants and procedure

This study is part of the Research and Development (R&D) project with reference PID2020-116487RB-100, funded by Spanish Ministry of Science and Innovation. The project involves high degrees of innovation, interdisciplinarity, and knowledge transfer, with the participation of five institutions, including universities and hospitals. This research focuses on a population sector identified in Spain as a group at the highest risk of improper photoprotection and susceptibility to the disease: college students.

A statistically representative sample of students from the diverse fields of studyFootnote 1—arts and humanities, sciences, health sciences, social and legal sciences, engineering and architecture — enrolled in Spanish universities through all the country, was recruited for this research through the databases of the Health Universities Network.

Data collection took place between October 2022 and March 2023. Before conducting data collection, the Research Ethics committee from [removed] reviewed and granted ethical approval of the instrument (registration number 1701202201422). The participants who completed the questionnaire adhered to the recommendations of the ethical committee at [removed]. They were not students or former students of any member of the research team. The decision to exclusively target university students aligns with the research project's objectives.

The universe of college students nationwide in Spain is 1,722,247.Footnote 2 The minimum sample figure of 384 students was calculated, with a confidence margin of 95% and a sampling error of 5%. The final sample was 496 completed surveys. Surveys lacking internal coherence, displaying anomalous durations, or being incomplete were excluded. The sample was selected based on predetermined criteria, including age, gender, habitat, and fields of study according to the most up-to-date data from the National Agency for Quality Assessment and Accreditation (ANECA).

The response rate for the online questionnaire was 52.4% of the sample.

Instrumentation

The questionnaire included two sections containing the CHACES epidemiological questionnaire (Blázquez-Sánchez et al. 2020; De Troya-Martín et al. 2009), and the HBM construct. To develop an online questionnaire instrument for this research project, a review of instruments measuring the variables of HBM was conducted. The items on the scales were carefully examined to determinate whether their alignment with the research objectives and to assess their optimal psychometric properties.

Additionally, the Practices, Attitudes and Knowledge related to Sun Exposure (CHACES) epidemiological questionnaire, which has been validated for use with a population over 18 years of age (Blázquez-Sánchez et al. 2020) and to diverse contexts and populations in Spain, was applied.

The questionnaire included also sociodemographic characteristics such as age, gender, educational level, field of study, marital status, and habitat, together with information regarding self-reported phototype and sun-reactive skin type (Author3 n.d; Fitzpatrick 1988). The primary sections of the questionnaire focused on the frequency of sun exposure habits during outdoor activities in various scenarios (across different days of the year and daily hours). It also collected information on the number of sunburns experienced (redness and pain) within the last year. Additionally, the questionnaire included six items related to sun-protection practices and ten tems assessing attitudes toward sun exposure and photoprotection (Author3 n.d). The key variable of the CHACES questionnaire for this research focuses on sunburn experiences as the determinant consequence of sun exposure beliefs, attitudes, and practices. This variable of the CHACES is operationalized based on a single burn, i.e., in two categories: no burns in the last year and one or more burns in the last year.

The wording of some questions was modified to better align them with the research objectives. The final questionnaire underwent validation by a panel of health research experts from the [removed]. Subsequently, a pretest was carried out with 10% of the sample to assess the performance of the variables and the data production software.

Table 1 displays the variables used in this research, which include the HBM constructs used (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy), along with the sunburn experiences.

Table 1 Survey questions and rating scales of HBM model constructs
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Statistical analysis

A descriptive statistical analysis was performed to obtain information on each of the variables. To evaluate statistically significant associations among the HBM variables, Pearson correlations, one-way analysis of variance (ANOVA) and Cronbach's α were employed to calculate internal consistency reliability, together with independent samples t-tests.

To examine the relationship between sunburn in the last year (dependent variable) and the HBM constructs (independent variables), a chi-square analysis was performed. Subsequently, for determining the relative strength and significance of the independent variables concerning the dependent variable and among themselves, a hierarchical clustering based on the chi-square strength was performed.

For all statistical analyses, a level of statistical significance equal to or less than 0.05 was applied. All data analysis was carried out using IBM SPSS Statistics 26.

Results

Agreement levels on HBM variables

Table 2 shows that the HBM variable with the highest degree of agreement is perceived severity (93.8%), specifically the statement ‘skin cancer is a serious disease’. Following closely are perceived benefits (90.9%) and perceived susceptibility (86.3%), corresponding to the statements ‘protecting myself from sun exposure is effective against skin cancer’ and ‘I am likely to get skin cancer if I expose myself to the sun’ respectively.

Table 2 Frequencies and percentages of the HBM variables (N = 496)
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Conversely, cues to action (66.7%), represented by the statement ‘I have experiences, tips, etc. that help me (as triggers) to protect myself from sun exposure’ and perceived barriers (67.7%), which include the statement ‘it is easy to protect myself effectively from sun exposure’ had the lowest percentages of agreement.

Correlation between the HBM variables

Table 3 illustrates the correlation coefficients among all the variables comprising the HBM. All the variables exhibit significant correlations with one another, with very high statistical significance values (p ≤ 0.01), except for the correlation between perceived susceptibility and perceived barriers (R2 = 0.113, p ≤ 0.05), which demonstrates a moderate statistical significance. Notably, strong correlations are observed, particularly between the variables perceived susceptibility and perceived severity (R2 = 0.512, p ≤ 0.01) as well as self-efficacy and perceived barriers (R2 = 0.505, p ≤ 0.01).

Table 3 Pearson correlation coefficients between each pair of HBM indicators
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Relationship between burns and HBM

In the last year, 83.7% of the sample reported experiencing skin burns. Skin burning, in this context, refers to the skin reddening accompanied by pain. Regarding the frequency of burns within a year, 51.2% recognized experiencing burning one and two times during the year. A quarter of the sample claimed to have been burned three to five times a year, while 7.4% reported being burned more than six times in the last year.

The presence of sunburn — having burned or not in the last year — exhibits a very strong statistical significance with the variables perceived susceptibility (p < 0.01) and self-efficacy (p < 0.01). Additionally, it shows a statistical significance with perceived barriers (p < 0.05) and with cues to action (p < 0.02). However, no statistical relationship exists between sunburn and the HBM variables: perceived severity (p > 0.05) and perceived benefits (p  > 0.05).

Figure 1 shows, on the one hand, the statistically significant relationships between the dependent variable — sunburn in the last year — and the independent variables: self-efficacy (p < 0.01), perceived susceptibility (p < 0.01), perceived barriers (p < 0.05), and cues to action (p < 0.02).On the other hand, Fig. 1 illustrates the statistically significant relationships between the independent variables and their hierarchy by degree of significance concerning the dependent variable.

Fig. 1
figure 1

Degree of strength of the chi-square with the HBM and sun burn variables. * The graph shows arrows of two sizes — wide and thin. The wide arrows show the statistically significant relationship between the dependent variable and the independent variables. The thin arrows show the statistically significant relationship between the independent variables. ** Gray arrows are a very strong statistically significant relationship (p  ≤ 0.01). Black arrows are a statistically significant relationship (p ≤  0.05)

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The hierarchical cluster analysis reveals that the variable with the strongest association with sunburn is self-efficacy (p < 0.01), making it the primary node. Subsequently, the second node with the most strength with the dependent variable, and correlated with the primary node, is perceived susceptibility (p < 0.04). From this second node, perceived barriers (p < 0.01) and cues to action (p < 0.02) are also correlated. Several statistical tests have been carried out to check the weight that covariances could have on statistical significance. However, the effect of covariances has not been shown to be decisive.

Discussion

This research aims to analyze the HBM constructs on skin cancer prevention among a high-risk population for this disease. As part of an interdisciplinary project involving five university and hospital institutions with researchers in oncology, dermatology, and communication, this study presents a high degree of transdisciplinary originality by utilizing a methodological instrument that, for the first time, combines the HBM constructs with essential components from a verified epidemiological questionnaire, which bring the individual experience and actual health behavior.

The findings reveal that self-efficacy and perceived susceptibility are key factors influencing preventive behaviors in this population. The study found a statistically significant relationship between self-efficacy — participants’ confidence in their ability to avoid sunburn — and their adoption of sun-protection measures. This suggests that students who believe they can effectively protect themselves from the sun are more likely to engage in preventive behaviors. This finding supports the HBM construct of self-efficacy, which emphasizes the importance of individuals' confidence in their ability to perform health-promoting actions, as highlighted in existing literature (Çelik and Koç 2023).

Perceived susceptibility also plays a crucial role in shaping skin cancer prevention behaviors. The study highlights a significant connection between participants’ awareness of their vulnerability to skin cancer and their engagement in photoprotection practices. This aligns with the HBM's assertion that individuals who perceive themselves as at risk are more motivated to adopt preventive measures (Rosenstock 1966). This finding aligns with other research, such as Davati et al. (2013), which suggests that an increased awareness of susceptibility can serve as a strong cue to action, encouraging individuals to adopt preventive measures against sun exposure. The influence of perceived susceptibility on behavior is moderated by perceived barriers and cues to action, indicating that young students who recognize their risk and encounter reminders to protect themselves avoid the factual behavior of sunburn and are more inclined to engage in preventive behaviors.

However, it is important to note that existing studies also identify additional factors influencing preventive actions. For example, the significance of knowledge or the lack thereof in shaping sun protection behavior among young individuals has been highlighted (Davis et al. 2015). Furthermore, factors related to sun exposure and sunscreen safety are crucial in understanding sun protection behavior (Julian et al. 2020). This study contributes to the existing literature by emphasizing the role of self-efficacy and perceived susceptibility, but it also acknowledges that other factors should be considered in order to gain a comprehensive understanding of skin cancer prevention behavior.

In practical terms, these findings suggest that it is essential to underscore the significance of targeted health education and communication programs aimed at improving skin cancer prevention practices among a high-risk population for this disease (Cambil-Martín et al. 2023; Davis et al. 2015; Julian et al. 2020; Trad and Estaville 2017). By doing so, it could be possible to promote healthier sun protection behaviors to a high-risk population and reduce their vulnerability to this disease. Communication plays a pivotal role in skin cancer prevention (Jiménez-Sánchez et al. 2023), as it contributes to increasing awareness and preventive behaviors among the at-risk population (Calloway et al. 2022; McWhirter and Hoffman-Goetz 2015).

Limitations and future research

This study focuses exclusively on young college students in Spain, which presents a limitation in terms of the generalizability of the findings. The same group at risk in other contexts should be explored to test the validity of the statistical model in other regions. On the other hand, although this group is identified as high-risk due to factors such as increased sun exposure during peak UV hours, lower usage of effective sunscreen, and a higher incidence of sunburn compared to other demographic groups (Blázquez-Sánchez et al. 2020; Cambil-Martín et al. 2023; García-Montero et al. 2020), these findings may not be directly applicable to older adults or individuals with different educational backgrounds. To address this limitation, future research should explore the use of the HBM in investigating how other at-risk populations shape their preventive behaviors, as well as examining their attitude related to photoprotection. Expanding the research scope will help inform and guide future studies and practices into the increasing epidemy of skin cancer that can challenge public health systems.

In addition, this study's analysis is based on the HBM incorporated data from the model's components. Thus, future research could consider other formulations of the model with additional factors, which may provide a more comprehensive understanding of the influences on preventive behaviors in different population groups.

Finally, to mitigate the risk of social desirability bias in survey responses, several measures were implemented. Participants were assured of their anonymity, and the importance of providing honest and accurate responses was emphasized throughout the data collection process. This approach aimed to encourage truthful reporting of behaviors and beliefs related to sun exposure and protection, thereby enhancing the validity of the findings.