The role of beliefs and behavioral intentions in the analysis of community health responses to climate change

Abstract

This study explores the complex relationship between climate change perceptions and health behavior intentions through an extended Health Belief Model (HBM). Given the increasing frequency of climate-related events, such as extreme weather and air quality deterioration, the implications for public health are profound. This study aims to identify how individual beliefs regarding susceptibility to climate-related health issues, perceived severity of these impacts, and the perceived benefits and barriers to action influence health behavior intentions. Data were collected from approximately 500 adults in Iran using an online questionnaire distributed via popular messaging platforms. The survey assessed demographic factors alongside key constructs of the HBM. The findings indicate that individuals who perceive a higher susceptibility and severity regarding climate impacts are more likely to express intentions to engage in health-promoting behaviors. Furthermore, increased environmental concern and social norms significantly enhance these intentions, while perceived barriers and self-efficacy don’t present a notable hindrance. The results underscore the critical need for interdisciplinary public health strategies that integrate climate science and community engagement. By fostering awareness and understanding of climate-related health risks, such strategies can promote proactive health behaviors and enhance community resilience in the face of ongoing climate challenges. This research contributes valuable insights for designing effective public health interventions that resonate with community values and address the multifaceted impacts of climate change on health.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-35106-3.

Introduction

The intersection of public health and environmental sustainability has gained increasing attention in the context of climate change, a global phenomenon that poses significant risks to health and well-being^1,2. As climate-related events, such as extreme weather patterns, rising temperatures, and deteriorating air quality, become more prevalent, understanding the implications for human health is crucial^3,4. The impacts of climate change extend beyond physical health, influencing mental health as well^5,6. Natural disasters and prolonged environmental stressors can lead to increased rates of anxiety, depression, and Post-Traumatic Stress Disorder (PTSD)⁷. Individuals displaced by climate-related events often face uncertainty and loss, contributing to mental health challenges that can persist long after the initial event³. Furthermore, the psychological toll of witnessing environmental degradation and the potential for future disasters can lead to a phenomenon known as “eco-anxiety,” which affects individuals’ overall well-being and quality of life⁸. These shifts pose significant public health challenges, particularly in regions that may not have previously experienced these diseases, necessitating enhanced surveillance and response strategies to protect populations at risk. Lastly, climate change threatens food security and nutrition, impacting health outcomes on a global scale¹. Changing weather patterns can disrupt agricultural productivity, leading to reduced crop yields and increased food prices^9,10. This not only affects access to nutritious food but also contributes to malnutrition and related health issues, particularly in low-income populations¹¹. As food systems become more vulnerable to climate variability, the need for sustainable agricultural practices and adaptive strategies becomes increasingly critical to safeguard public health¹². Individuals’ perceptions of climate change significantly influence their health behaviors and decision-making processes¹³. Understanding how people interpret the risks associated with climate change is essential for developing effective public health interventions¹⁴. Factors such as personal beliefs, social influences, and environmental awareness play pivotal roles in shaping individuals’ responses to climate-related health threats¹⁵.

Research grounded in the Health Belief Model (HBM) consistently demonstrates that individuals’ perceptions of susceptibility to health risks, perceived severity of those risks, and perceived benefits and barriers to action are central determinants of health behavior intentions^16–21. While these cognitive constructs provide a robust foundation for understanding health-related decision-making, the multifaceted and systemic nature of climate change necessitates a broader conceptual lens that extends beyond individual risk appraisals. Climate-related health behaviors are shaped not only by personal beliefs but also by social, normative, and environmental contexts that influence how risks are interpreted and acted upon. In this regard, Steg et al. (2014) proposed an integrative framework suggesting that pro-environmental behaviors are guided by a combination of hedonic, gain, and normative goals, arguing that strengthening normative considerations can promote environmentally relevant actions even when such behaviors entail personal costs. This perspective highlights the importance of environmental concern and social norms in sustaining pro-environmental engagement by appealing to individuals’ perceptions of what they ought to do, rather than relying solely on economic or self-interested motivations²². Supporting this view, recent multi-country evidence indicates that environmental concern and perceived behavioral control are strong predictors of pro-environmental intentions, while social norms, although comparatively weaker, remain statistically significant contributors²³. Additional research emphasizes that social norms play a critical role in addressing global environmental challenges by shaping individual behaviors, reinforcing collective responsibility, and interacting with policy instruments to support long-term behavior change²⁴. Experimental studies further substantiate the influence of social norms on pro-environmental behavior. Evidence from social dilemma paradigms demonstrates that normative cues are consistently associated with higher levels of environmentally responsible behavior, with descriptive norms often exerting stronger associations than injunctive or prohibitive norms²⁵. Similarly, experimental findings suggest that social norms remain positively associated with pro-environmental behavior across varying levels of personal cost, with personal norms serving as a key psychological mechanism linking normative information to environmentally responsible choices²⁶. Together, these findings underscore the relevance of normative and psychosocial processes in shaping responses to environmental challenges. Parallel insights emerge from health-related research, where health behaviors are increasingly understood as embedded within broader social and structural contexts. Prior studies consistently show that socioeconomic conditions, cultural norms, and social support structures play a significant role in shaping individual health-related choices and practices²⁷. Accordingly, health behaviors cannot be fully explained by individual-level cognitive models alone, as social determinants and contextual factors interact with psychological processes to influence behavioral patterns across populations²⁸. Empirical evidence from cross-sectional studies further indicates that social and psychological factors, such as family environment, peer influence, and perceived social norms, are significantly associated with health behaviors across diverse demographic and cultural settings²⁹. Despite growing recognition of these broader influences, much of the existing climate–health literature continues to focus primarily on the direct health impacts of climate change, including heat-related illnesses and respiratory diseases, with relatively limited attention to the psychosocial factors that shape individuals’ behavioral responses to these risks^30–32. Recent qualitative research highlights that health behaviors emerge from dynamic interactions among individual beliefs, social relationships, and environmental contexts, suggesting that models centered solely on individual cognition may insufficiently capture the complexity of health behavior change³³. Complementing this view, research on social determinants of health emphasizes that health status and health-related behaviors are strongly shaped by psychosocial and structural factors, such as socioeconomic conditions, social relationships, cultural context, and environmental exposures, which interact with individual psychological processes to influence health outcomes³⁴. Critiques of the HBM have similarly noted that the model primarily emphasizes cognitive constructs such as perceived susceptibility, perceived severity, perceived benefits, and perceived barriers, and may insufficiently account for social and contextual influences on health behaviors. Recent studies, however, suggest that HBM cognitions are not static but dynamically shaped by situational and environmental factors. For example, perceived susceptibility has been shown to mediate the relationship between environmental conditions and preventive behavioral intentions, highlighting the responsiveness of cognitive beliefs to contextual cues³⁵. Other research demonstrates that health beliefs interact with social support and resource-related factors to influence preventive health behaviors, underscoring the importance of integrating psychosocial and contextual dimensions into cognitively oriented health behavior models³⁶. Incorporating these broader determinants alongside traditional cognitive components may therefore provide a more comprehensive understanding of health behavior change, particularly in complex contexts such as climate change where social, environmental, and psychological factors intersect³⁷.

The paucity of integrated frameworks that simultaneously consider cognitive, social, and contextual influences limits the development of public health interventions that meaningfully resonate with community values ​​and behavioral realities. In response to this gap, the present study examines how individual beliefs and perceptions are associated with health behavior intentions in the context of climate change in Iran, while extending the Health Belief Model (HBM) to incorporate climate-relevant dimensions such as environmental concern and social norms. Rather than introducing novel constructs, this approach situates well-established psychosocial factors within an HBM-based framework to better capture the complexity of climate-related health behaviors. Moreover, to address limitations in existing research on pro-health climate behaviors, particularly in understudied regions, this study moves beyond the predominant focus on single climate hazards, such as heatwaves, that characterizes much of the current HBM literature³⁸. Instead, it considers a broader range of climate change impacts on health, reflecting the cumulative and interconnected nature of climate-related risks. By adopting this broader perspective and situating the analysis within Iran’s distinctive socio-cultural context, the study provides context-sensitive insights into how communities interpret and respond to climate-related health threats. Iran’s unique socio-political landscape, characterized by a complex interplay of environmental challenges, public health concerns, and governmental policies, makes it a critical site for studying community health responses to climate change^1,3,39. These conditions underscore the need for a deeper understanding of how health beliefs, social norms, and environmental perceptions interact to influence preventive health behaviors. Examining these dynamics offers an opportunity to identify pathways through which individual-level beliefs can be leveraged to support proactive health behaviors and strengthen community resilience in the face of escalating environmental risks.

Taken together, the multifaceted impacts of climate change on human health highlight the need for comprehensive and contextually grounded public health strategies. Addressing these challenges requires interdisciplinary approaches that integrate climate science, public health perspectives, and an understanding of community-level beliefs and norms. By exploring the relationships between climate perceptions, health beliefs, and behavioral intentions, this study seeks to inform the design of more effective, culturally responsive public health interventions aimed at promoting adaptive health behaviors in the context of a changing climate.

Theoretical framework and hypotheses

The extended HBM integrates traditional components of the HBM with additional dimensions relevant to climate change and public health. This framework, which is shown in Fig. 1, aims to explore how individual beliefs and behaviors related to health are influenced by perceptions of climate change and environmental factors⁴⁰. The first component, perceived susceptibility, refers to individuals’ beliefs about their likelihood of experiencing health issues due to climate change⁴¹. Understanding how people assess their personal risk can inform targeted interventions^20,42. The second component, perceived severity, involves the belief in the seriousness of health consequences arising from climate change⁴³. Highlighting the potential severity of health impacts can motivate individuals to take action^44,45. The third component, perceived benefits, reflects the belief that specific actions can reduce health risks associated with climate change⁴⁶. Identifying clear benefits can encourage individuals to adopt healthier and more sustainable behaviors^47,48. Conversely, the fourth component, perceived barriers, encompasses the obstacles individuals perceive that may prevent them from taking action against health risks related to climate change⁴⁹. Addressing these barriers is crucial for designing effective public health campaigns^20,50. Cues to action, the fifth component, consists of external triggers that prompt individuals to take health-related actions in response to climate change. Effective cues can enhance awareness and motivation to change behaviors^42,51. The sixth component, self-efficacy, pertains to individuals’ confidence in their ability to successfully perform behaviors that mitigate health risks from climate change⁵². Enhancing self-efficacy can empower individuals to take proactive steps. The seventh component, environmental concern, denotes the degree to which individuals are worried about environmental issues and their impact on health⁵³. Higher levels of environmental concern can correlate with increased health behavior intentions⁵⁴. The eighth component, social norms, reflects the perceived social pressures or norms regarding environmental and health behaviors⁵⁵. Understanding social influences can help shape interventions that leverage community support⁵⁶.

Fig. 1.

The conceptual framework of Extended HBM.

Lastly, knowledge and awareness represent the level of understanding individuals have about the health impacts of climate change and the actions they can take⁵⁷. Increasing knowledge can lead to greater awareness and informed decision-making. Social norms, knowledge and awareness, and environmental concern were selected as extensions to the extended HBM, rather than just control variables, because they are hypothesized to be integral components influencing health behavior intentions within the context of climate change, actively shaping individual beliefs and perceptions related to susceptibility, severity, benefits, and barriers. These constructs are not merely confounding factors but active contributors that directly impact how individuals perceive and respond to climate-related health risks, making them essential for understanding the complex interplay between environmental awareness, social influences, and proactive health behaviors.

This extended conceptual framework of the HBM provides a comprehensive approach to understanding how beliefs about health, influenced by climate change, shape individual intentions and behaviors. By integrating additional dimensions such as environmental concern, social norms, and knowledge, the framework allows for a more nuanced exploration of the factors that drive health-related decision-making in the context of a changing climate. This model can serve as a foundation for future research and public health interventions aimed at promoting health and sustainability. This study proposes several hypotheses based on the extended HBM to explore the relationships between health beliefs, climate change perceptions, and health behavior intentions related to climate change. All hypotheses are shown in the Table 1.

Table 1.

The study hypotheses.

Independent constructs	Dependent construct	Hypotheses	Expected sign
Perceived Susceptibility →	Health Behavior Intentions	1. Individuals who perceive a higher susceptibility to health risks from climate change are more likely to intend to engage in health-promoting behaviors.	Positive
Perceived Severity →		2. A greater perception of the severity of health impacts from climate change is likely associated with an increased likelihood of taking preventive health actions.	Positive
Perceived Benefits →		3. Individuals who believe in the benefits of taking action against climate change are more likely to intend to adopt those behaviors.	Positive
Perceived Barriers →		4. Higher perceived barriers to action against climate change are likely to be negatively related to health behavior intentions.	Negative
Cues to Action →		5. Exposure to cues (e.g., media, social initiatives) is likely to positively influence individuals’ intentions to engage in health-promoting behaviors related to climate change.	Positive
Self-Efficacy →		6. Greater self-efficacy is likely to be positively associated with intentions to take action against climate change and improve personal health.	Positive
Environmental Concern →		7. Higher levels of environmental concern are likely to be positively related to intentions to engage in sustainable and health-promoting behaviors.	Positive
Social Norms →		8. Individuals who perceive that their peers engage in eco-friendly behaviors are more likely to intend to adopt similar actions.	Positive
Knowledge and Awareness →		9. Increased knowledge and awareness about the health impacts of climate change are more likely to be positively associated with intentions to take preventive actions.	Positive
Perceived Benefits →	Perceived Barriers	10. Perceived benefits may mediate the relationship between perceived barriers and health behavior intentions.	Negative
Self-Efficacy →	Cues to Action	11. Higher self-efficacy may enhance responsiveness to cues that promote health-related actions.	Positive
Knowledge and Awareness →	Perceived Susceptibility	12. Increased knowledge about climate change may influence how susceptible individuals feel to its health effects.	Positive
Social Norms →	Environmental Concern	13. Social norms may influence individuals’ levels of environmental concern, impacting their health behavior intentions.	Positive

The mediation hypotheses, rooted in the theoretical underpinnings of the extended HBM, are designed to dissect the complex relationships between constructs and health behavior intentions. Besides the HBM, other theories have been used to address heatwaves, such as the Theory of Planned Behavior (TPB). However, this theory mostly focuses on attitudes, social norms, and perceived control over behavior with a broader focus that extends beyond health-specific contexts. The HBM is one of the most widely used models and explains why individuals engage in health behaviors such as seeking advice or undergoing assessment for health concerns. The HBM was therefore chosen because it addresses individual beliefs and perceptions related to health threats and to engage in protective actions. This approach is based on the premise that certain factors may not directly influence behavior but rather operate through intermediary variables. Although knowledge and awareness may automatically translate into action; they might also enhance an individual’s perception of susceptibility, which then drives behavioral intentions¹⁶. Similarly, self-efficacy, while directly impacting intentions, might empower individuals to respond effectively to cues to action, highlighting its role as a facilitator of behavioral change⁵⁸. These mediation effects align with social cognitive theory, which emphasizes the reciprocal interactions between personal, behavioral, and environmental factors in shaping health behaviors⁵⁹. By examining these indirect pathways, the study aims to provide a more nuanced understanding of how interventions targeting specific constructs can have cascading effects on other factors, ultimately influencing health-related decision-making within the context of climate change.

Material and method

Study location

This study is conducted in Iran, a country characterized by diverse climatic conditions, geographical features, and a range of public health challenges⁶⁰. Iran’s varied landscape includes mountainous regions, deserts, and coastal areas, contributing to significant regional differences in climate and environmental challenges⁶¹. As a country situated in a semi-arid region, Iran is particularly vulnerable to the impacts of climate change, including rising temperatures and altered precipitation patterns^1,62. According to the Iranian Meteorological Organization, average temperatures in Iran have increased by approximately 1.9 °C over the past century, with projections indicating a further rise of 2 to 5 °C by 2050. The Iranian population is facing a range of health issues exacerbated by climate change. The World Health Organization (WHO) estimates that climate change will result in an additional 1,800 deaths annually in Iran due to heat-related illnesses and respiratory diseases. The selected provinces included Tehran, Gilan, Mazandaran, and Golestan in the northern region; Bushehr and Hormozgan in the southern region; Esfahan, Yazd, and Qom in the central region; South Khorasan in the eastern region; Kermanshah, Kordestan, and Ilam in the western region; and Sistan-Baluchestan in the southeastern region.

Sample size calculation

An a priori sample size calculation was conducted using G*Power version 3.1 to determine whether the achieved sample was sufficient to detect statistically meaningful relationships. Although the primary analytical approach of the study was Structural Equation Modeling (SEM), G*Power was used to approximate the structural component of the model as a multiple linear regression, a commonly accepted approach when the primary endogenous construct is predicted by multiple exogenous variables⁶³. In the present study, health behavior intentions constituted the main dependent variable and were predicted by nine constructs derived from the extended HBM, including perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, self-efficacy, environmental concern, social norms, and knowledge and awareness. The power analysis was specified under the F-test family using the statistical test “linear multiple regression: fixed model, R² deviation from zero.” A conservative small effect size (f² = 0.05) was selected to ensure adequate sensitivity to detect modest but meaningful effects. The significance level (α) was set at 0.05, and the desired statistical power (1–β) was set at 0.80. The number of predictors was specified as nine, corresponding to the number of constructs directly predicting health behavior intentions in the structural model. Under these parameters, G*Power indicated a minimum required sample size of 332 participants.

The final sample size of approximately 500 respondents exceeded this minimum requirement, providing a substantial margin of statistical power. This larger sample size enhances the stability of parameter estimates, increases the precision of effect size estimation, and supports the reliable testing of complex relationships within the SEM framework. Sensitivity analysis further suggests that with a sample size of 500, the study achieves power greater than 0.90 even under conservative assumptions, confirming that the sample size is sufficient to draw robust and reliable conclusions.

Sampling technique

For this study, we employ convenience sampling to collect data through an online questionnaire. Participants are recruited primarily through popular messaging platforms such as WhatsApp and Telegram, which are widely used in Iran for communication. By utilizing these channels, we aim to reach a diverse group of individuals across various provinces and geographic regions. This strategy is particularly relevant given the high penetration of these platforms, facilitating broad participation. The online questionnaire is made available in both Persian and English to ensure inclusivity and accessibility for a wider audience. We specifically target adults aged 18 and older, as this age group is more likely to reflect on their health beliefs and behaviors in relation to climate change. Our goal is to achieve a sample size of approximately 500 participants. The sample consists of 80 participants from Tehran province; 20 from Gilan; 22 from Mazandaran; 18 from Golestan; 22 from Bushehr; 16 from Hormozgan; 22 from Kermanshah; 16 from Ilam; 17 from Kurdistan; 43 from South Khorasan; 61 from Esfahan; 32 from Yazd; 18 from Qom; and 19 from Sistan and Baluchestan. The data collection process was carried out between June and September 2024. All methods were carried out following relevant guidelines and regulations. Informed consent was obtained from all subjects and/or their legal guardian(s) prior to participation in the study. Also, this study was conducted in accordance with the relevant guidelines and regulations. The demographic data from the study samples showed that 69% of the respondents were male, indicating a majority male representation in the sample. In terms of marital status, 78% of the participants were married. The educational attainment of the respondents is noteworthy, with 30% holding doctorates, 36% possessing master’s degrees, 20% having bachelor’s degrees, and 14% classified as undergraduates. Also, the average age of the respondents was 40 years.

Data collection instrument

The data for this study is collected using an online questionnaire designed to assess health beliefs, perceptions of climate change, and health behavior intentions among participants in Iran. The questionnaire is structured to include several sections, each targeting specific constructs relevant to the study’s objectives (Table A1). Initially, the questionnaire gathers demographic information, including age, gender, education level, geographic location, and socioeconomic status. Following this, a section focuses on health beliefs and perceptions of climate change, which assess participants’ beliefs about their susceptibility to health issues related to climate change, the perceived severity of these health impacts, perceived benefits of taking action, and perceived barriers to engaging in health-promoting behaviors. The items in this section are based on Likert scales and adapted to ensure cultural relevance for the Iranian context. Additionally, the questionnaire explores cues to action by asking participants about external triggers that motivate them to consider the health impacts of climate change, such as media exposure, community initiatives, and personal experiences with climate-related events. Another important section evaluates self-efficacy, measuring participants’ confidence in their ability to engage in behaviors that mitigate health risks associated with climate change, including the perceived capacity to make lifestyle changes. The questionnaire also assesses participants’ environmental concern and social norms, capturing levels of worry about environmental issues and perceived social pressures to adopt sustainable behaviors. Following this, a section focuses on knowledge and awareness, gauging participants’ understanding of the health impacts of climate change and the actions they can take to mitigate these effects. Finally, participants indicate their intentions to engage in specific health-promoting behaviors, such as reducing their carbon footprint and participating in community initiatives.

Instrument validation procedure

The development and validation of the questionnaire followed a multi-stage process to ensure conceptual clarity, cultural appropriateness, and statistical robustness. The initial pool of items was generated after an extensive review of validated HBM instruments and climate-health behavioral research. All questionnaire items were revised and rewritten by the research team based on established theoretical constructs and adapted to reflect the sociocultural context of Iran, ensuring relevance to climate-related health perceptions. After drafting the instrument, a preliminary version was subjected to a pilot test involving 15 adult participants from different provinces. The purpose of this pilot test was to evaluate face validity, clarity of item wording, and respondent comprehension. Feedback from the pilot participants led to several refinements, including rephrasing ambiguous items, removing redundancies, adjusting culturally sensitive terminology, and improving the overall layout to enhance usability. Following pilot revision, the final instrument underwent comprehensive psychometric evaluation using the full study sample. Reliability assessment focused on internal consistency, which was evaluated through Cronbach’s alpha, Rho-A, and Composite Reliability (CR). All constructs exceeded the commonly accepted reliability threshold of 0.70, indicating satisfactory internal coherence among items⁶⁴. Construct validity was assessed by convergent and discriminant validity tests. Convergent validity was confirmed by Average Variance Extracted (AVE), with all constructs attaining AVE values beyond 0.50, indicating that items within each construct shared a sufficient proportion of variance⁵⁶. Outer loadings for all elements were assessed, with values exceeding 0.70 signifying robust indicator dependability. Variance Inflation Factor (VIF) values were computed for all items to evaluate potential multicollinearity, with all values much below the recommended threshold of 5, confirming that the constructs were separate and not overly associated⁶⁵. The multi-layered validation process, which included theoretical grounding, pilot testing, internal consistency reliability, convergent validity, and multicollinearity checks, confirmed the questionnaire’s robust psychometric adequacy for evaluating health beliefs, climate-change perceptions, and behavioral intentions among adult populations in Iran.

Statistical technique

The data collected from the online questionnaire will be analyzed using Structural Equation Modeling (SEM) to assess the relationships among health beliefs, perceptions of climate change, and health behavior intentions among participants in Iran. SEM is a powerful statistical technique that allows for the examination of complex relationships between observed and latent variables, making it particularly suitable for exploring the interconnectedness of health beliefs and behaviors in the context of climate change⁶⁴. Initially, descriptive statistics are calculated to summarize the demographic characteristics of the sample, including age, gender, education level, and marital status. Frequencies, means, and standard deviations are provided as an overview of participants’ health beliefs, climate change perceptions, and reported health behaviors. Before conducting SEM, the reliability of the measurement scales is assessed using Cronbach’s alpha to ensure that the items within each construct are internally consistent¹. The SEM approach is used to test the hypothesized relationships outlined in the study framework. This process begins with model specification, where the initial model is defined based on theoretical constructs, including paths that represent the relationships among latent variables³. Next, model estimation will be performed using maximum likelihood estimation, allowing us to derive estimates for path coefficients that indicate the strength and direction of relationships between variables⁹.

To evaluate relationships between indicators and constructs, outer loadings are assessed, with values above 0.70 indicating strong reliability⁶⁶. The VIF identifies multicollinearity, with acceptable values below 5⁵⁶. Internal consistency is measured using Rho-A and CR, both requiring values above 0.70 for reliability. Convergent validity was determined through AVE, with satisfactory values exceeding 0.50. For model fit, the SRMR should be below 0.08, while a lower d-ULS value indicates a better fit. Additionally, model goodness-of-fit is often evaluated using indices such as the CFI, TLI, and RMSEA, with CFI and TLI values above 0.90 and RMSEA below 0.08 indicating an acceptable fit⁵⁶.

Results

Pre-estimation statistics

The statistics from the estimated SEM model provide important insights into the model’s fit and validity. Firstly, the SRMR value of 0.018 indicates an excellent fit for the model. Generally, an SRMR value below 0.08 is considered acceptable, and values below 0.05 suggest a good fit. Therefore, a value of 0.018 implies that the model’s predicted values are very close to the observed values, supporting the model’s validity. The d-ULS statistic of 4.23 is another indicator of model fit. The lower this value, the better the fit of the model. While specific thresholds for d-ULS can depend on the context, a value of 4.23 suggests that the model has a reasonable fit, though comparisons to other models would provide a clearer context. Also, a CFI (equal to 0.93) and TLI (equal to 0.94) above 0.90 suggest that the model provides a good approximation of the observed data.

According to Table 2, the VIF values for all items were below 3, suggesting that multicollinearity is not a significant concern in this model. Lastly, factor loadings greater than 0.7 for all items indicate strong relationships between the observed variables and their respective latent constructs. This suggests that each item is a good indicator of the underlying construct it is intended to measure, further validating the model. Overall, the results indicate strong reliability and validity for all constructs, with Cronbach’s Alpha values ranging from 0.704 to 0.946, surpassing the generally accepted threshold of 0.70. Similarly, the Rho-A and Composite Reliability (CR) values for all constructs were above 0.7, further supporting their internal consistency. The AVE values for all constructs were above 0.5, demonstrating adequate convergent validity, with the exception of social norms which showed an AVE of 0.506 which is still acceptable.

Table 2.

Descriptive analysis of all items and reliability and validity statistics.

Construct	Items	Outer loading	VIF	Mean	Average	Reliability and validity statistics
Perceived Susceptibility	PS1	0.746	1.201	1.91	1.86	CA = 0.786 rho_A = 0.762 CR = 0.781 AVE = 0.637
	PS2	0.841	1.996	1.83
	PS3	0.840	2.006	1.89
	PS4	0.885	1.335	1.84
	PS5	0.852	1.402	1.84
Perceived Severity	PE1	0.823	1.565	2.50	1.97	CA = 0.704 rho_A = 0.833 CR = 0.806 AVE = 0.689
	PE2	0.866	1.647	1.89
	PE3	0.878	2.285	1.82
	PE4	0.828	1.550	1.97
	PE5	0.865	1.027	1.68
Perceived Benefits	PB1	0.821	1.735	1.84	1.76	CA = 0.706 rho_A = 0.749 CR = 0.809 AVE = 0.649
	PB2	0.790	1.693	1.83
	PB3	0.768	1.204	1.72
	PB4	0.712	1.414	1.89
	PB5	0.764	1.149	1.55
Perceived Barriers	PR1	0.748	1.064	4.19	3.93	CA = 0.727 rho_A = 0.790 CR = 0.827 AVE = 0.512
	PR2	0.798	2.119	4.24
	PR3	0.857	2.291	4.49
	PR4	0.752	1.838	4.42
	PR5	0.763	1.087	2.30
Cues to Action	CA1	0.834	2.161	1.88	2.67	CA = 0.733 rho_A = 0.821 CR = 0.873 AVE = 0.519
	CA2	0.878	2.153	1.76
	CA3	0.780	2.191	1.77
	CA4	0.752	2.558	4.01
	CA5	0.797	2.455	3.91
Self-Efficacy	SE1	0.828	1.382	3.92	2.30	CA = 0.749 rho_A = 0.830 CR = 0.760 AVE = 0.543
	SE2	0.819	1.449	1.91
	SE3	0.886	2.737	1.93
	SE4	0.808	1.871	1.86
	SE5	0.908	2.285	1.88
Environmental Concern	EC1	0.917	2.012	4.11	2.09	CA = 0.946 rho_A = 0.951 CR = 0.959 AVE = 0.824
	EC2	0.868	2.847	4.16
	EC3	0.948	2.710	4.12
	EC4	0.914	2.877	4.03
	EC5	0.890	2.640	4.03
Social Norms	SN1	0.769	2.123	1.95	1.91	CA = 0.758 rho_A = 0.770 CR = 0.835 AVE = 0.506
	SN2	0.724	2.026	1.96
	SN3	0.718	1.713	1.93
	SN4	0.739	2.102	1.86
	SN5	0.793	1.638	1.83
Knowledge and Awareness	KA1	0.794	2.425	1.94	1.83	CA = 0.756 rho_A = 0.779 CR = 0.837 AVE = 0.513
	KA2	0.723	2.140	1.80
	KA3	0.786	1.949	1.81
	KA4	0.833	2.472	1.80
	KA5	0.704	1.641	1.82
Health Behavior Intentions	HB1	0.714	2.809	1.91	1.84	CA = 0.809 rho_A = 0.824 CR = 0.868 AVE = 0.579
	HB2	0.717	2.540	1.87
	HB3	0.813	2.210	1.88
	HB4	0.859	2.353	1.76
	HB5	0.753	2.168	1.77

Statistical analysis outcomes

The results of the analysis, as presented in Table 3, detail both the direct and indirect associations of constructs within the HBM on health behavior intentions. The analysis revealed that cues to action was significantly associated with health behavior intentions, with a coefficient of 0.217. This indicates that increased cues to action are associated with higher intentions to engage in health-promoting behaviors. Similarly, environmental concern demonstrated a positive association with health behavior intentions, yielding a coefficient of 0.114. This suggests that individuals who exhibit greater environmental concern are more likely to intend to adopt health behaviors. Additionally, knowledge and awareness had a robust direct association with health behavior intentions, with a coefficient of 0.222, highlighting that higher levels of knowledge and awareness about health issues significantly enhance intentions to act. Furthermore, perceived severity showed a strong positive relationship with health behavior intentions, with a coefficient of 0.247. This finding indicates that individuals who perceive health impacts as more severe are more likely to engage in health-promoting actions. In contrast, perceived susceptibility had a marginally significant association with health behavior intentions, with a coefficient of 0.055, suggesting that the perception of personal susceptibility to health risks can be positively associated with intentions to take action. While self-efficacy was significantly related to cues to action, demonstrating that higher self-efficacy enhances the likelihood of responding to cues, its direct association with health behavior intentions was not significant. On the other hand, social norms were positively associated with both environmental concern and health behavior intentions, indicating that perceived social pressures and norms are critical in shaping both environmental awareness and health behaviors. In terms of perceived barriers, the results showed a negligible positive association with health behavior intentions, suggesting that perceived barriers did not significantly hinder intentions to engage in health-promoting behaviors. Additionally, perceived benefits exhibited no significant association with health behavior intentions, although it negatively associated with perceived barriers, highlighting a potential relationship where recognizing benefits may help reduce perceived barriers. The analysis also identified several indirect associations. Notably, knowledge and awareness were positively associated with health behavior intentions with a coefficient of 0.050, suggesting that increased knowledge may enhance intentions through other mediators. Similarly, self-efficacy had a notable indirect association with health behavior intentions, indicating that self-efficacy may promote health behaviors indirectly through other constructs. Furthermore, social norms exhibited a positive indirect association with health behavior intentions, underscoring the importance of social influences in shaping behavioral intentions. In contrast, the indirect association of perceived benefits with health behavior intentions were not significant, indicating that perceived benefits alone may not be significantly associated with intentions through indirect pathways.

Table 3.

The direct associations of all constructs in the HBM.

Direct association	Coefficient	Standard deviation	T Statistics	P Values	Hypothesis
Cues to Action -> Health Behavior Intentions	0.217	0.076	2.873	0.004	Accept
Environmental Concern -> Health Behavior Intentions	0.114	0.027	4.225	0	Accept
Knowledge and Awareness -> Health Behavior Intentions	0.222	0.044	5.101	0	Accept
Knowledge and Awareness -> Perceived Susceptibility	0.905	0.01	94.79	0	Accept
Perceived Barriers -> Health Behavior Intentions	-0.004	0.011	-0.379	0.705	Reject
Perceived Benefits -> Health Behavior Intentions	0.018	0.012	1.544	0.123	Reject
Perceived Benefits -> Perceived Barriers	-0.515	0.051	-10.066	0	Accept
Perceived Severity -> Health Behavior Intentions	0.247	0.042	5.812	0	Accept
Perceived Susceptibility -> Health Behavior Intentions	0.055	0.028	1.976	0.049	Accept
Self-Efficacy -> Cues to Action	0.925	0.01	91.687	0	Accept
Self-Efficacy -> Health Behavior Intentions	0.038	0.034	1.129	0.26	Reject
Social Norms -> Environmental Concern	0.751	0.032	23.324	0	Accept
Social Norms -> Health Behavior Intentions	0.242	0.037	6.557	0	Accept

Indirect	Coefficient	Standard Deviation	T Statistics	P Values
Knowledge and Awareness -> Health Behavior Intentions	0.05	0.025	1.965	0.05	Reject
Perceived Benefits -> Health Behavior Intentions	0.002	0.006	0.365	0.715	Reject
Self-Efficacy -> Health Behavior Intentions	0.201	0.07	2.863	0.004	Accept
Social Norms -> Health Behavior Intentions	0.085	0.022	3.937	0	Accept

Figure 2 summarizes the results from the estimated SEM model. The figure illustrates that some constructs are positively and significantly associated with the health behavior intentions due to climate change. In contrast, two constructs, including perceived benefits and barriers display a negative association with this intention. Additionally, the results confirm the indirect significant association of knowledge and awareness, and perceived benefits with health behavior intentions in the climate change condition.

Fig. 2.

Structural equation modelling on the association of all constructs with health behavior intention in climate change condition (Path model with t-values).

Discussion

Model-based discussion

This study illuminates the complex interplay of individual beliefs, social norms, and environmental concern in shaping intentions to adopt health-protective behaviors amidst climate change in Iran. By extending the HBM, we reveal that while constructs like perceived severity, cues to action, and knowledge are significant drivers, the association of social norms and the potential cultural context are uniquely significant, revealing both alignment with established theories and unique contextual nuances shaped by cultural values and policy influences. The significant positive association of cues to action, environmental concern, and knowledge and awareness with health behavior intentions underscore the importance of external motivators and informed decision-making in promoting health-related behaviors. The positive association of cues to action aligns with existing literature suggesting that prompt interventions can enhance individual health behaviors⁶⁷. Similarly, the role of environmental concern as a predictor of health behavior intentions supports previous research indicating that increased awareness of environmental issues can enhance proactive health behaviors⁶⁸. The positive association of knowledge and awareness with health behavior intentions further emphasizes the necessity of educational initiatives in public health campaigns. Previous studies have consistently shown that informed individuals are more likely to engage in health-promoting behaviors^69,70. This is particularly relevant in the context of climate change, where knowledge about health risks can empower individuals to take action⁷¹.

The findings also reveal the significance of perceived severity in shaping health behavior intentions. This is consistent with the HBM’s premise that individuals are more likely to act when they perceive a serious threat to their health^20,21. The marginally significant association of perceived susceptibility with health behavior intentions indicates that individual perceptions of vulnerability can also play a role, albeit to a lesser extent than severity⁴⁵. These results highlight the need for public health messaging to effectively convey the seriousness of health issues related to climate change to motivate behavior change^72,73.

Interestingly, the association of self-efficacy with health behavior intentions was not significant. This contrasts with prior research that emphasizes the role of self-efficacy in facilitating health-promoting behaviors^58,74,75. The non-significant association of self-efficacy with health behavior intentions, while seemingly contradictory to established literature, may be indicative of cultural or contextual factors specific to Iran. It is possible that in this setting, external factors like social norms and governmental policies play a more dominant role, overshadowing the direct impact of individual self-confidence. Alternatively, it’s plausible that self-efficacy acts primarily through other constructs, such as cues to action. However, the strong relationship between self-efficacy and cues to action suggests that enhancing self-efficacy might be crucial for individuals to respond to environmental cues effectively. As such, interventions aimed at building self-efficacy could be vital in increasing responsiveness to prompts for healthy behaviors^75,76.

Social norms emerged as a significant predictor of both environmental concern and health behavior intentions. This aligns with social cognitive theory, which posits that individuals are influenced by the behaviors and attitudes of those around them⁷⁷. Also, the significant association of social norms with both environmental concern and health behavior intentions warrants further consideration within the Iranian context. Iran’s collectivist culture, where social harmony and conformity are highly valued, may amplify the impact of perceived social pressures to engage in pro-environmental and pro-health actions⁷⁸. Moreover, governmental policies promoting environmental stewardship or specific health behaviors may further reinforce these social norms, creating a social environment in which individuals feel a strong obligation to act in accordance with societal expectations⁷⁹. The findings suggest that fostering supportive social environments may enhance both awareness of environmental issues and the intention to engage in health-promoting behaviors. Contrary to expectations and some prior research^20,42, perceived barriers did not significantly hinder intentions to engage in health-promoting behaviors. This could suggest that the participants in this study, perhaps due to cultural resilience or a strong sense of collective responsibility, are less deterred by practical obstacles than individuals in other contexts. It is also possible that government subsidies or community-level support systems alleviate some of the typical barriers associated with sustainable choices, warranting further investigation. This finding suggests that public health interventions should focus on addressing perceived benefits and enhancing knowledge rather than solely mitigating barriers. Additionally, while perceived benefits did not show a significant association, its inverse association with perceived barriers suggests that understanding the benefits of health behaviors may help reduce perceived obstacles.

The positive association between environmental concern and health behavior intentions underscores the interconnected nature of environmental sustainability and public health. Individuals who recognize the direct link between environmental conditions and health outcomes appear more motivated to engage in health-promoting behaviors, driven by a sense of personal responsibility and concern for future generations^1,3,80,81. This finding emphasizes the importance of integrating environmental considerations into public health frameworks, leveraging environmental awareness to catalyze meaningful and lasting behavior change.

The indirect associations observed in this study highlight the complexity of the relationships among constructs within the HBM. The indirect association of knowledge and awareness with health behavior intentions suggests that increased knowledge may promote behavior change through mediators, reinforcing the need for comprehensive educational strategies. Similarly, the indirect association of self-efficacy indicates its importance in facilitating health behavior intentions through other constructs.

Country-based discussion

Previous research employing the Health Belief Model (HBM) in the context of climate change–related health behaviors has predominantly focused on a fundamental set of cognitive constructs, such as perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy, across various international settings³⁸. To expand upon this line of inquiry, the current study integrated additional psychosocial dimensions namely social norms, knowledge and awareness, and environmental concern which prior research has identified as pertinent factors influencing climate-related health behavior intentions, including within the Iranian context^68,82,83. Integrating these constructs into the HBM framework facilitates a more comprehensive analysis of how individual beliefs interact with social and environmental factors in influencing health-related responses to climate change. Although multiple studies have employed the HBM to examine climate change–related behaviors^44,51,84,85, this corpus of research has predominantly centered on Western populations and has highlighted the significance of personal experience, risk perception, and self-efficacy in driving behavioral change. The findings of this study align generally with existing literature, as perceived severity, knowledge and awareness, and social norms were substantially correlated with health behavior intentions. However, the relative significance of cues to action and awareness identified in this study indicates that these factors may hold greater prominence within the Iranian context, emphasizing the importance of culturally adapted communication strategies and intervention designs. Furthermore, although this study uniquely emphasizes health-related behaviors and investigates a non-Western context, the observed relationships between knowledge and awareness, social norms, environmental concern, and behavioral intentions are consistent with findings from wider research on pro-environmental behaviors. This convergence indicates that the psychological mechanisms underlying pro-health climate initiatives exhibit significant parallels with those motivating pro-environmental behaviors more broadly, even across varied cultural contexts. This overlap underscores the interconnectedness of health promotion and environmental sustainability and indicates that interventions targeting both domains concurrently may achieve enhanced effectiveness. Finally, while previous research has acknowledged the limited use of the Health Belief Model in studies addressing specific climate hazards, such as heatwaves, and has advocated for greater methodological consistency across countries including Germany, Austria, Australia, Canada, and the United States³⁸, this study advances the field by extending the HBM to incorporate climate-specific psychosocial constructs and by focusing on an underexplored region in the Middle East. By contextualizing health beliefs within Iran’s unique socio-cultural and environmental setting, this study provides a more refined understanding of the factors influencing climate-related health behaviors, thereby guiding the design of targeted and more effective public health interventions.

Limitations and future research directions

This work, despite its contributions, has some limitations that must be acknowledged when interpreting the findings, while also providing explicit directions for further research. The employment of a convenience sampling method and online data collection constrains the generalizability of the findings. Participants were predominantly recruited using digital messaging platforms, potentially excluding persons without reliable internet connection, possessing lesser digital literacy, or having limited involvement in online groups. The sample may disproportionately represent better educated and urban populations, thus neglecting vulnerable groups such as rural inhabitants, older folks, or individuals with lower socioeconomic standing. Future research should utilize probability-based sample techniques, such as stratified or cluster sampling, and integrate offline data-gathering methods to assure comprehensive demographic representation and improve external validity.

Second, the study depended on self-reported data, which may be influenced by social desirability bias, recall bias, and the respondents’ subjective interpretations of the questionnaire items. Participants may have exaggerated their environmental concerns or health behavior intentions due to societal expectations around climate change and sustainability. Despite the questionnaire exhibiting robust psychometric features, intentions do not invariably convert into actual behaviors. Subsequent study ought to use objective or behavioral metrics, like observed behavioral data, longitudinal action monitoring, or triangulation with qualitative interviews, to more accurately reflect real-world health and environmental behaviors.

Third, the cross-sectional approach limits the capacity to establish causal inferences concerning the links among variables within the expanded HBM. Although structural equation modeling facilitated the examination of theoretically grounded pathways, the temporal order of beliefs, perceptions, and intents cannot be conclusively determined. Future research should employ longitudinal or experimental designs to investigate temporal changes in health beliefs, assess causal mechanisms, and evaluate the efficacy of targeted interventions designed to modify specific constructs such as perceived severity, knowledge, or social norms.

Fourth, while this study enhanced the HBM by integrating environmental concern, societal norms, and knowledge and awareness, the model may still fail to encompass the complete spectrum of factors affecting health behavior intentions on climate change. Structural and contextual variables, including economic restrictions, institutional trust, policy contexts, political ideology, media framing, and direct exposure to climate-related hazards, were not explicitly incorporated. Future research ought to incorporate multi-level frameworks that merge individual psychological variables with community, institutional, and policy elements to enhance the understanding of climate-related health behaviors.

The study was conducted within the distinct socio-cultural and political framework of Iran, perhaps restricting the applicability of the findings to other environments. Cultural norms, governance frameworks, public dialogue on climate change, and health systems differ significantly between locations and may affect the significance of the HBM elements. Subsequent research ought to undertake cross-cultural and comparative analyses to evaluate the robustness of the expanded HBM across other nations, especially in low- and middle-income contexts, to improve the model’s generalizability and policy significance.

Future studies can enhance the extended HBM and improve its applicability for developing effective public health interventions related to climate change by overcoming these limitations through more representative sampling, longitudinal designs, multi-method approaches, and cross-contextual comparisons.

Theoretical insights and implications

The findings of this study contribute significantly to the theoretical framework of the HBM by demonstrating the effectiveness of an extended version that integrates traditional components with additional dimensions relevant to climate change and public health. By incorporating constructs such as knowledge and awareness, social norms, and environmental concern, this extended HBM provides a more comprehensive understanding of the factors influencing health behavior intentions in the context of climate change. These added dimensions allow researchers to better understand the nuances of health risks, ultimately guiding the development of more effective public health interventions for use in climate change. This study extends traditional HBM applications by demonstrating that the relationships between beliefs and health behavior intentions are not always direct. The significant indirect associations observed, particularly regarding knowledge and awareness, highlight the importance of mediators and the need for interventions that target not only individual beliefs but also the pathways through which those beliefs influence action. By incorporating climate-specific dimensions such as environmental concern and social norms, this study extends the traditional HBM framework, underscoring the importance of contextualizing health behavior models for environmental issues like climate change. The findings of this study, conducted within the Iranian context, provide valuable insights into the cultural nuances of health behavior intentions related to climate change, emphasizing the need for culturally tailored interventions.

The inclusion of knowledge and awareness highlights the critical role that information plays in shaping health beliefs and behaviors. This dimension emphasizes that individuals who are better informed about the health risks associated with climate change are more likely to engage in proactive health behaviors. This finding reinforces the idea that educational interventions must be a key component of public health strategies aimed at mitigating the effects of climate change. Social norms emerged as a significant factor influencing both environmental concern and health behavior intentions, suggesting that individuals are motivated by the behaviors and attitudes of those around them. This underscores the importance of considering social influences within health behavior models, as the perceptions of what is acceptable or expected within a social group can drive individual actions. By integrating social norms into the HBM, researchers and practitioners can better address the communal aspects of health behavior change, fostering environments that support collective action. Furthermore, the incorporation of environmental concern into the HBM reflects the increasing recognition of the interconnectedness of health and environmental issues. This dimension emphasizes that concerns about environmental degradation can directly impact health behavior intentions, suggesting that public health efforts must address environmental sustainability as a part of health promotion. The study’s findings support the notion that health interventions should not only focus on individual behaviors but also consider broader environmental contexts that influence health outcomes. Overall, the extended HBM offers a more nuanced theoretical framework that acknowledges the complexities of health behavior in the face of climate change. By integrating additional dimensions, this model can enhance our understanding of how individuals perceive and respond to health risks, ultimately guiding the development of more effective public health interventions. Future research should continue to explore these expanded dimensions within the HBM to further refine the model and its applicability in various health contexts, particularly as the challenges posed by climate change evolve.

Policy and practice recommendations

To enhance public awareness, it is essential to develop and implement targeted campaigns that clearly communicate the links between climate change and health risks, emphasizing the severity of these risks to motivate individuals to engage in health-promoting behaviors. Integrating comprehensive education on climate change and its health impacts into school curricula can foster a sense of environmental responsibility among students from an early age, equipping them with the knowledge needed to make informed health decisions. Encouraging community-based programs that leverage social norms will promote healthy behaviors by facilitating collective action and support for health and environmental issues through workshops, group activities, and peer-led discussions. Additionally, designing interventions that specifically aim to enhance self-efficacy regarding health behaviors will empower individuals to take proactive steps; this could involve skill-building workshops, resources for overcoming barriers, and personalized feedback. Incorporating effective cues to action in public health messaging and interventions will further encourage individuals to adopt healthier behaviors in response to environmental changes by utilizing reminders, prompts, or visual indicators. Finally, it is crucial to regularly assess the effectiveness of health and environmental policies to ensure they meet the needs of populations, utilizing data-driven evaluations to guide adaptations and improvements that maintain relevance and impact in addressing the intertwined challenges of health and climate change. By implementing these recommendations, policymakers and public health practitioners can create a more informed and proactive society capable of effectively addressing the health challenges posed by climate change.

Conclusion

This study examined the relationships among Health Belief Model constructs and health behavior intentions in the context of climate change within an Iranian setting. The findings indicate that cues to action, environmental concern, and knowledge and awareness are associated with individuals’ reported intentions to engage in health-promoting behaviors. These observed relationships suggest that informational and contextual factors may be relevant components to consider when examining how individuals interpret and respond to climate-related health risks, without implying direct causal effects.

Perceived severity was also found to be associated with health behavior intentions, indicating that perceptions of the seriousness of climate-related health impacts may be more salient than perceptions of personal vulnerability in this context. In contrast, perceived susceptibility showed a weaker association, highlighting potential variability in how different dimensions of risk perception relate to behavioral intentions. This pattern suggests that individuals may prioritize broader assessments of threat severity over individualized risk perceptions, although further research is needed to clarify these dynamics.

While self-efficacy was not directly associated with health behavior intentions, its relationship with cues to action points to a possible indirect or conditional role in shaping behavioral responses. Similarly, the association between social norms and health behavior intentions underscores the relevance of social context and shared expectations in understanding climate-related health behaviors. These findings align with broader evidence suggesting that health behaviors are influenced by interactions between individual beliefs and social environments.

Overall, the results highlight the multifactorial nature of health behavior intentions in the context of climate change, suggesting that cognitive beliefs, social influences, and contextual factors are interconnected. Rather than advancing new theoretical constructs, this study contributes context-specific empirical evidence by applying an extended Health Belief Model framework in a non-Western setting. Future research employing longitudinal and qualitative designs would help clarify how these associations evolve over time and how contextual factors shape health-related decision-making in response to climate change. Such work may support the development of more contextually informed public health approaches aimed at addressing climate-related health challenges.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

AVE

Average Variance Extracted

CA

Cronbach’s Alpha

CFI

Comparative Fit Index

CR

Composite Reliability

d-ULS

Unweighted least squares discrepancy

HBM

Health Belief Model

PTSD

Post-Traumatic Stress Disorder

RMSEA

Root Mean Square Error of Approximation

SEM

Structural Equation Modeling

SRMR

Standardized Root Mean Square Residual

TLI

Tucker–Lewis Index

TPB

Theory of Planned Behavior

VIF

Variance Inflation Factor

WHO

World Health Organization

Author contributions

Mohammad Reza Pakravan-Charvadeh: Data curation, Methodology, Formal analysis, Investigation, Writing – original draft, Project administrationRahim Maleknia: Conceptualization, Validation, Writing – review & editing, Visualization, and Critical revision of the manuscript.

Data availability

The datasets used and analyzed during the current study available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Consent to participate

All participants provided informed consent electronically before completing the survey. Participation was voluntary, and responses were anonymous.

Consent to publish

Participants were informed that the results of the research would be published anonymously in scientific journals. Consent to publish anonymized data was obtained from all participants prior to data collection.