Learning mode, university students’ mental health, and acculturative stress – a cross-sectional study of Chinese international students in Melbourne, Australia.

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Peixin Zuo, Ann Gowing, Anurika De Silva, Harry Minas This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8042476/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Apr, 2026 Read the published version in Journal of International Students → Version 1 posted You are reading this latest preprint version Abstract Online learning was widely implemented in university teaching activities during the pandemic and remains an important component of education following cessation of pandemic-related restrictions. Although university students reported worsening mental health during the pandemic little is known about how current learning modes (in-person, hybrid and online) are associated with mental health of international students, particularly among Chinese international students (CIS). We conducted a cross-sectional online survey of 122 CIS enrolled at an Australian university between April and May 2024. Depression and anxiety symptoms were measured using the Patient Health Questionnaire (PHQ-9) scale and Generalised Anxiety Disorder Questionnaire (GAD-7) scale. Acculturative stress was assessed using the Acculturative Stress Scale for Chinese Students (ASSCS). Associations between learning mode (in-person vs. hybrid) and mental health outcomes were examined, and the potential mediating role of acculturative stress was explored. Results indicated that compared with students in the in-person learning group, those in the hybrid learning group reported higher scores for depression (geometric mean ratio (GMR) = 1.32, 95% CI: [1.05, 1.65]) and anxiety (GMR = 1.31, 95% CI: [1.03, 1.67]). Only minimal change was observed after adjusting for age, gender, financial difficulties, online learning self-efficacy, and acculturative stress. Mediation analysis showed that acculturative stress may partially account for these differences. While acculturative stress may play a role in this association, longitudinal research is required to clarify directionality and causal pathways. These findings suggest that assistance with effective acculturation could be a potentially important component of university-based mental health programs. Epidemiology School Counseling Cultural Studies Educational Psychology Online learning Hybrid learning Chinese international students Depression Anxiety Acculturative stress Figures Figure 1 Highlights Chinese international students (CIS) in the hybrid learning group reported higher scores on depression and anxiety scales than those in the in-person learning group. Acculturative stress may play a role in the association between learning mode and mental health among CIS. University-based mental health programs for international students may be strengthened by incorporating effective acculturation support as a core component. Introduction The COVID-19 pandemic has posed substantial challenges in various aspects of life worldwide (World Health Organisation [WHO] 2020 ), causing an unprecedented disruption in education, including school closures affecting an estimated 1.6 billion students globally (United Nations [UN], 2020 ). It also had a direct and substantial impact on international education. By March 2020, 142 countries had introduced border closures to restrict the movement of people and the spread of the virus (Connor, 2020 ), leading to significant declines in international student numbers in major host countries such as the United States, United Kingdom, Canada, and Australia (Hurley & Hildebrandt, 2021 ). For example, Australia hosted nearly 240,000 international students from China before the pandemic in 2019, but enrolments dropped by 25% to fewer than 180,000 in 2022 (Department of Education, 2024 ). Universities responded to the pandemic by rapidly shifting from face-to-face learning to online learning (Chen, 2023 ; Daniel, 2020 ; Gu & Li, 2022 ). Online learning, also referred to as e-learning, distance learning, remote learning, or web-based learning, enables teaching and learning via internet-supported platforms (Banson, 2022 ; Kearsley et al., 1995 ; Maddison et al., 2017 ). Online learning proved its feasibility in higher education settings, leading to a shift in the delivery of education programs more broadly (García-Morales et al., 2021 ). Many university leaders came to believe that online education brought new opportunities and institutional growth (Bayley & Yates, 2023 ). Subjects and courses continued to be delivered either fully online or in a hybrid format, supplementing traditional in-person education (Carlton, 2024 ). However, university students hold mixed views about online learning. They welcome its flexibility and accessibility (Bayley & Yates, 2023 ), but complain about having insufficient interaction with educators and peers (Khan, 2022 ; Tertiary Education Quality and Standards Agency [TEQSA], 2020 ). Concerns about the mental health of university students have grown during and after the pandemic. Multiple studies have reported worsening levels of depression and anxiety among university students (Pandya & Lodha, 2022 ; Riboldi et al., 2023 ; Zarowski et al., 2024 ). However, the relationship between online learning and students’ mental health remains unclear (Moore et al., 2022 ). A review of 45 studies by Moore et al. ( 2022 ) found that over half reported negative impacts of online learning on student mental health, one-third reported mixed impacts, and fewer than 10% reported positive impacts. However, most studies did not adequately adjust for the broader impact of the pandemic, making it difficult to disentangle the effects of learning mode itself (Moore et al., 2022 ). Compared to local students, international students at universities are more vulnerable to mental health problems (Riboldi et al., 2023 ) and have a higher likelihood of developing major depression (Russell et al., 2023 ). Their mental health is also challenged by acculturative stress. Acculturative stress refers to the stress that occurs during the process of acculturation, where an individual or a group of people from one culture are in contact with another culture (Berry, 2006 ). A clear relationship between acculturative stress and negative psychological states, such as an increased likelihood of depressive symptoms, has been identified among international students (Amlashi et al., 2024 ; Çimşir & Ünlü Kaynakçı, 2024 ). Chinese international students (CIS) experience acculturative stress due to several factors, including academic challenges, language barriers, discrimination, and limited social support, affecting their mental health (Ma et al., 2021 ; Xiong et al., 2025 ; Yan & Berliner, 2011 ; Zhao et al., 2023 ; Zuo et al., 2025 ). These factors may interact with learning mode to further influence mental health. Existing research on online learning has examined student engagement (Jarrah et al., 2025 ; Kearney et al., 2025 ), academic performance (Akpen et al., 2024 ; Chen, 2023 ), sense of belonging (Dulfer et al., 2025 ; Tang et al., 2023 ), and overall student satisfaction (Bi et al., 2023 ; Xu & Xue, 2023 ). To our knowledge, no studies have directly addressed the association between online learning and mental health in the context of CIS, nor explored whether acculturative stress might play a role in this relationship, despite CIS being the largest international student group in Australia and many other host countries (Department of Education, 2024 ). This study therefore aimed to examine the association between learning mode and mental health among CIS in Australia, along with the potential mediating role of acculturative stress. Methods Study Setting This study was conducted at a large university in Australia, between April 19th and May 19th, 2024. Ethics approval was obtained from the university’s Human Research Ethics Committee (Ref. No. 2024-27526-53340-5). Participants and Recruitment Eligible participants were CIS aged 18 years or older, enrolled at the university with a valid student visa at the time of the survey. Students were recruited through multiple channels: posters with QR codes linking to an invitation to participate in the survey were displayed across campus, advertisements with survey links were published fortnightly on the official university platform, and digital posters were circulated through student associations, clubs, and social media groups for CIS. The invitation to participate was also disseminated via WeChat groups. Survey respondents were also encouraged to share the survey link with peers. Participation was voluntary, with no incentives provided. A Plain Language Statement (PLS) was presented at the start of the survey outlining the study aims and procedures. Informed consent was obtained electronically prior to participation, and respondents who declined consent were directed to a final page containing information and resources for mental health support. Survey design The survey was developed and administered using Qualtrics XM (2024). It included six sections: demographic characteristics, online learning experiences, online learning self-efficacy (OLSE) scale, mental health, acculturation, and use of university counselling and psychological services. Four open-ended questions were included in the survey. Each item was presented in both English and Simplified Chinese. Skip logic was applied where relevant. Before launching the survey, two postgraduate students and two graduate researchers pilot tested the survey for readability, length, and logical flow. One-on-one feedback discussions with the first author followed, leading to minor amendments. The estimated completion time for the final survey was 10–12 minutes. Measures Demographics Participants were screened by asking, “Do you hold a valid student visa?” Those who responded “no” were excluded from further participation. Data were collected on age, gender, hometown, faculty, course and year level, length of stay in Australia, relationship status, sleep duration, commute time, and financial difficulties. Financial difficulties were defined as answering “yes” to either of two items: having run out of food in the past 12 months or being unable to afford medicine in the past 12 months. Learning Mode Participants were categorised as “in-person” or “hybrid” learners according to their response to the question: “Are you taking any subjects online/hybrid this semester?” Learning experiences and preferences Participants reported the number of subjects taken in one semester and the number completed in each delivery mode (fully online, hybrid, fully in-person). They rated their satisfaction with the learning modes they had experienced on a scale from 0 to 7 (0 = extremely dissatisfied, 7 = extremely satisfied), with optional free-text comments. Participants also ranked their preferred learning mode (in-person, online, hybrid) and provided further comments if desired. OLSE The 22-item Online Learning Self-Efficacy Scale (Zimmerman & Kulikowich, 2016 ) was used to measure the perceived self-efficacy related to online learning. This scale has been validated in university student samples in the United States (Zimmerman & Kulikowich, 2016 ), and preliminarily validated in Turkey, Iran, and China (Ahmadipour, 2022 ; Ma et al., 2024 ; Yavuzalp & Bahçivan, 2020 ). It contains three subscales: Learning, Time Management, and Technology, with items rated from 1 (“not confident”) to 6 (“very confident”). Example items include: “Navigate online course materials efficiently” and “Use the library’s online resources efficiently”. Total score ranges from 22 to 132, with higher scores indicating greater online learning self-efficacy. Acculturative stress The 32-item Acculturative Stress Scale for Chinese Students (ASSCS) (Bai, 2016 ) was used to measure acculturative stress. It contains 32 items that form five subscales: Language Insufficiency, Social Isolation, Perceived Discrimination, Academic Pressure, and Guilt Towards Family. Each item is rated from 1 to 7, resulting in a total score of 32–224, with higher scores indicating greater stress. This scale was developed and validated among a sample of CIS in the United States (Bai, 2016 ). Depression The 9-item Patient Health Questionnaire (PHQ-9) (Spitzer et al., 1999 ) was used to assess depressive symptoms. Each item is rated from 0 to 3, yielding a total score of 0–27, with higher scores indicating greater severity of depression. The PHQ-9 has been validated among Chinese-speaking populations in the United States and university students in China (Yin et al., 2022 ; Zhang et al., 2013 ). Anxiety The 7-item Generalised Anxiety Disorder Questionnaire (GAD-7) (Spitzer et al., 2006 ) was used to assess anxiety symptoms. Each item is rated from 0 to 3, resulting in a total score of 0–21, with higher scores indicating greater anxiety. The GAD-7 has been validated among Chinese university students (Zhang et al., 2021 ). Sample Size To detect a minimal clinically important difference of 1 unit in depression/anxiety scores between hybrid learning and in-person learning (Bi et al., 2023 ; Han et al., 2013 ), assuming a standard deviation of 3.8 units for depression/anxiety equal across both groups (Han et al., 2013 ), for 80% power, and a two-sided significance level of 0.025 (conservative Bonferroni adjustment for two primary outcomes), with equal group sizes, and allowing for 10% missing data, a total sample size of 614 participants is required. Statistical Analysis Participant characteristics were summarised by learning mode, using mean (standard deviation, SD) for symmetrically distributed numerical data, median (interquartile range, IQR; 25th -75th percentile) for non-symmetrically distributed numerical data, and frequency (percentage) for categorical data. The primary analysis was guided by Fig. 1 a, developed from existing literature identifying age, gender, financial difficulty, and OLSE as potential confounders of the association between learning mode and mental health (Ke et al., 2023 ; Wang et al., 2022 ). First, unadjusted linear regression models were fitted using complete case data to explore associations between learning mode and each of the mental health outcomes, depression and anxiety. Models were then adjusted for age, gender, financial difficulty, and OLSE, and subsequently further adjusted for acculturative stress. We also explored unadjusted associations between acculturative stress and mental health outcomes. Due to the non-symmetrical distribution of the data, depression and anxiety were log-transformed prior to the analysis. An exploratory causal mediation analysis, guided by Fig. 1 b, was conducted using complete case data to explore whether acculturative stress mediated the association between learning mode and mental health outcomes, adjusting for age, gender, financial difficulty, and OLSE. Given the cross-sectional design and exploratory nature of this study, no causal inferences are drawn from these analyses. Missing data in the mental health outcomes, acculturative stress, and OLSE were handled using multiple imputation by chained equations (MICE) with linear regression models. The imputation model included all the variables in the analysis model, as well as participant characteristics that appeared to differ between those with and without missing data, including length of stay, relationship status, and commute time (see Supplementary Materials). Thirty imputations were performed to account for approximately 26% missingness. Imputed datasets were compared with the complete-case data using density plots. Geometric mean ratios (GMR), corresponding two-sided 95% confidence intervals (CIs), and p-values were obtained from the models discussed above. Standard diagnostic plots were used to check model assumptions. All statistical analyses were performed in STATA 18 (StataCorp., 2023). Results Descriptive data Of the 187 students who entered the survey, 64 were excluded: non-consent (n = 4), immediate withdrawal after consent (n = 24), no valid student visa (n = 8), withdrawal after the visa question (n = 13), and no response to the learning mode question (n = 15). One participant self-identified as non-binary; due to small numbers, gender was dichotomised as male/female and this case was excluded. A total of 122 participants were included in the analysis. Descriptive summaries of their demographic characteristics, learning mode preferences, OLSE, and acculturative stress are shown in Table 1 ; mental health outcomes on depression and anxiety are summarised in Table 2 . Demographics Of the 122 participants, 73 (59.8%) were in the in-person learning group and 49 (40.2%) in the hybrid group. The mean age was 23.0 years (SD = 2.1 years). Most participants were female (n = 97, 79.5%), from Eastern China (n = 71, 58.2%), pursuing a master’s degree (n = 95, 77.9%), in their first or second year (n = 109, 89.3%), single (n = 83, 68.0%), and commuting less than 30 minutes to campus (n = 94, 77.0%). Learning Mode Preference and OLSE Most students preferred in-person learning (n = 71, 63.4%), followed by hybrid (n = 30, 26.8%), and online learning (n = 11, 9.8%). The overall median OLSE score was 99 (IQR 87–108). Students in the hybrid group reported lower in OLSE scores (median = 96, IQR 87-105.5) than those in the in-person group (median = 102.5, IQR 88–110). Table 1 Demographic Information Table 1 Total (n = 122) In person (n = 73) Hybrid (n = 49) Age, mean (SD), yrs 23.0 (2.1) 23.2 (2.3) 22.7 (1.9) Gender, n (%) Male 25 (20.5%) 19 (26.0%) 6 (12.2%) Female 97 (79.5%) 54 (74.0%) 43 (87.8%) Hometown, n (%) East China 71 (58.2%) 44 (60.3%) 27 (55.1%) Central China 21(17.2%) 12 (16.4%) 9 (18.4%) West China 18 (14.8%) 11 (15.1%) 7 (14.3%) Northeast China 10 (8.2%) 4 (5.5%) 6 (12.2%) SAR/Taiwan, China 2 (1.6%) 2 (2.7%) 0 (0.0%) Faculty, n (%) Architecture, Building and Planning 4 (3.3%) 4 (5.5%) 0 (0.0%) Arts 32 (26.2%) 24 (32.9%) 8 (16.3%) Business and Economics 14 (11.5%) 10 (13.7%) 4 (8.2%) Education 24 (19.7%) 13 (17.8%) 11 (22.4%) Engineering and Information Technology 9 (7.4%) 6 (8.2%) 3 (6.1%) Fine Arts and Music 2 (1.6%) 2 (2.7%) 0 (0.0%) Law 3 (2.5%) 3 (4.1%) 0 (0.0%) Medicine, Dentistry and Health Sciences 16 (13.1%) 4 (5.5%) 12 (24.5%) Science 17 (13.8%) 7 (9.6%) 10 (20.4%) Other 1 (0.8%) 0 (0.0%) 1 (2.0%) Course level, n (%) Undergraduate 25 (20.5%) 14 (19.2%) 11 (22.4%) Master 95 (77.9%) 58 (79.5%) 37 (75.5%) Graduate Researcher (PhD) 2 (1.6%) 1 (1.4%) 1 (2.0%) Year, n (%) First year 58 (47.5%) 31 (42.5%) 27 (55.1%) Second year 51 (41.8%) 33 (45.2%) 18 (36.7%) Third year 11 (9.0%) 7 (9.6%) 4 (8.2%) Fourth year 1 (0.8%) 1 (1.4%) 0 (0.0%) Fifth year and above 1 (0.8%) 1 (1.4%) 0 (0.0%) Length of stay, n (%) less than 3 months 15 (12.3%) 8 (11.0%) 7 (14.3%) 3–6 months 18 (14.8%) 8 (11.0%) 10 (20.4%) 6–12 months 14 (11.5%) 10 (13.7%) 4 (8.2%) 1–3 years 46 (37.7%) 28 (38.4%) 18 (36.7%) more than 3 years 29 (23.8%) 19 (26.0%) 10 (20.4%) Relationship, n (%) Single 83 (68.0%) 47 (64.4%) 36 (73.5%) Dating 34 (27.9%) 24 (32.9%) 10 (20.4%) Married/De facto 3 (2.5%) 1 (1.4%) 2 (4.1%) Other 2 (1.6%) 1 (1.4%) 1 (2.0%) Sleep, mean (SD), hours 7.1 (1.1) 7.2 (1.0) 7.1 (1.2) Commute time, n (%) less than 30 mins 94 (77.0%) 57 (78.1%) 37 (75.5%) more than 30 mins 28 (23.0%) 16 (21.9%) 12 (24.5%) Ran Out of Food, n (%) Yes 14 (11.5%) 10 (13.7%) 4 (8.2%) No 108 (88.5%) 63 (86.3%) 45 (91.8%) Couldn’t Afford Medicine, n (%) Yes 10 (8.2%) 7 (9.6%) 3 (6.1%) No 112 (91.8%) 66 (90.4%) 46 (93.9%) Favourite mode, n (%)* In-person 71 (63.4%) 49 (72.1%) 22 (50.0%) Online 11 (9.8%) 4 (5.9%) 7 (15.9%) Hybrid 30 (26.8%) 15 (22.1%) 15 (34.1%) OLSE score, median (IQR)* 99 (87–108) 102.5 (88–110) 96 (87-105.5) Acculturative stress score, median (IQR)* 88 (67–112) 83 (63–107) 101 (68–121) Abbreviations: IQR: Interquartile range (25th–75th percentile); SD: Standard deviation. Ranges: OLSE scores range from 22 to 132, with higher scores indicating a higher self-efficacy in online learning. Acculturative stress scores range from 32 to 224, with higher scores indicating a higher level of acculturative stress. *Missing data: Favourite mode: In person 5 (7%), Hybrid 5 (10%); OLSE: In person 19 (26%), Hybrid 9 (18%); Acculturative stress: In person 15 (21%), Hybrid 6 (12%) Acculturative Stress Overall median acculturative stress was 88 (IQR 67–112). Scores were higher and more variable among hybrid learners (median = 101, IQR 68–121) compared with in-person learners (median = 83, IQR 63–107). Depression and Anxiety Symptoms On average, students reported mild depressive symptoms (mean = 8.1, SD = 5.7). Using a PHQ-9 cut-off of 10, thirty-four (32.4%) students met criteria for moderate to severe depression. Hybrid learners reported greater symptoms (mean = 9.2, SD = 5.3) compared to in-person learners (mean = 7.3, SD = 5.8). Anxiety scores followed a similar pattern. The mean GAD-7 score was 7.5 (SD = 5.3), reflecting mild anxiety, with 31 (29.8%) students classified as moderate to severe. Hybrid learners reported slightly greater anxiety (mean = 8.6, SD = 5.2) than in-person learners (mean = 6.7, SD = 5.3). Table 2 Descriptive Statistics of Outcome Measures Table 2 Total (n = 122) In person (n = 73) Hybrid (n = 49) Depression score, median (IQR) 7 (4–11) 6 (4–9) 8 (5–12) Depression score, mean (SD) 8.1 (5.7) 7.3 (5.8) 9.2 (5.3) Depressive symptoms, n (%) Minimal (0–4) 27 (25.7%) 19 (30.6%) 8 (18.6%) Mild (5–9) 44 (41.9%) 28 (45.2%) 16 (37.2%) Moderate (10–14) 20 (19.0%) 7 (11.3%) 13 (30.2%) Moderately severe (15–19) 9 (8.6%) 5 (8.1%) 4 (9.3%) Severe (20–27) 5 (4.8%) 3 (4.8%) 2 (4.7%) Anxiety score, median (IQR) 7 (3–11) 6 (2–10) 7 (5–12) Anxiety score, mean (SD) 7.5 (5.3) 6.7 (5.3) 8.6 (5.2) Anxiety symptoms, n (%) Minimal (0–4) 29 (27.9%) 22 (36.1%) 7 (16.3%) Mild (5–9) 44 (42.3%) 23 (37.7%) 21 (48.8%) Moderate (10–14) 21(20.2%) 12 (19.7%) 9 (20.9%) Severe (15–21) 10 (9.6%) 4 (6.6%) 6 (14.0%) Abbreviations: IQR: Interquartile range (25th–75th percentile); SD: Standard deviation. Ranges: Depression scores range from 0 to 27, with higher scores indicating a higher level of depression. Anxiety scores range from 0 to 21, with higher scores indicating a higher level of anxiety. Missing data: Depression: In person 11 (15%), Hybrid 6 (12%); Anxiety: In person 12 (16%), Hybrid 6 (12%). Learning Mode and Depression As shown in Table 3 , the unadjusted regression model indicated a 1.32-fold (95% CI: [1.05, 1.65], p = 0.018) change in geometric mean depression scores for the hybrid group compared to the in-person group. Hardly any changes were observed in the association after adjusting for age, gender, financial difficulties, and OLSE (GMR = 1.33, 95% CI: [1.04, 1.71], p = 0.021). After further adjusting for acculturative stress, the association slightly attenuated (GMR = 1.17, 95% CI: [0.93, 1.48], p = 0.175). A 1-unit increase in acculturative stress was associated with a 1.01-fold (95% CI: [1.01,1.01], p < 0.001) relative change in geometric mean depression scores. Adjusted exploratory mediation analysis (Table 4 ) suggested that the total effect of learning mode on depression (GMR = 1.35, 95% CI: [1.06,1.72], p = 0.014) comprised a direct effect (GMR = 1.17, 95% CI: [0.95,1.45], p = 0.141) and an indirect effect via acculturative stress (GMR = 1.15, 95% CI: [1.01,1.32], p = 0.037). Learning Modes and Anxiety The unadjusted regression model indicated a 1.31-fold (95% CI: [1.03, 1.67], p = 0.028) change in geometric mean anxiety scores for hybrid group compared to in-person group. Hardly any changes were observed in the association after adjusting for age, gender, financial difficulties, and OLSE (GMR = 1.32, 95% CI: [1.02, 1.71], p = 0.033). Further adjusting for acculturative stress slightly attenuated the effect (GMR = 1.10, 95% CI: [0.88, 1.36], p = 0.397). Every 1-unit increase in acculturative stress was associated with a 1.01-fold (95% CI: [1.01,1.01], p < 0.001) relative change in geometric mean anxiety scores. In adjusted exploratory mediation analysis, the total effect of learning mode on anxiety (GMR = 1.31, 95% CI: [1.03,1.67], p = 0.026) included a direct effect (GMR = 1.10, 95% CI: [0.92,1.31], p = 0.307) and an indirect effect via acculturative stress (GMR = 1.20, 95% CI: [1.03,1.39], p = 0.016). Negligible differences were observed between adjusted and unadjusted models (see Table 4 ). Findings were consistent in sensitivity analyses using multiple imputed data (see Supplementary Materials). Table 3 Regression Results for Learning Modes on Depression and Anxiety Table 3 Log transformation output ∆ Depression Univariable Geometric mean ratio 95% CI p-value Learning mode In-person Reference - Hybrid 1.32 (1.05 to 1.65) 0.018 Multivariable – Model 1* Learning mode In-person Reference - Hybrid 1.33 (1.04 to 1.71) 0.021 Multivariable – Model 2** Learning mode In-person Reference - Hybrid 1.17 (0.93 to 1.48) 0.175 Anxiety Univariable Geometric mean ratio 95% CI p-value Learning mode In-person Reference - Hybrid 1.31 (1.03 to 1.67) 0.028 Multivariable – Model 1* Learning mode In-person Reference - Hybrid 1.32 (1.02 to 1.71) 0.033 Multivariable – Model 2** Learning mode In-person Reference - Hybrid 1.10 (0.88 to 1.36) 0.397 * Adjusted for age, gender, OLSE, and financial difficulties. ** Further adjusted for acculturative stress based on Model 1*. ∆ Geometric mean ratio, 95% confidence interval, and p-value are reported. Table 4 Exploratory Mediation Analysis of Acculturative Stress in the Relationship Between Learning Modes and Depression and Anxiety Table 4 Log transformation output ∆ Depression Unadjusted Geometric mean ratio 95% CI p-value Indirect effect 1.15 (1.01 to 1.29) 0.029 Direct effect 1.16 (0.96 to 1.40) 0.134 Total effect 1.32 (1.07 to 1.64) 0.010 Adjusted* Geometric mean ratio 95% CI p-value Indirect effect 1.15 (1.01 to 1.32) 0.037 Direct effect 1.17 (0.95 to 1.45) 0.141 Total effect 1.35 (1.06 to 1.72) 0.014 Anxiety Unadjusted Geometric mean ratio 95% CI p-value Indirect effect 1.17 (1.03 to 1.34) 0.016 Direct effect 1.09 (0.90 to 1.31) 0.386 Total effect 1.27 (1.01 to 1.60) 0.037 Adjusted* Geometric mean ratio 95% CI p-value Indirect effect 1.20 (1.03 to 1.39) 0.016 Direct effect 1.10 (0.92 to 1.31) 0.307 Total effect 1.31 (1.03 to 1.67) 0.026 * Adjusted for age, gender, OLSE, and financial difficulties. ∆ Geometric mean ratio, 95% confidence interval, and p-value are reported. Discussion Learning mode preferences The in-person mode is the most preferred learning mode (n = 71, 63.4%), followed by the hybrid mode (n = 30, 26.8%), and online mode is the least preferred, with only 11 students (9.8%) ranking it in the first place (see Table 1 ). Note that participants in the hybrid group reported lower scores on OLSE compared to those in the in-person group. One possible explanation is that only students who had experienced online learning could accurately assess the technology challenges they encountered, rather than imagining their self-efficacy. Rates of Depression and Anxiety In Ke et al. ( 2023 )’s study, PHQ-2 (Kroenke et al., 2003 ) and GAD-2 (Kroenke et al., 2007 ) were used to measure depression and anxiety during the pandemic in 2020 among CIS at the same university as in our study. A cut-off point of three or more was applied, and 43.8% and 45.7% of the CIS were reported to have depression and anxiety, respectively. According to the study of Ke and colleagues, these percentages were nearly double the rates reported in 2019 (22.1% vs 24.7%). To make a comparison, we extracted the items of PHQ-2 from PHQ-9, and those of GAD-2 from GAD-7, and then applied the same cut-off point. Among the CIS in our sample, 23.8% reported depression, and 39.0% reported anxiety (see Table 5 ). The percentage of depression in 2024 is similar to what it was before COVID (23.8% vs 22.1%). However, the percentage of anxiety is closer to what it was during the pandemic (39.0% vs 45.7%). The reason for this disparity is unclear, since our data were collected between April and May 2024, a similar collection window compared to April-June 2019 in the previous study. Table 5 Comparison Between Studies Data collection Depression (%) Anxiety (%) Source 2019, Apr-Jun 22.1% 24.7% Ke et al., 2023 2020, Sept-Oct 43.8% 45.7% Ke et al., 2023 2024, Apr-May 23.8% 39.0% This study CIS reported a higher percentage of moderate to severe depression than other international students (32.4% vs 25.9%) and a higher proportion of moderate to severe anxiety than other international students (29.8% vs 19.8%) in a study by Sanci et al. ( 2022 ). Possible reasons might be that, first, international students from other countries, like India, might have a better English level than CIS, making it easier for them to adapt to the new English environment of learning and living. Second, CIS very frequently experience sustained pressure to achieve high academic performance and may be more likely than other international students to experience negative emotions due to academic-related stress and to develop mental health problems (Zhao et al., 2015; Zhou et al., 2023 ). Learning mode, acculturation stress and mental health In this exploratory study, we observed lower levels of depression and anxiety among CIS in the in-person learning group compared with those in the hybrid learning group. The regression analysis demonstrated that adjusting for acculturative stress resulted in significant attenuation of the associations between learning mode and mental health. Moreover, mediation analysis found that acculturative stress mediated the association between learning mode and mental health outcomes of CIS. Our findings are consistent with existing literature that acculturative stress is positively associated with mental health problems among international students and immigrants worldwide (Amlashi et al., 2024 ; Lee et al., 2004 ; Sirin et al., 2013 ). Although CIS in the hybrid learning group reported higher scores on depression and anxiety scales than those in the in-person learning group, our findings suggest that learning mode does not have any significant association with the mental health of CIS after adjusting for acculturative stress. As previously mentioned, a review of studies on mental health and online learning pointed out that most studies did not control for the pandemic effect (Moore et al., 2022 ). What appeared to be related to online learning may, in fact, have been due to pandemic-related factors, including the increased social isolation as a product of the widespread quarantine measures that were imposed. Results of mediation analysis also suggested that the association between learning mode and depression and anxiety may operate primarily through acculturative stress. The ASSCS we used has five subscales: Language Insufficiency, Social Isolation, Perceived Discrimination, Academic Pressure, and Guilt Towards Family (Bai, 2016 ). Among these, some factors are found to be increased during online learning, for example, CIS reported an increased level of academic stress when learning online, as they tended not to answer questions via the microphone or type in chat due to their insufficient English skills in speaking and writing (Chang et al., 2021 ; Wang, 2021 ). Online classes also limited students’ opportunities to interact with peers in social settings (Adachi & Tran, 2022 ), and CIS perceived discrimination during group activities online (Nam et al., 2021 ). However, restricted by the small sample size, our study was unable to conduct more detailed analyses to adjust these variables separately. Furthermore, given the cross-sectional nature of this exploratory study, no causal inferences could be drawn from our analyses. Implications Observations from our study underscore the need for universities to implement mental health programs that specifically address the acculturative challenges faced by CIS, particularly in the context of online learning. In addition to providing academic support and increasing opportunities for social interaction on campus, universities should design targeted sessions aimed at reducing acculturative stress. Involving student representatives in the co-design of such programs may further enhance cultural specificity and effectiveness. To deepen our understanding of the preliminary results from this study, future research may benefit from being conducted at the institutional level to enable access to a larger sample, thereby increasing statistical power and enhancing the reliability of the findings. Studies with longitudinal designs could help examine potential causal relationships, both between online learning and acculturative stress, and between acculturative stress and mental health. Moreover, qualitative approaches, such as interviews and focus groups, could generate richer and more nuanced insights into the interplay between online learning, acculturation, and mental health, based on the lived experiences of CIS. Strengths and Limitations This study has several strengths. First, it focused specifically on CIS, the largest international student cohort in Australia, rather than treating international students as a homogeneous group. This allowed us to capture culturally specific experiences. Second, data were collected in 2024 when pandemic restrictions had ended. Our study has provided insights into learning mode and mental health in a context different from what it had been two to three years ago, and students had more autonomy in their study choices. Third, we applied robust statistical methods, including multiple imputation to address missing data. Lastly, we also used validated instruments to measure variables such as acculturative stress and OLSES. Several limitations must also be acknowledged. The voluntary nature of participation may have introduced selection bias, with students experiencing mental health difficulties potentially more likely to respond. The sample size recruited (n = 122) fell short of was required (n = 614), limiting statistical power and precision. Our findings should therefore be considered exploratory. Furthermore, the cross-sectional design precludes causal inference; mediation results in particular must be interpreted with caution. Finally, as the study was conducted at a single metropolitan, research-intensive university, the findings may not be generalisable to other settings or student populations. Conclusion Our study examined the relationship between learning mode and mental health outcomes among CIS. Results indicated that participants in the hybrid learning group self-reported higher scores of depression and anxiety compared to participants in the in-person learning group. Based on mediation analysis, acculturative stress significantly mediated the association between learning mode and depression and anxiety among CIS. Our exploratory study has shed some light on the interaction between learning mode and the mental health of university students, filling a gap in this understudied area. Findings could be used by professionals in education, cross-cultural, and mental health settings to develop targeted programs supporting the psychological wellbeing of CIS. Future research could adopt longitudinal designs and qualitative approaches, to provide a deeper and more nuanced understanding of acculturative stress and the mental health of CIS in online learning settings. Abbreviations ASSCS – Acculturative Stress Scale for Chinese Students CI – Confidence interval CIS – Chinese international students COVID-19 – Coronavirus disease 2019 GAD-2 – Generalised Anxiety Disorder Questionnaire 2 items GAD-7 – Generalised Anxiety Disorder Questionnaire 7 items GMR – Geometric mean ratio IQR – Interquartile range OLSE – Online learning self-efficacy PHQ-2 – Patient Health Questionnaire 2 items PHQ-9 – Patient Health Questionnaire 9 items PLS – Plain Language Statement SD – Standard deviation Declarations Data statement The data that support the findings of this study are available from the University of Melbourne, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of the Human Ethics Committee of the University of Melbourne. Competing interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' contributions All authors were involved in conceptualising the study and designing the methodology. PZ collected data and analysed it with the help of ADS. PZ drafted the manuscript. HM, AG, and ADS supervised the project, provided critical feedback and substantially revised the manuscript. Acknowledgements We would like to thank all the student participants who generously shared their time and information by completing the online survey. We also sincerely appreciate the support provided by the university platforms and various student clubs that helped us distribute the questionnaire. References Adachi, C., & Tran, L. (2022). International students are back on campus, but does that spell the end of digital learning? Here’s why it shouldn’t. 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05:43:27","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":185277,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8042476/v1/74a8a9648b8ce72c1e4dcb19.html"},{"id":95529513,"identity":"a5cf1262-7000-4b6f-8854-e510c31a66bf","added_by":"auto","created_at":"2025-11-10 10:17:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":60819,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation Between Learning Mode and Mental Health Outcomes\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8042476/v1/b5be17184943e5180ed8e008.png"},{"id":107705234,"identity":"14d48bff-f504-4943-849c-bfec3992fe93","added_by":"auto","created_at":"2026-04-24 09:09:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":708990,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8042476/v1/7a19f2f0-3f2e-45d0-8cd6-0fc4001a0e24.pdf"},{"id":95504394,"identity":"00406a04-6a5b-4bca-be2d-5aae27646061","added_by":"auto","created_at":"2025-11-10 05:43:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":47399,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8042476/v1/4d16099bc7cf103e040916bb.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eLearning mode, university students’ mental health, and acculturative stress – a cross-sectional study of Chinese international students in Melbourne, Australia.\u003c/p\u003e","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eChinese international students (CIS) in the hybrid learning group reported higher scores on depression and anxiety scales than those in the in-person learning group.\u003c/li\u003e\n \u003cli\u003eAcculturative stress may play a role in the association between learning mode and mental health among CIS.\u003c/li\u003e\n \u003cli\u003eUniversity-based mental health programs for international students may be strengthened by incorporating effective acculturation support as a core component.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe COVID-19 pandemic has posed substantial challenges in various aspects of life worldwide (World Health Organisation [WHO] \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), causing an unprecedented disruption in education, including school closures affecting an estimated 1.6\u0026nbsp;billion students globally (United Nations [UN], \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It also had a direct and substantial impact on international education. By March 2020, 142 countries had introduced border closures to restrict the movement of people and the spread of the virus (Connor, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), leading to significant declines in international student numbers in major host countries such as the United States, United Kingdom, Canada, and Australia (Hurley \u0026amp; Hildebrandt, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For example, Australia hosted nearly 240,000 international students from China before the pandemic in 2019, but enrolments dropped by 25% to fewer than 180,000 in 2022 (Department of Education, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUniversities responded to the pandemic by rapidly shifting from face-to-face learning to online learning (Chen, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Daniel, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Gu \u0026amp; Li, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Online learning, also referred to as e-learning, distance learning, remote learning, or web-based learning, enables teaching and learning via internet-supported platforms (Banson, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kearsley et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Maddison et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Online learning proved its feasibility in higher education settings, leading to a shift in the delivery of education programs more broadly (Garc\u0026iacute;a-Morales et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Many university leaders came to believe that online education brought new opportunities and institutional growth (Bayley \u0026amp; Yates, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Subjects and courses continued to be delivered either fully online or in a hybrid format, supplementing traditional in-person education (Carlton, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, university students hold mixed views about online learning. They welcome its flexibility and accessibility (Bayley \u0026amp; Yates, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), but complain about having insufficient interaction with educators and peers (Khan, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tertiary Education Quality and Standards Agency [TEQSA], \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConcerns about the mental health of university students have grown during and after the pandemic. Multiple studies have reported worsening levels of depression and anxiety among university students (Pandya \u0026amp; Lodha, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Riboldi et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zarowski et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, the relationship between online learning and students\u0026rsquo; mental health remains unclear (Moore et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A review of 45 studies by Moore et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found that over half reported negative impacts of online learning on student mental health, one-third reported mixed impacts, and fewer than 10% reported positive impacts. However, most studies did not adequately adjust for the broader impact of the pandemic, making it difficult to disentangle the effects of learning mode itself (Moore et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCompared to local students, international students at universities are more vulnerable to mental health problems (Riboldi et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and have a higher likelihood of developing major depression (Russell et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Their mental health is also challenged by acculturative stress. Acculturative stress refers to the stress that occurs during the process of acculturation, where an individual or a group of people from one culture are in contact with another culture (Berry, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). A clear relationship between acculturative stress and negative psychological states, such as an increased likelihood of depressive symptoms, has been identified among international students (Amlashi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; \u0026Ccedil;imşir \u0026amp; \u0026Uuml;nl\u0026uuml; Kaynak\u0026ccedil;ı, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Chinese international students (CIS) experience acculturative stress due to several factors, including academic challenges, language barriers, discrimination, and limited social support, affecting their mental health (Ma et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xiong et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Yan \u0026amp; Berliner, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Zhao et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zuo et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These factors may interact with learning mode to further influence mental health.\u003c/p\u003e\u003cp\u003eExisting research on online learning has examined student engagement (Jarrah et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kearney et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), academic performance (Akpen et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Chen, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), sense of belonging (Dulfer et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Tang et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and overall student satisfaction (Bi et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xu \u0026amp; Xue, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To our knowledge, no studies have directly addressed the association between online learning and mental health in the context of CIS, nor explored whether acculturative stress might play a role in this relationship, despite CIS being the largest international student group in Australia and many other host countries (Department of Education, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This study therefore aimed to examine the association between learning mode and mental health among CIS in Australia, along with the potential mediating role of acculturative stress.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Setting\u003c/h2\u003e\u003cp\u003eThis study was conducted at a large university in Australia, between April 19th and May 19th, 2024. Ethics approval was obtained from the university\u0026rsquo;s Human Research Ethics Committee (Ref. No. 2024-27526-53340-5).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants and Recruitment\u003c/h3\u003e\n\u003cp\u003eEligible participants were CIS aged 18 years or older, enrolled at the university with a valid student visa at the time of the survey. Students were recruited through multiple channels: posters with QR codes linking to an invitation to participate in the survey were displayed across campus, advertisements with survey links were published fortnightly on the official university platform, and digital posters were circulated through student associations, clubs, and social media groups for CIS. The invitation to participate was also disseminated via WeChat groups. Survey respondents were also encouraged to share the survey link with peers. Participation was voluntary, with no incentives provided. A Plain Language Statement (PLS) was presented at the start of the survey outlining the study aims and procedures. Informed consent was obtained electronically prior to participation, and respondents who declined consent were directed to a final page containing information and resources for mental health support.\u003c/p\u003e\n\u003ch3\u003eSurvey design\u003c/h3\u003e\n\u003cp\u003eThe survey was developed and administered using Qualtrics XM (2024). It included six sections: demographic characteristics, online learning experiences, online learning self-efficacy (OLSE) scale, mental health, acculturation, and use of university counselling and psychological services. Four open-ended questions were included in the survey. Each item was presented in both English and Simplified Chinese. Skip logic was applied where relevant. Before launching the survey, two postgraduate students and two graduate researchers pilot tested the survey for readability, length, and logical flow. One-on-one feedback discussions with the first author followed, leading to minor amendments. The estimated completion time for the final survey was 10\u0026ndash;12 minutes.\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eDemographics\u003c/h2\u003e\u003cp\u003eParticipants were screened by asking, \u0026ldquo;Do you hold a valid student visa?\u0026rdquo; Those who responded \u0026ldquo;no\u0026rdquo; were excluded from further participation. Data were collected on age, gender, hometown, faculty, course and year level, length of stay in Australia, relationship status, sleep duration, commute time, and financial difficulties. Financial difficulties were defined as answering \u0026ldquo;yes\u0026rdquo; to either of two items: having run out of food in the past 12 months or being unable to afford medicine in the past 12 months.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eLearning Mode\u003c/h2\u003e\u003cp\u003eParticipants were categorised as \u0026ldquo;in-person\u0026rdquo; or \u0026ldquo;hybrid\u0026rdquo; learners according to their response to the question: \u003cem\u003e\u0026ldquo;Are you taking any subjects online/hybrid this semester?\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eLearning experiences and preferences\u003c/h3\u003e\n\u003cp\u003eParticipants reported the number of subjects taken in one semester and the number completed in each delivery mode (fully online, hybrid, fully in-person). They rated their satisfaction with the learning modes they had experienced on a scale from 0 to 7 (0\u0026thinsp;=\u0026thinsp;extremely dissatisfied, 7\u0026thinsp;=\u0026thinsp;extremely satisfied), with optional free-text comments. Participants also ranked their preferred learning mode (in-person, online, hybrid) and provided further comments if desired.\u003c/p\u003e\n\u003ch3\u003eOLSE\u003c/h3\u003e\n\u003cp\u003eThe 22-item Online Learning Self-Efficacy Scale (Zimmerman \u0026amp; Kulikowich, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) was used to measure the perceived self-efficacy related to online learning. This scale has been validated in university student samples in the United States (Zimmerman \u0026amp; Kulikowich, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and preliminarily validated in Turkey, Iran, and China (Ahmadipour, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ma et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yavuzalp \u0026amp; Bah\u0026ccedil;ivan, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It contains three subscales: Learning, Time Management, and Technology, with items rated from 1 (\u0026ldquo;not confident\u0026rdquo;) to 6 (\u0026ldquo;very confident\u0026rdquo;). Example items include: \u0026ldquo;Navigate online course materials efficiently\u0026rdquo; and \u0026ldquo;Use the library\u0026rsquo;s online resources efficiently\u0026rdquo;. Total score ranges from 22 to 132, with higher scores indicating greater online learning self-efficacy.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAcculturative stress\u003c/h2\u003e\u003cp\u003eThe 32-item Acculturative Stress Scale for Chinese Students (ASSCS) (Bai, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) was used to measure acculturative stress. It contains 32 items that form five subscales: Language Insufficiency, Social Isolation, Perceived Discrimination, Academic Pressure, and Guilt Towards Family. Each item is rated from 1 to 7, resulting in a total score of 32\u0026ndash;224, with higher scores indicating greater stress. This scale was developed and validated among a sample of CIS in the United States (Bai, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eDepression\u003c/h2\u003e\u003cp\u003eThe 9-item Patient Health Questionnaire (PHQ-9) (Spitzer et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) was used to assess depressive symptoms. Each item is rated from 0 to 3, yielding a total score of 0\u0026ndash;27, with higher scores indicating greater severity of depression. The PHQ-9 has been validated among Chinese-speaking populations in the United States and university students in China (Yin et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eAnxiety\u003c/h2\u003e\u003cp\u003eThe 7-item Generalised Anxiety Disorder Questionnaire (GAD-7) (Spitzer et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) was used to assess anxiety symptoms. Each item is rated from 0 to 3, resulting in a total score of 0\u0026ndash;21, with higher scores indicating greater anxiety. The GAD-7 has been validated among Chinese university students (Zhang et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eSample Size\u003c/h2\u003e\u003cp\u003eTo detect a minimal clinically important difference of 1 unit in depression/anxiety scores between hybrid learning and in-person learning (Bi et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Han et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), assuming a standard deviation of 3.8 units for depression/anxiety equal across both groups (Han et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), for 80% power, and a two-sided significance level of 0.025 (conservative Bonferroni adjustment for two primary outcomes), with equal group sizes, and allowing for 10% missing data, a total sample size of 614 participants is required.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eParticipant characteristics were summarised by learning mode, using mean (standard deviation, SD) for symmetrically distributed numerical data, median (interquartile range, IQR; 25th -75th percentile) for non-symmetrically distributed numerical data, and frequency (percentage) for categorical data.\u003c/p\u003e\u003cp\u003eThe primary analysis was guided by Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, developed from existing literature identifying age, gender, financial difficulty, and OLSE as potential confounders of the association between learning mode and mental health (Ke et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). First, unadjusted linear regression models were fitted using complete case data to explore associations between learning mode and each of the mental health outcomes, depression and anxiety. Models were then adjusted for age, gender, financial difficulty, and OLSE, and subsequently further adjusted for acculturative stress. We also explored unadjusted associations between acculturative stress and mental health outcomes. Due to the non-symmetrical distribution of the data, depression and anxiety were log-transformed prior to the analysis. An exploratory causal mediation analysis, guided by Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, was conducted using complete case data to explore whether acculturative stress mediated the association between learning mode and mental health outcomes, adjusting for age, gender, financial difficulty, and OLSE. Given the cross-sectional design and exploratory nature of this study, no causal inferences are drawn from these analyses.\u003c/p\u003e\u003cp\u003eMissing data in the mental health outcomes, acculturative stress, and OLSE were handled using multiple imputation by chained equations (MICE) with linear regression models. The imputation model included all the variables in the analysis model, as well as participant characteristics that appeared to differ between those with and without missing data, including length of stay, relationship status, and commute time (see Supplementary Materials). Thirty imputations were performed to account for approximately 26% missingness. Imputed datasets were compared with the complete-case data using density plots.\u003c/p\u003e\u003cp\u003eGeometric mean ratios (GMR), corresponding two-sided 95% confidence intervals (CIs), and p-values were obtained from the models discussed above. Standard diagnostic plots were used to check model assumptions. All statistical analyses were performed in STATA 18 (StataCorp., 2023).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eDescriptive data\u003c/h2\u003e\u003cp\u003eOf the 187 students who entered the survey, 64 were excluded: non-consent (n\u0026thinsp;=\u0026thinsp;4), immediate withdrawal after consent (n\u0026thinsp;=\u0026thinsp;24), no valid student visa (n\u0026thinsp;=\u0026thinsp;8), withdrawal after the visa question (n\u0026thinsp;=\u0026thinsp;13), and no response to the learning mode question (n\u0026thinsp;=\u0026thinsp;15). One participant self-identified as non-binary; due to small numbers, gender was dichotomised as male/female and this case was excluded. A total of 122 participants were included in the analysis. Descriptive summaries of their demographic characteristics, learning mode preferences, OLSE, and acculturative stress are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; mental health outcomes on depression and anxiety are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eDemographics\u003c/h2\u003e\u003cp\u003eOf the 122 participants, 73 (59.8%) were in the in-person learning group and 49 (40.2%) in the hybrid group. The mean age was 23.0 years (SD\u0026thinsp;=\u0026thinsp;2.1 years). Most participants were female (n\u0026thinsp;=\u0026thinsp;97, 79.5%), from Eastern China (n\u0026thinsp;=\u0026thinsp;71, 58.2%), pursuing a master\u0026rsquo;s degree (n\u0026thinsp;=\u0026thinsp;95, 77.9%), in their first or second year (n\u0026thinsp;=\u0026thinsp;109, 89.3%), single (n\u0026thinsp;=\u0026thinsp;83, 68.0%), and commuting less than 30 minutes to campus (n\u0026thinsp;=\u0026thinsp;94, 77.0%).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eLearning Mode Preference and OLSE\u003c/h2\u003e\u003cp\u003eMost students preferred in-person learning (n\u0026thinsp;=\u0026thinsp;71, 63.4%), followed by hybrid (n\u0026thinsp;=\u0026thinsp;30, 26.8%), and online learning (n\u0026thinsp;=\u0026thinsp;11, 9.8%). The overall median OLSE score was 99 (IQR 87\u0026ndash;108). Students in the hybrid group reported lower in OLSE scores (median\u0026thinsp;=\u0026thinsp;96, IQR 87-105.5) than those in the in-person group (median\u0026thinsp;=\u0026thinsp;102.5, IQR 88\u0026ndash;110).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic Information\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;122)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIn person (n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHybrid (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, mean (SD), yrs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.0 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.2 (2.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.7 (1.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (20.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (26.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e97 (79.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54 (74.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43 (87.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHometown, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEast China\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e71 (58.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 (60.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (55.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral China\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21(17.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (16.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (18.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWest China\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (14.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (15.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (14.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNortheast China\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (5.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAR/Taiwan, China\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArchitecture, Building and Planning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (3.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (5.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (26.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (32.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (16.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBusiness and Economics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (11.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (13.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (19.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (17.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEngineering and Information Technology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (7.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFine Arts and Music\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLaw\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (4.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedicine, Dentistry and Health Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (13.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (5.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (24.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (13.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (9.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (20.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCourse level, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndergraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (20.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (19.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaster\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e95 (77.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (79.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (75.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGraduate Researcher (PhD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58 (47.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (42.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (55.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecond year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51 (41.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (45.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (36.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThird year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (9.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (9.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFourth year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFifth year and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLength of stay, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eless than 3 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (12.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (11.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (14.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026ndash;6 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (14.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (11.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (20.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u0026ndash;12 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (11.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (13.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;3 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (37.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (38.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (36.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emore than 3 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (23.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (26.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (20.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelationship, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e83 (68.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47 (64.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (73.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34 (27.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (32.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (20.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried/De facto\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep, mean (SD), hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.1 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.2 (1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.1 (1.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCommute time, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eless than 30 mins\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e94 (77.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57 (78.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (75.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emore than 30 mins\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (23.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (21.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (24.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRan Out of Food, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (11.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (13.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e108 (88.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63 (86.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45 (91.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCouldn\u0026rsquo;t Afford Medicine, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (9.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e112 (91.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66 (90.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46 (93.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFavourite mode, n (%)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-person\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e71 (63.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49 (72.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (50.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOnline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (9.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (5.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (15.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHybrid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (26.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (22.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (34.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOLSE score, median (IQR)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99 (87\u0026ndash;108)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e102.5 (88\u0026ndash;110)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96 (87-105.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcculturative stress score, median (IQR)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88 (67\u0026ndash;112)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83 (63\u0026ndash;107)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e101 (68\u0026ndash;121)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations:\u003c/p\u003e\u003cp\u003eIQR: Interquartile range (25th\u0026ndash;75th percentile);\u003c/p\u003e\u003cp\u003eSD: Standard deviation.\u003c/p\u003e\u003cp\u003eRanges:\u003c/p\u003e\u003cp\u003eOLSE scores range from 22 to 132, with higher scores indicating a higher self-efficacy in online learning.\u003c/p\u003e\u003cp\u003eAcculturative stress scores range from 32 to 224, with higher scores indicating a higher level of acculturative stress.\u003c/p\u003e\u003cp\u003e*Missing data:\u003c/p\u003e\u003cp\u003eFavourite mode: In person 5 (7%), Hybrid 5 (10%);\u003c/p\u003e\u003cp\u003eOLSE: In person 19 (26%), Hybrid 9 (18%);\u003c/p\u003e\u003cp\u003eAcculturative stress: In person 15 (21%), Hybrid 6 (12%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eAcculturative Stress\u003c/h2\u003e\u003cp\u003eOverall median acculturative stress was 88 (IQR 67\u0026ndash;112). Scores were higher and more variable among hybrid learners (median\u0026thinsp;=\u0026thinsp;101, IQR 68\u0026ndash;121) compared with in-person learners (median\u0026thinsp;=\u0026thinsp;83, IQR 63\u0026ndash;107).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eDepression and Anxiety Symptoms\u003c/h2\u003e\u003cp\u003eOn average, students reported mild depressive symptoms (mean\u0026thinsp;=\u0026thinsp;8.1, SD\u0026thinsp;=\u0026thinsp;5.7). Using a PHQ-9 cut-off of 10, thirty-four (32.4%) students met criteria for moderate to severe depression. Hybrid learners reported greater symptoms (mean\u0026thinsp;=\u0026thinsp;9.2, SD\u0026thinsp;=\u0026thinsp;5.3) compared to in-person learners (mean\u0026thinsp;=\u0026thinsp;7.3, SD\u0026thinsp;=\u0026thinsp;5.8).\u003c/p\u003e\u003cp\u003eAnxiety scores followed a similar pattern. The mean GAD-7 score was 7.5 (SD\u0026thinsp;=\u0026thinsp;5.3), reflecting mild anxiety, with 31 (29.8%) students classified as moderate to severe. Hybrid learners reported slightly greater anxiety (mean\u0026thinsp;=\u0026thinsp;8.6, SD\u0026thinsp;=\u0026thinsp;5.2) than in-person learners (mean\u0026thinsp;=\u0026thinsp;6.7, SD\u0026thinsp;=\u0026thinsp;5.3).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive Statistics of Outcome Measures\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;122)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIn person (n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHybrid (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression score, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (4\u0026ndash;11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (4\u0026ndash;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (5\u0026ndash;12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression score, mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.1 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.3 (5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.2 (5.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepressive symptoms, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMinimal (0\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27 (25.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (30.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (18.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMild (5\u0026ndash;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (41.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (45.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (37.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate (10\u0026ndash;14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (19.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (11.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (30.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerately severe (15\u0026ndash;19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (8.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (8.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (9.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSevere (20\u0026ndash;27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (4.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (4.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety score, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (3\u0026ndash;11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (2\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (5\u0026ndash;12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety score, mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.5 (5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.7 (5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.6 (5.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety symptoms, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMinimal (0\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (27.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (36.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (16.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMild (5\u0026ndash;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (42.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (37.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21 (48.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate (10\u0026ndash;14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21(20.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (19.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (20.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSevere (15\u0026ndash;21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (9.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (14.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations:\u003c/p\u003e\u003cp\u003eIQR: Interquartile range (25th\u0026ndash;75th percentile);\u003c/p\u003e\u003cp\u003eSD: Standard deviation.\u003c/p\u003e\u003cp\u003eRanges:\u003c/p\u003e\u003cp\u003eDepression scores range from 0 to 27, with higher scores indicating a higher level of depression.\u003c/p\u003e\u003cp\u003eAnxiety scores range from 0 to 21, with higher scores indicating a higher level of anxiety.\u003c/p\u003e\u003cp\u003eMissing data:\u003c/p\u003e\u003cp\u003eDepression: In person 11 (15%), Hybrid 6 (12%);\u003c/p\u003e\u003cp\u003eAnxiety: In person 12 (16%), Hybrid 6 (12%).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eLearning Mode and Depression\u003c/h2\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the unadjusted regression model indicated a 1.32-fold (95% CI: [1.05, 1.65], p\u0026thinsp;=\u0026thinsp;0.018) change in geometric mean depression scores for the hybrid group compared to the in-person group. Hardly any changes were observed in the association after adjusting for age, gender, financial difficulties, and OLSE (GMR\u0026thinsp;=\u0026thinsp;1.33, 95% CI: [1.04, 1.71], p\u0026thinsp;=\u0026thinsp;0.021). After further adjusting for acculturative stress, the association slightly attenuated (GMR\u0026thinsp;=\u0026thinsp;1.17, 95% CI: [0.93, 1.48], p\u0026thinsp;=\u0026thinsp;0.175). A 1-unit increase in acculturative stress was associated with a 1.01-fold (95% CI: [1.01,1.01], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) relative change in geometric mean depression scores.\u003c/p\u003e\u003cp\u003eAdjusted exploratory mediation analysis (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) suggested that the total effect of learning mode on depression (GMR\u0026thinsp;=\u0026thinsp;1.35, 95% CI: [1.06,1.72], p\u0026thinsp;=\u0026thinsp;0.014) comprised a direct effect (GMR\u0026thinsp;=\u0026thinsp;1.17, 95% CI: [0.95,1.45], p\u0026thinsp;=\u0026thinsp;0.141) and an indirect effect via acculturative stress (GMR\u0026thinsp;=\u0026thinsp;1.15, 95% CI: [1.01,1.32], p\u0026thinsp;=\u0026thinsp;0.037).\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eLearning Modes and Anxiety\u003c/h2\u003e\u003cp\u003eThe unadjusted regression model indicated a 1.31-fold (95% CI: [1.03, 1.67], p\u0026thinsp;=\u0026thinsp;0.028) change in geometric mean anxiety scores for hybrid group compared to in-person group. Hardly any changes were observed in the association after adjusting for age, gender, financial difficulties, and OLSE (GMR\u0026thinsp;=\u0026thinsp;1.32, 95% CI: [1.02, 1.71], p\u0026thinsp;=\u0026thinsp;0.033). Further adjusting for acculturative stress slightly attenuated the effect (GMR\u0026thinsp;=\u0026thinsp;1.10, 95% CI: [0.88, 1.36], p\u0026thinsp;=\u0026thinsp;0.397). Every 1-unit increase in acculturative stress was associated with a 1.01-fold (95% CI: [1.01,1.01], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) relative change in geometric mean anxiety scores.\u003c/p\u003e\u003cp\u003eIn adjusted exploratory mediation analysis, the total effect of learning mode on anxiety (GMR\u0026thinsp;=\u0026thinsp;1.31, 95% CI: [1.03,1.67], p\u0026thinsp;=\u0026thinsp;0.026) included a direct effect (GMR\u0026thinsp;=\u0026thinsp;1.10, 95% CI: [0.92,1.31], p\u0026thinsp;=\u0026thinsp;0.307) and an indirect effect via acculturative stress (GMR\u0026thinsp;=\u0026thinsp;1.20, 95% CI: [1.03,1.39], p\u0026thinsp;=\u0026thinsp;0.016). Negligible differences were observed between adjusted and unadjusted models (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFindings were consistent in sensitivity analyses using multiple imputed data (see Supplementary Materials).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRegression Results for Learning Modes on Depression and Anxiety\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eLog transformation output\u003csup\u003e∆\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnivariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGeometric mean ratio\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLearning mode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-person\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHybrid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.05 to 1.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultivariable \u0026ndash; Model 1*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLearning mode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-person\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHybrid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.04 to 1.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultivariable \u0026ndash; Model 2**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLearning mode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-person\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHybrid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.93 to 1.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnivariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGeometric mean ratio\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLearning mode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-person\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHybrid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.03 to 1.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultivariable \u0026ndash; Model 1*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLearning mode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-person\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHybrid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.02 to 1.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultivariable \u0026ndash; Model 2**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLearning mode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-person\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHybrid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.88 to 1.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.397\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e* Adjusted for age, gender, OLSE, and financial difficulties.\u003c/p\u003e\u003cp\u003e** Further adjusted for acculturative stress based on Model 1*.\u003c/p\u003e\u003cp\u003e\u003csup\u003e∆\u003c/sup\u003e Geometric mean ratio, 95% confidence interval, and p-value are reported.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExploratory Mediation Analysis of Acculturative Stress in the Relationship Between Learning Modes and Depression and Anxiety\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eLog transformation output\u003csup\u003e∆\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnadjusted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGeometric mean ratio\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndirect effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.01 to 1.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDirect effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.96 to 1.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.07 to 1.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGeometric mean ratio\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndirect effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.01 to 1.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDirect effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.95 to 1.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.141\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.06 to 1.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnadjusted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGeometric mean ratio\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndirect effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.03 to 1.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDirect effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.90 to 1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.386\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.01 to 1.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGeometric mean ratio\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndirect effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.03 to 1.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDirect effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.92 to 1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.307\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.03 to 1.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e* Adjusted for age, gender, OLSE, and financial difficulties.\u003c/p\u003e\u003cp\u003e\u003csup\u003e∆\u003c/sup\u003e Geometric mean ratio, 95% confidence interval, and p-value are reported.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003eLearning mode preferences\u003c/h2\u003e\u003cp\u003eThe in-person mode is the most preferred learning mode (n\u0026thinsp;=\u0026thinsp;71, 63.4%), followed by the hybrid mode (n\u0026thinsp;=\u0026thinsp;30, 26.8%), and online mode is the least preferred, with only 11 students (9.8%) ranking it in the first place (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Note that participants in the hybrid group reported lower scores on OLSE compared to those in the in-person group. One possible explanation is that only students who had experienced online learning could accurately assess the technology challenges they encountered, rather than imagining their self-efficacy.\u003c/p\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003eRates of Depression and Anxiety\u003c/h2\u003e\u003cp\u003eIn Ke et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u0026rsquo;s study, PHQ-2 (Kroenke et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and GAD-2 (Kroenke et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) were used to measure depression and anxiety during the pandemic in 2020 among CIS at the same university as in our study. A cut-off point of three or more was applied, and 43.8% and 45.7% of the CIS were reported to have depression and anxiety, respectively. According to the study of Ke and colleagues, these percentages were nearly double the rates reported in 2019 (22.1% vs 24.7%). To make a comparison, we extracted the items of PHQ-2 from PHQ-9, and those of GAD-2 from GAD-7, and then applied the same cut-off point. Among the CIS in our sample, 23.8% reported depression, and 39.0% reported anxiety (see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The percentage of depression in 2024 is similar to what it was before COVID (23.8% vs 22.1%). However, the percentage of anxiety is closer to what it was during the pandemic (39.0% vs 45.7%). The reason for this disparity is unclear, since our data were collected between April and May 2024, a similar collection window compared to April-June 2019 in the previous study.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison Between Studies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eData collection\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepression (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnxiety (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019, Apr-Jun\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKe et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020, Sept-Oct\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKe et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024, Apr-May\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThis study\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eCIS reported a higher percentage of moderate to severe depression than other international students (32.4% vs 25.9%) and a higher proportion of moderate to severe anxiety than other international students (29.8% vs 19.8%) in a study by Sanci et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Possible reasons might be that, first, international students from other countries, like India, might have a better English level than CIS, making it easier for them to adapt to the new English environment of learning and living. Second, CIS very frequently experience sustained pressure to achieve high academic performance and may be more likely than other international students to experience negative emotions due to academic-related stress and to develop mental health problems (Zhao et al., 2015; Zhou et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eLearning mode, acculturation stress and mental health\u003c/h2\u003e\u003cp\u003eIn this exploratory study, we observed lower levels of depression and anxiety among CIS in the in-person learning group compared with those in the hybrid learning group. The regression analysis demonstrated that adjusting for acculturative stress resulted in significant attenuation of the associations between learning mode and mental health. Moreover, mediation analysis found that acculturative stress mediated the association between learning mode and mental health outcomes of CIS.\u003c/p\u003e\u003cp\u003eOur findings are consistent with existing literature that acculturative stress is positively associated with mental health problems among international students and immigrants worldwide (Amlashi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Sirin et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Although CIS in the hybrid learning group reported higher scores on depression and anxiety scales than those in the in-person learning group, our findings suggest that learning mode does not have any significant association with the mental health of CIS after adjusting for acculturative stress.\u003c/p\u003e\u003cp\u003eAs previously mentioned, a review of studies on mental health and online learning pointed out that most studies did not control for the pandemic effect (Moore et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). What appeared to be related to online learning may, in fact, have been due to pandemic-related factors, including the increased social isolation as a product of the widespread quarantine measures that were imposed.\u003c/p\u003e\u003cp\u003eResults of mediation analysis also suggested that the association between learning mode and depression and anxiety may operate primarily through acculturative stress. The ASSCS we used has five subscales: Language Insufficiency, Social Isolation, Perceived Discrimination, Academic Pressure, and Guilt Towards Family (Bai, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Among these, some factors are found to be increased during online learning, for example, CIS reported an increased level of academic stress when learning online, as they tended not to answer questions via the microphone or type in chat due to their insufficient English skills in speaking and writing (Chang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Online classes also limited students\u0026rsquo; opportunities to interact with peers in social settings (Adachi \u0026amp; Tran, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and CIS perceived discrimination during group activities online (Nam et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, restricted by the small sample size, our study was unable to conduct more detailed analyses to adjust these variables separately. Furthermore, given the cross-sectional nature of this exploratory study, no causal inferences could be drawn from our analyses.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003eImplications\u003c/h2\u003e\u003cp\u003eObservations from our study underscore the need for universities to implement mental health programs that specifically address the acculturative challenges faced by CIS, particularly in the context of online learning. In addition to providing academic support and increasing opportunities for social interaction on campus, universities should design targeted sessions aimed at reducing acculturative stress. Involving student representatives in the co-design of such programs may further enhance cultural specificity and effectiveness.\u003c/p\u003e\u003cp\u003eTo deepen our understanding of the preliminary results from this study, future research may benefit from being conducted at the institutional level to enable access to a larger sample, thereby increasing statistical power and enhancing the reliability of the findings. Studies with longitudinal designs could help examine potential causal relationships, both between online learning and acculturative stress, and between acculturative stress and mental health. Moreover, qualitative approaches, such as interviews and focus groups, could generate richer and more nuanced insights into the interplay between online learning, acculturation, and mental health, based on the lived experiences of CIS.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and Limitations\u003c/h2\u003e\u003cp\u003eThis study has several strengths. First, it focused specifically on CIS, the largest international student cohort in Australia, rather than treating international students as a homogeneous group. This allowed us to capture culturally specific experiences. Second, data were collected in 2024 when pandemic restrictions had ended. Our study has provided insights into learning mode and mental health in a context different from what it had been two to three years ago, and students had more autonomy in their study choices. Third, we applied robust statistical methods, including multiple imputation to address missing data. Lastly, we also used validated instruments to measure variables such as acculturative stress and OLSES.\u003c/p\u003e\u003cp\u003eSeveral limitations must also be acknowledged. The voluntary nature of participation may have introduced selection bias, with students experiencing mental health difficulties potentially more likely to respond. The sample size recruited (n\u0026thinsp;=\u0026thinsp;122) fell short of was required (n\u0026thinsp;=\u0026thinsp;614), limiting statistical power and precision. Our findings should therefore be considered exploratory. Furthermore, the cross-sectional design precludes causal inference; mediation results in particular must be interpreted with caution. Finally, as the study was conducted at a single metropolitan, research-intensive university, the findings may not be generalisable to other settings or student populations.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study examined the relationship between learning mode and mental health outcomes among CIS. Results indicated that participants in the hybrid learning group self-reported higher scores of depression and anxiety compared to participants in the in-person learning group. Based on mediation analysis, acculturative stress significantly mediated the association between learning mode and depression and anxiety among CIS. Our exploratory study has shed some light on the interaction between learning mode and the mental health of university students, filling a gap in this understudied area. Findings could be used by professionals in education, cross-cultural, and mental health settings to develop targeted programs supporting the psychological wellbeing of CIS. Future research could adopt longitudinal designs and qualitative approaches, to provide a deeper and more nuanced understanding of acculturative stress and the mental health of CIS in online learning settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul\u003e\n \u003cli\u003eASSCS \u0026ndash; Acculturative Stress Scale for Chinese Students\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCI \u0026ndash; Confidence interval\u003c/li\u003e\n \u003cli\u003eCIS \u0026ndash; Chinese international students\u003c/li\u003e\n \u003cli\u003eCOVID-19 \u0026ndash; Coronavirus disease 2019\u003c/li\u003e\n \u003cli\u003eGAD-2 \u0026ndash; Generalised Anxiety Disorder Questionnaire 2 items\u003c/li\u003e\n \u003cli\u003eGAD-7 \u0026ndash; Generalised Anxiety Disorder Questionnaire 7 items\u003c/li\u003e\n \u003cli\u003eGMR \u0026ndash; Geometric mean ratio\u003c/li\u003e\n \u003cli\u003eIQR \u0026ndash; Interquartile range\u003c/li\u003e\n \u003cli\u003eOLSE \u0026ndash; Online learning self-efficacy\u003c/li\u003e\n \u003cli\u003ePHQ-2 \u0026ndash; Patient Health Questionnaire 2 items\u003c/li\u003e\n \u003cli\u003ePHQ-9 \u0026ndash; Patient Health Questionnaire 9 items\u003c/li\u003e\n \u003cli\u003ePLS \u0026ndash; Plain Language Statement\u003c/li\u003e\n \u003cli\u003eSD \u0026ndash; Standard deviation\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cul\u003e\n \u003cli\u003eData statement\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the University of Melbourne, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of the Human Ethics Committee of the University of Melbourne.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eCompeting interests\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eFunding\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eAuthors\u0026apos; contributions\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll authors were involved in conceptualising the study and designing the methodology. PZ collected data and analysed it with the help of ADS. PZ drafted the manuscript. HM, AG, and ADS supervised the project, provided critical feedback and substantially revised the manuscript.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eAcknowledgements\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eWe would like to thank all the student participants who generously shared their time and information by completing the online survey. We also sincerely appreciate the support provided by the university platforms and various student clubs that helped us distribute the questionnaire.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdachi, C., \u0026amp; Tran, L. (2022). \u003cem\u003eInternational students are back on campus, but does that spell the end of digital learning? 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Factors associated with mental health of Chinese international students in the global context: a systematic review. \u003cem\u003eBMC Public Health\u003c/em\u003e,\u003cem\u003e 25\u003c/em\u003e(1), 3460. https://doi.org/10.1186/s12889-025-24400-w \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Online learning, Hybrid learning, Chinese international students, Depression, Anxiety, Acculturative stress","lastPublishedDoi":"10.21203/rs.3.rs-8042476/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8042476/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOnline learning was widely implemented in university teaching activities during the pandemic and remains an important component of education following cessation of pandemic-related restrictions. Although university students reported worsening mental health during the pandemic little is known about how current learning modes (in-person, hybrid and online) are associated with mental health of international students, particularly among Chinese international students (CIS). We conducted a cross-sectional online survey of 122 CIS enrolled at an Australian university between April and May 2024. Depression and anxiety symptoms were measured using the Patient Health Questionnaire (PHQ-9) scale and Generalised Anxiety Disorder Questionnaire (GAD-7) scale. Acculturative stress was assessed using the Acculturative Stress Scale for Chinese Students (ASSCS). Associations between learning mode (in-person vs. hybrid) and mental health outcomes were examined, and the potential mediating role of acculturative stress was explored. Results indicated that compared with students in the in-person learning group, those in the hybrid learning group reported higher scores for depression (geometric mean ratio (GMR)\u0026thinsp;=\u0026thinsp;1.32, 95% CI: [1.05, 1.65]) and anxiety (GMR\u0026thinsp;=\u0026thinsp;1.31, 95% CI: [1.03, 1.67]). Only minimal change was observed after adjusting for age, gender, financial difficulties, online learning self-efficacy, and acculturative stress. Mediation analysis showed that acculturative stress may partially account for these differences. While acculturative stress may play a role in this association, longitudinal research is required to clarify directionality and causal pathways. These findings suggest that assistance with effective acculturation could be a potentially important component of university-based mental health programs.\u003c/p\u003e","manuscriptTitle":"Learning mode, university students’ mental health, and acculturative stress – a cross-sectional study of Chinese international students in Melbourne, Australia.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-10 05:43:22","doi":"10.21203/rs.3.rs-8042476/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b16367f4-6948-4dce-8323-db9b43f0c48f","owner":[],"postedDate":"November 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":57599448,"name":"Epidemiology"},{"id":57599449,"name":"School Counseling"},{"id":57599450,"name":"Cultural Studies"},{"id":57599451,"name":"Educational Psychology"}],"tags":[],"updatedAt":"2026-04-15T15:23:25+00:00","versionOfRecord":{"articleIdentity":"rs-8042476","link":"https://doi.org/10.32674/bzdqb085","journal":{"identity":"journal-of-international-students","isVorOnly":true,"title":"Journal of International Students"},"publishedOn":"2026-04-14 00:00:00","publishedOnDateReadable":"April 14th, 2026"},"versionCreatedAt":"2025-11-10 05:43:22","video":"","vorDoi":"10.32674/bzdqb085","vorDoiUrl":"https://doi.org/10.32674/bzdqb085","workflowStages":[]},"version":"v1","identity":"rs-8042476","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8042476","identity":"rs-8042476","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}