Emotion regulation and mental health in college students during coronavirus pandemic lockdowns

Abstract

The coronavirus disease 2019 pandemic triggered a global mental health crisis, with college students particularly vulnerable population due to disruptions in academic, social, and developmental trajectories. This narrative review synthesizes evidence on the relationships among emotion regulation (ER) strategies, lifestyle factors, and mental health outcomes during the pandemic. Findings from over 40 studies, indicate high rates of depression, anxiety, and stress among students during lockdowns. Maladaptive ER strategies, such as compensatory spending (β = 0.13-0.19) and binge eating (β = 0.14-0.19), were consistently were consistently associated with increased psychological distress, reflecting short-term coping attempts that exacerbate long-term outcomes. In contrast, adaptive strategies, including engagement in recreational activities, regular physical exercise, and social support, were linked to reduced distress. These relationships were moderated by demographic factors (e.g., gender, socioeconomic status) and contextual variables (e.g., academic stress, sleep quality). Some studies also reported increased vulnerability among male students, potentially due to disruptions in gender-related coping patterns. Overall, ER emerges as a modifiable determinant of resilience. Interventions should emphasize adaptive ER strategies, healthy lifestyle behaviors, and the mitigation of academic and financial stressors. Future research should adapt longitudinal and mixed-methods approaches to clarify causal pathways and long-term psychological effects.

Key Words: Emotion regulation; COVID-19 pandemic; College students; Mental health; Lifestyle factors; Psychological distress; Coping strategies; Social support; Physical activity; Academic stress

Core Tip: This review synthesizes evidence on how ER strategies influenced college students’ mental health during the coronavirus disease 2019 lockdowns. Maladaptive behaviors such as compensatory spending and binge eating were identified as key risk factors, whereas recreational activities, physical exercise, and social support served as protective factors. Psychological factors were further influenced by socioeconomic status, academic stress, and gender, with emerging evidence of increased vulnerability among male students. The high comorbidity of depression, anxiety, and stress, suggests shared underlying mechanisms. A multi-level intervention framework targeting ER skills, lifestyle factors, and institutional support is proposed to enhance student resilience in future crises.

INTRODUCTION

Beyond its profound physical health consequences, the coronavirus disease 2019 (COVID-19) pandemic precipitated a parallel global mental health crisis and functioned as a natural experiment in population-level psychological resilience under chronic stress. College students, who are in a critical developmental stage characterized by identity formation, social integration, and academic demands, faced a unique constellation of adversities. These included abrupt transitions to remote learning, loss of campus communities, uncertainty about future careers, and constrained living conditions. The convergence of these stressors placed this population at heightened risk for psychological distress, as reflected in consistently elevated rates of depression, anxiety, and stress[1-3].

Understanding the factors that contribute to vulnerability and resilience in this context is therefore essential. Zhao et al[4], a 2026 cross-sectional study of 494 Chinese students using the Depression Anxiety Stress Scales-21, advanced this area by shifting the focus from static risk factors to dynamic processes, particularly habitual emotion regulation (ER) strategies. ER refers to the processes through which individuals influence the emotions they experience, including their timing, intensity, and expression, and is widely recognized as a core transdiagnostic mechanism in mental health[5,6]. While pre-pandemic research established the importance of strategies such as cognitive reappraisal and expressive suppression, the pandemic context provides a unique opportunity to examine how context-specific ER behaviors (e.g., online compensatory spending in response to distress) are associated with mental health outcomes under sustained stress[7-9].

AIM AND SCOPE OF THIS REVIEW

This article extends beyond a single-study commentary to provide a comprehensive narrative review that contextualizes the findings within the broader literature. Specifically, it aims to: (1) Synthesize global evidence on the prevalence and predictors of mental health problems among college students during COVID-19 Lockdowns[1-3,10-16]; (2) Analyze the roles of maladaptive and adaptive ER strategies[4,7,10,17-28]; (3) Examine key demographic, socioeconomic, and contextual moderators[5,29-37]; (4) Integrate findings within relevant psychological and neurobiological frameworks; and (5) Derive evidence-based recommendations for intervention and future research. By synthesizing findings from over 40 empirical studies and reviews, this review provides a cohesive account of ER and student mental health during the pandemic, and highlights implications for future public health emergencies.

METHODOLOGICAL OVERVIEW

This narrative review synthesizes evidence on ER and mental health among college students during the COVID-19 pandemic. Although it does not follow a pre-registered systematic review protocol, a structured approach was used to identify and integrate relevant literature. The review builds on the foundational studies[1-4,29,30,38-40] cited in Zhao et al’s study[4], and is supplemented by targeted searches in PubMed and Google Scholar for articles published from 2020 to 2025. Search terms included combinations of: (“college student” OR “university student” OR “young adult”) AND (“COVID-19” OR “pandemic” OR “lockdown”) AND (“emotion regulation” OR “coping” OR “psychological adaptation”) AND (“mental health” OR “depress” OR “anxiety” OR “stress”). Priority was given to longitudinal studies, large-scale cross-sectional surveys, meta-analyses, and studies explicitly measuring ER constructs. More than 40 key studies were selected based on their relevance to the central themes of this review, including global prevalence, ER strategies as risk and protective factors, moderating variables, and intervention implications. Findings were synthesized thematically to provide a coherent overview of the current state of the field.

GLOBAL MENTAL HEALTH CRISES DURING LOCKDOWNS: CONSISTENT PATTERNS ACROSS POPULATIONS

A clear global consensus has emerged from the pandemic literature: Lockdowns and social restrictions were associated with significant deterioration in mental health, with young adults and college students disproportionately affected[3,10,12,41-45]. Although Table 1 summarizes key studies, the broader evidence base reinforces this pattern. Early in the pandemic, a rapid review published in The Lancet highlighted the heightened psychological vulnerability of young individuals[15]. Meta-analytic findings further support this trend. For instance, Salari et al[12] in 2020 estimated global prevalence rates of depression and anxiety at approximately 25%-30%, substantially exceeding pre-pandemic levels[46,47]. Studies focusing specifically on college students report even higher rates. Browning et al[13] in 2021 and Li et al[14] in 2021 documented prevalence rates of clinically significant depression and anxiety frequently exceeding 30%-40%, corroborating and contextualizing the alarming rates (depression: 65.0%, anxiety: 69.4%) reported by Zhao et al[4]. This heightened vulnerability likely reflects a convergence of stressors, including developmental reliance on peer interaction, disruptions to academic progression and key milestones (e.g., graduation, and internships), increased financial strain, and for some students, a return to stressful home environments.

Table 1 Synthesis of mental health outcomes among college students during coronavirus disease 2019 lockdowns (expanded).

Ref.	Country/region	Sample size	Key findings (prevalence/predictors)	Notable ER/coping factors examined
Zhao et al[4]	China	494	Depression: 65.0%; anxiety: 69.4%; stress: 50.8%	Compensatory spending (β = 0.13-0.19), binge eating (β = 0.14-0.19), recreational activities (β = -0.25 to -0.30) as key ER habits
Cao et al[2]	China	7143	Anxiety: 24.9% (mild: 21.3%; moderate: 2.7%; severe: 0.9%)	Family instability and economic concerns as major stressors
Liu et al[11]	United States	898	Depression: 43.5%; anxiety: 45.4%	COVID-19 exposure, financial stress, weak social support
Browning et al[13]	United States	1621	Significant increases in depression/anxiety from pre-pandemic baseline	Loneliness was the strongest predictor; coping through substance use was a risk factor
Li et al[14]	China	746217	Approximately 35% experienced psychological distress	Poor sleep quality and family relationships were major correlates
Pfefferbaum and North[15]	Review	N/A	Summarized acute and chronic stress responses in youth	Highlighted disruption of routines and uncertainty as key mediators
Aristovnik et al[16]	62 countries	31212 students	High levels of anxiety (37.5%) and depression (33.6%)	Academic stress, isolation, and concerns about academic future were top stressors

ER: Emotion regulation; COVID-19: Coronavirus disease 2019; N/A: Not applicable.

ER HABITS AS DETERMINANTS OF MENTAL HEALTH OUTCOMES

The pandemic functioned as a large-scale stress test for ER capacity, providing ecological support for theoretical distinctions between adaptive and maladaptive strategies. Zhao et al[4] identified compensatory spending and binge eating as significant risk factors, consistent with the concept of experiential avoidance - strategies aimed at escaping or dampening negative internal experiences. Although such behaviors may provide short-term relief, they typically exacerbate distress over time, a pattern also observed in healthcare workers during the pandemic[23,28,48]. Compensatory spending (“retail therapy”) aligns with the mood repair hypothesis and may be particularly pronounced in digital environments that facilitate online consumptions. Coakley et al[19] in 2021 discussed how lockdowns amplified online consumption as an ER tool, potentially leading to problematic buying-shopping disorder. Similarly, binge eating reflects emotional eating models in which food is used to regulate affect[23,24]. Rodríguez-Rey et al[28] in 2024 reported increases disordered eating among students during lockdowns, linking these behaviors to elevated anxiety and depression.

Conversely, engagement in recreational activities, physical exercise, and hobbies emerged as protective factors[4,10,18]. These behaviors align with attentional deployment (i.e., shifting focus) and the behavioral activation model of depression[35], which mitigates low mood by increasing exposure to positive reinforcement. Social interaction, although physically restricted, remained protective when maintained digitally, underscoring the importance of social sharing and co-regulation as core ER processes[9,17,49]. Table 2 summarizes effect sizes, but it is crucial to note the underlying mechanisms: Activities like exercise promote neurobiological resilience (e.g., increased brain-derived neurotrophic factor, reduced inflammation), while hobbies can foster flow states and a sense of mastery. Ye et al[9] in 2022 found that maintaining a routine and engaging in valued activities were among the strongest predictors of better mental health during lockdowns. Social interaction, though restricted physically, remained a key protective factor when maintained digitally, underscoring the role of social sharing and co-regulation as core ER processes[9,17,50]. Furthermore, the perceived lack of social connection was a significant predictor of loneliness and depression during lockdowns, as highlighted in studies on the broader population[51,52].

Table 2 Risk and protective factors for student mental health during lockdowns: A thematic synthesis.

Factor category	Specific factors	Association with mental health	Proposed mechanism/ER framework	Ref.
Maladaptive ER/risk factors	Compensatory spending	Positive (β approximately 0.13-0.19)[1]	Experiential avoidance; mood repair; financial stress feedback loop	Zhang and Ma[7]; Rajkumar[8]
	Binge eating/emotional eating	Positive (β approximately 0.14-0.19)[1]	Emotional dysregulation; avoidance; physiological guilt/shame cycles	Coakley et al[19]; Rodríguez-Rey et al[28]
	Problematic internet/social media use	Positive	Avoidance, social comparison, sleep disruption	Marciano et al[20]; Boursier et al[21]
	Rumination	Strong positive	Perseverative cognitive focus on distress; amplifies negative affect	Cao et al[2]
Adaptive ER/protective factors	Recreational activities/hobbies	Negative (β approximately -0.25 to -0.30)[1]	Behavioral activation; attentional deployment; flow/mastery experiences	Quan et al[18]; Heumann et al[35]
	Physical activity/exercise	Negative (βapproximately -0.22)	Behavioral activation; physiological stress buffering (e.g., endorphins)	Stanton et al[10]
	Mindfulness/acceptance	Negative	Reduced experiential avoidance; decentering from negative thoughts	Hong et al[26]; Conversano et al[27]
	Cognitive reappraisal	Negative	Reinterpreting stressors; finding meaning; promoting psychological flexibility	Gross[5]
	Social support (virtual/in-person)	Negative (β approximately -0.19)	Social sharing; co-regulation; belongingness	Ye et al[9]; Ooi et al[17]
Contextual and demographic moderators	Lower socioeconomic status	Positive	Increased material hardship, less access to resources, higher baseline stress	Quan et al[18]; Amerio et al[56]
	High academic stress	Strong positive	Threat to self-efficacy and future prospects; performance pressure	Steare et al[38]; Sundarasen et al[54]
	Poor sleep quality	Strong positive	Bidirectional relationship; impairs prefrontal cortex function needed for ER	Cellini et al[55]; Alvaro et al[59]
	Loneliness/lack of social integration	Strong positive	Unmet need for connection; lack of co-regulation opportunities	Bu et al[51]; Killgore et al[52]

ER: Emotion regulation.

THEORETICAL INTEGRATION AND MECHANISMS

The observed patterns can be integrated within established psychological and neurobiological frameworks. The process model of ER[5] provides a useful lens: Lockdowns constrained situation selection and modification strategies (e.g., leaving a stressful environment), thereby increasing reliance on attentional deployment and cognitive change. Maladaptive responses, such as rumination and avoidance represent failures in these later stages. The transdiagnostic model of emotional disorders highlights that deficits in ER constitute a core vulnerability factor for both anxiety and depression, explaining their high comorbidity during the pandemic. From a neurobiological perspective, chronic stress associated with the pandemic likely contributed to allostatic load, resulting in dysregulation of the hypothalamic-pituitary-adrenal axis and inflammatory processes, as discussed by Gou et al[30] and McEwen[31]. This physiological dysregulation can impair prefrontal cortex function - the brain region critical for executive control and adaptive ER - creating a vicious cycle where stress impairs the very capacity needed to regulate it[29,30,32]. Additionally, the disruption of daily routines and loss of reinforcing activities can be interpreted through the behavioral model of depletion of positive reinforcement, central to theories of depression[35]. Table 3 provides an overview of key theoretical frameworks that help interpret the patterns of ER and mental health observed during the pandemic.

Table 3 Theoretical frameworks for understanding emotion regulation and mental health during crisis.

Theoretical framework	Core tenet	Application to pandemic findings	Ref.
Process model of emotion regulation (Gross)	ER unfolds over time via situation selection, modification, attentional deployment, cognitive change, and response modulation	Lockdowns limited situation selection/modification, increasing burden on cognitive change (reappraisal) which many found difficult, leading to maladaptive response modulation (e.g., binge eating)	Gross[5]
Transdiagnostic/RDoC approach	Shared underlying mechanisms (like ER deficits) cut across traditional diagnostic categories	Explains high comorbidity (r approximately 0.85-0.96) of depression, anxiety, and stress; points to interventions targeting shared processes (e.g., intolerance of uncertainty)	Woon et al[33]; Keshavan et al[34]
Allostatic load/chronic stress model	Chronic stress leads to wear-and-tear on physiological systems (neuroendocrine, immune), impairing brain function and mental health	Lockdowns were a chronic stressor; allostatic load links pandemic stress to long-term mental and physical health risks	McEwen[31]; Guidi et al[32]
Behavioral models (e.g., BA for depression)	Depression is maintained by a cycle of avoidance, reduced activity, and loss of positive reinforcement	Loss of campus activities and routines depleted positive reinforcement; protective factors like recreational activities worked via behavioral activation	Heumann et al[35]
Social baseline theory	The human brain expects proximity to social resources; distancing taxes our neural and metabolic resources for regulation	Social isolation forced individuals to “go it alone” neurologically, depleting resources for ER and increasing distress	Coan and Sbarra[36]; Eisenberger[37]

ER: Emotion regulation; RDoC: Research Domain Criteria; BA: Behavioral activation.

DEMOGRAPHIC AND SOCIOECONOMIC DETERMINANTS OF LOCKDOWN MENTAL HEALTH

The pandemic exacerbated pre-existing social and economic inequalities. Lower family income consistently predicted poorer mental health outcomes, as financial insecurity compounded pandemic-related stress, limited access to essential resources (e.g., quiet study space, reliable internet, therapy) and heightened uncertainty about the future[2,18]. This pattern aligns with the family stress model, which posits that economic strain disrupts family functioning and emotional climate[18,53]. Academic stress was widespread and intensified by the rapid transition to online learning, concerns about assessment and performance (“Zoom fatigue”), as well as uncertainty regarding educational and career prospects[16,38,54]. Sleep dysregulation, particularly “revenge bedtime procrastination” (delaying sleep to regain a sense of free time), emerged as a critical bidirectional factor: Both a symptom of distress and a cause of impaired ER capacity the following day, as noted by Cellini et al[55].

Zhao et al’s study[4] identification of demographic and socioeconomic factors associated with mental health outcomes during lockdown corroborates the findings of multiple international studies. The findings indicated that family economic status, frequently going to sleep late at night, academic stress, and the lack of social support networks significantly influenced emotional states.

The relationship between socioeconomic status and mental health during the lockdown has been consistently demonstrated across studies. Quan et al[18] found that economic pressure mediated the relationship between family income and child depression, with lower-income families experiencing greater psychological distress during the lockdown period. This aligns with Zhao et al’s finding[4] that students from lower-income families exhibited higher rates of negative emotions.

Academic stress emerged as a particularly significant factor in Zhao et al’s study[4], with 76.3% of students reporting significant academic stress, which was strongly associated with adverse emotional outcomes. This finding is consistent with Steare et al’s systematic review[38], which identified academic demands as a major contributor to mental health problems among young individuals. The transition to online learning, concerns about academic performance, and uncertainty about future educational and career prospects likely exacerbated overall stress.

SEX AND GENDER DIFFERENCES IN PSYCHOLOGICAL RESPONSES TO LOCKDOWN

The finding of heightened distress among some male student samples challenges pre-pandemic epidemiology and necessitates a nuanced interpretation. Pre-pandemic, women consistently reported higher levels of internalizing symptoms. However, lockdown conditions may have disrupted gender-specific coping repertoires. Men are more likely to rely on problem-focused coping and externalizing activities (e.g., team sports, in-person socializing) which were severely restricted, whereas women may more frequently use emotion-focused strategies (e.g., social support via technology, expressive writing) that were more adaptable to lockdown conditions[39,40,56]. Additionally, stigma surrounding help-seeking remains higher among men, potentially resulting in delayed or unaddressed distress. However, this pattern is not universal; many studies still identified higher absolute levels in women. Measurement invariance is a critical issue: Common screening tools may not equally capture male manifestations of distress (e.g., irritability, anger, substance use vs sadness, worry), as discussed by Dion-Albert et al[40] and Martin et al[57]. This underscores the need for gender-sensitive assessment and outreach.

Zhao et al’s counterintuitive finding[4] of higher rates of negative emotions detected among male students contrasts with an extensive body of pre-pandemic literature, but aligns with emerging research on sex-specific responses to lockdown conditions. Their findings revealed that 70.7% of male students reported depressive symptoms, compared to 60.9% of female students.

This pattern may be explained by gender differences in coping strategies and social support utilization. Gao et al[39] found that female students generally employed adaptive coping strategies and sought social support during stressful periods, whereas disruptions to activity-based coping may have disproportionately affected male students.

These differences should be interpreted cautiously. As Dion-Albert et al[40] demonstrated, the manifestation and measurement of psychological distress may vary based on sex, with males potentially underreporting certain symptoms, while displaying others more prominently. The higher rates observed among male students in Zhao et al’s study[4] highlight the importance of gender-sensitive mental health interventions during crises. Higher rates in male students align with studies suggesting that lockdowns disrupted traditional male coping mechanisms more (e.g., group sports). While this contrasts with the pre-pandemic predominance of mental health symptoms being reported by female students, it is consistent with Liu et al’s study[11] conducted in 2020, which reported similar shifts among young adults.

THE INTERCONNECTED NATURE OF NEGATIVE EMOTIONAL STATES

Zhao et al[4] reported strong positive correlations among depression, anxiety, and stress (r = 0.865-0.961), underscoring the interconnected nature of these emotional states during lockdown. Similar patterns have been consistently documented across studies examining mental health during the pandemic[1,3,10].

The high degree of comorbidity suggests shared underlying mechanisms, potentially involving dysregulation of stress response systems. For instance, Civieri et al[29] demonstrated that anxiety and depression were associated with accelerated development of cardiovascular risk factors, indicating that chronic stress during lockdown may have both psychological and physiological manifestations. This interconnectedness has important implications for interventions. Rather than targeting individual disorders in isolation, interventions should focus on shared mechanisms, such as deficits in ER and maladaptive coping strategies[5,33,34].

IMPLICATIONS FOR MENTAL HEALTH INTERVENTION AND POLICY

The evidence synthesized in this review identifies clear targets for multi-level intervention. Table 4 synthesizes the evidence reviewed to propose a multi-level intervention framework targeting student mental health during and beyond public health crises.

Table 4 Proposed intervention framework based on review evidence.

Intervention level	Target	Example strategies	Theoretical basis
Universal prevention (all students)	Promote adaptive ER, reduce stigma	Curriculum-integrated psychoeducation on stress management and ER skills[5,26]. Campus-wide wellness campaigns promoting physical activity[10], sleep[55,59], hobbies[18]. Training faculty in psychological first aid and referral pathways	Mental health literacy; positive psychology; behavioral activation models[35]
Selected prevention (at-risk groups)	Address specific risk factors	Workshops for students with financial stress (financial literacy, budgeting)[7,8,18]. Skills groups for emotional eating[23,24] or problematic internet use[20,21]. Support groups for international students, low-income students[18,51]	Cognitive-behavioral therapy; dialectical behavior therapy skills
Indicated intervention/treatment (symptomatic students)	Treat clinical symptoms	Increased access to telehealth cognitive-behavioral therapy, acceptance and commitment therapy, or unified protocol[34]. Prescription and guidance for use of evidence-based mental health apps. Collaboration with campus health services for medication management if needed	Transdiagnostic cognitive-behavioral therapy[33,34]; pharmacotherapy
Environmental/policy	Modify structural determinants	Flexible academic policies (deadline extensions, pass/fail options)[16,38,54]. Emergency funds and grants for students in financial need[18,56]. Ensuring affordable, reliable internet and suitable study spaces. Creating and subsidizing opportunities for safe social/recreational engagement[4,9,17,18]	Socioecological model; public health approach

ER: Emotion regulation.

Individual- and group-level interventions

Universities must move beyond reactive counseling to proactive, skill-based resilience building. Universal psychoeducation programs on adaptive ER (e.g., cognitive reappraisal, mindfulness, behavioral activation) should be integrated into orientation and first-year curricula[5,26,27,58]. Targeted workshops can address specific risk factors like financial literacy to combat compensatory spending[7,8], mindful eating[23,24], and sleep hygiene[55,59]. Evidence-based protocols like Unified Protocol for Transdiagnostic Treatment[34] or Mindfulness-Based Stress Reduction[27] are ideally suited to address the comorbid nature of lockdown-related distress.

Digital and scalable solutions

The need for remote access necessitates digital tools. Cognitive-behavioral therapy-based apps (Woebot, Sanvello), mindfulness apps (Headspace, Calm), and peer-support platforms can provide scalable support. However, they must be evidence-based and promoted within a supported framework, not as standalone fixes. Tele-mental health must be expanded and efforts made to reduce stigma associated with their use.

Institutional/policy-level changes

Addressing upstream determinants is crucial. Universities should adopt trauma-informed and flexible academic policies (e.g., pass/fail options, deadline flexibility) to reduce academic stress[16,38]. Financial support packages for disadvantaged students are essential[18,56]. Creating structured opportunities for virtual and safe in-person social connection[9,17,51] as well as recreational activities[4,18,60] (e.g., online game nights, outdoor fitness classes) can foster protective factors.

Public health preparedness

Future pandemic response plans must explicitly include a mental health and psychosocial support component from the outset, with clear protocols for supporting student populations, including training for faculty and staff to identify and refer students experiencing distress.

LIMITATIONS AND FUTURE RESEARCH

While Zhao et al’s study[4] provides valuable insights, several limitations highlight important directions for future research. The cross-sectional design of Zhao et al[4] limits causal inferences - a limitation common to much of the pandemic-era mental health research. Future research should employ longitudinal designs to examine the evolution of ER habits and mental health outcomes over time, particularly during extended crisis periods[22]. Incorporating objective measures, such as wearable devices to capture physical activity and sleep or ecological momentary assessments to record real-time ER strategies, would strengthen the validity of findings.

Another limitations of Zhao et al[4] is that data were collected early in the pandemic (2020-2021), which may not reflect long-term trends. As Gou et al[30] demonstrated, the allostatic load resulting from chronic stress can have lasting effects on mental health[29-32]. Research examining the persistence of lockdown-related psychological distress is crucial for understanding the pandemic’s long-term consequences[25,29,30].

While the pandemic generated a wealth of data, significant limitations in the literature must guide future work. The reliance on cross-sectional designs precludes causal claims about ER and mental health. Longitudinal studies tracking cohorts from pre- through post-pandemic are essential[14,22,29,30,61]. There is a need for more objectively measured data (e.g., actigraphy for sleep and activity, smartphone sensing for social behavior, financial transaction data for spending) to complement self-reports, reducing bias. Most research stems from the early pandemic (2020-2021); the long-term mental health trajectory of the “COVID generation” students require investigation, as the allostatic load may manifest later[25,29,30]. Additionally, future research must explore cultural variations in ER and coping; the effectiveness of collectivist vs individualist coping strategies during lockdowns is under-studied. Finally, the differential impact on marginalized subgroups (e.g., students of color, lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority students, students with disabilities) within the broader student population needs focused attention to ensure equitable interventions.

CONCLUSION

The COVID-19 pandemic served as a tragic yet instructive natural experiment, demonstrating that ER is central to mental health during large-scale, chronic stress. This review consolidates evidence that college students experienced severe psychological distress[1-4,10-16], which was strongly influenced by maladaptive ER strategies (e.g., avoidance via spending or eating)[4,7,8,17,23] vs adaptive strategies (e.g., behavioral activation through hobbies or exercise)[4,10,18,35]. Contextual factors, including socioeconomic strain[18,56] and academic pressure[16,38,54], moderated these effects. The high comorbidity of disorders[4,29,33,34] underscores the value of transdiagnostic intervention approaches. Protecting student mental health in future crises requires a proactive, multi-level strategy: Interacting ER skill-building into educational programs[5,26,27], leveraging technology to expand access to support, and reforming policies to reduce structural stressors[18,38]. Future research should employ rigorous, longitudinal, and inclusive designs to examine the long-term psychological legacy of the pandemic[25,29,30] and to advance a robust science of resilience-capable of guiding responses to future global challenges.

ACKNOWLEDGEMENTS

The authors thank all researchers whose work contributed to this review.