Welcome to Psychiatryai.com: Latest Evidence - RAISR4D

Perceived stress and academic achievement among medical students with different chronotypes: a cross sectional study on first year medical students from India

BMC Med Educ. 2025 May 18;25(1):723. doi: 10.1186/s12909-025-07281-w.

ABSTRACT

BACKGROUND: Chronotype, which denotes an individual’s preference for morning or evening activity patterns, has been linked to variations in cognitive performance, sleep behavior, and stress levels. This study investigates the association between chronotype, perceived stress, and academic performance among first-year medical students.

METHODS: A cross-sectional descriptive study was conducted among 148 medical students at a private university. Chronotype was assessed using the Munich Chronotype Questionnaire (MCTQ), and perceived stress was measured using the Perceived Stress Scale (PSS). Academic performance was categorized into “Excellent” (marks > 65%) and “Average” (marks < 55%). Statistical analyses included independent t-tests, chi-square tests to evaluate differences and associations.

RESULTS: Morning chronotypes demonstrated significantly higher academic performance, with 49.1% in the “Excellent” group compared to 29% of Evening chronotypes (p =.03). Perceived stress scores were significantly higher among Evening chronotypes (24.9 ± 12.1) than Morning chronotypes (20.7 ± 9.3, p =.028). Furthermore, Evening chronotypes exhibited longer sleep latency (41.17 ± 13.35 min vs. 14.49 ± 12.14 min, p <.001) and greater variability in weekend sleep schedules (p <.001). Gender differences in stress and academic performance were minimal and not statistically significant.

CONCLUSION: Chronotype significantly affects academic performance and stress levels among medical students, with Morning types performing better academically experiencing less stress. Tailored strategies like flexible scheduling and sleep hygiene promotion can help Evening chronotypes overcome challenges, improving academic outcomes and psychological well-being.

PMID:40383776 | DOI:10.1186/s12909-025-07281-w

Document this CPD

AI-Assisted Evidence Search

Share Evidence Blueprint

QR Code

Search Google Scholar

close chatgpt icon
ChatGPT

Enter your request.

Psychiatry AI: Real-Time AI Scoping Review (RAISR4D)