Heavy Workload, Not Presenteeism, Emerges as the Strongest Link to Quiet Quitting Among Hospital Staff

Quiet quitting — the quietly corrosive habit of showing up for work while withholding any effort beyond the bare minimum — has become one of the most talked-about phenomena in modern employment, and now one of the most detailed statistical portraits of it among healthcare workers suggests that the problem may be rooted less in individual motivation than in the sheer weight of the job itself. In a cross-sectional study published in Frontiers in Public Health, researchers surveyed 329 healthcare professionals at a single public hospital in Denizli, Türkiye, and used structural equation modeling to trace how workload, work satisfaction, change fatigue, and presenteeism intertwine to shape quiet quitting. Their central model explained 55.6 percent of the variance in quiet quitting scores, and one finding stood out with unusual consistency: workload was the strongest and most stable correlate across every model specification and every professional group examined.

The study, conducted between July and September 2025, recruited physicians, nurses, and other healthcare professionals who had worked at the hospital for at least one year. From 383 eligible staff, 329 completed the questionnaires — a response rate of 85.9 percent — yielding a final sample of 146 physicians, 117 nurses, and 66 other healthcare professionals. Participants were, on average, 33 years old, worked roughly 44 hours per week, and had accumulated about eight and a half years of healthcare experience. Each respondent filled out validated instruments measuring five constructs: the 11-item Workload Scale, the five-item Work Satisfaction Scale, the six-item Change Fatigue Scale, the Stanford Presenteeism Scale, and the seven-item Quiet Quitting Scale, all rated on five-point scales.

The theoretical scaffolding for the analysis came from two well-established frameworks in occupational psychology. Job Demands–Resources theory holds that workplace characteristics divide into demands, which require sustained physical or psychological effort and carry costs, and resources, which support wellbeing and motivation. Conservation of Resources theory adds that people strive to acquire, protect, and replenish valued resources such as time, energy, and emotional capacity, and that resource loss is especially painful when persistent demands leave no room for recovery. In this framing, workload operates as a central job demand, change fatigue reflects the strain of repeated organizational upheaval, and quiet quitting — limiting effort to formally required duties — can be read as an attempt to conserve what resources remain.

The statistical architecture was considerable. The researchers first confirmed the measurement properties of all five scales through confirmatory factor analysis, then estimated a simultaneous path model using composite scores, applying robust maximum likelihood estimation to handle departures from multivariate normality. Indirect effects were tested with non-parametric bootstrapping based on 5,000 resamples, with bias-corrected 95 percent confidence intervals. The five-factor measurement model fit the data acceptably, and checks for common method variance — a concern whenever all measures are self-reported on a single occasion — suggested it was unlikely to account for the observed associations: a single-factor model fit far worse, and the first unrotated component explained only 33.67 percent of the variance, below the conventional 50 percent warning threshold.

When the structural model was estimated, workload emerged as the dominant force. Its standardized association with quiet quitting was β = 0.589 (p < 0.001), and its total effect — direct plus indirect — was the largest in the entire model at β = 0.612. In the bivariate correlations, workload and quiet quitting were strongly linked at r = 0.679. Work satisfaction, by contrast, showed a small but statistically significant negative association with quiet quitting (β = −0.097, p = 0.001), consistent with its role as a protective factor, though the authors caution that this modest magnitude means satisfaction’s buffering role should not be overstated. Workload was also negatively associated with work satisfaction (β = −0.242), hinting at a pathway by which heavy demands erode the very attitudes that guard against withdrawal.

Change fatigue told a subtler story. It was significantly associated with presenteeism (β = 0.539, p < 0.001) and, more weakly, with workload (β = 0.185, p = 0.011), but its direct path to quiet quitting was not statistically significant. Instead, change fatigue reached quiet quitting indirectly: through presenteeism (β = 0.125), through workload (β = 0.109), and through the sequential chain of workload followed by work satisfaction (β = 0.004). Its total indirect effect was β = 0.239 and its total effect β = 0.383 (p < 0.001). In other words, the emotional exhaustion produced by frequent organizational change appears to feed quiet quitting primarily by inflating perceived workload and pushing staff into a state of being physically present but psychologically detached.

Presenteeism itself proved the study’s most fragile finding. Its direct association with quiet quitting was positive but marginal — β = 0.233, p = 0.039 — yet the bootstrap confidence interval (B = 0.353, 95 percent CI [−0.008, 0.680]) included zero, failing the study’s strict significance criterion. Sensitivity analyses deepened the doubt: when 15 multivariate outliers were excluded, the coefficient collapsed to β = 0.076 and lost statistical significance entirely. Inspection revealed that those 15 cases were the participants with the lowest quiet quitting scores, so removing them squeezed the outcome’s range in a distribution already clustered near the ceiling. The authors conclude that this association requires replication before presenteeism can be considered a firmly established correlate of quiet quitting in this population.

The descriptive statistics carried their own headline. The mean quiet quitting score was 4.41 on a 1-to-5 scale, with a median of 4.57 and a pronounced negative skew — a distribution pressed hard against the upper end of the range. Because no validated cutoff points exist for this instrument, the researchers declined to label scores as low, moderate, or high, interpreting them only descriptively. Still, the combination of an elevated mean and workload’s dominant total effect suggests that workplace demands may help explain why quiet quitting scores ran so high in this sample, though the three-month collection window and single-institution setting limit how far that observation can be generalized.

A multigroup analysis revealed that the relationships did not operate uniformly across professions. Constraining the structural paths to be equal across physicians, nurses, and other professionals substantially worsened model fit, and the non-invariance was confined to pathways involving change fatigue and presenteeism. The workload–quiet quitting association, however, was statistically equivalent across all three groups and significant in each (β = 0.598 for physicians, 0.711 for nurses, 0.346 for other professionals), marking it as a common correlate regardless of role. Presenteeism was associated with quiet quitting among nurses and other professionals but not among physicians, while change fatigue showed a significant direct link among physicians and other professionals but not among nurses. Given the small size of the third group and the absence of formal measurement invariance testing, the authors treat these group-specific results as exploratory.

The study’s limitations frame what its findings can and cannot mean. Its cross-sectional design precludes causal inference — professionals who have already psychologically withdrawn may perceive their workload more negatively, and reverse or reciprocal relationships fit the data equally well. The single public hospital in Türkiye limits generalizability, voluntary participation raises the possibility of self-selection bias, and the near-ceiling distribution of quiet quitting scores may have attenuated the detectable strength of some associations. Monte Carlo power analysis showed the study was well powered for its principal indirect associations but limited for the two smallest pathways involving work satisfaction, and the average variance extracted for presenteeism and work satisfaction fell below the conventional 0.50 threshold. The authors also frame quiet quitting itself as a contested construct — one that may represent boundary-setting and work–life protection rather than simple disengagement. Their overall reading is that the pattern observed, with quiet quitting most strongly tied to workload and cumulative change strain, is more consistent with a response to working conditions than with an individual failing, and that manageable workload distribution and organizational support during periods of change are the most promising targets for the longitudinal, multicenter studies needed to test whether targeted interventions can actually reduce quiet quitting.

Subject of Research: Associations of workload, work satisfaction, change fatigue, and presenteeism with quiet quitting among healthcare professionals

Article Title: Associations of workload, work satisfaction, change fatigue, and presenteeism with quiet quitting among healthcare professionals: a structural equation modeling study

Article References: Yetim, B., Selvi Sarıgül, S., Biçer, İ., & Çelik, Y. (2026). Associations of workload, work satisfaction, change fatigue, and presenteeism with quiet quitting among healthcare professionals: a structural equation modeling study. Frontiers in Public Health, 14, Article 1936291. https://doi.org/10.3389/fpubh.2026.1936291

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1936291

Keywords: quiet quitting, healthcare professionals, workload, work satisfaction, change fatigue, presenteeism, structural equation modeling, occupational health, nurses, physicians, cross-sectional study, Türkiye