International students’ mental health has become an increasing concern in recent years, as more students leave their country for better education. They experience a wide range of challenges while studying abroad that have an impact on their psychological well-being. These challenges can include language obstacles, cultural differences, homesickness, financial issues and other elements that could severely impact the mental health of international students. Given the limited research on the demographic, cultural, and psychosocial variables that influence international students’ mental health, and the scarcity of studies on the use of machine learning algorithms in this area, this study aimed to analyse data to understand the demographic, cultural factors, and psychosocial factors that impact mental health of international students. Additionally, this paper aimed to build a machine learning-based model for predicting depression among international students in the United Kingdom. This study utilized both primary data gathered through an online survey questionnaire targeted at international students and secondary data was sourced from the ’A Dataset of Students’ Mental Health and Help-Seeking Behaviors in a Multicultural Environment,’ focusing exclusively on international student data within this dataset. We conducted data analysis on the primary data and constructed models using the secondary data for predicting depression among international students. The secondary dataset is divided into training (70%) and testing (30%) sets for analysis, employing four machine learning models: Logistic Regression, Decision Tree, Random Forest, and K Nearest Neighbor. To assess each algorithm’s performance, we considered metrics such as Accuracy, Sensitivity, Specificity, Precision and AU-ROC curve. This study identifies significant demographic variables (e.g., loan status, gender, age, marital status) and psychosocial factors (financial difficulties, academic stress, homesickness, loneliness) contributing to international students’ mental health. Among the machine learning models, the Random Forest model demonstrated the highest accuracy, achieving an 80% accuracy rate in predicting depression.

Explore the progression of average salaries for graduates in Mental Health from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Mental Health relative to other fields. This data is essential for students assessing the return on investment of their education in Mental Health, providing a clear picture of financial prospects post-graduation.

The topic of financial wellbeing is a current concern within the realm of personal and household finance. This study aims to examine the influence of cognitive factors, specifically financial literacy, mental budgeting, and self-control, on subjective financial wellbeing. While there exist multiple determinants of financial wellbeing, this research focuses on these particular cognitive factors. The present study aims to examine the mediating role of investment decision-making behavior in the association between cognitive factors and financial well-being. The study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data collected from a sample of 449 Chinese university students, with the aim of assessing the empirical associations. The results indicate that financial literacy, mental budgeting, and self-control exert a favorable and noteworthy influence on an individual’s financial well-being. The results indicate that individuals with a greater degree of financial literacy are more prone to achieving superior financial well-being. Moreover, individuals who practice mental budgeting, a technique that entails mentally classifying and monitoring their expenditures, demonstrate elevated levels of financial well-being. Likewise, the exercise of self-regulation is identified as a pivotal element that impacts an individual’s financial wellbeing. The findings indicate that there is evidence to support the mediator, investment decision-making behavior. This mediator partially mediates the association between the independent variables, namely financial literacy, mental budgeting, and self-control, and financial well-being. The results suggest that individuals with elevated levels of financial literacy, proficient mental budgeting skills, and self-regulatory abilities are inclined towards demonstrating favorable investment decision-making conduct. Consequently, this contributes to their general financial welfare. In general, the study’s theoretical implications augment the current knowledge repository, while its practical implications provide feasible perspectives for policymakers, financial institutions, and individuals to foster financial wellness and enhance financial results.

Explore the progression of average salaries for graduates in Clinical Mental Health Counseling from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Clinical Mental Health Counseling relative to other fields. This data is essential for students assessing the return on investment of their education in Clinical Mental Health Counseling, providing a clear picture of financial prospects post-graduation.

International students’ mental health has become an increasing concern in recent years, as more students leave their country for better education. They experience a wide range of challenges while studying abroad that have an impact on their psychological well-being. These challenges can include language obstacles, cultural differences, homesickness, financial issues and other elements that could severely impact the mental health of international students. Given the limited research on the demographic, cultural, and psychosocial variables that influence international students’ mental health, and the scarcity of studies on the use of machine learning algorithms in this area, this study aimed to analyse data to understand the demographic, cultural factors, and psychosocial factors that impact mental health of international students. Additionally, this paper aimed to build a machine learning-based model for predicting depression among international students in the United Kingdom. This study utilized both primary data gathered through an online survey questionnaire targeted at international students and secondary data was sourced from the ’A Dataset of Students’ Mental Health and Help-Seeking Behaviors in a Multicultural Environment,’ focusing exclusively on international student data within this dataset. We conducted data analysis on the primary data and constructed models using the secondary data for predicting depression among international students. The secondary dataset is divided into training (70%) and testing (30%) sets for analysis, employing four machine learning models: Logistic Regression, Decision Tree, Random Forest, and K Nearest Neighbor. To assess each algorithm’s performance, we considered metrics such as Accuracy, Sensitivity, Specificity, Precision and AU-ROC curve. This study identifies significant demographic variables (e.g., loan status, gender, age, marital status) and psychosocial factors (financial difficulties, academic stress, homesickness, loneliness) contributing to international students’ mental health. Among the machine learning models, the Random Forest model demonstrated the highest accuracy, achieving an 80% accuracy rate in predicting depression.

Explore the progression of average salaries for graduates in Master Of Education In Mental Health Counseling from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Master Of Education In Mental Health Counseling relative to other fields. This data is essential for students assessing the return on investment of their education in Master Of Education In Mental Health Counseling, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Education, Mental Health Counseling/Addiction Counseling from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Education, Mental Health Counseling/Addiction Counseling relative to other fields. This data is essential for students assessing the return on investment of their education in Education, Mental Health Counseling/Addiction Counseling, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Community Mental Health Counseling from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Community Mental Health Counseling relative to other fields. This data is essential for students assessing the return on investment of their education in Community Mental Health Counseling, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Psychology In Child Mental Health from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Psychology In Child Mental Health relative to other fields. This data is essential for students assessing the return on investment of their education in Psychology In Child Mental Health, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Public Health- Mental Health from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Public Health- Mental Health relative to other fields. This data is essential for students assessing the return on investment of their education in Public Health- Mental Health, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Mental Health Nursing from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Mental Health Nursing relative to other fields. This data is essential for students assessing the return on investment of their education in Mental Health Nursing, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Psychology (Mental Health Counseling) from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Psychology (Mental Health Counseling) relative to other fields. This data is essential for students assessing the return on investment of their education in Psychology (Mental Health Counseling), providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Clinical Mental Health Counseling Music Therapy from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Clinical Mental Health Counseling Music Therapy relative to other fields. This data is essential for students assessing the return on investment of their education in Clinical Mental Health Counseling Music Therapy, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Community Mental Health Nursing from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Community Mental Health Nursing relative to other fields. This data is essential for students assessing the return on investment of their education in Community Mental Health Nursing, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in M.Ed Counseling Psych Mental Health Counseling from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of M.Ed Counseling Psych Mental Health Counseling relative to other fields. This data is essential for students assessing the return on investment of their education in M.Ed Counseling Psych Mental Health Counseling, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Diploma In Mental Health Nursing from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Diploma In Mental Health Nursing relative to other fields. This data is essential for students assessing the return on investment of their education in Diploma In Mental Health Nursing, providing a clear picture of financial prospects post-graduation.