Bibliographic record
Abstract
OBJECTIVE: To present the psychometric properties of the Nepean Dysphoria Scale (NDS), the first instrument developed to measure the severity of dysphoria. METHOD: The NDS was administered to 134 university students and its characteristics were examined. The structure of the scale was investigated using exploratory factor analysis. Convergent and divergent validity were examined by investigating the associations between the NDS and its subscales with other conceptually similar (Beck Depression Inventory II, Dysfunctional Attitude Scale-Form A and Toronto Alexithymia Scale) and conceptually distinct (Anxiety Sensitivity Index) instruments. RESULTS: The 24-item NDS demonstrated excellent internal consistency. A four-factor solution was derived, with factors pertaining to irritability, discontent, surrender and interpersonal resentment. There were medium to strong correlations between the NDS and its subscales and depressive symptoms as measured by the Beck Depression Inventory II. The NDS and its subscales showed weaker, but still significant, correlations with Dysfunctional Attitude Scale-Form A, Toronto Alexithymia Scale and Anxiety Sensitivity Index. CONCLUSIONS: The study suggests that the NDS has good psychometric properties. Further research would more firmly establish the NDS as a valid measure of the complex emotional state of dysphoria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".