MétaCan
Menu
Back to cohort
Record W7037157236

Development, cross-cultural adaptation process and preliminary validation of the Italian version of the Nepean Dysphoria Scale

2016· article· en· W7037157236 on OpenAlexaboutno aff

Bibliographic record

VenueCINECA IRIS Institutional Research information system (University of Urbino) · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDysphoriaAlexithymiaPsychometricsBeck Depression InventoryScale (ratio)Test validityPersonality Assessment InventoryConstruct validityToronto Alexithymia ScaleInternal consistency
DOInot available

Abstract

fetched live from OpenAlex

Objectives Dysphoria is a complex emotional state that is prevalent in the clinical setting but very vague in its precise meaning. The aim of this study was to develop and validate the Italian version of the Nepean Dysphoria Scale (NDS-I), a self-report questionnaire developed to measure the severity of dysphoria. Methods The NDS was translated into Italian and subjected to a cross-cultural adaptation process according to standard guidelines. The scale was then administered to 132 psychology students, together with other conceptually similar (Beck Depression Inventory II, Dysfunctional Attitude Scale - Form A, Toronto Alexithymia Scale) and conceptually different (Anxiety Sensitivity Index - 3) instruments. Results The NDS-I demonstrated excellent internal consistency (Cronbach alpha = 0.949). Factor analysis confirmed four factors related to irritability, discontent, interpersonal resentment and surrender. There were medium to strong correlations between the scores on the NDS-I and its subscales and the scores on the Beck Depression Inventory II, and weak to medium but still significant correlations with the scores on the other instruments. Conclusions The NDS-I has good psychometric properties, thus supporting the validity of the original scale. Further research in clinical samples is needed to test it as a tool for routine clinical practice.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.271
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCINECA IRIS Institutional Research information system (University of Urbino)Same topicBotanical Studies and ApplicationsFrench-language works237,207