Activity level and general well-being indicators among university students

Context and relevance. The study of indicators of general well-being and drivers of activity among students is particularly relevant in the context of modern challenges in the educational environment. Student life is a critical stage of personal and professional development, accompanied by high academic loads, the need to adapt to sociocultural changes, and the formation of life goals and social connections. In this context, the ability to effectively manage one's own time, goals, and relationships, which are the drivers of activity, becomes a key factor in successful adaptation and psychological comfort. Objective. To study the indicators of general well-being among students in the higher education system and their relationship with the level of activity. Hypothesis. The level of activity is interrelated with indicators of general well-being among students: as activity increases, well-being also increases. Methods and materials. The study involved 297 undergraduate students of a humanitarian university (M = 21,1, SD = 4,0, 84% female). Indicators of general well-being were assessed using a battery of questionnaires (Spielberger-Khanin self-assessment scale of anxiety level, V. Zung's method of differential diagnosis of depressive states (adapted by T.I. Balashova), N.P. Fetiskin's scale of subjective well-being, N. Hall's method for assessing emotional intelligence, etc.), and the level of activity was determined using E.B. Bashkin's "Drivers of student learning activity" method. Results. The results showed that all the studied indicators of general well-being differed among students with different levels of activity. Conclusions. It has been shown that the ability to effectively manage goals, time, and relationships, on the one hand, contributes to a decrease in personal anxiety and depression, an increase in emotional intelligence, but on the other hand, it leads to an increase in situational anxiety and a decrease in subjective well-being.

Introduction

The study of general well-being indicators and drivers of activity among students is becoming particularly relevant in the context of contemporary challenges in the educational environment. Student life represents a critical stage of personal and professional development, accompanied by high academic loads, the need to adapt to sociocultural changes, and the formation of life orientations and social connections. In these conditions, the ability to effectively manage one’s own time, goals, and relationships — which are the drivers of activity — becomes a key factor in successful adaptation and psychological comfort. The article presents an empirical study of differences in anxiety, depression, subjective well-being, and emotional intelligence among students with different levels of activity. It also examines the relationships between general well-being indicators and activity drivers. The conducted study led to the conclusion that the ability to effectively manage goals, time, and relationships, on the one hand, contributes to a decrease in trait anxiety and depression and an increase in emotional intelligence, but, on the other hand, leads to an increase in state anxiety and a decrease in subjective well-being. General well-being

The concept of general well-being does not have a single origin attributable to a specific researcher; rather, it gradually developed through theoretical and empirical research spanning multiple disciplines. The earliest philosophical roots of this concept can be traced to John Stuart Mill in the 19th century. He defined happiness and the absence of suffering as the ultimate goals of human beings, thereby laying a solid foundation for subsequent formulations of well-being. However, he did not provide a formal definition of “general well-being” as a distinct psychological construct (Jacobs, 1991).

In the 20th century, Marie Jahoda was one of the first to formulate a multidimensional model of positive mental health, identifying criteria such as self-acceptance, growth, integration, autonomy, and environmental mastery. Although she did not introduce the term “general well-being”, her work became a fundamental basis for later models aimed at covering a wide range of well-being components (Jahoda, 1958).

Later, Carol Ryff proposed a model of psychological well-being, clearly defining the components of optimal psychological functioning: self-acceptance, personal growth, purpose in life, environmental mastery, autonomy, and positive relations. Ryff’s model, while not addressing the term “general well-being”, largely corresponds to its concept by integrating cognitive, emotional, and social aspects of positive functioning (Ryff, 1989).

Concurrently, Ed Diener introduced the concept of subjective well-being, which includes a cognitive component (perception of well-being and life satisfaction), an emotional component (positive and negative affects), and a behavioral component. Despite the similarity of the components he identified to Ryff’s model, Diener distinguished subjective well-being from psychological well-being (Diener, Suh, Lucas, Smith, 1999).

Later, Martin Seligman presented the PERMA model within positive psychology, comprising five elements: positive emotions, engagement, relationships, meaning, and accomplishment — reflecting both hedonic and eudaimonic aspects of well-being (Seligman, 2013). This model partially replicates and expands previous approaches, explicitly integrating life goals and achievements as core components of general well-being.

Thus, there exist concepts of mental health, subjective well-being, and psychological well-being, the synthesis of which constitutes the concept of general well-being. The synthesis of these concepts occurred as a result of empirical research showing that components of subjective and psychological well-being can be combined into a single model with a common higher-order factor. The adequacy and appropriateness of extracting this general well-being factor to describe different lower-order factors have been tested in several studies (Disabato et al., 2016; de Bruin, 2015; Chen et al., 2013). Based on these data, researchers from the United Kingdom proposed the Scales of General Well-Being (SGWB), which includes 14 well-being constructs: happiness, cheerfulness, calmness, optimism, engagement, mindfulness, self-acceptance, self-esteem, competence (sense of effectiveness in one’s own activities), self-development, sense of meaning and purpose in life, sense of importance and value of one’s own activities, congruence, and social connections (Longo, Coyne, Joseph, 2017).

Although the concept of general well-being is scarcely addressed by Russian researchers, it is consistent with the main methodological concepts of Russian psychology — L.S. Vygotsky’s cultural-historical theory and A.N. Leontiev’s activity approach (Rubtsov, Zaretsky, Maidansky, 2024). The key link is that well-being is not innate or purely individual; it is mediated by culture and generated by the quality of a person’s activity. Within the cultural-historical framework, well-being is the ability to use cultural tools to regulate one’s behavior and emotions; the presence of meanings set by the cultural context; the quality of social interaction in the zone of proximal development, through which a person not only learns but also receives support and recognition that can become the foundation of general well-being (Rubtsov, 2016). Within the activity approach, well-being is the opportunity to engage in meaning-making activity, where motive and goal are closely linked; the construction of identity through activity, success in which strengthens self-respect and self-esteem and also becomes an important factor of well-being. Thus, Vygotsky’s theory explains the cultural-historical foundations and mediation of various aspects of well-being, while the activity approach explains the mechanism of its realization through the structure of activity. Together, these approaches form a socio-activity model of well-being, useful both for theoretical understanding and for designing interventions and measurements across different cultures.

It is worth noting that despite the existence of the SGWB, there is still no consensus on a clear definition, components, and universally accepted structure of general well-being. Summarizing the studied approaches and concepts that have formed the basis for studying general well-being, it can be said that it is a complex and multidimensional construct, combining both subjective experiences and objective indicators of psycho logical functioning and adaptation of the individual. It is an integrative state including life satisfaction, positive and negative affects, as well as the realization of personal potential, social activity, and meaning-of-life orientations.

Drivers of activity

The first component of activity drivers is time manag

ement. This is a conscious and purposeful process of allocating time between academic and personal tasks in order to optimize productivity and reduce stress. In the student context, time management includes prioritization, planning task completion, and regulating distractions, which contributes to achieving academic and personal goals (Aeon, 2021). The ability to manage one’s own time becomes especially important today, in the era of accelerating information flows and constant changes in educational conditions. This skill requires deliberate formation and support both at the individual and institutional levels.

The second activity driver is goal management — a complex activity involving the conscious setting of a hierarchy of goals, structuring them according to priorities and time frames, adaptation, and reassessment during study and self-realization. Goal setting is viewed as a dynamic process that includes the development of stable motivation and self-regulation, particularly self-control and evaluation of one’s own achievements (Locke, Latham, 2006). In the context of student activity, goal management becomes a fundamental element of effectiveness, ensuring the optimization of efforts through conscious planning, motivation, and control.

The third component of activity drivers is relationship management. This is a dynamic process that includes emotional and social perception of oneself and others, communication skills, the ability to work in a team, as well as constructive conflict resolution and adaptation to various social contexts. Relationship management skills in students facilitate the establishment of social connections, which can improve learning motivation, facilitate material assimilation, and increase engagement in collective learning activities. The link between effective social interaction and academic performance and reduced anxiety is supported by empirical research (Jurado, Molero, et al, 2021).

The study uses a questionnaire developed by Bashkin E.B., Chudina Yu.A., and Shlyakhta D.A. (Bashkin, Chudina, Shlyakhta, 2025). This questionnaire measures all three components of activity: time management, relationship management, and goal management. The questionnaire consists of 28 items: 7 items for the Time Management scale, 12 items for the Relationship Management scale, and 9 items for the Goal Management scale. Based on a psychometric analysis conducted on 707 respondents, the researchers found the questionnaire to be valid and reliable. It allows assessment of three key drivers that determine the effectiveness of managing learning activities: prioritizing activities through their goals (goal management), optimal time allocation (time management), and key communication and interaction skills in implementing activities (relationship management).

Materials and methods

The aim of this study is to examine general well-being indicators among students in higher education and their relationship with the level of activity.

Procedure. The study was conducted in two stages: the first stage examined differences in general well-being indicators among students with different levels of activity; the second stage examined the relationship between general well-being indicators and the expression of activity drivers. General well-being indicators were assessed using a battery of questionnaires (Spielberger—Khanin Self-Rating Anxiety Scale, W. Zung’s Differential Depression Scale adapted by T.I. Balashova, N.P. Fetiskin’s Subjective Well-Being Scale, N. Hall’s Emotional Intelligence Scale). The level of activity was determined using E.B. Bashkin’s “Drivers of Student Learning Activity” questionnaire. Statistical processing of the obtained data was performed using Jamovi software. The following methods of mathematical statistics were used: Shapiro—Wilk normality test, Kruskal—Wallis test (to find significant differences), Dwass—Steel—Critchlow—Fligner test (for pairwise comparisons between groups), and Spearman’s rank correlation coefficient (to identify statistically significant correlations).

Hypothesis. The level of activity influences general well-being indicators among students: as activity increases, well-being also increases.

Participants. The study involved 297 undergraduate students of humanities majors (M = 21,1, SD = 4,0, 84% female) from the 2nd and 3rd years of the 2024/2025 academic year, studying at the Patrice Lumumba Peoples’ Friendship University of Russia. No data were excluded from further calculations. Results

At the preliminary stage of the study, the normality of the distribution of the empirical data was tested using the Shapiro—Wilk test. The results showed that the data were not normally distributed; therefore, it was decided to use nonparametric methods in subsequent work. Also at this stage, the distribution of respondents by level of activity was determined. It was found that 79 respondents had a high level of activity, 99 had a medium level, and 86 had a low level.

The first stage of the study was to search for significant differences in general well-being indicators among students with different levels of activity using the Kruskal—Wallis test (Table 1).

A comparative analysis of indicators of students with different levels of activity based on the Kruskal— Wallis H-test showed that significant differences exist for all variables: state and trait anxiety tests, emotional intelligence test, and depression and subjective well-being scales.

For a more precise interpretation of the results, pairwise differences were tested (Table 2).

Pairwise comparison analysis showed that all studied general well-being indicators differ between students with high and medium levels of activity.

The next stage of the study was a correlation analysis using Spearman’s method to identify significant correlations between general well-being indicators and activity drivers across the entire sample (Table 3).

The study revealed multiple correlations between activity drivers and general well-being indicators.

Table 1

Mean values and significance indicators of differences (Kruskal—Wallis test — H, significance of differences — p) between groups of students with different levels of activity in terms of overall well-being (N = 297) 

Note: «*» — significant differences were noted with a significance level of no more than 0.05.

Table 2

Indicators of pairwise differences (Dwass—Stiel—Krichlow—Fligner test — W its significance level — p) between groups of students with different levels of activity in terms of overall well-being (N = 297)

Table 3

Correlation coefficients between the Drivers of Activity Test scores and overall well-being scores (N = 297)

Discussion of results

Analysis of significant differences showed that all studied general well-being indicators differ among students with different levels of activity.

Thus, differences were found in state anxiety between students with high and medium levels of activity. Students with a high level had higher scores on this indicator. It can be assumed that students with high activity levels are often more involved in academic, social, and extracurricular activities, which increases their workload and the sense of responsibility they feel. Ambition and orientation toward high achievements can generate internal tension and anxiety as a reaction to significant stressful situations (exams, coursework) and expectations related to outcomes. According to a study by Gao et al., such state anxiety in students mobilizes resources and acts as an adaptive mechanism for maintaining focus and productivity (Gao et al., 2011). Anwar et al. also indicate that involvement in diverse tasks requires performing multiple roles and rapidly switching contexts, which increases environmental stress and the likelihood of anxiety reactions (Anwar et al., 2021). Furthermore, students with high activity levels may exhibit perfectionism, which creates internal requirements to avoid mistakes and meet external expectations, thereby increasing the experience of anxiety before responsible situations. In this case, a high level of state anxiety may reflect the student’s subjective attitudes toward self-regulation and control (Larigani et al., 2010). A tendency toward strict control and structuring of life reduces tolerance for uncertainty, which regularly manifests in academic settings. As a result, situations of uncertainty become stressors that cause strong state anxiety. The opposition between control and uncertainty is a fundamental factor of anxiety, especially in individuals with high self-regulation (Nahm, Chun, 2020).

Trait anxiety scores differ significantly across all three groups, with the highest scores observed in students with low activity levels. The same holds true for depression and subjective well-being. It can be noted that these results are rather contradictory, as students with the highest levels of depression also have the highest levels of subjective well-being. Such seemingly paradoxical results can be explained by the fact that subjective well-being is viewed through two components: cognitive and affective. Depressive states are characterized by a reduced positive affective tone and increased negative affect, yet the cognitive component (evaluation of one’s own life and its meanings) may remain relatively high, especially if the person rationalizes or cultivates positive aspects of their experience despite emotional difficulties (Bos et al., 2016). Moreover, compensatory cognitive strategies, such as reinterpreting the situation, focusing on social successes, meaningful goals, or supportive relationships, may contribute to maintaining subjective well-being despite symptoms of depression (Lin, 2022).

Differences in the studied indicators among students with different levels of activity can be explained by the following reasons. A low level of time, relationship, and goal management — which constitute the overall level of activity — indicates poorly developed self-regulation skills responsible for planning, behavioral control, and emotional reactions. Research shows that weak self-regulation leads to procrastination and rumination, creates chronic stress, and contributes to the formation of anxiety and depressive symptoms (Shao et al., 2020). Problems with time management cause a constant feeling of overload and falling behind, provoking state anxiety that later transforms into trait anxiety through persistent stress and decreased self-esteem (Kulsoom, Afsar, 2015). Deficits in relationship management skills may increase the risk of social isolation, conflicts, and emotional instability, which is confirmed by the strong correlation between insufficient social support and symptoms of anxiety and depression found by Shao et al. (Shao et al., 2020). The absence of stable life goals and weak goal-setting create existential uncertainty, exacerbate apathy and a sense of inner chaos, which is associated with higher levels of depressive symptoms (Lin, 2022).

Higher scores on subjective well-being in students with low activity levels may be related to the fact that such students often have lowered expectations of themselves and the world, leading to a reduction in cognitive conflicts and experiences, creating an effect of relative emotional ease and comfort — the “effect of lowered aspirations”. This approach reduces the risk of a perceived discrepancy between desired and actual states, thereby increasing satisfaction with the current situation (Mahmod et al., 2012). The lack of goal-setting and planning skills in students with low activity levels may contribute to an increase in the affective component of subjective well-being, as such students focus on positive emotions and present pleasures. They experience more positive “here and now” experiences, even if the cognitive component is low or neutral. Such a dissociation between affective and cognitive components of subjective well-being has been confirmed by psychological theories and empirical data (Lin, 2022).

The obtained results, according to which significant differences exist on all emotional intelligence scales among students with different levels of activity, indicate that activity drivers (time, goal, and relationship management) are associated with the ability to flexibly control internal emotional processes and interact effectively with others. The highest scores on all emotional intelligence scales are observed in students with high activity levels.

Effective time and goal management require developed self-regulation skills, which are closely related to emotional awareness and the ability to regulate one’s own emotions. Students who plan and control their behavior thereby train metacognitive processes and mindfulness, which contributes to increased emotional competence and more constructive management of emotional states (Palmer et al., 2001; Zee, Thijs, Schakel, 2002). Thus, the self-control necessary for allocating time resources simultaneously trains the management of emotional impulses, allowing one to maintain emotional balance and productivity in difficult situations.

Self-motivation is an integral part of goal setting and task completion. This component of emotional intelligence is activated and strengthened through self-regulation and positive emotional reinforcement. Intrinsic motivation is formed through the ability to recognize and direct emotions in a constructive direction, which is directly related to success in achieving set goals and resilience when facing difficulties (Patil et al., 2023).

Students with high relationship management skills are able to recognize others’ emotions and empathize with them, which facilitates the establishment and maintenance of social contacts. This, in turn, contributes to successful regulation of interpersonal interactions and conflict resolution. Relationship management skills based on empathy and social competencies create a favorable environment for personal growth and reduce emotional tension (Rahman et al., 2024).

The results of the correlation analysis revealed multiple correlations between general well-being indicators and activity drivers, which confirm and further emphasize the patterns found in the analysis of significant differences among students with different activity levels.

Emotional intelligence is closely interconnected with time management, goal setting, and the ability to build relationships within a team. For example, Zhang and Wang found that high emotional intelligence in employees contributes to increased effectiveness, including through the development of time management skills (employees with high emotional intelligence cope better with time constraints and are less prone to procrastination) (Zhang, Wang, 2012). The results of another study showed that high emotional intelligence in leaders promotes team cohesion and effectiveness (Zhang, Hao, 2022). Emotional intelligence also contributes to the development of conflict management skills and social adaptation (Soriano-Vazquez, Castro, Morales-Garcia, 2023).

Based on the obtained results, it can also be said that a high level of time, goal, and relationship management skills contributes to a reduction in trait anxiety and emotional depression. Effective time management provides structuring of daily activities, prioritization, and adherence to deadlines, which helps reduce feelings of chaos, overload, and uncertainty — key emotional triggers of anxiety and depressive states. Setting life goals provides meaning orientation and perspective, which is critical for preventing procrastination, apathy, and depression.

The results also show that a high level of goal and relationship management skills leads to an increase in state anxiety. Moreover, all drivers are negatively associated with subjective well-being. This may be related to increased personal responsibility and self-demands. People with highly developed self-regulation skills tend to strive for maximum task quality, which is accompanied by perfectionism and fear of failure. These factors create vulnerability to state anxiety in evaluation situations, performances, exams, or when receiving feedback. If this evaluation is negative or results do not meet expectations, the level of subjective well-being decreases (Cox, Chen, 2015). The ability to create mature and productive relationships may lead to an enhanced perception of potential social threats. Such individuals may experience affective fusion, where the emotional state of others is experienced as one’s own, which can cause state anxiety and negatively affect the affective component of subjective well-being (Russel, 2010).

Conclusion

In the course of this empirical study, it was found that activity drivers are closely related to indicators of state and trait anxiety, depression, subjective well-being, and emotional intelligence.

Analysis of significant differences in the studied indicators among students with different levels of activity showed that as the level of activity increases, emotional intelligence improves, while trait anxiety and depression decrease. However, there is a risk of increased state anxiety and reduced subjective well-being. These results indicate that focusing solely on improving competencies in goal, relationship, and time management, although positively affecting emotional intelligence, anxiety, and depression, cannot guarantee high general well-being. Excessive striving for self-control and life management can lead to perfectionism, which inevitably contributes to increased state anxiety, which in turn may reduce both the cognitive and affective components of subjective well-being.

Limitations. The limitations of this study include the small number of students with different levels of activity, as well as the lack of tools for a more comprehensive study of overall well-being. As a direction for further research, it is possible to explore other components of overall well-being in the context of activity levels.

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