Research summary
A systematic review and meta-analysis of longitudinal cohorts established a bidirectional relationship between depression and overweight/obesity, with obesity at baseline predicting later depression and depression predicting later weight gain; influencing factors were identified through subgroup analyses across age, sex, and BMI cut-off [1]. A 12-trial meta-analysis (13 contrast groups, 2,334 participants) showed internet-based CBT for depression and anxiety has a moderate-to-large mean effect (fixed-effects d = 0.40, mixed-effects d = 0.60) with significant heterogeneity, and subgroup analyses by symptom type and intervention design partially accounted for the heterogeneity [4]. A later meta-analysis of computerized treatments for adult depression (12 studies, 2,446 participants) found similar effect sizes across delivery modes and emphasised the role of personal support during the intervention [6], and a 20-trial direct-comparison meta-analysis (1,418 participants) found guided ICBT non-inferior to face-to-face CBT for psychiatric and somatic conditions [9]. A separate pooled review of computerized CBT for major depression, panic disorder, social phobia, and generalized anxiety disorder consolidated the case that CCBT is acceptable, effective, and practical at scale [8]. The WHO World Mental Health International College Student Project surveyed first-year students at 19 colleges across 8 countries to estimate prevalence of common mental disorders [2], and an earlier WHO WMH analysis compared college students (n=1,572) with same-age non-students (n=4,178) in 21 countries to quantify associations of mental disorders with college entry and attrition [5]. A global return-on-investment analysis using OneHealth modelling projected scaled-up depression and anxiety treatment in 36 countries 2016-2030 with a linear coverage increase and a 5% productivity adjustment to compute net economic returns [7]. The Supportive Accountability model, drawn from organizational psychology and CMC research, formalises why human support enhances adherence to eHealth interventions [10], and "Doing Meta-Analysis with R" provides the methodological infrastructure — including the dmetar package — used to run pooled, subgroup, meta-regression, and risk-of-bias analyses across the trials above [3].
Recent publications
- Overweight, Obesity, and DepressionDOI
- WHO World Mental Health Surveys International College Student Project: Prevalence and distribution of mental disorders.DOI
- Doing Meta-Analysis with RDOI
- Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-analysisDOI
- Mental disorders among college students in the World Health Organization World Mental Health SurveysDOI
- Internet-Based and Other Computerized Psychological Treatments for Adult Depression: A Meta-AnalysisDOI
- Scaling-up treatment of depression and anxiety: a global return on investment analysisDOI
- Computer Therapy for the Anxiety and Depressive Disorders Is Effective, Acceptable and Practical Health Care: A Meta-AnalysisDOI
- Internet-based vs. face-to-face cognitive behavior therapy for psychiatric and somatic disorders: an updated systematic review and meta-analysisDOI
- Supportive Accountability: A Model for Providing Human Support to Enhance Adherence to eHealth InterventionsDOI
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How to apply
Email Pim Cuijpers 6-12 months before your application deadline. Read several recent papers and reference specific work in your message. Use our how to email a Japanese professor guide for the proven email structure.
For applications via MEXT scholarship: see our MEXT 2027 complete guide and university-specific University Recommendation track.
External profiles
- ORCID: https://orcid.org/0000-0001-5497-2743
- OpenAlex: openalex.org
Profile compiled from public sources (Researchmap, OpenAlex, Kyoto University faculty directory). Last refreshed 2026-05. Report incorrect information.