The calamitous effects of global pandemics are not unfamiliar to human history. The 1918 Influenza pandemic, infamously known as the “Spanish Flu,” engulfed the world in three distinct waves over a span of more than three years, infecting nearly half of the global population and resulting in over 50 million fatalities. Fast forward to the 21st century, the world has been confronted with another pandemic of comparable scope-COVID-19. First emerging in late 2019, this highly infectious disease has brought even the most advanced healthcare systems to their knees, manifesting in a series of devastating waves in 2020 and 2021.

India, a country with an intricate public health infrastructure, initially appeared to take successful preventative measures against the first wave of the COVID-19 pandemic. A nationwide lockdown was initiated in March 2020, which led to a temporary slowdown in case numbers, providing a momentary sense of victory [1]. Public health experts and epidemiologists noted that this lockdown helped bolster healthcare facilities by providing a window for ramping up testing capabilities and other medical resources [2]. However, the complacency that followed proved costly when the second wave struck with unparalleled fury in April 2021. This wave was primarily driven by a new and more virulent strain of the virus, known as the B.1.617 or Delta variant [3]. Despite the Indian government's establishment of a SARS-CoV-2 Genomic Consortium for genomic sequencing, the emergence of this new variant caught healthcare systems, policymakers, and researchers off-guard [4]. The second wave led to unprecedented pressure on India's healthcare system. There were catastrophic shortages in essential medical supplies, including ventilator beds, oxygen, and critical medications such as Remdesivir. Epidemiological studies and health system reviews pointed to systemic failures and resource mismanagement as contributing factors to this collapse [5]. Amidst the already complicated landscape, a series of new health challenges emerged. The rise of Mucormycosis, commonly known as Black Fungus, was a disturbing phenomenon observed in post-COVID patients [6]. Scientific studies have indicated that this could be linked to prolonged hospital stays, excessive use of steroids, and immunocompromised states, complicating the already intricate treatment protocols [7]. The societal ramifications were equally dire. Public panic was exacerbated by media portrayals and real-life experiences such as the sight of floating bodies in rivers and the looting of medical supplies. Social studies have documented how misinformation and lack of reliable communication led to heightened public anxiety [8]. One distinguishing feature of the second wave in India was its impact on younger populations, contradicting earlier beliefs that they were at a lower risk. Studies indicate that this might have been due to multiple factors, including lax behavior during the period between the two waves and variations in vaccination coverage among different age groups [9]. By carefully examining India's unique scenario, this study aims to contribute nuanced perspectives to the global understanding of the COVID-19 pandemic and its varied impacts on different populations and infrastructures.

The pandemic's progression, notably captured by social and visual media, contributed significantly to widespread anxiety and panic. Unsettling images of overflowing hospitals, people gasping for oxygen, bodies floating in rivers, and numerous other grim realities bombarded the collective conscience of the nation. The media also discussed the continuously mutating strains, adding another layer of uncertainty and anxiety to an already distraught populace [5].

The pandemic's onset has led to a paradigm shift in academic institutions worldwide, one that has not only affected the modus operandi but also trickled down to the psychological well-being of university employees [1]. The shift to virtual learning environments, remote administrative work, and abrupt changes to academic protocols have presented unprecedented challenges for faculty, administrative staff, and support services alike [2]. The abrupt transition to online teaching has been stressful for faculty members, not just from a technical standpoint but also pedagogically. The loss of face-to-face interactions and the absence of immediate feedback have led to an emotional void, making educators question their teaching efficacy [3]. Such situations have resulted in heightened stress levels and even instances of burnout [4]. Work-from-home conditions, initially considered a boon by many, soon morphed into a bane as the lines between professional and personal life blurred. Academic employees found themselves caught in a 'role-conflict,' trying to balance professional responsibilities with household chores, and child or elder care, leading to increased levels of anxiety and depression [5]. University administrative staff faced their own set of challenges. In addition to adapting to remote working conditions, they were tasked with implementing unprecedented emergency measures, often with limited guidance. This resulted in increased workloads and diminished time for self-care, thereby affecting their overall psychological well-being [6]. Research has also indicated that the pandemic has exacerbated existing social inequalities among university employees. Those with limited access to technology, those caring for dependents, or those already suffering from mental health conditions found the new working conditions particularly challenging, contributing to a decline in overall well-being [7]. Initial studies have suggested that coping mechanisms such as social support, mindfulness exercises, and timely institutional interventions can alleviate some of the psychological distress experienced by academic employees [8]. However, the efficacy of these coping mechanisms varies greatly among individuals and warrants deeper investigation, a gap this study aims to address.

By diving deep into these multifaceted challenges, this research aims to develop a nuanced understanding of the impact of the COVID-19 pandemic on the psychological well-being of university employees. This will not only contribute to the existing body of knowledge but also provide actionable insights for policymakers and institutional leaders.

The present study aims to fill a critical gap in the existing literature by focusing on the psychological well-being of university employees in the context of the COVID-19 pandemic. Further, this research intends to shed light on the mediated role of coping mechanisms in mitigating the negative impacts of COVID-19 on psychological well-being. While there exists a considerable body of literature that explores the psychological well-being of healthcare workers, frontline staff, and the general population amid the COVID-19 pandemic, fewer studies have focused specifically on university employees. This study addresses this gap by examining the psychological impact of the COVID-19 pandemic on this overlooked demographic, particularly in the Indian context.

Most existing studies that discuss the psychological well-being of individuals during the pandemic tend to focus on diagnostic assessments or prevalence rates of psychological conditions. Our study adds a unique perspective by investigating how coping mechanisms mediate the relationship between COVID-19-related stressors and psychological well-being among university employees. This research contributes to the existing literature by focusing on India-a country that faced unique challenges during the pandemic, including a damaging second wave dominated by the Delta variant. Cultural norms and societal structures in India can substantially influence coping strategies and mental health outcomes, making this study valuable for understanding the unique coping mechanisms that university employees in India employ.

Traditionally, pandemics have been understood as events that lead to widespread illness and mortality, with their psychological impact being somewhat underrepresented in academic literature. However, the COVID-19 pandemic has brought mental health to the forefront, challenging traditional narratives that typically do not associate pandemics with psychological disturbances akin to post-traumatic stress disorders (PTSD) [5]. An earlier review by Brooks et al. in “The Psychological Impact of Quarantine and How to Reduce It” indicated that quarantine measures during epidemics like SARS, H1N1, and Ebola resulted in various psychological effects, such as confusion and anger [9]. Likewise, Pfefferbaum and North in “Mental Health and the COVID-19 Pandemic” argued that psychological outcomes could be a 'second wave' of the pandemic crisis [10]. These insights have broad implications for understanding the psychological toll of pandemics beyond merely counting cases or mortalities [11]. study published in the Journal of the American Academy of Child & Adolescent Psychiatry highlighted that the impact extends to children and adolescents, leading to increased instances of anxiety and depressive disorders. They found that social isolation measures exacerbated existing mental health problems among young people. Hawryluck et al. also demonstrated that participants who had been quarantined during the SARS outbreak experienced PTSD symptoms and depression for up to three years post-quarantine (Emerging Infectious Diseases, 2004). This long-term impact resonates with the growing concerns surrounding the lasting psychological effects of the Covid-19 pandemic. Hence, the cumulative evidence suggests that pandemics, traditionally viewed as medical and logistical crises, have profound long-term impacts on mental health, affecting both clinical outcomes and well-being across demographic groups. The COVID-19 pandemic has only reinforced the necessity of integrating mental health into pandemic preparedness and response strategies.

The pandemic has not only had broad societal impacts but has also exerted differential pressure on various demographics. A study [6] focused on the medical staff and the general public in Wuhan, China, where the pandemic originated. Utilizing the Impact of Event Scale-Revised (IES-R) and the Depression, Anxiety and Stress Scale (DASS-21), the study found that medical staff were more affected psychologically than the general public. About 51% of the respondents considered psychological counseling beneficial, with 66% of those being medical staff and 34% from the general public. Wang et al. [7] extended this research to a more international context, including seven middle-income Asian countries. The highest stress levels were observed in Thailand, while Vietnamese citizens reported the least. The study emphasized the need for early-stage psychological support for the general population. Another study [12] assessed the impact of lockdown measures on the general population in Reunion Island. The results revealed significant reductions in overall well-being and increased sleep disruption, anxiety, and sedentary behavior.

The shift to online learning due to the pandemic has had profound implications for the psychological well-being of both students and faculty. A study [13] elucidated that while hedonic motivation and facilitating leadership influenced the adoption of online teaching, it left questions about its impact on well-being. A study specifically focused on teachers in Spain and found increased levels of stress, anxiety, and depression [14]. Similarly, a study [15] noted that 73% of Italian university students surveyed were graded as depressed, and 35% as anxious, highlighting the emotional toll the pandemic took on students. This research aligns with findings from Son et al., who published a paper in “PLOS ONE” in 2020, demonstrating an uptick in anxiety and depressive symptoms among university students due to the pandemic. Educational settings are not just physical spaces for learning; they are also essential for socialization, emotional development, and mental well-being. As noted, the absence of a comprehensive mental health strategy in G20 educational systems during the pandemic was a significant oversight [16]. The transformation in educational settings, spurred by the pandemic, necessitates a deeper examination of its psychological impact on everyone involved, from students to faculty to administrative staff. Thus, the COVID-19 pandemic underscores the need to consider the psychological well-being of all stakeholders in educational settings, not just during the pandemic but as a fundamental aspect of educational policy and practice.

The COVID-19 pandemic has led to a major upheaval in higher education systems worldwide, with significant implications for the mental health and well-being of students, faculty, and staff. One of the critical studies in this context was conducted [16], which revealed that students' mental health and well-being were largely overlooked during the pandemic across the G20 countries. Research conducted [17] in the “Journal of Psychiatric Research” reveals that the abrupt shift to online learning, social isolation, and uncertainties related to academic progression has resulted in increased stress and anxiety levels among university students. Another study by Huckins et al., published in “JAMA Pediatrics,” demonstrated that college students showed a significant decrease in physical activity and an increase in screen time, which negatively affected their psychological well-being. Faculty members are also impacted. A study [18] in “Frontiers in Psychiatry” revealed that university staff experienced increased stress and burnout levels due to changes in teaching modalities and additional administrative work.

The global higher education landscape has thus become a critical area for assessing and addressing the multifaceted impacts on psychological well-being. It is evident from the existing literature that both students and educators are facing unparalleled mental health challenges. These findings necessitate urgent interventions and policies at the institutional and national levels to mitigate the negative psychological outcomes of this unprecedented crisis in global higher education. The research in this area underscores the importance of immediate, evidence-based interventions to improve mental health and well-being across higher educational institutions worldwide.

The interactive model looked at the ‘Impact of Event Scale’ and ‘Depression, Anxiety, and Stress Scale’ for effect-related inputs, which were assumed to be negative due to the prevailing pandemic and related events, based on employees’ personal experiences. ‘Coping Strategies Scale’ was used to

Fig. (1). Conceptual model of study. Source: By the researchers' team. Hypotheses. H1: There is a significant and negative effect of the IES-R factor on the coping strategies. H2: There is a significant and negative effect between the DAS factor and coping strategies. H3: There is a significant prediction of the coping strategies on the self-acceptance factor. H4: There is a significant and positive effect of coping strategies on the purpose of life. H5: There is a significant and positive effect of coping strategies with environmental mastery. H6: There is a significant and positive effect of coping strategies with positive relations with others. H7: There is a significant and positive prediction of the coping strategies for personal growth. H8: There is a significant and positive effect of coping strategies on autonomy.

measure individual responses to facing personal difficulties, which as per the selected scale could make an employee either adapt to counter unwanted events or give in and become a victim of the same. This cumulatively leads to one’s well-being in the existing scenario, which was captured by utilising well well-established ‘Psychological Well-Being Scale’. The data for all these four constructs was captured through standard instruments. A conceptual model was evolved through iteration as given in Fig. (1).

The data were subjected to validation testing to check their internal coherence and reliability. All constructs were found to be above the threshold value of 0.70 on Cronbach Alpha, as given in Table 4.

5.1. Impact of Events

The survey on IES is divided into three responses. Intrusion or internalizing of adverse impact, avoidance of the same, or increased excitement as hyperarousal causing extreme stress. The responses show that over 46% of employees have remained unaffected in all three adverse reactions, while 27% were affected a little bit. Only 5% were affected severely (Table 5 and Fig. 2).

Fig. (2). IES-R response chart.

Table 5. Percentage responses on IES-R.

Construct	Sub-Construct	Not At All	A Little Bit	Moderately	Quite a Bit	Extremely	Mean
Impact of Events (Percentage)	Intrusion	50	28	14	6	2	1.82
	Avoidance	39	27	19	10	5	2.14
	Hyperarousal	48	25	11	8	8	1.52

5.1.1. Intrusion

The Covid scenes, traumatic thoughts and consequent impact were extreme for a little over 2% of the respondents, while 6% and 14% were affected quite a bit and moderately respectively. The responses show that 50% did not show any effects, while 28% were affected a little bit. The average mean is 1.82, which shows positive responses to a reasonable extent.

5.1.2. Avoidance

The items of this sub-construct measured an individual avoiding the reality of virus-related panic or impact. About 5% of respondents attempted avoidance with 10% avoiding it quite a bit. Moreover, 39% did not require to avoid the effects while 27% had to make a little effort. The average mean of all items is 2.14, which reflects leaning towards a little bit and moderate avoidance of the situation.

5.1.3. Hyperarousal

The sub-construct looked at COVID events/news triggered by irritable nature, lack of sleep, or feeling of lack of concentration. Moreover, 48% of respondents did not encounter any of these adverse symptoms, while 25% felt a little bit. Almost 8% of respondents suffered extremely or quite a bit from these symptoms. Another 11% were moderately affected. Two hundred and four responded as attempting to be more watchful and cautious against COVID-19 symptoms.

5.2. Depression, Anxiety, and Stress

The survey questionnaire on this dimension provided data under three sub-constructs - depression, anxiety and stress. The results of this survey are very encouraging on this scale as just 1 to 3% of the respondents appear to be suffering from COVID-19 triggered adverse emotions, while above 70% responded as not affected at all. This is also evident from the average means of all items, which is closer to 1.40, implying that the effects of these dimensions were either not there or were only to some degree on most of the employees (Table 6 and Fig. 3).

Fig. (3). DASS-21 results.

Table 6. Percentage responses on DASS-21.

Construct	Sub-construct	Did Not Apply	Some Degree	Considerable	Very Much	All the Time	Mean
Depression, Anxiety, and Stress (Percentage)	Depression	72	20	5	2	1	1.40
	Anxiety	74	18	5	2	1	1.35
	Stress	65	26	5	3	1	1.47

5.2.1. Depression

The items in the sub-construct portray a lack of initiative, lower work-related enthusiasm, sinking feelings and hopelessness. Only 1 to 2% of the respondents felt overwhelmed, while 5% responded with considerable effects of these emotions. About 72% of the employees did not relate to any of such negative feelings, while 20% had some degree of depressive feeling. A mean average of 1.40 validates the results to be more positively inclined.

5.2.2. Anxiety

The items portray breathing difficulties, trembling, being scared or in panic. The responses were nearly identical to depression, as only 1 to 2% of the respondents felt overwhelmed with these emotions, while 74% didn’t feel any anxiety and18% were affected to some degree. The average of items means is 1.35, which projects positive responses.

5.3. Stress

Nervousness, difficulty in relaxing, agitation and sensitivity were some of the statements under this sub-construct. The responses were again identical to depression, as 65% didn’t feel any stress, while 26% felt stress to some degree. Only 1 to 3% of the respondents felt overwhelmed with these emotions.

5.3.1. Coping Strategies

The strategies reflect how the employees face adverse impacts, depression, anxiety, or stress due to prevailing situations. An employee can be resilient enough to adapt to the situation and prepare to sail through or fall into the melancholy and sickness of the same. This will lead to the maladaptation stage.

5.3.1.1. Adaptive Strategies

The items include active coping, planning, acceptance, emotional support, humour, positive reframing, and religion. The items or statements included concentrating efforts on doing something about the situation, getting emotional support, taking action to make the situation better, learning to live with it, and comfort in religion or spiritual beliefs. About 42% of the respondents used some adaptive strategies. As many as 38% remained under the never or a little bit zone, thus indicating an inability to adapt to the stressful situation. Table 7 and Fig. (4) depict the responses.

Fig. (4). Depiction of coping strategies.

Table 7. Coping strategies of respondents.

Construct	Sub-Construct	Never	A Little Bit	Sometimes	Mostly	Always	Mean
Coping Strategies (Percentage)	Mal-adaptive	60	14	14	8	4	1.81
	Adaptive	22	16	20	23	19	3.02

5.3.2. Mal-adaptive Strategies

The items in the sub-construct include behavioural disengagement, denial, self-distraction, self-blame, and use of substance or venting strategies. The statement capturing these coping mechanisms included, other activities to take the mind off things, saying that ‘this isn’t real’, trying to deal with it, refusing to believe, letting unpleasant feelings escape, using alcohol or other drugs to help, or blaming self for things that happened. The responses are indicative of struggle with 26% of the respondents. However, nearly 74% of the employees were adapting to the new situation and were able to cope with the challenges. The adaptive and maladaptive responses appear to be out of synchrony, reflecting respondents' bias with difficult questions.

5.4. Personal Well-being

Much debated health definition by the WHO [25] highlights the well-being of an individual as, “Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.” Well-being is a wider dimension with many sub-constructs encompassing objective and subjective well-being. The 18-item scale of Ryff and Keyes [26] has six sub-constructs that were studied for the respondents. It sought answers to how well each respondent felt about herself/himself to ascertain the impact of a virus-driven negative environment. The results (Fig. 5) showed a fair percentage of employees struggling to maintain their well-being, which can be flagged as a cause of concern, though the majority of nearly 60% responded well to the environment around them.

5.4.1. The Self-acceptance

The sub-construct looks at personal achievements, self-evaluation, and a feeling of accomplishment. As seen from Table 8, and the figure above, 61% of respondents feel quite satisfied, while 24% struggle to come to terms with accepting themselves. Others are neutral. The average mean value of 3.5 points towards positive self-acceptance.

5.4.2. The Purpose in Life

Statements affirming purpose include using each day well, living for the day, and fulfilling one’s life goals. The number of agreed respondents is 46%. However, if neutral or undecided 23% is included, the majority would fall in the positive mindset. As many as 31% of the respondents feel they are not meeting the purpose in the prevailing situations.

5.4.3. The Environmental Mastery

The ability to manage the environment around and mastery in everyday life constitute this sub-construct. About 56% of the respondents are managing it well, while 20% are fence-sitters. 24% feel that the situation is not conducive to letting them manage the environment around them well.

Fig. (5). Personal well-being.

Table 8. Personal well-being data.

Construct	Sub-construct	Strongly Disagree	Disagree	Neither Disagree Nor Agree	Agree	Strongly Agree	Mean
Personal Well Being (Percentage)	The Self-Acceptance	10	14	15	37	24	3.50
	The Purpose in Life	10	21	23	31	15	3.21
	The Environmental Mastery	9	15	20	38	18	3.41
	The Positive Relations with Others	18	29	20	24	9	2.76
	The Personal Growth	11	12	9	31	37	3.71
	The Autonomy	4	8	22	47	19	3.68

5.4.4. The Positive Relations with Others

Experience in warm and trusting relationships and the ability to gain and sustain trust are the key items of this sub-construct. This has come out as a major challenge for the respondents in the locked-down conditions with the pandemic situation. Only 33% agree with their abilities to maintain positive and trusting relationships as against 47%, who are doubtful and 20% remain undecided.

5.4.5. The Personal Growth

Continuous learning, taking up challenges and improvement in one’s life figure under this sub-dimension. 68% of respondents agree with these steps, while only 23% have scepticism about the same. Locked-down conditions should have stirred most to acquire new qualifications, add to their skills and continue on a learning path.

5.4.6. The Autonomy

Self-judgement, respecting own opinions and not being unduly influenced by what others say or think were some of the statements depicting individual autonomy. 66% felt they were autonomous, while only 12% considered being influenced by others. As many as 22% did not have any of the extreme views.

A two-stage research process was adopted in the current study. The researchers first used confirmatory factor analysis to validate the measurement model with the help of AMOS. Afterwards, the researcher tested the proposed relationships among the study variables by using the structural equation modelling technique. The data analysis section is subdivided into two parts [27]. The first part deals with the measurement model and the second part deals with the structural model. Under the measurement model, the reliability and validity of the constructs were established and under the structural model, the hypothesized relationships were tested.

5.6. Structural Model

Structural equation modelling through AMOS 20.0 was used to examine the study's proposed model. The first step in determining the robustness of any model (Fig. 6), according to Hair et al. [27], is to determine whether the model is a good fit or not. The following values illustrate the yardsticks for recommended values as suggested by prior studies for an overall fit. The value of chi-square statistics divided by the degree of freedom is 2.784, which is less than the cut-off value of less than 3. Further, the values of other model fit indices show that overall the proposed model is fit for the analysis as the values of RMR = 0.039 ≤ 0.08, RMSEA = 0.042 ≤ 0.08, CFI = 0.911 ≥ 0.90, AGFI = 0.924 ≥ 0.80, GFI = 0.907≥0.80. Since the model has an acceptable fit, we continued to analyze the path coefficients to test the hypothesis.

Fig. (6). Structural equation model.

Table 11. Hypothesized relationship.

Relationship			SRW	S.E.	C.R.	P	R2
Coping	<---	IESR	-.669	.015	-26.310	***	.631
Coping	<---	DAS	-.428	.010	-16.827	***
PL	<---	Coping	.431	.118	11.416	***	.186
EM	<---	Coping	.679	.090	22.070	***	.461
PR	<---	Coping	.392	.087	10.173	***	.154
PG	<---	Coping	.632	.072	19.448	***	.399
AUT	<---	Coping	.803	.061	32.199	***	.645
SA	<---	Coping	.051	.115	1.219	.223	.003

Note: SRW=standardized regression weight; SE=standard error; C.R.=critical ratio; ***p<0.01; R²=squared multiple correlation.

Results of the structural equation modelling technique (SEM) show that there is a significant and negative effect of the “impact of events” factor on the coping strategies of the participants (SRW=-.669; t-value= -26.310; p< 0.05). Hence, hypothesis 1 was accepted. A similar type of result was observed for the relationship between the “depression anxiety and stress” factor and coping strategies factor. Results of Table 11 show that DAS negatively predicts the coping strategies (SRW=-.428; t-value= -16.827; p< 0.05). Hence, hypothesis 2 was accepted. Further, results of the SEM show that coping strategies do not predict the self-acceptance factor (SRW=.051; t-value= 11.2191.416; p> 0.05). Hence, hypothesis 3 was not accepted. The coping strategies have shown a significant positive relationship with the purpose of life (SRW=.431; t-value= 11.416; p< 0.05). Hence, hypothesis 4 was accepted. Further, coping strategies have a significant positive relationship with environmental mastery (SRW=.679; t-value= 22.070; p< 0.05). Hence, hypothesis 5 was accepted. Results of the SEM technique also show that there is a significant and positive effect of the “coping strategies” factor on the positive relations with others (SRW=.392; t-value= 10.173; p< 0.05). Hence, hypothesis 6 was accepted. Results of Table 11 show that coping strategies positively predict personal growth (SRW=.632; t-value= 19.448; p< 0.05). Hence, hypothesis 7 was accepted. Finally, the results of the SEM analysis show that coping strategies have a significant and positive effect on autonomy (SRW=.803; t-value= 32.199; p< 0.05). Hence, hypothesis 8 was accepted.

Every research comes with some limitations, which should be kept in mind while generalizing the results of the study to the masses. The current study also has a few limitations. It is important to note that the cross-sectional design limits us from drawing any firm conclusions about causal relationships among the study variables. Therefore, future researchers could go for a longitudinal research design so that the causal relationship among the variables could be established. Another limitation is related to the data. As the data was collected from university staff, the results of the current study may not be applicable to other sectors. Hence, future researchers could include more sectors such as manufacturing or IT industry to enhance the generalizations of the results. While our (confirmed) model was built on theory and prior empirical research, further testing using a longitudinal design is warranted. Another limitation is related to response bias. Due to the self-report nature of the study, it was not possible to eliminate response bias even if respondents completed the surveys anonymously. In the future, the researchers should try to replicate the findings using more robust samples.

The first author compiles research designs, collects data, conducts theoretical studies, and compiles research drafts. The second author is the corresponding author, doing literature reviews, analyzing and interpreting data, and performing proofreading. The third author contributes to compiling research questionnaires and collecting data. The fourth author contributes to the introduction, research design and discussion.