COVID-19’s disruptions to daily life and pandemic fatigue during the pandemic in Chinese people: a moderated mediation effect of perceived stress and social support

Jie Zhuang; Qunhong Wu; Hongjiao Li; Xiyue Wang; Runzi Gu; Huan Liu; Baohua Liu; Yuexia Gao; Miaomiao Zhao

doi:10.1186/s12889-025-24261-3

. 2025 Aug 22;25:2892. doi: 10.1186/s12889-025-24261-3

COVID-19’s disruptions to daily life and pandemic fatigue during the pandemic in Chinese people: a moderated mediation effect of perceived stress and social support

Jie Zhuang ^1,^#, Qunhong Wu ^1,^2,^3,^#, Hongjiao Li ^1,^#, Xiyue Wang ¹, Runzi Gu ¹, Huan Liu ³, Baohua Liu ⁴, Yuexia Gao ^1,^2,^✉, Miaomiao Zhao ^1,^2,^✉

PMCID: PMC12372392 PMID: 40847300

Abstract

Background

People experienced significant disruptions in their daily lives due to COVID-19, leading to pandemic fatigue, however the underlying mechanisms have rarely been investigated. This study explored the relationship between COVID-19’s disruptions to daily life and pandemic fatigue by examining the potential role of perceived stress and perceived social support.

Methods

A cross-sectional questionnaire survey via the Wenjuanxing online platform using a convenience sampling approach was conducted from April to May 2022 in Shanghai Municipality, Jiangsu Province, and Zhejiang Province, China. Of the 2112 initial participants, 88 invalid questionnaires were excluded due to missing key variables or logical errors, yielding 2024 valid samples included (efficiency rate of 95.8%). Moderated mediation analysis was carried out applying Hayes’ PROCESS macro.

Results

COVID-19’s disruptions to daily life was positively associated with pandemic fatigue (β = 0.319, p < 0.001), while perceived stress partially mediated this relationship (β = 0.107, 95% CI = [0.088, 0.128]), accounting for 33.5% of the total effect. Perceived social support moderated the direct effect of COVID-19’s disruptions on pandemic fatigue (β= -0.113, p < 0.001) and the indirect effect of perceived stress by buffering its effect on pandemic fatigue (β= -0.102, p < 0.001), thus the moderated mediation effect was established.

Conclusion

This study revealed a plausible mechanism that explains pandemic fatigue during the COVID-19 through understanding the role of perceived stress and social support, providing theoretical and practical inputs for formulating intervention strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-24261-3.

Keywords: COVID-19’s disruptions to daily life, Perceived stress, Perceived social support, Pandemic fatigue

Introduction

The novel coronavirus pneumonia (COVID-19) outbreak constitutes an unprecedented global public health crisis, exerting profound implications on people worldwide for an extended period. In response, countries across the globe have formulated public health measures. However, the constant fluctuations in infection rates, intermittent lockdowns, and ever-changing guidelines have taken a significant toll on people’s well-being [1]. The prolonged duration of the pandemic, coupled with the uncertainty surrounding its resolution, has left people exhausted, resulting in pandemic fatigue [2, 3]. The World Health Organization (WHO) defines pandemic fatigue as distress arising from sustained and unresolved adversity in people’s lives, emerging gradually over time and influenced by a number of emotions, experiences and perceptions [4]. Pandemic fatigue manifests as a state of exhaustion and demotivation to engage in protective behaviors and information seeking, alongside decreased trust in authorities, reflecting the cumulative burden of navigating the challenges imposed by the pandemic [4–6]. Pandemic fatigue emerges as a consequence of prolonged exposure to information overload and behavioral restrictions during a pandemic [7, 8]. Studies from various regions across Europe [9, 10], North America [11], South America [12], Oceania [13], and Asia [14, 15] have documented the occurrence of pandemic fatigue, underscoring its global nature. In China, studies found that nearly half of the population reported experiencing pandemic fatigue during the COVID-19 [16, 17].

Pandemic fatigue imposes substantial adverse consequences on the population, encompassing anxiety, depression, sleep disorders, obsessive-compulsive tendencies, helplessness, hopelessness, resentment, and erosion of subjective well-being [18–21]. More critically, pandemic fatigue diminishes adherence to recommended health-protective behaviors such as social distancing and mask-wearing [22], that may exacerbate infection levels and complicate epidemic prevention and control efforts. While the pandemic phase of COVID-19 has officially concluded, its impact on global societies persists. The risk of another pandemic emergency in the coming decades is not only ever-present but also likely to escalate due to ongoing urbanization, climate change, and global interconnectedness [23]. Thus, deepening our understanding of the triggering and buffering mechanisms underlying pandemic fatigue is crucial for formulating effective policy responses to prepare for potential future epidemics.

COVID-19’s disruptions to daily life refer to the changes and disturbances in individuals’ normal routines, activities, work, and social interactions of individuals due to the COVID-19 pandemic and associated lockdown measures [24–26]. These disruptions encompass a wide range of daily life domains, including unplanned separation or cohabitation of family members, school closure, remote work, job instability, income loss, delays in routine medical services, and limited social interaction [27–30]. Such frustrating disruptions to daily life can leave individuals feeling exhausted, thereby contributing to the emergence of pandemic fatigue [31, 32]. However, the specific mechanisms by which these disruptions shape pandemic fatigue remain underexplored, especially with respect to perceived stress as a mediator and perceived social support as a moderator. To address this gap, the present study aims to test a moderated mediation model to clarify how perceived stress mediates the relationship between COVID-19 disruptions and pandemic fatigue, and how perceived social support moderates this pathway. By illuminating these mechanisms, we provide a theoretical foundation for precision interventions that simultaneously reduce stress and enhance social resources. Given the enduring psychological toll of COVID-19 and the growing risk of future public health emergencies, mapping these processes is an urgent for developing timely, evidence-based responses strategies. Beyond deepening our understanding of pandemic fatigue mechanisms, this research offers actionable insights to inform public health strategies in future crises.

COVID-19’s disruptions to daily life and pandemic fatigue

As indicated by its conceptual interpretation, pandemic fatigue occurs as a consequence of the disruptions in the usual routines and activities of an individual of daily living due to various measures implemented to decrease virus transmission [21, 31]. The COVID-19 pandemic has triggered unprecedented disruptions to everyday life, altering how people live, work, study, and interact [33, 34]. Lockdowns and movement restrictions forced changes in health-related behaviors, as closed gyms and reduced outdoor activity disrupted exercise routines, while supply-chain disruptions and financial strain drove a shift to shelf-stable processed foods [35, 36]. The closure of cinemas, theaters, and sports venues, coupled with travel restrictions that dashed vacation plans, severely constrained people’s access to leisure activities. In addition, remote work transition amidst COVID-19 blurred work-life boundaries, leading to overworking and increased work-related stress [37], while widespread job insecurity, repeated job-search rejections and income loss fostered a pervasive sense of hopelessness and amplified emotional distress [38]. Furthermore, the strain on medical resources amid the pandemic has resulted in delays to routine medical services [29, 39]. Over time, the loss of these familiar coping mechanisms left individuals grappling with pent-up tension and a growing sense of monotony, gradually eroding their motivation to sustain pandemic-related resilience, ultimately leading to pandemic fatigue. Consistent with this logic, a population-based, cross-sectional study in Hong Kong identified the disruptions to daily life caused by COVID-19 as a significant predictor of pandemic fatigue [32].

Therefore, this study proposes hypothesis H1: COVID-19’s disruptions to daily life during the pandemic are positively related to pandemic fatigue.

The mediation effect of perceived stress

Perceived stress refers to the subjective appraisal of being overwhelmed by environmental demands that exceed one’s coping abilities [40]. The Stressor-Strain-Outcome (SSO) model established the interrelationships among stressors, strain, and behavioral outcomes, positioning perceived stress as an intermediary that links stressors to psychological and behavioral consequences [41]. Lazarus and Folkman’s Stress and Coping Theory [42] further contextualize the pathway that perceived stress arises from one’s appraisal of a stressful encounter and through repeated reappraisal, individuals adjust their emotional responses and coping strategies, thereby influencing potential coping outcomes. This theory conceptualizes perceived stress as a dynamic cognitive process reflecting individual assessment, illustrating how cognitive appraisal shapes perceived stress in the face of stressful events, and how perceived stress, in turn, influences subsequent outcomes [43].

COVID-19’s disruptions to daily life serve as prototypical environmental stressors [44]. As unprecedented and impactful events, these disruptions are likely to be perceived as threatening and unmanageable, directly contributing to perceived stress. In turn, perceived stress impairs cognitive reappraisal and emotional regulation, thereby shaping subsequent emotional and behavioral responses. Indeed, empirical studies have linked COVID-19 related daily life disruptions to elevated levels of perceived stress [45, 46]. Notably, prior research has further identified perceived stress as a mediator in the relationship between stressors and pandemic fatigue [47, 48].

Therefore, this study proposes hypothesis H2: Perceived stress mediates the relationship between COVID-19’s disruptions to daily life and pandemic fatigue.

The moderating effect of social support

Perceived social support refers to individuals’ subjective perceptions of available and adequate social support, encompassing feelings of being loved, valued, and connected to a supportive network [49]. Stress and Coping Theory posits that stress arises from the interaction between individuals and their environment, highlighting the pivotal role of social perceived support in shaping stress appraisals and coping strategies [42]. Building on this foundation, the Stress-Buffering Hypothesis further specify perceived social support mitigates stress-related outcomes by attenuating or reappraising stressful events and fostering adaptive emotional responses and coping strategy [50]. Perceived social support can intervene in the appraisal of stressful events, preventing individuals from perceiving potential stressors as threatening to their physical and mental well-being when adequate social support is available. Conversely, when individuals perceive stressors as threatening, perceived social support can facilitate a reappraisal of these events, inhibit negative psychological responses, and promote adaptive adjustments to mitigate the adverse consequences of stress. This theoretical framework provides a theoretical basis for understanding how perceived social support moderates the effect of COVID-19’s disruptions to daily life on pandemic fatigue.

Perceived social support acts as a resource-reservoir buffer [51, 52] that mitigates the depletion of psychological resources like emotional energy and cognitive capacity caused by COVID-19 ’s daily-life disruptions, thereby dampening the direct psychological and behavioral toll of stressors. Numerous studies have found that social support from families, friends and communities did indeed act as a buffer, alleviating the negative impact caused by social interactions restricted, health and financial uncertainties, remote work, and online learning during COVID-19 pandemic [53–56]. This thereby reduced perceived stress and pandemic fatigue triggered by COVID-19’s disruptions to daily life. Additionally, high levels of perceived social support help to formulate positive stress reappraisal and adaptive responses, facilitating constructive coping strategies, which weaken the link between perceived stress and pandemic fatigue. Although limited research has examined the moderating role of perceived social support in the association between COVID-19 disruptions to daily life and pandemic fatigue, indirect evidence for such moderating role could be drawn from broader empirical studies documenting its moderating effect in stressful life events and psychological and behavioral outcome [57, 58].

Therefore, this study proposes H3a-H3c:

H3a: Perceived social support may moderate the relationship between COVID-19’s disruptions to daily life and pandemic fatigue.

H3b: Perceived social support may moderate the relationship between COVID-19’s disruptions to daily life and perceived stress.

H3c: Perceived social support may moderate the relationship between perceived stress and pandemic fatigue.

The present study

This study systematically integrates the SSO model [41], the Stress and Coping Theory [42] and the Stress-Buffering Hypothesis [50] to construct a theoretical framework for examining the mechanisms linking COVID-19’s disruptions to daily life with pandemic fatigue. It focuses on the mediating role of perceived stress and the moderated role of perceived social support (Fig. 1). We hypothesize that COVID-19’s disruptions to daily life directly exacerbate pandemic fatigue (H1) and indirectly do so through perceived stress as a mediator (H2). Moreover, we propose that perceived social support moderates this pathway at multiple stages: it moderates the association between COVID-19’s disruptions to daily life and pandemic fatigue (H3a), the association between COVID-19’s disruptions to daily life and perceived stress (H3b), and the association between perceived stress and pandemic fatigue (H3c).

Fig. 1 — The proposed moderated mediation model

Methods

Participants and procedure

This is a cross-sectional questionnaire survey conducted from April to May of 2022 in Shanghai Municipality, Jiangsu Province, and Zhejiang Province, China. The three regions are in the hinterland of the Yangtze River Delta (YRD) that implement the integrated development strategy in the economy, industry, infrastructure, environment, and public services. During the pandemic, the three regions saw rapid cross-regional disease transmission and shared similar and coordinated pandemic prevention and control policies. In 2022, the permanent resident population of Shanghai, Jiangsu and Zhejiang was 24.75 million, 85.15 million, and 65.77 million, respectively; the per capita GDP of Shanghai, Jiangsu and Zhejiang was 179.91 thousand CNY, 144.39 thousand CNY, and 118.50 thousand CNY, respectively [59].

To ensure the timeliness and feasibility of the survey, a convenience sampling approach was employed via the sample service function of the Wenjuanxing platform (http://www.wjx.cn). Adults aged 18 years or older residing in the three regions and demonstrating basic reading and comprehension proficiency were eligible for participation in this study. Participants were informed of the study objectives, procedures, and the nature of anonymously and voluntary before the survey. A total of 2,112 participants were involved in the survey. After data cleaning, 88 questionnaires with omissions of key study variables or logical errors were excluded, resulting in 2,024 participants being included in the present study. According to Preacher [60], the bootstrapping method effectively enhances statistical power even for small samples below 1,000 by resampling the data to approximate the sampling distribution of indirect effects. Given this, the sample size used in our study appears to have adequate power.

Measures

COVID-19’s disruptions to daily life

The Coronavirus Impact Scale (CIS) designed to measure the negative change in life under the coronavirus pandemic [61] was used to measure the COVID-19’s disruptions to daily life. The original question in the scale was “Rate how much the coronavirus pandemic has changed your life in each of the following ways”. To focus on “disruptions” (i.e., negative changes) in this study, the question was revised to “Rate how much the coronavirus pandemic has negatively disrupted your life in each of the following ways”. In addition, items in the scale have also been revised according to the specific life situations of Chinese people during the COVID-19 epidemic. The revised scale consists of 12 items such as daily routines, social interaction, family income, learning and education training playing, food access, routine medical care access, mental health service access, family or non-family support access, stress or discord in family relationships and so on. Each item was scored on a 5-point Likert scale to rate the degree of daily life disruption caused by COVID-19 (from 0 = None to 4 = Very severe), with a higher total score indicating a larger disruption in daily life caused by COVID-19. Confirmatory factor analysis showed the scale yield a single factor structure( χ²/df = 4.72, p < 0.001, CFI = 0.958 ,TLI = 0.904, SRMR = 0.082, RMSEA = 0.018). The Cronbach’s α of the scale was 0.913.

Pandemic fatigue

Pandemic fatigue was measured by the Pandemic Fatigue Scale (PFS) [8]. The PFS consists of six items divided into two constructs of behavioral fatigue (e.g., “I am losing my spirit to fight against COVID-19”) and information fatigue (e.g., “I am sick of hearing about COVID-19”), operationalizing the theoretical construct of reduced motivation and emotional weariness to the pandemic. Participants responded to these items using a 7-point Likert scale (from 1 = Strongly disagree to 7 = Strongly agree). A higher total score reflected a greater pandemic fatigue. The Chinese version of PFS has been used and verified. The PFS has been applied in studies across diverse cultural contexts including Chinese and demonstrated good reliability and validity [5, 9, 14, 16]. In the present study, confirmatory factor analysis showed the two-dimensional scale had a goodness of fit index (χ²/df = 4.87, p < 0.001, CFI = 0.988, TLI = 0.978, SRMR = 0.022, RMSEA = 0.080), and the Cronbach’s α of the scale was 0.919.

Perceived stress

Perceived stress was assessed using the Perceived Stress Scale (PSS). The PSS is a self-reported scale designed to measure the degree to which situations in one’s life are appraised as stressful [40, 62], ensuring it captured the theoretical construction of cognitive appraisal of stressor. The PSS consists of 10 items for negative and positive subscales scored on a 5-point Likert scale (from 0 = Never to 4 = Always). The total PSS scores ranged from 0 to 40, with higher scores indicating higher perceived stress. The internal consistency and structural validity of the Chinese version of PSS have been validated in prior research [63]. In the present study, confirmatory factor analysis showed the two-dimensional scale had a goodness of fit index (χ²/df = 3.49, p < 0.001, CFI = 0.901, TLI = 0.863, SRMR = 0.068, RMSEA = 0.013) and the Cronbach’s α of the scale was 0.842.

Perceived social support

The Multidimensional Scale of Perceived Social Support (MSPSS) was used to assesses individual’s perceived level of social support from family, friends, and significant others [64]. The MSPSS consistent with the Stress-Buffering Hypothesis [50], which emphasizes subjective perceptions of available resources. The MSPSS consists of 12 items scored on a 7-point Likert scale (from 1 = Strongly disagree to 7 = Strongly agree). The higher the total score, the higher the perceived social support of the individuals. The Chinese version of MSPSS had been proved good reliability and validity [65]. In the present study, confirmatory factor analysis showed a goodness of fit index on a two-factor structure (family vs. nonfamily, χ²/df = 4.61, p < 0.001, CFI = 0.896 TLI = 0.906, SRMR = 0.056, RMSEA = 0.031) and the Cronbach’s α of the scale was 0.905.

Statistical analysis

Data analysis was performed using IBM SPSS version 25.0. Descriptive statistics, including mean(M), standard deviation (SD), frequency distribution, and percentage were calculated for describing the participants’ socio-demographic characteristics. An independent t-test was used to compare the scores of pandemic fatigue across different levels of socio-demographic characteristics.

Prior to performing the main analysis, Harman’s single factor test and variance inflation factors were used to test for common method bias and multi-collinearity of the study variables. If the maximum explanation rate of the first factor is less than 50% [66] and the variance inflation factors (VIF) of the study variable is less than 5 [67], the above issues can be ruled out.

Pearson correlation coefficient was used to examine the bivariate correlations between study variables. Model 4 in the SPSS PROCESS macro was used to test the mediation effect and Model 59 was used to test the moderated mediation effect. The bias-corrected bootstrapping method with 5,000 resamples was employed to test the significance of the effects, with a 95% confidence interval (CI) that does not contain 0 indicating a significant effect. The Johnson-Neyman (J-N) technique was used to determine within which range of values of moderator the simple slope was statistically significant [68]. That is, when the moderator is continuous, the range in moderator for which the influence of the independent variable on the dependent variable is significant. In addition, in all models, sociodemographic characteristics, including age, gender, and marital status, that were significantly associated with pandemic fatigue were included as control variables, and all study variables were standardized.

Results

Basic characteristics and pandemic fatigue

In total, 2,112 participants were involved in the survey, and 2,024 effectively completed it, resulting in an effective response rate of 95.8%. The socio-demographic characteristics and the scores of pandemic fatigue were shown in Table 1. Of the participants, 1,059 (52.3%) were males and 965 (47.7%) were female. The majority of participants (84.7%) were under 45 years of age, with a mean age of 32.27 (SD = 10.85). Most participants (54.5%) were married. Over two-thirds resided in urban areas (71.2%) and had a bachelor’s degree or above education (66.9%). Additionally, half of participants (50.1%) reported an annual household income below 120,000 CNY. Independent t-test indicated that male, young, and unmarried participants exhibited significantly higher level of pandemic fatigue.

Table 1.

Sociodemographic characteristics and pandemic fatigue

Variables		n (%)	Pandemic fatigue (M ± SD)	P
Gender	Male	1,059 (52.3)	20.91 ± 8.549	< 0.001
	Female	965 (47.7)	19.54 ± 7.830
Age(years)	< 45	1,714 (84.7)	20.54 ± 8.374	< 0.001
	≥ 45	310 (15.3)	18.69 ± 7.276
Marital status	Married	1,104 (54.5)	19.82 ± 8.261	< 0.01
	Others	920 (45.5)	20.78 ± 8.189
Education level	Junior college or below	669 (33.1)	20.10 ± 8.534	0.554
	Bachelor or above	1,355 (66.9)	20.33 ± 8.094
Residence	Rural	583 (28.8)	20.10 ± 8.267	0.592
	Urban	1,441 (71.2)	20.32 ± 8.232
Annual household income (CNY)	< 120,000	1,015 (50.1)	20.39 ± 8.285	0.461
	≥ 120,000	1,009 (49.9)	20.12 ± 8.197

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Descriptive analysis of COVID-19’s disruptions to daily life

Figure 2 presents the distribution of participants’ responses regarding the severity of COVID-19 related life disruptions across 12 specific daily life domains. To further illustrate the functional implications of COVID-19-related disruptions, we categorized “Moderate,” “Severe,” and “Very severe” responses as “Moderate and above” to quantify the proportion of participants experiencing significant disruptions in each domain. Results showed that going outdoors and traveling was the most severely affected, with 92.9% of participants reporting moderate or above disruption, followed by daily routines (91.3%). Moreover, participants’ learning and education training plans (87.9%) and social interaction (86.0%) were also disrupted by COVID-19 significantly. On the contrary, the lowest rates of significant disruption were observed in family relationship (57.3%) and mental health service access (56.9%), though these still affected over half of the participants.

Fig. 2 — Distribution of participants reporting COVID-19 disruptions in specific daily life domains by severity

Testing for common method bias and multi-collinearity

Harman’s single factor test revealed 7 factors with eigenvalues greater than 1, and the first factor explained 22.74% (< 50%) of the total variances, indicating that there was no serious common method bias. In addition, collinearity diagnostic showed that the VIFs of the four study variables were below the recommended threshold of 5, suggesting that multicollinearity was not a concern for the data.

Bivariate correlations analysis

Table 2 presented the M, SD, and Pearson correlation coefficients for the four study variables. COVID-19’s disruptions to daily life was significantly positively correlated with perceived stress (r = 0.351, p < 0.001) and pandemic fatigue (r = 0.326, p < 0.001). In addition, perceived stress was significantly negatively correlated with perceived social support (r= -0.071, p < 0.01), while was significantly positively correlated with pandemic fatigue (r = 0.380, p < 0.001). Finally, perceived social support was significantly negatively correlated with pandemic fatigue (r = -0.210, p < 0.001).

Table 2.

Descriptive statistics and pearson correlations of the study variables

Variable	M	SD	1	2	3	4
1. COVID-19’s disruptions to daily life	27.15	9.185	1
2. Perceived stress	15.45	5.799	0.351^***	1
3. Perceived social support	50.76	11.666	-0.028	-0.071^**	1
4. Pandemic fatigue	20.26	8.240	0.326^***	0.380^***	-0.210^***	1

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M = mean, SD = standard deviation

^** p < 0.01, ^***p < 0.001

Testing for the mediation effect

The results of the simple mediation effect were presented in Table 3. COVID-19’s disruptions to daily life was positively associated with pandemic fatigue (β = 0.319, p < 0.001), supporting hypothesis H1. Then, COVID-19’s disruptions to daily life was positively associated with perceived stress (β = 0.353, p < 0.001), which in turn, was positively associated with pandemic fatigue (β = 0.303, p < 0.001), thus supporting hypothesis H2. In addition, perceived stress partially mediated the relationship between the COVID-19’s disruptions to daily life and pandemic fatigue (β = 0.212, p < 0.001). Bias-corrected bootstrapping test indicated that the indirect effect was significant (β = 0.107, 95% CI = [0.088, 0.128]), accounting for 33.5% of the total effect.

Table 3.

The mediation effect of the COVID-19’s disruptions to daily life on pandemic fatigue

	Model 1 (Pandemic fatigue)		Model 2 (Perceived stress)		Model 3 (Pandemic fatigue)
	β	t	β	t	β	t
Gender	0.057	2.672^**	-0.037	-1.754	0.068	3.342^**
Age	-0.015	-0.657	-0.024	-1.107	-0.007	-0.343
Marital status	-0.065	-2.892^**	-0.119	-5.402^***	-0.029	-1.335
COVID-19’s disruptions to daily life	0.319	14.989^***	0.353	16.884^***	0.212	9.768^***
Perceived stress					0.303	14.001^***

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^**p < 0.01, ^***p < 0.001

Testing for the moderated mediation effect

The moderated mediation analysis (Supplementary Table S1) revealed that perceived social support did not significantly moderate the association between COVID-19’s disruptions to daily life and perceived stress (β= -0.017, p = 0.266), leading to the rejection of hypothesis H3b. By contrast, perceived social support moderated the association between COVID-19’s disruptions to daily life and pandemic fatigue (β= -0.113, p < 0.001), and the association between perceived stress and pandemic fatigue (β= -0.102, p < 0.001), thus providing support for hypothesis H3a and H3c.

Bias-corrected bootstrapping method was further used to test for the conditional direct and indirect effects of COVID-19’s disruptions to daily life on pandemic fatigue at values of perceived social support. As shown in Table 4, the direct effect of COVID-19’s disruptions to daily life on pandemic fatigue was significant when perceived social support for individuals was low (β = 0.258, 95% CI = [0.212, 0.303]), medium (β = 0.145, 95% CI = [0.103, 0.187]), while was not significant when perceived social support was high (β = 0.032, 95% CI= [-0.026, 0.089]). Moreover, the indirect effect of COVID-19’s disruptions to daily life and pandemic fatigue through perceived stress was significant at three levels of social supports; however, the effect was strongest at low levels of perceived social support (β = 0.139, 95% CI = [0.111, 0.170]), weaker at medium levels of perceived social support (β = 0.098, 95% CI = [0.079, 0.119]) and weakest at high levels of perceived social support (β = 0.060, 95% CI = [0.036,0.086]). These findings suggested that perceived social support not only moderated the direct effect of COVID-19’s disruptions to daily life on pandemic fatigue but also moderated the indirect effect of perceived stress by buffering its effect on pandemic fatigue, and a moderated mediation model was established.

Table 4.

Conditional direct and indirect effects of COVID-19’s disruptions to daily life on pandemic fatigue at values of perceived social support

	Perceived social support	Effect	SE	LLCI	ULCI
Conditional direct effects	Low (M-1SD)	0.258	0.023	0.212	0.303
	Medium (M)	0.145	0.021	0.103	0.187
	High (M + 1SD)	0.032	0.029	-0.026	0.089
Conditional indirect effects	Low (M-1SD)	0.139	0.015	0.111	0.170
	Medium (M)	0.098	0.010	0.079	0.119
	High (M + 1SD)	0.060	0.013	0.036	0.086

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The J-N test was performed to further validate the moderating effect, and results were depicted in Fig. 3. As observed in Fig. 3A, the positive effect of COVID-19’s disruptions to daily life on pandemic fatigue tended to decrease gradually as perceived social support increased and eventually reversed it into a negative effect. Specifically, there were two regions where the effect of COVID-19’s disruptions to daily life on pandemic fatigue was significant (within a confidence band that did not contain zero): (1) when standardized scores of perceived social support < 0.81 (equivalent to a raw score of 60.17), COVID-19’s disruptions to daily life was positively related to pandemic fatigue; and (2) when standardized scores of perceived social support > 2.02 (equivalent to a raw score of 74.29), COVID-19’s disruptions to daily life was negatively related to pandemic fatigue. No significant effect was found when the standardized scores of perceived social supports fell between 0.81 and 2.02 (within a confidence ban that contained zero). In addition, Fig. 3B showed that the positive effect of perceived stress on pandemic fatigue was significant when the standardized scores of perceived social supports were < 1.99 (equivalent to a raw score of 73.96), while was not significant when the standardized scores of perceived social supports were ≥ 1.99.

Discussion

This study is the first to construct a moderated mediation model to elucidate how COVID-19 disruptions to daily life influence pandemic fatigue through perceived stress and how the effects of COVID-19’s disruptions to daily life and perceived stress on pandemic fatigue vary across different levels of perceived social support. Results revealed that COVID-19’s disruptions to daily life were positively associated with pandemic fatigue, this association was partially mediated by perceived stress. Perceived social support moderated both the direct effect of COVID-19’s disruptions on pandemic fatigue and the indirect effect via perceived stress, though it did not moderate the link between disruptions and perceived stress. The findings are expected to enhance our understanding of the mechanisms driving the formation and development of pandemic fatigue and provide a valuable insight into how to prevent pandemic fatigue and promote individual mental health in future public health emergencies of a similar nature.

The positive association between daily life disruptions and pandemic fatigue, as well as the mediating role of perceived stress, confirm hypotheses H1 and H2. These findings align with the SSO model and Lazarus and Folkman’s Stress and Coping Theory, highlighting perceived stress as a cognitive appraisal of stressful situations that played a critical mediating link in the pathway connecting COVID-19’s disruptions to daily life to pandemic fatigue. Conservation of Resources (COR) model indicates that loss of resources, or threat of such loss, is a crucial variable, predicting psychological distress, and will lead to investing more resources, making those already lacking in resources even more vulnerable to loss spirals [69]. According to it, pandemic-related disruptions impose multidimensional environmental challenges threaten resource loss, forcing constant reappraisal of threats and increasing cognitive load, which triggers perceived stress [70]. Prolonged stress then depletes internal resources needed for emotional regulation, creating a vicious cycle of resource depletion that culminates in emotional and behavioral exhaustion [71, 72].

In the present study, the domain-specific patterns of COVID-19’s disruptions to daily life revealed critical insights into the practical impacts of the pandemic. The most severely affected domains were going outdoors/traveling and daily routines (over 90% reporting moderate or above disruptions), aligning with mobility restrictions that destabilized habitual patterns and accumulated stress [73]. The second tier of disruption involved learning/education training (87.9%) and social interaction (86.0%), which reflect the wide educational institution closures and abrupt shift to mandator on-line learning [74, 75] and the toll of physical distancing on social life [76]. Economically, family income/economy and work/employment also suffered heavily, mirroring the job instability and financial strain documented in prior studies [37, 38]. In addition, mental health service access and family relationship stress showed relatively lower but still notable disruptions. These patterns highlight that high-impact domains are key stress sources, emphasizing tailored interventions such as flexible mobility policies, restoring routines, facilitating safe social interactions, and optimizing online education. Such measures would alleviate practical disruptions and interrupt stress accumulation, reducing pandemic fatigue risk.

This study found that perceived social support moderated the relationship between COVID-19’s disruptions to daily life and pandemic fatigue, and the relationship between perceived stress and pandemic fatigue, corroborating Hypothesis H3a and H3c. However, contrary to Hypothesis H3b, our data did not support a moderating role of social support on the relationship between COVID-19 disruptions and perceived stress. These findings underscore that the protective role of perceived social support is stage-dependent in the stressor-stress-outcome process: while it cannot prevent individuals from perceiving disruptions as stressful, it significantly mitigates the downstream psychological toll of that stress. This nuance enriches the Stress-Buffering Hypothesis by clarifying its limitations in overwhelming stressful environments caused by COVID-19, while affirming its critical role in mitigating downstream stress outcomes. In the direct relationship, social support acts as a resource-reservoir buffer [51, 52], mitigating daily disruption burdens and reducing depletion of psychological resources to dampen stressors’ toll. In the stage linking perceived stress to pandemic fatigue, it might enhance adaptive stress coping strategies [77], enabling reframing of stress as manageable challenges and weakening the transition to pandemic fatigue.

The failure to support H3b may reflect the unique context. From April to May 2022, Shanghai experienced a severe COVID-19 outbreak leading to a two-month citywide lockdown [78], and this wave rapidly spread to neighboring Zhejiang and Jiangsu Provinces, encompassing the Yangtze River Delta region [79]. The widespread pandemic and strict lockdowns created a universally high-stressful environment. During this period, lockdown stressors including food shortages, job and income loss, difficulties in getting medical service, and lockdown-related fears were associated with increased perceived stress and negative mental health outcomes [79, 80]. In such an extreme context, even robust social support could not alter individuals’ appraisal of these disruptions as overwhelming. This aligns with the Stress-Vulnerability Hypothesis [81, 82], which posits that protective factors like social support may lose efficacy under extreme and ubiquitous stressors. Here, the scale and universality of pandemic disruptions likely overrode social support’s buffering potential at the initial stage of stress appraisal, as prioritized threat processing in the amygdala [82]consumed cognitive resources needed to leverage social support for reappraisal.

Implications

Our findings contribute to the global literature on pandemic fatigue by contextualizing mechanisms within a specific sociocultural and temporal framework of China’s Yangtze River Delta region during the acute COVID-19 outbreak in 2022, clarifying how daily life disruptions translate into pandemic fatigue through perceived stress and how perceived social support buffers this pathway at distinct stages. Furthermore, our study is the first to demonstrate that social support’s protective effect persists for downstream outcomes, such as alleviating pandemic fatigue stemming from perceived stress, even when upstream stress appraisal is unbuffered, offering new insights into the role of social support in high-stress collective contexts. The findings of this study hold enduring relevance in the post-pandemic era, particularly as global societies navigate long-term health crisis preparedness and the residual psychological impacts of COVID-19. While the acute phase of the COVID-19 pandemic has subsided, its lessons remain critical for understanding how stressors influence pandemic fatigue from future public health emergencies, such as other emerging infectious diseases. Particularly within the cultural framework of collectivist societies like China where emphasis on intergenerational solidarity, communal governance, and collective problem-solving shapes stress-coping dynamics.

Given the findings of this study, policy recommendations to reduce pandemic fatigue should target stage-specific interventions that compensate for the initial stress appraisal gap and harness social support for downstream coping mechanisms. First, to address the unbuffered emotional impact of disruptions caused by the pandemic and its management measures, policymakers should prioritize reducing objective stressors in high-risk domains identified. This includes implementing flexible lockdown measures to preserve core routines, expanding safe outdoor activity zones, and stabilizing education and work transitions with tailored support. Such actions directly reduce the upstream disruptions that trigger stress, complementing social support’s limited role in early appraisal. Second, mental health policies should emphasize stress reframing and adaptive coping, leveraging social support’s proven role in weakening the perceived stress and pandemic fatigue link. This includes nationwide campaigns promoting stress management skills to help individuals view stressful situations from a perspective of shared experience and collective strength, as well as adopting adaptive coping strategies such as problem-solving and seeking social support. Third, recognizing that perceived social support exerts a stage-specific buffering effect, efforts to strengthen it should focus on enhancing individuals’ subjective perceptions of available support. This includes promoting neighborhood mutual-aid programs, spotlighting localized mental-health and peer-support resources on public platforms, and running campaigns that normalize seeking help as an active coping strategy.

Limitations

Our study has certain limitations. Firstly, this survey was conducted through an online questionnaire platform, which may have sample bias. Second, this study was conducted in three provinces/municipalities in eastern China, and the generalizability of the results needs to be treated with caution. Third, this study was a cross-sectional study. Therefore, we were unable to determine causality between the study variables. Fourth, the study focused on the moderating effect of perceived social support and measured it using relevant scales, the special phenomenon of network support during the pandemic was not included in this study. Future research could adopt longitudinal designs to clarify the causal relationships between daily life disruptions, perceived stress, and pandemic fatigue over time. Expanding the scope to include understudied regions beyond the Yangtze River Delta would enhance generalizability. Additionally, exploring the role of emerging forms of social support such as online social support and their interaction with traditional support systems could provide deeper insights. Investigating how cultural factors shape the stress-buffering effects of social support in diverse sociocultural contexts is another valuable direction.

Conclusion

The findings of the present study suggest a positive association between disruptions to daily life caused by COVID-19 and pandemic fatigue. In addition, the results highlight the role of perceived stress in mediating the negative impact of COVID-19 disruptions to daily life on pandemic fatigue and the important protective role of social support. The present findings suggest that in the face of major health crises, we should rally all surrounding forces to support each other and reduce stress sensitivity to alleviate possible fatigue.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1^{(16.6KB, docx)}

Acknowledgements

The authors would like to thank all the counselor teachers for their assistance and cooperation.Also, we would like to thank all participants who have participated in the present study.

Author contributions

MMZ, QHW and YXG conceptualized this study and organized the survey. JZ and HJL analyzed and interpreted the data and drafted the original manuscript. XYW, RZG assisted with data collection and literature review. HL and BHL contributed to the manuscript’s revision. All authors read and approved the final manuscript.

Funding

Funding for this study was provided by the National Natural Science Foundation of China [72304079, 72361137562]; the Social Science Foundation of Nantong (2020CNT010), the Public Welfare Project of Science and Technology Department in Zhejiang (LGF22G030018), the 2022 New Era Excellent Master’s and Doctor’s Thesis of Heilongjiang Province Project (LJYXL2022-023) and the Research on Emergency Response System and Capacity Construction of Public Health Emergencies(22YJC630216).

Data availability

The datasets used during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Research Ethics Committee of Nantong University. All subjects signed informed consent before filling in the questionnaire, and the survey results were anonymous.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Jie Zhuang, Qunhong Wu and Hongjiao Li have contributed equally to this work.

Contributor Information

Yuexia Gao, Email: gaoyuexia1103@163.com.

Miaomiao Zhao, Email: zhaomiaomiao@ntu.edu.cn.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1^{(16.6KB, docx)}

Data Availability Statement

The datasets used during the current study are available from the corresponding author on reasonable request.

[CR1] 1.Wang Y, Shi L, Que J, Lu Q, Liu L, Lu Z, Xu Y, Liu J, Sun Y, Meng S, et al. The impact of quarantine on mental health status among general population in China during the COVID-19 pandemic. Mol Psychiatr. 2021;26(9):4813–22. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR2] 2.Haktanir A, Can N, Seki T, Kurnaz MF, Dilmaç B. Do we experience pandemic fatigue? Current state, predictors, and prevention. Curr Psychol. 2021; 41(10):7314–7325. [DOI] [PMC free article] [PubMed]

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PERMALINK

COVID-19’s disruptions to daily life and pandemic fatigue during the pandemic in Chinese people: a moderated mediation effect of perceived stress and social support

Jie Zhuang

Qunhong Wu

Hongjiao Li

Xiyue Wang

Runzi Gu

Huan Liu

Baohua Liu

Yuexia Gao

Miaomiao Zhao

Abstract

Background

Methods

Results

Conclusion

Supplementary Information

Introduction

COVID-19’s disruptions to daily life and pandemic fatigue

The mediation effect of perceived stress

The moderating effect of social support

The present study

Fig. 1.

Methods

Participants and procedure

Measures

COVID-19’s disruptions to daily life

Pandemic fatigue

Perceived stress

Perceived social support

Statistical analysis

Results

Basic characteristics and pandemic fatigue

Table 1.

Descriptive analysis of COVID-19’s disruptions to daily life

Fig. 2.

Testing for common method bias and multi-collinearity

Bivariate correlations analysis

Table 2.

Testing for the mediation effect

Table 3.

Testing for the moderated mediation effect

Table 4.

Fig. 3.

Discussion

Implications

Limitations

Conclusion

Supplementary Information

Acknowledgements

Author contributions

Funding

Data availability

Declarations

Ethics approval and consent to participate

Consent for publication

Competing interests

Footnotes

Contributor Information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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