Abstract
Introduction
The healthcare industry needs healthcare professionals who are adaptive to change, proactive, energetic, creative, and persistent in the face of challenges. Consequently, the highest level of healthcare depends on the presence of competent, accessible, acceptable, and skilled healthcare professionals (World Health Organization [WHO], 2019). In this regard, nurses are pivotal in achieving significant advancements towards equity in healthcare, as they constitute the largest human resource in clinical settings (Murphy et al., 2022). Nevertheless, the nursing shortage remains a major concern of global healthcare systems for decades, reflecting an imbalance between the workforce demand and supply in the industry. This persistent problem stems from various reasons such as aging population, aging workforce, nurses’ burnout, and high turnover, that significantly compromise the effectiveness of clinical outcomes (Haddad, 2023; Murphy et al., 2022).
Apart from all the potential reasons for shortages in the nursing workforce, the Coronavirus disease 2019 (COVID-19) added more burden to the healthcare system on a global scale (Zhan et al., 2020). The profound impacts of COVID-19 on the professional, personal, and health aspects of healthcare workers have been emphasized in the healthcare literature (Arias-Ulloa et al., 2023; Morris, 2022; “COVID-19 s Impact on Nursing Shortages, the Rise of Travel Nurses, and Price Gouging,” 2022). Understaffing in healthcare was identified as a major cause of disruption to the provision of essential healthcare services during the pandemic (Murphy et al., 2022). Although understaffing is not a new trend in the nursing industry, the issue was aggravated by the global emergency and measures introduced to address the problem (Tony Yang & Mason, 2022). Healthcare professionals faced diverse challenges, ranging from prolonged working hours to care rationing, clinical uncertainty due to a lack of medical guidelines, and uncertain surroundings during the pandemic. These events had a significant impact on healthcare service delivery and function (Morris, 2022; Tony Yang & Mason, 2022).
Given the sub-optimal function of the healthcare system, nurses were faced with a higher average patient-to-nurse ratio, and many were assigned to work outside their specialties, thereby indirectly increasing their workload (Zhang et al., 2021). The increased level of perceived strain, excessive duties, and psychological distress among nursing personnel could significantly impact the quality of nursing care provided to patients (Søvold et al., 2021; Zhang et al., 2021). Continuous exposure to stressful events could lead to mental health issues, such as anxiety, depression, and burnout among healthcare professionals (Arias-Ulloa et al., 2023; Jalili et al., 2021; Sasangohar et al., 2020), which negatively impact health organizations. Therefore, these problems could be addressed by identifying the psychosocial risk factors for mental health issues and implementing preventive interventions.
Nonetheless, studies investigating the increased strain and stress experienced by frontline nurses during COVID-19 and other public emergencies are scarce, particularly behavioral social science research (Rosa et al., 2020). The global pandemic highlights the need to pay closer attention to frontline nurses’ work and well-being during public emergencies, as well as enhancing their preparedness beyond crisis for future sustainable healthcare (Armocida et al., 2020). Despite imposing unprecedented challenges to public health and the healthcare system, the pandemic has exposed and amplified vulnerabilities of healthcare delivery systems. In terms of nursing, the pandemic has indeed overstated the significant inherent systemic weaknesses from resource management to nursing welfare and accentuated the crucial need for a reassessment of nursing care integration into the broader health system (Romero-López-Alberca et al., 2021). Therefore, given the critical role of nurses in delivering quality care, it is essential to prioritize their well-being, as it directly impacts their physical and mental health, ultimately ensuring the sustainability of nursing talents.
In this regard, a growing body of literature has recognized nursing engagement as the most crucial element in retaining the nursing workforce while securing their health and well-being (Bailey & Cardin, 2018; Tomietto et al., 2019). Nursing engagement is a positive, fulfilling, and motivational state of work-related well-being (Bakker & Demerouti, 2012). It is a state of job satisfaction that is marked by enthusiasm, commitment, and immersion in nurses’ professional roles. Engaged employees frequently develop a deep sense of connection with their work and they are more likely to experience a sense of purpose and connection to their work (Garcia-Sierra et al., 2016; Pandita & Ray, 2018). This higher sense of fulfillment and purpose often leads to greater job satisfaction, making employees more likely to remain with their organization (Pandita & Ray, 2018). Therefore, healthcare providers could overcome health workforce scarcity and strengthen the delivery of quality care by enhancing work engagement among nurses.
Previous nursing literature has demonstrated the important role of nursing engagement in improving healthcare quality, preventing complications, and decreasing medical errors (Carthon et al., 2019; Kutney-Lee et al., 2016). Nevertheless, engagement studies are perceived to be less explored in nursing despite being widely investigated in the management and psychology fields (Keyko, 2014). Nursing engagement research within the Malaysian context is also still in its budding stage (Othman & Nasurdin, 2019). Meanwhile, from a theoretical viewpoint, engagement scholars have recently broadened their interest in studying employees’ positive dimensions, enhancing subjective well-being and work engagement, rather than focusing exclusively on the negative dimensions (Sun et al., 2022; Ugwu & Onyishi, 2020). This expansion demonstrates a growing orientation towards a positive psychology approach that emphasizes optimal individual functioning and strength to foster workforce well-being (Dubord & Forest, 2022). Notably, several recent studies have focused on subjective well-being, including employee engagement (Sun et al., 2022; Ugwu & Onyishi, 2020), work satisfaction (Ayalew et al., 2019; Kagan et al., 2021), and happiness at work (Chang et al., 2020; Javanmardnejad et al., 2021).
The expansion of empirical research indicates that there are evolving paradigm shifts in the scientific field toward positive psychology. Perfectionism and resilience are two key constructs in positive psychology that may shape individuals’ coping styles during stressful circumstances, including their long-term performance (Huang et al., 2022). Perfectionism is a multifaceted personality trait, characterized by a tendency to pursue perfection in all aspects of life (Pishghadam & Akhondpoor, 2011). Perfectionism is considered a strong workplace stressor that could affect workers’ engagement levels (Madigan et al., 2016). Resilience, on the other hand, entails employees’ behavioral tendency to adapt to workplace demands and recover from stressful conditions. Resilient workers are more likely to adapt to adverse events by mobilizing protective resources and harnessing social support (Klika & Herrenkohl, 2013). However, the effects of perfectionism on work engagement and the role of resilience in ameliorating this workplace stressor remain understudied in the nursing context.
Taken together, this study is underpinned by the Job Demand–Resource (JD-R) model, which suggests that the degree of motivation (well-being) and strain (burnout) are predicted by resources and demand in the workplace (Bakker & Leiter, 2010; Schaufeli & Bakker, 2004). The JD-R model also posits that an imbalance between workplace demands and resources induces two different types of processes: a health impairment process (leads to burnout) due to a high level of demands or a motivational process (leads to work engagement) due to the vast availability of resources (Demerouti & Bakker, 2011; Demerouti et al., 2001). The present study focuses on the motivational process of the JD-R model of engagement, which suggests that existing resources in the workplace can strengthen the motivational mechanism, leading to enhanced work engagement (Bakker & Demerouti, 2007). To bridge the aforementioned research gaps, this study explores how nurses’ engagement is shaped by interventions tailored toward resources and demands in healthcare organizations. This article presents a standard protocol for the research, serving as a comprehensive guideline for researchers, clinicians, and other pertinent stakeholders involved in the study, thereby promoting transparency and accountability.
Research Objectives
This study aims to investigate the antecedents of nurses’ work engagement based on the research gap underpinned by the Job Demands-Resources (JD-R) model. To strengthen the well-being of public healthcare nurses, the following research objectives were formulated to determine the factors influencing nursing engagement:
i. To assess the impact of stressors (work overload and perfectionism) on nursing engagement.
ii. To assess the mediating effect of resilience and the mitigating effect of social support between work stressors and nursing engagement.
iii. To integrate the understudied concept of personal demand into the JD-R model from a positive psychological perspective.
Theoretical Framework and Hypotheses Development
This study is underpinned by the JD-R model – a widely used model globally in various working populations. The model posits that employees’ well-being is shaped by two driving forces: job demands and job resources (Demerouti & Bakker, 2011). Accordingly, job demands encompass organizational features that necessitate psychological (emotional and cognitive) and physical efforts, which may result in negative health outcomes, such as job burnout (Demerouti & Bakker, 2011). On the other hand, job resources entail aspects of the work environment that influence personal growth and development. These resources assist employees in achieving their work goals, thereby enhancing health outcomes and increasing motivation (Bakker & Leiter, 2010). The JD-R model thus proposes dual pathways, linking high levels of job demands to strain, and linking job resources to motivational outcomes such as work engagement (Figure 1). In other words, the degree of motivation (well-being) and strain (burnout) are predicted by workplace resources and demands (Bakker & Leiter, 2010; Schaufeli & Bakker, 2004).
Job demands-resources model, adapted from Bakker and Demerouti (2007).
The JD-R has been applied in several empirical studies in the nursing field, as summarized in the reviews by McVicar (2016) and Keyko et al. (2016). These researchers utilized the JD-R model to elucidate the association between job stress and job satisfaction. Resultantly, work pressure and emotional demands were identified as the most consistent job demand-related events affecting job stress and job satisfaction (McVicar, 2016). Meanwhile, interpersonal and social relations, decision latitude, management and supervision, and task significance were the most common domains under job resources influencing job stress and satisfaction.
A systematic review by Keyko et al. (2016) revealed that nurses’ work engagement was shaped by multiple factors that can be grouped into six broad categories: job resources, organizational climate, personal resources, job demands, professional resources, and demographic factors. The researchers highlighted the importance of organizational aspects as a “precursor to operational resources,” and a significant predictor of work engagement in professional nursing practice. Specifically, the organizational aspect comprises leadership and structural empowerment (Keyko et al., 2016).
In the nursing context, lower levels of work engagement have been associated with higher levels of physical, emotional, and cognitive demands (Van Mol et al., 2018). These events also reduce the quality of care provided to patients, increasing the risk of poor treatment outcomes (Xanthopoulou et al., 2007). In addition, a Swedish Twin study found that high job demands increased the odds of long-term sickness absence and mental disorders (Mather et al., 2015). High emotional and physical job demands also resulted in sleep and burnout problems among the Malaysian workforce (Muhamad et al., 2020). In contrast, social support increased self-efficacy and a sense of security among nursing staff (Velando-Soriano et al., 2020). These findings reflect empirical evidence on the associations proposed by the JD-R model. However, Bakker and Demerouti (2017) highlighted several issues warranting further investigation such as the potential direct relationships between job resources and demands, as well as the significance of assessing these components at the organizational level. Further exploration of the underlying physiological or psychological mechanisms involved in the model’s description of health impairment and the motivational process is also warranted.
Although increasing job resources could significantly impact positive organizational outcomes, there is limited evidence-based data to support these events, particularly in the nursing context. Hence, this study focuses on the motivational process of the JD-R model of engagement, which suggests existing workplace resources can strengthen the motivational mechanism, leading to enhanced work engagement and reducing the risk of work-related adverse events (Bakker & Demerouti, 2007). Likewise, the optimistic nature of resources promotes employees’ well-being and provides a sense of security at work (Bajrami et al., 2022). More in-depth research is necessary to understand how nurses’ work engagement could be enhanced by providing resources during uncertainties and heightened work demands.
Apart from workload as a stressor under job demand, this study explores how dimensions of perfectionism affect work engagement among nurses. Perfectionism is a tendency to pursue perfection in all realms, constituting a personality trait that shapes an individual’s emotions and behaviors (Pishghadam & Akhondpoor, 2011). Perfectionism is a multidimensional concept, comprising positive and negative aspects, otherwise known as adaptive and maladaptive perfectionism, respectively (Egan et al., 2011). Our study focuses on both adaptive and maladaptive perfectionism, which refers to striving for flawlessness with high personal standards and a tendency of excessive self-evaluation and concern about other people’s comments and expectations, respectively (Frost et al., 1990).
Several studies have explored the relationship between perfectionism, learning motivation, and work engagement (Stoeber & Damian, 2016; Thomas & Bigatti, 2020; Xu et al., 2021). Maladaptive perfectionism demonstrated a negative impact on learning motivation; however, most previous research samples comprised athletes, middle school students, and other populations (Chang et al., 2015; Madigan et al., 2016), whereas research on nursing professionals is lacking. Therefore, to enhance nurses’ motivation, this study aims to explore how bidimensional perfectionism acts as a work stressor and its effects on nurses’ work engagement. Based on the aforementioned points, the research hypotheses in this study are as follows:
H1: Work overload negatively impacts nursing work engagement.
H2: Adaptive Perfectionism positively impacts nursing work engagement.
H3: Maladaptive Perfectionism negatively impacts nursing work engagement.
The second research objective is to explore the mediating effect of resilience in the relationship between stressors and nursing engagement via the buffering effect of social support. Resilience refers to an individual’s behavioral tendency to adapt to changing events and the ability to recover from stressful circumstances (Block & Kremen, 1996). In line with Richardson’s Resiliency model, resilience has a protective effect on cognition and behavior (Richardson, 2002). Studies have shown a positive relationship between perfectionism and self-esteem, and a significant correlation between resilience and self-esteem (Chen et al., 2013; Chung et al., 2021). As a positive psychological trait, resilient employees can mobilize protective resources and harness social support to cope effectively with adverse events and maintain positive emotional states (Klika & Herrenkohl, 2013). Huang et al. (2022) revealed a correlation between resilience, perfectionism, and positive coping style among nursing undergraduates. Additionally, resilience depicted a partial mediating effect in the relationship between perfectionism and academic performance (Huang et al., 2022). Therefore, resilience is expected to facilitate a reduction in perfectionism and improve work engagement among nurses. We speculate that there is a relationship between resilience and nursing engagement via social support. Thus, the fourth research hypothesis is as follows:
H4: Resilience mediates the relationship between workplace stressors and nursing engagement via social support.
Following the preceding discussion on the associations between study variables and nurses' engagement, the hypothesized conceptual model of the study is illustrated in Figure 2.
Conceptual framework.
Methodology
A study protocol serves as a guideline for clinical researchers to design and evaluate the step-by-step progress of the research (Al-Jundi & Sakka, 2016). By ensuring the safety of the clinical trial subjects and integrity of the data collected, a research protocol strongly improves the accountability and transparency of the intended investigation (Dane et al., 2021). Regarding the research community, the study protocol enabled academic scholars to assess whether the research findings were consistent with the investigators' original goals. Consequently, it also updates members of academia about the ongoing investigation and can assist in reducing duplication of research work. Hence, this study protocol was prepared using the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) reporting guidelines (Chan et al., 2013).
Study Type and Design
This study employed a quantitative, cross-sectional survey design. A cross-sectional study design, also known as descriptive research, analyzes data gathered from multiple individuals from a population of interest at a single point (Wang & Cheng, 2020). A multi-stage sampling technique was used in selecting the study population. The minimum sample size was determined using the Krejcie and Morgan sampling table (Krejcie & Morgan, 1970). Consequently, the Drop-Off/Pick-Up (DOPU) method for questionnaire distribution was selected to increase the survey response rate within a limited time frame.
Study Instruments
The nursing engagement survey comprised six sections to assess the factors influencing nurses’ engagement and well-being, as well as the effectiveness of these factors. The first segment entailed the participants’ demographic characteristics, such as gender, age, marital status, educational background, and duration of service in the nursing profession. In the following sections, five widely used instruments were employed to assess the research variables. All the research instruments entailed a 5-point Likert scale.
Nursing Engagement
Nursing Engagement will be measured using the Utrecht Work Engagement Scale (UWES-9) (Schaufeli et al., 2006), which covers three dimensions of work engagement: vigour, dedication, and absorption. This short version of the UWES-9 consists of nine items. Empirical evidence has shown that the UWES-9 is a three-factor construct that motivates psychometric properties. For instance, the UWES-9 obtained a Cronbach’s alpha value of 0.93 for the global scale when administered to samples of active healthcare workers during COVID-19. The Cronbach’s alpha values for absorption, dedication, and vigour were 0.79, 0.87, and 0.85, respectively (Domínguez-Salas et al., 2022). In another engagement study using the UWES-9 among nurses in Spain, an alpha value of 0.82 was obtained for vigour, 0.86 for dedication, and 0.8 for absorption (García-Iglesias et al., 2021).
Work Overload
Reilly’s role overload scale by Reilly (1982) will be utilized to assess nursing employees perceived work overload. The scale consists of 13 items, and the instrument has been extensively examined and evaluated on a parsimonious basis in previous studies (Deng et al., 2021; Ntopi et al., 2020). For instance, a study among health surveillance assistants in Malawi reported a Cronbach’s alpha value of .88, indicating acceptable reliability (Ntopi et al., 2020). An engagement study among residents undergoing regularization training in China also reflected a well-established reliability score with a Cronbach’s alpha value of .84 for Reilly’s Scale (Deng et al., 2021).
Bidimensional Perfectionism
The multidimensional trait of perfectionism of nurses will be measured using the short form of the revised almost perfect scale by Rice et al. (2014). This scale comprises eight items, measuring two key dimensions of perfectionism: adaptive perfectionism via the standards subscale, and maladaptive perfectionism via the discrepancy subscale. There are four items in each subscale. Previous studies have found that the Short Almost Perfect Scale (SAPS) demonstrates strong internal consistency, reliability, and good test-retest reliability (Rice et al., 2020). The recent psychometric evidence of the SAPS in Brazil obtained a Cronbach alpha value of .79 for discrepancy and 0.75 for standards (De Holanda Coelho et al., 2020).
Resilience
The psychological resilience of nursing staff will be assessed using the short version of the Connor-Davidson Resilience Scale (CD-RISC- 10), which consists of 10 items (Connor & Davidson, 2003). Numerous studies exploring the CR-RISC-10 have demonstrated strong psychometric properties and standardized factor loadings, suggesting excellent internal accuracy. A validation study of the CD-RISC-10 among student nurses in Southwestern Nigeria yielded a Cronbach alpha value of 0.81 (Aloba et al., 2016). In China, the scale yielded a Cronbach’s alpha value of 0.85 among Chinese nursing samples (He et al., 2021).
Social Support
The measurement scales for social support were adapted from the study by Mack and Rhineberger-Dunn (2019), which consists of eight items. The scale contains two subscales that measure supervisor and coworker support. Empirical evidence has highlighted the social support scale as a two-factor construct with good-to-excellent internal consistency and test-retest reliability (Mack & Rhineberger-Dunn, 2019). Specifically, a Cronbach’s alpha of .89 was obtained for the supervisor support subscale and .79 for the coworker subscale.
Study Population and Sample Size
According to the official portal of the Department of Statistics, Malaysia (DOSM), a total of 115,230 registered nurses are working in the public sector (Health Statistics, 2021). Due to the large scale of the population, this study employed a multi-stage sampling design. Multi-stage sampling is a method of obtaining a portion of a population by segmenting it into progressively smaller groups until a desirable or manageable sample frame is obtained. Subsequently, individuals from the ultimate sampling unit are randomly selected in the study (Lewis-Beck et al., 2011; Sedgwick, 2015). The rationale for employing this approach is that it enables researchers to efficiently and cost-effectively collect data from a sufficiently large sample size (Lewis-Beck et al., 2011). By utilizing this sampling method, researchers can draw inferences about the entire population based on information obtained from a smaller sample.
The study population comprised public healthcare nurses from Peninsular Malaysia, which were divided into four region clusters: Northern Region (Perlis, Kedah, Penang, and Perak), East Coast (Kelantan, Terengganu, and Pahang), Central Region, (Selangor, federal territories of Kuala Lumpur and Putrajaya) and Southern Region (Negeri Sembilan, Malacca, and Johor). In the first stage, a simple random sampling technique was employed to obtain the initial cluster, and the northern region was randomly drawn. Next, the selected cluster was subjected to additional sampling of the subdivision areas. In the second stage, the states in the chosen cluster were divided into separate clusters of Perlis, Kedah Penang, and Perak accordingly. In the third stage, all four capital cities in the selected states were selected, namely Kangar in Perlis, Alor Setar in Kedah, Georgetown in Pinang, and Ipoh in Perak. Finally, a general hospital from each city was chosen randomly and samples from the selected hospitals were included in the analysis. Given the homogeneity nature of the nursing workforce in most hospitals across Malaysia, this study focused on the major general hospitals situated in each of the respective states. Thus, the obtained study sample from the northern region represents the Malaysian nurse population, supporting the generalization of the research findings.
In terms of sample size, it is strongly suggested that the overall number of samples should preferably be at least 10 times greater than the number of study variables (Roscoe, 1975). This study examined five variables; hence, the sample size should be at least 50. Based on the Krejcie and Morgan sampling table (Krejcie & Morgan,1970), the minimum sample size for this study was computed as 381 respondents. The sample size was doubled to 762 to obtain a sufficient response rate from respondents as recommended by Hair et al. (1998). The rationale for doubling the sample size is to yield a more diverse sample, thereby enhancing the representativeness and generalizability of the results (Williamson, 2023). In addition, expanding the sample size can improve the study’s statistical power, strengthening the likelihood of detecting a statistically significant result. A larger sample size also yields a more accurate representation of the population and reduces the likelihood of Type II errors (James et al., 2016). Overall, this study population consisted of 762 Malaysian public healthcare nurses, aged 18 to 60 years, working in four general hospitals in Northern Malaysia.
Inclusion Criteria
i. Nursing personnel from diverse categories at the chosen hospital regardless of their designated department or area of expertise.
ii. Participants were required to have good English and Malay literacy levels to comprehend and respond to the research instrument and provide informed consent as the questionnaire and informed were distributed in dual language.
Exclusion Criteria
i. Nurses working in governmental health clinics and community clinics.
ii. Nursing professionals with limited experience include nursing assistants, student nurses, and those with less than one year of work experience in the field.
iii. Nurses on long-term leave (maternity and study leaves).
Withdrawal Criteria
The involvement of subjects (nurses) in this study relies on their voluntary participation, and they are free to leave at any time without feeling an obligation to continue or providing the reason for withdrawal.
Study Duration
Data collection for this study was conducted over three consecutive weeks (01/04/2023 to 31/04/2023). The participation duration for each subject was one point in time while completing the questionnaire. It took approximately 10 to 15 min to complete each set of questionnaires.
Risk and Benefit to Study Participants
This study was designed in such a way as to reduce unwanted risk factors during the data collection process via minimal contact with study participants. Hence, there was no significant risk to potential subjects. The anticipated benefits outweigh the minimal risk to the research participants, as the research protocol was thoroughly reviewed and approved by the Institutional Review Board (IRB), the national medical ethical committee, and other relevant authorities. Furthermore, respondents’ identifiable information was diligently managed and disseminated to safeguard their privacy and ensure data confidentiality. The researcher is responsible for the accuracy and comprehensiveness of the research reports, as well as obligated to publicly disclose the findings to human subjects transparently. In accordance with ethical requirements, all study participants will be informed of the research findings, and their contributions to the study will be acknowledged in published works.
Informed Consent/Assent Process
The enrolment of research subjects for this study began after obtaining ethical approval and relevant approvals from all regulatory bodies. Hence, before the data collection process, all potential respondents were given a participant information sheet, an informed consent form, and a questionnaire, along with a cover letter that provided a concise explanation of the research purpose. Supervisors (matrons) distributed the participant information sheet/informed consent form to prospective subjects (nurses) at their respective departments or wards during their break. In this regard, the matrons in charge were also responsible for briefly conveying the study information to the research subjects, as described by the researcher.
Furthermore, the participants’ confidentiality and privacy were ensured through the cover letter and informed consent forms. The nurses were also informed that their involvement was voluntary and that they could withdraw from the study at any point without feeling obligated to continue or provide a reason for the withdrawal. All potential respondents were provided sufficient time to consider their participation in this study. Hence, interested participants were encouraged to participate in this study after they provided written informed consent.
Privacy, Confidentiality and Data Protection
In order to ensure participants’ confidentiality, their identity, personal information, and responses (study data) were not disclosed to anyone outside the research team without their written consent. The data gathered were only utilized for study purposes. More importantly, the gathered data were kept confidential and protected from any unauthorized access. The research also segregated written information forms after data collection, which contained personally identifiable information of research participants and treated them as confidential documents.
Therefore, all the data files were stored securely in a safe or locked file cabinet. For digitalized data, the stored data were secured using encryption technology with a strong password to ensure data confidentiality. In general, regulations demand that all data acquired during research activities be preserved for a minimum of three years following the completion of the study and made available to regulatory authorities upon request. As a result, once the retention period for completed research expires, all paper files or electronic files with personal identifying information will be shredded, and any electronic files on hard drives, personal computers, or laptops will be permanently deleted.
Study Visits and Procedures
Approval from all research sites was obtained prior to the commencement of research activities. The researcher requested assistance from the Clinical Research Centre at the study sites to facilitate the study approval process, which requires approval from the Director of the Hospital and Head of the Nursing Department. This study employed Drop-Off and Pick-Up (DOPU) techniques for data collection, whereby survey questionnaires are delivered to respondents and retrieved upon completion. Considering the hospital guidelines that restrict direct contact with staff nurses, the DOPU method was chosen as a cost-effective approach and an alternative to other modes of data. Moreover, this data collection technique facilitates researchers in efficiently gathering research data within a brief period, while simultaneously achieving a higher response rate (Allred & Ross-Davis, 2011).
The survey began with a preliminary clarification of the research objective and the protection of participants’ privacy and confidentiality. All study participants were provided with participant information sheets and written consent forms to ensure they had adequately understood the research information before providing their written consent. The principal investigator’s contact information (phone number and email address) was provided in the survey and informed concern form for queries, doubts, or additional clarification of survey participants. Written informed consent was obtained from subjects who agreed to participate in the research project before enrolment in this study.
Survey questionnaires were delivered to the selected hospitals. The head nurses/matrons from randomly selected wards assisted the researcher in distributing the questionnaires to nurses who fulfilled the inclusion criteria. All participating nurses were given 3 weeks to complete the questionnaires. The researcher made a call reminder with the matrons in charge of the data collection process. Thereafter, the completed questionnaire was gathered by the investigator for data analysis after three weeks. The questionnaire distribution process is illustrated in Figure 3 below.
Flow chart of research questionnaire distribution process.
Pilot Study
To assess the validity and reliability of the research instruments, a pilot study was undertaken among a sample of 55 healthcare nurses. The pilot test is a preliminary investigation to assess the feasibility and viability of an approach planned for the main study (Leon et al., 2011). A construct is considered reliable if its alpha (α) value exceeds .70 (Hair et al., 2013). The pilot study results revealed that the work engagement, work overload, perfectionism, resilience, and social support scales displayed acceptable to excellent levels of reliability of .871, .872, .763, .830, and .894, respectively.
Data Analysis
Inferential statistical analysis was performed using Simultaneous Multi-group Analysis and Response-based Partial Least Square (Smart PLS) 3.0, whereas Statistical Package for the Social Sciences (SPSS) version 23 was employed for descriptive analysis. A Partial Least Squares Structural Equation Model (PLS-SEM) was utilized to analyze the proposed moderated mediation framework. PLS-SEM is a variance-based technique that is uszed to perform several multivariate statistical analyses, such as correlation, regression analysis, factor analysis, and path analysis. The statistical software also simultaneously assesses multiple regression models (Dash & Paul, 2021; Sarstedt et al., 2014). The respondents’ demographic characteristics were presented as frequencies (n) and percentages (%). Statistical significance was established when the
Expected Findings and Discussion
This study is the first attempt in Malaysia’s nursing context to use the JD-R model in elucidating the relationships between stressors (work overload and perfectionism) and nursing engagement, as well as the mediating role of resilience in enhancing nursing engagement via social support. The research hypotheses tested in this study posit that work overload and perfectionism impact nursing work engagement negatively, and the association between social support and nursing engagement is mediated by resilience.
We expect that the first and second research hypotheses will be supported. Work overload triggers an imbalance between workplace demands and resources that is likely to demotivate nurses and affect their work engagement. In contrast, ensuring an equilibrium between workplace demand and resources can strengthen motivational mechanisms and enhance work engagement (Bajrami et al., 2022). The findings will reveal how work engagement among Malaysian nurses can be shaped by workplace demands, including cognitive, emotional, and physical demands levels. As for the second research hypothesis, perfectionism is expected to also impact negatively on nursing engagement, which is consistent with previous studies (Xu et al., 2021; Yu, 2022). Nurses with higher levels of perfectionism are more vulnerable to learning demotivation, which may affect their level of engagement (Yu, 2022).
The researcher aims to gather evidence-based data to depict how resilience mediates the mediating role in the association between work stressors and nursing engagement via social support. Apart from being a positive psychological trait, resilience has a protective effect on employees’ cognition and behavior (Wan et al., 2023). These events are expected to enhance nurses’ capacity to mobilize job resources, social support, and better engagement with patients. Consistent with a recent study, resilience had a partial mediating effect on perfectionism and academic performance in nursing students (Huang et al., 2022). Thus, one way in which resilience shapes nurses’ work engagement is by facilitating adaptive perfectionism, rather than maladaptive perfectionism. These events have important implications in terms of quality of care and treatment outcomes for patients (Kyeko et al., 2016).
This study elucidates the current state of nursing staff and sets the roadmap for future positive outcomes in healthcare systems. Most importantly, improving nursing engagement will be reflected in improved patient safety, enhanced quality care, patient experience outcomes, nurses physical and psychological well-being (Bailey & Cardin, 2018; Bajrami et al., 2022; Tomietto et al., 2019) in line with previous nursing literature. The findings are pertinent in developing effective strategies and policies to address and minimize the impact of stressors, which constitute the most significant threat to nurses’ mental health and performance.
Overall, the research findings will be crucial to policymakers in Malaysia’s Ministry of Health (MOH) and hospitals as they plan to develop new programs and training programs to enhance nursing engagement. By highlighting the key strengths and weaknesses of nursing workforces, this study may provide the healthcare system with more insights that may be used to better equip its workforce to respond appropriately during public emergencies (Armocida et al., 2020). Nurse leaders could enhance quality care, retain excellent nursing workforces, and promote the physical and mental health of nursing staff through sufficient resources and a supportive environment (Murphy et al., 2022). This initiative will create a healthy environment for more work engagement, overcome workforce crisis, and promote the well-being of clinical nurses.
In addition, the results will be submitted for publication in peer-reviewed journals, subject to approval from the Director General of Health in Malaysia. Despite its noteworthy contributions to the body of knowledge, it is anticipated that the findings of the current study will generate significant interest among a diverse array of individuals and organizations, which will benefit the community overall.
Termination of Study
In the event that the research is discontinued, the participants will be notified of the termination, and a record of the termination will be submitted to the ethical committee.
Limitations of the Study
Despite the large sample size of nurses recruited in this study, the limitations stem from the fact only those from the Northern region of Malaysia participated in the survey. While the four selected hospitals are typical of the Malaysian healthcare industry, variations in workplace settings in comparison to healthcare centers in other Malaysian regions cannot be eliminated. Moreover, cross-sectional research design is limited by gathering data at a given point and results only reflect the relationships between the investigated variables. This study is unable to make any causal inference between workplace stressors and nursing engagement. In addition, relying only on survey instruments has inherent limitations, such as the potential for response bias. Quantitative surveys generally make no provisions for a detailed explanation of the measured variables. Despite these limitations, the strengths of this study lie in addressing the data paucity on the predictors of nursing engagement and well-being, particularly the impact of work overload and perfectionism, as well as using positive psychology traits (i.e., resilience and social support) in addressing the inherent problems.
Conclusion
This article presented a study protocol that has the potential to elucidate the current state of nursing staff and identify strategies to enhance nursing engagement and well-being. Such strategies and policies are pertinent to address and minimize the impact of stressors, which pose the most significant threat to the mental health of healthcare workers. By highlighting the key areas of strength and weakness of the nursing workforce, this study may provide the healthcare system with more insights that could be used to better equip its workforce to respond appropriately during times of adversity. Further, this study is likely to underscore the wider implications for healthcare organizations, consequently emphasizing the significance of nursing engagement in enhancing positive healthcare outcomes. In this light, engagement initiatives transcend being merely an organizational strategy, as they serve a fundamental element of healthcare excellence that ensures patient safety and workforce sustainability by advocating for nurses’ physical and mental well-being. As a result, the healthcare organizations may improve overall clinical care by building a more robust and effective health system.
Footnotes
ORCID iD
Ethical Considerations
). Prior to starting study-related activity,additional clearances from study sites and other pertinent authorities were obtained.