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Record W2164051356 · doi:10.1139/jpn.0832

A new, female-specific irritability rating scale

2008· article· en· W2164051356 on OpenAlexaffvenue
L. Ingeborgh van den Born, Gideon Koren, Elizabeth Lin, Meir Steiner

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2008
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsSt. Joseph’s Healthcare HamiltonCentre for Addiction and Mental HealthUniversity of TorontoMcMaster University
Fundersnot available
KeywordsIrritabilityRating scaleCronbach's alphaPsychologyClinical psychologyMoodAngerPsychiatryPsychometricsDevelopmental psychologyAnxiety

Abstract

fetched live from OpenAlex

OBJECTIVE: Irritability is a prominent symptom in the spectrum of female-specific mood disorders, and in some women, irritability is serious enough to disrupt their lives and warrant treatment. The objective of this research was to develop a new, female-specific state measure of irritability. METHODS: We constructed self-rating and observer rating scales using items derived from spontaneous descriptions of irritability by women with mood disturbances related to the menstrual cycle, childbearing or menopause. Following a pretest, the scales were shortened to the core items of irritability (annoyance, anger, tension, hostility, sensitivity to noise and touch) and tested on a new cohort of patients. RESULTS: The 14-item Self-Rating Scale and the 5-item Observer Rating Scale showed evidence for internal consistency (Self-Rating: n = 36 patients, Cronbach's alpha = 0.9257, mean interitem correlation = 0.4690; Observer Rating: Cronbach's alpha = 0.7418, mean interitem correlation = 0.3616), Self-Rating test-retest reliability (n = 29 patients, r(s) = 0.704, p = 0.01) and interrater reliability (n = 20 patients; tau(b) = 1.000, p = 0.001). CONCLUSION: This new, female-specific scale for rating irritability has the potential to further the evaluation of this prominent symptom cluster and increase specificity in clinical assessments of emotional disturbances related to reproductive cyclicity in women.

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 score0.013
Threshold uncertainty score0.234

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 head0.045
GPT teacher head0.316
Teacher spread0.271 · 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

Citations27
Published2008
Admission routes2
Has abstractyes

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