Depression symptoms in Canadian psychology graduate students: Do research productivity, funding, and the academic advisory relationship play a role?
Bibliographic record
Abstract
Depression is one of the most common psychological disorders affecting university students (Rimmer, Halikas, & Schuckit, 1982; Vazquez & Blanco, 2008); however, undergraduate students have received the majority of the research focus. The limited research available on graduate students suggests they may also be vulnerable to developing depression (Eisenberg, Gollust, Golberstein, & Hefner, 2007). The current investigation provides initial data on depression symptoms in Canadian psychology graduate students. Participants included psychology graduate students from across Canada (N 292; 87% women) who were currently enrolled in clinical, experimental, counselling, and educational programmes. Each of the participants completed the Center for Epidemiological Studies Depression Scale (CES-D; Radloff, 1977) and measures of: funding, research productivity, hours worked, and their advisory relationship. A substantial proportion of students (33%) reported clinically significant symptoms of depression (CES-D 16), with a significant minority reporting severe symptoms of depression and impairment. There were no differences in symptom reporting across programme type; however, results of regression analyses indicated that advisory relationship satisfaction and greater current weekly hours worked were significant predictors of depressive symptoms for students enrolled in experimental programmes. In contrast, depression symptoms were unrelated to funding, research productivity, hours worked, and advisory relationship satisfaction for students in all other programmes. Implications and future directions for research are discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".