Objective

This review will synthesize findings from research on the mental health of international students, incorporating quantitative, qualitative, and mixed-method studies. It will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure comprehensive and transparent reporting [29]. Through this systematic review and meta-analysis, we aim to identify interventions utilized to alleviate mental health issues, distress, self-criticism, and enhance well-being among international students. Furthermore, we will assess the effectiveness of each intervention included in the analysis.

Study design

This protocol was registered in the PROSPERO database (International Prospective Register of Systematic Reviews), with registration number CRD42024528767, and is reported in accordance with the guidelines provided in the PRISMA-P guide (Preferred Reporting Items for Systematic Review and Meta-Analyses Protocol) [29]. A systematic review protocol should present the methodological strategies that will be used in the systematic review, such as search strategies, eligibility criteria, what data will be extracted from the selected articles, what the variables of interest are, how the data will be analyzed, and how heterogeneities will be handled [30, 31]. Thus, the protocol should demonstrate transparency in the systematic review process.

Eligibility criteria

To be included, studies must be evaluated an intervention related to mental health among international students. There are no restrictions on the settings or countries of the interventions, and there are no date limits; these can be in-person or online format or mobile messaging. Educational or medical visits and self-help interventions will be evaluated. A control group is not a necessary requirement for inclusion within this review.

Studies meeting the following criteria will be included: (1) an intervention study with pre-and-post data; (2) targeted international students; (3) aimed to improve mental health or wellbeing; and (4) published in English and peer-reviewed journals. Exclusion criteria covered conference abstracts, published theses or dissertations, letters to editors, curriculum development, published protocols/guidelines, literature reviews, and syllabus material. Short-term exchange students will be excluded. Within the screening process, discrepancies were resolved by an additional reviewer.

Literature search

The bibliographic databases are CINAHL Complete (EBSCOhost), PubMed, Web of Science, ERIC (ProQuest), PsycINFO, and Google Scholar and focused on 3 areas: 1) international students, 2) mental health interventions, and 3) clinical or educational settings. The search will be modified for each database to include appropriate controlled vocabulary but remained largely similar across databases. For example, the complete search strategy in PubMed was (("international student" OR "international students" OR "foreign student" OR "foreign students)" AND ("substance abuse" OR "binge drinking") AND ("mental health" OR depress* OR anxi* OR "anxiety disorder" OR "anxiety disorders" OR "depressive disorder" OR "depressive disorders" OR "Depression"[Mesh] OR "Depressive Disorder"[Mesh] OR "Mental Health"[Mesh] OR "Anxiety"[Mesh] OR "Anxiety Disorders"[Mesh] OR "well-being" OR wellness OR stress* OR "Stress, Psychological"[Mesh])).

Screening procedure

All identified articles will be exported to Covidence for further screening. The screening procedure will be carried out in two stages and independently by two reviewers. In the first stage, the first and second authors will independently screen the titles and abstracts of the articles. They will then read the full texts to assess eligibility and determine if the studies meet the inclusion criteria. A third reviewer will decide on the article’s inclusion in case of disagreement. A fourth reviewer will randomly sample 10% of the studies from a pool of articles that have been excluded as a cross-examination. The screening procedure will be done without any contact between the two reviewers in order to avoid influences on the decision process.

Data extraction

Data extraction will be performed by filling out an Excel sheet with a detailed description of the main information of the selected studies and will also be performed by the first and second authors independently in order to avoid measurement bias, which occurs due to misinterpreting information or even the loss of important data collection. If information is insufficient, corresponding authors of articles may be contacted for clarification or more information.

The following data items will be extracted for each study, when available: (a) study identification items (authors, year of publication), (b) study design characteristics (purpose, sample size, intervention design/type such as survey, interview focus group, any control groups, type of assessment, duration of intervention, length of follow-up assessments), (c) target population items (age, gender), (d) setting (recruitment strategy, online or in-person setting), (e) drop-out rate and (f) outcomes (anxiety, depression, stress, seeking help intention, etc.).

Quality assessment

In order to evaluate the quality of research and risks of bias, two independent reviewers will assess the quality of each article using the Mixed Methods Appraisal Tool (MMAT) [32]. MMAT is widely used for critical research appraisal and is designed for systematic mixed study reviews. The tool is appropriate for assessing qualitative research, randomized controlled trials, non-randomized studies, quantitative descriptive studies, and mixed methods studies [32–36]. Chosen studies will be rated as having strong, moderate, or weak quality (vs. assigning overall quality scores) as Hong et al. recommended [32].

Data synthesis

The main outcome to be evaluated is what interventions have been used to improve international students’ mental health and well-being such as anxiety, depression, stress. In addition, other outcomes will also be analyzed, such as the effectiveness of each intervention. A detailed description of the results for all included studies will be provided in text and tables. Characteristics include study design and characteristics including sample size, duration, follow-up period, student population, intervention characteristics (i.e. mindfulness, writing, reading, social support), technical implementation (i.e. online, mobile, or in-person), duration, study and intervention drop-out rate, assessment tool used to determine effectiveness of intervention, strengths and limitations.

Meta-analysis

We will conduct a quantitative synthesis of the data retrieved from the selected studies using both Stata and R. This will involve employing appropriate meta-analytic techniques, including random-effects modeling, to estimate overall effect sizes and assess heterogeneity across studies [37]. We choose to report Hedge’s g instead of Cohen’s d for effect size calculation to adjust for small sample bias [38]. In situations where studies reported results of multiple outcomes, we will prioritize and select the outcome measure based on two rules. The primary outcomes in this review are depression and anxiety, while stress is considered a secondary outcome. We will measure changes from baseline using validated assessment tools, without restricting the type of indicator assessment scales. Following the Cochrane Handbook guidelines, we will standardize results across different scales using standardized mean differences (SMDs) with 95% confidence intervals (CIs).

Due to the diverse nature of the design of included studies, we anticipate categorizing them into various design types, including treatment-control, pre-post treatment-control, and treatment group pre-post only designs. This categorization will enable us to employ the appropriate tools and methods for calculating effect sizes accurately. For each study, we will extract key information, including sample sizes, means and standard deviations of the outcome measures being assessed during the pre- and post-test, and pre-post test correlations, if available. This data extraction process will allow us to calculate effect sizes for each study using standardized formulas.

Specifically, for randomized controlled trials (RCTs), we will extract the treatment and control groups’ sample sizes, means and standard deviations from the post-test (calculated using Stata meta esize). For non-RCT pre-post treatment-control design, we will extract the sample sizes, means, standard deviations, and pre-post correlations of both the treatment and the control groups from the pre- and post-test (R metafor package escalc) [39]. For non-RCT treatment group pre-post only design, we will extract the treatment group sample sizes and means of the pre- and post-test, pretest standard deviation, and the pre and post correlation to calculate its effect sizes [40, 41]. Last, for studies that only reported regression coefficients and other statistical tests as their measures of effect sizes, we will use R package esc to convert the reported beta or r to Hedge’s g.

After calculating the effect size for each intervention study, the next step is to aggregate these effect sizes to provide an overall estimate of the intervention’s effectiveness. This aggregation process involves combining the effect sizes using Stata meta command. By synthesizing the results across multiple studies, we can derive more robust conclusions about the overall impact of various interventions on international students’ mental health. We will report the overall effect size θ, its confidence interval, and the test statistic z and p-value, as well as a visual forest plot. We will also examine the presence of heterogeneity between studies using indices τ², I², H² and the chi-squared test of homogeneity.

To address between-study variability, subgroup analyses will be conducted to explore potential sources of heterogeneity and examine whether intervention effectiveness varies across different contexts. These analyses may involve stratifying the data based on intervention type, duration, study setting, design, or participant demographics. Understanding how intervention effects differ across these subgroups will provide insights into the factors influencing the effectiveness of mental health interventions for international students. Given variations in cultural background, language proficiency, acculturation level, and previous experiences, not all international students may respond equally to the same intervention. Identifying which interventions are most effective for specific subgroups and why can guide the development of targeted and culturally sensitive interventions, ultimately enhancing mental health outcomes for international students.

Last, to assess the publication bias that studies with insignificant results tend to be suppressed from being published, we will use the funnel plot and egger test to visually evaluate and statistically test its (a)symmetry. Moreover, we will conduct a trim-and-fill analysis to assess the robustness of our meta-analysis results against potential studies that might be missing from the current pool of publications.