Today, over 330,000 international tertiary-level students are enrolled in Türkiye (YÖK, 2024), with projections indicating continued growth. As this number rises, understanding their unique challenges and needs becomes increasingly critical. International students often face stressors tied to academic, cultural, social, and psychological adjustments in a new environment (Forbes-Mewet & Sawyer, 2016). These difficulties are compounded by societal factors, including exposure to ethnic bias and discrimination (Duru & Poyrazlı, 2011). Such experiences significantly heighten students' psychological distress (Sanchez, 2018), complicating adaptation and impacting well-being.

Racial and ethnic microaggressions were first conceptualized by Pierce in 1970 as "subtle, striking, often automatic and non-verbal communication situations" (Torino et al., 2018). Research on this phenomenon in Türkiye remains limited. Keels et al. (2017) classify school-based racial and ethnic microaggressions that students experience into three categories: "academic inferiority," "aggression expectations," and "stereotypical misrepresentations". Such behaviors reflect broader patterns of exclusion and bias faced by international students, as highlighted in studies (Bravo et al., 2023).

Although higher education in Türkiye strives to foster inclusivity, latent xenophobia and subtle discrimination persist. For instance, Toker Gokce (2013) found that university students from diverse ethnic backgrounds often experience discrimination based on religion, ethnicity, and personal expressions like clothing or speech styles. Behaviors such as ridicule and dismissiveness by peers further isolate these students. Ünal (2017) also documented how international students struggle with prejudice and societal expectations, while Gebru and Yuksel-Kaptanoglu (2020) reported instances of faculty and students perpetuating harmful stereotypes about international students' cultures. Snoubar (2017) revealed that approximately 80% of international students in Türkiye experienced discrimination, predominantly from peers, driven by factors such as country of origin, language, and cultural differences.

Racial and ethnic microaggressions have well-documented links to psychological and physiological distress. These subtle yet pervasive forms of discrimination undermine interpersonal relationships and mental health (Owen et al., 2019). While much research addresses international students' educational and social needs, limited attention has been given to the psychological repercussions of racial microaggressions. Evidence suggests that young adults exposed to racial or ethnic discrimination are more prone to adverse mental health outcomes, including increased psychological distress, depression, anxiety, and suicidal ideation (Bravo et al., 2023).

This study adopts Minority Stress Theory (MST) (Meyer, 2003) as its theoretical framework to explore the relationship between racial microaggressions and mental health among international students in Türkiye. MST posits that minority groups face unique stressors, such as prejudice, discrimination, and stigma, leading to chronic stress and adverse mental health outcomes.

Despite Türkiye's growing internationalization efforts, the experiences of international students concerning racial microaggressions remain understudied. This research aims to address this gap by investigating the impact of these subtle discriminatory behaviors on mental health and social integration. In doing so, it seeks to contribute to a more comprehensive understanding of the lived experiences of international students in Türkiye. This study aims to identify distinct psychological distress profiles among international students in Türkiye and examine the association between these profiles and experiences of school-based racial and ethnic microaggressions (SB-REMA). In line with the main purpose, we sought answers to the following research questions:

1. When considering international students' depression, anxiety, and stress scores together, do distinct psychological distress profiles emerge through latent profile analysis? 

2. Does the total score of school-based racial and ethnic microaggressions predict membership in psychological distress profiles?

3. Do the academic inferiority, expectations of aggression, and stereotypical misrepresentations predict membership in psychological distress profiles?

The sample consisted of international students in undergraduate and graduate programs at Turkish institutions. Power analysis was conducted using the pwrss R package with 80% power and a 5% Type I error rate (Bulus & Polat, 2023). For three latent profiles, 63 participants were required to detect a small effect (Cohen, 1992). Data was collected between April and May 2024 using convenient sampling, resulting in 160 undergraduate students. After excluding 20 participants who came to Türkiye for non-educational purposes and 24 with invalid responses, the final dataset included 116 participants. However, contrary to expectations, the profile analysis revealed three profiles (normal, moderate, high). With 116 participants, the statistical power decreased from 80% to 67% at 5% Types I error rate. Ethical approval was obtained from Istanbul Aydin University (Ethics Committee Approval No. 2023-02). Data were collected using a demographic form and two scales. The School-Based Racial and Ethnic Microaggressions Scale (Keels et al., 2017) assessed racial microaggressions within educational settings, including microinvalidations, microinsults, and microassaults. We calculated Cronbach's alpha values of the total scale and subscales (Academic Inferiority, Expectations of Aggression, Stereotypical Misrepresentations) as .91, .88, .84, and .75, respectively. The short-form Depression Anxiety Stress Scale (DASS-21; Lovibond & Lovibond, 1995) measured depression, anxiety, and stress. Cronbach's alpha values of the subscales were .88, .88, and .84, respectively. To determine different mental health profiles based on participants' scores on the depression, anxiety, and stress subscales of the DASS-21, we conducted an LPA to determine participants’ distress profiles in the R environment by using the tidyLPA package (Rosenberg et al., 2018). The inputs of LPA are depression, anxiety, and stress sum scores. We first examined different profile solutions and fit indices to find the profile that best represents the data. We used statistical indicators to compare models and determine the most appropriate ones, including BIC, SABIC, CAIC, AIC, AWE, Entropy, and BLRT (Weller et al., 2020). Following the latent profile analysis, an ordinal logistic regression analysis was conducted to examine the predictive role of the total score of the School-Based Racial and Ethnic Microaggressions Scale and its subscales on profile membership. To facilitate interpretation, odds ratios (OR) and their 95% confidence intervals were calculated to estimate the likelihood of belonging to a higher-risk profile relative to lower-risk profiles based on SB-REMA scores.

LPA findings showed that the three-profile solution was the best-fitting model. Significant BLRT values up to the third profile (p = .010) and a high entropy value (.973) support its accuracy and clarity (McLachlan & Peel, 2000; Clark & Muthén, 2009). Information criteria and the tidyLPA approach (Akogul & Erisoglu, 2017) further confirm its suitability. Clear separation between profiles and high posterior probabilities (> .70) indicate distinct and reliable classifications (Nagin, 2005). We labeled the profiles as low (Profile 1), moderate (Profile 2), and high (Profile 3). International students in the low profile had normal levels of depression, anxiety, and stress, indicating no mental health risks. The high profile showed high levels of these symptoms, pointing to significant risk and a need for intervention. The moderate profile reflected moderate symptoms, suggesting some challenges requiring attention but less severe than the high profile. Following the profile analysis, an ordinal logistic regression was conducted to examine whether School-Based Racial and Ethnic Microaggressions (SB-REMA) scores predicted profile membership. Higher SB-REMA scores significantly predicted higher-risk profile membership (b = 0.96, SE = 0.217, t = 4.42). This means a one-unit increase in standardized SB-REMA scores raised the odds of belonging to a higher-risk profile by 2.61 times (95% CI: 1.74–4.09). Further analysis of SB-REMA subscales revealed that the Stereotypical Misrepresentations subscale significantly predicted profile membership (b = 0.318, SE = 0.133, t = 2.39, p = 0.017), whereas the Academic Inferiority and Expectations of Aggression subscales did not (p > 0.05). This means a one-unit increase in standardized Stereotypical Misrepresentations subscale scores raised the odds of belonging to a higher-risk profile by 1.37 times (95% CI: 1.06–1.80).

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