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Article

Key Work Organization and Job Content Resources as Predictors of Work Engagement in the Lithuanian Education and Science Sector: A Sustainability Perspective

by
Gita Šakytė-Statnickė
1,2
1
Faculty of Social Sciences and Humanities, Klaipėda University, LT-92227 Klaipėda, Lithuania
2
Faculty of Business, Klaipėdos Valstybinė Kolegija, Higher Education Institution, LT-91274 Klaipėda, Lithuania
Societies 2026, 16(5), 161; https://doi.org/10.3390/soc16050161
Submission received: 29 January 2026 / Revised: 25 April 2026 / Accepted: 11 May 2026 / Published: 13 May 2026
(This article belongs to the Special Issue Leadership and Organizational Climate Building in the Context of School: From the Perspective of Student Development, Socialization and Achievement)
Versions Notes

Abstract

Background: Sustainability in education requires creating a supportive working environment that promotes the well-being, motivation, and professional development of employees in the education and science sector. From the perspective of sustainable human resource development in the education and science sector, it is essential to identify job resources that are positively associated with work engagement, as emphasized in the Job Demands-Resources (JD-R) model. The aim of this paper is to examine whether three key work organization and job content resources (influence at work, possibilities for development, and meaning of work) predict work engagement among employees in the Lithuanian education and science sector from a sustainability perspective. Methods: Based on the JD-R model, this study applied a quantitative research design. Data were collected through a structured written questionnaire completed by 446 employees in the Lithuanian education and science sector. The relationships between key work organization and job content resources and work engagement were examined using hierarchical multiple regression analysis, with gender, age, and position included as control variables. Results: The hierarchical regression analysis showed that meaning of work and influence at work remained statistically significant positive predictors of work engagement after controlling for gender, age, and position, whereas possibilities for development showed a positive but non-significant tendency in the controlled model. These findings are consistent with the Job Demands-Resources theory and can be interpreted from the perspective of the UNESCO Education for Sustainable Development framework, which emphasizes the importance of empowering teachers, scientists and other employees in the education and science sector, fostering continuous improvement, and connecting their work to a broader educational and societal purpose. Conclusions: The hierarchical regression analysis indicates that meaning of work and influence at work are the most stable predictors of work engagement in the education and science sector from a sustainability perspective. This study contributes to the literature by applying the JD-R model through a sustainability lens in the education and science sector. The results provide new insights into how influence at work, possibilities for development, and meaning of work can be interpreted as sustainability-oriented job resources associated with work engagement in the education and science sector.

1. Introduction

In an era of rapid changes and the strong integration of digital technologies in education, organizations in the education and science sector demand a high level of work engagement from employees. Work engagement is an important factor associated with employee performance and organizational functioning from a sustainability perspective. Additionally, work engagement significantly affects life satisfaction and community involvement, which is prominent in the public sector employees, including those in the education and science sector [1,2,3].
Sustaining high work engagement among employees in the education and science sector is increasingly viewed as a fundamental component of a resilient and sustainable education system. When educational professionals are motivated and supported, the entire system benefits through higher instructional quality, reduced turnover, and a greater capacity to adapt to societal needs [4,5]. Teachers’ work engagement is positively associated with job resources, with these resources being particularly important when job demands are high [6]. It is important to emphasize that work engagement is a key indicator of the sustainable functioning of the education and science sector, as it is associated with teacher burnout, increases teacher retention, facilitates the adaptation of such employees to active technological changes (digitization of the education sector, introduction of artificial intelligence) and contributes to the creation of education and science organizations as stable and sustainable systems [7,8,9].
The scientific literature identifies many different predictors of work engagement [10,11,12,13]. The most commonly used model in this area of research is the Job Demands-Resources model (JD-R model) [14,15].
Work organization and job content resources, such as influence at work, possibilities for development, and meaning of work, are important predictors of work engagement [16,17,18,19,20,21]. Although many studies have been conducted using the JD-R model and aiming to elucidate all the factors influencing work engagement [22], researchers agree that future research using this model could focus on systematically understanding what influences engagement in the specific industry sectors or across different professions [23]. By identifying key job resources that are relevant to employees in a specific sector, such as the education and science sector, and examining their predictive relationships with work engagement, this study can inform sustainability-oriented approaches aimed at supporting employee work engagement.
The education and science sector faces unique challenges, including emerging technologies (e.g., artificial intelligence), high workload, emotional stress, time-consuming tasks, etc., making it particularly important to identify key job resources. Addressing this gap is important for informing sustainability-oriented interventions tailored to the needs of this sector.
This study treats sustainability not as a background context, but as an analytical perspective that helps explain why specific job resources are especially important in the education and science sector. In line with the JD-R model, job resources stimulate motivation and work engagement [15,24]. From a sustainability perspective, these same resources can also be understood as conditions that support the long-term adaptability and professional continuity of the education and science sector workforce, which are important for sustainable educational systems [25,26]. Thus, influence at work, possibilities for development, and meaning of work are conceptualized in this paper as sustainability-oriented job resources because they strengthen employee work engagement and are theoretically relevant to the sustainable functioning of education and science organizations [27].
The aim of this paper is to examine whether three key work organization and job content resources (influence at work, possibilities for development, and meaning of work) predict work engagement among employees in the Lithuanian education and science sector from a sustainability perspective.

2. Literature Review

2.1. Work Engagement in the Education and Science Sector from a Sustainability Perspective

Work engagement is recognized as a key factor of long-term sustainability in educational institutions [28,29]. Work engagement is usually described in the scientific literature as “a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption” [30] (p. 99). As can be seen from the definition, work engagement comprises three components: vigor, which describes a high level of energy when working; dedication, which means strong commitment to the work being done and includes a sense of meaning, inspiration, and enthusiasm; absorption, which is characterized by a complete identification with work, where time seems to disappear and it is difficult to detach oneself from work [23,30].
The work engagement of teachers, scientists, and other employees in the education and science sector is important because previous research has shown that work engagement is associated with high creativity and effective task performance [31]. In addition, high levels of engagement are associated with better performance, greater effort and innovative behavior, which is crucial for an education or research organization’s adaptability to change and competitiveness [32]. Work engagement is an important factor associated with individual and organizational performance outcomes [2]. Engaged employees tend to experience lower levels of burnout and demonstrate a stronger commitment to their organizations, which fosters long-term organizational loyalty [33,34]. Teachers’ job satisfaction and work engagement have a positive impact on work outcomes [35].
High job demands, low personal resources and low job resources lead to the opposite of work engagement, namely burnout [36,37,38,39], which is often found among employees in the education and science sector due to the nature of the work. Recent research has particularly emphasized the importance of job and personal resources in fostering work engagement in the Job Demands and Resources (JD-R) model [14,15,40]. Work organization and job content resources such as influence at work, possibilities for development, and meaning of work are critical in influencing work engagement as they directly affect employees’ experiences, motivation, and capacity to perform effectively [16,17,18,19,20,21]. Recent studies in educational settings also continue to confirm that job resources remain important predictors of work engagement among teachers and academic staff [41,42,43].
Although the Job Demands-Resources (JD-R) model provides the main theoretical framework of this study, the three selected job resources can also be interpreted through complementary theoretical perspectives. Influence at work is conceptually related to psychological empowerment theory, which emphasizes employees’ perceived meaning, competence, self-determination, and impact, as well as to participative decision-making approaches, which highlight employees’ involvement in decisions affecting their work [44,45]. Possibilities for development can be linked to organizational learning and continuous professional development perspectives, which emphasize learning, competence development, professional adaptation, and collective capacity building in educational organizations [46,47]. Meaning of work can be connected to meaningful work theory and work as a calling/vocation perspective, which explains why employees may become more engaged when they perceive their work as personally significant, socially valuable, and connected to broader professional or societal purposes [48,49]. Thus, the JD-R model remains the central framework of the study, while these complementary perspectives help explain why influence at work, possibilities for development, and meaning of work may function as relevant job resources in the education and science sector.
In the Lithuanian context, the education sector provides a particularly relevant setting for examining work engagement and sustainability-oriented job resources. According to data from the Lithuanian State Data Agency, the Lithuanian education sector, particularly general education schools, is characterized by a strongly feminized and ageing teaching workforce. In the 2024–2025 school year, Lithuanian general education schools employed 27,186 teachers and school leaders, including 24,015 women and 3171 men; thus, women accounted for approximately 88.3% of this workforce. The age structure also shows that 45.1% of teachers and school leaders were aged 55 years or older, while only 5.3% were younger than 30 years [50]. These demographic characteristics highlight the relevance of work engagement, professional continuity, development opportunities, and meaningful work for the long-term functioning of the Lithuanian education system. Previous Lithuanian research has also examined work engagement in relation to job demands, job resources, and teacher performance, supporting the relevance of the JD-R perspective in this national educational context [42]. Lithuanian research on older employees in science, education, and public-sector organizations has also shown that work-related factors, including work scheduling autonomy and decision-making autonomy, are relevant to work engagement [51]. In addition, Lithuanian research on structural empowerment indicates that access to opportunities and resources is associated with occupational self-efficacy and work engagement, which supports the relevance of development opportunities as a psychosocial work resource [52]. More broadly, Lithuanian research on sustainable human resource management has emphasized that long-term employee well-being and organizational sustainability depend on work practices that support employee development, participation, and health-oriented working conditions [53]. In addition, the validated Lithuanian version of the Utrecht Work Engagement Scale provides an empirical basis for assessing work engagement in Lithuanian samples [54]. Therefore, the present study extends existing Lithuanian and international research by focusing on how selected work organization and job content resources (influence at work, possibilities for development, and meaning of work) are associated with work engagement in the Lithuanian education and science sector from a sustainability perspective.
Furthermore, from a sustainability perspective, supporting work engagement among employees in the education and science sector is relevant to the long-term capacity of educational and scientific institutions to maintain high-quality, adaptive, and socially responsive work environments [25,55]. Previous literature suggests that engaged educators may be better positioned to contribute to educational quality, professional continuity, and broader institutional aims related to sustainable development [56]. However, in the present study, sustainability is used as a theoretical and interpretative perspective rather than as a separately measured empirical outcome. Therefore, the study focuses specifically on whether selected work organization and job content resources are associated with work engagement in this sector.

2.2. Influence at Work and Work Engagement

From a sustainability perspective, it is crucial for education systems that educators and researchers are able to influence their work [25,55]. Empowering educators with decision-making authority not only supports their work engagement and well-being, but also enhances their capacity to deliver transformative education in order to develop sustainability competencies [56]. Influence at work is a necessary condition for work engagement in the work process [57] and has been recognized as one of the most important psychosocial working conditions affecting employee mental health [57,58,59], which is crucial for those working in the education and science sector. Other studies have shown that one of the main negative factors in the workplace is the perceived lack of control at work, which may contribute to the employee feeling powerless and helpless [60].
Employees in the education and science sector are often exposed to complex tasks and knowledge-intensive activities, and high levels of influence at work can help to meet the psychological needs for autonomy and competence, thereby increasing work engagement [61,62]. The ability to influence one’s work environment has been linked to greater psychological well-being, which is an important antecedent of work engagement. High levels of psychological well-being correlate with increased work engagement [63].
Specifically, when employees in the education and science sector can influence their teaching methods, research priorities, institutional policies, etc., they experience higher motivation and job satisfaction, which contribute to greater work engagement levels [35,64]. This positive relationship may be particularly relevant in contexts where employees face high job demands, such as heavy workloads, as previous research suggests that influence at work may buffer the adverse consequences of job demands [15,65]. From a sustainability perspective, influence at work is important not only as a motivational job resource, but also as a condition for participatory, inclusive, and adaptive educational organizations.
Based on the above considerations the following hypothesis can be proposed:
H1. 
Influence at work is positively associated with work engagement of employees in the education and science sector.

2.3. Possibilities for Development and Work Engagement

In the context of sustainable education, continuous professional development for employees in the education and science sector is vital not only for their personal careers but also for the adaptability and innovation of institutions [25,55]. When educational institutions prioritize capacity development and lifelong learning opportunities for their staff, they foster a culture of sustainability [66,67], and such an environment encourages engagement.
Possibilities for development in the education and science sector are particularly important given the dynamic nature of the sector and the need for continuous knowledge and skills development. Possibilities for development usually include opportunities for employees to acquire new knowledge and skills within a professional context–technological, pedagogical and research expertise, improve in the workplace and grow as a professional [68]. Previous studies have confirmed a positive relationship between possibilities for development and work engagement [69,70,71,72].
From a sustainability perspective, possibilities for development include not only the achievement of professional goals, traditional forms of professional development and the promotion of personal development, but also the development of sustainability competencies, access to interdisciplinary knowledge, support for the educational organization in implementing sustainable practices, etc. [73,74]. This increases the ability of employees in the education and science sector to independently initiate changes and contribute to the sustainable development of the educational organization. In addition, possibilities for development strengthen the long-term capacity of employees and institutions to respond to professional, technological, and societal change.
Based on the above considerations the following hypothesis can be proposed:
H2. 
Possibilities for development are positively associated with work engagement of employees in the education and science sector.

2.4. Meaning of Work and Work Engagement

The meaning of work in educational organizations is changing, as greater emphasis is placed on sustainability, and employees are also encouraged to contribute to the development of sustainability within the organization. When creating a culture of sustainability within an organization, the aim is to integrate sustainability into the organizational structure and everyday workplace culture, which requires an understanding of the role of employees in promoting sustainability [75]. In this process, the meaning of work for employees in the education and science sector is important due to the specifics of this sector. Employees who see their work as meaningful understand it better and are more productive and efficient in the professional environment [20,76]. The meaning of work is often understood when the positive aspects of work are emphasized, competencies that improve performance are developed, and opportunities to influence the content of the work performed are created [77]. In addition, employees in the education sector perceive the positive meaning of this work more intensely if it is directly related to their strategic and personal goals [78].
Previous research suggests that the meaning of work is closely related to work engagement and is also relevant in sustainability-oriented educational contexts. The negative correlation between job burnout and meaning of work was determined in Polish schools [7]. Chinese college teachers who find their work meaningful are more engaged and experience less job anxiety [79]. Feeling that one’s work is meaningful may enhance one’s work engagement [80].
An employee’s experience of meaningful work increases their desire to actively seek out information and experiences that are useful for their work, and this desire in turn increases their work engagement [81]. Meaning of work is one of the most important job resources that helps an employee become more engaged in work [79,82]. More recent evidence also suggests that meaningful work remains positively associated with work engagement in educational and higher education contexts [83,84]. From a sustainability perspective, meaning of work links everyday work activity with broader educational and social purpose, thereby strengthening both work engagement and commitment to the long-term mission of education and science sector organizations.
Based on the above considerations the following hypothesis can be proposed:
H3. 
Meaning of work is positively associated with work engagement of employees in the education and science sector.

3. Materials and Methods

3.1. Research Design and Measurement

The study used a quantitative research design, allowing for the measurement and statistical analysis of the relationships between the three job resources and work engagement. The research framework was based on the JD-R theory and model, according to which job resources promote work engagement [14,15,24,30,36]. In this study, these resources were further interpreted through a sustainability perspective in the education and science sector, because they may also support the long-term well-being, adaptability, and sustainable functioning of the workforce in this sector [25,27]. Sustainability was not operationalized as a separate empirical variable in this study. Instead, it served as a theoretical and interpretative perspective for explaining why key work organization and job content resources, grounded in the JD-R model and COPSOQ framework, may support work engagement and the sustainable functioning of education and science organizations [15,25,26,27,85,86].
The respondent survey was conducted using a written questionnaire, which was used to collect the research data. The questionnaire was developed based on an analysis of scientific literature examining the JD-R model and covered four main constructs: work engagement (WE), influence at work (IN), possibilities for development (PD), and meaning of work (MW). The questionnaire consisted of four scales designed to measure these constructs, as well as a block of demographic questions.
Work engagement was measured using the validated Lithuanian version of the 17-item Utrecht Work Engagement Scale (UWES-17), originally developed by Schaufeli and Bakker [87] and psychometrically validated in Lithuania by Lazauskaitė-Zabielskė, Urbanavičiūtė, and Rekašiūtė-Balsienė [54]. This scale covers three dimensions: vigor (e.g., “At my work, I feel bursting with energy”), dedication (e.g., “I am enthusiastic about my job”), and absorption (e.g., “I am immersed in my work”). The questions were rated on a 7-point Likert scale, where 0 meant “never” and 6 meant “always/daily.” Responses were summed and averaged to obtain an overall work engagement score.
Influence at work, possibilities for development, and meaning of work are part of “Work organization and job content” and were assessed with the Copenhagen Psychosocial Questionnaire (COPSOQ) [85]. “Work organization and job content” (WOJC) is included as a higher-order construct within this framework, reflecting how various aspects of work design influence psychological and physiological health outcomes [86]. In this study, the selected COPSOQ scales were translated from English into Lithuanian and then back-translated to ensure semantic and conceptual equivalence. No major changes to item content were introduced.
Influence at work was assessed using a 4-item scale (e.g., “Do you have a large degree of influence concerning your work?”). Possibilities for development were also measured using four questions (e.g., “Do you have the possibility of learning new things through your work?”), and the meaning of work was measured using three questions (e.g., “Is your work meaningful?”). All questions were taken from the COPSOQ instrument. Each item was rated on a scale from 0 to 100 (i.e., 0, 25, 50, 75, and 100 for questions with five response categories). The scale score was calculated as the average rating of the questions [85].
The internal consistency of the study scales was satisfactory, with Cronbach’s alpha coefficients of 0.923 for work engagement (17 items), 0.821 for influence at work (4 items), 0.815 for possibilities for development (4 items), and 0.843 for meaning of work (3 items).
The last section of the questionnaire consisted of demographic information, including the respondents’ age, gender, and current position at an educational or scientific organization.

3.2. Research Sample

Invitations to participate in the survey were sent via general institutional email addresses to Lithuanian education and science institutions, including schools, colleges, and universities. This was done to ensure the widest possible reach and to enable employees from different types of educational institutions to participate in the survey. This method of distributing invitations made it possible to reach employees from different types of institutions, occupational groups, and age categories within the Lithuanian education and science sector.
A total of 446 fully completed questionnaires were received, which constituted the final sample for analysis. The majority of respondents were women—88.3% (n = 394), while men accounted for 11.7% (n = 52). For descriptive purposes, age is presented in categories, whereas in regression analysis the original continuous age variable in years was used. The participants were distributed by age as follows: 2.5% (n = 11) were under 24 years old, 12.8% (n = 57) were 25–34 years old, 23.3% (n = 104) were 35–44 years old, 28.9% (n = 129) were aged 45–54, 26.2% (n = 117) were aged 55–64, and 6.3% (n = 28) were 65 years and older. According to their position in educational or scientific organizations, the respondents were distributed as follows: 26.2% (n = 117) were managerial staff, 73.8% (n = 329) were teaching and academic staff. Teaching and academic staff included teachers, lecturers, and researchers, whereas managerial staff included school, college, and university leaders and heads of units. To improve occupational homogeneity, service personnel were excluded from the final analytical sample.
This sample structure suggests that the study captured the experiences of different demographic groups within the Lithuanian education and science sector. The large proportion of women reflects the trends in the distribution of employees by gender in the Lithuanian education and science sector [50]. The age distribution shows that both younger and older employees participated in the study. The distribution of positions shows that the study mainly involved teaching and academic staff directly engaged in educational or scientific work, so the findings primarily reflect the characteristics of this occupational group.
Data collection took place from March to April 2025.
Three control variables were included in the regression analysis: gender, age, and occupational position. Gender was coded as a binary variable (0 = female, 1 = male). Age was treated as a continuous variable measured in years. Position was coded as a binary variable (0 = teaching and academic staff, 1 = managerial staff).

3.3. Ethical Considerations

Participation in the study was voluntary and unpaid. Before completing the questionnaire, respondents were informed about the aim of the study, the anonymous nature of participation, the confidential handling of data, and their right to discontinue participation at any stage without consequences. Informed consent was obtained from all participants prior to participation in the study.

3.4. Data Analysis

The research data were analyzed using IBM SPSS Statistics 25.0 software. First, descriptive statistics were used to determine the characteristics of the sample. The Kolmogorov–Smirnov test indicated that the distributions of the study variables deviated from normality. As a sensitivity-oriented preprocessing step, Blom-normalized scores were calculated for the three COPSOQ-based predictor variables: influence at work, possibilities for development, and meaning of work. These normalized predictor scores were used in the hierarchical regression analysis, whereas work engagement was retained in its original UWES scale as the dependent variable to preserve the interpretability of the outcome. Descriptive statistics and correlations are reported for the original scale scores. The reliability of the study was assessed using Cronbach’s alpha coefficient. Hierarchical multiple regression analysis was conducted to determine whether the key work organization and job content resources predicted work engagement. In the first model, influence at work, possibilities for development, and meaning of work were entered as main predictors. In the second model, gender, age, and occupational position were added as control variables.

4. Results

4.1. Descriptive Statistics

Table 1 presents the descriptive statistics for the study constructs. A descriptive statistical analysis was performed to determine the main characteristics of four constructs—work engagement (WE), influence at work (IN), possibilities for development (PD), and meaning of work (MW)–by assessing minimum and maximum values, means, and standard deviations.
As shown in Table 1, respondents in the present sample reported a relatively high level of work engagement (WE), with an average score of 4.76 out of 6. The perception of influence at work (IN) was moderate (52.76 out of 100) and showed considerable variability, indicating differences in respondents’ perceived opportunities to influence their work environment. Possibilities for development (PD) and meaning of work (MW) were rated highly (82.17 and 80.61 out of 100, respectively), suggesting that many respondents perceived favorable opportunities for professional growth and considered their work meaningful. These findings describe the analytical sample and should not be generalized to all employees in the Lithuanian education and science sector.

4.2. Correlations

Before performing multiple linear regression, the correlations between the main constructs of the study were assessed. As can be seen in Table 2, all variables correlate statistically significantly with the dependent variable—WE (p < 0.001). The strongest correlation was found between WE and MW (r = 0.651), which indicates a close relationship between these two constructs. Moderate correlations were also found between WE and PD (r = 0.420) and between WE and IN (r = 0.384). These results indicate that all three independent constructs are related to work engagement.
Moderate correlations were also found between the independent variables themselves: IN and PD (r = 0.497), PD and MW (r = 0.462), and IN and MW (r = 0.326). Although these relationships are statistically significant, their strength is not sufficient to pose a risk of excessive variable overlap in the regression model.

4.3. The Hierarchical Regression Models

The hierarchical regression analysis examined the predictive role of the key work organization and job content resources, which were theoretically conceptualized in the preceding sections as sustainability-relevant conditions for work engagement in the education and science sector. The dependent variable was work engagement (WE). In the first model, three main predictors were entered: influence at work, possibilities for development, and meaning of work. In the second model, three control variables were added: gender, age, and position. This modelling strategy made it possible to assess whether the main work organization and job content resources predicted work engagement of employees in the Lithuanian education and science sector and whether their predictive relationships remained stable after controlling for demographic and occupational characteristics.
Model fit indices for the hierarchical regression models predicting work engagement are presented in Table 3. The first regression model was statistically significant, F(3, 442) = 120.932, p < 0.001. The model explained 45.1% of the variance in work engagement, R2 = 0.451, adjusted R2 = 0.447. This indicates that influence at work, possibilities for development, and meaning of work together explained a substantial proportion of variance in work engagement.
The second model, which additionally included gender, age, and position, was also statistically significant, F(6, 439) = 61.725, p < 0.001. This model explained 45.8% of the variance in work engagement, R2 = 0.458, adjusted R2 = 0.450. Compared with the first model, the increase in explained variance was small, ΔR2 = 0.007. The additionally calculated model-change test indicated that this increase was not statistically significant, ΔF(3, 439) = 1.833, p = 0.140. Therefore, gender, age, and position did not significantly improve the prediction of work engagement.
Regression coefficients for the predictors of work engagement are presented in Table 4. In the first model, all three main predictors were positively associated with work engagement. Meaning of work was the strongest predictor, B = 0.657, SE = 0.048, β = 0.547, t = 13.713, p < 0.001, 95% CI [0.563, 0.751]. This indicates that a higher perceived meaning of work was associated with higher work engagement. Influence at work was also a statistically significant positive predictor, B = 0.205, SE = 0.050, β = 0.167, t = 4.092, p < 0.001, 95% CI [0.106, 0.303]. This result indicates that greater perceived influence at work was associated with higher employee work engagement. Possibilities for development were also a statistically significant, although weaker, predictor in the first model, B = 0.113, SE = 0.057, β = 0.086, t = 1.975, p = 0.049, 95% CI [0.001, 0.225]. Thus, before the inclusion of control variables, greater possibilities for development were associated with higher work engagement; however, the association was weak.
After gender, age, and position were included in the second model, meaning of work remained the strongest and statistically significant predictor of work engagement, B = 0.643, SE = 0.049, β = 0.536, t = 13.234, p < 0.001, 95% CI [0.548, 0.739]. Influence at work also remained statistically significant, B = 0.199, SE = 0.054, β = 0.163, t = 3.707, p < 0.001, 95% CI [0.093, 0.304]. However, possibilities for development were no longer a statistically significant predictor in the second model, B = 0.103, SE = 0.057, β = 0.079, t = 1.802, p = 0.072, 95% CI [−0.009, 0.216].
The control variables did not significantly predict work engagement. Gender was not a statistically significant predictor, B = 0.005, β = 0.002, p = 0.950. Age was also not statistically significant, B = 0.004, β = 0.068, p = 0.059. Position likewise did not significantly predict work engagement, B = 0.077, β = 0.045, p = 0.240.
Regression diagnostics were examined to evaluate selected assumptions of the regression model. The collinearity diagnostics did not indicate problematic multicollinearity among the predictors. Variance inflation factor values ranged from 1.039 to 1.559, and tolerance values ranged from 0.641 to 0.962, indicating that the independent variables were not excessively intercorrelated. The Durbin-Watson statistic for the final model was 2.054, suggesting no clear evidence of residual autocorrelation. In addition, standardized residuals ranged from −2.840 to 2.848, remaining within the commonly accepted ±3 threshold. Overall, these diagnostic indicators suggest that the regression model did not show problematic violations related to multicollinearity, independence of errors, or extreme standardized residuals.
A summary of hypothesis testing is presented in Table 5. H1 stated that influence at work is positively associated with work engagement of employees in the education and science sector. This hypothesis was supported. Influence at work was a positive and statistically significant predictor of work engagement both in the first model, β = 0.167, p < 0.001, and in the second model after controlling for gender, age, and position, β = 0.163, p < 0.001. This indicates a stable, although relatively modest, positive association.
H2 stated that possibilities for development are positively associated with work engagement of employees in the education and science sector. This hypothesis was only partially supported. In the first model, possibilities for development were a positive and statistically significant predictor, β = 0.086, p = 0.049. However, after the control variables were included, the association became statistically non-significant, β = 0.079, p = 0.072. Because the 95% confidence interval in the final model included zero, 95% CI [−0.009, 0.216], the conservative conclusion is that possibilities for development showed a positive tendency but did not show a sufficiently stable independent association with work engagement after controlling for gender, age, and position.
H3 stated that meaning of work is positively associated with work engagement of employees in the education and science sector. This hypothesis was supported. Meaning of work was the strongest positive predictor of work engagement both in the first model, β = 0.547, p < 0.001, and in the second model, β = 0.536, p < 0.001. This result indicates that perceived meaning of work was the central predictor of work engagement in this sample of employees from the education and science sector.

5. Discussion

The results show that the selected work organization and job content resources were positively associated with work engagement in the initial model. However, after controlling for gender, age, and occupational position, meaning of work and influence at work remained statistically significant predictors, whereas possibilities for development showed a positive but non-significant tendency. Meaning of work emerged as the strongest predictor of work engagement in the present sample.
First, the study found that when employees in the education and science sector perceive greater influence over their work environment or work-related decisions, their work engagement tends to increase. The results of the study support previous research. For example, Ryan and Deci [61] and Baka et al. [62] suggest that high levels of influence at work can help to meet the psychological needs for autonomy and competence, thereby supporting work engagement. In addition, Mazzetti et al. [65] and Bakker et al. [15] emphasize that, under conditions of high job demands, influence at work may serve as a buffering resource that helps mitigate the adverse effects of these demands and may support work engagement. Although job demands were not directly measured in the present study, this mechanism provides a useful theoretical explanation for the observed association between influence at work and work engagement. The results of the study also support Andersen et al.’s [57] view that influence at work is a prerequisite for work engagement in the work process. From a sustainability perspective, influence at work can be interpreted as a psychosocial resource that may support employees’ participation, autonomy, and involvement in organizational life. In the present study, higher perceived influence at work was associated with higher work engagement, suggesting that employees who perceive greater opportunities to shape aspects of their work may be more engaged. In educational and scientific organizations, such influence may include participation in shaping educational content, research directions, or organizational processes, which may strengthen employees’ sense of involvement and responsibility for institutional activities [88,89,90]. Theoretically, this form of participation may also be relevant to the development of a more inclusive, transparent, and long-term decision-making culture [91,92]. This interpretation is consistent with the idea that sustainable educational and scientific organizations depend not only on formal policies or infrastructure, but also on working conditions that support employee agency and participation. However, the present study did not directly measure participatory governance, institutional resilience, decision-making culture, or sustainability outcomes; therefore, these implications should be interpreted as theoretical rather than empirically tested conclusions.
Second, possibilities for development were positively associated with work engagement in the initial model; however, after controlling for gender, age, and occupational position, their independent predictive role was no longer statistically significant. This result suggests that development opportunities may be relevant to work engagement, but their unique explanatory role is weaker when sociodemographic and occupational characteristics are considered. Their role may be partly indirect, context-dependent, or shared with other job resources rather than operating as a stable independent predictor in the controlled model. The finding only partially supports previous studies indicating that professional development opportunities are linked to job satisfaction and work engagement [71], that possibilities for development are positively associated with work engagement [72], and that job resources such as autonomy, development opportunities, and social support may enhance work engagement [69,70]. From a sustainability perspective, development opportunities remain important because they support lifelong learning, professional adaptability, and employees’ capacity to respond to technological, pedagogical, and societal change in educational contexts [27,93,94,95,96]. Thus, although possibilities for development did not emerge as a stable independent predictor in the controlled model, they remain theoretically relevant as part of a broader sustainability-oriented work environment. In theoretical terms, development opportunities may support lifelong learning and professional adaptability, which are important in educational and scientific work settings characterized by pedagogical, technological, and societal change [73,93,96,97,98]. However, the present study did not measure sustainability-related teaching practices, sustainability competencies, or institutional sustainability outcomes. Therefore, the role of development opportunities should be discussed as a theoretically relevant condition within a sustainability-oriented work environment, not as an empirically confirmed driver of sustainability outcomes.
Third, meaning of work emerged as the strongest predictor of work engagement in the controlled model. This stronger association may be explained by the specific nature of educational and scientific work. Employees in this sector may perceive their work not only as a set of formal tasks, but also as a socially valuable contribution with a broader purpose. Previous research shows that meaningful work is consistently associated with higher work engagement, and in the educational context this link may be especially salient because teaching and academic staff can directly observe the positive impact of their work on others [80,99]. From a sustainability perspective, meaning of work can be linked to the perception that one’s work contributes to broader educational and societal goals [100,101,102]. Previous literature on education for sustainable development and whole-institution approaches provides a broader theoretical context for interpreting why meaning of work may be particularly relevant in educational and scientific organizations. When educational work is connected to broader societal and sustainability-related aims, it can be interpreted as socially purposeful and institutionally significant [103,104]. However, the present study did not directly examine whether respondents associated their work meaning with sustainability-related aims; therefore, this interpretation should be treated as theoretical rather than as an empirical finding of the study.
The results of the present study indicate that meaning of work was the strongest predictor of work engagement among the analyzed resources. This finding is consistent with previous studies showing that work meaning is associated with work engagement and related work outcomes [20,76]. It also corresponds to Li’s [79] findings that teachers who perceive their work as meaningful tend to report higher engagement and lower job anxiety, and to other studies indicating that meaningful work is one of the important motivational factors associated with work engagement [80,81,82]. The strength of this relationship in the present study may be explained by the nature of educational and scientific work, where employees often connect their daily tasks with students’ development, knowledge creation, and contribution to the public good. In this sense, meaning of work may operate as a proximal motivational resource that directly supports dedication and involvement in work. Several alternative explanations should also be considered. Meaning of work may be more closely associated with the motivational core of work engagement than the other analyzed job resources, especially because work engagement includes dedication as one of its central dimensions [14,65,105]. At the same time, the observed relationship may also be influenced by other factors not included in the model, such as self-efficacy, organizational commitment, or professional identity, which have also been linked to work engagement in educational contexts [106,107,108]. Therefore, the findings should be interpreted within the empirical scope of the study: employees in the present sample who perceived their work as more meaningful also reported higher work engagement. Future research could examine whether meaning of work and work engagement are associated with sustainability-related teaching practices, transformative education, or the promotion of sustainability principles, as these outcomes were not directly assessed in the present study.

6. Conclusions

This study contributes to the broader discussion on sustainability by emphasizing the human resources aspect of a sustainable education system, as sustainability in education also means creating a sustainable working environment that promotes the well-being, motivation, and professional development of employees in the education and science sector. The results of the study highlight the importance of empowering teachers, providing them with opportunities for development, and helping them find meaning in their work. These elements are relevant to work engagement in the education and science sector and may be theoretically linked to the development of more sustainable, resilient, and adaptive educational organizations.
The results of the hierarchical regression analysis showed that meaning of work and influence at work were statistically significant positive predictors of work engagement after controlling for gender, age, and occupational position. Possibilities for development showed a positive tendency, but its independent predictive association was not statistically significant in the controlled model. Therefore, the findings indicate that meaning of work and influence at work are the most stable work organization and job content resources explaining work engagement in the present sample. From a sustainability perspective, these findings suggest that educational and scientific organizations seeking more sustainable human resource development should not focus only on formal policies, curricula, or infrastructure, but also on selected work organization and job content resources, because strengthening meaning of work and influence at work may contribute to higher work engagement.
These findings are theoretically relevant to understanding sustainability-oriented change in education, where influence at work, possibilities for development, and meaning of work may be considered supportive psychosocial conditions for employee engagement. Work environments in which educators are empowered to act autonomously, engage in meaningful professional development, and perceive their work as socially meaningful may support motivation and work engagement. From a sustainability perspective, such conditions can be interpreted as theoretically relevant to broader educational goals, although sustainability outcomes were not directly measured in this study.

7. Theoretical and Practical Implications

This study contributes to a deeper understanding of work engagement in the education and science sector by examining whether three key work organization and job content resources (influence at work, possibilities for development, and meaning of work) predict work engagement from a sustainability perspective.
By showing that meaning of work and influence at work remained significant predictors of work engagement in the controlled model, while possibilities for development showed a positive but non-significant tendency, the study contributes to the application of the JD-R theory in the education and science sector from a sustainability perspective.
Practically, the findings suggest that sustainability-oriented human resource management in educational and scientific organizations should prioritize psychosocial work conditions that strengthen employees’ perceived meaning of work and influence at work. Development opportunities also remain important as part of a broader sustainability-oriented work environment, although their independent predictive role should be interpreted cautiously in the present model.
Furthermore, institutions seeking to develop a more sustainable work environment should not limit themselves to updating training programs or improving infrastructure. The present findings suggest that attention should also be paid to psychosocial work conditions, particularly meaning of work and influence at work, because these resources were positively associated with work engagement. Such practices may support long-term employee engagement, especially in sectors such as education, where human capital is central to organizational functioning.

8. Limitations and Future Research

Although this study provides valuable insights into work engagement in the Lithuanian education and science sector, several limitations should be acknowledged. First, the study is limited to employees in the Lithuanian education and science sector. Therefore, the findings should not be generalized beyond this national and sectoral context without caution. Comparative studies in different countries or institutional contexts could reveal whether the model presented in the article holds true in other cultural or institutional contexts. Longitudinal studies could also help determine whether changes in influence at work, possibilities for development, and meaning of work lead to changes in work engagement over time. This is particularly important because the present study used a cross-sectional design, which does not allow causal conclusions to be drawn. In addition, all variables were measured using self-reported questionnaire data from the same respondents, which may introduce social desirability bias and common method variance. Future studies could reduce this limitation by using time-separated measurements or additional data sources.
Second, the sample was strongly dominated by women. This structure is consistent with the gender distribution typical of the Lithuanian education sector; however, the relatively small number of male respondents limits the possibility of drawing stronger conclusions about gender-based differences in work engagement. Although gender was included as a control variable in the hierarchical regression model, future studies with more balanced samples could examine whether the relationships between job resources and work engagement differ by gender.
Third, the final analytical sample was restricted to teaching and academic staff and managerial staff, while service personnel were excluded to improve occupational homogeneity. Occupational position was included as a control variable in the regression model. Nevertheless, the teaching and academic staff category still includes different professional roles, such as teachers, lecturers, and researchers. Future research could analyze these occupational subgroups separately in order to determine whether the predictors of work engagement differ across specific professional roles within the education and science sector.
Fourth, this study examined direct predictive relationships using hierarchical multiple regression analysis. This approach was appropriate for the aim of the study, which was to assess whether selected work organization and job content resources predict work engagement after controlling for gender, age, and occupational position. However, future studies could apply more complex analytical approaches, such as structural equation modeling, mediation analysis, moderation analysis, or longitudinal designs, to examine indirect mechanisms, causal ordering, and potential differences across occupational or institutional groups.
Fifth, the study focuses mainly on three job resources, while the Job Demands-Resources (JD-R) theory offers a broader range of possible predictors. Future research could expand the model by including additional job resources and job demands to better understand the dynamics of work engagement in the education and science sector from a sustainability perspective.
Another limitation is that sustainability was used as a theoretical and interpretative perspective rather than measured as a separate empirical construct. Future studies could include direct measures of sustainability-oriented organizational practices, sustainable human resource management, or sustainability climate to examine how these factors interact with job resources in predicting work engagement. Therefore, the present findings should not be interpreted as evidence that the analyzed job resources directly produce sustainability outcomes. Rather, they show that selected psychosocial work resources are associated with work engagement and can be interpreted within a sustainability-oriented theoretical framework.
Future research could investigate whether and how sustainability-oriented practices in educational institutions are related to the association between job resources and work engagement. Cross-cultural or cross-institutional comparative studies could reveal whether organizational environments that explicitly integrate sustainability are associated with stronger work engagement. Future research should also explore not only statistical relationships but also educators’ personal experiences of work meaning, professional development, and participation in organizational life. By integrating quantitative evidence with qualitative insights, future studies could provide a more comprehensive understanding of how work engagement can be supported in sustainability-oriented educational and scientific organizations.

Funding

This research was funded by the Research Council of Lithuania (LMTLT), agreement number S-PD-24-53.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Committee on Research Ethics Compliance of Klaipeda University (approval No. MTEK-07; date of approval: 1 April 2025).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The author declares no conflict of interest.

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Table 1. Descriptive Statistics (N = 446).
Table 1. Descriptive Statistics (N = 446).
ConstructsMinimumMaximumMeanStd. Deviation
WE1.886.004.75780.75045
IN0.00100.0052.760721.94458
PD25.00100.0082.174915.96122
MW0.00100.0080.605417.79954
The WE scale ranged from 0 to 6; the IN, PD, and MW scales ranged from 0 to 100. Note. WE = work engagement; IN = influence at work; PD = possibilities for development; MW = meaning of work.
Table 2. Correlations of Constructs (N = 446).
Table 2. Correlations of Constructs (N = 446).
ConstructsWEINPDMW
Pearson CorrelationWE1.000
IN0.3841.000
PD0.4200.4971.000
MW0.6510.3260.4621.000
Note. WE = work engagement; IN = influence at work; PD = possibilities for development; MW = meaning of work. Correlations are reported for the original scale scores. All non-diagonal correlations are statistically significant at p < 0.001. Blom-normalized predictor scores were used in the hierarchical regression analysis.
Table 3. Model fit indices for the hierarchical regression models predicting work engagement.
Table 3. Model fit indices for the hierarchical regression models predicting work engagement.
ModelPredictorsRR2Adjusted R2SE EstimateFdf1df2p
1Influence at work
Possibilities for development
Meaning of work		0.6710.4510.4470.55803120.9323442<0.001
2Influence at work
Possibilities for development
Meaning of work
Gender
Age
Position		0.6760.4580.4500.5564661.7256439<0.001
Note. Dependent variable: work engagement (WE). N = 446. Blom-normalized scores of influence at work, possibilities for development, and meaning of work were used in the hierarchical regression analysis.
Table 4. Regression coefficients predicting work engagement.
Table 4. Regression coefficients predicting work engagement.
PredictorBSEβtp95% CI for BToleranceVIF
Model 1
Influence at work0.2050.0500.1674.092<0.001[0.106, 0.303]0.7421.347
Possibilities for development0.1130.0570.0861.9750.049[0.001, 0.225]0.6561.524
Meaning of work0.6570.0480.54713.713<0.001[0.563, 0.751]0.7811.281
Model 2
Influence at work0.1990.0540.1633.707<0.001[0.093, 0.304]0.6411.559
Possibilities for development0.1030.0570.0791.8020.072[−0.009, 0.216]0.6501.538
Meaning of work0.6430.0490.53613.234<0.001[0.548, 0.739]0.7531.329
Gender0.0050.0840.0020.0630.950[−0.159, 0.170]0.9621.039
Age0.0040.0020.0681.8910.059[0.000, 0.009]0.9491.054
Position0.0770.0650.0451.1770.240[−0.051, 0.204]0.8481.179
Note. Dependent variable: work engagement (WE). B = unstandardized regression coefficient; SE = standard error; β = standardized regression coefficient; CI = confidence interval; VIF = variance inflation factor. Blom-normalized scores of influence at work, possibilities for development, and meaning of work were used in the hierarchical regression analysis.
Table 5. Summary of hypothesis testing.
Table 5. Summary of hypothesis testing.
HypothesisStatementMain ResultDecision
H1Influence at work is positively associated with work engagementModel 1: β = 0.167, p < 0.001
Model 2: β = 0.163, p < 0.001		Supported
H2Possibilities for development are positively associated with work engagementModel 1: β = 0.086, p = 0.049
Model 2: β = 0.079, p = 0.072		Partially supported
H3Meaning of work is positively associated with work engagementModel 1: β = 0.547, p < 0.001
Model 2: β = 0.536, p < 0.001		Supported
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Šakytė-Statnickė, G. Key Work Organization and Job Content Resources as Predictors of Work Engagement in the Lithuanian Education and Science Sector: A Sustainability Perspective. Societies 2026, 16, 161. https://doi.org/10.3390/soc16050161

AMA Style

Šakytė-Statnickė G. Key Work Organization and Job Content Resources as Predictors of Work Engagement in the Lithuanian Education and Science Sector: A Sustainability Perspective. Societies. 2026; 16(5):161. https://doi.org/10.3390/soc16050161

Chicago/Turabian Style

Šakytė-Statnickė, Gita. 2026. "Key Work Organization and Job Content Resources as Predictors of Work Engagement in the Lithuanian Education and Science Sector: A Sustainability Perspective" Societies 16, no. 5: 161. https://doi.org/10.3390/soc16050161

APA Style

Šakytė-Statnickė, G. (2026). Key Work Organization and Job Content Resources as Predictors of Work Engagement in the Lithuanian Education and Science Sector: A Sustainability Perspective. Societies, 16(5), 161. https://doi.org/10.3390/soc16050161

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