DEVELOPMENT, CROSS-CULTURAL ADAPTATION PROCESS AND PRELIMINARY VALIDATION OF THE ITALIAN VERSION OF THE NEPEAN DYSPHORIA SCALE
Bibliographic record
Abstract
Objectives \nDysphoria is a complex emotional state that is prevalent in the \nclinical setting but very vague in its precise meaning. The aim of \nthis study was to develop and validate the Italian version of the \nNepean Dysphoria Scale (NDS-I), a self-report questionnaire \ndeveloped to measure the severity of dysphoria. \nMethods \nThe NDS was translated into Italian and subjected to a crosscultural \nadaptation process according to standard guidelines. \nThe scale was then administered to 132 psychology students, \ntogether with other conceptually similar (Beck Depression Inventory \nII, Dysfunctional Attitude Scale – Form A, Toronto Alexithymia \nScale) and conceptually different (Anxiety Sensitivity \nIndex – 3) instruments. \nResults \nThe NDS-I demonstrated excellent internal consistency (Cronbach \nα = 0.949). Factor analysis confirmed four factors related \nto irritability, discontent, interpersonal resentment and surrender. \nThere were medium to strong correlations between the \nscores on the NDS-I and its subscales and the scores on the \nBeck Depression Inventory II, and weak to medium but still significant \ncorrelations with the scores on the other instruments. \nConclusions \nThe NDS-I has good psychometric properties, thus supporting \nthe validity of the original scale. Further research in clinical \nsamples is needed to test it as a tool for routine clinical practice.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".