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Record W2166523999 · doi:10.1177/1073191112449857

Development and Validation of New Anxiety and Bipolar Symptom Scales for an Expanded Version of the IDAS (the IDAS-II)

2012· article· en· W2166523999 on OpenAlexaff
David Watson, Michael W. O’Hara, Kristin Naragon‐Gainey, Erin Koffel, Michael S. Chmielewski, Roman Kotov, Sara M. Stasik, Camilo J. Ruggero

Bibliographic record

VenueAssessment · 2012
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of Toronto
FundersNational Institute of Mental Health
KeywordsPsychologyAnxietyDiscriminant validityManiaClinical psychologyConvergent validitySocial anxietyDepression (economics)Bipolar disorderPsychiatryPsychometricsMoodInternal consistency

Abstract

fetched live from OpenAlex

The original Inventory of Depression and Anxiety Symptoms (IDAS) contains 11 nonoverlapping scales assessing specific depression and anxiety symptoms. In creating the expanded version of the IDAS (the IDAS-II), our goal was to create new scales assessing other important aspects of the anxiety disorders as well as key symptoms of bipolar disorder. Factor analyses of the IDAS-II item pool led to the creation of seven new scales (Traumatic Avoidance, Checking, Ordering, Cleaning, Claustrophobia, Mania, Euphoria) plus an expanded version of Social Anxiety. These scales are internally consistent and show strong convergent and significant discriminant validity in relation to other self-report and interview-based measures of anxiety, depression, and mania. Furthermore, the scales demonstrate substantial criterion and incremental validity in relation to interview-based measures of DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, fourth edition) symptoms and disorders. Thus, the expanded IDAS-II now assesses a broad range of depression, anxiety, and bipolar symptoms.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.048
GPT teacher head0.368
Teacher spread0.320 · 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 source (direct Gemma or distilled Codex), 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

Citations473
Published2012
Admission routes1
Has abstractyes

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