Magdalena Jelińska
Michał B. Paradowski- 1Institute of Applied Linguistics, University of Warsaw, Warsaw, Poland
- 2Institute of Linguistics, University of Silesia, Sosnowiec, Poland
In response to the outbreak of the COVID-19 pandemic, educational institutions around the world were forced into lockdown in order to contain the spread of the virus. To ensure continuous provision of education, most transitioned to emergency remote instruction. This has been particularly the case in higher education (HE) institutions. The circumstances of the pandemic have brought unprecedented psychological pressure on the population, in the case of educators and students exacerbated by the transition to a mode of instruction that was completely novel to the majority. The present study examines how college and university instructors dealt with teaching online in these unparalleled circumstances, with a focus on how factors connected with their daily lives and livelihoods influenced their well-being. Between April and September 2020, a comprehensive online survey was filled out by 804 HE instructors from 92 countries. We explore how sociodemographic variables such as gender, age, relationship status, living conditions, and length of professional experience non-trivially affect situational anxiety, work-life synergy, coping, and productivity. The results contribute to a better understanding of the impact of the pandemic and emergency remote instruction on college and university instructors’ well-being by explaining the mechanisms mediating the relationship between individual, contextual, and affective variables. It may provide helpful guidelines for college and university administrators as well as teachers themselves as to how help alleviate the adverse effects of the continuing pandemic and possible similar disruptions leading to school closures on coping and well-being.
Introduction
The circumstances of the pandemic have brought unprecedented psychological pressure on the population. The adverse—sometimes long-lasting—psychological impact of the lockdown restrictions, stay-at-home orders, quarantine, and other repercussions span anxiety, post-traumatic stress symptoms, psychological distress, confusion, panic disorder, anger, depression, insomnia, and emotional exhaustion (Brooks et al., 2020; Qiu et al., 2020; Cénat et al., 2021a).
Teachers and students have been among the more impacted groups (International Labour Organization, 2020). As campuses almost all over the world successively shut down, in order to ensure the continuity of learning and of communication between teachers and students (Karalis, 2020), educators were thrust into the provision of alternative modes of delivery, or “emergency remote teaching” (Hodges et al., 2020; Reimers and Schleicher, 2020) that for most was an entirely novel form of work. Often, the anxieties were exacerbated by job uncertainty, especially for faculty on precarious contracts who—as happened for instance across the United Kingdom—were often dismissed by their institutions in an attempt to cut costs (World Bank, 2020:10).
The combined effect of lockdowns and the transition to online delivery have severely affected teacher and student coping and well-being. The strong possibility of deteriorating mental health because of the sense of uncertainty and anxiety among students and faculty members was understandably envisaged already in the initial stages of the pandemic (Sahu, 2020).
Literature Review
The impact of the COVID-19 pandemic on higher education has been a burgeoning topic of discussion (Fischer, 2020). However, the majority of the extant literature concerned with “pandemic pedagogy” tends to focus on the logistics and provision of training (Reimers and Schleicher, 2020), without taking into account the psychological impact of the situation on the teachers’ functioning, let alone trying to tease apart the relative influence of the factors affecting instructors’ well-being. For instance, the University of Houston (2020) published a report summarizing the faculty’s perceptions regarding the transition to a remote teaching model, revealing significant variation in terms of the implementation of technology tools and of the mode of instruction. Watermeyer et al. (2021) carried out a survey of academic teachers’ reaction to the move to online teaching, and found that the majority of the respondents felt confident or strongly confident in their ability to facilitate online teaching and assessment and considered their institutions to be supportive in facilitating the move to online delivery. Bensaid and Brahimi (2021) likewise attributed the successful maintenance of the learning cycle in higher education institutions in the Gulf to their already established distance education, swift administration and policy steps, and access to resources. Jelińska and Paradowski (2021b) in turn revealed how teachers’ perception of how their students were coping with the novel situation was influenced by their own demographics and professional adaptation to emergency remote teaching.
Where the psychological impact of the pandemic in education was a concern, the existing literature has tended to focus on the student population. A topical analysis of tweets (Duong et al., 2020) revealed that negative sentiments toward the central issues of COVID-19 were significantly higher among students than in the general population. Khodabakhshi-Koolaee (2020) in interviews with 15 postgrad students in Iran who had experienced living in quarantine, as three of the four main emerging themes identified (i) developing negative emotions, confusion and pessimism, (ii) concerns about family health, as well as (iii) economic and social concerns and “fear of tomorrow.” In a qualitative phenomenological study with five university students in the Philippines, Alvarez (2020) showed how learning engagement and isolation and the lack of affective and emotional support affected learning engagement. Another study (Yang et al., 2021) showed that students’ self-efficacy and well-being were positively predicted by their perceived closeness with the teacher, peer influence, and perceived control over own learning. Students’ perceived learning outcomes were also found to be positively influenced by instructional support and instructor innovation, and–interestingly–negatively by teacher performance (Wang et al., 2021). In a multi-national survey of undergraduate students, Nguyen et al. (2021) reported that the majority preferred synchronous classes, which mode–especially when it involved active-learning techniques–correlated with higher levels of engagement and motivation. Student engagement and adaptability were also found to significantly correlate with academic emotion (Zhang et al., 2021). An analysis carried out at a university in Russia (Dikaya et al., 2021) revealed an association between students’ attitudes to forced remote learning and their interpersonal communicative skills and thinking and learning styles. A survey of students’ emotions during and perceptions of the shift to online teaching at a Greek university (Karalis and Raikou, 2020) found that although the majority of the students were satisfied with the new way of attending classes, upon the closure of the university over three quarters had felt negative emotions such as stress and anxiety about how the studies would be completed, fear of the possibility of non-continuation of studies, and/or sadness about the interruption; after the online classes had started, some of the initial negative emotions gave way to an increase in relief that the semester would not be lost, and joy at the continuity of the classes. Across the Turkish border, students reported high perceived stress, mild generalized anxiety, and low satisfaction with life (Aslan et al., 2020). In a questionnaire probing the mental health of medical college students, Cao et al. (2020) found that risk factors increasing anxiety were economic consequences as well as having relatives or acquaintances infected with SARS-CoV-2, while social support, living with parents, and family income stability were protective factors. Similar results were obtained by Wilczewski et al. (2021), whose investigation of the psychological and academic effects of learning online among international students enrolled at the University of Warsaw revealed that those who had returned to their home countries (and therefore likely had familial support) exhibited higher academic adjustment, while quarantine and self-isolation increased the levels of loneliness – and acculturative stress when in the host country. Amendola et al. (2021) study carried out among students in Switzerland showed that anxiety symptoms decreased with time, and its levels were predicted by older age, female gender, out-of-country nationality, loneliness, concerns about own health (positively), and resilience and social support (negatively). Awoke et al. (2021) measured perceived stress among health science students in Ethiopia, with identified correlates of the construct including rare contacts with friends and a decreased household income. In a study employing interview surveys with 195 university students in the United States, over seventy per cent of the participants indicated increased stress and anxiety due to the COVID-19 outbreak. The identified factors that contributed to the increased levels of stress, anxiety, and depressive thoughts among the students included among others fear and worry about their own health and the health of their loved ones, difficulty in concentrating, disruptions to sleeping patterns, decreased social interactions due to physical distancing, and increased concerns regarding academic performance. To cope with stress and anxiety, participants sought support from others and helped themselves by adopting either negative or positive coping mechanisms. Clabaugh et al. (2021) found that levels of stress and difficulty with coping with pandemic disruptions were related to neuroticism, an external locus of control, gender, and ethnicity, while a study from Mexico (Gaeta et al., 2021) discovered a relationship between university students’ self-regulated learning and emotions such as tranquillity, hope, gratitude, joy, loneliness, and disinterest, mediated by coping strategies. A study by Alemany-Arrebola et al. (2020) showed that college students with a higher level of anxiety expressed more negative emotions and declared lower academic self-efficacy. A World Bank report on tertiary education during the pandemic recognized that “[l]ong periods of self-isolation can have an adverse impact on the psychological well-being of students and staff, especially for those who live alone, international students, and students/staff who are not in their place of origin” (2020:6).
On the teacher front, Jelińska and Paradowski (2021a) demonstrated how educators’ engagement in and coping with remote instruction were moderated by gender, teaching level, mode of delivery (synchronous vs. asynchronous), and the economic status of the respective countries, while MacIntyre et al. (2020) investigated the correlates of approach and avoidant coping strategies among an international sample of language teachers during the conversion to online instruction. Our own analysis of responses from 1,149 language instructors revealed that on average, they found that the remote mode of delivery depressed students’ language progress by around 64% (!), with concern about students’ outcomes most prominent in beginner-level classes (Paradowski and Jeliǹska, under review a). Elsewhere (Paradowski and Jelińska, under review b) we analyzed how inequalities among educators related to demographics, family support, access to resources and infrastructure, and anxieties about the future influenced their psychological overload, and how this influence was mediated by their perception of student coping. We also identified predictors of stress among 435 linguistics instructors teaching online, revealing the influence of anxiety about the future, living conditions, self-acceptance, appraisal of the situational impact, course optionality, and perceived effectiveness of the virtual mode of delivery, with a mediating effect of acceptance of the virtual instructional mode (Paradowski and Jelińska, under review c). A study carried out after school reopening among teachers from the Basque Country (Ozamiz-Etxebarria et al., 2021) showed that levels of anxiety, depression and stress symptoms were influenced by gender, age, job stability, the level of education taught, and parental status. In the Philippines, Rabacal et al. (2020) revealed a moderate impact of COVID-19 on teachers’ quality of life, while Oducado et al. (2020) found that more than half of the teachers surveyed experienced moderate stress related to the epidemic, but these authors focused primarily on the health factor. Otherwise, however, studies examining the relationships between instructors’ adaptation to and well-being during the crisis teaching period and background variables have been scarce. This contribution intends to help fill the lacuna by investigating how university instructors’ sociodemographic characteristics as well as life and work circumstances affected their coping and wellness.
Wellbeing constitutes a complex and multi-dimensional construct related to life satisfaction, resilience, work outcomes, more adequate regulation strategies and better health (Keyes, 1998; Diener et al., 1999; Diener, 2009; Dodge et al., 2012; Fisher, 2014), and is defined in various ways generally within either a hedonic or a eudaimonic theoretical approach (Kesebir and Diener, 2008). According to the hedonic tradition, subjective wellbeing constitutes “a person’s cognitive and affective evaluations of his or her life” (Diener et al., 2003:63). The cognitive component reflects a sense of satisfaction with life, whereas the emotional element is composed of high positive and low negative affect referring to moods and emotions (e.g., Bradburn, 1969; Diener, 1984, 2006; Diener and Suh, 1997:200; Diener et al., 1999; Kahneman et al., 1999; Lyubomirsky and Lepper, 1999; Arthaud-Day et al., 2005; Kim-Prieto et al., 2005; De Leersnyder et al., 2013). The eudaimonic tradition in turn relies on a notion of psychological wellbeing which refers to positive psychological functioning and development covering purpose in life, autonomy, personal growth, self-esteem, acceptance, mastery, control, and positive relations with others (e.g., Rogers, 1961; Ryff, 1989a, b; Waterman, 1993; Keyes, 1998; Ryan and Deci, 2001; Keyes et al., 2002; Ryff and Singer, 2008). This theoretical approach also includes emotional and affect regulation (Korpela et al., 2018; Puente-Martínez et al., 2018), which are linked to positive self-image (including enhanced self-esteem), situation management, and relatedness (Koole, 2009).
In most theories, a key indicator of wellbeing is positive affect (Lyubomirsky et al., 2005; Cohn and Fredrickson, 2009; Kong and Zhao, 2013; Coffey et al., 2014; Szczygieł and Mikolajczak, 2017). However, existing negative emotions and mood should not be ignored as emotional wellbeing has been defined as “the ratio of positive affect (PA) to negative affect (NA) in a person’s life over a representative time period” (Larsen, 2009:249). Studies indicate that the amounts of positive and negative affect are uncorrelated (e.g., Diener and Emmons, 1985; Schmukle et al., 2002), and that their relative contribution to emotional wellbeing varies (e.g., Larsen et al., 1990).
Many researchers have indicated that the negative affect system is more reactive than the positive affect system (e.g., Ito et al., 1998; Cacioppo and Gardner, 1999; Ito and Cacioppo, 2005; Grinde, 2012). Moreover, Larsen (2002) indicated that the same levels of objectively bad and good events cause respectively higher levels of negative than positive affect. As observed by Musch and Klauer (2003), compared with positive ones, negative events engage more attentional resources and are stored more accessibly in memory. These findings lead to the conclusion that negative affect is stronger than positive affect with respect to its reactivity, duration, and cognitive processing (Larsen, 2002, 2009; Larsen and Prizmic, 2008). Individuals tend to pay more attention to negative information compared to positive information, processing and recalling the former more thoroughly (Baumeister et al., 2001; Rozin and Royzman, 2001). As a result, negative emotions and mood influence overall emotional wellbeing to a greater extent than positive ones (Larsen, 2009). For this reason, Grinde (2016) suggested that negative feelings should be included in wellbeing measures. In this study, we focus on this aspect of emotional wellbeing.
In the ongoing discussion about the relevant definition of well-being, Dodge et al. (2012:230) took into account various existing conceptualizations and characterized wellbeing as the balance between individual psychological, social and/or physical resources and psychological, social and/or physical challenges encountered in everyday life. The challenges introduce an imbalance, which in turn reduces wellbeing. To restore the equilibrium and regain their wellbeing, an individual needs to use or adapt all their resources.
This approach seems to be particularly relevant in the context of the COVID-19 pandemic and crisis shifts in life such as the abrupt transition to remote teaching, which are potential challenges disturbing teachers’ wellbeing. Studies on past infectious disease outbreaks have shown that such health emergencies impact survivors’, their families’, and affected communities’ mental health and can lead to higher levels of anxiety, PTSD, insomnia, and depression (Mohammed et al., 2015; Keita et al., 2017). Confinement and social and physical distancing can additionally exacerbate the negative symptoms and require additional relevant individual resources in order to re-establish the balance and protect wellbeing. A body of research from the COVID-19 pandemic has accordingly identified numerous stressors and risk factors for mental health, spanning but not limited to fear of or actually getting infected (Bo et al., 2020; Nguyen et al., 2020; Rogers et al., 2020), inadequate information as well as excessive consumption of negative information from social media (Gao et al., 2020), the experience of quarantine (Lei et al., 2020), infection and/or death of loved ones, stigma, social isolation and loneliness, frustration, boredom, job/wage losses and associated financial insecurities (Brooks et al., 2020; Cénat et al., 2020, 2021b; Nicola et al., 2020), among others. Not surprisingly, studies have reported increased levels of anxiety (Lee et al., 2020; Lei et al., 2020; Moghanibashi-Mansourieh, 2020), distress (Hao et al., 2020; Mazza et al., 2020), post-traumatic stress (Bo et al., 2020; Liu et al., 2020), depression (Lei et al., 2020; Nguyen et al., 2020), insomnia (Li et al., 2020), and other dimensions of psychological impact (Ahmed et al., 2020; Cao et al., 2020; Moccia et al., 2020; Xiong et al., 2020; Cénat et al., 2021a, b; Huang and Zhao, 2021) in pandemic-affected populations.
Teachers’ work is considered to be one of the most stressful professions (Frenzel et al., 2016; MacIntyre et al., 2019). Many researchers have observed that teaching is related to a lower-than-average level of mental health, poorer physical health, and lower job satisfaction, making teachers particularly vulnerable to burnout (Johnson et al., 2005; Chang, 2009; Brackett et al., 2010; Keller et al., 2014; MacIntyre et al., 2019). All these factors may significantly reduce teachers’ subjective wellbeing (Kieschke and Schaarschmidt, 2008; Woolfolk Hoy, 2008) and decrease their work effectiveness and learners’ outcomes (Klusmann et al., 2008; Day and Gu, 2009; Frenzel et al., 2016; Lee et al., 2016). In addition, in the context of the COVID-19 pandemic the conditions of living and working under lockdown could induce negative feelings and increase teachers’ negative affect. An online poll of 1,122 US faculty members conducted in October 2020 (Business Wire, 2021) revealed that more than twice as many respondents were feeling stressed, fatigued, and angry compared with the year before.
The COVID-19 pandemic enforced various challenges such as remote work, limited social interactions, and social isolation, provoking feelings of situational loneliness, which may negatively affect health and wellbeing (DiGiovanni et al., 2004; Cacioppo et al., 2010; Lin et al., 2010; Theeke, 2010; Beutel et al., 2017; Mullen et al., 2019; Son et al., 2020; Groarke et al., 2020; Nguyen et al., 2021). In the United Kingdom, 36% of adult respondents declared feeling lonely sometimes or often during the epidemic (Li and Wang, 2020). Higher loneliness was related to physical distancing and reduced social contact (Losada-Baltar et al., 2021). It was also associated with financial concerns and worries about the impact of prolonged quarantine as well as feelings of fear and uncertainty, increased depression, anxiety, stress, and an increased affective response to different aspect of the pandemic in Poland, the United Kingdom, and the United States (Brooks et al., 2020; Holmes et al., 2020; Jia et al., 2020; Kantor and Kantor, 2020; Killgore et al., 2020; Okruszek et al., 2020; Smith and Lim, 2020; Son et al., 2020; Cacioppo et al., 2021). Studies indicate that more frequent face-to-face contacts (unlike remote or virtual interactions), as well as closeness and quality of relationships moderate the negative loneliness-inducing influence of the COVID-19 pandemic and function as protective factors (Bu et al., 2020a, b; Groarke et al., 2020; Li and Wang, 2020; Tull et al., 2020; Rosenberg et al., 2021). Close, frequent and satisfying relationships constitute a basic human need and are core indicators of the social aspect of wellbeing (Baumeister and Leary, 1995; Ryan and Deci, 2000; Seligman, 2011).
The aforementioned results concern the general population. However, there is little evidence how situational anxiety and loneliness and anxiety as well as closeness of social relationships, which turned out to be significant determinants of functioning during the COVID-19 pandemic, influence the wellbeing of teachers, especially in the context of a challenge (Dodge et al., 2012) such as an emergency transition to distance instruction. In this study we examine the importance of these variables in the emotional aspect of wellbeing, alongside other factors such as perceived situational coping, work-life synergy (as an indicator of work/life satisfaction protecting against burnout) and self-perceived productivity (efficacy). We also take into account other individual factors and capital, such as teachers’ age, gender, relationship status, and years of experience, which may play a particular role in protecting wellbeing (op. cit.).
The aim of this study is accordingly to investigate factors influencing higher education (HE) teachers’ negative affect as a substantial component of emotional wellbeing (Larsen, 2002, 2009; also: Ito et al., 1998; Cacioppo and Gardner, 1999; Ito and Cacioppo, 2005; Larsen and Prizmic, 2008; Grinde, 2012) during the first few months of the COVID-19 pandemic in the context of adaptation to emergency remote teaching, thus potentially conditions more stressful than during “business as usual.” Based on Dodge et al.’s (2012) resources–challenges balance approach to wellbeing and factoring in current research pointing to situational loneliness, anxiety and social relationships as among the most significant factors influencing mental health and wellbeing during the COVID-19 pandemic, we examine their role in the professional group of HE instructors during a time of heightened vulnerability to stress and its various consequences. In line with the recommendations by Bricheno et al. (2009), apart from subjective indicators we also include objective factors potentially determining wellbeing such as gender, age, relationship status, living conditions, and the number of years of teaching experience.
The study is guided by the following exploratory research questions:
RQ1: To what extent did HE teachers’ negative affect vary depending on sociodemographic factors such as: (1a) gender, (1b) age, (1c) relationship status, (1d) living conditions, and (1e) length of experience in teaching?
RQ2: Which of the factors potentially affecting professional adaptation to emergency remote instruction in the COVID-19-related context, from among: (2a) situational loneliness, (2b) situational anxiety, (2c) family and social support, (2d) perceived self-productivity, (2e) situational coping, (2f) work-life synergy, and (2g) sociodemographic variables such as gender, age, relationship status, living conditions and length of experience in teaching, are associated with teachers’ negative affect, and to what extent?
RQ3: What is the relative contribution of the respective predictors and to what extent does each of them determine teachers’ negative affect and, consequently, emotional wellbeing?
Materials and Methods
Participants
In this contribution, we focus on survey respondents from higher education institutions. From April through September 2020 a total of 8041 HE instructors participated in the study. More than 80% were teaching at a university or graduate school. The instructors hailed from 6 continents and 92 countries and autonomous territories, half of them (52%) from Europe (Table 1). The mean reported age was 44.1 years (SD = 12.5), with over half the respondents aged between 36 and 55. Most did not report the length of their professional experience, 23% had been teaching for more than 5 years (M = 2.5, SD = 1.60), whereas 18.5% less than that. During the COVID-19 pandemic approximately three quarters were teaching synchronous classes in real time, despite more than two thirds reporting no prior experience with remote instruction.
Table 1. Socio-demographic characteristics of the participants (N = 804).
Almost 72% of the participants were female. A similar percent declared to live with their families or partners. Approximately 14% had a close other who had contracted COVID-19, and 3.5% experienced the death of a close person due to the virus.
Measures
To evaluate how the epidemic reality and remote teaching conditions affect instructors’ wellbeing, we devised an online survey composed of 441 items (Supplementary Material). It included items concerning respondents’ sociodemographics, the circumstances surrounding the participants’ transition to emergency remote instruction, their personal experiences, behaviors, attitudes, feelings, physical and mental health, and personality traits. To measure psychological constructs, 23 short scales were developed from International Personality Item Pool [IPIP] (2018), International Personality Item Pool (n.d.) items. In order to glean more multidimensional information related to the specific circumstances of the situation that could not be properly measured with existing batteries, we complemented these with custom-made scales, single-item indicators, as well as open-ended questions.
In the following analysis we focus on the relative contribution of demographic variables as well as factors measured with four short scales (Supplementary Appendix 2) and three single-item indicators:
Negative affect was measured with 11 items assessing to what extent instructors felt negative emotional states such as sadness (e.g., “I have been sad”), irritation (e.g., “I have been feeling irritable”), strain (e.g., “I feel building up pressure”), and emotional instability (e.g., “I have been having bouts of anxiety/panic attacks”) as well as symptoms of fatigue (e.g., “I feel tired during the day”). Items in this and the other scales were answered on a six-point Likert scale ranging from completely disagree to completely agree. The internal consistency of this scale was high (Cronbach’s α and McDonald’s ωh = 0.92, Guttman’s λ6 = 0.90). Positive correlations (r = 0.75, p < 0.05) with perceived stress measured by the Perceived Stress Scale (PSS; Cohen et al., 1983) and negative (r = –0.45, p < 0.05) with self-compassion measured with the short form of the Self-Compassion Scale (Raes et al., 2011) corroborate good convergent validity of the scale developed for this study.
Situational loneliness was measured with a 3-item scale assessing the extent to which teachers felt lonely (e.g., “I feel lonely”) and lacked contact with their colleagues (e.g., “I miss daily conversation with my colleagues”) during the period of lockdown. In the current study its internal consistency reached Cronbach’s α = 0.86, McDonald’s ωh = 0.85, and Guttman’s λ6 = 0.84; however, given its short length, further studies may be needed to verify its validity.
Situational anxiety caused by the COVID-19 pandemic was assessed with a 5-item scale measuring to what extent instructors felt worried about different aspects of their living conditions such as their future, job stability, housing conditions, economic situation, and concern about their family members (e.g., “I worry about my job stability”). The scale showed good internal consistency of Cronbach’s α = 0.81, McDonald’s ωh = 0.82, and Guttman’s λ6 = 0.80. Positive correlation (r = 0.47, p < 0.05) with perceived stress measured with the Perceived Stress Scale (PSS; Cohen et al., 1983) indicates relatively good convergent validity of the developed situational anxiety scale.
Family and social support was assessed with 4 items measuring to what extent the teachers felt the support and closeness of their families and significant others (e.g., “I have good relations at home,” “I feel comfortable having my family/partner/roommates/flatmates around during this time”). The scale reported good internal consistency of Cronbach’s α and McDonald’s ωh = 0.80, and Guttman’s λ6 = 0.78.
The single-item indicators concerned situational coping, work-life synergy and self-productivity, complemented with sociodemographic information such as teachers’ age, gender, relationship status, and years of professional experience. We applied the comprehensive single item approach (CSI) proposed by Konstabel et al. (2012, 2017), which assumes that the content validity of a one-item indicator is preserved when this item has a comprehensive content and is newly written instead of being selected from a longer scale. This approach is based on the assumption that every individual has self-knowledge and is able to characterize it if a given construct is sufficiently simple, unambiguous or circumscribed to be comprehensible to the respondent (Wanous and Reichers, 1996; Loo, 2002). This means that the CSI should not be applied to more complex traits or dispositions. Thus, in this research it was only used with generic and more homogenous variables.
Procedure
The custom-made online questionnaire was active from April until September 2020 on a commercial survey software platform (in order to reach respondents in countries where solutions such as Google Forms cannot be accessed without a VPN). Participant recruitment was carried out with a snowball sampling technique via several channels utilizing the researchers’ direct personal contacts, mailing lists and websites of professional associations, and thematic groups and pages on social media. Participation was voluntary and the respondents were informed about the purpose of the survey. The protocol had received IRB approval.
Eligibility required having transitioned from regular face-to-face classes to online teaching as part of the response to the COVID-19 epidemic. The filter question excluded more than 13% of the initial survey takers – persons who either continued teaching face-to-face, or who had already been teaching online before the school closures happened.
Data Analysis
To observe the differences between the variables and to answer RQ1a-1e, we calculated a t-test for relationship status and one-way ANOVAs for all the remaining sociodemographic variables. To find the answer to RQ2 concerning the extent of the association between such potential factors affecting HE teachers’ professional adaptation to emergency remote instruction in the COVID-19-related context as (2a) situational loneliness, (2b) situational anxiety, (2c) family and social support, (2d) perceived self-productivity, (2e) situational coping, (2f) work-life synergy, and (2g) sociodemographic variables such as: gender, age, relationship status, living conditions, and length of experience in teaching on the one hand, and teachers’ negative affect on the other, we calculated Pearson’s correlation coefficient for continuous variables and Spearman’s ρ for categorical variables. To study the impact of the predictive factors on negative affect as an indicator of teachers’ wellbeing, we used STATISTICA’s General Regression Models (GRM) module for building models containing categorical and continuous predictor variables (analysis of covariance design). As opposed to (multiple) regression models, applicable only to continuous variables, the general linear model permits analyses of any ANCOVA or MANCOVA design which includes both categorical (e.g., gender) and continuous predictor variables as well as a wide variety of different types of design. Analysis of covariance (ANCOVA), defined as a general linear model, combines at least one categorical predictor (i.e., one-way ANOVA) and continuous predictors (i.e., linear regression). The dependent variable(s) in such a general linear model is/are always continuous. Similarly as in the case of regression, using ANCOVA requires meeting five assumptions: normality of residuals, homogeneity of variance, homogeneity of regression slopes, linearity of regression, and independence of error terms (Garson, 2012; Philippas, 2014). In this study, a general linear model was the most suitable statistical tool as it allowed to take into account both categorical and continuous predictors. Applying forward selection, based on adding the most statistically significant variables to the model until there are no variables left meeting the entry criteria and a satisfactory regression equation has been found, underlies the answer to RQ3. This selection method allows building a purely exploratory model, which is not based on any theoretical assumptions, but on the statistically significant impact of the variables.
The linearity assumption was examined via a visual inspection of scatterplots, which indicated that the variables and the residuals of the regression (i.e., the errors between the observed and the predicted values) were normally distributed. The variance inflation factor (VIF) not exceeding 1.6 and tolerance values ranging from .64 to .94 indicated lack of multicollinearity. The lack of collinearity was also confirmed by a matrix of Pearson’s bivariate correlations among all the predictors. A visual analysis of a scatterplot of residuals versus predicted values indicated that the assumption of homoscedasticity was satisfied as well.
The significance level was set at .001 for ANCOVAs and at .05 for the remaining analyses. Effect sizes are reported with Cohen’s d for the t-test and ηp2 for ANOVA, respectively.
Results
To answer RQ1 and find out whether and to what extent HE teachers’ negative affect varied depending on sociodemographic factors such as: (1a) gender, (1b) age, (1c) relationship status, (1d) living conditions, and (1e) length of teaching experience, we carried out Student’s t-test and ANOVA. Descriptive statistics for teachers’ negative affect with respect to the sociodemographic variables are displayed in Table 2. The results indicate that in the first few months of the COVID-19 pandemic, teachers differed in their wellbeing, which reflected their negative emotional states.
Table 2. Significant differences in teachers’ negative affect (N = 804).
Significantly stronger negative moods were reported by female teachers (M = 32.61, SE = 0.53; possible value range: 11–66) compared with their male counterparts (M = 30.53, SE = 0.83). The intensity of negative affect significantly varied also between single individuals (M = 34.02, SE = 0.86) and teachers having partners or families (M = 31.50, SE = 0.53), with the former group feeling more negative emotions than the latter. The differences in negative affectivity were also age-specific; however, they were unrelated to teachers’ professional experience.
The observed differences with respect to gender, relationship status, age and length of professional experience seem to suggest that teachers’ negative affect during the COVID-19 pandemic may be related not only to psychological dispositions and states, but also to particular sociodemographic and situational variables.
To probe which of the factors affecting professional adaptation to emergency remote instruction are associated with teachers’ negative affect and to answer RQ2, we conducted correlation analyses (Table 3). Negative affect was significantly and positively correlated with higher situational anxiety (r = 0.47) and situational loneliness (r = 0.36). Moreover, the stronger the negative emotional state, the less the teachers reported work-life synergy (r = –0.43) and the less productive they felt (r = –0.33) during the pandemic. Finally, those who felt more negative emotions were also coping worse than others (r = –0.30).
Table 3. Pearson’s r[1] and Spearman’s ρ[2] correlation coefficients between negative affect and factors influencing professional adaptation to emergency remote instruction in the COVID-19-related context.
To reveal which of the factors affecting professional adaptation to emergency remote instruction predict teachers’ negative affect, as well as provide an answer to RQ3 concerning the relative contribution of the respective predictors and the extent to which each of them determines teachers’ negative affect and, consequently, emotional wellbeing, we used ANCOVA to build a stepwise regression model with the forward selection procedure. It was preceded by a simple linear regression giving more general insight into the extent to which all the factors affecting professional adaptation to emergency remote instruction predict teachers’ negative affect. The entire model, as shown in Table 4, is significant (F8,317 = 37.40, p < 0.001) and predicts approximately 49% of variance in negative affect. The most influential predictor of teachers’ negative emotional states was anxiety (β = 0.30, t = 6.82, p < 0.001), explaining approximately 22% of the variance in negative affect. The subsequent most consequential predictors turn out to be work-life synergy (β = 0.25. t = –5.81. p < 0.001) followed by teacher productivity (reduced: β = 0.26, t = 5.62, p < 0.001; unchanged: β = –0.15, t = –3.50, p < 0.001). The next important predictor is situational coping (β = 0.26, t = 3.16, p < 0.001). The last two moderator variables are teachers’ age (β = –0.16, t = –3.77, p < 0.001) and situational loneliness (β = 0.09, t = 2.04, p < 0.001). It should be noted that all the influences of these predictors have medium to large effects (Cohen, 1988). Interestingly, family and social support as well as variables such as gender, relationship status, and length of professional experience no longer contribute to the regression model. The results are presented in Table 5.
Table 4. The regression results of the effects of variables predicting teachers’ negative affect.
Table 5. General linear model with ANCOVA (forward selection stepwise regression) for variables predicting teachers’ negative affect.
Discussion and Conclusion
The current COVID-19 pandemic is unprecedented in scale, as are the nearly global school closures that have gone along with it. The well-being of students and instructors has been upended, to the extent that many instructors started contemplating quitting the profession (Business Wire, 2021; Gewin, 2021). The current study has attempted to reveal some of the mechanisms responsible for college and university instructors’ differential coping with the transition and wellness, with the resultant model predicting approximately 49% of variance in negative affect.
The impact of anxiety was prominent not only in the statistics, but was also a recurrent theme in the open-ended questions, where the respondents repeatedly mentioned “anxiety and fear about the pandemic,” “general anxiety about the world right now,” “anxiety, workload, uncertainty,” “my own personal struggle with anxiety increasing due to covid,” and “the uncertainty and anxiety surrounding the state of the world in general.”
The impact of gender on anxiety (albeit with only a very small effect size) mirrors the findings by Alemany-Arrebola et al. (2020) among college students, where women had higher scores in trait and state anxiety; the latter accentuated in cases where a relative had died – thus showing that the stressful situation of the pandemic and remote learning together with a critical event such as the illness and death of a relative or friend due to COVID-19 increases anxiety levels (and—in the case of the original study—influences the perception of academic self-efficacy). A similar conclusion was reported in Turkey by Aslan et al. (2020), where female (as well as less physically active) students displayed higher levels of perceived stress and by Karaman et al. (2021), in Switzerland by Amendola et al. (2021), and in the US (Business Wire, 2021; Clabaugh et al., 2021), while among teachers a similar trend was observed in the Basque Country (Ozamiz-Etxebarria et al., 2021). In the general population, three studies carried out in Italy (Mazza et al., 2020; Moccia et al., 2020) and Iran (Moghanibashi-Mansourieh, 2020) showed women’s mental health to be more impacted than men’s; on the other hand, research in China (Cao et al., 2020; Chen et al., 2020; Huang and Zhao, 2021) and a meta-analysis by Cénat et al. (2021a) of papers again mainly hailing from this country found no gender differences in females’ and males’ experience of pandemic-related stressors. A comparison of the results implies a possible role of context (teaching/studying vs others) influencing the potential role of gender in perceived situational anxiety.
Apprehension about job stability could be alleviated by institutions making furlough arrangements for all faculty and suspensions of staff dismissals at least during the period of the crisis, in line with recommendations by the World Bank, since “faculty dismissed at this time will find it almost impossible to secure alternative employment amid the crisis” (2020:10).
The adverse impact of loneliness is fairly straightforward and, as with anxiety, was a recurrent theme in the answers to the open-ended questions, which frequently mentioned “isolation, not being able to interact with my students, not being able to teach them;” “I feel isolated. The teaching is fine, but I have had very little interaction with colleagues, which makes me feel irrelevant;” “lack of contact with the students. I felt very isolated and like I was talking into the void;” “the isolation and feeling that I am not connecting with students and fellow teachers in my school;” or “disconnection from students.” Loneliness constitutes an emotional experience provoked by unfulfilled needs for social contact (Margalit, 2010). Cacioppo and Hawkley (2009) point out that the experience of loneliness impairs individual ability to self-regulate affecting physiological, cognitive and emotional functioning. It may constitute an important risk factor for depressive symptoms even for healthy people (Cacioppo et al., 2006; Grov et al., 2010). Neto and Barros (1992) in their study examining loneliness among teachers found that educators whose professional experience was longer than 20 years were significantly lonelier than those with a shorter professional experience; the former group also experienced lowered self-efficacy, which constitutes one of the predictors of job satisfaction (Lent and Brown, 2006; Duffy and Lent, 2009). While loneliness is usually a temporary state, COVID-19-induced lockdown and social distancing may have extended it. Lack of personal contact with teachers and longing for live communication during the lesson were downsides of remote instruction indicated by around 80% of the students in a study by Karalis and Raikou (2020).
The significance of the right work-life synergy and maintaining the right priorities is especially important in view of the reality that ensuring of teacher and student well-being may sometimes be at odds with pressures to “cover the syllabus”: “[t]here is a potential tradeoff between ensuring well-being and significantly increased screen time derived from a transition to distance learning” (Reimers and Schleicher, 2020:8). Our findings from a sample of nearly 1,500 educators (Jelińska and Paradowski, 2021a) showed that the most engaged and best-coping teachers were characterized by having modified their lesson plans and eased the grading scheme during this period.
Teacher well-being should never be forgotten, neither by administrators nor teachers themselves. Already in the spring of 2020, a guide published by the OECD recommended that:
Second only to supporting learning, a key priority of education institutions should be the well-being of students and staff… A protracted pandemic, and its multiple effects in the health, income and well-being of individuals and communities, is likely to strain the psychological reserves of all, including students and teachers. Educators and leaders of education systems should make explicit and visible their goals for well-being, and pursue strategies that help maintain well-being in the face of a global health event that will have a considerable toll in the lives and health of individuals… As such impact becomes proximal to every learner and educator, this may impact their motivation and functioning. (Reimers and Schleicher, 2020:7f).
At the time of writing this paper, a discussion is ranging in the press and on teacher groups in the social media concerning the coverage of a story where a teacher has been giving lessons from her hospital bed following a surgery. While many news outlets were portraying the action as a model and inspiration, most teachers have rightly expressed frustration at the unhealthy, dystopian expectations of a broken education system. Teachers deserve a humanistic approach, especially during the added strain of emergency remote instruction. Our respondents commented: “Thank you for sharing this survey! I enjoyed completing it, and thought it was one of the more comprehensive and compassionate surveys I’ve done during this time.”; “Just completed this survey and I too would HIGHLY recommend that you spend some time completing it. It’s LONG as surveys go, so grab yourself a good cup of tea/coffee and some nibbles and find yourself a quiet space, it’s going take over half an hour, but I can safely say I have never felt that a survey could be life affirming but this is! It actually made me feel better. It’s like your own personal therapist at these difficult times. Thank you! Well done.” and “I was able to relate all the questions to my experiences. I appreciated that the survey seemed to focus on the educator as a whole person rather than just a ‘provider of lessons and materials.’,” underlining the importance of seeing teachers in a holistic and humanistic manner.
Despite the challenges of emergency remote teaching, HE instructors are in a privileged position compared with most of their counterparts teaching at lower levels of education, as the education level handled has already turned out to be a significant predictor of coping and engagement (Jelińska and Paradowski, 2021a).
The post-pandemic world may see the trend of classes becoming more blended (Bozkurt, 2019; Kim, 2020), integrating conventional face-to-face instruction with online learning (Garrison and Kanuka, 2004; Dziuban et al., 2018). The “new normal” will hopefully remove most of the current stressors, but awareness of the variables influencing teacher coping and well-being will be nonetheless be useful to both teachers and administrators.
One of the obvious limitations, shared by most large-scale surveys, is the issue of participant self-selection. Given that participation in this study was completely voluntary, and that on many occasions the questionnaire took upwards of 45 min to complete, the respondents were already motivated, could relate to the topic, and had the spare time and technology to comfortably fill it out. This means a limit on the representativeness and generalization potential of the data and resultant findings (see Brown, 2001:85).
This university instructors’ perspective will be complemented with later publications on other relevant aspects of educators’ adaptation to the transition, as well as analyses of students’ points of view.
Data Availability Statement
The data analyzed in this study is subject to the following licenses/restrictions: The data are part of a larger project still in progress. Requests to access these datasets should be directed to MBP, https://schoolclosure.ils.uw.edu.pl.
Ethics Statement
The survey protocol had been reviewed and approved by University of Warsaw’s Human Research Ethics Committee. The respondents were provided with information about the survey and participated voluntarily.
Author Contributions
MBP conceptualized the study, designed the survey instrument, piloted and administered the data collection, and contributed to the interpretation of the data and the writing of the article. MJ contributed to the survey instrument, carried out the quantitative analyses, and contributed to the writing of the article. Both authors approved the submitted version.
Funding
The authors are supported by the SONATA-BIS Grant No. 2016/22/E/HS2/00034 from the National Science Centre of Poland. MBP also acknowledges support from COST Actions 15109 COSTNET, 15130 SAREP, and 18232 MAT-DYN-NET.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments
We thank the volunteers who completed and provided feedback on the pilot versions of the survey, all the participants who took the time to fill in the questionnaire despite other commitments, as well as friends, colleagues, professional associations, and administrators of the thematic groups on social media for publicizing and/or enabling to share information about the survey. We also thank Adaora Anyichie-Odis, lmran Aslan, and Ryan Michael Oducado for comments on an earlier draft of this article, and TA and SC for detailed and constructive feedback.
Supplementary Material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2021.643229/full#supplementary-material
Footnotes
- ^ The data analysed in this paper form part of a much larger project https://schoolclosure.ils.uw.edu.pl that also included educators teaching in the K–12 track as well as student populations. These latter data are omitted from the analyses herein. For reasons of space and thematic coherence, we also exclude a presentation and discussion of other contextual findings as well as those from the battery of psychological tests that concluded the questionnaire.
References
Ahmed, M. Z., Ahmed, O., Aibao, Z., Hanbin, S., Siyu, L., and Ahmad, A. (2020). Epidemic of COVID-19 in China and associated psychological problems. Asian J. Psychiatr. 51:102092. doi: 10.1016/j.ajp.2020.102092
Alemany-Arrebola, I., Rojas-Ruiz, G., Granda-Vera, J., and Custodio Mingorance-Estrada, Á (2020). Influence of COVID-19 on the perception of academic self-efficacy, state anxiety, and trait anxiety in college students. Front. Psychol. 11:570017. doi: 10.3389/fpsyg.2020.570017
Alvarez, A. V. (2020). The phenomenon of learning at a distance through emergency remote teaching amidst the pandemic crisis. Asian J. Distance Educ. 15, 127–143.
Amendola, S., von Wyl, A., Volken, T., Zysset, A., Huber, M., and Dratva, J. (2021). A longitudinal study on generalized anxiety among university students during the first wave of the COVID-19 pandemic in switzerland. Front. Psychol. 12:643171. doi: 10.3389/fpsyg.2021.643171
Arthaud-Day, M. L., Rode, J. C., Mooney, C. H., and Near, J. P. (2005). The subjective well-being construct: a test of its convergent, discriminant, and factorial validity. Soc. Indic. Res. 74, 445–476. doi: 10.1007/s11205-004-8209-6
Aslan, I., Ochnik, D., and Çınar, O. (2020). Exploring perceived stress among students in turkey during the COVID-19 pandemic. Int. J. Environ. Res. Public Health 17:8961. doi: 10.3390/ijerph17238961
Awoke, M., Mamo, G., Abdu, S., and Terefe, B. (2021). Perceived stress and coping strategies among undergraduate health science students of jimma university amid the COVID-19 outbreak: online cross-sectional survey. Front. Psychol. 12:639955. doi: 10.3389/fpsyg.2021.639955
Baumeister, R. F., and Leary, M. R. (1995). The need to belong: desire for interpersonal attachments as a fundamental human motivation. Psychol. Bull. 117, 497–529. doi: 10.1037/0033-2909.117.3.497
Baumeister, R. F., Bratslavsky, E., Finkenauer, C., and Vohs, K. D. (2001). Bad is stronger than good. Rev. Gen. Psychol. 5, 323–370. doi: 10.1037/1089-2680.5.4.323
Bensaid, B., and Brahimi, T. (2021). “Coping with COVID-19: higher education in the GCC countries,” in Research and Innovation Forum 2020: Disruptive Technologies in Times of Change, Chap. 12, eds A. Visvizi, M. D. Lytras, and N. F. Aljohani (Berlin: Springer), doi: 10.1007/978-3-030-62066-0
Beutel, M. E., Klein, E. M., Brähler, E., Reiner, I., Jünger, C., Michal, M., et al. (2017). Loneliness in the general population: prevalence, determinants and relations to mental health. BMC Psychiatry 17:97. doi: 10.1186/s12888-017-1262-x
Bo, H. X., Li, W., Yang, Y., Wang, Y., Zhang, Q., Cheung, T., et al. (2020). Posttraumatic stress symptoms and attitude toward crisis mental health services among clinically stable patients with COVID-19 in China. Psychol. Med. 1–2. doi: 10.1017/S0033291720000999
Bozkurt, A. (2019). “From distance education to open and distance learning: a holistic evaluation of history, definitions, and theories,” in Handbook of Research on Learning in the Age of Transhumanism eds S. Sisman-Ugur and G. Kurubacak (Hershey, PA: IGI Global), 252–273. doi: 10.4018/978-1-5225-8431-5.ch016
Brackett, M. A., Palomera, R., Mojsa-Kaja, J., Reyes, M. R., and Salovey, P. (2010). Emotion-regulation ability, burnout, and job satisfaction among British secondary-school teachers. Psychol. Sch. 47, 406–417. doi: 10.1002/pits.20478
Bricheno, P., Brown, S., and Lubansky, R. (2009). Teacher Well-Being: A Review of the Evidence. London: Teacher Support Network.
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., et al. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet 395, 912–920. doi: 10.1016/S0140-6736(20)30460-8
Bu, F., Steptoe, A., and Fancourt, D. (2020a). Loneliness during a strict lockdown: trajectories and predictors during the COVID-19 pandemic in 38,217 United Kingdom adults. Soc. Sci. Med. 265:113521. doi: 10.1016/j.socscimed.2020.113521
Bu, F., Steptoe, A., and Fancourt, D. (2020b). Who is lonely in lockdown? Cross-cohort analyses of predictors of loneliness before and during the COVID-19 pandemic. Public Health 186, 31–34. doi: 10.1016/j.puhe.2020.06.036
Business Wire (2021). Fidelity Investments & The Chronicle of Higher Education Study: More Than Half of College and University Faculty Considering Leaving Teaching, Citing Burnout Caused by Pandemic. Available online at: https://www.businesswire.com/news/home/20210225005616/en/Fidelity-Investments-The-Chronicle-of-Higher-Education-Study-More-Than-Half-of-College-and-University-Faculty-Considering-Leaving-Teaching-Citing-Burnout-Caused-by-Pandemic (accessed March 15, 2021).
Cacioppo, J. T., and Hawkley, L. C. (2009). Perceived social isolation and cognition. Trends Cogn. Sci. 13, 447–454. doi: 10.1016/j.tics.2009.06.005
Cacioppo, J. T., Hawkley, L. C., and Thisted, R. A. (2010). Perceived social isolation makes me sad: five year cross-lagged analyses of loneliness and depressive symptomatology in the chicago health, aging, and social relations study. Psychol. Aging 25, 453–463. doi: 10.1037/a0017216
Cacioppo, J. T., Hughes, M. E., Waite, L. J., Hawkley, L. C., and Thisted, R. A. (2006). Loneliness as a specific risk factor for depressive symptoms: cross-sectional and longitudinal analyses. Psychol. Aging 21, 140–151. doi: 10.1037/0882-7974.21.1.140
Cacioppo, M., Bouvier, S., Bailly, R., Houx, L., Lempereur, M., Mensah-Gourmel, J., et al. (2021) Emerging health challenges for children with physical disabilities and their parents during the COVID-19 pandemic: the ECHO French survey. Ann. Physical Rehab. Med. 64:101429. doi: 10.1016/j.rehab.2020.08.001
Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., et al. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 287:112934. doi: 10.1016/j.psychres.2020.112934
Clabaugh, A., Duque, J. F., and Fields, L. J. (2021). Academic stress and emotional well-being in united states college students following onset of the COVID-19 pandemic. Front. Psychol. 12:628787. doi: 10.3389/fpsyg.2021.628787
Diener, E. (2006). Guidelines for National Indicators of Subjective Well-Being and Ill-Being. Appl. Res. Qual. Life 1, 151–157. doi: 10.1007/s11482-006-9007-x
Dikaya, L. A., Avanesian, G., Dikiy, I. S., Kirik, V. A., and Egorova, V. A. (2021). How personality traits are related to the attitudes toward forced remote learning during COVID-19: predictive analysis using generalized additive modeling. Front. Educ. 6:629213. doi: 10.3389/feduc.2021.629213
Lee, S. A., Jobe, M. C., and Mathis, A. A. (2020). Mental health characteristics associated with dysfunctional coronavirus anxiety. Psychol. Med. 1–2. doi: 10.1017/S003329172000121X
Cénat, J. M., Blais-Rochette, C., Kokou-Kpolou, C. K., Noorishad, P.-G., Mukunzi, J. N., McIntee, S. E., et al. (2021a). Prevalence of symptoms of depression, anxiety, insomnia, posttraumatic stress disorder, and psychological distress among populations affected by the COVID-19 pandemic: a systematic review and meta-analysis. Psychiatry Res. 295:113599. doi: 10.1016/j.psychres.2020.113599
Cénat, J. M., Dalexis, R. D., Guerrier, M., Noorishad, P.-G., Derivois, D., Bukaka, J., et al. (2021b). Frequency and correlates of anxiety symptoms during the COVID-19 pandemic in low- and middleincome countries: a multinational study. J. Psychiatr. Res. 132, 13–17. doi: 10.1016/j.jpsychires.2020.09.031
Cénat, J. M., Dalexis, R. D., Kokou-Kpolou, C. K., Mukunzi, J. N., and Rousseau, C. (2020). Social inequalities and collateral damages of the COVID-19 pandemic: when basic needs challenge mental health care. Int. J. Public Health 65, 717–718. doi: 10.1007/s00038-020-01426-y
Chang, M. (2009). An appraisal perspective of teacher burnout: examining the emotional work of teachers. Educ. Psychol. Rev. 21, 193–218. doi: 10.1007/s10648-009-9106-y
Chen, Y., Zhou, H., Zhou, Y., and Zhou, F. (2020). Prevalence of self-reported depression and anxiety among pediatric medical staff members during the COVID-19 outbreak in Guiyang, China. Psychiatry Res. 288:113005. doi: 10.1016/j.psychres.2020.113005
Coffey, J. K., Warren, M., and Gottfried, A. (2014). Does infant happiness forecast adult life satisfaction? Examining subjective well-being in the first quarter century of life. J. Happiness. Stud. 16, 1401–1421. doi: 10.1007/s10902-014-9556-x
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences, 2nd Edn. Hillsdale, NJ: Erlbaum.
Cohen, S., Kamarck, T., and Mermelstein, R. (1983). A global measure of perceived stress. J. Health Soc. Behav. 24, 386–396. doi: 10.2307/2136404
Cohn, M., and Fredrickson, B. (2009). “Positive emotions,” in Oxford Handbook of Positive Psychology, 2nd Edn, eds S. J. Lopez and C. R. Snyder (New York, NY: Oxford University Press), 13–24.
Day, C., and Gu, Q. (2009). “Teacher emotions: well-being and effectiveness,” in Advances in Teacher Emotion Research, eds P. A. Schutz and M. Zemblyas (Boston, MA: Springer), 15–31. doi: 10.1007/978-1-4419-0564-2_2
De Leersnyder, J., Boiger, M., and Mesquita, B. (2013). Cultural regulation of emotion: individual, relational, and structural sources. Front. Psychol. 4:55. doi: 10.3389/fpsyg.2013.00055
Diener, E. (1984). Subjective well-being. Psychol. Bull. 95, 542–575. doi: 10.1037/0033-2909.95.3.542
Diener, E. (2009). “Subjective well-being,” in The Science of Well-Being, ed. E. Diener (New York, NY: Springer), 11–58.
Diener, E., and Emmons, R. A. (1985). The independence of positive and negative affect. J. Personal. Soc. Psychol. 47, 1105–1117. doi: 10.1037/0022-3514.47.5.1105
Diener, E., Oishi, S., and Lucas, R. E. (2003). Personality, culture, and subjective well-being: emotional and cognitive evaluations of life. Annu. Rev. Psychol. 54, 403–425. doi: 10.1146/annurev.psych.54.101601.145056
Diener, E., and Suh, E. (1997). Measuring quality of life: economic, social, and subjective indicators. Soc. Indic. Res. 40, 189–216. doi: 10.1023/A:1006859511756
Diener, E., Suh, M., Lucas, E., and Smith, H. (1999). Subjective well-being: three decades of progress. Psychol. Bull. 125, 276–302. doi: 10.1037/0033-2909.125.2.276
DiGiovanni, C., Conley, J., Chiu, D., and Zaborski, J. (2004). Factors influencing compliance with quarantine in Toronto during the 2003 SARS outbreak. Biosecur. Bioterr. 2, 265–272. doi: 10.1089/bsp.2004.2.265
Dodge, R., Daly, A. P., Huyton, J., and Sanders, L. D. (2012). The challenge of defining wellbeing. Int. J. Wellb. 2, 222–235. doi: 10.5502/ijw.v2i3.4
Duffy, R. D., and Lent, R. W. (2009). Test of a social cognitive model of work satisfaction in teachers. J. Vocat. Behav. 75, 212–223. doi: 10.1016/j.jvb.2009.06.001
Duong, V., Pham, P., Yang, T., Wang, Y., and Luo, J. (2020). The ivory tower lost: how college students respond differently than the general public to the COVID-19 pandemic. arxiv [Preprint]. Available online at: https://arxiv.org/abs/2004.09968 (accessed December 16, 2020).
Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., and Sicilia, N. (2018). Blended learning: the new normal and emerging technologies. Int. J. Educ. Technol. Higher Educ. 15:3. doi: 10.1186/s41239-017-0087-5
Fischer, K. (2020). Confronting the seismic impact of COVID-19: the need for research. J. Int. Stud. 10, i–ii. doi: 10.32674/jis.v10i2.2134
Fisher, C. D. (2014). “Conceptualizing and measuring wellbeing at work,” in Work and Wellbeing: Wellbeing: A Complete Reference Guide, Vol. III, eds P. Y. Chen and C. L. Cooper (Hoboken, NJ: Wiley), 1–25. doi: 10.1002/9781118539415.wbwell018 Work and Wellbeing.
Frenzel, A. C., Daniels, L. M., Durksen, T., Klassen, R., Becker-Kurz, B., and Klassen, R. M. (2016). Measuring teachers’ enjoyment, anger, and anxiety: the teacher emotions scales (TES). Contemp. Educ. Psychol. 46, 148–163. doi: 10.1016/j.cedpsych.2016.05.003
Gaeta, M. L., Gaeta, L., and Rodriguez, Md. S. (2021). The impact of COVID-19 home confinement on mexican university students: emotions, coping strategies, and self-regulated learning. Front. Psychol. 12:642823. doi: 10.3389/fpsyg.2021.642823
Gao, J., Zheng, P., Jia, Y., Chen, H., Mao, Y., Chen, S., et al. (2020). Mental health problems and social media exposure during COVID-19 outbreak. PLoS One 15:e0231924. doi: 10.1371/journal.pone.0231924
Garrison, D. R., and Kanuka, H. (2004). Blended learning: uncovering its transformative potential in higher education. Int. Higher Educ. 7, 95–105. doi: 10.1016/j.iheduc.2004.02.001
Garson, G. D. (2012). Univariate GLM, ANOVA, & ANCOVA. Asheboro, NC: Statistical Associates Publishers.
Gewin, W. (2021). Pandemic burnout is rampant in academia. Nature 591, 489–491. doi: 10.1038/d41586-021-00663-2 (accessed March 15, 2021).
Grinde, B. (2016). Why negative feelings are important when assessing well-being. J. Happiness Stud. 17, 1741–1752. doi: 10.1007/s10902-015-9667-z
Groarke, J. M., Berry, E., Graham-Wisener, L., McKenna-Plumley, P. E., McGlinchey, E., and Armour, C. (2020). Loneliness in the UK during the COVID-19 pandemic: cross-sectional results from the COVID-19 psychological wellbeing study. PLoS One 15:e0239698. doi: 10.1371/journal.pone.0239698
Grov, C., Golub, S. A., Parsons, J. T., Brennan, M., and Karpiak, S. E. (2010). Loneliness and HIV-related stigma explain depression among older HIV-positive adults. AIDS Care 22, 630–639. doi: 10.1080/09540120903280901
Hao, X., Zhou, D., Li, Z., Zeng, G., Hao, N., Li, E., et al. (2020). Severe psychological distress among patients with epilepsy during the COVID-19 outbreak in southwest China. Epilepsia 61, 1166–1173. doi: 10.1111/epi.16544
Hodges, C., Moore, S., Lockee, B., Trust, T., and Bond, A. (2020). The Difference Between Emergency Remote Teaching and Online Learning. Boulder, CO: Educause Review.
Holmes, E. A., O’Connor, R. C., Perry, V. H., Tracey, I., Wessely, S., Arseneault, L., et al. (2020). Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry 7, 547–560. doi: 10.1016/S2215-0366(20)30168-1
Huang, Y., and Zhao, N. (2021). Mental health burden for the public affected by the COVID-19 outbreak in China: who will be the high-risk group? Psychol. Health Med. 26, 23–34. doi: 10.1080/13548506.2020.1754438
International Labour Organization (2020). COVID-19 and the Education Sector. Available at: https://www.ilo.org/sector/Resources/publications/WCMS_742025/lang–en/index.htm (accessed Jun 2020).
International Personality Item Pool [IPIP] (2018). Administering IPIP Measures, With a 50-Item Sample Questionnaire. Available at: https://ipip.ori.org/new_ipip-50-item-scale.htm (accessed December 16, 2020).
International Personality Item Pool (n.d.). A Scientific Collaboratory for the Development of Advanced Measures of Personality Traits and Other Individual Differences. Available online at: http://ipip.ori.org/ (accessed December 16, 2020).
Ito, T. A., and Cacioppo, J. T. (2005). Variations on a human universal: individual differences in positivity offset and negativity bias. Cogn. Emot. 19, 1–26. doi: 10.1080/02699930441000120
Ito, T. A., Larsen, J., Smith, N., and Cacioppo, J. (1998). Negative information weighs more heavily on the brain: the negativity bias in evaluative categorizations. J. Personal. Soc. Psychol. 75, 887–900. doi: 10.1037/0022-3514.75.4.887
Jelińska, M., and Paradowski, M. B. (2021a). Teachers’ engagement in and coping with emergency remote instruction during COVID-19-induced school closures: a multi-national contextual perspective. Online Learn. J. 25, 303–328. doi: 10.24059/olj.v25i1.2492
Jelińska, M., and Paradowski, M. B. (2021b). Teachers’ perception of student coping with emergency remote instruction during the COVID-19 pandemic: The relative impact of educator demographics and professional adaptation and adjustment. Front. Psychol. 12:648443. doi: 10.3389/fpsyg.2021.648443
Jia, R., Ayling, K., Chalder, T., Massey, A., Broadbent, E., Coupland, C., et al. (2020). Mental health in the UK during the COVID-19 pandemic: cross-sectional analyses from a community cohort study. BMJ Open 10:e040620. doi: 10.1136/bmjopen-2020-040620
Johnson, S., Cooper, C., Cartwright, S., Donald, I., Taylor, P., and Millet, C. (2005). The experience of work-related stress across occupations. J. Manag. Psychol. 20, 178–187. doi: 10.1108/02683940510579803
Kahneman, D., Diener, E., and Schwarz, N. (eds) (1999). Well-Being: Foundations of Hedonic Psychology. New York, NY: Russell Sage Foundation.
Kantor, B. N., and Kantor, J. (2020). Mental health outcomes and associations during the COVID-19 pandemic: a cross-sectional population-based study in the United States. Front. Psychiatry 11:569083. doi: 10.3389/fpsyt.2020.569083
Karalis, T. (2020). Planning and evaluation during educational disruption: lessons learned from COVID-19 pandemic for treatment of emergencies in education. Eur. J. Educ. Stud. 7, 125–142. doi: 10.5281/zenodo.3789022
Karalis, T., and Raikou, N. (2020). Teaching at the times of COVID-19: inferences and implications for higher education pedagogy. Int. J. Acad. Res. Bus. Soc. Sci. 10, 479–493. doi: 10.6007/IJARBSS/v10-i5/7219
Karaman, M. A., Eşici, H., Tomar, İ. H., and Aliyev, R. (2021). COVID-19: Are school counseling services ready? Students’ psychological symptoms, school counselors’ views, and solutions. Front. Psychol. 12:647740. doi: 10.3389/fpsyg.2021.647740
Keita, M. M., Taverne, B., Sy Savané, S., March, L., Doukoure, M., Sow, M. S., et al. (2017). Depressive symptoms among survivors of Ebola virus disease in Conakry (Guinea): preliminary results of the PostEboGui cohort. BMC Psychiatry 17:127. doi: 10.1186/s12888-017-1280-8
Keller, M. M., Chang, M.-L., Becker, E. S., Goetz, T., and Frenzel, A. C. (2014). Teachers’ emotional experiences and exhaustion as predictors of emotional labor in the classroom: an experience sampling study. Front. Psychol. 5:1442. doi: 10.3389/fpsyg.2014.01442
Kesebir, P., and Diener, E. (2008). In pursuit of happiness: empirical answers to philosophical questions. Perspect. Psychol. Sci. 3, 117–125. doi: 10.1111/j.1745-6916.2008.00069.x
Keyes, C. L. M., Shmotkin, D., and Ryff, C. D. (2002). Optimizing well-being: the empirical encounter of two traditions. J. Personal. Soc. Psychol. 82, 1007–1022. doi: 10.1037/0022-3514.82.6.1007
Khodabakhshi-Koolaee, A. (2020). Living in home quarantine: analyzing psychological experiences of college students during Covid-19 pandemic. J. Milit. Med. 22, 130–138. doi: 10.30491/JMM.22.2.130
Kieschke, U., and Schaarschmidt, U. (2008). Professional commitment and health among teachers in Germany: a typological approach. Learn. Instr. 18, 429–437. doi: 10.1016/j.learninstruc.2008.06.005
Killgore, W. D. S., Cloonan, S. A., Taylor, E. C., and Dailey, N. S. (2020). Loneliness: a signature mental health concern in the era of COVID-19. Psychiatry Res. 290:113117. doi: 10.1016/j.psychres.2020.113117
Kim, J. (2020). Teaching and Learning After COVID-19: Three Post-Pandemic Predictions. Washington, DC: Inside Higher Ed.
Kim-Prieto, C., Diener, E., Tamir, M., Scollon, C., and Diener, M. (2005). Integrating the diverse definitions of happiness: a time-sequential framework of subjective well-being. J. Happiness Stud. 6, 261–300. doi: 10.1007/s10902-005-7226-8
Klusmann, U., Kunter, M., Trautwein, U., Lüdtke, O., and Baumert, J. (2008). Teachers’ occupational well-being and quality of instruction: the important role of self-regulatory patterns. J. Educ. Psychol. 100, 702–715. doi: 10.1037/0022-0663.100.3.702
Kong, F., and Zhao, J. (2013). Affective mediators of the relationship between trait emotional intelligence and life satisfaction in young adults. Personal. Individ. Differ. 54, 197–201. doi: 10.1016/j.paid.2012.08.028
Konstabel, K., Lönnqvist, J.-E., Leikas, S., Garcia Velázquez, R., Qin, H., Verkasalo, M., et al. (2017). Measuring single constructs by single items: constructing an even shorter version of the Short Five personality inventory. PLoS One 12:e0182714. doi: 10.1371/journal.pone.0182714
Konstabel, K., Lönnqvist, J.-E., Walkowitz, G., Konstabel, K., and Verkasalo, M. (2012). The ‘Short Five’ (S5): measuring personality traits using comprehensive single items. Eur, J, Personal. 26, 13–29. doi: 10.1002/per.813
Koole, S. L. (2009). The psychology of emotion regulation: an integrative review. Cogn. Emot. 23, 4–41. doi: 10.1080/02699930802619031
Korpela, K. M., Pasanen, T. P., Repo, V., Hartig, T., Staats, H., Mason, M., et al. (2018). Environmental strategies of affect regulation and their associations with subjective well-being. Front. Psychol. 9:562. doi: 10.3389/fpsyg.2018.00562
Larsen, R. (2009). The contributions of positive and negative affect to emotional well-being. Psychol. Top. 18, 247–266.
Larsen, R. J. (2002). “Differential contributions of positive and negative affect to subjective well-being,” in Annual Meeting of the International Society for Psychophysics, Vol. 18, eds J. A. Da Silva, E. H. Matsushima, and N. P. Riberio-Filho (Rio de Janeiro: Editora Legis Summa), 186–190.
Larsen, R. J., Cruz, M., Ketelaar, T., Welsh, W., and Billings, D. (1990). Individual differences in trait happiness and physiological response to emotional stimuli [Abstracts of Papers That Will Be Presented at the Thirtieth Annual Meeting of the Society for Psychophysiological Research]. Psychophysiology 27(Suppl. 4A):47. doi: 10.1111/j.1469-8986.1990.tb02374.x
Larsen, R. J., and Prizmic, Z. (2008). “The regulation of emotional well-being: overcoming the hedonic treadmill,” in The Science of Subjective Well-Being, eds M. Eid and R. J. Larsen (New York, NY: Guilford), 258–289.
Lee, M., Pekrun, R., Taxer, J. L., Schutz, P. A., Vogl, E., and Xie, X. (2016). Teachers’ emotions and emotion management: integrating emotion regulation theory with emotional labor research. Soc. Psychol. Educ. 19, 843–863. doi: 10.1007/s11218-016-9359-5
Lei, L., Huang, X., Zhang, S., Yang, J., Yang, L., and Xu, M. (2020). Comparison of prevalence and associated factors of anxiety and depression among people affected by versus people unaffected by quarantine during the COVID-19 epidemic in Southwestern China. Med. Sci. Monit. 26, e924609-1–e924609-12. doi: 10.12659/msm.924609
Lent, R. W., and Brown, S. D. (2006). Integrating person and situation perspectives on work satisfaction: a social-cognitive view. J. Vocat. Behav. 26, 236–247. doi: 10.1016/j.jvb.2006.02.006
Li, L. Z., and Wang, S. (2020). Prevalence and predictors of general psychiatric disorders and loneliness during COVID-19 in the United Kingdom. Psychiatry Res. 291:113267. doi: 10.1016/j.psychres.2020.113267
Li, Y., Qin, Q., Sun, Q., Sanford, L. D., Vgontzas, A. N., and Tang, X. (2020). Insomnia and psychological reactions during the COVID-19 outbreak in China. J. Clin. Sleep Med. 16, 1417–1418. doi: 10.5664/jcsm.8524
Lin, E. C. L., Peng, Y. C., and Tsai, J. C. H. (2010). Lessons learned from the anti-SARS quarantine experience in a hospital-based fever screening station in Taiwan. Am. J. Infect. Control 38, 302–307. doi: 10.1016/j.ajic.2009.09.008
Liu, N., Zhang, F., Wei, C., Jia, Y., Shang, Z., Sun, L., et al. (2020). Prevalence and predictors of PTSS during COVID-19 outbreak in China hardest-hit areas: gender differences matter. Psychiatry Res. 287:112921. doi: 10.1016/j.psychres.2020.112921
Loo, R. (2002). A caveat on using single-item versus multiple-item scales. J. Manag. Psychol. 17, 68–75. doi: 10.1108/02683940210415933
Losada-Baltar, A., Jiménez-Gonzalo, L., Gallego-Alberto, L., Pedroso-Chaparro, M., Fernandes-Pires, J., and Márquez-González, M. (2021). “We Are Staying at Home.” association of self-perceptions of aging, personal and family resources, and loneliness with psychological distress during the lock-down period of COVID-19. J. Gerontol. Ser. B 76, e10–e16. doi: 10.1093/geronb/gbaa048
Lyubomirsky, S., King, L., and Diener, E. (2005). The benefits of frequent positive affect: does happiness lead to success? Psychol. Bull. 131, 803–855. doi: 10.1037/0033-2909.131.6.803
Lyubomirsky, S., and Lepper, H. S. (1999). A measure of subjective happiness: preliminary reliability and construct validation. Soc. Indic. Res. 46, 137–155. doi: 10.1023/A:1006824100041
MacIntyre, P. D., Gregersen, T., and Mercer, S. (2020). Language teachers’ coping strategies during the Covid-19 conversion to online teaching: correlations with stress, wellbeing and negative emotions. System 94:102352. doi: 10.1016/j.system.2020.102352
MacIntyre, P. D., Ross, J., Talbot, K., Mercer, S., Gregersen, T., and Banga, C. A. (2019). Stressors, personality and wellbeing among language teachers. System 82, 26–38. doi: 10.1016/j.system.2019.02.013
Margalit, M. (2010). Lonely Children and Adolescents: Self-Perceptions, Social Exclusion and Hope. New York, NY: Springer, doi: 10.1007/978-1-4419-6284-3
Mazza, C., Ricci, E., Biondi, S., Colasanti, M., Ferracuti, S., Napoli, C., et al. (2020). A nationwide survey of psychological distress among Italian people during the COVID-19 pandemic: immediate psychological responses and associated factors. Int. J. Environ. Res. Public Health 17:3165. doi: 10.3390/ijerph17093165
Moccia, L., Janiri, D., Pepe, M., Dattoli, L., Molinaro, M., De Martin, V., et al. (2020). Affective temperament, attachment style, and the psychological impact of the COVID-19 outbreak: an early report on the Italian general population. Brain Behav. Immun. 87, 75–79. doi: 10.1016/j.bbi.2020.04.048
Moghanibashi-Mansourieh, A. (2020). Assessing the anxiety level of Iranian general population during COVID-19 outbreak. Asian J. Psychiatr. 51:102076. doi: 10.1016/j.ajp.2020.102076
Mohammed, A., Sheikh, T. L., Gidado, S., Poggensee, G., Nguku, P., Olayinka, A., et al. (2015). An evaluation of psychological distress and social support of survivors and contacts of Ebola virus disease infection and their relatives in Lagos, Nigeria: a cross sectional study–2014. BMC Public Health 15:824. doi: 10.1186/s12889-015-2167-6
Mullen, R. A., Tong, S., Sabo, R. T., Liaw, W. R., Marshall, J., Nease, D. E., et al. (2019). Loneliness in primary care patients: a prevalence study. Ann. Fam. Med. 17, 108–115. doi: 10.1370/afm.2358
Nguyen, H. C., Nguyen, M. H., Do, B. N., Tran, C. Q., Nguyen, T. T. P., Pham, K. M., et al. (2020). People with suspected COVID-19 symptoms were more likely depressed and had lower health-related quality of life: the potential benefit of health literacy. J. Clin. Med. 9:965. doi: 10.3390/jcm9040965
Nguyen, T., Netto, C. L. M., Wilkins, J. F., Bröker, P., Vargas, E. E., Sealfon, C. D., et al. (2021) Insights into students’ experiences and perceptions of remote learning methods: from the COVID-19 pandemic to best practice for the future. Front. Educ. 6:647986. doi: 10.3389/feduc.2021.647986
Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., et al. (2020). The socio-economic implications of the coronavirus and COVID-19 pandemic: a review. Int. J. Surg. 78, 185–193. doi: 10.1016/j.ijsu.2020.04.018
Oducado, R. M., Rabacal, J., Moralista, R., and Tamdang, K. (2020). Perceived stress due COVID-19 pandemic among employed professional teachers. IJERI Int. J. Educ. Res. Innovat. 15, 305–316. doi: 10.46661/ijeri.5284
Okruszek, Ł, Aniszewska-Stańczuk, A., Piejka, A., Wiśniewska, M., and Żurek, K. (2020). Safe but lonely? Loneliness, anxiety, and depression symptoms and COVID-19. Front. Psychol. 11:579181. doi: 10.3389/fpsyg.2020.579181
Ozamiz-Etxebarria, N., Berasategi Santxo, N., Idoiaga Mondragon, N., and Dosil Santamaría, M. (2021). The psychological state of teachers during the COVID-19 crisis: the challenge of returning to face-to-face teaching. Front. Psychol. 11:620718. doi: 10.3389/fpsyg.2020.620718
Philippas, D. (2014). “Analysis of Covariance (ANCOVA),” in Encyclopedia of Quality of Life and Well-Being Research, ed. A. C. Michalos (Dordrecht: Springer), doi: 10.1007/978-94-007-0753-5_82
Puente-Martínez, A., Páez, D., Ubillos-Landa, S., and Da Costa-Dutra, S. (2018). Examining the structure of negative affect regulation and its association with hedonic and psychological wellbeing. Front. Psychol. 9:1592. doi: 10.3389/fpsyg.2018.01592
Qiu, J., Shen, B., Zhao, M., Wang, Z., Xie, B., and Xu, Y. (2020). A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: implications and policy recommendations. Gen. Psychiatry 33:e100213. doi: 10.1136/gpsych-2020-100213
Rabacal, J. S., Oducado, R. M. F., and Tamdang, K. A. (2020). COVID-19 impact on the quality of life of teachers: a cross-sectional study. Asian J. Public Opin. Res. 8, 478–492. doi: 10.15206/ajpor.2020.8.4.478
Raes, F., Pommier, E., Neff, K. D., and Van Gucht, D. (2011). Construction and factorial validation of a short form of the self-compassion Scale. Clin. Psychol. Psychother. 18, 250–255. doi: 10.1002/cpp.702
Reimers, F. M., and Schleicher, A. (2020). A Framework to Guide an Education Response to the Covid-19 Pandemic of 2020. Paris: OECD.
Rogers, J. P., Chesney, E., Oliver, D., Pollak, T. A., McGuire, P., Fusar-Poli, P., et al. (2020). Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: a systematic review and meta-analysis with comparison to the COVID-19 pandemic. Lancet Psychiatry 7, 611–627. doi: 10.1016/S2215-0366(20)30203-0
Rosenberg, M., Luetke, M., Hensel, D., Kianersi, S., Fu, T.-C., and Herbenick, D. (2021). Depression and loneliness during April 2020 COVID-19 restrictions in the United States, and their associations with frequency of social and sexual connections. Soc. Psychiatry Psychiatr. Epidemiol. 1–12. doi: 10.1007/s00127-020-02002-8
Rozin, P., and Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personal. Soc. Psychol. Rev. 5, 296–320. doi: 10.1207/S15327957PSPR0504_2
Ryan, R., and Deci, E. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55, 68–78. doi: 10.1037/0003-066X.55.1.68
Ryan, R., and Deci, E. (2001). On happiness and human potentials: a review of research on hedonic and eudaimonic well-being. Annu. Rev. Psychol. 52, 141–166. doi: 10.1146/annurev.psych.52.1.141
Ryff, C. D. (1989a). Beyond Ponce de Leon and life satisfaction: new directions in quest of successful ageing. Int. J. Behav. Dev. 12, 35–55. doi: 10.1177/016502548901200102
Ryff, C. D. (1989b). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. J. Personal. Soc. Psychol. 57, 1069–1081. doi: 10.1037/0022-3514.57.6.1069
Ryff, C. D., and Singer, B. H. (2008). Know thyself and become what you are: an eudaimonic approach to psychological wellbeing. J. Happiness Stud. 9, 13–39. doi: 10.1007/s10902-006-9019-0
Sahu, P. (2020). Closure of universities due to coronavirus disease 2019 (COVID-19): impact on education and mental health of students and academic staff. Cureus 12:e7541. doi: 10.7759/cureus.7541
Schmukle, S. C., Egloff, B., and Burns, L. R. (2002). The relationship between positive and negative affect in the Positive and Negative Affect Schedule. J. Res. Personal. 36, 463–475. doi: 10.1016/S0092-6566(02)00007-7
Seligman, M. (2011). Flourish: A Visionary New Understanding of Happiness and Well-Being. New York, NY: Free Press.
Smith, B. J., and Lim, M. H. (2020). How the COVID-19 pandemic is focusing attention on loneliness and social isolation. Public Health Res. Pract. 30:3022008. doi: 10.17061/phrp3022008
Son, C., Hegde, S., Smith, A., Wang, X., and Sasangohar, F. (2020). Effects of COVID-19 on college students’ mental health in the United States: interview survey study. J. Med. Int. Res. 22:e21279. doi: 10.2196/21279
Szczygieł, D., and Mikolajczak, M. (2017). Why are people high in emotional intelligence happier? They make the most of their positive emotions. Personal. Individ. Differ. 117, 177–181. doi: 10.1016/j.paid.2017.05.051
Theeke, L. A. (2010). Sociodemographic and health-related risks for loneliness and outcome differences by loneliness status in a sample of U.S. Older Adults. Res. Gerontol. Nurs. 3, 113–125. doi: 10.3928/19404921-20091103-99
Tull, M. T., Edmonds, K. A., Scamaldo, K. M., Richmond, J. R., Rose, J. P., and Gratz, K. L. (2020). Psychological outcomes associated with stay-at-home orders and the perceived impact of covid-19 on daily life. Psychiatry Res. 289:113098. doi: 10.1016/j.psychres.2020.113098
University of Houston (2020). Remote Teaching Check-in Survey Report. Houston, TX: University of Houston. Available online at: https://fs.uh.edu/api/download.php?docID=451.
Wang, R., Han, J., Liu, C., and Xu, H. (2021). How do University Students’ perceptions of the instructor’s role influence their learning outcomes and satisfaction in cloud-based virtual classrooms during the COVID-19 pandemic? Front. Psychol. 12:627443. doi: 10.3389/fpsyg.2021.627443
Wanous, J. P., and Reichers, A. E. (1996). Estimating the reliability of a single-item measure. Psychol. Rep. 78, 631–634. doi: 10.2466/pr0.1996.78.2.631
Waterman, A. S. (1993). Two conceptions of happiness: contrasts of personal expressiveness (eudaimonia) and hedonic enjoyment. J. Personal. Soc. Psychol. 64, 678–691. doi: 10.1037/0022-3514.64.4.678
Watermeyer, R., Crick, T., Knight, C., and Goodall, J. (2021). COVID-19 and digital disruption in UK universities: afflictions and affordances of emergency online migration. Higher Educ. 81, 623–641. doi: 10.1007/s10734-020-00561-y
Wilczewski, M., Gorbaniuk, O., and Giuri, P. (2021). The psychological and academic effects of studying from the home and host country during the COVID-19 pandemic. Front. Psychol. 12:644096. doi: 10.3389/fpsyg.2021.644096
Woolfolk Hoy, A. (2008). What motivates teachers? Important work on a complex question. Learn. Instr. 18, 492–498. doi: 10.1016/j.learninstruc.2008.06.007
World Bank (2020). World Development Report 2020: Trading for Development in the Age of Global Value Chains. Washington, DC: World Bank Group. Available online at: https://openknowledge.worldbank.org/bitstream/handle/10986/32437/9781464814570.pdf
Xiong, J., Lipsitz, O., Nasri, F., Lui, L. M. W., Gill, H., Phan, L., et al. (2020). Impact of COVID-19 pandemic on mental health in the general population: a systematic review. J. Affect. Disord. 277, 55–64. doi: 10.1016/j.jad.2020.08.001
Yang, J., Peng, M. Y.-P., Wong, S., and Chong, W. (2021). How E-learning environmental stimuli influence determinates of learning engagement in the context of COVID-19? SOR model perspective. Front. Psychol. 12:584976. doi: 10.3389/fpsyg.2021.584976
Keywords: teacher well-being, emergency remote instruction, COVID-19 pandemic, negative affect, situational anxiety, loneliness, higher education, work-life synergy
Citation: Jelińska M and Paradowski MB (2021) The Impact of Demographics, Life and Work Circumstances on College and University Instructors’ Well-Being During Quaranteaching. Front. Psychol. 12:643229. doi: 10.3389/fpsyg.2021.643229
Received: 17 December 2020; Accepted: 05 May 2021;
Published: 11 June 2021.
Edited by:
David Ian Walker, University of Alabama, United StatesReviewed by:
Seockhoon Chung, University of Ulsan, South KoreaTaylor Wayne Acee, Texas State University, United States
Copyright © 2021 Jelińska and Paradowski. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Michał B. Paradowski, bS5iLnBhcmFkb3dza2lAdXcuZWR1LnBs