Background

Accidents in the workplace account for a significant portion of global morbidity and mortality, with an estimated 2.3 million people succumbing to work-related accidents or diseases every year and 340 million occupational accidents occurring annually [1]. The incidence of work-related deaths in developing countries is 3 to 4 times higher than in developed industrialized countries [2]. In Iran, the fatal and non-fatal accident ratios are 0.95 in 100,000 and 253 in 100,000 respectively [3], making work-related accidents the second leading cause of death in the country [4]. Improved prevention and Occupational Safety and Health (OSH) practices could reduce injuries and fatalities [1]. Promoting workplace safety enhances employee motivation, increases productivity, and reduces organization costs related to work-related injury and illnesses, relieving pressure on the health systems [5].

Work-related accidents are influenced by individual, job, organizational, environmental, and other factors [6]. Among individual factors, personality traits such as accident proneness (AP) are significantly associated with the occurrence of work-related accidents [7]. While identifying accident-prone individuals and developing prevention strategies is crucial, further investigation into the factors associated with accident proneness is needed [8].

Research into factors associated with accident proneness can be effectively conducted using theories, such as the Theory of Planned Behavior and the Health Belief Model (HBM) [11]. The HBM has been used to explain work-related accidents [9], offering a structured approach to explore the factors associated with accident-proneness and work-related accidents [7].

Previous research indicates that psychological models like the HBM may be enhanced by integrating additional variables to better explain and predict behaviors [10, 11]. For example, Ataei’s study demonstrated that an extended model provided a more robust explanation of the intention to use green pesticides [12]. Similarly, Wang’s research showed that an expanded model effectively predicted healthy nutrition behaviors [13]. Furthermore, Yuen found that combining the HBM with emotional appeal theory improved predictions of safety behavior [14].

These findings are especially relevant when considering accident proneness and work-related accidents within the Iranian context. Cultural differences between Iran and Western countries are significant when applying the HBM to study accident proneness and work-related accidents [15], Notably, the conceptual understanding of health in Iran places a high importance on spiritual health, which is integral to the overall health framework [16, 17].

Spiritual health

Research has shown that spirituality is one of the effective social-psychological indicators of people’s health behaviors [18, 19]. Spiritual health is defined as the ability to establish relationships with others and/or a transcendent being, having goals, and a sense of meaning in life [20]. Importantly, spiritual health is integral to all other health dimensions. Without spiritual health, biological, psychological, and social dimensions of health are unable to function properly [16]. Good spiritual health increases the quality of life, and longevity, and reduces anxiety, depression, and suicide [21]. Along with improving job satisfaction, job stress, and improving employee performance [22]. Making spiritual health an important dimension of health, that plays a significant role in improving the performance of employees and reducing the risks to life and costs associated with work-related accidents and illnesses [18, 19].

Spiritual health and HBM

Researchers have addressed these modifying variables, to account for various factors not accounted for in the original HBM. Important factors have been culturally related, as this has been one of the weaknesses identified in the HBM [23], as cultural context must be accounted for in the HBM [24]. Importantly, when applying the HBM to Iran, the cultural dimension of spirituality and spiritual health must be accounted for [25].

To date, no study has examined associations between the components of the Health Belief Model and spiritual health in predicting accident proneness in Iran. Models that have been tested and validated in other societies and countries cannot be directly applied to the screening and prevention programs of another country without adaptation to its cultural characteristics [25] Therefore, this study aimed to design and present an extended Health Belief Model incorporating spiritual health and evaluated its ability to predict vulnerability to accident proneness among workers in Saveh industries. By integrating spiritual health into the Health Belief Model, it is hypothesized that the extended model will have an improved ability to predict accident proneness. The extended model will also provide insights into how spiritual health is associated with accident proneness.

By combining spiritual health into the HBM, more culturally sensitive and effective screening and prevention programs can be developed, potentially reducing work-related accidents and enhancing employee well-being and performance.

Method

This cross-sectional study was conducted in 2022 on employees working in various private sectors in the Saveh Industrial City, and ethical approval for the study was obtained from the Saveh University of Medical Sciences. A descriptive-analytical approach was taken when doing this study.

Sample

The sample included 422 workers from the Saveh Industrial City. A power analysis was conducted, considering a population of 40,000 workers, a 95% confidence interval, and an alpha coefficient of 0.05, the sample size was calculated to be 384 people. To ensure a sufficient sample and data, an additional 10% was added to obtain the initial sample size of 422.

The inclusion criteria included that workers needed one year of work experience, be of Iranian nationality, and have a work-related accident within the last 6 months to 1 year. The exclusion criteria included having no history of mental distress, severe stress such as divorce, or death of a first-degree relative in the last 6 months.

A multi-stage cluster random sampling method was used in this study. A sample list was developed by initially approaching the local office of the Industrial City, from which a list of industries of each zone was received (industries are divided into three food-pharmaceutical, cosmetic-health, and technical-service zones based on the division of the local office of the Industrial City). A total of five industries from each zone were randomly selected and a total of 15 industries were selected from the triple zones. The identified industries were then approached and 28 workers were selected from the personnel list using a systematic random sampling method.

Data collection

Each of the identified workers in the various industries was approached at their workplace. Informed consent was obtained from them in a private office, and the research questionnaire was provided to participants. The participants were informed they had a week to complete these questionnaires at home, after this one-week period, we collected the completed versions from them in the confidential space at their workplace.

Measures

The data collection tool developed from prior studies was broken into Sects. [11, 26,27,28,29], based on the measurement instruments identified for the study. The sections were the following:

  1. 1.

    Demographic information: This section provided basic demographic information such as age, gender, educational status, work experience, marital status, physical activity, tobacco use, and working shift.

  2. 2.

    HBM: A HBM questionnaire was developed based on a review of the literature [26, 29]. This questionnaire comprised 31 questions aligned with the model’s constructs, utilizing a 5-point Likert scale ranging from completely agree to completely disagree. Perceived vulnerability was assessed with 8 questions such as: “According to the conditions of my workplace, there is a possibility of an accident happening to me”. Perceived severity included 7 questions, for instance: “Occupational accidents can cause my disability”. Perceived benefits encompassed 5 questions including: “Observance of occupational safety tips will protect the health of myself and my colleagues.” Perceived barriers involved 6 questions, such as: “The use of safety equipment creates limitations for me when doing work”. Self-efficacy with gauged through 5 questions, like: “I can obtain personal safety and protection information related to my job to protect my health”.

  3. 3.

    Qualitative content validity was assessed by 8 specialists in health education, epidemiology, occupational health, and public health. The content validity index (CVI) was used to evaluate the simplicity, specificity, and clarity of the questions, confirming a CVI of 83%. The content validity ratio (CVR) assessed the necessity of the questions. The content validity was confirmed with CVI 82% and CVR 78%. Reliability was tested with a sample of 20 workers, yielding a Cronbach’s alpha coefficient of 0.79.

  4. 4.

    Spiritual health was measured using the Spiritual Wellbeing Scale [30]. The range of scores that can be obtained was 20–140. An increase in the obtained score indicates higher spiritual health [31]. Fatemi et al. confirmed the reliability of this instrument using Cronbach’s alpha of 0.94 [32].

  5. 5.

    The Accident Proneness (AP) questionnaire had 9 dimensions including personality traits, harmful factors of the work environment, miscellaneous factors, musculoskeletal disorders, safety culture, safety attitude, occupational stress, interest in the organization, and degree of risk-taking [27]. The sum of the scores of all dimensions represents the total AP score of the individual. An increase in the obtained score indicates a higher AP of the individual. It is rated on a 4-point scale ranging from low risk (< 82.5), medium risk (82.6–114.5), high risk (114.6–148.5), to very high risk (> 148.6) [27]. In Iran, the reliability of the questionnaire was confirmed using Cronbach’s alpha of 0.86 [27].

Data analysis

The data were analyzed using SPSS version 26 software (IBM Corp, 2019). Descriptive statistics were employed to determine frequencies, central tendencies, and dispersion to describe the data. Correlation tests were conducted to assess the relationships between the constructs of the HBM, spiritual health and AP (Fig. 1). Analysis of Variance (ANOVA) was utilized to compare the means of the HBM constructs and spiritual health, across different levels of AP. Stepwise regression analysis was performed to investigate the predictive value of each HBM construct, along with the modifying factor of spiritual health, on AP. Data normality was assessed using skewness indices and the Kolmogorov–Smirnov test. A significance level of p < 0.05 was considered statistically significant.

Fig. 1
figure 1

Health Belief Model of Accident Proneness, including Spiritual Health

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Results

Demographic characteristics

The results showed that out of 384 participants in the present study, 367 (95.6%) were men. The average age of the participants was 36.2 ± 7.2 and the highest work experience (29.9%) was 5–9 years. About half of them (54.9%) had a high school degree and one-third were tobacco users (Table 1). In terms of AP, 229 (59.6%), 148 (38.5%), and 7 (1.8%) people had high, medium, and low AP respectively (Fig. 2).

Table 1 Distribution of some demographic characteristics of the studied workers
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Fig. 2
figure 2

Chart of Accident Proneness in Participants

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Initial descriptive statistics were run (Table 2), followed by conducting ANOVA tests which showed that the mean score of all HBM constructs and spiritual health, except for perceived barriers, was higher in workers with lower AP than those with medium and higher AP. They were also higher for workers with medium AP than those with higher AP. These differences were statistically significant (p < 0.05).

Table 2 Mean and standard deviation of constructs of HBM and spiritual health according to Accident –Proneness
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Correlation matrix of HBM constructs with spiritual health and AP

The linear correlation coefficient of each of the HBM constructs with each other, as well as with spiritual health and AP shows that the constructs of self-efficacy (r = 0.56), perceived susceptibility (r = 0.54), perceived severity (r = 0.46), perceived benefits ( r = 0.45), and spiritual health (r = 0.39) have an inverse and significant linear relationship with AP (p < 0.05), while the construct of perceived barriers (r=-0.30) has a indirect and significant linear correlation with AP (p < 0.05) (Table 3).

Table 3 Correlation matrix of the research variables
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Predictors of accident proneness

Hierarchical multiple regression analysis was used to determine the predictive power of the HBM extended with the construct of spiritual health for accident proneness. The results showed that in the first model, the variables of perceived self-efficacy, perceived susceptibility, and perceived severity were independent predictors of AP of workers and explained a total of 0.43 of the variance of AP behavior. In the second step, the perceived self-efficacy construct (β = 34%), perceived susceptibility (β = 27%), spiritual health (β = 16%), and perceived severity (β = 12%) were included, respectively, which explained a total of 46% of the variance of AP behavior of workers. In the second model, by adding the spiritual health variable to the HBM as a modifying factor, the predictive power of the model was increased by 3% (Table 4).

Table 4 Results obtained from multiple linear regression: Health beliefs, and spiritual health predicting accident–proneness
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Discussion

This study aimed to assess the predictive capacity of the Health Belief Model (HBM), augmented with spiritual health, in understanding accident proneness (AP). The findings indicate that most participants were male workers, with many exhibiting high AP. Workers with lower AP had higher mean scores in HBM constructs and spiritual health, except for perceived barriers. Significant inverse relationships were found between AP and key HBM constructs. This enhancement aligns with existing literature suggesting that extended HBM yield superior predictive ability of behavior [16]. For instance, Yuen et al. demonstrated that combining the HBM with emotional appeal theory increased explanatory power, elucidating 61% of variance in safety behavior among seafarers [14]. This supports the notion that theoretical amalgamation bolsters predictive powers [33].

This study’s results revealed lower mean scores of spiritual health among workers exhibiting medium and high AP, suggesting a negative association between spiritual well-being—encompassing meaning and purpose—and health outcomes [34]. Aini et al. similarly highlighted the adverse effect of low spiritual health on occupational stress [35]. Confirming previous research linking spiritual health to occupational satisfaction and reduced occupational stress, thereby potentially mitigating work-related accidents. Without spiritual health, researchers argue that physical, mental, and social dimensions may not function optimally, limiting overall potential [32]. In general, studies in the field of religion and health indicate that individuals with an active spiritual life tend to be psychologically healthy [36, 37], a finding echoed in this study.

The predictive power of the adjusted HBM model in this study was 46%, a 3% improvement over the original model, attributable to the inclusion of spiritual health as a modifying factor. This underscores the extended HBMs enhanced capacity to assess levels of accident proneness, emphasizing the critical role of spiritual health within the model. All HBM showed factors exhibited correlations with spiritual health, and the stepwise regression showed an improved model through its inclusion to measure AP. Higher levels of spiritual health were associated with reduced accident proneness, affirming its role as a modifying factor within the HBM. Supporting the argument that modifying factors have the potential to influence the relationship between the constructs of the HBM [38]. Previous studies into the modifying factors of the HBM have consistently identified spirituality as an important modifying factor [39, 40]. Highlighting the importance of spirituality, and especially spiritual health, in improving physical and mental health [19, 41, 42].

The findings also highlighted that the majority of the workers (98.2%) had high or medium AP, and only 1.8% had low AP. Underscoring that the majority of workers have the propensity to engage in AP behaviors. Confirming previous studies that the distribution of accidents among people is not based on chance and that AP is an important factor in the occurrence of accidents [43, 44]. Research shows that the distribution of accidents among people at risk for work-related accidents is not uniform and under equal conditions, three-quarters of accidents happen to one-quarter of people at risk [29]. This is because the majority of people have a low AP, which is reflected in their engagement in considering the consequences of their actions before performing them [45]. However, people with a high AP act suddenly and without careful consideration of the consequences of their actions. Resulting in more accidents occurring among people with high AP.

Notably, self-efficacy (SE) emerged as the foremost predictor of AP in this study, consistent with previous research findings linking SE to reduced occupational accidents [46, 47]. Enhancing employees’ SE has been shown to foster safer workplace behaviors [46], reflecting its crucial role in risk management across various contexts [48]. Moreover, SE can support employees who have experienced work-related accidents in returning to work and improving their life satisfaction [49]. This highlights the important relationship between the perceived ability to perform occupational safety actions and actual safety behaviors.

SE involves skills and a belief in one’s ability to perform safety skills. When SE is cultivated for safe behaviors, these beliefs guide employees’ responses, efforts, and safety in the workplace. This study’s findings support that perceived susceptibility significantly predicts AP, with higher perceived susceptibility being associated with lower levels of AP. This relationship is crucial for accident prevention, as research has shown that as perceived susceptibility fosters the adoption of preventive behaviors, such as using safety devices and personal protection [50]. The effectiveness of perceived susceptibility in predicting behavior is well-established in prevention programs [51], including those focused on accident prevention [52, 53].

This study’s findings support the HBM, which suggests that individuals who consider themselves at risk for work-related accidents are more likely to adopt safe behaviors and prevent accidents. If a person perceives they are susceptible to a work-related accident and its complications, they are more likely to engage in preventive actions [54, 55]. The study also found that lower perceived severity leads to fewer preventive actions, consistent with other studies [56, 57]. According to the results of our study and previous studies, it can be said that the way one perceives risk plays a significant role in influencing safety behavior.

Furthermore, the study confirmed the role of the perceived benefits in the HBM for predicting behavior. As perceived benefit scores increased, AP scores decreased, indicating an inverse correlation between the perceived benefits and AP. This result confirms previous research showing an inverse relationship between perceived benefits and safety behaviors [60]. For instance, Moradhaseli et al. demonstrated that perceived benefits influence farmers’ job-related health behaviors [61], while Panakobkit et al. found that perceived benefits significantly increased the likelihood of using respiratory protective equipment. These results suggest that supporting employees in understanding the benefits of workplace safety measures can effectively reduce work-related accidents and illness. Addressing barriers is crucial, as this study and previous research have shown that the perception of barriers decreases the adoption of safe behaviors [63, 64].

The study has several limitations that should be taken into account. Firstly, the reliance on self-reported survey data introduces the possibility of recall bias, which may affect the accuracy of responses. Future studies could enhance reliability by validating self-reported information against official work records. Secondly, while the study included respondents from various industries, the sample was confined to Saveh Industrial City in Iran, potentially limiting the generalizability of our findings to other regions in the country. To improve external validity, future studies should consider expanding the sample to include employees from diverse geographical locations. Nonetheless, a notable strength of this study was its use of randomized cluster sampling, which enhances the generalizability of the findings among employees within Saveh Industrial City.

Conclusion

The high prevalence of AP observed in this study underscores the need to design policies aimed at mitigating occupational accident risks through targeted interventions by policymakers and health planners. The inclusion of spiritual health as a modifying factor to the Health Belief Model (HBM) improved its ability to predict accident proneness (AP). This extended model can be used as a conceptual framework that is culturally appropriate for Iran for planning effective intervention programs to reduce AP within the workplace. This adaptation not only improves the cultural resonance of the HBM but also emphasizes the significance of incorporating spiritual health assessments in occupational safety frameworks tailored for Iran. Moreover, the results indicate a preponderance of workers with high or medium AP, emphasizing the importance of bolstering self-efficacy and promoting awareness of workplace safety measures. These efforts are crucial steps toward reducing work-related accidents and fostering a safer work environment.