logo
Loading...
Quiet quitting during COVID-19: the role of psychological empowerment

Education

Quiet quitting during COVID-19: the role of psychological empowerment

M. Lu, A. A. Mamun, et al.

This study, conducted by Mingxiao Lu, Abdullah Al Mamun, Xuelin Chen, Qing Yang, and Mohammad Masukujjaman, delves into the quiet-quitting intentions of Chinese university lecturers during the challenges of the COVID-19 pandemic, uncovering key factors like work overload and pay-for-performance that influence job burnout and well-being.... show more
Introduction

The study addresses rising quiet-quitting intention (QQ)—doing only required work without extra effort—among Chinese university lecturers during COVID-19, a period marked by increased workload (e.g., shift to online teaching), emotional fatigue, and uncertainty. Grounded in Social Exchange Theory (SET), the research examines how work-related factors—work overload (WO), perceived career development opportunities (PC), perceived pay-for-performance (PP), affective organizational commitment (AC), and work conditions (WC)—influence job burnout (JB) and employee well-being (EW), which in turn affect QQ. The study also tests whether psychological empowerment (PE) moderates the relationships between JB/EW and QQ. The purpose is to identify key levers to reduce QQ by mitigating burnout and enhancing well-being among lecturers, thereby protecting teaching quality and organizational effectiveness.

Literature Review

The study is theoretically grounded in Social Exchange Theory (SET), which posits that workplace relationships are reciprocal exchanges where individuals seek to maximize rewards and minimize costs. Unfavorable exchanges (e.g., excessive demands, unfair rewards) disrupt reciprocity and can lead to negative attitudes and behaviors. The review defines key constructs: job burnout (exhaustion, cynicism, inefficacy), employee well-being (psychological well-being), work overload (excessive demands/time pressure), perceived career development opportunities (formal opportunities for growth), perceived pay-for-performance (alignment of pay with performance), affective organizational commitment (emotional attachment to organization), work conditions (job demands/resources; facilities and environment), quiet-quitting intention (limiting effort to job description), and psychological empowerment (meaning, competence, self-determination, impact). Hypotheses: H1A WO→+JB; H1B WO→−EW. H2A PC→−JB; H2B PC→+EW. H3A PP→−JB; H3B PP→+EW. H4A AC→−JB; H4B AC→+EW. H5A WC→−JB; H5B WC→+EW. H6 JB→+QQ. H7 EW→−QQ. Moderation: H8 PE moderates JB→QQ; H9 PE moderates EW→QQ. The review also references JD-R theory to frame work conditions as demands/resources and prior findings linking these factors to burnout, well-being, and turnover intentions.

Methodology

Design: Quantitative cross-sectional survey. Population: University lecturers in China. Sampling: Convenience sampling via WJX online platform. Data collection: September 12 to October 22, 2022. Final sample: 698 valid responses (48% male; majority aged 26–45; 65.5% public universities; 63.5% lecturers/senior lecturers; most with master’s degree; monthly income predominantly CNY 5,000–8,000). Measures: Established multi-item scales for WO, PC, PP, AC, WC, JB, EW, PE, and QQ; 5-point Likert (1=strongly disagree to 5=strongly agree). Translation/back-translation to Chinese; expert review for equivalence. Common method variance: Harman’s one-factor test (<50% variance by single factor) and full collinearity VIFs (<3.3) indicated no serious CMV or multicollinearity. Analysis: PLS-SEM using SmartPLS. Assessed reliability (Cronbach’s alpha, Dijkstra–Henseler’s rho, composite reliability) and convergent validity (AVE, loadings), discriminant validity (Fornell–Larcker, HTMT). Structural model tested path coefficients with bootstrapped CIs, t- and p-values; reported R² and f². Post-hoc analyses: Importance-Performance Map Analysis (IPMA) with QQ as target; Multi-Group Analysis (PLS-MGA) after Measurement Invariance of Composite Models (MICOM) to compare subgroups (gender, age, education, tenure, income). Ethical approval obtained; informed consent secured.

Key Findings

Measurement model: All constructs showed good reliability (Cronbach’s alpha ≥0.879) and composite reliability (≥0.912); AVE ≥0.674 confirmed convergent validity; HTMT <0.90 confirmed discriminant validity; full collinearity VIFs 1.145–2.719 below 3.3 threshold. Structural model fit: Adjusted R²: JB=0.319, EW=0.329, QQ=0.538. Effect sizes (f²): On QQ, JB=0.235, EW=0.170, PE=0.036. Key paths (Table 4): - JB antecedents: WO→JB β=0.254, t=6.847, p<0.001 (supported, H1A); PP→JB β=−0.136, t=3.038, p=0.001 (H3A supported); AC→JB β=−0.071, t=1.672, p=0.047 (H4A supported); WC→JB β=−0.264, t=5.906, p<0.001 (H5A supported); PC→JB β=−0.026, t=0.595, p=0.276 (H2A rejected). - EW antecedents: WO→EW β=−0.264, t=7.031, p<0.001 (H1B supported); PC→EW β=0.034, t=0.706, p=0.240 (H2B rejected); PP→EW β=0.088, t=1.969, p=0.019 (H3B supported); AC→EW β=0.098, t=2.075, p=0.024 (H4B supported); WC→EW β=0.280, t=6.062, p<0.001 (H5B supported). - Outcomes: JB→QQ β=0.394, t=12.321, p<0.001 (H6 supported); EW→QQ β=−0.333, t=11.185, p<0.001 (H7 supported). Moderation by PE (Table 6): PE×JB→QQ β=0.078, p=0.009 (H8 supported); PE×EW→QQ β=−0.059, p=0.037 (H9 supported). Direct PE→QQ β=−0.139, p<0.001. IPMA: JB had highest importance for predicting QQ; EW second-highest importance but low performance, suggesting managerial priority on improving EW. Multi-group analysis: Measurement invariance largely established (69/75 MICOM p>0.05). Differences observed: stronger PC→JB and PC→EW effects among younger (18–35) lecturers and those with ≤5 years tenure; females showed a stronger JB→QQ path than males; PC→JB stronger among lower-income (≤CNY 8000) respondents.

Discussion

Findings support the SET perspective: when lecturers face high demands (work overload) without commensurate resources, burnout increases and well-being declines, which elevates quiet-quitting intentions. Conversely, job resources—fair performance-based pay, affective organizational commitment, and favorable work conditions—mitigate burnout and enhance well-being, thereby reducing QQ. The strong positive link between JB and QQ and strong negative link between EW and QQ confirm that psychological states are central mechanisms linking work context to quiet quitting. Psychological empowerment significantly moderates these pathways, amplifying the positive JB→QQ association (burnout more strongly drives QQ when PE is higher) and amplifying the negative EW→QQ association (well-being more strongly reduces QQ when PE is higher). This suggests empowered lecturers translate their psychological states more directly into behavioral intentions—both adverse (under high burnout) and beneficial (under high well-being). Practically, reducing overload, improving work conditions, ensuring fair and transparent pay-for-performance, and fostering affective commitment can curb burnout and boost well-being, thereby lowering QQ. Enhancing psychological empowerment and authentic leadership can further leverage well-being to deter QQ and buffer its antecedents by strengthening lecturers’ sense of meaning, competence, autonomy, and impact.

Conclusion

The study develops and empirically validates a SET-based framework linking work demands/resources to burnout and well-being, which in turn shape quiet-quitting intentions among Chinese university lecturers during COVID-19, with psychological empowerment as a moderator. Work overload increases burnout and lowers well-being; pay-for-performance, affective commitment, and work conditions reduce burnout and increase well-being. Burnout elevates, and well-being reduces, QQ; psychological empowerment strengthens both relationships. These insights guide universities to prioritize managing workload, improving work conditions, strengthening fair performance-based rewards, and cultivating affective commitment and empowerment to reduce QQ. Future research should generalize beyond Chinese higher education, examine other sectors and developed-country contexts, and employ longitudinal designs to capture dynamics post-COVID-19.

Limitations

Cross-sectional design and convenience sampling of Chinese university lecturers limit causal inference and generalizability across contexts and sectors. The COVID-19 backdrop may constrain applicability as conditions evolve. The relative novelty and limited literature on quiet-quitting intention may introduce bias in construct operationalization. Future work should use longitudinal designs, test in different industries and developed-country settings, and expand the set of antecedents and mechanisms as the literature matures.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 22+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny