Does going to university in a different country affect your mental health? A Japanese international university surveyed its students in 2018 and published a study the following year that was approved by several ethical and regulatory boards.
The study found that international students have a higher risk of mental health difficulties than the general population, and that social connectedness (belonging to a social group) and acculturative stress (stress associated with joining a new culture) are predictive of depression.
Explore the students data using PostgreSQL to find out if you would come to a similar conclusion for international students and see if the length of stay is a contributing factor.
Here is a data description of the columns you may find helpful.
| Field Name | Description |
|---|---|
inter_dom | Types of students (international or domestic) |
japanese_cate | Japanese language proficiency |
english_cate | English language proficiency |
academic | Current academic level (undergraduate or graduate) |
age | Current age of student |
stay | Current length of stay in years |
todep | Total score of depression (PHQ-9 test) |
tosc | Total score of social connectedness (SCS test) |
toas | Total score of acculturative stress (ASISS test) |
The most reliable patterns emerge from the first four years, which account for the majority of the sample. Later years (5–10) exhibit extreme values that are likely influenced by very small sample sizes and should be interpreted with caution. These findings underscore the need for targeted early intervention programs to address depression and foster social integration during the initial years of study abroad.
Depression Trends
- Average PHQ-9 depression scores are highest in the first year (7.48) and remain relatively elevated through years 2–4.
- Scores drop sharply after year 4, but this pattern is less reliable due to very small sample sizes in later years (e.g., only 1–3 students in years 6–10).
- The highest single depression score (13) occurs at year 10, but with n = 1, it is not representative.
Social Connectedness
- Social connectedness (SCS) scores are lowest during the first year (33.93) but improve during years 2–4, peaking around 48.
- Correlation analysis shows a moderate-to-strong negative relationship between depression and social connectedness (r = –0.54), indicating that students with higher depression scores tend to feel less socially connected.
- Later years display greater variability in scores, likely reflecting both individual differences and the instability caused by small sample sizes.
Acculturative Stress
- Acculturative stress (ASISS) scores remain consistently high across all stay durations (~72–91), suggesting that cultural adjustment challenges persist even after multiple years in Japan.
- Correlation analysis reveals a moderate positive relationship between depression and acculturative stress (r = 0.41), meaning students with higher acculturative stress tend to report more depressive symptoms.
- Year 10 shows the lowest acculturative stress (50), but this is based on a single student and should not be generalized.
Sample Size Impact
- Years 1–4 contain most of the data (n = 95, 39, 46, 14), making these trends more reliable.
- Years 5–10 have very small counts (n ≤ 3), limiting confidence in observed patterns and increasing the likelihood of outliers skewing averages.
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SQL Exploration: Used aggregation functions (AVG, ROUND, COUNT) and grouping to examine trends by length of stay.
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Correlation Analysis: Quantified the relationships between depression, social connectedness, and acculturative stress, confirming patterns consistent with prior research.
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Data Integrity Consideration: Recognized that trends beyond year 4 need cautious interpretation due to small sample sizes.
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Mental Health Patterns: Identified that early years abroad are most vulnerable for depression, and acculturative stress remains consistently high.
- Regression Modeling: Develop a multiple regression model to examine how social connectedness and acculturative stress jointly predict depression scores, controlling for length of stay.
- Non-Linear Trend Analysis: Explore whether mental health trajectories over time follow a non-linear pattern (e.g., sharp early change followed by plateau).
WITH inter AS (
SELECT
stay::numeric AS stay_years,
todep::numeric AS phq9,
tosc::numeric AS scs,
toas::numeric AS asiss
FROM students
WHERE inter_dom = 'Inter'
)
SELECT
stay_years AS "Years in Japan",
COUNT(*) AS "Number of Students",
COUNT(phq9) AS "PHQ-9 Responses (n)",
ROUND(AVG(phq9), 2) AS "Average Depression Score (PHQ-9)",
COUNT(scs) AS "SCS Responses (n)",
ROUND(AVG(scs), 2) AS "Average Social Connectedness Score (SCS)",
COUNT(asiss) AS "ASISS Responses (n)",
ROUND(AVG(asiss), 2) AS "Average Acculturative Stress Score (ASISS)"
FROM inter
GROUP BY stay_years
ORDER BY stay_years DESC;WITH inter AS (
SELECT
stay::numeric AS stay_years,
todep::numeric AS phq9,
tosc::numeric AS scs,
toas::numeric AS asiss
FROM students
WHERE inter_dom = 'Inter'
)
SELECT
stay_years AS stay,
COUNT(*) AS n_students,
COUNT(phq9) AS n_phq9,
ROUND(AVG(phq9), 2) AS avg_phq9,
COUNT(scs) AS n_scs,
ROUND(AVG(scs), 2) AS avg_scs,
COUNT(asiss) AS n_asiss,
ROUND(AVG(asiss), 2) AS avg_asiss
FROM inter
GROUP BY stay_years
HAVING COUNT(*) >= 5 -- optional: guard against tiny cells
ORDER BY stay_years DESC;-- Start coding here...
SELECT
stay,
COUNT(*) AS count_int,
ROUND(AVG(todep), 2) AS average_phq,
ROUND(AVG(tosc), 2) AS average_scs,
ROUND(AVG(toas), 2) AS average_as
FROM students
WHERE inter_dom = 'Inter'
GROUP BY stay
ORDER BY stay DESC;
SELECT
CORR(todep::numeric, tosc::numeric) AS corr_phq9_scs, -- expect negative
CORR(todep::numeric, toas::numeric) AS corr_phq9_asiss -- expect positive
FROM students
WHERE inter_dom = 'Inter';-- Run this code to view the data in students
SELECT *
FROM students;