Power BI / FIG. D9 · EDUCATION

Student Mental Health

What drives depression among students? 27,901 records point to pressure and circumstance more than family history.

SOURCE
Public student mental health dataset
DATA
27,901 student records
DEPRESSION RATE
58% overall
BUILT WITH
Power Query · DAX
Student Mental Health Power BI report, first page
FIG. D9 · The pressure cooker page

01 · THE QUESTION

Is student depression about who they are, or what they face?

The project set out to find the root causes behind a high depression rate and turn them into actions a university could take.

  • Q1How strongly do academic pressure and financial stress relate to depression?
  • Q2What role do sleep and other lifestyle signs play?
  • Q3How strong a warning sign is a history of suicidal thoughts?
  • Q4Does family history matter as much as current circumstances?

02 · THE DATA & CLEANING

From raw files to clean tables

One table of 27,901 students with academic pressure, financial stress, sleep duration, study habits, family history and a depression flag.

  • a.Financial stress was stored as text with "?" values; it was cleaned, then converted to whole numbers.
  • b.Sleep duration had stray quote marks; it was cleaned into a Sleep Group column.
  • c.A Sleep Rank (1 to 4) was added so sleep can be ordered and plotted.

03 · THE DATA MODEL

One fact table, described by its look-ups

FACT Student records
DIMENSIONS
  • Academic pressure
  • Financial stress
  • Sleep group
  • Family history

04 · REPORT PAGES

What's in the report

  1. P1The pressure cookerEnvironmental stress: depression rate by academic pressure and by financial stress level.
  2. P2The warning signsLifestyle and indicators: sleep groups and history of suicidal thoughts.
  3. P3Circumstance vs historyFamily history compared with current pressures, and a risk view for students facing several stresses at once.

05 · FINDINGS

Key findings

  • 58% of students in the data are flagged as depressed.
  • Academic pressure is the strongest predictor: 86% at the highest level versus 19% at the lowest.
  • Financial stress follows the same pattern: 81% versus 32%.
  • Less sleep, more risk: 65% for under 5 hours versus 51% for over 8 hours.
  • A history of suicidal thoughts is the strongest single flag: 79% versus 23%.
  • Family history matters less than expected: 61% versus 56%.

06 · RECOMMENDATIONS

What to do next

  1. 01Start proactive outreach for students who score high on several risk factors at once.
  2. 02Fund programmes that reduce financial stress.
  3. 03Add sleep screening and support to wellness services.

07 · TECHNICAL CHALLENGES

Problems solved along the way

  • CHALLENGE 1Messy data typesKey columns mixed text and numbers and contained stray characters. Power Query cleaned and retyped them before any analysis.
  • CHALLENGE 2Showing every studentPower BI aggregates by default. Using the Sleep Rank and the record ID on the scatter chart shows all 27,000+ students as separate points, so clusters are visible.

See it for yourself.

Open the live report →