Interventions for Students’ Well-Being at the University of Helsinki (INSIGHT): Protocol and Preliminary Descriptive Results for a Quasi-Experimental Controlled Trial of a Social Identity Intervention and Two Active Comparators
Bibliographic record
Abstract
Background: University students' mental health problems are prevalent globally, which underlines the need for accessible and cost-effective mental health services in universities. Loneliness is a key risk factor for mental health problems, and it disproportionately affects students from minority backgrounds. Therefore, addressing loneliness and fostering inclusion and equality can be crucial strategies for enhancing students' well-being. Objective: The aim of this study is to investigate a social-identity group intervention called Groups 4 Health (G4H) for university students' well-being using both quantitative and qualitative methods. Here, we present the research protocol and report preliminary descriptive findings from the study cohort. Methods: The quantitative part of the study is a 4 parallel-arm nonrandomized controlled trial aiming to recruit 600 student participants from the University of Helsinki. The experimental group, which receives the G4H intervention, includes 5 group meetings held over a 7-week period. The experimental group will be compared with 2 active comparators: groups organized by the University of Helsinki study psychologists and a 7-week online intervention course focused on well-being and study skills, and to a no-intervention control group. The primary quantitative outcomes of the study are loneliness and depression; secondary outcomes include several measures of students' well-being, academic performance, and cost-effectiveness of the intervention. Quantitative data are collected before the intervention, during the intervention (at week 3), immediately post intervention (at week 7 after baseline), and at 1- and 3-month follow-ups. The qualitative part of the study explores the challenges and opportunities related to inclusion and equality identified in the G4H intervention using observations, interviews, and focus group discussions. Results: In the preliminary findings based on the first data freeze in March 2025, we observed differences in the background characteristics between the trial arms, highlighting the need to address group selection bias. First results from the study are expected in 2026. Conclusions: If proven effective, these interventions have significant potential to improve students' well-being in both short and long term, fostering mental health and supporting academic success and future career paths.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.030 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".