Abstract
Background
The July-August 2024 student protest in Bangladesh was associated with a rise in misinformation and disinformation, threatening the mental well-being of students. This study investigated the association of student activism, exposure to misinformation and disinformation with mental health outcomes among the university students of Bangladesh during the July-August 2024 student protest.
Methods
The cross-sectional online survey was conducted from September to October 2024, among Bangladeshi university students aged 18–30 using a non-probability convenience sampling strategy (N = 565). A self-administered Google Form was distributed via online platforms. Anxiety and depression were assessed using standardized GAD-7 and PHQ-9 tools. Univariate, bivariate, and multivariate analyses were conducted in Stata version 14.2.
Results
Participants were evenly distributed across age groups (18–30 years), with most coming from rural areas (68.5%). Among them, 38.05% participated in the protests occasionally, while 29.56% did so frequently, mostly motivated by personal beliefs (92.39%). Over one-third of respondents (38.05%) encountered misinformation, yet 85.39% felt moderately confident in recognizing it. The main contributor to this misinformation was self-belief bias (50.97%). The majority of the students reported severe anxiety and depression. Female participants had 1.67 times higher odds of elevated depression compared to males (95% CI: 1.22 to 2.29, p < 0.001). Distress related to the activism was highly associated with the outcomes (p < 0.001).
Conclusion
The findings highlight the psychological vulnerability of university students and its significant connection to activism and exposure to misinformation and disinformation. It is essential to provide targeted mental health support and media information literacy, particularly for protesting students as their anxiety and depression may be prolonged affecting their quality of life.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s40359-026-05131-y.
Keywords: Student Activism, Misinformation, Disinformation, Depression, Anxiety, Mental Health, Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9)
Introduction
Student activism involves the active participation of students in political and social causes, often driving major societal changes. Historically, such activism has shaped political landscapes worldwide with youth idealism, dedication, and nationalism making them powerful drivers of policy change [1, 2]. Universities, as vital centers of intellectual and political consciousness, play a significant role in shaping societal dynamics within these contexts [3]. Throughout history, students in Bangladesh have been pivotal in major political and social movements, starting with the Language Movement of 1952 and continuing through the Liberation War of 1971. In July 2024, an anti-quota demonstration escalated into a widespread uprising known as the July-August 2024 student protest, which included demands for policy reform and broader political change [4, 5]. The protests reached a peak in late July and culminated in the fall of the government on August 5, 2024 [6].
During this period, social media played a significant role in organizing protests and disseminating information. However, when activism unfolds simultaneously across online media platforms, it becomes vulnerable to misinformation and disinformation, complicating narratives and influencing people’s engagement [7, 8]. While activism can foster empowerment and a sense of purpose [9], the spread of misleading content can amplify its psychological burden. Misinformation is often unintentional, while disinformation is deliberate primarily through social media and interpersonal communication both shaping individuals’ understanding of events and their psychological and well-being [10, 11]. Evidence suggests that university students are particularly vulnerable to the mental health consequences of misinformation exposure [8, 12, 13]. This vulnerability is further compounded when students simultaneously navigate the psychological demands of activism [14, 15]. Notably, the psychological toll on student protestors in Bangladesh during the July-August 2024 student protest was immense [4, 16]. Many faced anxiety, depression, trauma, post-traumatic stress disorder (PTSD), and grief, not only from direct exposure to violence but also from the confusion and stress fueled by digital disinformation [4].
Despite growing interest in the mental health consequences of socio-political engagement through activism, there is a lack of comprehensive research on the combined associations of such activism and simultaneous digital misinformation and disinformation on young adults in politically volatile and resource-constrained low- and middle-income countries (LMIC) like Bangladesh [15].
This study integrates four complementary theoretical frameworks to explain the mechanisms through which student activism and misinformation/ disinformation exposure contribute to anxiety and depression. The Stress Process Model (SPM) [17] provides the overarching structure, treating high-intensity activism and prolonged misinformation exposure during the July-August 2024 student protest as cumulative stressors that produce psychological distress. Cognitive Load Theory (CLT) [18] describes how exposure to contradictory and false information during political crises overloads working memory, impairing emotional regulation and leading to rumination, overestimating threats, and feelings of helplessness. The activism pathway exposes students to stressors like personal harm and violence, which can cause moral injury and emotional exhaustion, overwhelming their coping resources and contributing to depressive symptoms [14]. The Transactional Stress Theory (TST) [19] explains why students exposed to the same stressors can experience different levels of distress. Students who experienced harm or viewed their activism as highly threatening, while also perceiving limited social support, gender-related constraints, or low media literacy, were expected to report increased anxiety and depression. TST therefore bridges the SPM and CLT by explaining individual differences across both pathways. The WHO Infodemic Framework [20] contextualizes both pathways within a shared information environment in which misinformation spreads at scale, generating differential psychological burden depending on individual cognitive resources and social support. Together, these frameworks propose that activism and misinformation and disinformation exposure operate through partially independent but mutually reinforcing pathways to mental health outcomes, with individual and social resources moderating the severity of impact.
The theoretical framework guiding this study is presented in Fig. 1. The four complementary frameworks are integrated to explain the mechanisms through which student activism and misinformation exposure contribute to anxiety and depression.
Fig. 1.
The figure presents a conceptual model illustrating how student activism and misinformation exposure contribute to psychological distress, anxiety, and depression. The Stress Process Model17 identifies the primary stressors, including activism-related harm, threats, and continuous misinformation exposure. Cognitive Load Theory18 specifies the cognitive mechanism whereby conflicting, high-volume information increases cognitive load and impairs emotional regulation. The Transactional Stress Theory19 explains how appraisal of threat and insufficient coping resources amplify distress. The WHO Infodemic Framework20 characterizes the broader information environment of social media, peer networks, and institutional mistrust that generates misinformation at scale. Dashed borders indicate contextual conditions that amplify primary pathways. Gender, social support, and media literacy are hypothesized to indirectly moderate the outcomes
To our knowledge, this is the first study to simultaneously examine the combined psychological burden of activism participation and misinformation/disinformation exposure among university students in a low- and middle-income country during an acute sociopolitical crisis. Unlike prior studies that examine activism or misinformation/disinformation independently, this study captures their concurrent psychological effects using internationally validated severity measures (GAD-7, PHQ-9), thereby preserving the gradient of psychological burden. Beyond its methodological contribution, this study carries exceptional historical significance. The July-August 2024 student protest in Bangladesh represents one of the most consequential episodes of student-led activism in South Asian history, which within weeks culminated in the resignation of a government that had been in power for fifteen consecutive years [6]. Situating mental health research within this extraordinary context not only fills a critical gap in the literature on activism and psychological well-being, but also generates urgently needed evidence for policymakers, universities, and mental health practitioners navigating the aftermath of mass sociopolitical upheaval in resource-limited settings.
We hypothesized that a higher level of participation in student activism, combined with exposure to misinformation and disinformation, is associated with mental health issues among university students in Bangladesh. The study aimed to examine the combined psychological burden of student activism and misinformation/disinformation exposure on the mental health of university students during the July–August 2024 student protest in Bangladesh. The objective was to generate evidence that could inform university-based mental health interventions, promote media and information literacy, and guide targeted policy responses applicable to similar sociopolitical contexts in low- and middle-income settings.
Methods
Study design and participants
A cross-sectional online survey was conducted from September to October 2024 among Bangladeshi university students aged 18 to 30 years enrolled in undergraduate or postgraduate (MS/MPhil/PhD) programs. This age range was selected as Bangladeshi university-going students typically enroll in graduation programs at age 18 after completing higher secondary education and in post-graduation programs in their late twenties within this age range [21]. A self-administered Google form questionnaire was distributed via email and social media platforms (Facebook, Messenger, WhatsApp, Viber) to reach a diverse sample from public and private universities. Individuals who self-reported a prior diagnosis of severe mental health conditions were excluded from the study, with exclusion determined through self-disclosure at the informed consent stage of the questionnaire.
Convenience sampling was strategically employed to select participants who met specific criteria aligned with the study’s objectives. To ensure the questionnaire’s clarity and reliability, a pilot test was conducted with 20 students before the main data collection. Mental health outcomes were evaluated using trusted standardized instruments: the Generalized Anxiety Disorder-7 (GAD-7) for anxiety and the Patient Health Questionnaire-9 (PHQ-9) for depression [22, 23]. All participants were thoroughly briefed on the study’s objectives, ethical standards, and confidentiality protocols. The questionnaire was distributed to 700 students via email and social media platforms, yielding 565 valid responses for analysis.
Instrument
The self-administered questionnaire was divided into five sections (see Appendices).
Baseline characteristics
Baseline characteristics included sociodemographic information like age (18–22, 23–24, 25–30 years), gender, area of residence, and academic level 1st year to postgraduate. Academic disciplines were categorized as Arts and Humanities, Social Sciences, Biological Sciences, Mathematical and Physical Sciences, Engineering/Technology, Business/Commerce, Law, and Other. Economic background was assessed using the monthly family income in Bangladeshi Taka (BDT).
Student activism-related variables
Participation frequency in activism was evaluated using a five-point scale, ranging from “Never” to “Very Frequently.” Motivational factors such as personal beliefs, values, and peer influences were examined to understand whether intrinsic or extrinsic drivers shaped one’s activism.
Additionally, participants were asked if they or any of their first-degree relatives had been directly affected during the activism e.g., harmed, injured, or threatened to assess how the intensity of activism, underlying motivations, and personal consequences contributed to psychological distress among university students.
Misinformation and disinformation
Participants reported the frequency of exposure on a scale from “Never” to “Very Frequently”. Students’ ability in identifying misinformation or disinformation was measured using a scale from “Not Confident” to “Very Confident”. The reasons behind the belief or sharing of misinformation were measured such as lack of awareness, emotional response, confirmation bias, trust in sources, or limited access to reliable information. The reasons behind the belief or sharing of misinformation were assessed using study-specific categories. The categorization of reasons for believing or sharing misinformation (e.g., emotional response, self-belief bias, trust in sources, limited information access) was adapted from existing literature on misinformation psychology [24–26].
Additionally, participants indicated whether misinformation had influenced their views or actions related to activism by “Yes,” “No,” or “Unsure”, and whether they had ever fact-checked information before sharing.
Mental health and distress
The participants indicated whether they had sought mental health support due to July-August 2024 student protest-related or misinformation-induced distress, with response options - “Yes,” “No,” and “Considered but did not seek help.”
Evaluation of anxiety and depression
Anxiety levels were measured using the Generalized Anxiety Disorder 7 (GAD-7) scale that assesses the frequency of anxiety symptoms, over a two-week period [12]. Responses range from 0 (not at all) to 3 (nearly every day), with total scores (0–21) indicating severity from none/minimal to severe to explore the status of students’ mental health during the July-August 2024 student protest.
Depression was evaluated using the Patient Health Questionnaire-9 (PHQ-9) that measures low mood, fatigue, and hopelessness over the past two weeks according to the Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) criteria [13]. Each of the nine items is rated on a scale from 0 (not at all) to 3 (nearly every day), yielding a total score (0–27) that classifies depression as mild, moderate, moderately severe, or severe. Both the GAD-7 and PHQ-9 have demonstrated strong content, construct, and criterion-related validity, and high internal consistency [Cronbach’s alpha (α) = 0.86–0.89].
Statistical analysis
Data analyses were conducted using STATA version 14.2. Univariate analyses summarize independent variables as frequencies and percentages. Afterward, bivariate analyses were done to assess the differences among ordered outcome groups (separately for anxiety levels and depression levels) across the categories of the explanatory variables using the Kruskal-Wallis tests, Mann-Whitney U tests, and Spearman’s rank correlation tests, and associations were quantified using epsilon squared (ε²), rank-biserial correlation (rrb), and the Spearman’s rank correlation coefficient (ρ) as the measures of effect sizes, respectively. Variables exhibiting a p-value of < 0.05 in the bivariate analyses were included in the multivariate analyses to explore the factors associated with anxiety and depression. As both of our outcome variables are ordinal in nature, we compared three ordinal logistic regression (OLR) approaches for conducting multivariate analyses: (1) a proportional odds model (POM), using the OLOGIT command, (2) a partial proportional odds model (PPOM), and (3) a generalized ordered logit (GOLOGIT) model, using the GOLOGIT2 commands. Model selection was based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), where lower values indicated a better fit. The POM demonstrated a better fit (exhibited optimum AIC/BIC values among all models) and was therefore chosen for conducting final analyses. The variables with p < 0.05 in bivariate analyses were included only.
Ethical consideration
The study was approved by the Biosafety, Biosecurity and Ethical Committee of Jahangirnagar University (Ref No: BBEC, JU/M 2024/11 (147)). Participation was entirely voluntary, and students were informed of their right to withdraw at any time without consequences. Informed consent was obtained electronically before survey access, and participants were assured that their responses would remain anonymous and reported only in an aggregated form.
Results
Sociodemographic factors and misinformation/disinformation-related parameters
Table 1 summarizes the sociodemographic characteristics and activism-related tendencies of 565 university students in the July-August 2024 student protest. Gender distribution was nearly equal, with 47.8% male and 52.2% female. Participants were mostly aged 18–24 (32.7% aged 18–22, 34.2% aged 23–24) and primarily mid-program undergraduates (50.6%), notably from arts and humanities (73.6%). Over two-thirds (68.5%) of the students came from rural areas.
Table 1.
Sociodemographic factors and Misinformation/disinformation-related parameters in the July-August 2024 student protest among the university students (n = 565)
| Variables | Categories | Frequency (n) | Percentage (%) |
|---|---|---|---|
| Age | 18–22 | 185 | 32.74 |
| 23–24 | 193 | 34.16 | |
| 25–30 | 187 | 33.10 | |
| Gender | Male | 270 | 47.79 |
| Female | 295 | 52.21 | |
| Academic year | 1st-2nd | 176 | 31.15 |
| 3rd-5th | 286 | 50.62 | |
| Postgraduate | 103 | 18.23 | |
| Discipline | Science | 112 | 19.82 |
| Arts | 416 | 73.63 | |
| Commerce | 37 | 6.55 | |
| Monthly family income (BDT) | < 10,000 | 78 | 13.81 |
| 10,000–29,999 | 176 | 31.15 | |
| 30,000–49,999 | 182 | 32.21 | |
| 50,000 or more | 129 | 22.83 | |
| Place of origin | Rural | 387 | 68.5 |
| Urban | 178 | 31.5 | |
| Participation in the July activism | Never | 29 | 5.13 |
| Rarely | 94 | 16.64 | |
| Occasionally | 215 | 38.05 | |
| Frequently | 167 | 29.56 | |
| Very frequently | 60 | 10.62 | |
| Activism motivation | None/not sure | 32 | 5.66 |
| Personal belief | 522 | 92.39 | |
| Peer influence | 11 | 1.95 | |
| Personal or family impact due to the July activism | No | 406 | 71.86 |
| Yes | 159 | 28.14 | |
| Misinformation/ disinformation exposure frequency | Never | 42 | 7.43 |
| Rarely | 90 | 15.93 | |
| Occasionally | 166 | 29.38 | |
| Frequently | 215 | 38.05 | |
| Very frequently | 52 | 9.2 | |
| Self-confidence in identifying misinformation/ disinformation | None | 41 | 7.26 |
| Moderate | 483 | 85.39 | |
| Full | 41 | 7.26 | |
| Perceived psychology of misinformation spreaders | Emotion | 153 | 27.08 |
| Bias towards self-belief | 288 | 50.97 | |
| Trusted source | 25 | 4.42 | |
| Lack of reliable information | 99 | 17.52 | |
| Perceived role of misinformation/ disinformation in shaping activism-related views or actions | No | 228 | 40.35 |
| Yes | 213 | 37.7 | |
| Not sure | 124 | 21.95 | |
| Frequently used fact-checking website | BD Fact Check | 254 | 44.96 |
| Rumor scanner | 311 | 55.04 | |
| Fact-checking before sharing information on social media | No | 259 | 45.84 |
| Yes | 306 | 54.16 | |
| Mental distress encountered due to the activism | Never | 71 | 12.57 |
| Rarely | 135 | 23.89 | |
| Occasionally | 201 | 35.58 | |
| Frequently | 123 | 21.77 | |
| Very frequently | 35 | 6.19 | |
| Mental health support sought due to self-perceived distress related to the activism | No | 255 | 45.13 |
| Yes | 115 | 20.35 | |
| Considered but did not | 195 | 34.51 |
In the July-August 2024 student protest, 38.05% of students participated occasionally, while 29.56% participated frequently, motivated mainly by personal belief (92.39%). Over a third (38.05%) frequently faced misinformation, yet 85.39% were moderately confident in identifying it. The main drivers of misinformation were self-belief bias (50.97%) and emotional influences (27.08%).
Rumor Scanner was the preferred tool for verifying information among 55.04% of participants, and 54.16% engaged in fact-checking before sharing. About 35.58% experienced activism-related distress, with 20.35% seeking mental health support and 34.51% considered seeking help but ultimately did not.
Prevalence of anxiety and depression among the participants
Table 2 illustrates the overall levels of anxiety and depression among university students during the July-August 2024 student protest period. Among all the students, 37.88% experienced severe anxiety, while 14.16% were found to have severe depression.
Table 2.
Anxiety and depression levels among the university students during the July-August 2024 student protest (n = 565)
| Anxiety levels | Frequency (n) | Percentage (%) |
|---|---|---|
| None to minimal | 43 | 7.61 |
| Mild | 141 | 24.96 |
| Moderate | 167 | 29.56 |
| Severe | 214 | 37.88 |
| Depression levels | Frequency (n) | Percentage (%) |
|---|---|---|
| None to minimal | 62 | 10.97 |
| Mild | 162 | 28.67 |
| Moderate | 141 | 24.96 |
| Moderate-severe | 120 | 21.24 |
| Severe | 80 | 14.16 |
Correlation of sociodemographic and activism-related parameters with anxiety
Table 3 demonstrates bivariate analyses between the independent variables and levels of anxiety severity. Gender showed very strong evidence of association with anxiety severity (p < 0.001), as did frequent exposure to misinformation/disinformation related to the July activism (p < 0.001) and distress related to the activism (p < 0.001). Students’ place of origin also showed strong evidence of association with the outcome (p < 0.01), as did seeking or considering seeking mental health support due to such distress (p < 0.01). Age was statistically significantly associated with anxiety severity (p = 0.0218). Confidence in identifying misinformation (p = 0.025) and self-perception regarding the psychology of individuals who spread misinformation or disinformation (p = 0.029) were also associated with students’ anxiety levels.
Table 3.
Association of sociodemographic and July-August 2024 student protest-related characteristics with anxiety levels among the university students (n = 565)
| Variables | Categories | P-value | Effect size |
|---|---|---|---|
| Age | 18–22 | 0.0218 | ε² = 0.013 |
| 23–24 | |||
| 25–30 | |||
| Gender | Male | < 0.001 | rrb = 0.255 |
| Female | |||
| Academic year | 1st -2nd | 0.354 | ε² = 0.0037 |
| 3rd -5th | |||
| Postgraduate | |||
| Discipline | Science | 0.1141 | ε² = 0.0077 |
| Arts | |||
| Commerce | |||
| Monthly family income (BDT) | < 10,000 | 0.1745 | ε² = 0.0088 |
| 10,000–29,999 | |||
| 30,000–49,999 | |||
| 50,000 or more | |||
| Place of origin | Rural | < 0.01 | rrb = 0.133 |
| Urban | |||
| Participation in the July activism | Never | 0.011 | ρ = 0.1073 |
| Rarely | |||
| Occasionally | |||
| Frequently | |||
| Very frequently | |||
| Activism motivation | None | < 0.01 | ε² = 0.0164 |
| Personal belief | |||
| Peer influence | |||
| Personal or family impact due to the July activism | No | 0.464 | rrb = -0.031 |
| Yes | |||
| Misinformation/ disinformation exposure frequency | Never | < 0.001 | ρ = 0.2293 |
| Rarely | |||
| Occasionally | |||
| Frequently | |||
| Very frequently | |||
| Self-confidence in identifying misinformation/ disinformation | None | 0.025 | ε² = 0.013 |
| Moderate | |||
| Full | |||
| Perceived psychology of misinformation spreaders | Emotion | 0.029 | ε² = 0.0161 |
| Bias towards self-belief | |||
| Trusted source | |||
| Lack of reliable information | |||
| Perceived role of misinformation/ disinformation in shaping activism-related views or actions | No | 0.426 | ε² = 0.003 |
| Yes | |||
| Not sure | |||
| Frequently used fact-checking website | BD Fact Check | 0.223 | rrb = 0.051 |
| Rumor scanner | |||
| Fact-checking before sharing information on social media | No | 0.367 | rrb = -0.038 |
| Yes | |||
| Distress encountered due to the July activism | Never | < 0.001 | ρ = 0.26 |
| Rarely | |||
| Occasionally | |||
| Frequently | |||
| Very frequently | |||
| Mental health support sought | No | < 0.01 | ε² = 0.024 |
| Yes | |||
| Considered but did not |
Contribution of independent variables to depression severity
Table 4 shows bivariate analyses between the independent variables and levels of depression severity. Gender, frequency of participation in activism, frequency of encountering misinformation/disinformation, activism-related distress, and mental health support seeking due to such distress all showed very strong evidence of association with depression severity (p < 0.001). Age showed moderate evidence of a statistically significant association (p = 0.039). Not fact-checking information before sharing on social media was also associated with depression severity (p < 0.05).
Table 4.
Association of sociodemographic and July-August 2024 student protest-related characteristics with depression levels among the university students (n = 565)
| Variables | Categories | P-value | Effect size |
|---|---|---|---|
| Age | 18–22 | 0.0386 | ε² = 0.012 |
| 23–24 | |||
| 25–30 | |||
| Gender | Male | < 0.001 | rrb = − 0.156 |
| Female | |||
| Academic year | 1st -2nd | 0.3728 | ε² = 0.001 |
| 3rd -5th | |||
| Postgraduate | |||
| Discipline | Science | 0.0665 | ε² = 0.006 |
| Arts | |||
| Commerce | |||
| Monthly family income (BDT) | < 10,000 | 0.0595 | ε² = 0.0079 |
| 10,000–29,999 | |||
| 30,000–49,999 | |||
| 50,000 or more | |||
| Place of origin | Rural | 0.115 | rrb = − 0.026 |
| Urban | |||
| Participation in the July activism | Never | < 0.001 | ρ = 0.158 |
| Rarely | |||
| Occasionally | |||
| Frequently | |||
| Very frequently | |||
| Activism motivation | None | 0.2158 | ε² = 0.0019 |
| Personal belief | |||
| Peer influence | |||
| Personal or family impact due to the July activism | No | 0.558 | rrb = -0.025 |
| Yes | |||
| Misinformation/ disinformation exposure frequency | Never | < 0.001 | ρ = 0.154 |
| Rarely | |||
| Occasionally | |||
| Frequently | |||
| Very frequently | |||
| Self-confidence in identifying misinformation/ disinformation | None | 0.966 | ε² = 0.0000 |
| Moderate | |||
| Full | |||
| Self-perception on the psychology of people who spread misinformation/ disinformation | Emotion | 0.341 | ε² = 0.0006 |
| Bias towards self-belief | |||
| Trusted source | |||
| Lack of reliable information | |||
| Perceived role of misinformation/ disinformation in shaping activism-related views or actions | No | 0.7576 | ε² = 0.0000 |
| Yes | |||
| Not sure | |||
| Frequently used fact-checking website | BD Fact Check | 0.922 | rrb = 0.0041 |
| Rumor scanner | |||
| Fact-checking before sharing information on social media | No | < 0.05 | rrb = − 0.082 |
| Yes | |||
| Distress encountered due to the July activism | Never | < 0.001 | ρ = 0.193 |
| Rarely | |||
| Occasionally | |||
| Frequently | |||
| Very frequently | |||
| Mental health support sought | No | < 0.001 | ε² = 0.036 |
| Yes | |||
| Considered but did not |
Key predictors of varying levels of anxiety severity
Multivariate analysis results from Table 5 identified several key predictors of varying levels of anxiety severity (none or minimal, mild, moderate, severe) related to the July-August 2024 student protest. Participants aged 25–30 years had lower odds of higher anxiety levels than those aged 18–22 years (OR = 0.70, 95% CI: 0.47 to 1.05, p = 0.085), although this association did not reach statistical significance. Female students had very strong evidence of having 2.25 times higher odds of reporting moderate-to-severe levels of anxiety compared to males (95% CI: 1.60 to 3.16, p < 0.001).
Table 5.
Multivariate analysis between sociodemographic and July-August 2024 student protest-related characteristics and anxiety levels (n = 565)
| Variables | Categories | Odds ratio (95% CI) | P-value |
|---|---|---|---|
| Age | 18–22 | Ref. | |
| 23–24 | 1.11 (0.75 to 1.63) | 0.606 | |
| 25–30 | 0.70 (0.47 to 1.05) | 0.085 | |
| Gender | Male | Ref. | |
| Female | 2.25 (1.60 to 3.16) | < 0.001 | |
| Place of origin | Rural | Ref. | |
| Urban | 0.77 (0.54 to 1.08) | 0.131 | |
| Participation in the July activism | Never | Ref. | |
| Rarely | 1.09 (0.42 to 2.80) | 0.859 | |
| Occasionally | 0.98 (0.39 to 2.47) | 0.970 | |
| Frequently | 1.57 (0.62 to 4.02) | 0.343 | |
| Very frequently | 1.34 (0.48 to 3.72) | 0.580 | |
| Activism motivation | None | Ref. | |
| Personal belief | 1.70 (0.70 to 4.14) | 0.239 | |
| Peer influence | 0.91 (0.23 to 3.71) | 0.901 | |
| Misinformation/ disinformation exposure frequency | Never | Ref. | |
| Rarely | 2.46 (1.16 to 5.22) | 0.019 | |
| Occasionally | 2.18 (1.07 to 4.43) | 0.030 | |
| Frequently | 3.36 (1.78 to 6.73) | 0.001 | |
| Very frequently | 4.81 (2.0 to 11.53) | < 0.001 | |
| Self-confidence in identifying misinformation/ disinformation | None | Ref. | |
| Moderate | 1.56 (0.81 to 3.06) | 0.185 | |
| Full | 1.1 (0.46 to 2.67) | 0.826 | |
| Self-perception on the psychology of people who spread misinformation/ disinformation | Emotion | Ref. | |
| Bias towards self-belief | 1.18 (0.81 to 1.72) | 0.398 | |
| Trusting a source | 0.44 (0.18 to 1.07) | 0.070 | |
| Lack of reliable information | 0.93 (0.57 to 1.51) | 0.758 | |
| Distress encountered due to the July activism | Never | Ref. | |
| Rarely | 0.75 (0.43 to 1.33) | 0.335 | |
| Occasionally | 1.14 (0.66 to 1.98) | 0.639 | |
| Frequently | 2.06 (1.12 to 3.78) | 0.020 | |
| Very frequently | 1.52 (0.63 to 3.62) | 0.346 | |
| Mental health support sought | No | Ref. | |
| Yes | 1.21 (0.78 to 1.89) | 0.395 | |
| Considered but did not | 1.44 (0.99 to 2.08) | 0.052 |
Ref. = Reference category, CI = Confidence Interval, Adjusted model
Frequent exposure to misinformation/disinformation during the time of the July-August 2024 student protest demonstrated statistical evidence of association with anxiety. Those encountering misinformation/disinformation very frequently had 4.81 times higher odds of having elevated levels of anxiety (95% CI: 2.0 to 11.53, p < 0.001) compared to those who were never exposed. Students who perceived trust in a particular source as the main psychological reason for spreading misinformation or disinformation from that source had lower odds of higher anxiety levels than those who perceived emotion as the main reason, although this association did not reach statistical significance (OR = 0.44, 95% CI: 0.18 to 1.07, p = 0.07).
Additionally, students experiencing frequent activism-related distress showed 2.06 times higher odds of having higher levels of anxiety (95% CI: 1.12 to 3.78, p = 0.02). Finally, those who considered but didn’t seek mental health support had weak statistical evidence of having elevated odds (OR = 1.44, 95% CI: 0.99 to 2.08, p = 0.052).
Key predictors of varying levels of depression severity
Multivariate analysis results from Table 6 identified several key predictors of varying levels of depression severity (none or minimal, mild, moderate, moderately severe, and severe) related to the July-August 2024 student protest. Female participants showed very strong evidence of having 1.67 times higher odds of experiencing elevated depression levels compared to males (95% CI: 1.22 to 2.29, p < 0.001). Regarding participation in activism, frequent participation was associated with 2.71 times higher odds of the outcome compared with those who never participated (95% CI: 1.31 to 5.60, p = 0.007). Furthermore, occasional participation (OR = 1.91, 95% CI: 0.94 to 3.87, p = 0.073) and very frequent participation (OR = 2.12, 95% CI: 0.94 to 4.81, p = 0.072) were associated with higher odds of elevated depression, although neither association reached statistical significance. In this study, “very frequent participation” referred to participating almost every day during the period the activism took place. Compared to individuals who did not consider mental health support, those who sought support had 2.09 times higher odds of experiencing depression (95% CI: 1.39 to 3.15, p < 0.001). Similarly, those who considered seeking support but did not do so had 1.70 times higher odds of experiencing depression (95% CI: 1.20 to 2.41, p = 0.003).
Table 6.
Multivariate analysis between sociodemographic and July-August 2024 student protest-related characteristics and depression levels (n = 565)
| Variables | Categories | Odds ratio (95% CI) | P-value |
|---|---|---|---|
| Age | 18–22 | Ref. | |
| 23–24 | 1.04 (0.72 to 1.51) | 0.829 | |
| 25 and above | 0.75 (0.51 to 1.11) | 0.148 | |
| Gender | Male | Ref. | |
| Female | 1.67 (1.22 to 2.29) | < 0.001 | |
| Participation in the July activism | Never | Ref. | |
| Rarely | 1.43 (0.68 to 3.06) | 0.346 | |
| Occasionally | 1.91 (0.94 to 3.87) | 0.073 | |
| Frequently | 2.71 (1.31 to 5.60) | 0.007 | |
| Very frequently | 2.12 (0.94 to 4.81) | 0.072 | |
| Misinformation/ disinformation exposure frequency | Never | Ref. | |
| Rarely | 1.11 (0.54 to 2.28) | 0.773 | |
| Occasionally | 0.94 (0.47 to 1.88) | 0.868 | |
| Frequently | 1.61 (0.82 to 3.14) | 0.163 | |
| Very frequently | 1.72 (0.75 to 3.94) | 0.197 | |
| Fact-checking before sharing information on social media | No | Ref. | |
| Yes | 1.14 (0.83 to 1.16) | 0.416 | |
| Distress encountered due to the July activism | Never | Ref. | |
| Rarely | 0.69 (0.39 to 1.21) | 0.188 | |
| Occasionally | 1.06 (0.61 to 1.82) | 0.844 | |
| Frequently | 1.34 (0.75 to 2.39) | 0.328 | |
| Very frequently | 1.62 (0.71 to 3.71) | 0.254 | |
| Mental health support sought | No | Ref. | |
| Yes | 2.09 (1.39 to 3.15) | < 0.001 | |
| Considered but did not | 1.70 (1.20 to 2.41) | 0.003 |
Ref. = Reference category, CI = Confidence Interval,Adjusted model
Discussion
This study examined the psychological burden of the July-August 2024 student protest and the simultaneous encountering of misinformation and disinformation by the university students, focusing particularly on depression and anxiety symptoms. The analysis revealed that a majority of students experienced severe anxiety and varying degrees of depression — a finding consistent with Husain (2026), who similarly documented high psychological distress among Bangladeshi student activists following the same uprising [27]. Our results also highlighted key sociodemographic and psychosocial factors such as gender, age, exposure to misinformation and disinformation, and the willingness to seek mental health support that are linked to mental health outcomes. Previous studies have shown that misinformation and disinformation impact mental health, and that sociodemographic factors have strong associations with anxiety and depression caused by these influences [28, 29].
Age and gender emerged as significant predictors of the severity of anxiety. In our study, younger students (18–22 years) and female students reported significantly higher anxiety levels. This is corroborated by Husain (2026), who also found that gender was a significant predictor of psychological responses (p = 0.028) among Bangladeshi student activists during the same uprising [27]. These findings echo prior studies suggesting that females show a higher tendency toward internalizing anxiety and depression [30], due to a combination of hormonal, psychological, and sociocultural factors. The higher burden of anxiety and depression among female students in our study is consistent with the directional trend reported by Chakhunashvili (2025) among political activists in Georgia, where females also showed higher rates of both anxiety and depression [31]. Additionally, early university years often involve significant transitions and adaptation stress, which may exacerbate emotional challenges [32].
Interestingly, academic year and discipline were not significantly associated with anxiety or depression levels. This may suggest that mental health challenges during political activism transcend academic differences and are more rooted in external sociopolitical stressors than educational factors alone [32].
In this study, frequent exposure to activism and related stressors, such as misinformation and disinformation, was significantly associated with higher anxiety and depression scores. According to the research [28, 32], university students often face transitional life challenges, including academic pressure, social restructuring, and identity exploration. These pressures can intensify during politically turbulent times. These results are consistent with prior literature indicating that sociopolitical unrest can aggravate psychological distress among youth populations [9]. These findings are theoretically grounded in the Stress Exposure Model [17], which suggests that sustained exposure to sociopolitical stressors depletes individuals’ coping resources, heightening vulnerability to anxiety and depression. Concurrently, the simultaneous circulation of misinformation and disinformation during the uprising reflects what the WHO has conceptualized as an infodemic [19], a crisis-driven information environment that compounds psychological burden beyond the direct stressors of activism itself.
Students’ place of origin - urban vs. rural - was significantly associated with anxiety, with urban students reporting higher levels of distress. This could reflect urban students’ greater exposure to protest-related events, both physically and digitally. Active participation in the July-August 2024 student protest, especially at frequent or very frequent levels, was associated with increased anxiety symptoms. This aligns with prior research showing that political involvement, while empowering for some, can be psychologically taxing, particularly in high-risk or emotionally charged contexts [32].
Perceived misinformation or disinformation also played a notable role. Students who reported frequently encountering misinformation had significantly higher anxiety scores, underscoring the psychological burden associated with information overload or conflicting narratives [33]. This is consistent with Cognitive Load Theory [20], which holds that the processing of excessive or conflicting information overwhelms cognitive capacity, impairing judgment and amplifying emotional distress; a mechanism particularly relevant during the rapid, unverified information flows that characterized the July–August 2024 student protest. Conversely, students with great confidence in identifying misinformation showed reduced symptoms, indicating media literacy and critical thinking may buffer against anxiety. This protective pattern aligns with the cognitive appraisal framework of Lazarus and Folkman [18], which suggests that individuals who appraise information environments as manageable through critical evaluation of sources, experience reduced psychological strain compared to those who perceive such environments as threatening and uncontrollable.
The findings highlight gender disparities, activism participation frequency, and mental health support-seeking as key factors in depression severity among students. Students who sought or considered seeking mental health help reported significantly higher depression scores, indicating that those most affected were likely to recognize the need for psychological support. However, a substantial portion of students who considered seeking help ultimately did not, reflecting potential barriers to access, stigma, or normalization of distress during activism periods. Stigma continues to be a significant barrier for those living with mental illnesses and substance use disorders [34], which may contribute to the reluctance some students feel toward pursuing professional support.
The study showed that exposure to misinformation significantly affects individuals’ mental health and well-being [35, 36]. This emphasizes the importance of media and information literacy among the students. Interestingly, students who trusted specific sources reported lower anxiety levels, implying that critical thinking about information can be protective [12, 37]. News literacy and news trust are significant predictors of fact-checking intent among social media users, indicating that students with stronger media literacy skills are better equipped to navigate misinformation-prone environments [38]. However, students feeling distressed from activism were more likely to experience heightened anxiety [14, 31], and those considering mental health support but not seeking it faced a slightly higher risk of anxiety [39]. Most importantly, they show the critical need to tackle misinformation as a substantial anxiety risk factor to create supportive environments that promote awareness, resilience, and well-being. The weakened association between misinformation exposure and depression in the adjusted model may reflect the time-dependent nature of depressive symptoms, which typically develop following prolonged distress rather than acute exposure. Additionally, the overall optimism about the movement's outcome might have temporarily buffered against depression despite increased anxiety.
Conversely, an argument could be made that student unrest fosters empowerment and solidarity, enhancing self-esteem and political awareness among students. Therefore, it is recommended that universities offer sufficient mental support for these students during protests [32].
These findings emphasize the need for proactive mental health interventions during and immediately after periods of sociopolitical unrest. Universities have a vital role in equipping staff and volunteers with essential mental health training, empowering them to recognize and support students in distress [27]. By providing access to online resources and engaging tools on stress management alongside mindfulness practices, educational institutes can foster a nurturing environment that prioritizes the mental well-being of every student, particularly during or following periods of collective student mobilization. Training in digital literacy and misinformation identification may also serve as a preventive strategy to reduce the psychological toll of disinformation exposure [29, 40].
Future direction
Students involved in the July–August 2024 student protest experienced significant anxiety and depression, with potential long-term mental health consequences if adequate support is not provided. Besides, the majority of students did not seek mental health support, and a substantial proportion considered doing so but did not follow through. This gap between need and help-seeking behavior underscores the urgency of targeted institutional action. Future research should employ longitudinal designs to clarify the temporal relationships between activism participation, misinformation exposure, and mental health outcomes. Mixed-methods approaches would further enrich understanding by capturing students’ subjective experiences of psychological distress in the context of sociopolitical engagement.
We propose several practical steps for universities and policymakers. Universities should strengthen mental health support for students involved in activism or exposed to stressful sociopolitical events. This includes on-campus counseling services, trained staff for trauma-informed care, peer support programs, and online counseling options during crisis periods. These services should be easily accessible and stigma-free so students can seek help early. Educational institute should also promote media literacy through targeted training programs. Arranging short workshops on fact-checking, youth-focused media information literacy, source evaluation, and critical thinking help students identify misinformation and reduce the psychological burden of information overload. Moreover, the university should prioritize mental health interventions for female and first-year students, as findings indicate a high level of anxiety within these groups. At the policy level, universities and education authorities need to develop mental health response plans for students who participate in activism. Collaboration with government initiatives and reliable media or fact-checking organizations can also help reduce the spread of harmful misinformation. Overall, protecting students' mental health during activism should be a shared responsibility between institutions and policymakers.
Strength and limitations
Despite the strengths of the sample size, contextual relevance and the use of GAD-7 and PHQ-9 tools, which effectively detect anxiety and depression, this study has several limitations. First, the cross-sectional nature of the study precludes causal inference; longitudinal designs are needed to establish temporal relationships. Second, the reliance on self-reported data, particularly regarding mental health symptoms, activist engagement, and the self-disclosure of pre-existing severe mental health disorders during the informed consent stage, may be subject to recall or disclosure bias. Third, self-selection bias is acknowledged, as students more severely affected by the revolution may have been more motivated to participate, potentially inflating mental health burden estimates. Fourth, data collection in a politically sensitive context may have introduced social desirability bias, with participants potentially over- or under-reporting their level of activism involvement. Fifth, the study did not account for several potentially confounding variables, including social media usage intensity, direct exposure to violence or trauma, family support systems, and academic performance that may cause anxiety and depression. Sixth, the categorization of reasons for believing or sharing misinformation, such as emotional response, self-belief bias, trust in sources, and limited information access, was adapted from existing literature which may limit the reliability of these measures as it was not based on previously validated scale. Finally, as the study was conducted among university students in Bangladesh during a specific sociopolitical event, the findings may not be generalizable to other populations or forms of activism, although they could be relevant to similar low- and middle-income settings.
Conclusion
This study highlights that active participation of Bangladeshi university students in the July-August 2024 student protest and frequent exposure to misinformation and disinformation were significantly associated with severe anxiety, especially with female students and younger age groups suffering from a disproportionately higher psychological burden. The findings provide a timely evidence base for university-based mental health interventions tailored to the unique experiences of student activists during sociopolitical crises. Simultaneously, promoting digital and media information literacy and encouraging fact-checking behaviors emerge as critical preventive strategies against misinformation-induced psychological distress. These findings carry implications beyond Bangladesh, offering an evidence base for universities, mental health policymakers, and public health stakeholders in comparable low- and middle-income settings navigating the psychological aftermath of student-led sociopolitical upheaval.
Supplementary Information
Acknowledgements
We are grateful to all participating students for taking the time to complete the questionnaire.
Abbreviations
- BDT
Bangladeshi Taka
- GAD-7
Generalized Anxiety Disorder-7
- PHQ-9
Patient Health Questionnaire-9
- PTSD
Post-traumatic stress disorder
Authors' contributions
TTP and MK wrote original draft, performed data collection, formal analysis and data curation; SY conceptualized, designed and directed the study, did supervision, reviewing and editing the manuscript. JHBM designed and supervised the study, did data curation and editing the manuscript; RSS performed methodology, formal analysis, data curation and validation; MRN analyzed data and prepared draft manuscript. The final manuscript has been read and approved by all authors.
Funding
The authors received no financial support for the study, authorship, and/or publication of this article.
Data availability
The datasets used and/or analyzed during the current study are in English and are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study was approved by the Biosafety, Biosecurity and Ethical Committee of Jahangirnagar University (Ref No: BBEC, JU/M 2024/11 (147)). All procedures performed in the study were in accordance with the ethical standards of the committee and with the Declaration of Helsinki. At the beginning of the online Google Form, just below the title, we have used a statement saying this work is completely voluntary, the response will be anonymous, participants have to be aged 18 or older, and they may withdraw the response at any time. We assumed it will take 5 min to fill up the survey, and we mentioned that too. Participants proceeded with the survey only after reviewing this information, thereby providing informed electronic consent. Participants were fully informed about the purpose of the study before participating and completing the online questionnaire.
Consent for publication
Not applicable. All participants gave their consent for the use of their anonymous quotations and anonymized data of their interactions in published works.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used and/or analyzed during the current study are in English and are available from the corresponding author on reasonable request.