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Record W4390079285 · doi:10.1017/s1355617723008603

1 Psychometric comparison of the long and short forms of the Personality Assessment Inventory in a neuropsychiatric population

2023· article· en· W4390079285 on OpenAlexaff
Alanna Coady, Megan Udala, E S Concepcion, Naomi C. Nystrom, Maya Libben, Jamie Piercy, Harry B. Miller

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsPsychologyClinical psychologyPopulationPersonalityPsychometricsPsychiatryPersonality Assessment InventoryRespondentComparabilityNeuropsychologyMedicineCognitionSocial psychology

Abstract

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Objective: The Personality Assessment Inventory (PAI; Morey, 1991; 2007) is a 344 item self-report measure of personality, psychopathology, and factors affecting treatment. The PAI short form (PAI-SF) contains the first 160 items of the PAI and is often favoured as a screening tool or brief version to mitigate respondent burden and fatigue. The PAI has been psychometrically validated among numerous populations (Slavin-Mulford et al., 2012), while psychometric research on the PAI-SF is gradually emerging. The psychometric properties of the PAI-SF range from adequate to strong in psychiatric (Sinclair et al., 2009), forensic (Sinclair et al., 2010), outpatient and nonclinical (Ward et al., 2018), and stroke (Udala et al., 2020) samples. To advance research validating the PAI-SF among diverse populations, this project investigated the psychometric comparability between the PAI and the PAI-SF in a neuropsychiatric population. Based on previous literature, it was hypothesized that the PAI-SF would produce congruent results to the PAI in this sample. Participants and Methods: For this study, participant files (N=214) were collected retrospectively from short- and long-term residential psychiatric and substance use treatment facilities in Minnesota for patients with neurological and cognitive concerns referred for neuropsychological evaluation. The PAI-SF was scored using the first 160 items from a patient’s long-form PAI protocol. To determine the psychometric comparability of long- and short-forms, paired-samples t-tests, intraclass correlations, and percent agreement in clinical classification between forms were analyzed. Results: Analyses of participant data found that intra-class correlations ranged from .87 to .98 for each subscale on the PAI when compared to the PAI-SF, demonstrating good to excellent reliability between forms. Symptoms are considered clinically elevated when they exceed the clinical significance threshold for a subscale (typically a T-score of 70+). Agreement between the PAI and PAI-SF subscales in the classification of clinically elevated scores ranged from 86% to 100%. When forms did not agree, the PAI-SF was more likely to be clinically significant relative to the PAI. A comparison of subscale means between forms was examined by independent samples T-tests with a Bonferroni correction. Results revealed significant differences between the PAI and PAI-SF on one validity scale (Negative Impression Management), three clinical scales (Anxiety; Depression; Antisocial Features), and one treatment scale (Treatment Rejection). Conclusions: Results demonstrated that the PAI and PAI-SF have high reliability between forms in a neuropsychiatric population. Although mean scores differed on a small number of subscales between the PAI and PAI-SF, differences did not appear sufficiently large enough to shift clinical classifications, as the two forms performed similarly in their identification of clinically elevated scales. Findings align with previous literature and suggest that the PAI-SF may perform adequately in a neuropsychiatric population if brevity or participant burden is of concern. However, caution is warranted when making clinical decisions with the PAI-SF as more research is needed.

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)0.005
metaresearch head score (Gemma)0.012
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 score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.129
GPT teacher head0.434
Teacher spread0.305 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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