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Record W2057452070 · doi:10.1521/pedi.2009.23.5.447

A Five-Factor Model Description of Depressive Personality Disorder

2009· article· en· W2057452070 on OpenAlexaff
David D. Vachon, Martin Sellbom, Andrew G. Ryder, Joshua D. Miller, R. Michael Bagby

Bibliographic record

VenueJournal of Personality Disorders · 2009
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychologyConceptualizationPersonalityPopulationBig Five personality traitsClinical psychologyPersonality Assessment InventoryAnxietyAssertivenessConstruct (python library)Developmental psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

This investigation extends previous work on Five-Factor Model (FFM) personality disorder profiles. Specifically, a FFM expert consensus prototype for Depressive Personality Disorder (DPD) using the 30 facets of the NEO Personality Inventory-Revised (NEO PI-R) was developed. Initial validation of this prototype in a psychiatric population employed several clinical scales. When combined with trait information yielded by criteria translation and empirical approaches, the composite FFM profile emphasized several facets that represent the core components of DPD. In addition to several traits represented by the current DSM conceptualization of DPD, such as depressiveness, anxiousness, self-consciousness, and low tendermindedness, the composite profile was also characterized by several unrepresented traits, such as high modesty and low positive emotionality, warmth, assertiveness, trust, and achievement striving. Future definitions of depressive personality, conceptualized either as a DSM-V personality disorder or as a multifaceted construct, should consider these additional traits.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.326
Teacher spread0.291 · 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.

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
Published2009
Admission routes1
Has abstractyes

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