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Record W3000356174 · doi:10.1002/pmh.1469

Examining the predictive association of irritability with borderline personality disorder in a clinical sample of female adolescents

2020· article· en· W3000356174 on OpenAlexaff
Lisa Dyce, Roberto B. Sassi, Khrista Boylan

Bibliographic record

VenuePersonality and Mental Health · 2020
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster University
Fundersnot available
KeywordsIrritabilityBorderline personality disorderPsychologyMoodClinical psychologyPredictive valuePsychiatryMedicineInternal medicineAnxiety

Abstract

fetched live from OpenAlex

OBJECTIVES: Borderline personality disorder (BPD) is a disorder associated with emotion dysregulation and is common in clinical samples of adolescents. The identification and delineation of BPD from other disorders is important, yet methods for effectively screening for BPD are lacking. Here, we examine whether irritability can be used as a screening item for BPD in adolescents at risk for the disorder. METHODS: We assessed Diagnostic Interview for Borderline-Revised and Development of Well-Being Assessment scores in a clinical sample of female adolescents ages 12-17 (n = 78) to identify BPD and group cases into 'irritable' and 'non-irritable' mood types, respectively. We then examined the prevalence of irritability and its predictive association with BPD. RESULTS: (1) = 17.740, p < 0.001). Irritability was endorsed in all (n = 20) BPD cases (sensitivity: 100%), while in non-BPD cases (n = 58), irritability was endorsed in 27 (specificity: 53%; positive predictive value: 0.33; and negative predictive value: 1.0). CONCLUSION: Irritability is a highly sensitive screening item for BPD in adolescents. The absence of irritability in an adolescent may be an important clinical tool to rule out BPD. © 2020 John Wiley & Sons, Ltd.

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)0.003
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 score0.012
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.066
GPT teacher head0.382
Teacher spread0.316 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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