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Record W4310705608 · doi:10.1521/pedi.2022.36.6.662

Construct Validity of the Dutch, English, French, and Spanish LPFS-BF 2.0: Measurement Invariance Across Language and Gender and Criterion Validity

2022· article· en· W4310705608 on OpenAlexafffund
Yann Le Corff, Antón Aluja, Gina Rossi, Mélanie Lapalme, Karine Forget, Luis F. Garcı́a, Jean‐Pierre Rolland

Bibliographic record

VenueJournal of Personality Disorders · 2022
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsPsychologyConstruct validityMeasurement invarianceCriterion validityConstruct (python library)Concurrent validityPersonalityPsychometricsMetric (unit)Test validityMental healthScale (ratio)Social psychologyClinical psychologyConfirmatory factor analysisStructural equation modelingPsychiatryStatisticsMathematicsComputer science

Abstract

fetched live from OpenAlex

, the need for short measures of the level of personality functioning has emerged, both for screening purposes and for assessing change during treatment. The Level of Personality Functioning Scale-Brief Form 2.0 (LPFS-BF 2.0) was constructed for this and has received support for its two-factor structure and criterion validity. The authors aimed to provide additional construct validity evidence for the LPFS-BF 2.0 by examining its factor structure and measurement invariance across the Dutch, English, French, and Spanish versions and across gender, and its criterion validity. Results showed that the two-factor model had a good fit to the data in the four linguistic versions. Configural and metric invariance were supported across linguistic versions and gender, while scalar invariance was partially supported. Reporting a mental health disorder and having consulted with a mental health professional were associated with higher LPFS-BF 2.0 scores.

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 score0.078
Threshold uncertainty score0.876

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.328
Teacher spread0.260 · 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

Citations32
Published2022
Admission routes2
Has abstractyes

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