Social Support as a Moderator for Depressive Symptoms and Well-being During the Transition to University
Bibliographic record
Abstract
Nearly 40% of Canadian university students are depressed (Othman et al., 2019).However, strong social support may mitigate adverse outcomes for some students (Santini et al., 2015).This study examined: 1.If students who showed initial depression were more likely to experience poorer end-of-semester outcomes in well-being (i.e., continued depressive symptoms, burnout, and poor social and academic adjustment).2. If social support was a moderator for initial depression and poorer end-of-semester wellbeing.3.If seeing friends face-to-face is a stronger moderator than phone calls or text messages on end-of-semester well-being.Participants (N=461) were first-time first-year undergraduates who completed questionnaires in September and in December (N=368) of their first semester.Entering university with depressive symptoms was shown to be associated with end-of-semester depression burnout and decreased academic adjustment.Students with initially low depression and high social support had less depression in December.Question three was unsupported, well-being was unaffected by mode of communication and September depression.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".