Learning mode, university students’ mental health, and acculturative stress – a cross-sectional study of Chinese international students in Melbourne, Australia.
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PeixinZuo1
AnnGowing2
Anurika
De
Silva3HarryMinas1✉Emailh.minas@unimelb.edu.au
1Global and Cultural Mental Health Unit, Centre for Mental Health and Community Wellbeing, Melbourne School of Population and Global HealthUniversity of Melbourne3010ParkvilleVictoriaAustralia
2Youth Research Collective, Faculty of EducationUniversity of Melbourne3010Melbourne, ParkvilleVictoriaAustralia
3Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global HealthUniversity of Melbourne3010ParkvilleVictoriaAustralia
Peixin Zuo a, Ann Gowing b, Anurika De Silva c, Harry Minas a (corresponding author) Email: h.minas@unimelb.edu.au
a Global and Cultural Mental Health Unit, Centre for Mental Health and Community Wellbeing, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria 3010, Australia
b Youth Research Collective, Faculty of Education, University of Melbourne, Melbourne, Parkville, Victoria 3010, Australia
c Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria 3010, Australia
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.
Keywords
Online learning
Hybrid learning
Chinese international students
Depression
Anxiety
Acculturative stress
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.
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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.
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Ethics approval was obtained from the university’s Human Research Ethics Committee (Ref. No. 2024-27526-53340-5).Participants and Recruitment
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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. A
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
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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. 1a, 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. 1b, 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).
Fig. 1
Association Between Learning Mode and Mental Health Outcomes
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 | Total (n = 122) | In person (n = 73) | Hybrid (n = 49) |
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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).
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Table 2 | Total (n = 122) | In person (n = 73) | Hybrid (n = 49) |
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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 | 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 | 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.
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.
A
List of 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
A
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.
A
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
A
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.
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