A multilevel approach on empowering leadership and safety behavior in the medical industry: The mediating effects of knowledge sharing and safety climate

Safety Science 117 (2019) 1–9

Contents lists available at ScienceDirect

Safety Science journal homepage: www.elsevier.com/locate/safety

A multilevel approach on empowering leadership and safety behavior in the medical industry: The mediating effects of knowledge sharing and safety climate

T

⁎

Yi-Hsuan Leea, Tzu-En Lub, , Cheng Chia Yangc, Gin Changa a

Department of Business Administration, National Central University, No. 300, Jhongda Rd., Jhongli City, Taoyuan County 32001, Taiwan Department of International Business, Chien Hsin University of Science and Technology, No. 229, Jianxing Rd., Zhongli Dist., Taoyuan City 32097, Taiwan c Department of Administration, Kuang-Tien General Hospital, No. 117, Shatian Rd., Shalu Township, Taichung County 433, Taiwan b

A B S T R A C T

This study aimed to validate the influence of empowering leadership on safety behavior in the medical industry and examine the mediating effects of knowledge sharing and safety climate. We adopted a hierarchical linear model to perform a cross-hierarchy analysis on the entire research framework. We examined knowledge sharing and safety behavior on the individual level and examined empowering leadership and safety climate on the organizational level. The findings revealed that empowering leadership is a prerequisite of safety behavior, particularly when leaders are empowering leaders. Such leaders formulate and comply with safety procedures and requirements and enhance safety participation. We validated that knowledge sharing is a key mediator between empowering leadership and safety behavior. Empowering leaders empower employees to participate in decision making and encourage them to resolve problems together and share knowledge, thereby enhancing their knowledge sharing behavior, safety participation willingness, and safety compliance. We also validated the mediating effects of safety climate. Leaders influence employees’ safety behavior through safety climate. When leaders adopt empowering leadership, they create favorable safety climate, which promote safety behavior.

1. Introduction The World Health Organization (WHO, 2018) has estimated that approximately one out of every ten patients will be harmed by health care, meaning that out of every ten patients receiving medical treatment, one will be affected by medical negligence. Moreover, according to the statistics of the British Medical Journal (BMJ), “in the United States, medical negligence is the third leading cause of death after heart attack and cancer” (Makary and Daniel, 2016). This stunning statistical figure has aroused concern among all fields of health care. In the past two decades, patient safety has been the top priority of the global medical system (Cho and Choi, 2018). Patient safety mainly refers to preventing the risk of medical-related injuries (Wallin et al., 2018). Meanwhile, the significance of ensuring patient safety has also been widely recorded in the medical care literature (Braisaite et al., 2015; O’Brien et al., 2018). Relevant research has verified that, if medical care personnel have proper awareness of patient safety, it will reduce many negative impacts such as patient dissatisfaction, complaints and claims, medical mistakes, medical disputes, patient deaths, etc. (Lee et al., 2017). Previous studies have mentioned the links between a patient safety culture and clinical outcomes (DiCuccio, 2015; Wang et al., 2014). In

⁎

particular, Najjar et al. (2015) found that a low incidence of adverse events is associated with a positive patient safety culture. The improvement of safety requires an organizational culture that places safety as its top priority. Most importantly, staff at all organizational levels, from front-line staff to managers and operators, must be committed to safety (Fischer et al., 2018; Thornton et al., 2017). Hospitals often use different programs and methods to promote a safety culture, but unfortunately they often fail to achieve their goals, mainly due to a lack of participation from the leadership (Bahadori et al., 2018). A robust safety culture requires active leadership. Nursing leaders and clinical nurses are fully capable of creating a safety culture that supports patient participation and provides resources for patients and families (Canadian Patient Safety Institute, 2017; Jangland et al., 2017). Therefore, leadership and a safety culture are important factors affecting safety performance, and complementarity between them is vital for its achievement. Leadership is a critical component in organizations that demand a high level of trust, such as medical institutions and nuclear power plants. Leadership can contribute to the establishment of a safety climate (SC), and is a precondition for the achievement of favorable safety performance (Martínez-Córcoles et al., 2013). Previous studies have analyzed the effects of leadership on safety performance (Clarke and

Corresponding author. E-mail addresses: [email protected] (Y.-H. Lee), [email protected], [email protected] (T.-E. Lu), [email protected] (C.C. Yang).

https://doi.org/10.1016/j.ssci.2019.03.022 Received 16 December 2016; Received in revised form 3 February 2019; Accepted 26 March 2019 0925-7535/ © 2019 Elsevier Ltd. All rights reserved.

Safety Science 117 (2019) 1–9

Y.-H. Lee, et al.

safety activities (such as participating in safety meetings, assisting colleagues in solving safety-related problems, and raising safety concerns). Its purpose is to promote the development of a supportive safety environment. Safety compliance, on the other hand, refers to the requirement that individuals need to carry out their business in accordance with work safety norms, which includes following standard operating procedures. This study further proposes that employees’ SBs have an important impact on the safety outcomes of their organization. Relevant literature has also found that safety participation and safety compliance help organizations to create a better safety environment and reduce accidents and injuries. This has been verified by many studies and is also the focus of many SB studies (Neal and Griffin, 2006; Martínez-Córcoles et al., 2013; Shen et al., 2017; Lyu et al., 2018; Wang et al., 2018).

Ward, 2006; McFadden et al., 2009; Mullen and Kelloway, 2009), mostly focusing on either the theory of leadership–member exchange (LMX; Dansereau et al., 1975; Graen and Cashman, 1975) or transitional leadership (Bass, 1985, 1990). Few researchers have discussed the optimal leadership theories for working environments that demand a high level of trust, such as the medical industry. Martínez-Córcoles et al. (2011) analyzed a nuclear power plant to elucidate the effects of empowering leadership (EL) on employees’ perceptions of safety behavior (SB). The researchers found that EL reinforced the SC and enhanced SB perceptions. In this paper, we adopt the EL concept proposed by Arnold et al. (2000) to clarify the effects of EL and EL-related processes on SB. Another crucial factor influencing SB is the aforementioned SC. Zohar (1980) argued that SCs can serve as framework guidelines for measuring SB and facilitate the development of consistent SB-related perceptions and expectations among employees. Subsequently, many scholars have found that SCs are positively correlated to SB (e.g., Neal and Griffin, 2006; Shen et al., 2017; Lyu et al., 2018). That is, a favorable SC is essential for promoting SB (Mearns et al., 2003; Manapragada et al., 2018; Shen et al., 2017; Lyu et al., 2018). The National Patient Safety Agency (2004-2009) introduced the Seven Steps to Patient Safety guide for medical institutions, which contained a chapter on learning and sharing safety lessons. These efforts clearly show that knowledge sharing (KS) is a vital aspect of patient safety. EL facilitates collaborative learning and promotes KS behavior (Martínez-Córcoles et al., 2012; Srivastava, Bartol, and Locke, 2006). Empowering leaders clearly outline the missions of their team members and highlight team objectives. They create learning cultures by sharing goals, thereby enhancing willingness to share knowledge and promoting learning (Chang and Chuang, 2011). Edmondson (2002) believed that KS could result in the evaluation of past behaviors, discovery of errors, creation of new behaviors, and reduction of medical errors. By reinforcing employees’ willingness to engage in collaborative learning and share their experiences, it enables team members to learn from past mistakes and address patient safety concerns (Firth-Cozens, 2001). Based on the above illustration, this study puts forward three hypotheses: H1: Leadership style will positively affect safety behavior. H2: Leadership style will affect personal safety behavior through knowledge sharing. H3: Leadership style will affect safety behavior through a safety climate. Nurses represent one of the most important groups of front-line personnel in medical institutions, making up the largest proportion of hospital staff. They play an important role in the implementation and promotion of patient safety advocated by medical institutions, because they shoulder the majority of the responsibility for patient safety. Thus, their perceptions of safety behavior are closely related to the effectiveness of patient safety work (Armstrong et al., 2017; Colet et al., 2018). Therefore, this study focuses on nurses (they make up the highest proportion of the sample) to investigate whether EL is helpful in the medical industry for creating SBs. Secondly, this study explores how EL promotes employees' SBs through KS. Finally, it looks at how EL promotes employees' SBs through a SC.

2.2. Empowering leadership (EL) and safety behavior (SB) Srivastava et al. (2006) defined EL as the sharing of authority with subordinates to improve intrinsic motivation. EL behaviors comprise encouraging participation in decision making, coaching, leading by example, showing concern and interacting with employees, and information sharing. Martínez-Córcoles et al. (2013) indicated that EL directly influences subordinates’ safety participation and safety compliance. Bandura (1977) asserted that employees are affected by social learning processes. Therefore, when leaders demonstrate EL traits, employees are likely to observe and imitate these behaviors. Hoffmeister et al. (2014) stated that leaders are role models for their subordinates and enhance their safety compliance and safety participation. Thus, in this paper we argue that team members observe the behaviors of their leaders. When leaders lead by example and practice appropriate SBs, employees are likely to imitate these behaviors, thereby enhancing their compliance with safety systems and their safety participation. Naevestad (2008) explained that leaders should encourage employees to participate regularly in safety discussions and activities, actively integrate different perspectives on SBs, and adopt SB as a core value of organizational culture. Leaders should urge members to express their personal views and opinions and encourage employees to participate in the formulation of safety decisions to enhance the group’s commitment to them and ensure safety. Yule et al. (2007) found that employees are more likely to abide by safety protocols if they are aware of the potential damage that could be caused by their violation. Therefore, enhancing employees’ safety knowledge contributes to improving their safety compliance and safety participation (Neal et al., 2000). Coaching behavior refers to managers’ close interactions with employees in the workplace, allowing them to identify the root causes of poor performance and provide mentoring to improve performance (Hackman and Wageman, 2005). Therefore, empowering leaders coach employees in the workplace and fully impart their experience, skills, and knowledge. The rapid and comprehensive dissemination of information reduces the time required for learning, enables employees to promptly apply this knowledge in their field of work, and accelerates the organization’s progress towards safety goals. These behaviors enhance employees’ safety participation and compliance behaviors. To summarize previous research, we believe that empowering leaders can directly influence employees’ SBs. Therefore, we propose the following hypothesis:

2. Literature review and hypothesis development 2.1. Safety behavior (SB) SB is one of the major concerns of most organizations around the world (Amponsah-Tawaih and Adu, 2016). Especially in medical institutions, SB has an important impact on the promotion of patient safety and the reduction of medical negligence (Katz-Navon et al., 2005). SBs refer to an individual's behaviors with regards safety (Christian et al., 2009). Improper SBs are a major cause of work accidents. Improvements in individuals’ SBs can help reduce the occurrence of work accidents (Feng and Chang, 2018). Neal and Griffin (2006) classified SBs into safety compliance and safety participation. Safety participation refers to the voluntary participation of employees in

H1: Empowering leadership (EL) positively influences patients’ safety behaviors (SBs). 2.3. The mediating effect of knowledge sharing (KS) on empowering leadership (EL) and safety behavior (SB) Cabrera et al. (2006) asserted that personal knowledge is shared 2

Safety Science 117 (2019) 1–9

Y.-H. Lee, et al.

H2: Empowering leadership (EL) influences patients’ safety behaviors (SBs) through the mediating effect of knowledge sharing (KS) behaviors.

among employees within an organization. This personal knowledge gradually becomes organizational knowledge, forming a culture in which KS complements organizational learning. However, KS does not occur automatically in groups; leaders serve as the actuators of KS behavior. Srivastava et al. (2006) asserted that team leaders who are able to gain members’ approval of their authority and who praise members’ KS behaviors can effectively promote KS behavior in their teams. House and Dessler (1974) maintained that supportive leaders are able to lead by example and guide their team members. They treat their subordinates fairly and enable employees to improve at their work. Therefore, we believe that EL causes team members to perceive their views and knowledge as beneficial to the team. This type of fair perception motivates members to share their unique knowledge with one another (Srivastava et al., 2006). Similarly, empowering leaders urge employees to participate in decision making and share knowledge. Therefore, such leaders encourage members to express their personal opinions and provide relevant suggestions (Locke et al., 1997). When members’ opinions are adopted, their willingness to share information increases, and when they are empowered to make decisions concerning their work, they generally exchange knowledge with other members of the team to facilitate the decision-making process. This behavior enables them to acquire sufficient information to make rational decisions. Therefore, EL can stimulate KS (Xue et al., 2011). Arnold et al. (2000) asserted that the coaching behaviors of empowering leaders empower team members to resolve problems together and provide opportunities for members to share knowledge. Hackman and Wageman (2005) indicated that appropriate coaching is a stimulus for members to actively learn within an organization, thereby strengthening the ability of teams to carry out tasks. In other words, the learning and research and development (R&D) behaviors of members, organizational procedures, and knowledge application within the organization increase concurrently with employees’ awareness of increased coaching behavior. Therefore, the coaching behavior of EL benefits members’ KS behaviors (Nemanich et al., 2010; Robertson et al., 2012). Bowen and Lawler (1992) argued that empowerment not only allocates authority to employees but also urges them to share information and knowledge. Thus, empowering leaders should share authority and knowledge with their team members and utilize EL to promote members’ KS behaviors. Martínez-Córcoles et al. (2012) explained that empowering leaders effectively create environments for collaborative learning. In summary, we agree that EL facilitates the creation of environments that support collaborative learning and enhances KS behavior. Previous research has verified that KS is essential because it reduces unnecessary learning processes within companies (Scarbrough, 2003). Meurier (1997) found that the most prominent reason for medical malpractice is a lack of knowledge and experience. An effective knowledge management environment forms trial-and-error learning and work environments that enhance employees’ safety knowledge and prevent the reoccurrence of mistakes and accidents (Edmondson, 2004). According to the framework proposed by Neal et al. (2000), safety knowledge is an antecedent of SB. Those researchers highlighted that safety knowledge affects safety compliance and safety participation. Christian et al. (2009) performed a posterior analysis and found that safety knowledge is an antecedent of safety performance and leads safety participation and safety compliance. Martínez-Córcoles et al. (2012) found that employees’ safety participation willingness increases when they engage in mutual learning and acquire safety knowledge. In summary, we hypothesize that KS behavior enhances employees’ safety knowledge, their safety participation willingness, and their compliance with occupational safety regulations. We believe that KS is an important mediator. Empowering leaders incorporate employees into decision-making processes and encourage them to resolve problems together and share knowledge, thereby enhancing their KS behavior.

2.4. The mediating effect of a safety climate (SC) on empowering leadership (EL) and safety behavior (SB) Zohar (1980) introduced the concept of the SC in 1980. It has since been defined as a “snapshot” of employees’ safety awareness (Mearns et al., 1997, 2000; Yule et al., 2007; Shannon and Norman, 2009). Based on the framework proposed by Zohar and Luria (2005), Zohar (2008), we define a SC as an organizational climate that focuses on safety. A SC is used to describe the perceived value of workplace safety, including the awareness of safety policies, protocols, and practices. Many scholars have found that a SC is positively correlated to SBs (Neal and Griffin, 2006; Shen et al., 2017; Lyu et al., 2018). Therefore, a favorable SC is essential for enhancing employees’ SBs (Mearns et al., 2003; Manapragada et al., 2018; Shen et al., 2017; Lyu et al., 2018). An antecedent of the promotion of a beneficial SC is the creation of intervention strategies, a process in which leaders are key (FernandezMuniz et al., 2007; Kohn et al., 2000). Several previous studies have thoroughly analyzed the relationships between leadership behavior, a SC, and safety performance (Martínez-Córcoles et al., 2011; Yule et al., 2007). Numerous scholars have argued that effective leadership traits for improving the SC include the ability to formulate clear and feasible objectives and deliver concepts and values. Leaders should value feedback and communication, encourage participation, show concern, and interact with their teams (Katsva and Condrey, 2005; Flin and Yule, 2004). Clarke (2006) asserted that leaders should be inspirational, provide consultation, and engage in rational persuasion. They should also formulate objectives, systems, and regulations, provide incentives, and actively express concern to create a favorable SC. Flin and Yule (2004) suggested that leaders can improve the SC by leading their teams toward common goals, showing concern, providing feedback, and encouraging SB. Hoffmeister et al. (2014) highlighted several leadership behaviors that influence the SC, including being a role model to subordinates, gaining the recognition, respect, and trust of subordinates, inspiring employees to develop new interpretations, and encouraging the application of new methods to overcome challenges. This literature indicates that leadership behaviors influence the SC. Although a common theoretical framework highlighting behavior that enhances the SC has yet to be developed, these studies do discuss various common EL traits. Leaders should guide their teams toward achieving common goals and assist subordinates in forming clear views of their objectives and visualizing projects (i.e., KS; Flin and Yule, 2004). They should be role models and convey work requirements through action (i.e., leading by example; Blair, 2003; Hoffmeister et al., 2014). They should communicate frequently with their subordinates and encourage them to join in the decision-making process (i.e., encouraging participation in decision making; Katsva and Condrey, 2005; Flin and Yule, 2004). They should train employees to be independent and autonomous and resolve workplace problems through innovative means (i.e., coaching; Yang et al., 2009). They should actively care for their team members (i.e., showing concern and interacting with the team; McFadden et al., 2009). Thus, we believe that EL enhances the SC. The relationship between the SC and safety performance has been analyzed by numerous scholars (Hofmann and Stetzer, 1996; Neal and Griffin, 2006; Neal et al., 2000; Smith et al., 2006; Zohar, 2000, 2002; Zohar and Luria, 2005; Martínez-Córcoles et al., 2011; Clarke, 2006, 2013). Thus, a favorable SC is essential for promoting SB (Mearns et al., 2003). Previous studies have indicated that the SC mediates the relationship between leadership behaviors and employees’ SBs (Barling et al., 2002; Clarke and Ward, 2006; Kelloway et al., 2006; Clarke, 2006; 3

Safety Science 117 (2019) 1–9

Y.-H. Lee, et al.

Group level Empowerment Leadership

3.1.2. Knowledge sharing (KS) To measure the employees’ KS behavior, we used Lee’s (2001) seven-item scale. The employees were asked to assess transferring or disseminating knowledge behavior within their work unit on a fivepoint scale (1 = strongly disagree; 5 = strongly agree). Sample items included: “We and our service provider share business proposals and reports with each other” and “We and our service provider share knowhow from work experience with each other”. These items were averaged into a composite score, with higher scores indicating greater KS.

Safety Climate

H3

H2 Knowledge Share

H1

Safety Behavior

3.1.3. Safety climate (SC) To measure SC, we adapted 25 items from Sexton’s (2006) Safety Attitude Questionnaire (SAQ). The scale consisted of five dimensions: teamwork climate, safety climate, perceptions of management, job satisfaction, and working conditions. Sample items by dimension included (a) teamwork climate: “I have the support I need from other personnel to care for patients”; (b) safety climate: “I am encouraged by my colleagues to report any patient safety concerns I may have”; (c) perceptions of management: “The hospital administration supports my daily efforts”; (d) job satisfaction: “I am proud to work at this hospital”; and (e) working conditions: “This hospital does a good job of training new personnel”. The employee participants were asked to answer each item on a five-point scale (1 = strongly disagree; 5 = strongly agree). Since our hypotheses are concerned with the organizational level of SC from a general perspective, the analyses were conducted with an SC composite that combined the five sub-scales. In our study, the correlations among the five dimensions ranged from 0.689 to 0.825. We further conducted a second-order CFA to determine whether the five dimensions were nested under a second-order factor (i.e., overall score for SC). The CFA results showed that the second-order model fit the data well (CFI = 0.866, AGFI = 0.862, NFI = 0.920, RMR = 0.032). The results suggested that it should be appropriate to combine the scores of the five dimensions into an overall score for SC.

Individual level Fig. 1. Research framework.

Martínez-Córcoles et al., 2011). However, few scholars have analyzed the safety participation and safety compliance aspects of the SC. Clarke (2006, 2013) found that a positive SC influenced employees’ safety participation and safety compliance. We believe that empowering leaders help their teams visualize the safety behavior of the organization and lead by example in fulfilling safety requirements. Such leaders also train members to independently resolve work-related problems, help them improve their safety skills, and actively care for members so as to create a favorable SC. Consequently, a favorable SC is essential for enhancing employees’ SBs (Mearns et al., 2003). Thus, we believe that EL affects SB through the SC. Based on the preceding discussion, the following hypothesis was formed: (see Fig. 1.) H3: The safety climate (SC) mediates the relationship between empowering leadership (EL) and employees’ safety behavior (SB).

3.1.4. Safety behavior (SB) To measure the employees’ SB, we adapted six items from Neal and Griffin (2006). The scale used in our study consisted of two dimensions: safety participation and safety compliance. Sample items included “If I have good ideas for patient safety promotion, I will provide them to my supervisor” (safety participation) and “When I care for or treat patients, I always identify patient status in at least two ways” (safety compliance). The employees were asked to self-report their SBs towards patients on a five-point scale (1 = strongly disagree; 5 = strongly agree). The inter-correlations among the two dimensions were highly correlated and thus hard to separate from each other (Neal and Griffin, 2006). In our study, the correlation between the two dimensions was 0.69, consistent with the empirical study of Neal and Griffin (2006). Thus, we combined the scores of the two dimensions into an overall SB score.

3. Research method 3.1. Variable measurement 3.1.1. Empowering leadership (EL) To measure EL, we adapted16 items from Arnold et al. (2000) because the original scale was too long given the time constraints of this study (Martínez-Córcoles et al., 2011). The scale consists of five dimensions: leading by example, participative decision making, coaching, informing, and showing concern for/interacting with the team. Sample items (by dimension) include “My supervisor sets high standards for performance by his/her own behaviour” (leading by example); “My supervisor encourages work group members to express ideas/suggestions” (participative decision making); “My supervisor helps my work group see areas in which we need more training” (coaching); “My supervisor explains his/her decisions and actions to my work group” (informing); and “My supervisor shows concern for work group members’ well-being” (showing concern for/interacting with the team). Employees were asked to rate their supervisors’ EL style on a five-point scale (1 = strongly disagree; 5 = strongly agree). The participants’ responses to the items within each dimension were averaged to form an overall EL score based on existing theoretical perspectives (e.g., Martínez-Córcoles et al., 2011). In our study, the correlations among the five dimensions ranged from 0.676 to 0.865. We further conducted second-order confirmatory factor analysis (CFA) to determine whether the five dimensions were nested under a second-order factor (i.e., overall score of EL). The CFA results demonstrated that the secondorder model fit the data well (GFI = 0.870, AGFI = 0.820, NFI = 0.942, RMR = 0.029). The results suggested that it should be appropriate to combine the scores of the five dimensions into an overall score for EL.

3.1.5. Control variables Prior studies have suggested that employee demographics such as age, job tenure, education, and gender are significantly associated with employees’ SB and safety performance (Zhou and George, 2001; Shalley and Gilson, 2000; Zhang and Bartol, 2010). Thus, in order to enhance the generalizability of the results, we controlled for the employees’ age, job tenure, education, and gender when testing the hypotheses. 3.1.6. Common method variance In this study, a self-reported scale was used to collect data from a single subject, which can easily lead to the problem of common method variance. Therefore, we conducted Harman’s single-factor test as a post hoc statistical analysis to examine this potential threat (Podsakoff et al., 2003). We performed a principal component factor analysis, including all the scales used in this study, to determine whether a single general factor accounted for the majority of the variance among all the scales. 4

Safety Science 117 (2019) 1–9

Y.-H. Lee, et al.

The results of the factor analysis indicated that eight factors with eigenvalues greater than one explained 71.85% of the total variance. The first factor accounted for 41.77% (< 50%) of the variance, thus not explaining most of the variance (Podsakoff and Organ, 1986). Accordingly, we concluded that common method bias was not a major concern in this study.

Table 1 Sample profiles (n = 775). Item

Variable

n

Percentage

Gender

Male Female

127 648

16.4 83.6

Age (years)

< 20 20–29 30–39 40–49 50–59 ≥60

3 309 322 103 37 1

0.4 39.9 41.5 13.3 4.8 0.1

Educational Level

High school or vocational school University or college Graduate school and above

31 711 33

4 91.7 4.3

Seniority

< 6 months 6–11 months 1–2 years 3–4 years 5–10 years 11–20 years ≥21 years

28 60 137 93 221 197 39

3.6 7.7 17.7 12 28.5 25.4 5

Occupational Type

Physician Nurse Medical technologist Administrator

95 525 106 49

12.3 67.7 13.7 6.3

Managerial Position

Yes No

80 695

10.3 89.7

3.2. Sampling and data collection In this study we adopted the convenience sampling method. Data were collected from 775 medical staff in three large hospitals in Taiwan. We first obtained the permission and support of each hospital’s managers for the data collection. The surveys were collected during work hours by the managers contacted in each hospital. Each manger was instructed to distribute the survey questionnaire within certain work units. The work units selected by the contacted managers had to fulfill the following conditions: (1) they had to represent the smallest functional unit in the hospital, (2) all employees had to report directly to the same supervisor, and (3) the employees had to have been working together on a long-term basis. The employee participants were randomly selected up to a maximum of 30 individuals from each work unit. In addition, this study used hierarchical linear model analysis. The survey was distributed to a total of 70 work units, and the average work unit size was 11 employee members (ranging from 3 to 30). To reduce the possibility of social desirability influencing responses (Podsakoff and Organ, 1986), each participant received a questionnaire packet containing a self-addressed stamped envelope and a cover letter explaining the purpose of the study and providing assurances of confidentiality. Additionally, after completing the questionnaires, the respondents were required to return them directly to the researchers by mail. A total of 1000 surveys were distributed and 775 completed surveys were returned, representing a 77.5% valid response rate. Of the total of 775 employees participating in this study, 67.7% of the respondents were nurses, 13.7% were medical technologist, 12.3% were physicians, and 6.3% administrators. Nurses play a vital role in safeguarding patients; as frontline advocates, nurses are the primary implementers of safety and quality initiatives in the clinical setting (Armstrong et al., 2017; Colet et al., 2018). In this study, nurses make up the highest proportion of the respondents (67.7%). Of the total of 775 employees participating in this study, 81.8% were 39 years of age or younger. The male-to-female ratio was approximately 16:84. 91.7% had completed college or university degrees and 4.3% had completed graduate degrees. Most respondents had more than five years of organizational tenure, making up 58.9% of the sample. A total of 89.7% of the employee respondents were in non-managerial positions, while the remaining 10.3% were in managerial positions (see Table 1).

Discriminant validity was obtained by comparing the shared variance between factors with the average variance extracted from the four factors (Fornell and Larcker, 1981). Table 3 shows that the constructs met this criterion. Hence, discriminant validity was assured. To sum up, the four constructs showed satisfactory levels of reliability, convergent validity, and discriminant validity. 4. Results Given that each participant provided data at the work-unit level (level 2, which included EL and SC) and at the individual level (level 1, which included KS and SB), our hypothesis testing required hierarchical or cross-level techniques. Conventional statistical techniques, such as the ordinary least squares method, may have violated the independence assumption and led to an overestimation of the parameters. Since hierarchical linear modeling (HLM) can deal with non-independence issues and estimate the impacts of factors at different levels simultaneously (Raudenbush and Bryk, 2002), we used it as an analytic tool to test our hypotheses. Moreover, the mediation effects were tested with four criteria recommended by Baron and Kenny (1986) and Sobel (1982). To examine the appropriateness of multilevel analysis, we estimated a null model in which no predictors were specified at either level 1 (individual level) or level 2 (organizational level) to test the significance level of the level-2 residual variance of the intercept. The results showed that there was significant between-group variance (χ2 = 156, df = 69, p < 0.00) for SB. Calculating the ICC value indicated that 6.9% of the variance in SB was between-group. Thus, a multilevel analysis was justified. Hypothesis 3 suggested that the SC mediates the relationship between EL and SB. We followed the procedure proposed by Kenny et al. (1998) to test for mediation, as presented in Table 4. In the first step, we examined the effect of EL on SB and the results showed a significant positive association (Hypothesis 1), thus meeting the first requirement. Next, EL needs to be associated with the SC. We used regression analysis to test this hypothesis because both variables belong to the organizational level. After controlling for the influences of age, tenure, education, and gender, the results indicated that there was a significant

3.3. Reliability and validity We employed three software packages, SPSS 21, AMOS 20.0, and HLM 7, to conduct the statistical analysis. Four CFAs were carried out using AMOS 20.0 to test the measurement models. Model fit measures (CFI, NFI, AGFI, and RMR) were used to assess the model’s overall goodness of fit, and the values all exceeded their respective common acceptance levels (Hair et al., 2006). This showed that the measurement model exhibited a fairly good fit with the collected data (see Table 2). Convergent validity of the scale items was estimated by means of reliability, composite reliability, and average variance extracted (Fornell and Larcker, 1981). The standardized CFA loadings for all scale items exceeded the minimum loading criterion of 0.5, and the Cronbach’s alphas and composite reliabilities of all factors also exceeded the recommended level of 0.7 (Hair et al., 1998). In addition, the average variance extracted values were all above the threshold value of 0.5 (Hair et al., 2006). Hence, all three conditions for convergent validity were met for the four constructs (see Table 2). 5

Safety Science 117 (2019) 1–9

Y.-H. Lee, et al.

Table 2 Convergent validity. Variables

α

AVE > 0.5

λ > 0.5

CR > 0.7

CFI > 0.9

AGFI > 0.8

NFI > 0.9

RMR < 0.05

Empowering leadership Safety climate Knowledge sharing Safety behavior

0.970 0.940 0.960 0.903

0.875 0.867 0.798 0.675

0.825–0.933 0.552–0.912 0.850–0.934 0.597–0.910

0.984 0.970 0.965 0.924

0.870 0.886 0.850 0.950

0.820 0.862 0.810 0.970

0.942 0.920 0.931 0.980

0.024 0.032 0.021 0.014

Note: α = Cronbach’s alpha.

supporting the first requirement. Second, they showed that the relationship between EL and KS was significant (γ = 0.653, p < 0.00; see M6), supporting the second requirement. Similarly, KS was significantly related to SB (γ = 0.534, p < 0.00; see M1), supporting the third requirement. Finally, the results revealed that the relationship between KS and SB was significant (γ = 0.526, p < 0.00; see M3). However, the relationship between EL and SB was no longer significant (γ = 0.087, p > 0.05; see M3). Hence, KS mediates the effect EL has on SB. Thus, Hypothesis 2 was supported.

Table 3 Mean, standard deviation, correlation, and discriminant validity. Variables

Mean

SD

(1)

(1) Empowering Leadership (2) Safety Climate (3) Knowledge Sharing (4) Safety Behavior

3.946

0.722

0.935a

3.930 3.996 4.020

0.639 0.709 0.646

0.735** 0.764** 0.563**

(2)

(3)

(4)

0.931a 0.704** 0.628**

0.893a 0.609**

0.818a

Note: *p < 0.05; **p < 0.01; ***p < 0.001. a Represent the square root of average variance extracted, and the other matrix entries are the factor correlation.

5. Discussion and conclusions

association between EL and the SC (β = 0.64, p < 0.00; see M7). In step 3, we examined the effect of the SC on SB and the results showed a significant positive association (γ = 0.598, p < 0.00; see M4), supporting the third requirement. Finally, we examined whether the effect of EL on SB became insignificant or reduced when both EL and the SC were used jointly as predictors of SB, which would confirm the mediating effect of the SC. The results revealed that the relationship between EL and SB was indeed no longer significant (γ = 0.114, p > 0.05; see M5). Hence, the SC fully mediates the effect of EL on SB. In other words, EL enhances employees’ SB fully through the SC. Thus, Hypothesis 3 was supported. The results of the hypothesis tests are shown in Table 4. Hypothesis 1 posited a positive relationship between EL and SB. As expected, the results supported this (γ = 0.37, p < 0.00; see M2). Hypothesis 2 suggested that KS mediated the relationship between EL and SB. We followed a similar procedure (Kenny, Kashy, and Bolger, 1998) in testing the mediation effect, as presented in Table 4. First, the results showed that EL was significantly related to SB (Hypothesis 1),

This study aimed to validate the influence of empowering leadership (EL) on safety behavior (SB) in the medical industry and to examine the mediating effects of knowledge sharing (KS) and a safety climate (SC). Social and organizational factors have an effect in medical research. Analyzing these factors enables researchers to understand and improve SB models and prevent medical malpractice stemming from human behavior. The main objective of our research was to develop a verification model to explain the effects of leaders’ behaviors on employees’ SBs. The findings revealed that EL is a prerequisite. Such leaders formulate and comply with safety procedures and requirements and enhance safety participation. They adopt various means of encouraging employees to participate in decision making and share their views. They also show concern for employees’ work performance and psychological states, thereby motivating employees to identify with the organization, fostering their abilities, and reducing their risk of engaging in dangerous behaviors. The findings obtained in this paper show that organizational-level EL directly influences the individual-level SBs

Table 4 Results of Hierarchical Linear Modeling. Variable

Individual Level Intercept Age Education Tenure Gender Knowledge Sharing

Safety Behavior

Safety Climate M7

Null Model

M1

M2

M3

M4

M5

M6

4.050**

3.568*** 0.172*** 0.028 0.020 −0.001 0.534***

3.362*** 0.172*** 0.073 −0.001 −0.008

3.583 *** 0.107** 0.021 0.020 0.001 0.526***

3.499*** 0.168*** 0.056 −0.002 −0.043

3.482*** 0.169*** 0.055 −0.001 −0.034

3.893*** 0.108* 0.034 −0.039 −0.098

0.370***

0.087

0.653***

0.598***

0.114 0.498***

0.315 0.354 −0.036 0.286 1445.75

0.353 0.355 −0.035 0.324 1449.10

0.109 0.435 0.045 0.080 1595.91

Group-Level Empowering Leadership Safety Climate τ00 σ2 R12 R22 Deviation

Knowledge Sharing

0.029 0.390

***

1512.23

0.058 0.224 −0.166 0.029 1130.32

0.507 0.357 −0.033 0.478 1458.60

0.070 0.225 −0.165 0.041 1134.09

Notes: N = 775 (employees), 70 (groups). * p < 0.05. ** p < 0.01. *** p < 0.001. 6

1.471*** 0.640***

Safety Science 117 (2019) 1–9

Y.-H. Lee, et al.

of subordinates (H1), which is consistent with the findings of MartínezCórcoles et al. (2013), who asserted that behavioral leadership directly influences employees’ behaviors. This influence stems from social learning processes (Bandura, 1977). Team members observe and imitate the SBs of their leaders, improving safety compliance and safety participation. A new mediator is also proposed in this paper—KS. Previous papers that have adopted KS as a mediator have largely focused on the unidirectional influence of EL on KS (Srivastava et al., 2006) or the influence of KS on SB (Christian et al., 2009). Consequently, the positive influence of EL on SB with KS as a mediator has yet to be analyzed. In this study, we validated that KS is a key mediator between EL and SB. Empowering leaders empower employees to participate in decision making and encourage them to resolve problems together and share knowledge, thereby enhancing their KS behavior, safety participation willingness, and safety compliance (H2). We found that KS has an absolute mediating effect on the relationship between EL and SB, indicating that the mediating effect of KS on SB is greater than the direct influence of EL on SB. These findings imply that, without pre-existing KS, employees are less willing to share their knowledge, even when empowering leaders motivate them to share their views, prospects, and suggestions with others. The lack of sharing and interactive learning behaviors among team members hinders the effective dissemination of safety knowledge within the unit, which negatively impacts SBs therein. Therefore, we believe that EL can only effectively influence SB with the mediation of KS. These findings are consistent with the outcomes proposed by Martínez-Córcoles (2012), namely that EL motivates team members to learn from one another and acquire safety knowledge, and thus enhances safety participation. We also validated the mediating effects of a SC. Leaders influence employees’ SBs through a SC. When leaders adopt EL, they create a favorable SC, which promotes SB (H3). Not only are the findings obtained in this study consistent with the outcomes of a number of previous studies, which have verified the mediating effect of a SC on the relationship between leadership behaviors and employees’ SBs (Barling et al., 2002; Clarke and Ward, 2006; Kelloway et al., 2006; Clarke, 2006, 2013; Martínez-Córcoles et al., 2011), but they surpass past observations. Unlike previous research that has analyzed the SC from the individual perspective, we have discussed the effects of the organizational SC on SB and validated the importance of the SC for the relationship between EL and SB. From the academic perspective, the results offer some suggestions. Liao and Huang (2009) argued that a cross-level analysis should be performed to comprehensively elucidate the complex hierarchical situations in an organization. This paper is among the few to adopt HLM to effectively evaluate the cross-level relationships of SBs. We endeavored to determine the value of SBs from a multilevel perspective. A cross-level analysis is a robust and essential research approach for comprehensively examining how EL influences SBs through complete mediation. Medical safety has gained increasing awareness in recent years. Care is no longer a unidirectional service based on medical paternalism. James (2013) highlighted the importance of medical safety through data analysis and argued that enhancing safety performance is vital in organizations, such as hospitals, that demand a high level of trust. In an organization, employees are the point of contact with patients and key service providers. Organizations rely on leaders, the organizational environment, and policies to educate and change employees’ personal SBs and maximize the safety and comfort of the care provided to patients. In view of the above research results, this study proposes the following practical implications for future reference. First, this study argues that the medical industry should actively train first-line supervisors to follow the EL management style through appropriate training courses and coaching methods. Second, this paper shows that a favorable SC must be established to improve SB. These objectives can be achieved through the periodical organization of safety courses and

announcements of the latest safety rules and regulations. Organizations should endeavor to establish a punishment-free reporting culture, enhance employees’ psychological SC, raise employees’ confidence about expressing their views in the workplace, encourage employees to discuss mistakes, and create an organizational environment in which employees enjoy sharing safety knowledge, thereby enhancing their safety participation and safety compliance willingness, improving their SB, and creating a mutually beneficial situation for employees and patients. Finally, hospitals should implement SOPs to help employees acquire knowledge rapidly in the workplace. We suggest the establishment of a knowledge exchange platform (e.g., knowledge management system, benchmark learning, or experience retention) to aid the compilation of a comprehensive database. This database would facilitate employees’ acquisition of knowledge and help units to communicate with one another. In the medical industry, organizations should create environments that encourage KS and establish information systems that integrate explicit and implicit knowledge. Alternatively, they could promote verbal dissemination of knowledge and experience to aid the communication and application of information. However, like any other study this paper has some limitations. Only three hospitals were surveyed. Therefore, the sample size was relatively small. We suggest that future researchers with sufficient resources expand the survey scope. In addition, the survey participants served in different departments, and the research outcomes were calculated using the average evaluation score of each department. Thus, the outcomes for specific departments may be of limited value; future researchers with sufficient resources could independently measure different professions (e.g., doctors and nurses) and compare the results. Second, the questionnaire adopted in this paper was designed using measurement tools developed by renowned international scholars. Although we endeavored to translate the English items faithfully and clearly into Chinese, we still ran the risk of the respondents misinterpreting them. Moreover, discrepancies between domestic and international practices may have rendered certain items inappropriate for the Taiwanese context. We suggest that future researchers incorporate open, qualitative items into their surveys, or adopt hybrid research methods, to reduce the occurrence of this problem. Third, we adopted a cross-sectional research design. The data we collected centered on the current work conditions of employees. However, employees’ perceptions may change over time. Future researchers could adopt a longitudinal research design and collect longterm data in various departments to compare changes in the effects of EL on SB over time. These outcomes could be used to determine the importance of EL and to validate its relationship with SB, thereby reducing errors stemming from common method variance. Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ssci.2019.03.022. References Amponsah-Tawaih, K., Adu, M.A., 2016. Work pressure and safety behaviors among health workers in Ghana: the moderating role of management commitment to safety. Saf. Health Work 7 (4), 340–346. Armstrong, G.E., Dietrich, M., Norman, L., Barnsteiner, J., Mion, L., 2017. Development and psychometric analysis of a nurses’ attitudes and skills safety scale: initial results. J. Nurs. Care Qual. 32 (2), E3–E10. Arnold, J.A., Arad, S., Rhoades, J.A., Drasgow, F., 2000. The empowering leadership questionnaire: the construction and validation of a new scale for measuring leader behaviors. J. Org. Behav. 21, 249–269. Bahadori, M., Teymourzadeh, E., Ravangard, R., Saadati, M., 2018. Accreditation effects on health service quality: nurse viewpoints. Int. J. Health Care Qual. Assurance 31 (7), 697–703. Bandura, A., 1977. Social Learning Theory. General Learning Press. Barling, J., Loughlin, C., Kelloway, E.K., 2002. Development and test of a model linking safety-specific transformational leadership and occupational safety. J. Appl. Psychol. 87, 488–496.

7

Safety Science 117 (2019) 1–9

Y.-H. Lee, et al.

Kelloway, E.K., Mullen, J., Francis, L., 2006. Divergent effects of transformational and passive leadership on employee safety. J. Occup. Health Psychol. 11 (1), 76–86. Kenny, D.A., Kashy, D.A., Bolger, N., 1998. Data analysis in social psychology. In: Gilbert, D., Fiske, S.T., Lindzey, G. (Eds.), The handbook of social psychology, 4th ed. McGraw-Hill, New York, pp. 223–265. Kohn, L.T., Corrigan, J.M., Donaldson, M.S., 2000. To Err is Human: Building a Safer Health System. Institute of Medicine Report. National Academy Press, Washington, DC. Lee, J.N., 2001. The impact of knowledge sharing, organizational capability and partnership quality on IS outsourcing success. Inf. Manage. 38, 323–335. Lee, Y.C., Weng, S.J., Huang, C.H., 2017. A longitudinal study of identifying critical factors of patient safety culture in Taiwan. J Test Eval. 45 (3), 1029–1044. Liao, L.W., Huang, T.C., 2009. The relationship between the HPWS and the performance of the human resource professionals: an examination of cross-level mediating effects of organizational innovation. J. Human Resource Manage. 19 (4), 17–41. Locke, A.E., Alavi, M., Wagner, J., 1997. Participation in decision making: an information exchange perspective. In: Ferris, G.R. (Ed.), Research in Personnel and Human Resource Management, 15. JAI Press, Greenwich, Connecticut, pp. 293–331. Lyu, S., Hon, C.K., Chan, A.P., Wong, F.K., Javed, A.A., 2018. Relationships among safety climate, safety behavior, and safety outcomes for ethnic minority construction workers. Int. J. Environ. Res. Public Health 15 (3), 484. Makary, M.A., Daniel, M., 2016. Medical error—the third leading cause of death in the US. BMJ 353, i2139. Martínez-Córcoles, M., Gracia, F.J., Tomás, I., Peiró, J.M., Schöbel, M., 2013. Empowering team leadership and safety performance in nuclear power plants: a multilevel approach. Saf. Sci. 51 (1), 293–301. Martínez-Córcoles, M., Gracia, F., Tomás, I., Peiró, J.M., 2011. Leadership and employees’ safety behaviors in a nuclear power plant: a structural equation model. Saf. Sci. 49, 1118–1129. Martínez-Córcoles, M., Schöbel, M., Gracia, F.J., Tomás, I., Peiró, J.M., 2012. Linking empowering leadership to safety participation in nuclear power plants: a structural equation model. J. Saf. Res. 43, 215–221. Manapragada, A., Bruk-Lee, V., Thompson, A.H., Heron, L.M., 2018. When Safety Climate is not Enough: Examining the Moderating Effects of Psychosocial Hazards on Nurse Safety Performance. J. Adv. Nurs. https://doi.org/10.1111/jan.13911. McFadden, K.L., Henagan, S.C., Gowen III, C.R., 2009. The patient safety chain: transformational leadership’s effect on patient safety culture, initiatives, and outcomes. J. Oper. Manage. 27, 390–404. Mearns, K., Flin, R., Fleming, M., Gordon, R., 1997. Human and Organisational Factors in Offshore Safety. HSE Books, Suffolk. Mearns, K., Whitaker, S., Flin, R., Gordon, R., O’Connor, P., 2000. Factoring the human into safety: translating research into practice. Benchmarking Human and Organisational Factors in Offshore Safety Vol. 1. Mearns, K., Whitaker, S., Flin, R., 2003. Safety climate, safety management practice and safety performance in offshore environments. Saf. Sci. 41, 641–680. Meurier, C.E., Vincent, C.A., Parmer, D.G., 1997. Learning from errors in nursing practice. J. Adv. Nurs. 26, 111–119. Mullen, J.E., Kelloway, E.K., 2009. Safety leadership: a longitudinal study of the effects of transformational leadership on safety outcomes. J. Occup. Org. Psychol. 82, 253–272. Naevestad, T.O., 2008. Safety cultural preconditions for organizational learning in highrisk organizations. J. Contingencies Crisis Manage. 16 (3), 154–163. Najjar, S., Nafouri, N., Vanhaecht, K., Euwema, M., 2015. The relationship between patient safety culture and adverse events: a study in Palestinian hospitals. Saf. Health 1, 16. National Patient Safety Agency, ‘Seven Steps to Patient Safety’, 2004–2009. Available at http://www.nrls.npsa.nhs.uk/resources/collections/seven-steps-to-patient-safety/. Neal, A., Griffin, M.A., Hart, P.M., 2000. The impact of organizational climate on safety climate and individual behavior. Saf. Sci. 34, 99–109. Neal, A., Griffin, M.A., 2006. A study of the lagged relationships among safety climate, safety motivation, safety behavior, and accidents at the individual and groups levels. J. Appl. Psychol. 91 (4), 946–953. Nemanich, L.A., Keller, R.T., Vera, D., Chin, W.W., 2010. Absorptive capacity in R&D project teams: a conceptualization and empirical test. IEEE Trans. Eng. Manage. 57 (4), 674–688. O’Brien, B., Andrews, T., Savage, E., 2018. Anticipatory vigilance: a grounded theory study of minimizing risk within the perioperative setting. J Clin Nurs. 27 (1–2), 247–256. Podsakoff, P.M., Organ, D.W., 1986. Self-reports in organizational research: Problems and prospects. J. Manage. 12, 69–82. Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y., Podsakoff, N.P., 2003. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol. 88, 879–903. Raudenbush, S.W., Bryk, A.S., 2002. Hierarchical Linear Models: Applications and Data Analysis Methods, second edition. Sage, Newbury Park, CA. Robertson, P.L., Casali, G.L., Jacobson, D., 2012. Managing open incremental process innovation: absorptive capacity and distributed learning. Res. Policy 41 (5), 822–832. Scarbrough, H., 2003. Knowledge management, HRM and innovation process. Int. J. Manpower 24, 501–516. Sexton, J.B., Helmreich, R.L., Neilands, T.B., Rowan, K., Vella, K., Boyden, J., Roberts, P.R., Thomas, E.J., 2006. The safety attitudes questionnaire psychometric properties benchmarking data and emerging research. BMC Health Serv. Res. 6, 44. Shalley, C.E., Gilson, L.L., Blum, T.C., 2000. Matching creativity requirements and the work environment: effects on satisfaction and intentions to leave. Acad. Manag. J. 43, 215–223. Shannon, H., Norman, G., 2009. Deriving the factor structure of safety climate scales. Saf. Sci. 47, 327–329.

Baron, R.M., Kenny, D.A., 1986. Moderator-mediator variables distinction in social psychological research: conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 51 (6), 1173–1182. Bass, B.M., 1985. Leadership and Performance Beyond Expectations. The Free Press, New York. Bass, B.M., 1990. Bass & Stogdill’s Handbook of Leadership, third ed. The Free Press, New York. Blair, E., 2003. Culture and leadership: seven key points for improved safety performance. Professional Safety 48 (6), 18–22. Bowen, D.E., Lawler, E.E., 1992. The empowerment of service works: What, why, how, and when. Sloan Manage Rev. 33 (3), 31–39. Braisaite, I., Kaunonen, M., Suominen, T., 2015. Healthcare professionals’ knowledge, attitudes and skills regarding patient safety: a systematic literature review. Scand. J. Caring Sci. 29 (1), 30–50. Cabrera, Á., Collins, W.C., Salgado, J.F., 2006. Determinants of individual engagement in knowledge sharing. Int. J. Human Resour. Manage. 17 (2), 245–264. Canadian Patient Safety Institute, 2017. Engaging patients in patient safety. Available at: https://www.patientsafetyinstitute.ca/en/toolsResources/Patient-Engagement-inPatient-Safety-Guide/Documents/Engaging%20patients%20as%20partners.pdf. Chang, H.H., Chuang, S.S., 2011. Social capital and individual motivations on knowledge sharing: participant involvement as a moderator. Inf. Manage. 48 (1), 9–18. Cho, S.M., Choi, J., 2018. Patient safety culture associated with patient safety competencies among registered nurses. J. Nurs. Scholarsh. 50 (5), 549–557. Christian, M.S., Bradley, J.C., Wallace, J.C., Burke, M.J., 2009. Workplace safety: a metaanalysis of the roles of person and situation factors. J. Appl. Psychol. 94 (5), 1103–1127. Clarke, S., Ward, K., 2006. The role of leader influence tactics and safety climate in engaging employees' safety participation. Risk Anal. 26 (5), 1175–1185. Clarke, S., 2006. The relationship between safety climate and safety performance: a metaanalytic review. J. Occup. Health Psychol. 11 (4), 315–327. Clarke, S., 2013. Safety leadership: a meta-analytic review of transformational and transactional leadership styles as antecedents of safety behaviors. J. Occup. Org. Psychol. 86, 22–49. Colet, P.C., Cruz, J.P., Cacho, G., Al-Qubeilat, H., Soriano, S.S., Cruz, C.P., 2018. Perceived infection prevention climate and its predictors among nurses in Saudi Arabia. J. Nurs. Scholarsh. 50, 134–142. Dansereau, F., Graen, G.B., Haga, W.J., 1975. A vertical dyad linkage approach to leadership within formal organizations. Org. Behavior Human Perform. 13, 46–78. DiCuccio, M.H., 2015. The relationship between patient safety culture and patient outcomes: a systematic review. J. Patient Saf. 11 (3), 135–142. Edmondson, A.C., 2004. Learning from failure in health care: frequent opportunities, pervasive barriers. Qual. Saf. Health Car. 13, 3–9. Edmondson, A.C., 2002. The local and variegated nature of learning in organizations: a group-level perspective. Organ. Sci. 13 (2), 128–146. Feng, J., Chang, Y.C., 2018. Relationship between perception of patient safety climate, work pressure and safety behavior. Cheng Ching Med. J., Chang Gung Nursing 29 (2), 190–198. Fernandez-Muniz, B., Montes-Peon, J.M., Vazquez-Ordas, C.J., 2007. Safety culture: analysis of the causal relationships between its key dimensions. J. Saf. Res. 38, 627–641. Firth-Cozens, J., 2001. Cultures for improving patient safety through learning: the role of teamwork. Qual. Health Care 10, ii26–ii31. Fischer, S., Jones, J., Verran, J., 2018. Consensus achievement of leadership, organizational and individual factors that influence safety climate: implications for nursing management. J. Nurs. Manage. 26 (1), 50–58. Flin, R., Yule, S., 2004. Leadership for safety: industrial experience. Qual. Saf. Health Care 13 (Suppl. II), 45–51. Fornell, C., Larcker, D.F., 1981. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18 (1), 39–50. Graen, G.B., Cashman, J.F., 1975. A role making model in formal organizations: a developmental approach. In: Hunt, J.G., Larson, L.L. (Eds.), Leadership Frontiers. Kent State University Press, Kent, OH, pp. 143–165. Hackman, J.R., Wageman, R., 2005. A theory of team coaching. Acad. Manag. Rev. 30 (2), 269–287. Hair, J., Black, B., Babin, B., Anderson, R., Tatham, R., 2006. Multivariate Data Analysis, sixth ed. Prentice-Hall, Upper Saddle River, NJ. Hair Jr., R., Anderson, R.E., Tatham, R.L., Black, W.C., 1998. Multivariate Data Analysis, fifth ed. Macmillan, New York. Hoffmeister, K., Gibbons, A.M., Johnson, S.K., Cigularov, K.P., Chen, P.Y., Rosecrance, J.C., 2014. The differential effects of transformational leadership facets on employee safety. Saf. Sci. 62, 68–78. Hofmann, D.A., Stetzer, A., 1996. A cross-level investigation of factors influencing unsafe behaviours and accidents. Pers. Psychol. 49, 307–339. House, R.J., Dessler, G., 1974. The path goal theory of leadership: some post hoc and priori tests. In: Hunt, J.G., Larson, L. (Eds.), Contingency Approaches to Leadership. Southern Illinois University Press, Carbondale, pp. 46–48. James, J.T., 2013. A new, evidence-based estimate of patient harms associated with hospital care. J. Patient Saf. 9 (3), 122–128. Jangland, E., Gunningberg, L., 2017. Improving patient participation in a challenging context: a 2-year evaluation study of an implementation project. J. Nurs. Manag. 25 (4), 266–275. Katsva, M., Condrey, S.E., 2005. Motivating personnel at Russian nuclear power plants: a case-study of motivation theory application. Public Personnel Manage. 34 (4), 343–356. Katz-Navon, T., Naveh, E., Stern, Z., 2005. Safety climate in health care organizations: a multidimensional approach. Acad. Manage. J. 48 (6), 1075–1089.

8

Safety Science 117 (2019) 1–9

Y.-H. Lee, et al.

who.int/features/factfiles/patient_safety/en/. Xue, Y.J.B., Liang, H., 2011. Team climate, empowering leadership, and knowledge sharing. J. Knowledge Manage. 15 (2), 299–312. Yang, C.C., Wang, Y.S., Chang, S.T., Guo, S.E., Huang, M.F., 2009. A study on the leadership behavior, safety culture, and safety performance of the healthcare industry. World Acad. Sci., Eng. Technol. 53, 1148–1155. Yule, S., Flin, R., Murdy, A., 2007. The role of management and safety climate in preventing risk-taking at work. Int. J. Risk Assess. Manage. 7 (2), 127–151. Zhang, X., Bartol, K.M., 2010. Linking empowering leadership and employee creativity: the influence of psychological empowerment, intrinsic motivation, and creative process engagement. Acad. Manage. J. 53, 107–128. Zhou, J., George, J., 2001. When job dissatisfaction leads to creativity: encouraging the expression of voice. Acad. Manag. J. 44, 682–696. Zohar, D., 1980. Safety climate in industrial organizations: theoretical and applied implications. J. Appl. Psychol. 65 (1), 96–102. Zohar, D., 2000. A group-level model of safety climate: testing the effect of group climate on microaccidents in manufacturing jobs. J. Appl. Psychol. 85 (4), 587–596. Zohar, D., 2002. The effects of leadership dimensions, safety climate, and assigned priorities on minor injuries in work groups. J. Org. Behavior 23, 75–92. Zohar, D., 2008. Safety climate and beyond: a multi-level multi-climate framework. Saf. Sci. 46, 376–387. Zohar, D., Luria, G., 2005. A multilevel model of safety climate: cross-level relationships between organization and group-level climates. J. Appl. Psychol. 90 (4), 616–628.

Shen, Y., Ju, C., Koh, T.Y., Rowlinson, S., Bridge, A.J., 2017. The impact of transformational leadership on safety climate and individual safety behavior on construction sites. Int. J. Environ. Res. Public Health 14 (1), 45. Smith, G., Huang, Y., Ho, M., Chen, P., 2006. The relationships between safety climate and injury rates across industries: the need to adjust for injury hazards. Accid. Anal. Prev. 38, 556–562. Sobel, M.E., 1982. Asymptotic confidence intervals for indirect effects in structural equation models. Sociol. Methodol. 13, 290–312. Srivastava, A., Bartol, K.M., Locke, E.A., 2006. Empowering leadership in management teams: effects on knowledge sharing, efficacy, and performance. Acad. Manag. J. 49 (6), 1239–1251. Thornton, K., Schwarz, J., Kendall Gross, A., Anderson, W., Liu, K., Romig, M., for the Project Emerge Collaborators, 2017. Preventing harm in the ICU – building a culture of safety and engaging patients and families. Crit. Care Med. 45, 1531–1537. Wallin, A., Gustafsson, M., Anderzen Carlsson, A., Lundén, M., 2018. Radiographers’ experience of risks for patient safety incidents in the radiology department. J. Clin. Nurs. https://doi.org/10.1111/jocn.14681. Wang, D., Wang, X., Xia, N., 2018. How safety-related stress affects workers’ safety behavior: the moderating role of psychological capital. Saf. Sci. 103, 247–259. Wang, X., Liu, K., You, L.M., Xiang, J.G., Hu, H.G., Zhang, L.F., Zhu, X.W., 2014. The relationship between patient safety culture and adverse events: a questionnaire survey. Int. J. Nurs. Stud. 51 (8), 1114–1122. World Health Organisation, 2018. Ten facts on patient safety. available at: http://www.

9