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Article

Mood and Anxiety in University Students During COVID-19 Isolation: A Comparative Study Between Study-Only and Study-And-Work Groups

by
Gabriel de Souza Zanini
1,2,
Luana Marcela Ferreira Campanhã
1,
Ercízio Lucas Biazus
1,
Hugo Ferrari Cardoso
3 and
Carlos Eduardo Lopes Verardi
1,3,*
1
Department of Physical Education, School of Sciences, São Paulo State University (UNESP), Bauru 17033-360, Brazil
2
Department of Physical Education, Faculdades Integradas de Jau, Jau 17207-310, Brazil
3
Department of Psychology, School of Sciences, São Paulo State University (UNESP), Bauru 17033-360, Brazil
*
Author to whom correspondence should be addressed.
COVID 2025, 5(8), 127; https://doi.org/10.3390/covid5080127
Submission received: 30 June 2025 / Revised: 23 July 2025 / Accepted: 4 August 2025 / Published: 5 August 2025
(This article belongs to the Section COVID Public Health and Epidemiology)
Browse Figure
Versions Notes

Abstract

The COVID-19 pandemic precipitated unprecedented social isolation measures, profoundly disrupting daily life, educational routines, and mental health worldwide. University students, already susceptible to psychological distress, encountered intensified challenges under remote learning and prolonged confinement. This longitudinal study examined fluctuations in anxiety and mood among 102 Brazilian university students during the pandemic, distinguishing between those solely engaged in academic pursuits and those simultaneously balancing work and study. Data collected via the Brunel Mood Scale and State-Trait Anxiety Inventory in April and July 2021 revealed that students exclusively focused on studies exhibited significant increases in depressive symptoms, anger, confusion, and anxiety, alongside diminished vigor. Conversely, participants who combined work and study reported reduced tension, fatigue, confusion, and overall mood disturbance, coupled with heightened vigor across the same period. Notably, women demonstrated greater vulnerability to anxiety and mood fluctuations, with socioeconomic disparities particularly pronounced among females managing dual roles, who reported lower family income. These findings suggest that occupational engagement may serve as a protective factor against psychological distress during crises, underscoring the urgent need for tailored mental health interventions and institutional support to mitigate the enduring impacts of pandemic-related adversities on the student population.

1. Introduction

In late 2019, the first cases of infection with a novel coronavirus (COVID-19 or SARS-CoV-2) were reported. Within a few months, the virus had spread globally, leading to a pandemic and becoming a major public health concern [1]. Numerous measures were implemented to contain the spread of COVID-19, necessitating significant changes in societal habits and behaviors [1,2]. The primary measure adopted was social isolation, enforced through federal, state, and municipal decrees, which mandated the closure of businesses and schools while allowing only essential activities to continue to meet the population’s needs [1,3].
As a result of the pandemic and consequent social isolation, these phenomena caused economic, physiological, emotional, and behavioral challenges among individuals [1,3,4,5]. Pereira et al. (2020) [3] found that individuals subjected to prolonged periods of social isolation were more susceptible to mental health issues, such as psychological distress, increased anxiety indicators, and depression.
The education sector was significantly affected by the need for social isolation, as face-to-face activities in primary schools and higher education institutions (HEIs) were suspended. Remote education, involving synchronous and/or asynchronous activities, was widely adopted, directly impacting the teaching–learning process and influencing students and teachers across all levels due to economic, social, and emotional factors [6].
The scientific literature shows consistency in associating the impacts of stressful events and anxiety indicators with decreased academic performance and worsening mental health among students and teachers [7,8,9]. Given the social isolation measures adopted by health authorities to contain COVID-19 transmission, identifying mental health indicators becomes essential. Isolation poses risks for the development of clinical conditions such as depression [9], burnout [10], increased suicidal ideation, and even suicide [11].
The increase in psychological distress and anxiety among university students is linked to pandemic-related effects, particularly uncertainty about the future, employment, and quality of life, as well as its direct impact on interpersonal relationships [12]. In this context, Ma et al. (2020) [13] emphasized that a key factor in helping students maintain emotional control is the routine and social interactions within the campus environment.
However, Cao et al. (2020) [12] also demonstrated that students who returned to live with their parents, supported by family financial stability, experienced better anxiety management. Nevertheless, factors like concentration problems were associated with increased anxiety and worry among young people. Students reported significant difficulties studying in family environments, where they struggled to focus, alongside issues such as disrupted sleep patterns. Furthermore, the changes in students’ daily lives led to challenges in adjusting to living with their parents again or facing isolation alone [14].
Additionally, a study by Tsurugano et al. (2021) [15] found that working students were more vulnerable to job loss due to the COVID-19 pandemic. Financial insecurity negatively affected their academic performance and increased susceptibility to illnesses. University students who needed to support themselves often lived in precarious conditions, with limited leisure opportunities and low purchasing power. Another factor that influenced students’ behavioral processes was the transition from in-person classes to remote learning. This shift required both students and teachers to adapt to the new reality of education, often encountering technical issues such as poor Internet connectivity and challenges in providing learning materials [16].
Given that many university students had to work during the social isolation period—sometimes at hours overlapping with their academic schedules—it is speculated that those balancing work and studies during this uncertain time experienced greater mental health challenges. These challenges were particularly associated with financial pressures, as many students began working to supplement family income, often due to unemployment among parents or guardians. This study aimed to identify and compare anxiety levels and mood variations among university students engaged in work and study versus those focused solely on their studies during the social isolation period caused by the COVID-19 pandemic.

2. Materials and Methods

2.1. Participants

The sample consisted of 102 students, both male and female, with a mean age of 20.32 ± 9.51 years. Participants were enrolled in biological and health sciences courses (n = 67), humanities (n = 22), and engineering and exact sciences (n = 13) (Table 1). All participants were university students from Bauru, São Paulo, Brazil, and, during the study period, the institution offered remote psychological support by appointment. However, there was no systematic record of the number of participants who used this service. This possibility should be considered as a potential modulating factor in emotional responses. This longitudinal and observational study aimed to examine the evolution of mood variation and anxiety indicators among students subjected to social isolation due to the COVID-19 pandemic.

2.2. Procedures

Data collection occurred in two distinct moments: April 2021 and July 2021. Both rounds of data collection were conducted remotely via an online platform. Students were invited to participate via institutional email and completed the data collection instruments voluntarily. All participants provided informed consent, ensuring anonymity and data confidentiality. This study was approved by the Research Ethics Committee under protocol number CAAE: 50496021.4.0000.5398.

2.3. Instruments

2.3.1. Sociodemographic Questionnaire

This questionnaire, developed by the authors, collected data such as age, marital status, gender, average income, and academic program. Based on these responses, students were classified into two groups: fully isolated and partially isolated (due to work-related obligations).

2.3.2. Brunel Mood Scale (BRUMS)

The Brunel Mood Scale [17], adapted from the Profile of Mood States (POMS) by McNair et al. (1971) [18] and validated for use in Portuguese by Rohlfs et al. (2008) [19], was used to measure mood states in adults and adolescents. The scale has demonstrated high internal consistency (Cronbach’s alpha > 0.70 for all constructs). BRUMS includes 24 items measuring simple mood indicators such as anger, vigor, nervousness, and dissatisfaction. Respondents rate their current mood on a 5-point Likert scale (0 = not at all; 4 = extremely). Scores for each mood state range from 0 to 16. Six mood states are assessed: Tension (T), Depression (D), Anger (A), Vigor (V), Fatigue (F), and Confusion (C). T, D, A, F, and C are considered negative factors, while V is positive. The Total Mood Disturbance (TMD) score is calculated as follows: TMD = (T + D + A + F + C) − V + 100 [20]. A mood profile with high Vigor and low scores for the other variables is termed the "Iceberg Profile," indicative of positive mental health (Morgan et al., 1987) [20].

2.3.3. State-Trait Anxiety Inventory (STAI)

The STAI [21] is a self-assessment questionnaire divided into two parts: one measuring trait anxiety (personality aspects) and the other measuring state anxiety (contextual aspects). Each part consists of 20 items rated on a 4-point Likert scale (1 to 4). The state anxiety component reflects how the individual feels "at the moment," while the trait component reflects how they "generally feel." Scores range from 20 to 80, with lower scores indicating lower anxiety levels. Anxiety levels are classified as low (0–30), moderate (31–49), or high (≥50). In this study, only the State Anxiety subscale, consisting of 20 items, was used, as it is considered more appropriate for assessing emotional responses associated with the pandemic context. Internal consistency was excellent, with Cronbach’s alpha = 0.91.

2.3.4. Statistical Analysis

Statistical analyses were performed using SPSS 26.0 for Windows (SPSS Inc., Chicago, IL, USA). The Shapiro–Wilk test was used to assess normality, and Levene’s test was applied to test homoscedasticity. Variables are presented as mean ± standard deviation and median. A two-way repeated-measures ANOVA was applied to evaluate intragroup and intergroup differences in parametric data, with Bonferroni post hoc tests used to identify significant differences. For non-parametric data, the Kruskal–Wallis test was employed, with Dunn’s post hoc test applied to pinpoint significant results. Statistical significance was set at p < 0.05.

3. Results

This study analyzed 102 higher education students subjected to social isolation during the COVID-19 pandemic in 2021. The sociodemographic characteristics of the participants are listed in Table 1, where differences between the groups were identified.
The data suggest a difference in the number of students and individuals engaged in dual roles (working and studying), with the female group being predominant in both situations. This phenomenon may be explained by the smaller male population in the sample. Furthermore, the data revealed a significant difference (p = 0.043) in the average family income among female students. Those who worked and studied during the research period reported a lower average family income compared to the group composed of female students who only studied during the same period. Considering only the group of students who exclusively studied during the research period, a significant difference (p = 0.031) was also observed in the gender variable.
In Table 2, data related to the analyzed variables are presented, with groups separated for the analysis model. In the BRUMS instrument, the ANOVA identified significant intragroup differences in the factors Tension (F2, 94 = 1.44, p= 0.05, η2 = 0.220, power = 0.560), Depression (F2, 94 = 2.369, p = 0.041, η2 = 0.163, power = 0.641), and Anger (F2, 94 = 0.655, p = 0.002, η2 = 0.113, power = 0.829), all showing increased scores in the second data collection. Regarding the Vigor factor (p = 0.041), the mean responses decreased compared to the first application. In the IDATE instrument, State factor, a significant increase (F1, 87 = 1.03, p = 0.047, η2 = 0.313, power = 0.443) in mean responses was observed from the first to the second data collection.
In the group composed of students who only studied during the researched period, the BRUMS instrument revealed increased mean responses in the factors Depression (d = 0.55; p = 0.051), Anger (d = 0.10; p = 0.043), and Confusion (d = 0.39; p = 0.042), alongside a decrease in the mean responses for the Fatigue factor (d = 0.14; p = 0.039). In the IDATE State, an increase in the mean responses between data collection periods was also observed (d = 0.26; p = 0.038).
Conversely, in the group of students who worked and studied during the research period, the BRUMS instrument showed a decrease in mean responses between data collection periods in the factors Tension (d = 0.28; p = 0.043), Fatigue (d = 0.54; p = 0.021), Confusion (d = 0.37; p = 0.036), and in the total scale—TMD (d = 0.21; p = 0.001)—as well as an increase in the mean responses for the Vigor factor (d = 0.25; p = 0.048).
When comparing the means of participants between groups, the Bonferroni test demonstrated differences in the factors Tension (p = 0.002), Depression (p = 0.001), Anger (p = 0.001), Vigor (p = 0.002), Fatigue (p = 0.001), Confusion (p = 0.01), and TMD (p = 0.002) of the BRUMS instrument.
Additionally, in Figure 1, it is possible to observe that mood profile curves were altered from the first moment, with reduced Vigor and a slight increase in negative variables. However, later, the mood curve showed an even greater reduction in the Vigor factor due to the increase in negative variables, mainly anger, depressive symptoms, and tension.

4. Discussion

The present study aimed to investigate mood fluctuations and anxiety levels among university students subjected to social isolation during the COVID-19 pandemic. Participants were divided into two groups: those solely engaged in academic studies and those simultaneously balancing work and study between April and July 2021. Analysis revealed notable differences between these groups. Women comprised the majority in both. A significant disparity in average family income was also found, both between the two groups and between male and female participants.
The COVID-19 pandemic severely disrupted healthcare systems and global economies, leading to ongoing supply chain issues and labor shortages that affected access to goods and services [22,23]; this economic instability, combined with reduced purchasing power and restrictive measures, has had direct implications for mental health. To contain the virus, governments worldwide imposed social distancing policies, which contributed to increased loneliness, depression, anxiety, and post-traumatic stress symptoms. These restrictions forced many individuals, particularly those outside essential services, to transition to remote work and education—altering both the quality of instruction and workplace dynamics [23,24].
Amid these challenges, our initial hypothesis proposed that individuals balancing work and study would exhibit more pronounced anxiety and mood changes due to heightened social pressures and reduced leisure time. Contrary to expectations, findings revealed that students who only studied reported higher levels of anxiety and mood disturbances than their peers who also worked. These results are consistent with prior research indicating that university students experience elevated anxiety and depression compared to the general workforce [25,26]. Although women are typically more susceptible to depressive symptoms, female workers demonstrated lower levels of anxiety and depression than female students [27].
Moreover, gender-based differences in psychological distress during crises must be considered. Working women often exhibit higher rates of depression and psychological distress, partly due to the cumulative burden of multiple roles and the conflict between work and family responsibilities [28,29,30,31]. In contrast, men—though less frequently diagnosed with affective disorders—exhibit higher suicide rates, frequently associated with stigma, reluctance to seek help, and adverse labor conditions [28,29,31]. While occupational stressors affect both sexes, the manifestations of psychological suffering tend to differ. During crises such as the COVID-19 pandemic, both genders reported increased psychological distress, yet the predominant stressors varied; men more often cited work-related and financial insecurities, whereas women were more likely to report increased domestic demands, rising living costs, and restrictions on social interaction [32].
Nonetheless, students exclusively immersed in academic settings might have experienced limited social interaction and a reduced sense of belonging. Conversely, those engaged in both work and study environments benefited from broader social networks and a stronger sense of purpose. This sense of belonging—integral to psychological well-being—enhances self-worth and social contribution [33,34]. As Cruz [35] noted, human beings are inherently social and rely on meaningful interpersonal relationships for development and autonomy.
Moreover, individuals whose jobs remained in-person or resumed early likely benefited from occupational and social support, both protective factors for mental health [36]. In contrast, unemployment has been consistently linked to increased depressive symptoms. A longitudinal study by Lee et al. [37] demonstrated that each additional year of unemployment significantly increased the risk of depression, especially under conditions of prolonged isolation.
Our findings suggest that social isolation had a disproportionate impact on students, placing them at a greater risk for anxiety and mood disorders compared to those who balanced academic and work responsibilities. This aligns with broader research, including a multicenter Brazilian study that found high rates of anxiety (62.8%) and depression (49.3%) among university students more than a year after the peak of pandemic restrictions [38]. Female gender and lower socioeconomic status emerged as significant predictors of poorer mental health outcomes, corroborating our observation that female students, particularly those not working, exhibited greater vulnerability [30,39,40].
Similarly, studies among European university students have shown that employment during academic studies serves as a protective factor against anxiety and depression [25,41]; the authors posited that occupational involvement promotes psychological resilience by fostering structured routines, financial stability, and social interaction—factors that may explain the more favorable mental health outcomes among our dual-role participants.
Additional evidence suggests that strong familial and peer support mitigates psychological distress, even in adverse conditions. For example, a study among Indian university students found that family and friend support positively correlated with well-being, with academic engagement mediating this relationship—highlighting the role of social support in fostering resilience [42]. During the pandemic, many students faced uncertainty about their academic future and employment prospects, alongside fears of virus exposure and social disconnection, all contributing to heightened psychological strain. Mood disturbances, particularly depression, have been associated with poor academic performance [43,44].
According to Levine [45], loneliness induced by social exclusion undermines psychological health by diminishing one’s sense of purpose, self-esteem, and social value. Individuals who resumed work reported feeling socially useful—an experience not mirrored among isolated students. These findings reaffirm that social isolation among university students heightened their risk for psychological disorders relative to their dual-role peers.
Collectively, this body of evidence underscores the multifactorial nature of psychological distress in student populations. It highlights that mental health outcomes during the pandemic were influenced not only by economic hardship but also by digital fatigue, social disconnection, and the erosion of structured routines. These insights call for comprehensive interventions that go beyond financial aid, encompassing digital well-being, meaningful social engagement, and resilience-building strategies. Such measures are essential to guiding institutional policies that support mental health and long-term adaptation in academic environments.
While this study provides valuable insights into the mental health effects of pandemic-related isolation, it is not without limitations. The sample had a gender imbalance, with women representing 66% of participants—a factor that may have influenced anxiety and mood scores, given the established vulnerability of women to affective disorders [30,40]. Moreover, the sample size did not meet recommended thresholds for certain psychometric analyses, limiting the generalizability of the findings. The findings of this study should be interpreted with caution regarding their generalizability, as they reflect the reality of a single Brazilian city. Different socioeconomic and cultural contexts may produce variations in the psychological effects of the pandemic on university students. The use of self-reported data also introduces potential bias, and this study’s timeframe might not have fully captured the long-term mental health impacts of the pandemic. Additionally, the absence of data from broader demographic and occupational groups restricts the applicability of the results, and the presence of employment was used as a proxy for structured daily routine and potential social interaction, but actual levels of social support were not directly measured in this study.
Despite these limitations, the findings emphasize the acute mental health challenges faced by university students during the COVID-19 pandemic—especially those in isolation. Conversely, individuals balancing study and work demonstrated psychological resilience, suggesting that occupational engagement and broader social interactions may serve as buffers against anxiety and mood disturbances. These conclusions carry practical relevance for educational institutions and policymakers. Promoting environments that support a sense of belonging, offering accessible mental health resources, and integrating structured opportunities for social and professional engagement may mitigate the psychological impacts of isolation during future crises. Finally, this study provides a relevant contribution in highlighting the importance of job-related social support, but this should be more clearly discussed.

5. Conclusions

The data suggest that groups consisting only of students are more susceptible to changes in their behavioral patterns, such as increased anxiety and mood fluctuations, when compared to individuals who experience dual work-study schedules. It is speculated that this phenomenon is associated with a greater sense of belonging and increased social integration due to the work environment, offering a broader social interaction zone. Additionally, it was observed that the female population exhibited greater vulnerability to the development of anxiety disorders and mood fluctuations compared to men in similar situations. Finally, future studies should aim to explore this phenomenon across distinct populations, including those outside the university context. Moreover, with the ongoing increase in vaccination rates, research should focus on understanding the impact of the return to regular activities.

Author Contributions

Conceptualization, G.d.S.Z. and C.E.L.V.; methodology, G.d.S.Z. and C.E.L.V.; software, G.d.S.Z.; validation, C.E.L.V. and H.F.C.; data curation, G.d.S.Z. and C.E.L.V.; writing—original draft preparation, G.d.S.Z. and C.E.L.V.; writing—review and editing, G.d.S.Z., L.M.F.C. and E.L.B.; visualization, H.F.C.; supervision, C.E.L.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee under protocol number CAAE: 50496021.4.0000.5398, 2 September 2021.

Informed Consent Statement

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

Data Availability Statement

Data supporting this study’s findings are available from the corresponding author upon reasonable request.

Conflicts of Interest

All authors approved the final manuscript and consent to its publication.

References

  1. Farias, H.S.d. O avanço da COVID-19 e o isolamento social como estratégia para redução da vulnerabilidade. Espaço E Econ. Rev. Bras. Geogr. Econ. 2020, 17, 2317–7837. [Google Scholar] [CrossRef]
  2. Baker, M.G.; Kvalsvig, A.; Verrall, A.J.; Wellington, N. New Zealand’s COVID-19 elimination strategy. Med. J. Aust. 2020, 213, 198–200. [Google Scholar] [CrossRef]
  3. Pereira, M.D.; de Oliveira, L.C.; Costa, C.F.T.; de Oliveira Bezerra, C.M.; Pereira, M.D.; dos Santos, C.K.A.; Dantas, E.H.M. A pandemia de COVID-19, o isolamento social, consequências na saúde mental e estratégias de enfrentamento: Uma revisão integrativa. Res. Soc. Dev. 2020, 9, e652974548. [Google Scholar] [CrossRef]
  4. Florêncio Júnior, P.G.; Paiano, R.; Costa, A.D.S. Isolamento social: Consequências físicas e mentais da inatividade física em crianças e adolescentes, (SE-Ensaios Teóricos em Atividade Física e Saúde). Rev. Bras. Atividade Física Saúde 2020, 25, 1–2. [Google Scholar] [CrossRef]
  5. Costa, D.S.d.; Medeiros, N.d.S.B.; Cordeiro, R.A.; Frutuoso, E.d.S.; Lopes, J.M.; Moreira, S.d.N.T. Sintomas de depressão, ansiedade e estresse em estudantes de Medicina e estratégias institucionais de enfrentamento. Rev. Bras. Educ. Méd 2020, 44, e040. [Google Scholar] [CrossRef]
  6. Vieira, K.M.; Postiglioni, G.F.; Donaduzzi, G.; dos Santos Porto, C.; Klein, L.L. Vida de estudante durante a pandemia: Isolamento social, ensino remoto e satisfação com a vida. EaD Foco 2020, 10, e1147. [Google Scholar] [CrossRef]
  7. Aragão, J.A.; dos Santos, I.F.; Pimentel, J.V.A.; Nunes, M.S.F.; Cruz, M.L.A.; Reis, F.P. Ansiedade, depressão e outros transtornos mentais no estudante de medicina durante a pandemia da COVID-19. In Saúde em Foco: Doenças Emergentes e Reemergentes; 2021; Volume 2, Editora Cientifica: Guaruja, Brazil; pp. 15–30. [Google Scholar]
  8. da Silva, T.V.S.; Vieira, L.M.; Cardoso, A.M.R.; de Oliveira, R.V.D. Qualidade, d.vida, ansiedade e depressão em estudantes de Odontologia na pandemia da COVID-19 e fatores relacionados. Res. Soc. Dev. 2021, 10, e34710817481. [Google Scholar] [CrossRef]
  9. Maia, B.R.; Dias, P.C. Ansiedade, depressão e estresse em estudantes universitários: O impacto da COVID-19. Estud. Psicol. 2020, 37, e200067. [Google Scholar] [CrossRef]
  10. Bonome-Vanzelli, S.R.C.; Verardi, C.E.L. A Saúde Física e Mental de Professores de Educação Física: Aptidão Física, Burnout e Estados de Humor; Editora Cientifica Digital: Sao Paulo, Brazil, 2019. [Google Scholar] [CrossRef]
  11. Sher, L. The impact of the COVID-19 pandemic on suicide rates. QJM An. Int. J. Med. 2020, 113, 707–712. [Google Scholar] [CrossRef]
  12. Cao, W.; Fang, Z.; Hou, G.; Han, M.; Xu, X.; Dong, J.; Zheng, J. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020, 287, 112934. [Google Scholar] [CrossRef]
  13. Ma, Z.; Zhao, J.; Li, Y.; Chen, D.; Wang, T.; Zhang, Z.; Chen, Z.; Yu, Q.; Jiang, J.; Fan, F. Mental health problems and correlates among 746217 college students during the coronavirus disease 2019 outbreak in China. Epidemiol. Psychiatr. Sci. 2020, 29, e181. [Google Scholar] [CrossRef] [PubMed]
  14. Wang, C.; Zhao, H. The impact of COVID-19 on anxiety in Chinese university students. Front. Psychol. 2020, 11, 1168. [Google Scholar] [CrossRef] [PubMed]
  15. Tsurugano, S.; Nishikitani, M.; Inoue, M.; Yano, E. Impact of the COVID-19 pandemic on working students: Results from the Labour Force Survey and the student lifestyle survey. J. Occup. Health 2021, 63, e12209. [Google Scholar] [CrossRef]
  16. Sahu, P. Closure of universities due to coronavirus disease 2019 (COVID-19): Impact on education and mental health of students and academic staff. Cureus 2020, 12, e7541. [Google Scholar] [CrossRef]
  17. Terry, P.C.; Lane, A.M.; Fogarty, G.J. Construct validity of the Profile of Mood States—Adolescents for use with adults. Psychol. Sport. Exerc. 2003, 4, 125–139. [Google Scholar] [CrossRef]
  18. McNair, D.; Lorr, M.; Droppleman, L. Manual for the Profile of Mood States; Educational and Industrial Testing Service: San Diego, CA, USA, 1971. [Google Scholar]
  19. Rohlfs, I.C.P.D.M.; Rotta, T.M.; Luft, C.D.B.; Andrade, A.; Krebs, R.J.; Carvalho, T.d. A Escala de Humor de Brunel (Brums): Instrumento para detecção precoce da síndrome do excesso de treinamento. Rev. Bras. Med. Esporte 2008, 14, 176–181. [Google Scholar] [CrossRef]
  20. Morgan, W.P.; Brown, D.R.; Raglin, J.S.; O’connor, P.J.; Ellickson, K.A. Psychological monitoring of overtraining and staleness. Br. J. Sports Med. 1987, 21, 107–114. [Google Scholar] [CrossRef]
  21. Biaggio, A.M.B.; Natalício, L. Manual para o inventário de ansiedade Traço-Estado (IDATE). Rio Jan. CEPA 1979, 15. [Google Scholar]
  22. Usman, M.; Ali, Y.; Riaz, A.; Riaz, A.; Zubair, A. Economic perspective of coronavirus (COVID-19). J. Public Aff. 2020, 20, e2252. [Google Scholar] [CrossRef]
  23. Barrutia Barreto, I.; Silva Marchan, H.A.; Sánchez Sánchez, R.M. Consecuencias económicas y sociales de la inamovilidad humana bajo COVID-19: Caso de estudio Perú. Lect. Econ. 2021, 94, 285–303. [Google Scholar] [CrossRef]
  24. Xu, Z.; Elomri, A.; Kerbache, L.; El Omri, A. Impacts of COVID-19 on global supply chains: Facts and perspectives. IEEE Eng. Manag. Rev. 2020, 48, 153–166. [Google Scholar] [CrossRef]
  25. Romeo, A.; Benfante, A.; Castelli, L.; Di Tella, M. Psychological distress among Italian university students compared to general workers during the COVID-19 pandemic. Int. J. Environ. Res. Public Health 2021, 18, 2503. [Google Scholar] [CrossRef]
  26. Odriozola-González, P.; Planchuelo-Gómez, Á.; Irurtia, M.J.; de Luis-García, R. Psychological effects of the COVID-19 outbreak and lockdown among students and workers of a Spanish university. Psychiatry Res. 2020, 290, 113108. [Google Scholar] [CrossRef] [PubMed]
  27. Arcand, M.; Juster, R.P.; Lupien, S.J.; Marin, M.F. Gender roles in relation to symptoms of anxiety and depression among students and workers. Anxiety Stress. Coping 2020, 33, 661–674. [Google Scholar] [CrossRef] [PubMed]
  28. Halonen, J.I.; Koskinen, A.; Varje, P.; Kouvonen, A.; Hakanen, J.J.; Väänänen, A. Mental health by gender-specific occupational groups: Profiles, risks and dominance of predictors. J. Affect. Disord. 2018, 238, 311–316. [Google Scholar] [CrossRef] [PubMed]
  29. Sussell, A.L.; Yeoman, K.; Nixon, C.T.; Scott, K.A.; Robinson, T.S.; Poplin, G.S. US Workers’ Self-Reported Mental Health Outcomes by Industry and Occupation. JAMA Netw. Open 2025, 8, e2514212. [Google Scholar] [CrossRef]
  30. Sachs, B.D.; Ni, J.R.; Caron, M.G. Sex differences in response to chronic mild stress and congenital serotonin deficiency. Psychoneuroendocrinology 2014, 40, 123–129. [Google Scholar] [CrossRef]
  31. Liu, S.; Yang, L.; Zhang, C.; Xu, Y.; Cai, L.; Ma, S.; Wang, Y.; Cai, Z.; Li, R.; Du, H. Gender differences in mental health problems of healthcare workers during the coronavirus disease 2019 outbreak. J. Psychiatr. Res. 2021, 137, 393–400. [Google Scholar] [CrossRef]
  32. Kobayashi, T.; Maeda, M.; Takebayashi, Y.; Sato, H. Traditional gender differences create gaps in the effect of COVID-19 on psychological distress of Japanese workers. Int. J. Environ. Res. Public. Health 2021, 18, 8656. [Google Scholar] [CrossRef]
  33. dos Santos, D.G.G.; Guimarães, M. Pertencimento: Um elo conectivo entre o ser humano, a sociedade e a natureza. REMEA-Rev. Eletrônica Mestr. Educ. Ambient. 2020, 37, 208–223. [Google Scholar] [CrossRef]
  34. Gudolle, L.S.; Antonello, C.S.; Flach, L. Aprendizagem situada, participação e legitimidade nas práticas de trabalho. RAM Rev. Adm. Mackenzie 2012, 13, 14–39. [Google Scholar] [CrossRef]
  35. Cruz, M.M.S.; Freire, P. Pedagogia Da Autonomia: Saberes Necessários À Pratica Educativa. Coleção leitura; Paz e Terra: São Paulo, Brazil, 1996; 166p. [Google Scholar]
  36. Górny, M. The importance of work in human life and development. The consequences of unemployment. Adam Mickiewicz Univ. Poznań 2018, 18, 51–64. [Google Scholar] [CrossRef]
  37. Lee, J.O.; Jones, T.M.; Yoon, Y.; Hackman, D.A.; Yoo, J.P.; Kosterman, R. Young adult unemployment and later depression and anxiety: Does childhood neighborhood matter? J. Youth Adolesc. 2019, 48, 30–42. [Google Scholar] [CrossRef] [PubMed]
  38. Barbosa, B.C.R.; Paula, W.; de Ferreira, A.D.; Freitas, E.D.d.; Chagas, C.M.d.S.; Oliveira, H.N.d.; Ferreira, L.G.; Silva, L.S.d.; Vidigal, F.d.C.; Nobre, L.N.; et al. Anxiety and depression symptoms in university students from public institutions of higher education in Brazil during the COVID-19 pandemic: A multicenter study. SciELO Preprints, 2023. [Google Scholar] [CrossRef]
  39. Hou, F.; Bi, F.; Jiao, R.; Luo, D.; Song, K. Gender differences of depression and anxiety among social media users during the COVID-19 outbreak in China: A cross-sectional study. BMC Public Health 2020, 20, 1648. [Google Scholar] [CrossRef] [PubMed]
  40. Vaccarino, V.; Bremner, J.D. Behavioral, emotional and neurobiological determinants of coronary heart disease risk in women. Neurosci. Biobehav. Rev. 2017, 74, 297–309. [Google Scholar] [CrossRef]
  41. Ahmed, N.; Barnett, P.; Greenburgh, A.; Pemovska, T.; Stefanidou, T.; Lyons, N.; Ikhtabi, S.; Talwar, S.; Francis, E.R.; Harris, S.M.; et al. Mental health in Europe during the COVID-19 pandemic: A systematic review. Lancet Psychiatry 2023, 10, 537–556. [Google Scholar] [CrossRef]
  42. Chaudhry, S.; Tandon, A.; Shinde, S.; Bhattacharya, A. Student psychological well-being in higher education: The role of internal team environment, institutional, friends and family support and academic engagement. PLoS ONE 2024, 19, e0297508. [Google Scholar] [CrossRef]
  43. Campanhã, L.M.F.; da Silva, M.L.M.P.; Junior, A.T.; Claro, R.F.T.; de Souza Zanini, G. Educação física escolar e os efeitos nas variações de humor dos estudantes–uma revisão narrativa. Rev. CPAQV–Cent. Pesqui. Avançadas Qual. Vida 2021, 13, 2–8. [Google Scholar] [CrossRef]
  44. Hysenbegasi, A.; Hass, S.L.; Rowland, C.R. The impact of depression on the academic productivity of university students. J. Ment. Health Policy Econ. 2005, 8, 145. [Google Scholar]
  45. Levine, M.P. Loneliness and eating disorders. J. Psychol. 2012, 146, 243–257. [Google Scholar] [CrossRef]
Covid 05 00127 g001
Figure 1. Iceberg profile about the groups. SB: study before. SA: study after. WSB: work and study before. WSA: work and study after.
Figure 1. Iceberg profile about the groups. SB: study before. SA: study after. WSB: work and study before. WSA: work and study after.
Covid 05 00127 g001
Table 1. Demographics and characteristics of the participants.
Table 1. Demographics and characteristics of the participants.
VariablesMaleFemaleTotal
N35 (34%)67 (66%)102 *
Age (y)24.03 ± 0.9719.24 ± 3.2520.32 ±9.51
Work/Study17 (38%)28 (62%)45 (44%)
Study18 (32%)39 (68%)57 (56%) *
Family Income (BRL)Work/StudyStudy
Male 3781 ± 512.014051 ± 871.124121.27 ± 354.17
Female3341.35 ± 324.995102.26 ± 267.354687.12 ± 126.94 * †
BRL: currency in Brazil, Real; BRL 1.00 is equivalent to USD 0.20. * Denotes significant difference between the groups [(male/female) p < 0.05]. † denotes a significant difference between the same group (p < 0.05).
Table 2. BRUMS and Anxiety State scores before and after the 3-month period.
Table 2. BRUMS and Anxiety State scores before and after the 3-month period.
VariablesTensionDepressionAngerVigorFadigueConfusionTMDAnxiety State
Mean
Before9.17 ± 0.898 ± 2.167.76 ± 2.955.98 ± 2.1510.84 ± 1.028.96 ± 0.35138.76 ± 15.0146.29 ± 2.31
After10.21 ± 2.319.31 ± 5.110.32 ± 4.124.15 ± 3.0110.12 ± 0.919.15 ± 0.7142.65 ± 17.651.35 ± 2.66
p0.051 *0.048 *0.002 *0.041 *0.910.0750.0670.047 *
Study Group
Before9.49 ± 0.978.63 ± 0.847.82 ± 0.795.85 ± 0.5411.21 ± 0.989.47 ± 0.89140.77 ± 13.9146.47 ± 4.93
After9.11 ± 1.329.65 ± 0.978.87 ± 1.656.19 ± 0.3310.35 ± 1.3510.91 ± 1.64142.34 ± 10.9152.31 ± 0.66
p0.0690.051 *0.043 *0.0610.039 *0.042 *0.0670.038 *
Work and Study Group
Before8.73 ± 3.797.14 ± 1.447.69 ± 3.926.16 ± 4.0310.35 ± 3.028.28 ± 2.99136.04 ± 13.0146.06 ± 1.15
After7.81 ± 0.488.01 ± 3.417.55 ± 1.517.97 ± 0.798.79 ± 1.556.55 ± 0.89120.56 ± 15.3346.59 ± 0.71
p0.043 *‡0.061 ‡0.341 ‡0.048 *‡0.021 *‡0.036 *‡0.001 *‡0.713
TMD: total mood disorder; * denotes significant difference between the before and after. ‡ Denotes a significant difference between the study and work/study group.
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MDPI and ACS Style

Zanini, G.d.S.; Campanhã, L.M.F.; Biazus, E.L.; Cardoso, H.F.; Verardi, C.E.L. Mood and Anxiety in University Students During COVID-19 Isolation: A Comparative Study Between Study-Only and Study-And-Work Groups. COVID 2025, 5, 127. https://doi.org/10.3390/covid5080127

AMA Style

Zanini GdS, Campanhã LMF, Biazus EL, Cardoso HF, Verardi CEL. Mood and Anxiety in University Students During COVID-19 Isolation: A Comparative Study Between Study-Only and Study-And-Work Groups. COVID. 2025; 5(8):127. https://doi.org/10.3390/covid5080127

Chicago/Turabian Style

Zanini, Gabriel de Souza, Luana Marcela Ferreira Campanhã, Ercízio Lucas Biazus, Hugo Ferrari Cardoso, and Carlos Eduardo Lopes Verardi. 2025. "Mood and Anxiety in University Students During COVID-19 Isolation: A Comparative Study Between Study-Only and Study-And-Work Groups" COVID 5, no. 8: 127. https://doi.org/10.3390/covid5080127

APA Style

Zanini, G. d. S., Campanhã, L. M. F., Biazus, E. L., Cardoso, H. F., & Verardi, C. E. L. (2025). Mood and Anxiety in University Students During COVID-19 Isolation: A Comparative Study Between Study-Only and Study-And-Work Groups. COVID, 5(8), 127. https://doi.org/10.3390/covid5080127

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