Background
Patient safety represents a serious global challenge in healthcare systems. The World Health Organization (WHO, 2021) reports that approximately 134 million patient safety incidents (PSIs) occur annually in low- and middle-income countries, causing 2.6 million deaths, while around 10% of hospitalized patients in high-income countries experience similar events. Adverse events (AEs) are the most frequent type of PSIs, accounting for 72.5% in South Africa (Singh & Mahomed, 2023) and 87.78% in Indonesia (Dhamanti et al., 2024). Commonly reported incidents include medication errors, patient falls, healthcare-associated infections (HAIs), procedural errors, and patient identification errors (WHO, 2021). The impacts of AEs include injury, prolonged hospitalization, increased complications, death, psychological stress on healthcare workers, and financial and reputational losses for hospitals (Lee & Cho, 2022; Almanhali et al., 2024; Kim & Kim, 2024). Globally, AEs also hinder the achievement of universal health coverage (UHC) and sustainable development goals (SDGs) (WHO, 2024).
Nurses play a central role in the patient safety practices, as they engage in direct and continuous interactions with patients across all areas of the international patient safety goals (IPSG), such as patient identification, effective communication, and fall prevention (Jeong & Jeong, 2022; Ramsay et al., 2025). Nurses' compliance with IPSG procedures is influenced by individual factors, such as motivation (M), knowledge, and fatigue, as well as organizational factors, including work environment (WE) support and safety culture (Bjerkan et al., 2021; Cho & Steege, 2021; Janes et al., 2021; Wang et al., 2024). Therefore, organizations need to ensure synergy between nurses’ internal and external factors to strengthen compliance with patient safety practices (Astarini & Lilyana, 2021; Kim et al., 2022).
Professional competence (PC), as one of the internal factors identified in numerous previous studies, has a significant relationship with the quality of care and patient safety (Halabi et al., 2021; Zaitoun et al., 2023). This competence is developed through formal education, training, and continuous clinical experience, as emphasized in Benner’s from novice to expert theory (Zaitoun, 2024). Organizational support for both formal and informal learning is essential to strengthen nurses' competencies in applying patient safety principles (Kim, 2020; Taji et al., 2023; Hamid et al, 2024).
Organizational factors, including the nursing WE, has also been widely identified in previous studies as an external factor influencing patient safety. A positive WE that fosters collaboration, team communication, and professional autonomy has been shown to have a direct effect on nurses' compliance with patient safety practices (Cho & Steege, 2021; Hennus et al., 2021; Kim & Kim, 2024). A healthy WE enhances job satisfaction and work engagement, whereas high workloads and lack of organizational support can trigger burnout and reduce safety M (El-Gazar et al., 2022; Arsani et al., 2023; Fan et al., 2024).
M has been widely recognized as a mediating factor linking both internal and external factors of individuals and the implementation of patient safety practices, given its role as a key mechanism in enhancing nurses' awareness (Subramaniam et al., 2023). Structural model analyses have shown that safety climate (Seo & Lee, 2022) and leadership (Subramaniam et al., 2023) indirectly influence patient safety compliance through the mediation of M and knowledge. However, research by Yoon and Lee (2022) on military nurses found that only knowledge mediated this relationship, indicating that the mediating role of M remains inconsistent, although M has been consistently shown to be directly associated with compliance with patient safety goals (Alhidayah et al., 2020; Kim & Jang, 2024; Manalu et al., 2024). 
This inconsistency regarding the mediating role suggests the possibility of contextual differences or the presence of other determinants influencing the relationship among the variables. According to the job demands-resources (JD-R) theory, PC and the WE act as resources that do not directly enhance performance but are instead mediated by M (Bakker et al., 2023). Similarly, self-determination theory (SDT) explains that autonomy, relatedness, and competence shaped by the WE contribute to nurses' M (Padauleng et al., 2020; Koivisto et al., 2021). Based on these perspectives, further research is needed to integrate both individual-level factors (PC) and organizational-level factors (WE) simultaneously, while considering nurses' M as a mediator. Therefore, this study aimed to analyze the relationship between PC and the WE on patient safety management activities (PSMAs), with nurses’ M serving as a mediating variable.

Materials and Methods
Design, setting, and sample
This study employed a quantitative correlational design with a cross-sectional approach. The research was conducted across three hospitals in Malang Raya, East Java. The study population consisted of all staff nurses working in inpatient units. The sample size was determined using Slovin’s formula, yielding a minimum of 195 nurses from a population of 381, which was adjusted by 10% to anticipate non-responses, resulting in a minimum target sample size of 215. Proportional quota sampling was used to select participants based on hospital representation. Data collection resulted in 225 valid completed questionnaires, which were included in the analysis. 

Research instrument
Demographic characteristics
A demographic questionnaire was used to obtain information on nurses’ characteristics, including age, gender, education level, years of experience, and clinical career level. 

Professional competence 
Professional competence (PC), serving as the independent variable, was measured using the short version of the nurse PC (NPC) scale by Nilsson et al. (2018), which was validated in an Arabic version by Grande et al. (2023). This instrument consists of 21 items encompassing three dimensions: direct nursing care, holistic value-based care, and professional care pedagogics. Each item is rated on a 4- point Likert scale (1=very low to 4=very high), with total scores ranging from 21–84, where higher scores indicate a higher level of PC. The original study reported a Cronbach’s α=0.981, while in this study, the instrument was culturally adapted into Indonesian, and all items were found to be valid, with Pearson’s correlation coefficients (r=0.601–0.848) and a Cronbach’s α of 0.966.

Work environment
The nursing work environment (WE), as an independent variable, was measured using the short form of the practice environment scale of the nursing work index (PES-NWI), the PES-5, which was developed by Lake et al. (2024). This instrument consists of 28 items covering five subscales: staffing and resource adequacy, collegial nurse–physician relationships, nurse manager ability, leadership, and support, nursing foundations for quality of care, and nurse participation in hospital affairs. Each item is rated on a 4-point Likert scale (1=strongly disagree to 4=strongly agree). Total scores range from 28 to 112, with higher scores indicating a more positive perception of the WE. The original study reported a Cronbach’s α of 0.81, whereas in this study, the instrument was culturally adapted into Indonesian, yielding Pearson’s correlation coefficients (r=0.41–0.869) and a Cronbach’s α of 0.951. 

Motivation
Motivation (M), as a mediating variable, was measured using the safety M tool by Vinodkumar and Bhasi (2010), which was adapted into five positive statements relevant to patient safety by Subramaniam et al. (2023) sto represent the individual responsibility dimension. Responses were rated on 4-point Likert scale (1=strongly disagree to 4=strongly agree), with total scores ranging from 5 to 20; higher scores indicate higher levels of safety M. The original version reported a Cronbach’s α of 0.72, whereas in this study, the instrument was culturally adapted into Indonesian, yielding Pearson’s correlation coefficients (r=0.826–0.909) and a Cronbach’s α of 0.921. 

Patient safety management activities
Patient safety management activities (PSMAs) were measured using the safety care activity scale developed by (Yang, 2021). The original instrument consisted of 44 items across eight dimensions, but it was adapted for the context of this study to include 27 items representing five main dimensions: patient identification, medication, infection management, fall management, and data security. Responses were rated on a 4-point Likert scale (1=strongly disagree to 4=strongly agree). 
The original version reported Cronbach’s α values ranging from 0.88 to 0.95. In this study, the instrument was culturally adapted into Indonesian. One item (r<0.361) was considered invalid and removed due to thematic redundancy, resulting in 26 valid items. After removal, validity testing showed r=0.656–0.936, and the Cronbach’s α was 0.985. The total questionnaire score after adjustment ranged from 26 to 104, with higher scores indicating better PSMAs. 

Data analysis
Data were analyzed using descriptive and inferential statistics. Descriptive analysis was employed to describe the characteristics of respondents and the distribution of each variable, presented as frequencies and percentages. Inferential analysis was conducted using structural equation modelling-partial least squares (SEM-PLS) with SmartPLS version 4.0 software to examine both direct and indirect relationships among variables, including the mediating effect of M. 
Model evaluation was performed through the assessment of the outer model (convergent and discriminant validity, as well as construct reliability) and the inner model (coefficient of determination/R², path coefficients, bootstrapping, and effect size). Statistical significance was determined using t≥1.96 and P≤0.05 (Hair et al., 2021) the model imposes some daunting assumptions and restrictions (e.g. normality and relatively large sample sizes. 

Results
Descriptive analysis
Table 1 shows that the majority of respondents in this study were female (80%), within the young adult age range (24 to 44 years old) (80%), and had more than 15 years of experience (33.8%).


Most respondents held a diploma in nursing (54.7%) and were at clinical career level III (36%).
Table 2 shows that the mean score for PC (95% CI, 65.42%, 67.27%) was categorized as high; the WE (95% CI, 82.69%, 84.85%) was categorized as moderate to good; M (95% CI, 17.09%, 17.68%) was categorized as high; and PSMAs (95% CI, 88.16%, 91.07%) were categorized as good.



Inferential analysis
Figure 1 shows the structural model of the study, including the path coefficients and R² values for M and PSMAs.

The model illustrates both direct and mediating effects among the study variables. 
Table 3 presents the results of the outer model analysis, indicating that all constructs met the criteria for convergent validity and reliability.


The average variance extracted (AVE) values for all constructs were above 0.50 (0.650-0.872), composite reliability (CR) values exceeded 0.70 (0.902-0.965), and Cronbach’s α values were greater than 0.70 (0.866-0.955). 
The results of the inner model analysis (Table 4) show that the R² value for the M variable is 0.235, indicating that PC and WE explained 23.5% of the variance in nurses’ M.


The R² value for patient safety implementation was 0.697, suggesting that M, PC, and WE collectively explained 69.7% of the variance in PSMAs. The Q² predictive relevance value was 0.769 (>0.35), indicating that the research model had a high predictive ability for endogenous variables (Hair et al., 2021) the model imposes some daunting assumptions and restrictions (e.g. normality and relatively large sample sizes. 
Table 5 indicates that all direct effects between variables were statistically significant (P<0.05).


PC had a positive and significant effect on M (β=0.354, t=4.342, P<0.001) and PSMAs (β=0.082, t=1.732, P=0.042). The WE also had a positive and significant effect on M (β=0.177, t=2.56, P=0.005) and on PSMAs (β=0.119, t=2.953, P=0.002). Furthermore, M showed the strongest positive effect on PSMAs (β=0.734, t=16.728, P<0.001). 
For the indirect effects, both PC and WE significantly influenced PSMAs through M, with path coefficients of β=0.260 (t=4.381, P<0.001) and β=0.13 (t=2.477, P=0.007), respectively. These findings indicate that M serves as a mediating variable in the relationship between the two independent variables and PSMAs. 
Table 6 shows that the indirect paths between PC and WE on PSMAs through M were significant (P<0.05), while the direct paths also remained significant.


These findings indicate that M partially mediates the effects of PC and WE on PSMAs.

Discussion
This study demonstrated that PC and WE significantly influence nurses’ M and PSMAs, both directly and indirectly through M. Among these relationships, M showed the strongest direct effect on PSMAs. M was positively related to patient safety practices, which is consistent with the results of Saleh et al. (2022) and Subramaniam et al. (2023). High M encourages nurses to adhere more closely to procedures and to be more proactive in ensuring patient safety. Safety M reflects an internal commitment to safe practices (Alhidayah et al., 2020; Kim & Jang, 2024), aligning with SDT, which emphasizes that autonomous M strengthens professional responsibility in the workplace. However, Yoon and Lee (2022) found no significant association between M and PSIs reporting, likely due to the hierarchical structure of the military healthcare. In contrast, the current study suggests that M operates as an internalized individual commitment rather than an external obligation. 
The SDT also explains the findings that PC and WE has a positive and significant relationship with the M. According to SDT (Ryan & Deci, 2020), the fulfilment of basic psychological needs (competence, autonomy, and relatedness) forms the foundation of intrinsic M. High levels of competence can enhance self-confidence, autonomy, and professional engagement, thereby strengthening intrinsic M in nursing practice (Ahlstedt et al., 2020). In addition, a supportive nursing WE enhances psychological empowerment and reduce stress (Saleh et al., 2022), thereby fulfilling the basic psychological needs outlined in SDT (Ryan & Deci, 2020). Therefore, strengthening PC and creating a supportive WE should be prioritized as strategic interventions to foster nurses’ M. 
The findings further revealed that PC and WE not only foster nurses’ M but also contribute to their engagement in PSMAs. Integrating clinical competence, humanistic values, and educational functions as components of PC enhances nurses’ awareness of and compliance with patient safety (Park et al., 2024), while competence in appropriate assessment, intervention, and evaluation supports the delivery of high-quality care (Halabi et al., 2021; Kukkonen et al., 2025). The finding also reinforces the evidence that the WE serves as a fundamental foundation for shaping nurses’ safety behaviors within healthcare facilities. Adequate staffing and organizational support, as components of WE, have been shown to reduce burnout and enhance compliance with safety practices (Putra et al., 2021; El-Sayed et al., 2024). Therefore, nurses should actively participate in regular competence development, while healthcare organizations need to provide adequate learning support and facilities related to patient safety. 
Furthermore, the mediating role of M between PC and the WE highlights that nurses’ internal drive serves as a key mechanism transforming individual and organizational resources into safe clinical practices. Within the framework of JD-R Theory (Bakker et al., 2023), PC functions as an individual resource that enhances M and work engagement (Jakobsson et al., 2023; Yamada et al., 2023). Within the JD-R framework, the WE functions as an organizational resource that supports autonomy, open communication, and supportive leadership, all of which strengthen nurses’ M to engage in safety practices (Seo and Lee, 2022; Subramaniam et al., 2023) safety compliance and safety participation. A positive WE enhances intrinsic M and helps balance job-related stress (Jakobsson et al., 2023; Wang et al., 2024). This is also consistent with SDT, which emphasizes that autonomy support and social relatedness foster autonomous M (Ryan & Deci, 2020). However, the application of JD-R theory may not always fully align with certain nursing contexts, such as intensive care units (ICUs), where the influence of individual resources, such as clinical expertise, self-efficacy, and resilience on M and performance has been found to be insignificant (Oetelaar et al., 2021; Gou et al., 2024). Therefore, PC, as a form of personal resource, may represent a more relevant factor in enhancing M and performance within the context of general inpatient care, where job demands are not as high as in ICUs. 
The study has several limitations that should be acknowledged. The analysis did not include comparisons across hospitals, which may limit the understanding of how organizational characteristics influence practices. Future research should include comparative analyses across different hospital types to explore contextual variations in resource availability. In addition, studies could extend this model by integrating job demands as a variable to better capture the influence of highly demanding WEs. 

Conclusion
This study highlights that M serves as a key psychological mechanism linking individual resources and job resources to nurses’ performance in maintaining patient safety. The integration of JD-R theory and SDT provides a comprehensive explanation of how PC and WE address nurses’ basic psychological needs and foster intrinsic M. Therefore, strengthening PC through continuous learning—such as coaching, mentoring, critical reflection, and career development programs—along with fostering a supportive WE, should be prioritized to maintain nurses’ M and PSMAs. Future research is recommended to examine this model by comparing different hospital contexts and incorporating job demands to better capture the influence of highly demanding WEs across various healthcare settings. 

Ethical Considerations
Compliance with ethical guidelines
This study received ethical approval from three institutional ethics committees: (1) the Health Research Ethics Committee, Faculty of Health Sciences, Universitas Brawijaya (Code: 184/UN10.F17.10.4/TU/2025); (2) the Ethics Committee of Radjiman Wediodiningrat Hospital (Code: TK.02.04/D.XXXXVII.3.6/11252/2025); and (3) the Ethics Committee of Kanjuruhan General Hospital (Code: 072.1/EA.KEPK-032/35.07.302.101/2025). All participants were provided with information about the study and gave written informed consent before participation.

Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Authors' contributions
Conceptualization and methodology: Clara Agustina and Kuswantoro Rusca Putra; Investigation and data curation: Clara Agustina; Formal analysis: Clara Agustina; data interpretation: Kuswantoro Rusca Putra and Fransiska Imavike Fevriasanty; Supervision: Kuswantoro Rusca Putra; Writing the original draft: Clara Agustina; Review and editing: Fransiska Imavike Fevriasanty; Final approval: All authors.

Conflict of interest
The authors declared no conflict of interest.

Acknowledgments
The authors would like to thank the Department of Nursing, Faculty of Health Sciences, Universitas Brawijaya, Malang, Indonesia, for the academic support provided during the preparation of this original research article. Special appreciation is also extended to colleagues who offered constructive feedback.


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