Adapted and validated psychological health scale in the doctoral context
Bibliographic record
Abstract
Despite the growing number of studies on the psychological health of doctoral students, interest seems to be focused on their psychological distress. This may be due to the lack of available tools contextualized to doctoral work to measure both psychological distress and well-being, which represent two indissociable aspects of psychological health. Since such a tool appears essential for future empirical research that will attempt, for example, to clarify the predictors and consequences of this construct, the present study aimed to adapt an existing work- related psychological health scale (Gilbert et al., 2011) into a short, doctoral- contextualized version, and to examine its psychometric qualities. Four indicators of construct validity (exploratory, confirmatory, convergent, and predictive) and two indicators of reliability (internal consistency and temporal stability) were examined among two samples including 380 and 377 doctoral students, respectively. A short unidimensional scale comprising eight items (four items measuring the distress pole and four items measuring the well-being pole) with good psychometric qualities was obtained, supporting its use in future studies.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".