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Analyzing Students' Mental Health

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 NameDescription
inter_domTypes of students (international or domestic)
japanese_cateJapanese language proficiency
english_cateEnglish language proficiency
academicCurrent academic level (undergraduate or graduate)
ageCurrent age of student
stayCurrent length of stay in years
todepTotal score of depression (PHQ-9 test)
toscTotal score of social connectedness (SCS test)
toasTotal score of acculturative stress (ASISS test)

Let's start by counting all of the records in the data, then all records per student type to see how the records are categorized and scored.

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DataFrameas
students
variable
-- Save the CSV file as students
SELECT * 
FROM 'students.csv';
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DataFrameas
counts_per_student_type
variable
-- Counts per student type (`inter_dom`)
SELECT 
	inter_dom,
	COUNT(*) AS counts
FROM students
GROUP BY inter_dom;
  • Filter the data to see how it differs between the student types.
  • Find the summary statistics of the diagnostic tests for all students using aggregate functions, rounding the test scores to two decimal places, remembering to use aliases.
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DataFrameas
aggs_for_dep_score
variable
-- Aggregates for depression score
SELECT
	COUNT(*) AS counts,
	SUM(todep) AS total_dep_score,
	ROUND(AVG(todep), 2) AS avg_dep_score,
	MIN(todep) AS min_dep_score,
	MAX(todep) AS max_dep_score
FROM students;

Repeat the calculation of aggregates by only taking in values wherein the type of student is international.

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DataFrameas
dep_score_aggs_for_inter_studs
variable
-- Aggregates for depression score of international students
SELECT
	COUNT(*) AS counts,
	SUM(todep) AS total_dep_score,
	ROUND(AVG(todep), 2) AS avg_dep_score,
	MIN(todep) AS min_dep_score,
	MAX(todep) AS max_dep_score
FROM students
WHERE inter_dom = 'Inter';
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DataFrameas
tosc_score_agss_for_inter_studs
variable
-- Aggreagates for social connectedness score of international students
SELECT
	COUNT(*) AS counts,
	SUM(tosc) AS total_tosc_score,
	ROUND(AVG(tosc), 2) AS avg_tosc_score,
	MIN(tosc) AS min_tosc_score,
	MAX(tosc) AS max_tosc_score
FROM students
WHERE inter_dom = 'Inter';
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DataFrameas
toas_score_aggs_for_inter_studs
variable
-- Aggregates for acculturative stress score of international students
SELECT
	COUNT(*) AS counts,
	SUM(toas) AS total_toas_score,
	ROUND(AVG(toas), 2) AS avg_toas_score,
	MIN(toas) AS min_toas_score,
	MAX(toas) AS max_toas_score
FROM students
WHERE inter_dom = 'Inter';

See if length of stay impacts the average diagnostic scores rounded to two decimal places for international students, and order the results by descending order of the length of stay.

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DataFrameas
df1
variable
-- Checking on length of stay values
SELECT DISTINCT stay
FROM students;