Algorithm to evaluate the training of healthcare workers for the prevention of occupational accidents

Algorithm to evaluate the training of healthcare workers for the prevention of occupational accidents | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Algorithm to evaluate the training of healthcare workers for the prevention of occupational accidents Gözde Toktaş, Hasan Uğur Öncel This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8670860/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Workplace accidents in the healthcare sector and the factors that cause them demonstrate that healthcare workers are exposed to numerous occupational risks. Preventing occupational accidents among healthcare workers primarily requires that workers be aware of hazards and risks, and that awareness be increased. In this study, an awareness level for occupational health and safety initiatives aimed at preventing workplace accidents among healthcare workers and algorithms for evaluating training programs were developed. Methods First, studies on occupational health and safety awareness among healthcare workers were reviewed, and then a questionnaire inventory consisting of 47 items was created to measure the desired domain. The questions were first submitted to 10 experts for their opinion. As a result of evaluating the expert opinions, the number of questions in the draft scale was reduced to 44, and the questions were finalized. Data was collected from 806 volunteer participants using a survey technique, and the collected data was analyzed using the Kaiser-Meyer-Olkin test, Bartlett test, exploratory factor analysis, and confirmatory factor analysis. Results The scale, determined to consist of 44 items based on the analyses, comprises 5 sub-dimensions. The Cronbach's alpha coefficient of the developed scale is 0.9787, and its goodness-of-fit criterion is only the Standardized Root Mean Square Residual (SRMR) fit measure has an acceptable fit value, while Root Mean Square Error of Approximation (RMSEA), Goodness of Fit Index (GFI), Adjustment Goodness of Fit Index (AGFI), Comparative Fit Index (CFI), Normed Fit Index (NFI), and Chi-square / degrees of freedom (χ2/df) have excellent fit values. Conclusion In this study, an awareness-level scale was developed for occupational health and safety initiatives to prevent workplace accidents among healthcare workers. This scale will support the work of healthcare managers and professionals. Healthcare Worker Occupational Health Safety Training Algorithm Awareness Level Scale Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Workplace accidents occurring worldwide cause significant losses and can negatively impact countries' economies. Workplace accidents among healthcare workers, along with the factors that cause them, demonstrate that healthcare workers are exposed to numerous occupational risks. This situation highlights the urgent need to prevent workplace accidents that affect workers in this sector. In this context, the first step in preventing occupational accidents and diseases is ensuring that employees are aware of which behaviours may pose a risk [ 1 ]. Today's understanding of occupational health and safety is based on a preventive, proactive approach [ 2 ]. The primary philosophy of the occupational health and safety approach is to ensure workers operate in a healthy and safe environment by identifying workplace hazards and risks and taking the necessary precautions to mitigate them. It is essential to identify ways to prevent occupational accidents and diseases, ensure employees receive regular training, and ensure they are aware of protective and preventive behaviours [ 3 ]. Occupational health and safety training has become a crucial tool in promoting desired changes in employee behavior and preventing occupational accidents and diseases. By identifying employees' workplace training needs and meeting them at appropriate intervals and in specific situations, a significant reduction in occupational accidents and diseases is expected [ 4 ]. It is possible to achieve behavioural change by converting the knowledge acquired through training into practice, thereby instilling correct behavioural models related to Occupational Health and Safety. Continuous technological developments create a variable environment for occupational safety. This development increases the need for continuous training for employees. In addition, frequent workforce changes in hospitals increase the need for training. This study will enable the individual assessment of employees' training. Furthermore, the results will provide managers with insights into training effectiveness and will make a significant contribution to determining which training topics employees need. As this data will be personalised, it will indicate which training courses the employee needs. Meeting training needs at appropriate intervals will undoubtedly help prevent accidents among healthcare workers. Materials and Methods Type of research This research employs a methodological model to develop a scale to assess healthcare workers' awareness of occupational health and safety practices. Data were collected through a questionnaire in the research, and the following sampling formula with a known population has been used to determine the sample size: $$\:n=\frac{N.P.Q.{Z}^{2}}{\left(N-1\right){\:d}^{2}+Z²PQ}$$ 1 N: Population size, n: Sample size P: Observation rate of X in the population, Q (1-P): Non-observation rate of X Z α : α = 0.05, 0.01, 0.001 for 1.96, 2.58, and 3.28 values d= Sample error t α,sd = Critical values of the t-distribution with degrees of freedom (sd = n-1). When t α,sd the critical values are, sd = n-1→ 5000 can be taken as equal to the Zα values The study population consists of 1,057 individuals working at a private hospital. In this study, the minimum required sample size was calculated from a population of 1057 individuals, as shown in Eq. ( 1 ). Using a significance level of t α = 0.05, a sampling error of ± 0.05, and values of p = 0.5 and q = 0.5, the minimum sample size was found to be 282 individuals. This means that 282 or more surveys must be conducted to achieve 95% confidence, ensuring that the survey results are within ± 5% of the actual value. Convenience sampling was used in the study. Convenience sampling is a non-random sampling method in which the sample is selected from the population based on the researcher's judgment. In convenience sampling, data is collected from the population in the easiest, fastest, and most economical way [ 5 ]. Data collection tools and techniques In the study, data was collected through a questionnaire administered to healthcare workers who volunteer to participate. The draft questionnaire consists of two parts. The first part contains questions designed to determine participants' socio-demographic characteristics. The second part of the questionnaire form contains five-point Likert-type statements designed to assess healthcare workers' awareness of occupational health and safety practices. Questions to assess the level of awareness regarding occupational health and safety practices To develop the Algorithm for evaluating the Training of Healthcare Workers in the Prevention of Occupational Accidents, a literature review on occupational health and safety practices was conducted. Based on the data collected a pool of 47 items was created. The questions were first submitted to experts for their opinion. As a result of evaluating the expert opinions, the number of questions in the draft scale was reduced to 44, and the questions were finalized. A pilot study was conducted with 20 people representing the target participants to obtain feedback on the item statements and determine whether any improvements were needed. During the scale development process, a literature review was conducted, the item pool was created, the scale type was determined, experts reviewed the item pool, and the items were piloted and evaluated. The statements in the draft scale were prepared according to a five-point Likert scale. The response options are: 1 = Strongly disagree, 2 = Disagree, 3 = Undecided, 4 = Agree, 5 = Strongly agree. Following the application of the draft scale to the main population, statistical analyses resulted in the development of the Occupational Health and Safety Awareness Assessment Scale, comprising 44 questions and five sub-dimensions. Statistical analysis Statistical Package for the Social Sciences (SPSS) for Windows, version 25.0, and SAS (version 9.4) were used for statistical analysis of the data obtained in the study [ 6 ]. For the quantitative variables measured in the research, descriptive statistics such as the mean and standard deviation were used. For qualitative variables measured by counting, such as gender and age, descriptive statistics were presented as numbers and percentages. The data used were first tested for normality using the Shapiro-Wilk test and Skewness values. If the tests showed that the data were normally distributed, parametric tests were used in the statistical analysis; otherwise, non-parametric tests were used. The t-test was used for pairwise comparisons between two-category variables, such as gender, and Analysis of Variance was applied to find differences between variables with three or more categories. Pearson's r moment product correlation coefficient was used to reveal the relationship between quantitative variables, while the Chi-square test was used to examine the relationship between qualitative variables. The means and standard deviations of the scale items, subscales, and overall scale scores were presented in a descriptive statistics table. To test the scale's structure, factor analysis, Cronbach's Alpha, and item-total correlation were performed to assess reliability and validity. Cronbach's Alpha reliability coefficients were calculated to test the internal consistency reliability of the scales. A significance level of 0.05 was accepted throughout the study. Results This section presents the results of the data analysis obtained from questionnaires completed by 806 participants included in the study. First, the findings related to the participants' responses to the socio-demographic questions in the first section of the questionnaire are presented. Subsequently, the results of the exploratory factor analysis, confirmatory factor analysis, reliability analysis, and correlation analysis of the obtained data are presented. Using Kendall's W test, the responses of 10 experts were analyzed for the validity of comprehensibility and simplicity of the questions related to occupational safety, and the results are presented in Table 1 . This table shows that the Kendall W coefficient is 0.448, indicating a moderate level of agreement among the experts furthermore, since the significance values are less than 0.05 (p = 0.000), the null hypothesis that 'there is no agreement among experts' is rejected, and it is therefore concluded that there is a moderate and statistically significant level of agreement among experts. Table 1 Kendall's W Test Results for Agreement Among Experts N 10 Kendall's W a 0.448 Chi-square 205.966 df 46 p. 0.000 Demographic characteristics of participants A total of 806 questionnaires were collected for the study, and the demographic information of the participants is presented in based on the analysis of these questionnaires. Accordingly: The average age of participants was 31.4 ± 9.75, and 71.1% were female (573) and 28.9% were male (233). The average length of service at the workplace of participants was 28.8 ± 30.78 months. Participants were divided into five groups according to their educational status. Accordingly, 31.4% of participants were high school graduates (253), 40.9% were associate degree graduates (330), 18.7% were bachelor's degree graduates (151), 5.1% were master's degree graduates (41), and 3.8% were doctoral degree graduates (31). In terms of working hours, 7.2% of participants worked less than 45 hours (58), 71.8% worked 45 hours (579), and the remaining 21.0% worked 45 hours or more (169). By work type, 66.0% of participants work during the day (532), 1.7% work at night (14), and the remaining 32.3% work shifts (260). Finally, it was found that 98.9% of participants had received occupational safety training (797) and 1.1% had not received occupational safety training (9). Professions of participants, 24.7% were nurses (199), 5.7% were doctors (46), 0.4% were pharmacists (3), 1.4% were midwifes (11), 13.5% were technicians (109), 1.2% were physiotherapists (10), 0.5% were psychologists (4), 0.4% were dietitians (3), 0.1% was audiologist (1), 1.7% were technical staff (14), 9.7% were auxiliary healthcare personnel (78), 6.9% were administrative staff (56), 4.2% were others (34), 9.9% were contract staff (80), 19.6% visiting patient services staff (158). The other socio-demographic characteristics of the participants are shown in Table 2 . Table 2 Other Socio-Demographic Characteristics of Participants Total (N = 806) Department Worked In , n (%) Emergency Department 36 (4.5%) Pharmacy 13 (1.6%) Outpatient Clinics 165 (20.5%) Oral and Dental Health 7 (0.9%) Physical Therapy and Rehabilitation 20 (2.5%) Radiation Oncology 10 (1.2%) Operating Rooms 58 (7.2%) Hospital General 64 (7.9%) Radiology 30 (3.7%) Main Warehouse 7 (0.9%) Administrative Departments 61 (7.6%) In Vitro Fertilisation 7 (0.9%) Archive 3 (0.4%) Bone Marrow Transplantation Unit 21 (2.6%) Inpatient Services 100 (12.4%) Nursery 12 (1.5%) Laboratory 16 (2.0%) Kitchen 25 (3.1%) Laundry 1 (0.1%) Medical Oncology 12 (1.5%) Intensive Care Units 60 (7.4%) Delivery Room 18 (2.2%) Central Sterilisation Unit 4 (0.5%) Other 51 (6.3%) Nuclear Medicine 5 (0.6%) Emergency Disaster Management Task , n (%) Firefighting Team 43 (5.3%) Hospital Disaster and Emergency Plan Organizational Structure 91 (11.3%) Rescue Team 24 (3.0%) Protection Team 13 (1.6%) First Aid Team 25 (3.1%) Not Assigned 610 (75.7%) Findings related to the scales used in the study In this study, the ‘Occupational Health and Safety Awareness Level Scale’ was used as a candidate scale. This scale was applied to 806 employees, and the resulting dataset was randomly divided into two parts: Data Set 1 and Data Set 2. Before analysing these data sets and the total data set using advanced statistical methods, the mean, standard deviation, and skewness values for each data set are presented in Table 3 . Table 3 Mean, Standard Deviation, and Skewness Values of the Scale Items Used in the Study N Average Ss Min Max Skew Data Set 1 403 4.25 0.64 1.00 5.00 -1.09 Data Set 2 403 4.25 0.62 1.75 5.00 -0.73 General 806 4.25 0.63 1.00 5.00 -0.92 Within the scope of this study, the questionnaires were randomly divided into two groups, each with 403 participants. Exploratory factor analysis was applied to Data Set 1, and confirmatory factor analysis was applied to Data Set 2. The first step in scale development is exploratory factor analysis. However, before exploratory factor analysis, it is necessary to determine the number of factors. Determining the number of factors One of the most crucial steps in developing the ‘Occupational Health and Safety Awareness Level Scale’ is determining the number of factors to be extracted before conducting exploratory factor analysis. In this study, the method used to determine the number of factors, Minimum Average Partial (MAP) Correlation Analysis, was developed by Velicer (1976) [ 7 ]. In this research, Minimum Average Partial Correlation analysis was performed using Data Set 1, and the results obtained are presented in Table 4 . Minimum Average Partial Correlation analysis indicates that five factors are sufficient. Table 4 Minimum Average Partial Correlation Analysis Results Minimum Average Partial Correlation Analysis N Prin Comp Partialled Squared Fourth-Powered 0 0.2985 0.1043 1 0.0234 0.0022 2 0.0152 0.0010 3 0.0144 0.0008 4 0.0143 0.0008 5 0.0135* 0.0007* 6 0.0140 0.0008 7 0.0144 0.0007 8 0.0148 0.0007 9 0.0152 0.0007 10 0.0153 0.0008 * MAP = Minimum Values in Columns Exploratory factor analysis Exploratory factor analysis is a multivariate statistical method that combines p interrelated variables to identify a small number of conceptually meaningful new variables (factors, dimensions) [ 8 ]. Confirmatory factor analysis is a method applied to assess whether the original structure of previously obtained and used scales. by other researchers is confirmed by newly obtained data [ 9 ]. Confirmatory factor analysis confirms a previously tested factor structure, meaning that the factor structure is valid [ 10 ]. To determine whether the data set was suitable for factor analysis, the Kaiser-Meyer-Olkin and Bartlett Sphericity tests were first performed [ 11 ]. The findings presented in Table 5 demonstrate that the assumptions required for exploratory factor analysis are met and that the data are suitable for factor analysis. Table 5 Kaiser-Meyer-Olkin and Bartlett’s Test Results of the Scale Kaiser-Meyer-Olkin and Bartlett's Test Kaiser–Meyer–Olkin Measure of Sampling Adequacy 0,964 Bartlett’s Test of Sphericity Approximate Chi‑Square 17926,992 S.D. 946 p 0.000 In this study, the Varimax orthogonal rotation method was selected for factor analysis. When conducting exploratory factor analysis, the most critical considerations in determining the number of factors are that the items included in each factor are consistent in terms of meaning and content, that the factor eigenvalues are one or greater, that the factor loadings of the items included in a factor are 0.40 or greater, and that the difference between the load values of the items in one factor and the load values of the items in another factor is at least 0.10 or greater [ 12 ]. When factor analysis and varimax rotation were applied to data set 1, five factors with eigenvalues greater than 1.00 were obtained. This number corresponds to the same number of factors obtained using the Minimum Average Partial method. Since there were no items with factor loadings below 0.40 in the analysis, factor analysis was performed on all 44 items. The factor loadings obtained from the factor analysis explains 69.66% of the total variance of the five-factor structure. This is a remarkably high rate of explanation. The factors obtained from the exploratory factor analysis, the items loaded onto them, and the factor headings are shown in Table 6 . Table 6 Factors and Their Item Loadings Factor Number of Items Items F1. Knowledge Level on Hospital Disaster and Emergency Plan Preparedness 17 15. I know the components that form the fire triangle. 26. I know that the principle of fire response is “Give Alarm, Rescue, Control, Evacuate/Escape.” 28. There are written and visual signs indicating the locations of medical gas shut‑off valves. 29. I am knowledgeable about the fire safety procedures in my workplace. 30. I know of the fire detection and alarm systems in my workplace. 31. I am knowledgeable about the emergency plans of my workplace. 32. Regular drills are conducted in my workplace as part of disaster and emergency preparedness activities. 33. I regularly receive training on disasters and emergencies. 34. A purple code is announced for the activation of the emergency response plan. 35. There is an organizational chart established within the scope of the Hospital Disaster and Emergency Plan. 36. The Hospital Disaster and Emergency Plan is updated at the beginning of each year by the Hospital Disaster and Emergency Plan preparation committee. 37. Activities related to reducing non‑structural risks are carried out regularly. 38. I know the location of hospital disaster triage areas. 39. Evacuation methods are divided into two types: internal evacuation (moving patients to other safe areas within the hospital) and external evacuation (moving patients to a safe area outside the hospital). 40. I am knowledgeable about the evacuation plan of my workplace. 41. I know evacuation triage. 42. A yellow code is announced for situations requiring evacuation in the hospital. F2. Training Content and Competency 8 11. I am knowledgeable about my responsibilities as an employee in the field of Occupational Health and Safety. 12. I am aware that I must report near‑miss incidents to the relevant unit. 13. Training needs related to Occupational Health and Safety are identified individually for each employee. 14. I know the safety data sheets of the chemicals used in my department. 16. I am aware that fire types are classified according to the burning material as Class A, Class B, Class C, and Class D fires. 17. I know how to respond to a fire according to its class. 18. Different types of fire extinguishers are available in areas depending on the potential type of fire. 25. There are emergency response teams (firefighting, rescue, protection, first aid) in my workplace. F3. Emergency Preparedness Behavior Level 8 1. Employees receive Basic Occupational Health and Safety Training as soon as possible after starting work. 7. I know that I must inform the relevant personnel if I experience a work accident. 21. The emergency color code for an internal hospital fire is red. 22. I know the internal emergency number I should call in case of a fire. 23. I know the external emergency number I should call in case of a fire. 24. I regularly receive training related to fire safety. 43. I know the emergency exits in my work area. 44. I know the location of the designated assembly area. F4. Patient, Employee, and Facility Safety 7 6. I participate in the risk assessment process at every stage where my involvement is needed. 8. I have knowledge about the personal protective equipment that must be used in my department. 9. Necessary precautions are taken against the risks identified in my department during the risk assessment process. 10. The activities and work organization in the workplace are arranged in a way that prevents employees from having work accidents. 19. I know the locations of the fire extinguishers in my work area. 20. Fire extinguishers are regularly inspected by authorized personnel. 27. When a fire alarm is activated, the Incident Management Team is mobilized. F5. Risk Factors Knowledge Level 4 2. The workplace I work in is classified as a “very hazardous” workplace. 3. Considering the workplace hazard class, the nature of the work, the results of the risk assessment, and employee‑related personal factors, periodic medical examinations for employees are repeated at least once a year. 4. Occupational Health and Safety Trainings for employees are repeated at least once a year in accordance with the workplace hazard class (very hazardous), taking into account emerging and newly identified risks. 5. In accordance with the workplace hazard class (very hazardous), the risk assessment is renewed at least once every two years. Confirmatory factor analysis The PROC CALIS procedure in SAS 9.4 was used to confirm the factor structure. After confirmatory factor analysis, scales with goodness-of-fit index values within the acceptance criteria shown in Table 7 have a confirmed factor structure and are valid and reliable. Table 7 Fit Index Acceptance Criteria Fit Indices Excellent Fit Acceptable Fit Reference RMSEA/ SRMR 0≤RMSEA≤0,05 0,05≤RMSEA≤0,10 [ 13 ] GFI / AGFI 0,90≤GFI≤1,00 0,85≤GFI≤0,90 [ 14 ] NFI 0,90≤NFI≤1,00 0,85≤NFI≤0,90 [ 14 ] CFI 0,90≤CFI≤1,00 0,85≤CFI≤0,90 [ 14 ] χ 2 /df 0≤χ 2 /df≤3 3≤χ 2 /df≤5 [ 11 ] In this study, a confirmatory factor analysis was conducted using Data Set 2 to assess the validity of the factor structure identified for the Occupational Health and Safety Awareness Level Scale. Following the exploratory factor analysis, the PROC CALIS procedure in SAS 9.4 was used to test the factor structure of the candidate scale for awareness of occupational health and safety studies, consisting of a single five-dimensional structure and 44 items. Data from 403 participants in Data Set 2 were used for the confirmatory factor analysis of this scale, which is a five-point Likert scale. To determine whether these data supported the tested factor structure, structural equation modeling results are presented in Table 8 . Table 8 Goodness‑of‑Fit Indices for the Occupational Health and Safety Awareness Level Scale Fit Indices Excellent Fit Acceptable Fit Model Fit Results Fit Level RMSEA 0≤RMSEA≤0,05 0,05≤RMSEA≤0,10 0.046 Excellent Fit SRMR 0≤SRMR≤0.05 0.05≤SRMR≤0.10 0.0620 Acceptable Fit GFI 0,90≤GFI≤1,00 0,85≤GFI≤0,90 0.9852 Excellent Fit AGFI 0,90≤AGFI≤1,00 0,85≤AGFI≤0,90 0.9835 Excellent Fit NFI 0,90≤NFI≤1,00 0,85≤NFI≤0,90 0.9836 Excellent Fit CFI 0,90≤CFI≤1,00 0,85≤CFI≤0,90 0.9248 Excellent Fit χ 2 /df 0≤χ 2 /df≤3 3≤χ 2 /df≤5 0.1295 Excellent Fit This table shows that the Occupational Health and Safety Awareness Level Scale has been validated and proven to be reliable. To reveal the relationship between the observed variables and factors, the statistical significance of the t-values should be examined. It was found that all factor loadings were p < 0.0001 and statistically highly significant. This means that all factor-variable relationships are supported, and the initially proposed factor structure is confirmed. Scale reliability analysis The reliability of the Occupational Health and Safety Awareness Level Scale used in the study was examined using Cronbach's alpha [ 15 ]. The Cronbach's alpha internal consistency coefficients for the scale developed in the study, and its sub-dimensions, are presented in Table 9 . The 44- item scale, which underwent validity and reliability analyses, has an internal consistency coefficient of 0.9787, indicating high reliability (Supplementary Material 1). Furthermore, the Cronbach's alpha internal consistency coefficients for the scale's sub-dimensions ranged from 0.8022 to 0.9693, indicating that the scale is highly reliable. Table 9 Cronbach’s Alpha Coefficients of the Scales and Their Subscales Used in the Study Factor Cronbach Alpha F1 0.9693 F2 0.9340 F3 0.8921 F4 0.8871 F5 0.8022 Overall Scale 0.9787 Results regarding the relationship between scales and sub-dimensions In this study, a correlation analysis was conducted to examine the relationship between the general and sub-dimension scores of the developed Occupational Health and Safety Awareness Level Scale. There are positive, highly significant relationships between the scale's overall score and the sub-dimension scores of F1, F2, F3, F4, and F5 (respectively, r = 0.9607, p = 0.0001; r = 0.9364, p = 0.0001; r = 0.8642, p = 0.0001; r = 0.8308, p = 0.0001; r = 0.7630, p = 0.0001). It was found that the scale's sub-dimensions had moderately high, statistically significant positive correlations with one another. Discussion To prevent occupational accidents among healthcare workers, it is essential that employees are aware of the risks and that their awareness is enhanced. Reinforcing the training provided to workers and monitoring the effectiveness of the measures taken highlights the necessity of preventive systems in today's occupational health and safety approach. Failure to analyze problems correctly not only prevents preventive measures from being taken but also causes occupational accidents. Increasing employee awareness through occupational health and safety training can help employees avoid unsafe behaviors and establish a culture of safety in the workplace. Providing occupational health and safety training on topics that employees need will lead to a significant reduction in workplace accidents. This study aims to prevent occupational accidents among healthcare workers by using an algorithm that evaluates their individual training. Literature reviews have identified a need for tools to measure healthcare workers' awareness of occupational health and safety issues. To this end, a valid and reliable scale to assess employees' awareness of occupational health and safety practices and algorithms to evaluate the training they receive have been developed. The developed scale and algorithms will determine the level of awareness and evaluate the training. The algorithms will integrate occupational health and safety efforts into today's rapidly changing and evolving digital age. It will contribute to the literature by including practices that prevent occupational accidents experienced by healthcare workers. It is believed that the developed scale and algorithms, when applied in practice to healthcare workers, will help determine their awareness of occupational health and safety efforts, one of the most critical factors in preventing workplace accidents. This will enable conducting a current situation analysis and identifying areas for improvement. The results will serve as an essential evaluation tool for workplaces and employers. Although various measures have been taken in this study to reduce bias, some limitations remain. The voluntary selection of participants may limit the generalizability of the results, as it may introduce volunteer bias. A sample consisting solely of healthcare workers employed in specific institutions may not fully reflect the occupational health and safety awareness levels of healthcare workers across different institutions and regions. When examining studies conducted in the field of occupational health and safety, such as employee awareness of occupational health and safety issues, the effectiveness of training in raising employee awareness, the impact of training on accident prevention, and the impact of safety awareness on safe behaviour, it is clear that training has a positive effect on employees and that the effectiveness of training needs to be evaluated. In his study conducted in private healthcare facilities, Devebakan (2007) shared that 47% of the participants stated that occupational health and safety training was not provided at their hospital, while 38.1% of the group who noted that training was provided at their hospital indicated that no measurement or evaluation was conducted after the training [ 16 ]. Regarding healthcare workers' awareness of occupational health and safety, a study conducted among healthcare providers in Tanzania concluded that 430 participants had not received occupational health and safety training, that employees engaged in hazardous behaviours, and that occupational health and safety practices were inadequate. It was concluded that training activities should be prioritised to improve the current situation [ 17 ]. In particular, a study conducted with healthcare workers in operating theatres [ 18 ] and another study conducted with radiology workers [ 19 ] identified deficiencies in ensuring radiation safety. They stated that training was needed to address these deficiencies and increase workers' knowledge. A study conducted in the healthcare sector in Ankara found statistically significant correlations between safety awareness and safety behaviours, and that increased safety awareness positively influenced safety behaviours. The study emphasised the importance of training activities in preventing occupational accidents [ 20 ]. A survey conducted in the Philippines revealed that employees are frequently exposed to occupational hazards and that providing new-employee training to strengthen occupational health and safety, while also supporting other employees with new training, improves compliance [ 21 ]. Conclusion and recommendations In this study, the Occupational Health and Safety Awareness Level Scale and algorithms for evaluating training were developed. The scale and algorithms developed for this study will contribute to research in the field of occupational health and safety in the healthcare sector. The scale items and algorithms have not been previously used or published. The study emphasizes that preventing occupational accidents resulting from exposure to occupational risks faced by healthcare workers, increasing their awareness of occupational health and safety issues and evaluating the training they receive are equally important. The scale and algorithms developed in this study will contribute to research and data collection on healthcare workers' awareness. High safety awareness among healthcare workers, who work intensively to provide uninterrupted healthcare services, will enable them to avoid unsafe actions. It is recommended that practices be continuously measured and evaluated to ensure the sustainability of occupational health and safety and to establish a safety culture. The hospital management system flow charts, developed for hospital management to evaluate healthcare workers' training, are shown in the following figures. Figure 1 below shows the hospital addition process. After the hospital addition process is completed, the hospital administrator addition process is shown in Fig. 2 below. After completing the topic addition (Fig. 3 ), question addition (Fig. 4 ), and exam addition (Fig. 5 ) processes shown below, the selection of questions is performed as shown in Fig. 6 . The process is completed by selecting the hospital to which the selected questions will be sent (Fig. 7 ). Abbreviations SPSS Statistical Package for the Social Sciences PROC CALIS Covariance Analysis of Linear Structural Equations SAS 9.4 Version 9.4 of the Statistical Analysis System Software SRMR Standardized Root Mean Square Residual RMSEA Root Mean Square Error of Approximation GFI Goodness of Fit Index AGFI Adjustment Goodness of Fit Index CFI Comparative Fit Index NFI Normed Fit Index MAP Minimum Average Partial Declarations Supplementary Information Supplementary Material 1 Acknowledgements We would like to extend our special thanks to Hasan Kaba and Sebahattin Murat Halıcı for their support in integrating this study into digital systems so that it could be evaluated using artificial intelligence. Author contributions G.T:conceptualization, data curation, investigation and writing- original draft. H.U.Ö: methodology, statistical analysis, supervision, writing- review and editing, validation. All authors have approved the manuscript for publication. Funding The author(s) received no financial support for this article. Data availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study has received ethical approval from the Ethics Committee of Istanbul Gedik University, Republic of Turkey. Following the ethics committee approval, permission was obtained from the institutions where the research would be conducted (Decision number: E-56365223-050.04-2025.137548.41 date:03.02.2025). The committee's procedures and guidelines are consistent with the principles of the Helsinki Declaration. Therefore, the research was conducted in accordance with internationally accepted ethical standards. Following the ethics committee approval, permission was obtained from the institutions where the research would be conducted. Before starting the study, the purpose of the study was explained to the participants and informed consent was obtained. After obtaining written consent via consent forms, healthcare workers who volunteered to participate in the study were asked to complete the scale. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Peker V. Lojistik Sektöründe İş Sağlığı ve Güvenliği Uygulamaları ve Risk Analizleri [Master’s Thesis]. Gebze Institute of Technology, Institute of Social Sciences, Department of Business Administration, (2009). Güler M. İş Sağlığı ve Güvenliği Eğitiminin İş Kazalarının Önlenmesine Etkisi: İETT Örneği, Master’s Thesis, Istanbul University, Institute of Social Sciences, Department of Industrial Relations and Human Resources, Istanbul, (2011). Turan A, Müezzinoğlu A. ‘Risk Değerlendirme Yöntemleri’. Türk Tabipleri Birliği Mesleki Sağlık ve Güvenlik Dergisi. 2006;7(25):32–6. Karaboğa Ö. Metal Sektöründe İş Sağlığı ve Güvenliği Eğitimlerinin Fayda-Maliyet Açısından İncelenmesi, Specialist Thesis, Ministry of Labour and Social Security, Directorate General of Occupational Health and Safety, Ankara, (2014). Haşıloğlu SB, Baran T, Aydın O. ‘Pazarlama Araştırmalarındaki Potansiyel Problemlere Yönelik Bir Araştırma: Kolayda Örnekleme ve Sıklık İfadeli Ölçek Maddeleri’. Pamukkale J Bus Inform Manage. 2015;2(1):19–28. Yazıcıoğlu Y, Erdoğan S. SPSS Uygulamalı Bilimsel Araştırma Yöntemleri. Detay Publishing, Ankara; 2004. Velicer WF. ‘Determining The Number Of Components From The Matrix Of Partial Correlations’. Psychometrika. 1976;41:321–7. https://doi.org/10.1007/BF02293557 . Büyüköztürk Ş. ‘Faktör Analizi: Temel Kavramlar ve Ölçek Geliştirmede Kullanımı. Kuram ve Uygulamada Eğitim Yönetimi’’. 2002;32(32):470–83. Çapık C. ‘Geçerlik ve Güvenirlik Çalışmalarında Doğrulayıcı Faktör Analizinin Kullanımı’. J Anatolia Nurs Health Sci. 2014;17(3):196–205. Yaşlıoğlu MM. ‘Sosyal Bilimlerde Faktör Analizi ve Geçerlilik: Keşfedici ve Doğrulayıcı Faktör Analizlerinin Kullanılması’. Istanbul Univ J Bus Adm. 2017;46:74–85. Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate Data Analysis. Upper Saddle River, NJ: Prentice Hall; 1998. Büyüköztürk Ş. Sosyal Bilimler İçin Veri Analizi El Kitabı. Pegem Akademi, Ankara; 2011. Brown TA. Confirmatory Factor Analysis For Applied Research, Methodology In The Social Sciences. New York: The Guilford Press; 2006. Tabachnick BG, Fidell LS. Using Multivariate Statistics. 5th ed. Boston: b.), Allyn & Bacon/ Pearson Education; 2007. Özdamar K. Paket Programlar İle İstatistik Veri Analizi. Eskişehir: Kaan Kitabevi; 2002. Devebakan N. Özel Sağlık İşletmelerinde İş Sağlığı ve Güvenliği, Doctoral Dissertation, Dokuz Eylül University, Institute of Social Sciences, Department of Labour Economics and Industrial Relations, Izmir, (2007). Manyele SV, Ngonyani HA, Eliakimu E. ‘The Status of Occupational Safety Among Health Service Providers in Hospitals in Tanzania’. Tanzan J Health Res. 2008;10(3):159–65. https://doi.org/10.4314/thrb.v10i3.14356 . Bacı H. Ameliyathanede Radyasyon Güvenliği; Çalışanların İyonize Radyasyondan Korunmadaki Bilgi Ve Davranışları, Master’s Thesis, Atılım University, Institute of Social Sciences, Department of Health Care Management, Ankara, (2016). Balsak H. Radyoloji Çalışanlarının Tanı Amaçlı Kullanılan Radyasyonun, Zararlı Etkileri Hakkında Bilgi, Tutum ve Davranışları, Master’s Thesis, İnönü University, Institute of Health Sciences, Department of Public Health, Malatya, (2014). Uzuntarla F, Kucukali S, Uzuntarla Y. ‘‘An Analysis on the Relationship between Safety Awareness and Safety Behaviors of Healthcare Professionals’’, Journal Of Occupational Health, 62(1), Ankara, (2020). https://doi.org/10.1002/1348-9585.12129 Faller EM, Miskam NB, Pereira A. ‘Exploratory Study on Occupational Health Hazards Among Health Care Workers in the Philippines’. Annals Global Health. 2018;84(3):338–41. https://doi.org/10.29024/aogh.2316 . Additional Declarations No competing interests reported. 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Toktaş","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYHACAwaGA0CKvQHEtiBKi2EDwwGgNh6QPgMJUrRIJIA4RGiR9z+8/cGHM3/k5Wc+v7rhR4EEA397dwJ+Kw4cK2ycccPAcMPtnLKbPUCHSZw5uwG/lsYew2aeDwaMG6Rz0m7wALUYSOQS0NLMA9ZiP3/mmbSbf4jRIs8G0nLDILHhBvux20TZYsDDVjhzxhnj5A1ncthuyxhI8BD0i3z/4Q0fPhyTs53ffvzZzTd/bOT423sJ2HIAzuQxAJN4lYNtaYAz2R8QVD0KRsEoGAUjEwAAevhNK0q+gskAAAAASUVORK5CYII=","orcid":"","institution":"Gedik University","correspondingAuthor":true,"prefix":"","firstName":"Gözde","middleName":"","lastName":"Toktaş","suffix":""},{"id":596469896,"identity":"29f83acf-af92-45d7-b5ca-7816204295b4","order_by":1,"name":"Hasan Uğur Öncel","email":"","orcid":"","institution":"Gedik University","correspondingAuthor":false,"prefix":"","firstName":"Hasan","middleName":"Uğur","lastName":"Öncel","suffix":""}],"badges":[],"createdAt":"2026-01-22 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6","display":"","copyAsset":false,"role":"figure","size":351865,"visible":true,"origin":"","legend":"\u003cp\u003eQuestion Selection Flow Chart\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8670860/v1/7a991b1e9889a9b868d94d62.jpeg"},{"id":103728663,"identity":"91801471-a6a9-4d09-aed4-a4e337de0a88","added_by":"auto","created_at":"2026-03-02 08:43:35","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":271868,"visible":true,"origin":"","legend":"\u003cp\u003eHospital Selection Flow Chart\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8670860/v1/31daa4eba1da180b9dc54f63.jpeg"},{"id":104407993,"identity":"5d1bde23-adfa-40d3-9236-b101266ac31a","added_by":"auto","created_at":"2026-03-11 12:41:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2022548,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8670860/v1/6fd07316-aead-4b80-ab3f-d38c49de0bf7.pdf"},{"id":103728667,"identity":"221747c8-652c-4868-b93d-7dde08a49d86","added_by":"auto","created_at":"2026-03-02 08:43:35","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":43253,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-8670860/v1/6038eb6fba8c9e8ce94f54f0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Algorithm to evaluate the training of healthcare workers for the prevention of occupational accidents","fulltext":[{"header":"Background","content":"\u003cp\u003eWorkplace accidents occurring worldwide cause significant losses and can negatively impact countries' economies. Workplace accidents among healthcare workers, along with the factors that cause them, demonstrate that healthcare workers are exposed to numerous occupational risks. This situation highlights the urgent need to prevent workplace accidents that affect workers in this sector. In this context, the first step in preventing occupational accidents and diseases is ensuring that employees are aware of which behaviours may pose a risk [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Today's understanding of occupational health and safety is based on a preventive, proactive approach [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe primary philosophy of the occupational health and safety approach is to ensure workers operate in a healthy and safe environment by identifying workplace hazards and risks and taking the necessary precautions to mitigate them. It is essential to identify ways to prevent occupational accidents and diseases, ensure employees receive regular training, and ensure they are aware of protective and preventive behaviours [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Occupational health and safety training has become a crucial tool in promoting desired changes in employee behavior and preventing occupational accidents and diseases. By identifying employees' workplace training needs and meeting them at appropriate intervals and in specific situations, a significant reduction in occupational accidents and diseases is expected [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is possible to achieve behavioural change by converting the knowledge acquired through training into practice, thereby instilling correct behavioural models related to Occupational Health and Safety. Continuous technological developments create a variable environment for occupational safety. This development increases the need for continuous training for employees. In addition, frequent workforce changes in hospitals increase the need for training. This study will enable the individual assessment of employees' training.\u003c/p\u003e \u003cp\u003eFurthermore, the results will provide managers with insights into training effectiveness and will make a significant contribution to determining which training topics employees need. As this data will be personalised, it will indicate which training courses the employee needs. Meeting training needs at appropriate intervals will undoubtedly help prevent accidents among healthcare workers.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eType of research\u003c/h2\u003e \u003cp\u003eThis research employs a methodological model to develop a scale to assess healthcare workers' awareness of occupational health and safety practices.\u003c/p\u003e \u003cp\u003eData were collected through a questionnaire in the research, and the following sampling formula with a known population has been used to determine the sample size:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:n=\\frac{N.P.Q.{Z}^{2}}{\\left(N-1\\right){\\:d}^{2}+Z\u0026sup2;PQ}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eN: Population size,\u003c/p\u003e \u003cp\u003en: Sample size\u003c/p\u003e \u003cp\u003eP: Observation rate of X in the population,\u003c/p\u003e \u003cp\u003eQ (1-P): Non-observation rate of X\u003c/p\u003e \u003cp\u003eZ\u003csub\u003eα\u003c/sub\u003e : α\u0026thinsp;=\u0026thinsp;0.05, 0.01, 0.001 for 1.96, 2.58, and 3.28 values\u003c/p\u003e \u003cp\u003ed= Sample error\u003c/p\u003e \u003cp\u003et\u003csub\u003eα,sd\u003c/sub\u003e = Critical values of the t-distribution with degrees of freedom (sd\u0026thinsp;=\u0026thinsp;n-1). When t\u003csub\u003eα,sd\u003c/sub\u003e\u003c/p\u003e \u003cp\u003ethe critical values are, sd\u0026thinsp;=\u0026thinsp;n-1\u0026rarr; 5000 can be taken as equal to the Zα values\u003c/p\u003e \u003cp\u003eThe study population consists of 1,057 individuals working at a private hospital. In this study, the minimum required sample size was calculated from a population of 1057 individuals, as shown in Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Using a significance level of t\u003csub\u003eα\u003c/sub\u003e = 0.05, a sampling error of \u0026plusmn;\u0026thinsp;0.05, and values of p\u0026thinsp;=\u0026thinsp;0.5 and q\u0026thinsp;=\u0026thinsp;0.5, the minimum sample size was found to be 282 individuals. This means that 282 or more surveys must be conducted to achieve 95% confidence, ensuring that the survey results are within \u0026plusmn;\u0026thinsp;5% of the actual value. Convenience sampling was used in the study. Convenience sampling is a non-random sampling method in which the sample is selected from the population based on the researcher's judgment. In convenience sampling, data is collected from the population in the easiest, fastest, and most economical way [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection tools and techniques\u003c/h3\u003e\n\u003cp\u003eIn the study, data was collected through a questionnaire administered to healthcare workers who volunteer to participate. The draft questionnaire consists of two parts. The first part contains questions designed to determine participants' socio-demographic characteristics. The second part of the questionnaire form contains five-point Likert-type statements designed to assess healthcare workers' awareness of occupational health and safety practices.\u003c/p\u003e\n\u003ch3\u003eQuestions to assess the level of awareness regarding occupational health and safety practices\u003c/h3\u003e\n\u003cp\u003eTo develop the Algorithm for evaluating the Training of Healthcare Workers in the Prevention of Occupational Accidents, a literature review on occupational health and safety practices was conducted. Based on the data collected a pool of 47 items was created.\u003c/p\u003e \u003cp\u003eThe questions were first submitted to experts for their opinion. As a result of evaluating the expert opinions, the number of questions in the draft scale was reduced to 44, and the questions were finalized. A pilot study was conducted with 20 people representing the target participants to obtain feedback on the item statements and determine whether any improvements were needed. During the scale development process, a literature review was conducted, the item pool was created, the scale type was determined, experts reviewed the item pool, and the items were piloted and evaluated.\u003c/p\u003e \u003cp\u003eThe statements in the draft scale were prepared according to a five-point Likert scale. The response options are: 1\u0026thinsp;=\u0026thinsp;Strongly disagree, 2\u0026thinsp;=\u0026thinsp;Disagree, 3\u0026thinsp;=\u0026thinsp;Undecided, 4\u0026thinsp;=\u0026thinsp;Agree, 5\u0026thinsp;=\u0026thinsp;Strongly agree. Following the application of the draft scale to the main population, statistical analyses resulted in the development of the Occupational Health and Safety Awareness Assessment Scale, comprising 44 questions and five sub-dimensions.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical Package for the Social Sciences (SPSS) for Windows, version 25.0, and SAS (version 9.4) were used for statistical analysis of the data obtained in the study [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. For the quantitative variables measured in the research, descriptive statistics such as the mean and standard deviation were used. For qualitative variables measured by counting, such as gender and age, descriptive statistics were presented as numbers and percentages. The data used were first tested for normality using the Shapiro-Wilk test and Skewness values. If the tests showed that the data were normally distributed, parametric tests were used in the statistical analysis; otherwise, non-parametric tests were used. The t-test was used for pairwise comparisons between two-category variables, such as gender, and Analysis of Variance was applied to find differences between variables with three or more categories. Pearson's r moment product correlation coefficient was used to reveal the relationship between quantitative variables, while the Chi-square test was used to examine the relationship between qualitative variables. The means and standard deviations of the scale items, subscales, and overall scale scores were presented in a descriptive statistics table. To test the scale's structure, factor analysis, Cronbach's Alpha, and item-total correlation were performed to assess reliability and validity. Cronbach's Alpha reliability coefficients were calculated to test the internal consistency reliability of the scales. A significance level of 0.05 was accepted throughout the study.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThis section presents the results of the data analysis obtained from questionnaires completed by 806 participants included in the study. First, the findings related to the participants' responses to the socio-demographic questions in the first section of the questionnaire are presented. Subsequently, the results of the exploratory factor analysis, confirmatory factor analysis, reliability analysis, and correlation analysis of the obtained data are presented.\u003c/p\u003e \u003cp\u003eUsing Kendall's W test, the responses of 10 experts were analyzed for the validity of comprehensibility and simplicity of the questions related to occupational safety, and the results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. This table shows that the Kendall W coefficient is 0.448, indicating a moderate level of agreement among the experts furthermore, since the significance values are less than 0.05 (p\u0026thinsp;=\u0026thinsp;0.000), the null hypothesis that 'there is no agreement among experts' is rejected, and it is therefore concluded that there is a moderate and statistically significant level of agreement among experts.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKendall's W Test Results for Agreement Among Experts\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKendall's W\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e205.966\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDemographic characteristics of participants\u003c/h2\u003e \u003cp\u003eA total of 806 questionnaires were collected for the study, and the demographic information of the participants is presented in based on the analysis of these questionnaires. Accordingly:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe average age of participants was 31.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.75, and 71.1% were female (573) and 28.9% were male (233).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe average length of service at the workplace of participants was 28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;30.78 months.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eParticipants were divided into five groups according to their educational status. Accordingly, 31.4% of participants were high school graduates (253), 40.9% were associate degree graduates (330), 18.7% were bachelor's degree graduates (151), 5.1% were master's degree graduates (41), and 3.8% were doctoral degree graduates (31).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIn terms of working hours, 7.2% of participants worked less than 45 hours (58), 71.8% worked 45 hours (579), and the remaining 21.0% worked 45 hours or more (169).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBy work type, 66.0% of participants work during the day (532), 1.7% work at night (14), and the remaining 32.3% work shifts (260).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFinally, it was found that 98.9% of participants had received occupational safety training (797) and 1.1% had not received occupational safety training (9).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eProfessions of participants, 24.7% were nurses (199), 5.7% were doctors (46), 0.4% were pharmacists (3), 1.4% were midwifes (11), 13.5% were technicians (109), 1.2% were physiotherapists (10), 0.5% were psychologists (4), 0.4% were dietitians (3), 0.1% was audiologist (1), 1.7% were technical staff (14), 9.7% were auxiliary healthcare personnel (78), 6.9% were administrative staff (56), 4.2% were others (34), 9.9% were contract staff (80), 19.6% visiting patient services staff (158).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe other socio-demographic characteristics of the participants are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOther Socio-Demographic Characteristics of Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;806)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDepartment Worked In\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Department\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36 (4.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharmacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient Clinics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e165 (20.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral and Dental Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical Therapy and Rehabilitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiation Oncology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperating Rooms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital General\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMain Warehouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdministrative Departments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn Vitro Fertilisation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArchive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBone Marrow Transplantation Unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInpatient Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNursery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKitchen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaundry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Oncology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntensive Care Units\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelivery Room\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Sterilisation Unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNuclear Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmergency Disaster Management Task\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirefighting Team\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital Disaster and Emergency Plan Organizational Structure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91 (11.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRescue Team\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtection Team\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst Aid Team\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Assigned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e610 (75.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFindings related to the scales used in the study\u003c/h3\u003e\n\u003cp\u003eIn this study, the \u0026lsquo;Occupational Health and Safety Awareness Level Scale\u0026rsquo; was used as a candidate scale. This scale was applied to 806 employees, and the resulting dataset was randomly divided into two parts: Data Set 1 and Data Set 2. Before analysing these data sets and the total data set using advanced statistical methods, the mean, standard deviation, and skewness values for each data set are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean, Standard Deviation, and Skewness Values of the Scale Items Used in the Study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSkew\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eData Set 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eData Set 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeneral\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWithin the scope of this study, the questionnaires were randomly divided into two groups, each with 403 participants. Exploratory factor analysis was applied to Data Set 1, and confirmatory factor analysis was applied to Data Set 2. The first step in scale development is exploratory factor analysis. However, before exploratory factor analysis, it is necessary to determine the number of factors.\u003c/p\u003e\n\u003ch3\u003eDetermining the number of factors\u003c/h3\u003e\n\u003cp\u003eOne of the most crucial steps in developing the \u0026lsquo;Occupational Health and Safety Awareness Level Scale\u0026rsquo; is determining the number of factors to be extracted before conducting exploratory factor analysis. In this study, the method used to determine the number of factors, Minimum Average Partial (MAP) Correlation Analysis, was developed by Velicer (1976) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this research, Minimum Average Partial Correlation analysis was performed using Data Set 1, and the results obtained are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Minimum Average Partial Correlation analysis indicates that five factors are sufficient.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMinimum Average Partial Correlation Analysis Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMinimum Average Partial Correlation Analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN Prin Comp Partialled\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSquared\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFourth-Powered\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0135*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0007*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e* MAP\u0026thinsp;=\u0026thinsp;Minimum Values in Columns\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eExploratory factor analysis\u003c/h2\u003e \u003cp\u003eExploratory factor analysis is a multivariate statistical method that combines p interrelated variables to identify a small number of conceptually meaningful new variables (factors, dimensions) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Confirmatory factor analysis is a method applied to assess whether the original structure of previously obtained and used scales. by other researchers is confirmed by newly obtained data [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Confirmatory factor analysis confirms a previously tested factor structure, meaning that the factor structure is valid [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. To determine whether the data set was suitable for factor analysis, the Kaiser-Meyer-Olkin and Bartlett Sphericity tests were first performed [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The findings presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e demonstrate that the assumptions required for exploratory factor analysis are met and that the data are suitable for factor analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKaiser-Meyer-Olkin and Bartlett\u0026rsquo;s Test Results of the Scale\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaiser-Meyer-Olkin and Bartlett's Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaiser\u0026ndash;Meyer\u0026ndash;Olkin Measure of Sampling Adequacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,964\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBartlett\u0026rsquo;s Test of Sphericity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApproximate Chi‑Square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17926,992\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.D.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e946\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn this study, the Varimax orthogonal rotation method was selected for factor analysis. When conducting exploratory factor analysis, the most critical considerations in determining the number of factors are that the items included in each factor are consistent in terms of meaning and content, that the factor eigenvalues are one or greater, that the factor loadings of the items included in a factor are 0.40 or greater, and that the difference between the load values of the items in one factor and the load values of the items in another factor is at least 0.10 or greater [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. When factor analysis and varimax rotation were applied to data set 1, five factors with eigenvalues greater than 1.00 were obtained. This number corresponds to the same number of factors obtained using the Minimum Average Partial method. Since there were no items with factor loadings below 0.40 in the analysis, factor analysis was performed on all 44 items. The factor loadings obtained from the factor analysis explains 69.66% of the total variance of the five-factor structure. This is a remarkably high rate of explanation. The factors obtained from the exploratory factor analysis, the items loaded onto them, and the factor headings are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors and Their Item Loadings\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF1. Knowledge Level on Hospital Disaster and Emergency Plan Preparedness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15. I know the components that form the fire triangle.\u003c/p\u003e \u003cp\u003e26. I know that the principle of fire response is \u0026ldquo;Give Alarm, Rescue, Control, Evacuate/Escape.\u0026rdquo;\u003c/p\u003e \u003cp\u003e28. There are written and visual signs indicating the locations of medical gas shut‑off valves.\u003c/p\u003e \u003cp\u003e29. I am knowledgeable about the fire safety procedures in my workplace.\u003c/p\u003e \u003cp\u003e30. I know of the fire detection and alarm systems in my workplace.\u003c/p\u003e \u003cp\u003e31. I am knowledgeable about the emergency plans of my workplace.\u003c/p\u003e \u003cp\u003e32. Regular drills are conducted in my workplace as part of disaster and emergency preparedness activities.\u003c/p\u003e \u003cp\u003e33. I regularly receive training on disasters and emergencies.\u003c/p\u003e \u003cp\u003e34. A purple code is announced for the activation of the emergency response plan.\u003c/p\u003e \u003cp\u003e35. There is an organizational chart established within the scope of the Hospital Disaster and Emergency Plan.\u003c/p\u003e \u003cp\u003e36. The Hospital Disaster and Emergency Plan is updated at the beginning of each year by the Hospital Disaster and Emergency Plan preparation committee.\u003c/p\u003e \u003cp\u003e37. Activities related to reducing non‑structural risks are carried out regularly.\u003c/p\u003e \u003cp\u003e38. I know the location of hospital disaster triage areas.\u003c/p\u003e \u003cp\u003e39. Evacuation methods are divided into two types: internal evacuation (moving patients to other safe areas within the hospital) and external evacuation (moving patients to a safe area outside the hospital).\u003c/p\u003e \u003cp\u003e40. I am knowledgeable about the evacuation plan of my workplace.\u003c/p\u003e \u003cp\u003e41. I know evacuation triage.\u003c/p\u003e \u003cp\u003e42. A yellow code is announced for situations requiring evacuation in the hospital.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF2. Training Content and Competency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11. I am knowledgeable about my responsibilities as an employee in the field of Occupational Health and Safety.\u003c/p\u003e \u003cp\u003e12. I am aware that I must report near‑miss incidents to the relevant unit.\u003c/p\u003e \u003cp\u003e13. Training needs related to Occupational Health and Safety are identified individually for each employee.\u003c/p\u003e \u003cp\u003e14. I know the safety data sheets of the chemicals used in my department.\u003c/p\u003e \u003cp\u003e16. I am aware that fire types are classified according to the burning material as Class A, Class B, Class C, and Class D fires.\u003c/p\u003e \u003cp\u003e17. I know how to respond to a fire according to its class.\u003c/p\u003e \u003cp\u003e18. Different types of fire extinguishers are available in areas depending on the potential type of fire.\u003c/p\u003e \u003cp\u003e25. There are emergency response teams (firefighting, rescue, protection, first aid) in my workplace.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF3. Emergency Preparedness Behavior Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1. Employees receive Basic Occupational Health and Safety Training as soon as possible after starting work.\u003c/p\u003e \u003cp\u003e7. I know that I must inform the relevant personnel if I experience a work accident.\u003c/p\u003e \u003cp\u003e21. The emergency color code for an internal hospital fire is red.\u003c/p\u003e \u003cp\u003e22. I know the internal emergency number I should call in case of a fire.\u003c/p\u003e \u003cp\u003e23. I know the external emergency number I should call in case of a fire.\u003c/p\u003e \u003cp\u003e24. I regularly receive training related to fire safety.\u003c/p\u003e \u003cp\u003e43. I know the emergency exits in my work area.\u003c/p\u003e \u003cp\u003e44. I know the location of the designated assembly area.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF4. Patient, Employee, and Facility Safety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6. I participate in the risk assessment process at every stage where my involvement is needed.\u003c/p\u003e \u003cp\u003e8. I have knowledge about the personal protective equipment that must be used in my department.\u003c/p\u003e \u003cp\u003e9. Necessary precautions are taken against the risks identified in my department during the risk assessment process.\u003c/p\u003e \u003cp\u003e10. The activities and work organization in the workplace are arranged in a way that prevents employees from having work accidents.\u003c/p\u003e \u003cp\u003e19. I know the locations of the fire extinguishers in my work area.\u003c/p\u003e \u003cp\u003e20. Fire extinguishers are regularly inspected by authorized personnel.\u003c/p\u003e \u003cp\u003e27. When a fire alarm is activated, the Incident Management Team is mobilized.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF5. Risk Factors Knowledge Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2. The workplace I work in is classified as a \u0026ldquo;very hazardous\u0026rdquo; workplace.\u003c/p\u003e \u003cp\u003e3. Considering the workplace hazard class, the nature of the work, the results of the risk assessment, and employee‑related personal factors, periodic medical examinations for employees are repeated at least once a year.\u003c/p\u003e \u003cp\u003e4. Occupational Health and Safety Trainings for employees are repeated at least once a year in accordance with the workplace hazard class (very hazardous), taking into account emerging and newly identified risks.\u003c/p\u003e \u003cp\u003e5. In accordance with the workplace hazard class (very hazardous), the risk assessment is renewed at least once every two years.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eConfirmatory factor analysis\u003c/h2\u003e \u003cp\u003eThe PROC CALIS procedure in SAS 9.4 was used to confirm the factor structure. After confirmatory factor analysis, scales with goodness-of-fit index values within the acceptance criteria shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e have a confirmed factor structure and are valid and reliable.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFit Index Acceptance Criteria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFit Indices\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExcellent Fit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAcceptable Fit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRMSEA/ SRMR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026le;RMSEA\u0026le;0,05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,05\u0026le;RMSEA\u0026le;0,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGFI / AGFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,90\u0026le;GFI\u0026le;1,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,85\u0026le;GFI\u0026le;0,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,90\u0026le;NFI\u0026le;1,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,85\u0026le;NFI\u0026le;0,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,90\u0026le;CFI\u0026le;1,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,85\u0026le;CFI\u0026le;0,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/df\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026le;χ\u003csup\u003e2\u003c/sup\u003e/df\u0026le;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u0026le;χ\u003csup\u003e2\u003c/sup\u003e/df\u0026le;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn this study, a confirmatory factor analysis was conducted using Data Set 2 to assess the validity of the factor structure identified for the Occupational Health and Safety Awareness Level Scale. Following the exploratory factor analysis, the PROC CALIS procedure in SAS 9.4 was used to test the factor structure of the candidate scale for awareness of occupational health and safety studies, consisting of a single five-dimensional structure and 44 items. Data from 403 participants in Data Set 2 were used for the confirmatory factor analysis of this scale, which is a five-point Likert scale. To determine whether these data supported the tested factor structure, structural equation modeling results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGoodness‑of‑Fit Indices for the Occupational Health and Safety Awareness Level Scale\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFit Indices\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExcellent Fit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAcceptable Fit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel Fit Results\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFit Level\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRMSEA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026le;RMSEA\u0026le;0,05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,05\u0026le;RMSEA\u0026le;0,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExcellent Fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSRMR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026le;SRMR\u0026le;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u0026le;SRMR\u0026le;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAcceptable Fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,90\u0026le;GFI\u0026le;1,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,85\u0026le;GFI\u0026le;0,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExcellent Fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAGFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,90\u0026le;AGFI\u0026le;1,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,85\u0026le;AGFI\u0026le;0,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExcellent Fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,90\u0026le;NFI\u0026le;1,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,85\u0026le;NFI\u0026le;0,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExcellent Fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,90\u0026le;CFI\u0026le;1,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,85\u0026le;CFI\u0026le;0,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExcellent Fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/df\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026le;χ\u003csup\u003e2\u003c/sup\u003e/df\u0026le;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u0026le;χ\u003csup\u003e2\u003c/sup\u003e/df\u0026le;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExcellent Fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis table shows that the Occupational Health and Safety Awareness Level Scale has been validated and proven to be reliable.\u003c/p\u003e \u003cp\u003eTo reveal the relationship between the observed variables and factors, the statistical significance of the t-values should be examined. It was found that all factor loadings were p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 and statistically highly significant. This means that all factor-variable relationships are supported, and the initially proposed factor structure is confirmed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eScale reliability analysis\u003c/h2\u003e \u003cp\u003eThe reliability of the Occupational Health and Safety Awareness Level Scale used in the study was examined using Cronbach's alpha [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The Cronbach's alpha internal consistency coefficients for the scale developed in the study, and its sub-dimensions, are presented in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. The 44- item scale, which underwent validity and reliability analyses, has an internal consistency coefficient of 0.9787, indicating high reliability (Supplementary Material 1). Furthermore, the Cronbach's alpha internal consistency coefficients for the scale's sub-dimensions ranged from 0.8022 to 0.9693, indicating that the scale is highly reliable.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCronbach\u0026rsquo;s Alpha Coefficients of the Scales and Their Subscales Used in the Study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCronbach Alpha\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9693\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.8921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.8871\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.8022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall Scale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9787\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eResults regarding the relationship between scales and sub-dimensions\u003c/h2\u003e \u003cp\u003eIn this study, a correlation analysis was conducted to examine the relationship between the general and sub-dimension scores of the developed Occupational Health and Safety Awareness Level Scale. There are positive, highly significant relationships between the scale's overall score and the sub-dimension scores of F1, F2, F3, F4, and F5 (respectively, r\u0026thinsp;=\u0026thinsp;0.9607, p\u0026thinsp;=\u0026thinsp;0.0001; r\u0026thinsp;=\u0026thinsp;0.9364, p\u0026thinsp;=\u0026thinsp;0.0001; r\u0026thinsp;=\u0026thinsp;0.8642, p\u0026thinsp;=\u0026thinsp;0.0001; r\u0026thinsp;=\u0026thinsp;0.8308, p\u0026thinsp;=\u0026thinsp;0.0001; r\u0026thinsp;=\u0026thinsp;0.7630, p\u0026thinsp;=\u0026thinsp;0.0001). It was found that the scale's sub-dimensions had moderately high, statistically significant positive correlations with one another.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo prevent occupational accidents among healthcare workers, it is essential that employees are aware of the risks and that their awareness is enhanced. Reinforcing the training provided to workers and monitoring the effectiveness of the measures taken highlights the necessity of preventive systems in today's occupational health and safety approach. Failure to analyze problems correctly not only prevents preventive measures from being taken but also causes occupational accidents. Increasing employee awareness through occupational health and safety training can help employees avoid unsafe behaviors and establish a culture of safety in the workplace. Providing occupational health and safety training on topics that employees need will lead to a significant reduction in workplace accidents.\u003c/p\u003e \u003cp\u003eThis study aims to prevent occupational accidents among healthcare workers by using an algorithm that evaluates their individual training. Literature reviews have identified a need for tools to measure healthcare workers' awareness of occupational health and safety issues. To this end, a valid and reliable scale to assess employees' awareness of occupational health and safety practices and algorithms to evaluate the training they receive have been developed. The developed scale and algorithms will determine the level of awareness and evaluate the training. The algorithms will integrate occupational health and safety efforts into today's rapidly changing and evolving digital age. It will contribute to the literature by including practices that prevent occupational accidents experienced by healthcare workers.\u003c/p\u003e \u003cp\u003eIt is believed that the developed scale and algorithms, when applied in practice to healthcare workers, will help determine their awareness of occupational health and safety efforts, one of the most critical factors in preventing workplace accidents. This will enable conducting a current situation analysis and identifying areas for improvement. The results will serve as an essential evaluation tool for workplaces and employers. Although various measures have been taken in this study to reduce bias, some limitations remain. The voluntary selection of participants may limit the generalizability of the results, as it may introduce volunteer bias. A sample consisting solely of healthcare workers employed in specific institutions may not fully reflect the occupational health and safety awareness levels of healthcare workers across different institutions and regions.\u003c/p\u003e \u003cp\u003eWhen examining studies conducted in the field of occupational health and safety, such as employee awareness of occupational health and safety issues, the effectiveness of training in raising employee awareness, the impact of training on accident prevention, and the impact of safety awareness on safe behaviour, it is clear that training has a positive effect on employees and that the effectiveness of training needs to be evaluated. In his study conducted in private healthcare facilities, Devebakan (2007) shared that 47% of the participants stated that occupational health and safety training was not provided at their hospital, while 38.1% of the group who noted that training was provided at their hospital indicated that no measurement or evaluation was conducted after the training [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Regarding healthcare workers' awareness of occupational health and safety, a study conducted among healthcare providers in Tanzania concluded that 430 participants had not received occupational health and safety training, that employees engaged in hazardous behaviours, and that occupational health and safety practices were inadequate. It was concluded that training activities should be prioritised to improve the current situation [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn particular, a study conducted with healthcare workers in operating theatres [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and another study conducted with radiology workers [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] identified deficiencies in ensuring radiation safety. They stated that training was needed to address these deficiencies and increase workers' knowledge.\u003c/p\u003e \u003cp\u003eA study conducted in the healthcare sector in Ankara found statistically significant correlations between safety awareness and safety behaviours, and that increased safety awareness positively influenced safety behaviours. The study emphasised the importance of training activities in preventing occupational accidents [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A survey conducted in the Philippines revealed that employees are frequently exposed to occupational hazards and that providing new-employee training to strengthen occupational health and safety, while also supporting other employees with new training, improves compliance [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eConclusion and recommendations\u003c/h2\u003e \u003cp\u003eIn this study, the Occupational Health and Safety Awareness Level Scale and algorithms for evaluating training were developed. The scale and algorithms developed for this study will contribute to research in the field of occupational health and safety in the healthcare sector. The scale items and algorithms have not been previously used or published. The study emphasizes that preventing occupational accidents resulting from exposure to occupational risks faced by healthcare workers, increasing their awareness of occupational health and safety issues and evaluating the training they receive are equally important.\u003c/p\u003e \u003cp\u003eThe scale and algorithms developed in this study will contribute to research and data collection on healthcare workers' awareness. High safety awareness among healthcare workers, who work intensively to provide uninterrupted healthcare services, will enable them to avoid unsafe actions. It is recommended that practices be continuously measured and evaluated to ensure the sustainability of occupational health and safety and to establish a safety culture. The hospital management system flow charts, developed for hospital management to evaluate healthcare workers' training, are shown in the following figures. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below shows the hospital addition process. After the hospital addition process is completed, the hospital administrator addition process is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below. After completing the topic addition (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), question addition (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), and exam addition (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) processes shown below, the selection of questions is performed as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The process is completed by selecting the hospital to which the selected questions will be sent (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e "},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSPSS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePROC CALIS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCovariance Analysis of Linear Structural Equations\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSAS 9.4\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVersion 9.4 of the Statistical Analysis System Software\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSRMR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandardized Root Mean Square Residual\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRMSEA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRoot Mean Square Error of Approximation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGFI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGoodness of Fit Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAGFI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjustment Goodness of Fit Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCFI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eComparative Fit Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNFI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNormed Fit Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMAP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMinimum Average Partial\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Material 1\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to extend our special thanks to Hasan Kaba and Sebahattin Murat Halıcı for their support in integrating this study into digital systems so that it could be evaluated using artificial intelligence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eG.T:conceptualization, data curation, investigation and writing- original draft. H.U.\u0026Ouml;: methodology, statistical analysis, supervision, writing- review and editing, validation. \u0026nbsp;All authors have approved the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) received no financial support for this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has received ethical approval from the Ethics Committee of Istanbul Gedik University, Republic of Turkey. Following the ethics committee approval, permission was obtained from the institutions where the research would be conducted (Decision number: E-56365223-050.04-2025.137548.41 date:03.02.2025). The committee\u0026apos;s procedures and guidelines are consistent with the principles of the Helsinki Declaration. Therefore, the research was conducted in accordance with internationally accepted ethical standards. Following the ethics committee approval, permission was obtained from the institutions where the research would be conducted. Before starting the study, the purpose of the study was explained to the participants and informed consent was obtained. \u0026nbsp;After obtaining written consent via consent forms, healthcare workers who volunteered to participate in the study were asked to complete the scale.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePeker V. Lojistik Sekt\u0026ouml;r\u0026uuml;nde İş Sağlığı ve G\u0026uuml;venliği Uygulamaları ve Risk Analizleri [Master\u0026rsquo;s Thesis]. Gebze Institute of Technology, Institute of Social Sciences, Department of Business Administration, (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eG\u0026uuml;ler M. İş Sağlığı ve G\u0026uuml;venliği Eğitiminin İş Kazalarının \u0026Ouml;nlenmesine Etkisi: İETT \u0026Ouml;rneği, Master\u0026rsquo;s Thesis, Istanbul University, Institute of Social Sciences, Department of Industrial Relations and Human Resources, Istanbul, (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTuran A, M\u0026uuml;ezzinoğlu A. \u0026lsquo;Risk Değerlendirme Y\u0026ouml;ntemleri\u0026rsquo;. T\u0026uuml;rk Tabipleri Birliği Mesleki Sağlık ve G\u0026uuml;venlik Dergisi. 2006;7(25):32\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaraboğa \u0026Ouml;. 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Annals Global Health. 2018;84(3):338\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.29024/aogh.2316\u003c/span\u003e\u003cspan address=\"10.29024/aogh.2316\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Healthcare Worker, Occupational Health, Safety Training, Algorithm, Awareness Level Scale","lastPublishedDoi":"10.21203/rs.3.rs-8670860/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8670860/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWorkplace accidents in the healthcare sector and the factors that cause them demonstrate that healthcare workers are exposed to numerous occupational risks. Preventing occupational accidents among healthcare workers primarily requires that workers be aware of hazards and risks, and that awareness be increased. In this study, an awareness level for occupational health and safety initiatives aimed at preventing workplace accidents among healthcare workers and algorithms for evaluating training programs were developed.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFirst, studies on occupational health and safety awareness among healthcare workers were reviewed, and then a questionnaire inventory consisting of 47 items was created to measure the desired domain. The questions were first submitted to 10 experts for their opinion. As a result of evaluating the expert opinions, the number of questions in the draft scale was reduced to 44, and the questions were finalized. Data was collected from 806 volunteer participants using a survey technique, and the collected data was analyzed using the Kaiser-Meyer-Olkin test, Bartlett test, exploratory factor analysis, and confirmatory factor analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe scale, determined to consist of 44 items based on the analyses, comprises 5 sub-dimensions. The Cronbach's alpha coefficient of the developed scale is 0.9787, and its goodness-of-fit criterion is only the Standardized Root Mean Square Residual (SRMR) fit measure has an acceptable fit value, while Root Mean Square Error of Approximation (RMSEA), Goodness of Fit Index (GFI), Adjustment Goodness of Fit Index (AGFI), Comparative Fit Index (CFI), Normed Fit Index (NFI), and Chi-square / degrees of freedom (χ2/df) have excellent fit values.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn this study, an awareness-level scale was developed for occupational health and safety initiatives to prevent workplace accidents among healthcare workers. This scale will support the work of healthcare managers and professionals.\u003c/p\u003e","manuscriptTitle":"Algorithm to evaluate the training of healthcare workers for the prevention of occupational accidents","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 08:43:24","doi":"10.21203/rs.3.rs-8670860/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-24T16:46:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269939303061708902010047510772716704777","date":"2026-02-24T16:07:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T15:39:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-23T10:26:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-30T20:07:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-28T15:24:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-01-28T14:08:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"86b7e6ec-f7a2-48cf-9a4b-98896d76b5cc","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T08:43:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-02 08:43:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8670860","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8670860","identity":"rs-8670860","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}