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Record W4311672009 · doi:10.1708/3922.39074

Validation of the Italian version of the Northoff Catatonia Rating Scale

2022· article· en· W4311672009 on OpenAlexaff
Nicola Meda, Irene Recchia, Argentina Guaglianone, Daniele Olivo, Georg Northoff, Marco Solmi, Giorgio Pigato, Fabio Sambataro

Bibliographic record

VenueRivista di psichiatria · 2022
Typearticle
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsOttawa HospitalRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsCatatoniaRating scaleClinical psychologyPsychomotor learningPsychiatryPsychologyPsychomotor retardationDSM-5MedicineSchizophrenia (object-oriented programming)Developmental psychologyPathologyAlternative medicine

Abstract

fetched live from OpenAlex

PURPOSE: Catatonia is a psychomotor syndrome characterized by heterogeneous motor, behavioral and affective alterations, and, in some cases, neurovegetative abnormalities that can be life-threatening. Although the prevalence estimates of catatonia are 10-20% of the hospitalized population, its clinical recognition remains a challenge for most clinicians. Differently from other catatonia rating scales, the Northoff Catatonia Rating Scale (NCRS) also evaluates the affective alterations that patients experience during catatonia and thus provides a more inclusive assessment of the alterations associated with this condition. To provide clinicians with a valuable tool for diagnosis, we translated the NCRS in Italian and validated it on a sample of 52 hospitalized patients with psychiatric disorders. METHODS: An Italian version of the NCRS was prepared using the forward-backwards translation from English and administered to a sample of 52 in-patients (age 46.9±2.37 years). The inter-rater reliability, score correlations, internal coherence and decision statistics were computed. RESULTS: The inter-rater agreement was higher for the motor subscale (100% agreement) than for the behavioral (94%) or affective subscales (92.3%). The inter-rater agreement was 100% for the diagnosis of catatonia. The NCRS correctly identified all patients with catatonia according to DSM-5 (sensitivity= 100%) and had a specificity of 88.9%, and its subscale scores were highly inter-correlated. CONCLUSIONS: This validation shows that the NCRS yields a good accuracy in diagnosing catatonia and high inter-rater reliability. Moreover, the high correlation between its subscales supports the view that catatonia is a multi-faceted truly psycho-motor syndrome. In conclusion, the validation and Italian translation of the NCRS provides the clinicians with a helpful tool for diagnosing catatonia which is easy to use and assesses the full psychomotor complexity of the syndrome.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.293

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.234
Teacher spread0.228 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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