1 Introduction

The COVID-19 pandemic has presented organizations worldwide with significant challenges (Greenstein, 2021; Viegas & Nunes, 2021; Pataki-Bittó & Kun, 2022; Svihus, 2023). Many organizations encountered serious problems due to the absence of contingency plans (Belzunegui-Eraso & Erro-Garcés, 2020). This has resulted in several implications for organizations and their employees, affecting the environment in which people work, with whom they work, and how they work (Fouad, 2020). In education, the abrupt shift from traditional to remote teaching has been a defining feature of this transformation (Misirli & Ergulec, 2021; Zhou et al., 2022a, b). The widespread and immediate shift towards online teaching and learning (Sidi et al., 2023), demanded that education professionals quickly adapt to unfamiliar technologies and the skills and abilities necessary for performing their tasks (Wohlfart et al., 2021).

The shift to remote work has uncovered several challenges that extend beyond the professional sphere and permeate into the health and well-being of individuals. An analysis of the literature reveals that the challenges are multifaceted and heterogeneous and have several impacts and implications for employees. For example, a key concern arising from this transition is the breakdown in communication with colleagues, a vital component of a collaborative work environment (Tavares et al., 2020). This lack of direct interaction can contribute to feelings of isolation and detachment, potentially laying the groundwork for the emergence of health problems. The immediate adaptation to new technological requirements further compounds the challenges of remote work (Khong et al., 2023). The pressure to stay technologically proficient and relevant in a rapidly evolving digital landscape introduces an additional layer of stress, potentially contributing to health problems among remote workers. Adding to this complexity are the broader societal shifts induced by remote work, as outlined by Maghlaperidze et al. (2021). Social isolation, shifts in employees’ priorities and reduced career prospects lead to disparities in job satisfaction and work-life balance (Boca et al., 2020; Feng & Savani, 2020). The cumulative effect of these challenges has a substantial impact on the mental and physical health of individuals engaged in remote work (Ozimek, 2020; Greenstein, 2021; Pataki-Bittó & Kun, 2022). It seems that the absence of organizational support adds another layer to the challenges of remote work. The work environment and working conditions have a significant impact on the psychological well-being of teachers and also affect their capacity to perform professional responsibilities effectively (Ratanasiripong et al., 2022). Employees may find themselves navigating unfamiliar territory without the necessary tools or assistance, potentially amplifying stress and anxiety levels (Tavares et al., 2020). A lack of support becomes a critical factor contributing to the psychosocial implications of remote work, as highlighted by Buomprisco et al. (2021). Feelings of frustration, anxiety, fear, and loneliness become pervasive, impacting the mental health of individuals (Waight et al., 2022) which also impact key performance outcomes such as job satisfaction, engagement and turnover intention.

To address these challenges, organizations must comprehend the intricacies of remote work and provide appropriate support to their employees (Restubog et al., 2020; Como et al., 2021). Recognizing and addressing these challenges is imperative for organizations and policymakers seeking to foster a healthier and more sustainable remote work environment in the face of ongoing and future uncertainties. This is not only essential for the organizations’ ability to attract, develop, and retain their intellectual capital but also for mitigating the adverse effects on the well-being of education professionals, who play a crucial frontline role in the educational system (Sokal et al., 2020; Stang-Rabrig et al., 2022). It is evident that much work has been conducted to advance our understanding of the challenges that remote work has presented. Nevertheless, the literature highlights several issues that limit our understanding and deserve further attention.

First, while many studies investigate the impact of COVID-19 in various contexts, there is a dearth of evidence focusing on educational professionals. Consequently, many scholars are calling for the implementation of targeted studies that specifically address the experiences and challenges faced by educators (Song et al., 2020; Ma et al., 2022; Stang-Rabrig et al., 2022; Agyapong et al., 2023). Unlike well-planned conventional online learning experiences, educational professionals faced an accelerated transition which necessitated the adaptation to new, frequently unfamiliar, digital resources for their instructional endeavors (Tulaskar & Turunen, 2022). This contributed to the preexisting difficulties associated with attrition rates in the field of education (Madigan & Kim, 2021) leading to significant ramifications for students’ academic achievements (e.g., Schleicher, 2018; Sorensen & Ladd, 2020). Understanding the factors related to teachers’ well-being is fundamental to enabling interventions that better support teachers and students in educational settings (Gray et al., 2017). This study answers calls for further research by analyzing real-world data obtained from educational professionals in Brazil.

Second, it is evident that the effects of remote work are intricate and diverse, encompassing various aspects that influence outcomes such as the nature of work, the individuals involved as well as the nature and level of organizational support. Consequently, scholars are advocating for investigations to focus on specific parameters that are utilized within distinct contexts. Hence, to gain a more comprehensive and nuanced understanding of the domain it is essential to prioritize the most relevant factors and interrogate them in greater depth. The existing body of research offers comprehensive evidence supporting the notion that health and well-being are important factors and warrant further investigation within an educational setting (Song et al., 2020; Jamal et al., 2021; Zhou et al., 2022a, b). Prior work also suggests that attitudes and behaviors are influenced and stimulated by the availability of appropriate resources (Bakker & Demerouti, 2014), and they contribute to a positive and productive organizational climate (Pataki-Bittó & Kun, 2022). These factors are known to predict important changes in attitudes and behaviors, which are crucial elements of individuals’ experience in the work environment (Kelliher & Anderson, 2010; Timms et al., 2015; Suh & Lee, 2017; Galanti et al., 2021; Irawanto et al., 2021). Consequently, this study focuses on health complaints and organizational support and assesses how they impact important performance outcomes.

Finally, despite their importance, previous studies fail to provide empirical evidence relating to the correlation and magnitude of these factors with regard to specific relevant outcomes such as job satisfaction, engagement and turnover intention. Job satisfaction is regarded as a dominant indicator of employee well-being (Grawitch et al., 2007). An unsatisfied teacher may not dedicate the same level of effort and attention to work, which can have a negative impact on the quality of teaching (Oubibi et al., 2022) and leave the profession (Li et al., 2022a, b). Employee engagement is another essential concept that is known to have positive consequences at both individual and organizational levels (Schaufeli, 2012). However, there is a paucity of literature on the relationship between remote work during COVID-19 and its impact on employee engagement (Mehta & Sharma, 2022; Oubibi et al., 2022). Turnover intention has also been recognized as a significant problem in education as it has serious consequences for students’ learning outcomes (Räsänen et al., 2020). According to certain estimates, approximately 50% of newly employed teachers exit the field within five years (Sims & Jerrim, 2020). Li and Yao (2022) assert that an increase in turnover intention may signify a progressive discrepancy between perceived job demands and inadequate resources in the field of education.

Taken together it seems that these outcomes merit further investigation. Yet despite their importance, we do not know whether or to what extent health complaints and organizational support impact educational professionals’ job satisfaction, work engagement and turnover intention or how these constructs relate to each other. The goal of this research, therefore, is to redress the current situation and analyze empirical data from educational professionals in Brazil. To accomplish this, an analysis of the literature was undertaken, and relevant constructs were identified and categorized. A positivist methodology was employed in the study. A structured instrument was constructed, and empirical data were collected from 288 educators in Brazil. The goal of the survey was to capture respondents’ perceptions of the key parameters relating to health and well-being and organizational support and to ascertain how these factors related to job satisfaction, engagement and turnover intention. The instrument was pre-tested with academics and researchers and pilot-tested with a sample of educators following good practice to ensure that it was valid and reliable. Data was analyzed using structured equation modeling to identify underlying relationships and interdependencies from the collected responses.

By analyzing the direct, indirect, and total effects of health complaints and organizational support on employees’ work attitudes and behaviors, the study aims to contribute new knowledge and provide evidence-based recommendations to better support education professionals. It makes a valuable departure from the norm by focusing on the experiences of educational professionals in Brazil during the transition from in-person to remote working. This is important because the majority of previous work focuses on US and Europe and it is important to consider potential cultural nuances (Li, & Yao, 2022). The uniqueness of this study lies in its commitment to understanding the experiences of educational professionals during this transition and its emphasis on both the immediate and long-term effects of health issues and organizational support. Acknowledging the possibility of increased remote working in the future, the study provides insights that are crucial for the development of educational professionals and work environments.

The findings suggest that health complaints had a negative impact on educational professionals’ satisfaction and employee engagement and a positive effect on employee turnover intention during the pandemic. They also suggest that organizational support had a positive effect on their levels of satisfaction and employee engagement and a negative effect on employee turnover intention during this transition to remote work. In addition, the results highlight that job satisfaction and engagement have a strong impact on turnover intention. The results emphasize the importance of understanding the intricacies of remote work and providing appropriate support to their employees. They underscore the importance of implementing measures to mitigate health complaints and strengthen organizational support for a better work environment. This is not only essential for the organizations’ ability to attract, develop, and retain important intellectual capital but also for mitigating the adverse effects on the well-being of education professionals.

The remainder of this paper is structured as follows. First, an analysis of current scholarship and debate concerning the impacts and effects of the pandemic are discussed, the proposed hypotheses are defined and the conceptual model is presented. Second, an overview of the scientific research methodology methods employed in this study is provided. The study’s key findings are then presented, followed by a discussion on how these findings relate to the extant literature. Finally, the paper concludes by demonstrating how this study contributes new knowledge and presents some implications for future research in this area.

2 Literature review

2.1 Impacts and effects of the pandemic on work

The impacts of the COVID-19 pandemic have led to significant changes in work environments, triggered by measures such as travel restrictions, hygiene regulations, social distancing, and the closure of educational institutions (Dingel & Neiman, 2020; Gaffney et al., 2021; Maghlaperidze et al., 2021; Viegas & Nunes, 2021). These changes have impacted the way people work and reshaped their perceptions towards work (Kramer & Kramer, 2020; Irawanto et al., 2021). Previous studies found that there is a positive and significant link between the workplace environment and the mental and physical well-being of employees (Donald & Siu, 2001). For example, prior work has found that issues such as physical and social isolation, new work arrangements, and increased workload, have resulted in a lack of organizational belongingness and impacted people’s work-related attitudes or behaviors (Spurk & Straub, 2020; Stang-Rabrig et al., 2022) as well as physical and mental health (O’Neil et al., 2020). Scholars also suggest that attitudes and behaviors are influenced and stimulated by the availability of appropriate resources (Bakker & Demerouti, 2014), and they contribute to a positive and productive organizational climate (Pataki-Bittó & Kun, 2022).

An analysis of the extant literature reveals that three outcomes are important and worthy of further investigation. These are job satisfaction, engagement and turnover intention. They are now discussed in more detail.

2.1.1 Job satisfaction

Understanding job satisfaction is particularly crucial in the high-strain, high-turnover world of school teachers and principals (e.g., Darmody & Smyth, 2016; Dicke et al., 2018). An unsatisfied teacher may not dedicate the same level of effort and attention to work, which can have negative impacts on the quality of teaching and the school environment (Oubibi et al., 2022). Job satisfaction is a broad concept that refers to the overall attitude towards work (Gragnano et al., 2020). It can be interpreted as contentment with job demands and has far-reaching effects on employee well-being at work (Dhamija et al., 2019). According to Grawitch et al. (2007), it is a dominant indicator of employee well-being. For example, Gragnano et al. (2020) discovered that it serves as a reliable measure of both well-being and psychological health and that it is related to many positive worker behaviors including job commitment. For education professionals, job satisfaction can positively influence enthusiasm and interpersonal relationships (e.g., Weiqi, 2007). It is also known to be a predictor of turnover intention (Grawitch et al., 2007) where the higher the levels of job satisfaction the lower the intention to leave. While job satisfaction is lauded for enhancing workers’ productivity, it depends on the absence of work stressors, particularly those resulting from the rapid pace of change in information and communication technologies (Suh & Lee, 2017). Bessa et al. (2015) found that low levels of job satisfaction are related to higher rates of work abandonment and major depressive disorder among the teaching population. Radical transitions, such as those derived from the pandemic, have been associated with lower job satisfaction (Vaziri et al., 2020; Mehta & Sharma, 2022).

2.1.2  Engagement

As remote activities performed by professionals entail physical and cognitive changes in their execution, these alterations can have an impact on individuals’ work engagement (Sardeshmukh et al., 2012). Work engagement is one of the important topics in current human resource management because it is strongly linked to organizational productivity (Žnidaršič & Marič, 2021). It is defined as a persistent and positive affective-motivational state where employees focus, voluntarily devote themselves to work-related activities, and lose track of time (Mazzetti et al., 2023; Schaufeli & Bakker, 2004). Maintaining employee engagement at work is of interest to many organizations, including schools (Oubibi et al., 2022). Engaged employees are described as energetic, proactive, produce quality work, and effectively handle difficult job situations (Schaufeli et al., 2006). According to Bakker and Demerouti (2014) deeply engaged employees show enthusiasm for work, maintain a positive perspective on their role and the organization, seek constant improvement of their professional skills, persist in performance improvement, and show respect for coworkers. They are more likely to employ coping strategies when faced with adversity and exhibit innovative behaviors (Kwon & Kim, 2020). Žnidaršič & Marič, (2021) found that a healthy work environment and job satisfaction as important factors influencing educators’ work engagement. Oubibi et al., 2022) also found that engaged teachers who perceive significant organizational support are more likely to experience more satisfaction.

2.1.3 Turnover intention

Teacher turnover has been recognized as a significant problem in education worldwide and results in serious consequences for students’ learning (Räsänen et al., 2020). Turnover intention, which refers to the deliberate decision of an individual to leave their current organization despite having the opportunity to continue in the job (Vermooten et al., 2019), represents another critical factor. Teachers’ turnover intention is an important measure as it reflects teachers’ attitudes toward their work and influences their professional development. In fact, it is one of the most influential factors in actual turnover (Tekleab et al., 2005). High turnover levels are concerning as they imply the loss of internal work knowledge, disruption of work activities and productivity, increased costs associated with seeking a suitable replacement, and the potential disruption of team cohesion, ultimately leading to a negative impact on organizational performance (McCarthy et al., 2020). Li and Yao (2022) conducted a meta-analysis on teachers’ turnover intention comprising 94 quantitative studies and found that burnout, workload, and stress were positively related to turnover intention and younger teachers with higher burnout and lower intrinsic motivation tended to show higher levels of intention to quit. Califf and Brooks (2020) also found that burnout is positively and significantly related to turnover intention.

Based on this analysis it is evident that job satisfaction, engagement and turnover intention are important constructs that merit further investigation. The next section examines the existing body of research and discusses related studies specifically focused on health complaints and organizational support and their influence on these dimensions in the context of COVID-19.

2.2 Related studies

Previous studies have examined health complaints and organizational support, as well as the attitudes and behaviors of professionals working remotely in the context of COVID-19. For instance, Song et al. (2020) utilized standardized measures to assess anxiety, depression, work engagement, job satisfaction, and turnover intention to assess mental health and attitudes toward work. Their findings concluded that employees’ mental health had been somewhat affected, and their work attitudes had changed after the COVID-19 outbreak. Employees tended to be more satisfied with their current jobs and demonstrated lower turnover intention. However, their level of engagement in their work has noticeably declined. Irawanto et al. (2021) conducted a study focusing on the effects of remote work, work-life balance, and job stress on job satisfaction. They also investigated whether work-life balance and job stress played a moderating role in the relationship between remote work and job satisfaction among Indonesian workers. Their research uncovered that working from home, work–life balance, and work stress have a significant effect, both directly and indirectly, on job satisfaction. It seems that remote working established a new pace of work and can sustain job satisfaction.

Nagarajan et al. (2022) investigated the impact of the COVID-19 pandemic on the performance and satisfaction of 300 employees in educational institutions in India. The research focused on how job crafting and employee engagement could mitigate these negative effects. They demonstrated that the pandemic had a negative impact on employee performance and satisfaction. Parent-Lamarche (2022) examined the impact of the COVID-19 pandemic on mental health. The study involved a series of statistical analyses to examine the relationships between telecommuting, work engagement, and intention to leave. The results suggest that organizations must take a proactive approach to promote the health and well-being of their employees by providing support and resources. Mehta and Sharma (2022) conducted a study with 186 employees including educational institutions. They explored how mechanisms of organizational support impact employees’ attitudes toward work during remote work amid the COVID-19 pandemic. Additionally, the study also examined how anxiety affects the relationship between employee engagement, job satisfaction, and organizational commitment. They report that organizational support mechanisms are crucial for maintaining employee engagement during the COVID-19 crisis. Table 1 presents the summary of these studies and a comparative analysis relative to the constructs investigated in this research.

Table 1 Comparative analysis of related work and this research
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In today’s competitive work environment, it is important to ensure that educational professionals are satisfied, engaged, and remain in their posts. While job satisfaction, work engagement, and turnover intention have been studied in previous work, these variables have not been examined together in the context of education despite high attrition rates. In order to understand the dynamics within the education sector, we argue that a holistic perspective should be adopted. We acknowledge that the interplay between these constructs is complex. Nevertheless, examining them together provides a more nuanced understanding of the phenomena.

2.3 Hypotheses definition

Recent research in this context has highlighted several health-related complaints among employees (Dennerlein et al., 2020; Minihan et al., 2022), including increased stress and anxiety (Yücel, 2021) as well as physical health, such as pain or discomfort in individuals (O’Neil et al., 2020; Clair et al., 2021). It is important to understand that if health complaints are not adequately managed, they can lead to numerous negative consequences, including high levels of stress, isolation, and burnout, which negatively impact mental health and well-being and the ability to cope with responsibilities related to teaching in virtual and home environments (Besser et al., 2022). Furthermore, these complaints can result in dissatisfaction, increased turnover intention (Minihan et al., 2022), and lower engagement (Sandoval-Reyes et al., 2021). Therefore, understanding the impact of COVID-19 on the health of educational employees is crucial for creating more efficient strategies for emotional support during and after the pandemic (Hutchison et al., 2023). Furthermore, given that the goal of education professionals is to meet the learning needs and academic development of students, understanding and addressing the stress and burnout of these professionals is crucial for cultivating healthy academic environments for all members of the school community (Gray et al., 2017). In light of this discussion, the following hypotheses are postulated:

  • H1: Health complaints are negatively related to employee satisfaction.

  • H2: Health complaints are negatively related to employee engagement.

  • H3: Health complaints are positively related to employee turnover intention.

Perceived Organizational Support (POS) is a theoretical concept in organizational psychology that refers to employees’ beliefs concerning the extent to which their organization values their contributions and cares about their well-being. This theory suggests that employees develop perceptions of the organization’s support based on their interactions, experiences, and observations within the workplace (Eisenberger et al., 1986). Prior research has also shown that inadequate organizational support can result in work stress and exhaustion. The lack of organizational support also negatively impacts remote workers’ well-being (Como et al., 2021), leading to burnout and increased employee turnover intention (Afshari et al., 2022). Furthermore, the lack of support, and recognition, the scarcity of resources, and the feeling of having a job with too many tasks can make professionals, such as teachers, feel disheartened, tired, and as if they are not doing a good job (Doucet, 2019). Conversely, Miglioretti et al. (2021) reported that providing direct or indirect support and the appropriate resources, along with autonomy and flexibility in work hours, demonstrated a positive impact on work-life balance for employees, contributing to increased engagement, reduced job insecurity, and improved psychological well-being (Li et al., 2022a, b). However, when properly provided, it increases job satisfaction and reduces turnover intentions (Yücel, 2021). Moreover, it improves employee engagement levels and productivity (Galanti et al., 2021; Sardeshmukh et al., 2012). Therefore, researchers have emphasized the importance of organizational support for professionals working from home during the COVID-19 pandemic (Prodanova & Kocarev, 2021). As a result, the following hypotheses are proposed:

  • H4: Organizational support is positively related to employee satisfaction.

  • H5: Organizational support is positively related to employee engagement.

  • H6: Organizational support is negatively related to employee turnover intention.

Figure 1 illustrates the conceptual model used in this study.

Fig. 1
figure 1

Conceptual model

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3 Methodology

3.1 Measurement instrument

A structured survey was developed to capture respondents’ perspectives regarding key parameters relating to health and well-being, organizational support, and their correlation with job satisfaction, engagement, and turnover intention. The choice of survey data collection was motivated by the necessity to efficiently gather primary data from a potentially large population while ensuring standardized information for meaningful comparisons among participants. To measure employee health, an adapted version of the “Subjective Inventory of Health Complaints” developed by Eriksen et al. (1999) was utilized. This five-item scale comprised physical elements such as pain and discomfort and psychological elements such as anxiety and fear. The items used in the data collection instrument are listed in Appendix A. Perceived organizational support was measured using an eight-item scale employed by Eisenberger et al. (1986) where participants rated their perceptions on how they felt the organization considered their values, offered help and cared about their opinions. Job satisfaction was measured using a scale adapted from Irawanto et al. (2021). It consists of a four-item scale capturing various facets of satisfaction with colleagues, supervisors, income, and overall job satisfaction. Work engagement was measured using a nine-item scale to assess employees’ level of involvement in their work. It was adapted from the Utrecht Work Engagement Scale (UWES-9) by Schaufeli et al. (2006). A four-item turnover intention scale was used, based on the scale developed by Jung and Yoon (2013) and adapted from Memon et al. (2021) to measure participants’ likelihood of leaving their jobs. A five-point Likert-type response format was used to assess all items in this study based on good practice in measuring attitudes, character traits, and personality (Boone et al., Jr, 2012; Nemoto & Beglar, 2014) (see Appendix A). Likert scales offer the advantage of capturing attitude direction and intensity within the same instrument (Likert, 1932). They are familiar to respondents, facilitate efficient data collection from a large number of participants, and allow for meaningful comparisons and analysis within the scale (Hartley, 2014; Nemoto & Beglar, 2014).

3.2 Data collection

The survey was developed in Google Forms to enable data collection. The questionnaire was divided into three sections and comprised 19 questions. The first section consisted of nine questions capturing professional characteristics such as role and experience; the second section included five sets of questions related to each of the five constructs listed in Appendix A, namely health complaints, organizational support, job satisfaction and engagement, and turnover intention; the third section consisted of five personal characterization questions relating to the participant, such as age and gender. Additionally, two questions were included to ensure that the sample comprised professionals in the field of education, and that the respondents worked remotely in Brazil. A non-probabilistic sampling approach was used in this study, specifically convenience and snowball sampling. Educational professionals in Brazil were invited to participate and encouraged to share the survey through various communication channels such as email and WhatsApp, as well as social media platforms including Facebook, Instagram, and LinkedIn. The data collection period was from October 5 to November 19, 2022. It resulted in 316 responses, with a final count of 288 valid responses.

3.3 Data analysis

JASP version 0.17.1 (2023) was used to conduct descriptive and bivariate analyses. For the multivariate analysis, the study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) using Smart PLS-4 version 4.0.9.3.

The distribution of the data was assessed using the Shapiro-Wilk test to examine deviations from normality. Significant values at the p < 0.05 level indicated a non-normal distribution. Given that all variables exhibited an asymmetric distribution (Shapiro-Wilk p < 0.001), taking into account the non-normality of the data and the complexity of the model, which encompasses multiple constructs and observed variables, the selection of the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique was deemed appropriate for understanding the relationships between the impacts of the pandemic and the attitudes and behaviors of education professionals. The choice was made due to its capacity, flexibility, and versatility in conducting non-parametric analyses (Ringle et al., 2014).

A two-step approach was used for data analysis and interpretation, as recommended by Hair et al. (2017). In the first step, the reliability and validity of the measurement model used in the study to verify how consistent and accurate the measures are in capturing the variables under study was assessed. In the second step, the hypothesized relationships in the structural model were examined to check whether these relationships are consistent with the proposed hypotheses.

4 Results

4.1 Survey sample and demographics

A total of 288 education professionals engaged in remote work across Brazil participated in the study. The sample characteristics indicate that the majority of participants in our study were female (56.6%), within the 26 to 45 age range (60.76%). Over 60.06% were married or lived with their partners and 52.78% of participants reported having one or two children. The majority of participants had a post-grad degree (90.62%) and more than three-quarters reported a salary range between one and seven times the minimum wage. 67.78% teach at graduate level, and over 72% work in public institutions. Only 10.07% of the participants had experience with remote work before the pandemic. Appendix B provides an overview of the demographic and professional characteristics of the participants in our study.

4.2 Evaluation of the constructs

The hypothetical model in our study is characterized as reflective since all indicator items are highly correlated with each other and are influenced by the same latent construct (Hair et al., 2009). The results of the PLS algorithm indicate that the majority of the item loadings are greater than 0.708. However according to Hair et al. (2017) and Bido and Da Silva (2019), if some loadings are lower than 0.708 but AVE > 0.5 and CR > 0.7, the items are acceptable therefore we included them in our study. However, with caution, we chose to exclude SO_6 - ‘If I allowed it, the organization would take advantage of me,’ with a loading of 0.451, as its omission improved the model’s consistency without negatively affecting important properties such as composite reliability, convergent validity, and content validity. After this exclusion, there was a positive impact on the indicators, where Cronbach’s Alpha (α), which was 0.869, improved to 0.881, Composite Reliability (rho_C), which was 0.899, improved to 0.908, and Average Variance Extracted (AVE), which was 0.534, improved to 0.588, as shown in Appendix C. Figure 2 presents the inicial model of factor loadings.

Fig. 2
figure 2

Initial model of item factor loadings

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Ringle et al. (2014) and Sarstedt et al. (2021) state that it is necessary to validate measurement models. Thus, after assessing item loadings, the reliability of the indicators and convergent validity were evaluated using Cronbach’s Alpha coefficient (α), Composite Reliability (rho_C), and Average Variance Extracted (AVE), as shown in Table 2. All estimated values were found to be adequate according to the standards set by the literature, with all Cronbach’s alpha (α) and composite reliability values greater than 0.70 and AVE values greater than 0.50 (Hair et al., 2017; Ringle et al., 2014)

Table 2 Coefficients of construct validity and reliability criteria
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To assess the discriminant validity of the model, the Fornell-Larcker criterion and Heterotrait-Monotrait Ratio (HTMT) were utilized, as they are considered robust and precise methods (Hair et al., 2014; Sarstedt et al., 2021). The first evaluation was performed using the Fornell-Larcker method, which compares the square root of the extracted variance (AVE) of each construct with the correlations between that construct and other constructs in the model. According to Table 3, the diagonal values (square root of AVE) are higher than the other correlations, meeting the criteria of this method and validating the distinction between constructs.

Table 3 Correlation matrix of latent variables
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Next, discriminant validity was assessed using the Heterotrait-Monotrait (HTMT) ratio, where, according to Table 4, the interactions were within the accepted limits with values ranging from (0.188) to (0.738). This method compares the quotient between different constructs and the correlations among indicators of the same construct. According to Hair et al. (2017) and Sarstedt et al. (2021), this quotient should be less than 0.85 for each pair of constructs.

Table 4 Heterotrait-Monotrait (HTMT)
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Furthermore, discriminant validity was also evaluated through cross-loadings. This assessment examines whether the factor loading of an indicator on its own construct is greater than the factor loading of that same indicator on other constructs (Hair et al., 2017). For example, we can see that the item from the organizational support construct in Table 5, SO_7 - ‘The organization showed little concern for me’ (0.607), has a lower value compared to the item from the Satisfaction construct, SF_3 - ‘Do you feel, or have you felt satisfied and happy with your supervisors?’ (0.616).

Table 5 Factorial loading matrix – Cross-Loadings (n = 288)
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4.3 Structural model evaluation

The complete consolidated structural model (measurement and structure) is presented in Fig. 3. The fit measures were adequate, and it was judged that the estimated complete structural model was consistent with the literature review presented.

Fig. 3
figure 3

Complete structural model

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Next, we focus on the model’s latent variables. A bootstrapping technique with 5,000 resamples was used to obtain the structural coefficients, VIF values, f² values, standard error, t-test values, and p-values. These were examined to determine the significance of the assertions for the dimensions that compose the theoretical model under the condition (t-test ≥ 1.96 and p-value < 0.05), the adjusted R², and the predictive validity Q², as shown in Table 6.

All relationships showed VIF values between 1.028 and 1.640, indicating low multicollinearity according to Hair et al. (2017). The assessment of effect size used Cohen and Cohen (1988) and Hair et al. (2017), who classify f² as 0.02 (small), f² as 0.15 (medium), and f² as 0.35 (large). The adjusted R² was also evaluated based on Cohen and Cohen (1988), who suggests that the explained variance of the endogenous variables by the independent variables be classified as R² = 2% (weak), R² = 13% (moderate), and R² = 26% (strong). The predictive relevance Q² of the model was classified using the Stone-Geisser indicator, where Q² > 0 suggests the existence of predictive relevance. Q² = 0.02 (weak), Q² = 0.15 (moderate), and Q² = 0.35 (strong) are considered as suggested by Hair et al. (2017).

Table 6 Indicators and coefficients of the structural model
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The relationship between V1 (health complaints) and V3 (satisfaction) obtained a structural coefficient of β= -0.088 (t ≥ 1.96; p < 0.046), suggesting a negative relationship between the two variables. The effect size f² was small (0.015), with a standard error of (0.044). The relationship between V2 (organizational support) and V3 (satisfaction) showed a structural coefficient of β = 0.3849 (t ≥ 1.96; p < 0.05), with an f² effect size of (0.235), indicating a medium effect. The standard error was (0.050), indicating a significant positive relationship between V2 (organizational support) and V3 (employee satisfaction). Overall, the model demonstrated substantial explanatory power of the variability in V3 (satisfaction) by V1 (health complaints) and V2 (organizational support) with an R² of (0.523). The predictive relevance Q² of (0.391) is classified as moderate in predicting V3 (satisfaction) based on V1 (health complaints) and V2 (organizational support).

Regarding the relationship between V1 (health complaints) and V4 (engagement), the structural coefficient was β= -0.239 (t ≥ 1.96; p < 0.05), with a small effect size f² of (0.080). The standard error was (0.054), indicating a negative and significant relationship between V1 (health complaints) and V4 (engagement). The relationship between V2 (organizational support) and V4 (engagement) had a structural coefficient of β = 0.457(t ≥ 1.96; p < 0.05), with an f² effect size of (0.291), considered medium. The standard error was (0.047), indicating a significant positive relationship between V2 (organizational support) and V4 (employee engagement). The adjusted R² was (0.297), which means that 29.7% of the variability in V4 (engagement) is explained by V1 (health complaints) and V2 (organizational support). The predictive relevance Q² of the model was (0.289), classified as moderate.

Finally, the relationship between V1 (health complaints) and V5 (turnover) obtained only a structural coefficient of β = 0.110 (t < 1.96; p > 0.05), with a small effect size f² of (0.013). The standard error was (0.063), indicating no significant relationship between V1 (health complaints) and V5 (turnover intention). For the relationship between V2 (organizational support) and V5 (turnover), the structural coefficient was β= -0.128 (t < 1.96; p > 0.05), a negative relationship with a small effect size f² of (0.012). The standard error was (0.069), demonstrating no significant relationship between V2 (organizational support) and V5 (turnover intention). The adjusted R² was (0.122), which means that only 12.2% of the variability in V5 (turnover intention) is explained by V1 (health complaints) and V2 (organizational support).

4.4 Analysis of the effects

As presented in Table 7, variable V1 (health complaints) produced a small direct negative effect of (-0.088, p < 0.05) on variable V3 (satisfaction). There was also a small negative indirect effect of (-0.101, p < 0.05) in the relationship between V1 (health complaints) and V3 (satisfaction), indicating the presence of partial mediation. The total effect, which corresponds to the sum of the direct and indirect effects, was (-0.189, p < 0.05), and was considered to be medium. These results suggest that health complaints had a negative impact on employee satisfaction during the pandemic and remote work period, providing support for hypothesis 1 (H1).

Table 7 Direct (D), indirect (I), and total (T) effects of relationships
Full size table

A direct negative effect of (-0.239, p < 0.05) was identified between variable V1 (health complaints) and variable V4 (engagement). No indirect effect was found in this relationship, resulting in a total effect equivalent to the direct effect of (-0.239, p < 0.05), which is considered to be medium. These results suggest that health complaints had a negative effect on employee engagement during the pandemic and remote work period, providing support for hypothesis 2 (H2).

Regarding hypothesis 3 (H3), a direct positive effect of V1 (health complaints) on V5 (turnover) was observed (0.110, p > 0.05), but it was not significant. However, an indirect positive effect (0.046, p < 0.05) was also identified in this relationship, resulting in total mediation. The total effect found was (0.157, p < 0.05), considered medium. These results suggest that health complaints have a positive effect on employee turnover intention during the pandemic and remote work period, providing support for hypothesis 3 (H3).

Regarding hypothesis 4 (H4), a large direct positive effect of V2 (organizational support) on V3 (satisfaction) was found (0.384, p < 0.05). A medium indirect positive effect of (0.193, p < 0.05) was also observed in the relationship between V2 (organizational support) and V3 (satisfaction), indicating partial mediation. The total effect found was (0.577, p < 0.05), and it is considered to be large. These results suggest that organizational support has a positive effect on employee satisfaction during the pandemic and remote work period, providing support for hypothesis 4 (H4).

A direct positive effect of V2 (organizational support) on V4 (engagement) was identified (0.457, p < 0.05). No indirect effect was found in this relationship, resulting in a total effect equivalent to the direct effect (0.457, p < 0.05), considered large. These results suggest that organizational support has a positive effect on employee engagement during the pandemic and remote work period, providing support for hypothesis 5 (H5).

Finally, variable V2 (organizational support) has a direct, but not significant negative effect (-0.128, p > 0.05) on variable V5 (turnover). However, an indirect negative effect (-0.131, p < 0.05) was also observed in this relationship, resulting in total mediation. The total effect, which corresponds to the sum of the direct and indirect effects, was (-0.260, p < 0.05), which is considered to be medium. These results suggest that organizational support has a negative effect on employee turnover intention during the pandemic and remote work period, providing support for hypothesis 6 (H6).

5 Discussion

During the COVID-19 pandemic, the sudden shift from traditional to online teaching presented challenges for educators who had to quickly adapt to online learning methods (Lemoine et al., 2020). This transition highlighted the importance of identifying key factors to overcome these challenges (Galanti et al., 2021). This shift resulted in professionals experiencing health complaints such as anxiety, depression, and stress (Godinic et al., 2020; O’Neil et al., 2020; Restubog et al., 2020; Viramgami et al., 2020; van Zoonen & ter Hoeven, 2022), as well as burnout and physical/psychosomatic issues (Sigahi et al., 2021; Song et al., 2020). These factors influenced the behaviors or attitudes of professionals, generating additional concerns regarding the well-being of the workers (Afshari et al., 2022; Alfanza, 2021). This study investigated how COVID-19 influenced the attitudes and behaviors of education professionals who transitioned to remote work, specifically examining the effects of health complaints and organizational support on job satisfaction, work engagement, and turnover intention. These results suggest that health complaints had a negative impact on employee satisfaction and employee engagement and a positive effect on employee turnover intention in the transition to remote work. They also suggest that organizational support had a positive effect on employee satisfaction and employee engagement and a negative effect on employee turnover intention during this time. They also demonstrated that job satisfaction and engagement have a significant impact on turnover intention. In other words, the higher the levels of satisfaction and engagement the lower the levels of turnover intention.

While remote work has been associated with lower levels of engagement and higher turnover intention (Parent-Lamarche, 2022), it is important to recognize the benefits it offered during the pandemic, such as reduced physical contact and the prevention of infectious diseases (Song et al., 2020; Wontorczyk & Rożnowski, 2022). Remote work continues to provide advantages such as increased autonomy, geographical flexibility, productivity, job satisfaction, work-life balance, and reduced environmental impact (Clancy, 2020; Greenstein, 2021; Miglioretti et al., 2021). However, the successful implementation of remote work depends on proper management by both companies and workers (Charalampous et al., 2022). It is crucial to note that remote work without appropriate support can lead to ergonomic problems, including uncomfortable equipment/furniture, long working hours, and improper postures that can harm workers’ health (Sigahi et al., 2021). Additionally, a sedentary lifestyle, social isolation, and increased stress can contribute to physical and psychosomatic issues (Gaffney et al., 2021).

5.1 Health complaints

Our study identified signs that the majority of individuals studied experienced feelings of anxiety, sadness, loneliness, fear, worry, pain, physical discomfort, headaches, migraines, fatigue, and dizziness, indicating the prevalence of physical and emotional health complaints. These findings corroborate the studies by Şimşir et al. (2022) and Parent-Lamarche (2022), who suggest that the fear of COVID-19 may contribute to an increased risk of mental and physical health problems, potentially impacting work engagement (Wontorczyk & Rożnowski, 2022). Participants in this study expressed a lack of energy, vigor, and job satisfaction. These indicators were found to have a negative impact on work engagement. They are consistent with the findings of Yu et al. (2021) who observed that higher health complaints were associated with lower levels of work engagement, similar to the research by Clair et al. (2021), who linked health complaints during the COVID-19 pandemic to reduced job satisfaction.

Furthermore, health complaints also had possible implications for employees’ turnover intention. A majority of participants indicated that they would consider leaving their jobs if the working conditions worsened. The positive relationship between health complaints and turnover intention indicates that increased health complaints are associated with a higher likelihood of employees considering leaving their positions. These observations align with Jimenez et al. (2023), whose meta-analysis study concluded that the psychological and psychosomatic distress experienced by workers during the pandemic can negatively impact job satisfaction, and work engagement, and increase employees’ turnover intention. This highlights the need to pay attention to the psychosomatic signs of professionals, remove barriers, and provide resources that enable them to meet their professional demands to avoid conflictual relationships with students (Sokal et al., 2020).

5.2 Organizational support

From an organizational support perspective, many employees had to quickly adapt to new technologies and work procedures without adequate support (Shirmohammadi et al., 2022). The unexpected and urgent nature of the COVID-19 pandemic may have left employers and workers physically and mentally unprepared or lacking the infrastructure to cope with the challenges of remote work (Sandoval-Reyes et al., 2021).

However, participants in our study expressed greater satisfaction with remote work, similar to Russell et al. (2020), who reported higher levels of engagement while experiencing reduced turnover intention. Our study also found significant positive effects of organizational support on employees’ attitudes and behaviors. These findings align with those of Giauque et al. (2019), who argue that organizational support through policies and practices that balance work and personal demands, as well as a positive and supportive work environment, can reduce perceived stress, increase job satisfaction, and improve organizational commitment, ultimately decreasing employee turnover. The study also revealed that participants shared a sense of immersion, excitement, pride, inspiration, and enthusiasm regarding their work. This suggests that when the gain of resources such as social support and self-efficacy outweighs the loss of resources caused by the pandemic, employees can cope better and demonstrate improved performance and behavioral aspects (Ojo et al., 2021).

In our findings, it was observed that organizational tolerance for errors was a positive contributing factor, where the majority of respondents felt that the organization was understanding when they made mistakes. This indicates that a work environment that supports learning and development, rather than solely punishing failure, contributes to a positive perception of organizational support and fosters innovation and creativity (Muñoz et al., 2022; Yu & Frenkel, 2013), as employees may be more willing to take risks and explore new ideas (Eisenberger et al., 2020).

Furthermore, another important aspect that may have contributed to the positive perception of support for employees was the fact that the majority of respondents agreed that the organization would be willing to help them with personal favors. This may indicate the existence of a level of organizational support that extends beyond the purely professional context, which can contribute to higher satisfaction with the organization (Maan et al., 2020) and reduce turnover intentions (Yücel, 2021), as evidenced by our sample, where the majority partially or completely disagrees with the idea of changing jobs in the short or medium term or feeling pressured to leave their job. Furthermore, according to the descriptive data of the sample, it is important to consider that over 72% of the participants work in public institutions, which may reflect the stability offered by the Brazilian public service and could impact their job satisfaction and work engagement levels (Song et al., 2020).

Despite these positive findings, a significant portion of participants felt that their opinions were undervalued and perceived a lack of concern for their well-being within the organization. According to the Perceived Organizational Support theory, when employees do not perceive the organization as valuing their contributions or caring about their well-being, it can negatively impact job satisfaction (Eisenberger et al., 2002; Rhoades & Eisenberger, 2002).

Furthermore, our sample also revealed a strong consensus regarding the potential for organizations to take advantage of employees, indicating a possible lack of trust. This suggests that organizations need to improve perceived organizational support to increase employees’ trust in the organization and reduce the perception that the organization will exploit their vulnerabilities (Eisenberger et al., 2020).

Overall, the results highlight the significant positive effect of work resources on work engagement, which in turn has a significant negative effect on turnover intention (Li et al., 2022a, b). These findings underscore the influence of organizational support on employees’ well-being, job satisfaction, work engagement, and turnover intention (Eisenberger et al., 2002; Imran et al., 2020; Maan et al., 2020).

The study focused on job satisfaction, work engagement and turnover intention which have received some attention in previous work. However, it was not clear whether or to what extent they impacted educational professionals. Furthermore, the interplay and inter-relationships between these variables needed to be better understood. When utilizing a causality method, it is possible to establish reference bases to measure how much such variables can impact (or be influenced) by attributes such as organizational support and health complaints. By demonstrating the direct, indirect, and total effects, this article improves the understanding of this phenomenon, allowing organizations to take more assertive actions to improve the performance of teams and their products.

6 Conclusion

Remote work can be a viable alternative for many professionals during the crisis of the COVID-19 pandemic. However, promoting a healthy work environment that provides protection, security, health, and enables the development of employees is essential. Our study examined how two important constructs namely health complaints and organizational support impacts the satisfaction, engagement, and turnover intention of educational professionals in Brazil. The investigation of impacts occurred through the analysis of structural relationships of satisfaction, engagement, and turnover intention, as well as the direct, indirect, and total effects in their relationships. The results revealed stark differences in how these impacts manifested in the attitudes of educational professionals. While the research results indicate that health complaints can negatively impact workers’ satisfaction, engagement, and turnover intention, However, organizational support can positively contribute to employees’ perception of their work environment, increasing job satisfaction and improving commitment to the organization, thus reducing the likelihood of employee turnover.

The study highlights the crucial importance of mitigating health issues among education professionals. Simultaneously, the findings underscore the need for adequate resources and support to optimize the performance of education professionals, reaffirming the significant relationship between support and attitudes. Furthermore, the relevant role of satisfaction and engagement as preventive measures in reducing intentions to leave is acknowledged. In other words, our research shows that healthy professionals with adequate support demonstrate higher satisfaction and engagement in their activities, reflecting a professional who is more confident in their abilities and better prepared to handle educational challenges. These findings provide crucial insights for education professionals, educational authorities, and policymakers, highlighting how attitudes have been impacted by the effects of the COVID-19 pandemic. This offers valuable input for the development of interventions that enhance relationships between professionals and the public. Moreover, this study is of paramount importance, as research on how health complaints and organizational support impact the attitudes of professionals through structural equation modeling has rarely been conducted in the Brazilian population.

In today’s evolving work landscape, organizations must develop the capability to effectively navigate the challenges and embrace the opportunities presented by remote work. A key aspect of this is fostering a healthy work environment that prioritizes the physical and mental well-being of employees. To achieve this, organizations must provide adequate resources and support systems that empower employees to address the unique challenges associated with remote work. Central to this effort is the provision of emotional and psychological support, as well as the cultivation of a culture that encourages collaboration, communication, and active employee participation. By offering such resources and incentives, organizations can boost employee satisfaction, and engagement, and ultimately enhance employee retention rates.

This is the first study that explores a consistent relationship between turnover, satisfaction, and engagement, allowing this relationship to be measured and analyzed from the perspective of school management. In Brazil, there needs to be more resources to be invested in education, demanding more effective use. Unlike other productive sectors, in which defects and failures can be adjusted, errors of this nature can be irreparable in the education process. Thus, the prior identification of variables that can positively or negatively influence education workers will make the educational process more assertive.

6.1 Theoretical contributions

The study makes a significant theoretical contribution to research by uncovering the intricate relationship between health complaints, organizational support, and employee behavior. We not only identify these interrelationships but also shed light on the unique characteristics of the sample studied. Our findings highlight the value of the theory of Perceived Organizational Support as a powerful tool to foster employee perception that their contributions are valued, and their well-being is prioritized. Conversely, we demonstrate that a lack of such support can detrimentally impact job satisfaction and other behavioral outcomes. Furthermore, we provide additional empirical evidence emphasizing the pressing need for psychological and social support, as well as the importance of fostering relationships built on respect, appreciation, and recognition among workers.

6.2 Practical contributions

The pandemic has thrust remote work into the spotlight and enabled advancements in digital technologies for communication and collaboration. However, while remote work offers new possibilities for cooperation, there remain untapped opportunities to maximize its benefits for both employees and organizations. Recognizing that individuals are becoming increasingly adept with technology and that digital tools are increasingly integrated into educational settings, we believe that innovation using technology and social resources can enhance task performance and generate positive emotions. Establishing efficient, clear, and reliable communication channels that facilitate regular project discussions, goal setting, and task coordination can significantly improve well-being and productivity. However, it is crucial to prioritize the security of corporate data and employee privacy when promoting easy collaboration and information sharing. Managing these complexities can create additional demands and potential stressors.

The physical work environment remains a crucial factor in safeguarding employee health, even in a remote work setup. Shifting from the traditional office to alternative settings necessitates considerations such as ergonomic arrangements, creating appropriate workspaces, and establishing clear boundaries between work and rest areas. Supporting individualized work adaptations can enhance comfort, strike a better work-life balance, prevent physical issues, and ultimately contribute to employee well-being and increased productivity.

We have observed that the flexibility of remote work, combined with a humanized environment where employees feel safe and supported to express their ideas, makes an organization more appealing and fosters employee retention. It enables better integration of personal and professional life and facilitates the hiring of diverse talent from various geographic locations, cultures, and backgrounds, leading to a more creative, inclusive, and diverse workforce. In a virtual environment, achieving this entails implementing open communication policies, providing virtual brainstorming spaces, and cultivating a culture of respect and inclusion. Therefore, organizations must prioritize preparedness for unforeseen circumstances. It is crucial to incorporate contingency plans into strategic planning to ensure business continuity while safeguarding the health and safety of employees in future similar situations.

6.3 Limitations and future research

While this study contributes to the body of knowledge, it is important to acknowledge several limitations. Firstly, the study was conducted among a specific group of professionals who worked remotely during the COVID-19 period, which restricts the generalizability of the findings to a broader population. To enhance the external validity, it is advisable to replicate the study with professionals from diverse backgrounds or utilize longitudinal data to explore temporal effects and capture the characteristics of other professional groups. Furthermore, this study adopts a cross-sectional design and utilizes a non-probabilistic sample, which may limit the robustness of the conclusions and restrict the generalizability of the results. Employing a longitudinal design or a probabilistic sampling method could strengthen the study’s findings and allow for more generalizable outcomes. Caution should be exercised when interpreting the conclusions, as they may yield different results in alternative contexts, cultures, and age groups.

Another possible limitation is related to the level of analysis. This study was conducted from the individual perspective of the employee. Therefore, perhaps due to the conceptual assumptions implicit in the model, other implications may be discovered. In light of this, this point could be further explored, delving deeper into the investigation and discussing the phenomena from an organizational perspective on how to improve productivity, and performance, and yield organizational benefits in the context of remote work.

It should be emphasized that the present study explored only three among many important work-related aspects of professionals that contribute to the development of work environments, suggesting a relative limitation in understanding what constitutes these environments. Therefore, future research can expand on other work-related elements to obtain an even deeper understanding of the topic. Notably, aspects such as furniture, ergonomics, general infrastructure, and other latent or control variables were not directly investigated, which may present new research opportunities. The presence of indirect effects in the tested relationships underscores the complexity of these phenomena, suggesting that other variables not examined in this study may play crucial mediating or moderating roles. Further comprehensive research can shed light on the broader dynamics of the remote work environment. Including the variable “healthy work environments” in the structural model could help evaluate potential relationships or effects among the studied and suggested behaviors.

It is important to acknowledge these limitations and encourage future studies to address them, as they contribute to a better understanding of how the remote work environment can be optimized for employee well-being and organizational success. By investigating these unexplored aspects, future research can advance the field and provide valuable insights into the evolving nature of healthy work environments in crises.

7 Appendix A Description of the items

Variable

Description

Acronym

Items

Measurement Scale

V1 Health complaints

Measures the presence of negative symptoms in employee health. Adapted from Eriksen et al. (1999).

QS

QS_1 - Have you felt pain or discomfort in your shoulder/neck/back/arms/legs?

QS_2 - Have you felt stomach pain/heartburn/gas/diarrhea/constipation?

QS_3 - Have you felt headaches/migraines?

QS_4 - Have you felt anxiety/sadness/loneliness/fear/worry?

QS_5 - Have you felt tightness in the chest/fatigue/dizziness/shortness of breath/difficulty sleeping?

5-point Likert scale ranging from:

1 = Never;

2 = Rarely;

3 = Sometimes;

4 = Frequently;

5 = Always.

V2 Organizational support

Measures employees’ perception of organizational support within the company. Adapted from Eisenberger et al. (1997).

SO

SO_1 - The organization strongly considered my goals and values

SO_2 - The organization offered help when I had a problem.

SO_3 - The organization truly cared about my well-being.

SO_4 - When I made a mistake, the organization understood me.

SO_5 - The organization was willing to help me when I needed a specific favor.

SO_6 - If I allowed it, the organization would take advantage of me.

SO_7 - The organization showed little concern for me.

SO_8 - The organization cared about my opinions.

5-point Likert scale ranging from:

1 = Strongly disagree;

2 = Disagree;

3 = Neither agree nor disagree;

4 = Agree;

5 = Strongly agree.

V3 Job satisfaction

Measures the level of employee satisfaction at work. Adapted from Irawanto et al. (2021).

SF

SF_1 - Have you felt satisfied with remote work?

SF_2 - Have you felt satisfied with your coworkers?

SF_3 - Have you felt satisfied and happy with your supervisors?

SF_4 - Have you felt satisfied with your compensation?

V4 Work engagement

Measures the level of employee engagement at work. Adapted from Schaufeli et al. (2006).

EG

EG_1 - Have you felt energized in your work?

EG_2 - Have you felt strong and vigorous in your work?

EG_3 - Do you wake up/would you wake up in the morning, feeling eager to go to work?

EG_4 - Have you felt enthusiastic about your work?

EG_5 - Have you felt inspired by your work?

EG_6 - Have you felt proud of your work?

EG_7 - Have you felt happy when working intensively?

EG_8 - Have you felt immersed in your work?

EG_9 - Have you felt excited when working?

V5 Turnover intention

Measures the employee’s willingness to change jobs voluntarily. Adapted from Memon et al. (2021).

RT

RT_1 - Have you frequently thought about changing jobs?

RT_2 - Have you felt pressured to leave your job?

RT_3 - Have you seriously considered changing jobs in the next six months?

RT_4 - Would you leave your job if the existing working conditions worsened?

8 Appendix B Profile of the respondents

Variables

N

% total

Variables

N

% total

Age group

Marital status

  18 to 25 years old

4

1.39

Single

79

27.43

  26 to 35 years old

71

24.65

Married or Stable Union

173

60.07

  36 to 45 years old

104

36.11

Divorced

31

10.76

  46 to 55 years old

67

23.26

Widower

1.04

 

  Over 55 years old

42

14.58

Prefer not to answer

0.69

 

Gender

Children

  Male

119

41.32

 

None

109

37.85

  Female

163

56.6

 

1 child

81

28.13

  Non-binary

0.35

 

2 children

71

24.65

 

  Prefer not to answer

5

1.74

 

3 or more children

27

9.37

Remuneration range

Education level

  1 to 3 minimum wages

108

37.5

 

High school

2

0.69

  4 to 7 minimum wages

127

44.1

 

Undergraduate degree

25

8.68

  8 to 11 minimum wages

40

13.89

 

Specialization

103

35.76

  12 to 20 minimum wages

12

4.17

 

Master’s degree

98

34.03

  More than 20 minimum wages

1

0.35

 

Doctorate degree

60

20.84

Institution type

Start of hybrid remote mode

  Private

61

21.18

 

Before the pandemic

29

10.07

  Public

210

72.92

 

During the pandemic

254

88.19

  Both

17

5.9

 

After the pandemic

5

1.74

Position held

Teaching level

 Teachers

137

47.57

 

Elementary education

93

32.29

Administrative staff

96

33.34

 

Higher education

195

67.71

  Administrative staff with Leadership role

22

7.63

    

  Teachers with Leadership role

33

11.46

    

9 Appendix C Descriptive results

Construct

Item

Initial external loadings

Final external loadings

Initial Cronbach’s Alfa

Final Cronbach Alfa

Initial Composite reliability (rho_c)

Final Composite reliability (rho_c)

Initial AVE

Final AVE

 

V1 Health complaints

QS_1

0.809

0.809

0.877

0.877

0.910

0.910

0.670

0.670

 

QS_2

0.765

0.765

 

QS_3

0.820

0.820

 

QS_4

0.828

0.828

 

QS_5

0.867

0.867

 

V2 Organizational support

SO_1

0.786

0.794

0.869

0.881

0.899

0.908

0.534

0.588

 

SO_2

0.791

0.799

 

SO_3

0.866

0.867

 

SO_4

0.763

0.773

 

SO_5

0.754

0.777

 

SO_6

0.451

*

 

SO_7

0.639

0.607

 

SO_8

0.716

0.727

 

V3 Job satisfaction

SF_1

0.781

0.782

0.762

0.762

0.849

0.849

0.587

0.587

 

SF_2

0.780

0.780

 

SF_3

0.848

0.848

 

SF_4

0.642

0.642

 

V4 Work engagement

EG_1

0.846

0.845

0.948

0.948

0.956

0.956

0.709

0.709

 

EG_2

0.856

0.856

 

EG_3

0.814

0.813

 

EG_4

0.919

0.919

 

EG_5

0.894

0.895

 

EG_6

0.824

0.824

 

EG_7

0.829

0.829

 

EG_8

0.691

0.691

 

EG_9

0.884

0.884

 

V5 Turnover intention

RT_1

0.878

0.879

0.842

0.842

0.894

0.894

0.681

0.681

 

RT_2

0.789

0.788

 

RT_3

0.901

0.902

 

RT_4

0.719

0.718

 

* Excluded item after the evaluation process