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Record W2026790730 · doi:10.1521/pedi.15.3.235.19205

Personality Disorder in University Students: A Multitrait-Multimethod Matrix Study

2001· article· en· W2026790730 on OpenAlexaff
Birendra K. Sinha, David C. Watson

Bibliographic record

VenueJournal of Personality Disorders · 2001
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsMacEwan UniversityUniversity of Alberta
Fundersnot available
KeywordsMinnesota Multiphasic Personality InventoryPsychologyMillon Clinical Multiaxial InventoryPersonality disordersPersonalityClinical psychologyPersonality Assessment InventoryPsychometricsPsychiatryDiscriminant validityPersonality testTest validitySocial psychologyInternal consistency

Abstract

fetched live from OpenAlex

The present study examined the prevalence of personality disorders (PDs) in a sample of first-year university students. The three self-report measures used to assess personality disorders were the (a) Coolidge Axis II Inventory (CATI); (b) Millon Clinical Multiaxial Inventory-II (MCMI-II); and (c) Minnesota Multiphasic Personality Inventory-Personality Disorder Scale (MMPI-PD). The prevalence of PD was estimated by including the number of participants above the cut-off scores selected for each of the three PD instruments. The results indicate prevalence in the range of 0% to 16% for the males, and approximately 1% to 26% for the females. These findings generally confirm the prevalence range of 5% to 15% reported in other investigations of nonpatient samples. With few exceptions, the three tests are generally consistent in their estimates of PD prevalence of all the 11 personality disorders. The multitrait-multimethod matrix reveals that the disorders are generally positively correlated with each other on all the three tests, suggesting considerable construct overlap. Specifically, passive-aggressive and schizotypal disorders produce the most convergent correlations. On the MMPI-PD, however, schizoid is a relatively more discriminant disorder.

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)0.004
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 score0.120
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.377
Teacher spread0.350 · 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

Citations22
Published2001
Admission routes1
Has abstractyes

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