Unravelling the link between psychosocial safety climate (PSC) and burnout: a longitudinal study of healthcare workers in Malaysia

Introduction

The psychosocial safety climate (PSC) refers to employees shared perceptions of organizational policies, practices, and procedures that prioritize the protection of workers’ psychological health and safety (1). As a higher-order organizational construct, PSC reflects senior management’s commitment to stress prevention, the prioritization of psychological health relative to productivity, open communication about mental health and safety issues, and active organizational participation in addressing psychological risks (2). Over the past decade, PSC has become a leading indicator of psychosocial risk, underpinned by a strong theoretical and empirical foundation within occupational health research (3,4). Today, PSC is recognized as a well-established theoretical framework, supported by extensive evidence demonstrating its pivotal role in shaping workplace well-being and mitigating stress-related outcomes (1,5). Instead of focusing on physical or chemical hazards, which are more synonymous with occupational health exposure, the PSC includes a psychological component which deals with human perceptions and their responses to stress. This can be more specifically termed the psychosocial hazard. PSC also found to play a pivotal role shaping the work environment, well-being, and performance of healthcare providers. Prioritising PSC within healthcare settings is crucial to safeguarding the well-being of healthcare providers and improving patient outcomes (6).

Modern healthcare systems are under constant strain from shifting population demographics, which drive changes in disease patterns and exacerbate health inequities between rural and urban areas. These systemic pressures are amplified in upper- and middle-income countries (UMICs) and low- and middle-income countries (LMICs), where workforce shortages (7,8), ageing populations (9), and limited fiscal capacity strain the delivery of safe and effective care (10,11).The stressors have been further exacerbated by pandemic-related disruptions, which revealed underlying inefficiencies in care delivery, resource allocation, and workforce preparedness (12). The coronavirus disease 2019 (COVID-19) pandemic crisis also exposed weaknesses in healthcare infrastructure globally which highlighting gaps in surge capacity, staffing resilience, and mechanisms for protecting the mental health of frontline workers (13). Alongside these systemic issues, healthcare staff face mounting challenges in their daily work, including high workloads, unequal resource distribution, interpersonal conflicts, and frequent exposure to physical and psychological hazards (5-7). A comprehensive review reported that over one-third of public health professionals experience burnout, a condition strongly linked to depression, anxiety, absenteeism, and reduced care quality (14). Recent evidence from Malaysia highlights a high prevalence of occupational exhaustion among healthcare workers, with prolonged working hours and reduced psychological well-being significantly linked to lower quality of life during the COVID-19 pandemic (15). The cumulative impact of these pressures highlights an urgent need to support healthcare worker mental health and reinforce organizational resilience globally such as PSC to safeguard HCW well-being. Although the current study data predate COVID-19, this discussion draws on pandemic-era experiences to contextualise the enduring relevance of psychosocial pressures in healthcare settings, rather than to infer direct pandemic-specific effects.

The World Health Organization (WHO) believes that mental health is clearly an integral part of the general health system and defines it as a state of well-being in which every individual realizes his or her own potential, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to his or her community (16). The concept of productive work is highly dependent on the individual’s mental health state. An alteration in mental health status would have a detrimental effect on work productivity. Work could also potentially exert negative implications on mental health whereby a stressful work condition will ultimately lead to mental disorders such as anxiety, disturbed sleep, depression and burnout (17,18).

First introduced by Freudenberger (19), the term burnout is most commonly used in the human service field to “refer to a state of emotional exhaustion caused by excessive psychological and emotional demands made on people helping people” (20). Burnout is more than just feeling tired after a long day at work; it is a profound psychological syndrome that arises from chronic, unrelenting workplace stress when coping mechanisms fail (21). Traditionally, burnout is characterised by emotional exhaustion, depersonalisation, and reduced professional efficacy, which be considered as a major occupational health concern, particularly in healthcare (22). Emotional exhaustion, the core of burnout, leaves individuals feeling drained, as though they no longer have the energy to face their daily tasks. Cynicism, or depersonalization, reflects a growing sense of detachment or negativity towards one’s work and colleagues, and a shield may be raised to protect themselves from further emotional strain. Lastly, reduced professional efficacy (inefficacy) saps confidence and fulfilment, leaving individuals doubting their competence and questioning their accomplishments (22). Maslach and Schaufeli (23) report that factors relating to one’s occupation are more highly correlated to burnout than “biographical or personal factors”. They focused on the occupation variables including job stress, job satisfaction, job withdrawal, job expectation, relations with co-workers and supervisors as well as the agency policy. Burnout doesn’t just impact the individual, but it ripples outwards. On a personal level, it erodes mental health, contributing to anxiety, depression, and sleep disturbances (24). In the workplace, it drains organizational productivity, fuels absenteeism, and drives valuable workers to leave their roles, adding to systemic pressures. In clinical environments, burnout is associated with reduced patient safety, more frequent medical errors, and compromised quality of care (25). Clinicians struggling with burnout may make more errors, experience diminished empathy, and face difficulty maintaining the high standards their patients deserve (25). Numerous occupational and demographic factors contribute to burnout, including long working hours, shift work, interpersonal stressors, and inadequate support from supervisors and organisations (26). Malaysian studies similarly report burnout across various sectors including lecturers, junior doctors, and nurses underscoring the influence of psychosocial work conditions on mental health (27-29). Burnout, therefore, is not just an individual problem. Rather it is a collective challenge that calls for urgent attention to create healthier, more sustainable workplaces.

There are several factors which contribute to burnout. There are some which are related to occupations like type of employment (full-time versus part-time employment) and ergonomic problems (seat adjustment, back support, vibration, rocking/bouncing seats). These have been found to be significant risk factors among urban transit operators and there is an increased risk of burnout among physically inactive workers (30). Long working hours are highly correlated with burnout when working over 40 hours per week and correlation is even stronger when working over 60 hours per week (31). A meta-analysis looking at gender differences of burnout found that women were more predominant in the exhaustion subscale while males were somewhat more depersonalized than women (32).

There have been a few studies that have looked at burnout and risk factors among Malaysians. One reported that a substantial prevalence of burnout was found among English teachers and that it was associated with duration of teaching experience (33). Teachers with less than 25 years of teaching experience were found to be significantly more emotionally exhausted compared to those with 25 years of teaching experience and more (mean difference =4.42±8.68). Another study on burnout among Malaysians looked at the PSC as the antecedent factor of emotional demand in predicting burnout (3).

PSC exists in every single work organization in the world, regardless of the type of organization (public or private) and regardless of the kind of services the organization provides. Earlier research on PSC predominantly argues for the PSC to be the antecedent of job conditions and conducive work environment which indirectly leads to a work-related outcome (e.g., burnout and work engagement) through Job-Demand-Resource (JDR) model among academicians and industrial workers (2,34). PSC research has been expanded to other occupational fields; and the recent study conducted among Malaysian nurses supports the moderating roles of PSC on emotional demands by integrating the JDR model in the built hypothesis (35).

While PSC research has expanded globally, several gaps remain particularly in UMIC and LMIC healthcare settings. First, most Malaysian PSC studies have been cross-sectional, and even two-wave longitudinal design limiting the ability to assess temporal relationships and infer causality. Second, very few studies have examined PSC in healthcare systems characterised by hierarchical organisational structures, high power distance, collectivist work norms, and policy-driven performance targets all cultural and systemic factors that may meaningfully shape the PSC-burnout relationship (36,37). Third, previous research has primarily focused on establishing the construct and theoretical foundation of PSC, with limited emphasis on its practical implications. Building on this established theoretical framework, our study aimed to investigate how perceived PSC influences a critical work-related outcome (i.e., burnout) among healthcare workers and whether higher PSC predicts lower burnout over time. Our work also contributes much needed data on Southeast Asian healthcare settings where limited PSC research has been carried out.

The present study addresses these gaps by examining PSC and burnout among Malaysian healthcare workers using a three-wave longitudinal design. Although the data were collected a decade ago, the longitudinal structure offers rare and valuable methodological insight into how PSC predicts burnout over time, an approach still scarce in PSC literature globally (1,38). Moreover, many fundamental organisational stressors in Malaysian hospitals such as workload, resource constraints, hierarchical decision-making, and psychosocial risk exposure remain highly relevant today, making the findings applicable for current workforce challenges. This is particularly important for nurse managers, who require robust, evidence-based organisational indicators to support staff well-being and retention.

By integrating the PSC framework with longitudinal evidence from a Malaysian hospital setting, this study contributes three novel elements to the literature: (I) empirical examination of PSC as a temporal predictor of burnout within an UMIC healthcare system; (II) extension of PSC research into culturally and structurally distinct organisational environments; and (III) actionable insights for organisational interventions aimed at strengthening psychosocial safety and reducing burnout among Malaysian healthcare workers. In addition, this study contributes to addressing important gaps in understanding temporal associations, contextual influences, and practical relevance of PSC in healthcare settings. We present this article in accordance with the STROBE reporting checklist (available at https://jphe.amegroups.com/article/view/10.21037/jphe-2026-1-0007/rc).

Methods

Study designs and participants

This study employed a three-waves longitudinal observational study over a one-year period. Data were systematically collected at three time points: baseline (Time 1, T1 at 0 months), the first follow-up (Time 2, T2 at 3 months), and the second follow-up (Time 3, T3 at 9 months). The longitudinal design enabled the tracking of temporal changes and relationships, enhancing the robustness of the study’s findings.

To ensure representative sampling, 45 work units—comprising 15 clinics and 30 wards from diverse clinical departments at the University of Malaya Medical Centre (UMMC), Malaysia were randomly selected. Ethical approval for the study was secured from the University of Malaya Medical Centre Medical Ethics Committee (No. MEC 201311-0538), and all participants provided written informed consent, underscoring adherence to ethical research standards. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

To enhance representativeness and reduce sampling bias, a multi-stage stratified sampling method incorporating probability proportional to size (PPS) was employed. The required sample size was determined using OpenEpi, with parameters set at 80% statistical power, a 95% confidence level, and an expected odds ratio of 1.39 (28). Accounting for an anticipated 20% attrition rate over the study period, the desired sample size was estimated to be 800 participants, ensuring adequate power for detecting meaningful associations. Eligible participants were permanent staff employed for at least six months with no prior mental health morbidity. Prior history of mental health morbidity was assessed through self-report at enrolment and applied as an eligibility criterion to minimise potential confounding from pre-existing mental health conditions. The flow of cohort retention is illustrated in Figure 1.

Figure 1 Cohort retention flow. PSC, psychosocial safety climate; T, time.

Materials and procedure

Data collection was conducted over a one-year period, from December 2014 to December 2015, using a longitudinal design comprising three waves: baseline (T1), a three-month follow-up (T2), and a nine-month follow-up (T3). At each wave, participants completed structured, hardcopy self-administered questionnaires encompassing socio-demographic and occupational data, along with key psychosocial measures. PSC was measured using the validated Malay version of the PSC-12 scale, which was systematically translated and culturally adapted from the original English version (39) to ensure conceptual and linguistic equivalence. We reported the development and validation of the Malay version of the PSC-12 in a separate publication (40).

PSC scores were categorised into three ordinal levels: low (≤37), moderate [38–40], and high (≥41), based on established cut-off thresholds (41). Meanwhile Maslach Burnout Inventory General Survey (MBI-GS) questionnaire was the main tool used to measure burnout encompassing three key domains: emotional exhaustion, which reflects feelings of being emotionally drained and overextended; cynicism or depersonalization, characterized by a detached or negative attitude towards one’s work or colleagues; and professional efficacy, which assesses an individual’s sense of competence and accomplishment in their job. The MBI-GS generates three noncumulative scores, whereby higher mean scores on the emotional exhaustion (EX) and cynicism (CY) subscales indicate greater burnout, while lower scores on the professional efficacy (PE) subscale correspond to higher burnout (42).

While derived from the same participant cohort and study procedures as the parent longitudinal study, the current study addresses a distinct objective through a specific analysis focused on burnout trajectories rather than broader occupational outcomes.

Statistical analysis

All data were entered into IBM SPSS Statistics version 21 using a double-entry approach to ensure data accuracy and consistency. Data cleaning procedures, including code validation and checks for entry errors and missing values, were systematically applied. Backups were maintained on separate encrypted storage devices to prevent data loss. Assumptions for parametric analysis such as normality (using the Kolmogorov-Smirnov test and graphical inspection of histograms and Q-Q plots) and homogeneity of variance (using Leven’s test) were assessed prior to conducting inferential tests. The categorical data was presented as frequencies (percentages), continuous data was reported using mean ± SD, median + IQR and P threshold is set at two-tailed.

Descriptive statistics were used to summarize socio-demographic and occupational characteristics, as well as the distribution of PSC and burnout scores. Burnout was analyzed both as a continuous variable based on the total MBI-GS score, and across its three core subscales: exhaustion, cynicism, and professional efficacy.

Initial associations between independent and outcome variables were explored using univariate and bivariate analyses. Variables with Ps <0.25 were included in the multivariable model. Repeated measures ANOVA with post hoc pairwise comparisons was used to examine temporal trends in PSC and burnout over the three data collection points. As a robustness check, the consistency of effect estimates across repeated analyses and time points was examined to assess the stability of the findings. Multivariable logistic regression models were employed to identify significant predictors of burnout, controlling for potential confounders. Variance inflation factors (VIF) were used to assess multicollinearity, with all included predictors falling below the acceptable threshold (VIF <5). A P<0.05 was considered statistically significant in the final model. We selected the final model based on the principle of parsimony and best fit using the Hosmer-Lemeshow approach of using −2 log likelihood ratios. Interactions were assessed but none were found.

Further elaborating on the analysis, the study included 618 participants who remained enrolled across all three waves, as illustrated in Figure 1. Although cohort retention was maintained, analyses were conducted using model-specific complete-case samples, resulting in variation in sample sizes depending on data availability for variables included in each model. The 135 missing data were handled using a model-specific complete-case approach, whereby observations with missing values for variables required in each analysis were excluded. A post-hoc power analysis based on the observed effect size (partial η²=0.024; Cohen’s f=0.157) demonstrated statistical power is >90%, suggesting that study validity and statistical precision were unlikely to have been materially affected.

Results

Socio-demographic and occupational characteristics

A total of 618 participants remained enrolled throughout the three-wave longitudinal study. The median age was 28.08 years (IQR, 11 years), with a mean age of 31.52 years (SD ±9.40 years). Participants ranged in age from 20 to 59 years. The sample was predominantly female (89.6%), with males comprising only 10.4%. This gender imbalance aligns with the composition of the workforce as nurses and paramedics accounted for 80.0% of the sample, with only a small number of physicians (0.5%) included; while 19.5% were from the supporting staff category. Most (76.2%) participants had completed tertiary education, consistent with their roles as nurses and paramedics, whereas 23.8% of participants who had secondary education were primarily in supporting roles, such as drivers, health attendants, and clerical staff.

A slight majority of participants (53.2%) were married, while the remaining respondents were either single, divorced, or widowed. The vast majority (96.8%) identified as non-smokers. Although only 19.9% reported engaging in regular physical activity, the prevalence of chronic illness was relatively low, with just 8.3% indicating one or more existing health conditions. The latter observation could be attributed to the relatively young demographic of the sample, which consisted mainly of younger staff and who were thus less likely to have chronic health conditions.

Occupationally, 68.1% of participants worked in medical-based units, while 31.9% were in surgical-based units. The median duration of employment at their current workplace was 6.12 years. A majority of participants (79.1%) worked in shifts, compared to 20.9% who followed regular working hours.

The distribution and trend of PSC score

Participants reported a mean PSC score of 41.44 (SD ±8.27) and a median of 42.88. Most (61.1%) were classified in the high PSC category, while 28.5% and 9.0% fell within the low and moderate categories, respectively. Subscale scores ranged from 10.01 (SD ±2.40) to 10.76 (SD ±2.15) across key PSC dimensions. This has been reported in a prior publication (43).

A significant improvement in PSC scores was observed over the study period, with an increase from Time 1 (baseline–0 months) to Time 3 (follow-up 2–9 months). This was demonstrated by repeated measures analysis, showing a statistically significant improvement in PSC scores from T1 to T3 (mean difference =1.42, P=0.04). This progressive enhancement in PSC levels demonstrates a favourable upward trend in PSC scores over time.

Distribution and trend of burnout score

About half (51.3%) of study participants were documented to have burnout while the rest did not (Table 1). The professional efficiency mean score was 26.61 (SD ±8.23) with 47.3% reporting high professional efficiency, 21.9% having moderate professional efficiency and 29.4% with low professional efficiency. The average score for exhaustion was 12.27 (SD ±7.76) with 33.4%, 21.8% and 44.0% reporting high, moderate and low exhaustion levels respectively.

There was not much difference in proportion between high (37.3%) and moderate (38.4%) cynicism levels, while only 21.9% documented low cynicism levels. The mean cynicism score was 9.35 (SD ±6.00) with a median of 8.61. Repeated measures analysis revealed significant changes between Time 1 and Time 3 scores for professional efficiency and exhaustion as depicted in Table 2, but no significant change for cynicism.

Association and temporal effect between PSC and burnout

Only PSC Time 1 and age were found to be significant independent predictors for burnout at Time 1 after adjusting for other covariates (Table 3). The lower the PSC level, the higher the likelihood for the healthcare worker to develop burnout [adjusted odds ratio (aOR) 0.97; 95% confidence interval (CI): 0.94, 0.99, P=0.002]; the younger the staff, the more likely they were to burnout (aOR 0.97; 95% CI: 0.94, 0.99, P=0.002). Duration of employment and types of working hours which were initially significant during crude analysis were not significant after adjusting for other variables and were eliminated from the model. No significant interaction was found.

We checked to see if independent variables measured at Time 1 would be able to predict burnout at Time 2 (i.e., at the 3-month interval). Among the main significant predictors included in the final prediction model were PSC Time 1, PSC Time 2 and burnout Time 1, together with education level and work unit category as significant covariates. Looking at the P and 95% CI for PSC Time 1, it does not meet the significant value cut-off point in Table 4. However, we retained it in the final model and considered it to be an important predictor since the −2 likelihood ratio difference between the tested models (with and without PSC Time 1) was found to be greater than the critical value, indicating that the variable could not be eliminated from the prediction model. From our analysis, we think that PSC has an important acute effect in preceding burnout by 3 months.

We further analysed the effect of PSC and burnout at 9 months (Table 5). PSC at Time 1 was not a significant predictor for burnout at Time 3 (after 9 months) after controlling for other relevant socio-demographic and occupational covariates. However, PSC at Time 3 was a significant independent predictor for burnout at Time 3 (aOR 0.95; 95% CI: 0.92, 0.98, P<0.001).

Discussion

This longitudinal study examined the temporal relationship between PSC and burnout among hospital-based healthcare workers across three measurement points over one year. By adopting a three-wave design, this study offers insights that extend beyond the cross-sectional PSC literature and contributes needed evidence from a large Southeast Asian healthcare setting. We think that there will be a distinct difference on burnout with this kind of time-based exposure based on the stipulated theoretical stress-strain model (44). Previous studies have reported that a one-year longitudinal study might not be long enough or adequate enough to exert a substantive effect compared to two years of longitudinal study (45), but there is a condition called ‘boundary restriction’ that renders the one-year follow-up to be more feasible in this context (44). Therefore, a three-wave data collection with a mix of 3-, 6- and 9-month intervals over the entire one-year study period was performed with the purpose of exploring PSC association with an adverse psychological event (burnout). The findings provide several important theoretical and practical implications:

Temporal dynamics between PSC and burnout

Our research has the distinct advantage of being able to properly explore the temporal effect of PSC on adverse psychological outcomes over a longer time duration (9-month interval between T1 and T3) as compared to a previous similar study which only looked at the PSC association with emotional demand and depression using a two-wave longitudinal study (3,35). The stipulated theory proposed here is that a longer exposure to an exhaustion-laden work environment precipitates a higher risk of developing adverse psychological outcomes. Given the longer exposure duration which provides a robust methodology to capture the dynamic relationship between PSC and burnout over time, current study revealed a consistent finding with the PSC theory and the broader stress-strain framework (1,46); PSC at baseline significantly associated with the subsequent burnout three months later but not at the nine-month interval. This pattern suggests that PSC may exert a stronger short-term protective effect, buffering employees from immediate psychosocial strains but potentially diminishing over longer durations if organizational conditions change. Similar short-term temporal effects have been reported in longitudinal occupational stress research, where the strength of predictive relationships decreases as the measurement interval lengthens (47). The observed short-term temporal association may suggest that PSC operates through more immediate workplace mechanisms, such as perceived management support, communication, and organisational responsiveness, which may influence burnout over shorter intervals. The absence of a sustained association at 9 months may reflect the influence of additional dynamic factors, including changing workload pressures, emotional demands, and other organisational conditions not captured in the present analysis.

The lack of statistical significance at nine months does not necessarily imply an absence of long-term influence. Instead, it may reflect dynamic adaptation processes, where healthcare workers develop coping strategies, recalibrate expectations, or receive social support that weakens the direct PSC-burnout association over time. This explanation aligns with evidence that burnout trajectories can fluctuate depending on work demands, coping resources, and organizational changes (48) (Leiter & Maslach, 2016). Methodologically, this demonstrates the value of multi-wave designs in capturing short- versus long-term effects that would be missed in two-wave studies.

Contribution to PSC literature: extending evidence from UMIC and hospital contexts

While conducted in an UMIC context, the findings may offer relevance to comparable resource-constrained healthcare settings, including some LMIC contexts within the region. While PSC is well studied in Australia and Europe, empirical evidence from UMIC or LMIC healthcare systems remains scarce. Studies in Malaysia have examined PSC in industrial or academic settings (3,49), but no previous study has assessed its temporal association with burnout among healthcare workers, making the present work an important contribution. PSC levels in the UMMC clinical units were quite high with a total mean score of 41.44 (SD ±8.27) and more than half of enrolled healthcare workers perceived their work environment to have high PSC levels; which would indicate a low risk of developing adverse psychological outcomes. This is consistent with previous findings as enhancing PSC in organizations to levels above 37 has been associated with a 14% reduction in job strain and a 16% decrease in depressive symptoms among the working population (41). Meanwhile, repeated measures analysis over the three time-related data found a significant increasing pattern of the perceived PSC level among study participants. This significant difference was observed at the 6-month interval (between T2 and T3) and the 9-month interval (between T1 and T3). It has been reported elsewhere that policy transformation like privatisation of healthcare services and managerial change can contribute to the dynamism of the hospital climate including the psychosocial work environment (50).

The longitudinal upward trend in PSC across the three waves is particularly worthy. Climate constructs are typically assumed to be stable, but recent evidence suggests they can improve when organizations implement structural and cultural interventions (51). This observation provides an empirically grounded example of PSC’s dynamic nature, reinforcing that PSC is modifiable and responsive to organizational action.

Comparison with previous longitudinal studies

To date, most PSC studies use two-wave designs, limiting insight into temporal pathways. Only a few multi-wave studies exist globally (38,52), and they largely originate from non-healthcare sectors. Our three-wave study enhances temporal resolution and allows more nuanced interpretation of time-lagged effects.

While prior research frequently incorporates the JD-R model as a mediator (53), our findings show that PSC directly predicted burnout without explicitly modelling emotional demands or resources. This suggests that in high-intensity clinical environments, PSC may operate not only via the JD-R pathway but also as an independent organisational signal influencing workers’ expectation, trust, and perceived psychological safety. This aligns with arguments that PSC is a “cause of the causes”—a primary upstream organisational factor shaping downstream working conditions (54).

Burnout levels and organizational context

There is still a lack of research on the issue of burnout among healthcare workers. It is imperative to acknowledge that the landscape of burnout among healthcare worker is dynamic and can evolve over time. Burnout levels in this study warrant attention within the Malaysian context. Although overall PSC levels were high, burnout symptoms were still evident, reflecting an international pattern where healthcare roles remain highly demanding regardless of supportive climates (55). Having said that, current study finding on the reversal in direction between crude and adjusted estimates may reflect underlying confounding, whereby the association between medical-based work units and burnout became evident only after accounting for relevant covariates. This finding suggests a complex interplay of occupational factors influencing burnout risk and should be interpreted cautiously. Local studies similarly report elevated burnout among Malaysian doctors, nurses, and allied health professionals (56). The combination of high clinical workload, complexity of cases, and chronic staffing shortages creates sustained emotional demands, which may override the buffering role of organisational climate in the long term.

A recent study highlights the urgency of addressing burnout among healthcare workers (57). Ongoing research endeavours continue to shape our understanding, and results may shift with the evolution of research and the implementation of effective management strategies. Findings from our study show that the PSC as an organizational construct consistently remains a potent discriminating factor for burnout. It revealed a direct association between PSC and burnout at each time point of collected data without the presence of the JD-R model as the moderator. This is particularly distinct from previous similar research where most of them integrated the JD-R model to achieve similar research findings.

On the same note, our study support other research findings on the importance of supervisor and co-workers support as variables of interest in the development of burnout among healthcare workers in Malaysian hospital settings (58). There is interest among researchers in Malaysia to delve into the topic of PSC and its interaction with burnout (59,60) but the focus has not been on healthcare workers.

Implications for Malaysian healthcare leadership

This study’s temporal findings are particularly relevant to Malaysian nurse managers and hospital administrators, who shape frontline work environments. The short-term protective effect of PSC suggests that organisational actions policy reinforcement, communication improvements, leadership visibility may yield immediate benefits in reducing burnout risk. However, the diminishing nine-month effect highlights the need for sustained, institutionalised strategies rather than one-off initiatives.

Given Malaysia’s ongoing challenges with workforce retention, staffing pressures, and post-pandemic recovery, PSC should be considered a key indicator in organisational well-being strategies. The findings support integrating PSC into routine psychosocial risk assessments, leadership training, and Occupational Safety and Health (OSH) frameworks, in line with WHO recommendations for strengthening worker mental health systems (61).

Directions for future research

For healthcare workers, occupational burnout is a formidable threat, given the daily confrontations with highly stressful situations demanding significant expertise, knowledge, and both physical and mental aptitude. Their routine exposure to crisis scenarios, accidents, and tragedies can deeply impact their mental well-being, with frequent exposure to extreme suffering and death potentially leading to psychological exhaustion and trauma. Operating under time constraints in a challenging and often changing environment further compounds the stress. Therefore, the future research direction of PSC has great potential especially in Malaysia. Future studies should deepen understanding of the mechanisms and pathways through which PSC influences burnout among healthcare workers, particularly by examining how emotional demands, workload pressures, moral distress, and team climate mediate or modify this relationship. Comparative studies across primary care and hospital settings are also warranted, as these environments differ markedly in autonomy, job demands, resource availability, and supervisory structures factors that may shape how PSC is perceived and acted upon. In addition, exploring urban–rural disparities in PSC would provide valuable insight into how variations in leadership practices, staffing levels, and patient volumes influence organisational psychological safety across the Malaysian health system. Finally, future studies should adopt longer (≥2-year) multi-wave designs to better understand how PSC effects evolve or attenuate over time, addressing current gaps in knowledge on the stability and decay of organisational climate influences in healthcare settings. Such investigations will help clarify whether PSC’s influence is situational, structural, or both, and will provide more granular evidence for policy and practice.

Strengths and limitations

This study’s principal strength lies in its three-wave longitudinal design, which provides richer temporal insight than the predominantly cross-sectional or two-wave PSC studies. This allows clearer differentiation between short-term and longer-term organisational effects on burnout. The use of validated Malay-language instruments, consistent data collection procedures, and a healthcare workforce sample from a major tertiary hospital further enhance internal validity and contribute novel evidence from an underrepresented UMIC context.

However, the study has some limitations. The age of the dataset may raise concerns, although many structural pressures workload intensity, staffing constraints, and psychosocial hazards remain fundamentally unchanged in Malaysian hospitals, ensuring continued conceptual relevance. Attrition across study waves, the single-site setting, and the pre-determined eligibility criterion excluding healthcare workers with pre-existing mental health conditions may limit the generalisability of the findings. From a methodological perspective, formal sensitivity analyses using alternative model specifications, sample restrictions, or imputation methods were not performed; therefore, the potential influence of missing data on the findings cannot be entirely excluded. In addition, unmeasured factors such as emotional demands and leadership style may also have influenced burnout trajectories. These limitations highlight the need for expanded multi-site, multi-wave studies with more comprehensive analytical approaches in future research.

Conclusions

This multi-wave study demonstrates that PSC exerts a short-term protective effect against burnout among Malaysian healthcare workers, offering rare longitudinal evidence from a Southeast Asian healthcare setting. Despite the dataset’s age, the persistence of systemic workforce pressures ensures the ongoing relevance of these findings. Strengthening PSC remains an important organisational strategy for mitigating burnout and supporting the psychological well-being of healthcare workers within Malaysia’s evolving health system.

Acknowledgments

The authors would like to express their gratitude to all study participants from the University of Malaya Medical Centre (UMMC), Malaysia.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jphe.amegroups.com/article/view/10.21037/jphe-2026-1-0007/rc

Data Sharing Statement: Available at https://jphe.amegroups.com/article/view/10.21037/jphe-2026-1-0007/dss

Peer Review File: Available at https://jphe.amegroups.com/article/view/10.21037/jphe-2026-1-0007/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jphe.amegroups.com/article/view/10.21037/jphe-2026-1-0007/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Ethical approval for the study was secured from the University of Malaya Medical Centre Medical Ethics Committee (No. MEC 201311-0538), and all participants provided written informed consent, underscoring adherence to ethical research standards. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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