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Record W2781984705 · doi:10.14264/uql.2017.627

Scientific analysis of personality and individual differences

2006· article· en· W2781984705 on OpenAlexaboutno aff
Gregory John Boyle

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisMultivariate statisticsContext (archaeology)Exploratory factor analysisStructural equation modelingPersonalityCognitionVariance (accounting)Cognitive psychologyPsychometricsSocial psychologyApplied psychologyDevelopmental psychologyStatisticsMathematics

Abstract

fetched live from OpenAlex

This thesis concerns the scientific analysis of individual differences in human psychological functioning (spanning three decades from 1975 onwards). A key aspect of the work (about 50%) has been the taxonomic delineation of psychological constructs relating to cognitive abilities, personality traits (normal and abnormal), motivation dynamic traits, and emotional (mood) states within the framework of the Cattellian Psychometric Model (CPM). The research has been empirical, using a combination of multivariate experimental and quasi-experimental designs, although some critical reviews and integrative position papers have also been generated. Simplifying the taxonomy of psychological constructs was demonstrably needed since the CPM included no fewer than 92 primary factors -- far too many for practical utility. Accordingly, a sustained, programmatic sequence of exploratory and confirmatory factor-analytic studies was conducted over many years to elucidate a reduced number of broad factors that would have greater utility for psychological measurement, test construction and professional practice (other multivariate statistical procedures such as canonical correlation analysis, multiple regression analysis, discriminant function analysis, multidimensional scaling, multivariate analysis of variance, and structural equation modelling were employed, as required). The 92 primary CPM factors were reduced down to 29 broad factors (a 68% reduction). The resultant Boyle Psychometric Model (BPM), while more concise, still retained excellent specificity for detailed psychological measurement.A second key aspect of the work (also about 50%) has been the generation of original findings in important applied psychological areas. Thus, several empirical studies investigated the application of psychometric measures within the educational psychology context, where non-cognitive psychological variables were found to influence acquisition and retrieval of cognitive information under stressful conditions, highlighting mood-state dependent effects. Also, sports participation enhanced students' positive mood states; and for females at secondary school, academic performance was influenced differentially, depending on menstrual-cycle phase. Empirical studies into clinical/medical/health psychology all had a common underlying theme of using psychometric tests to generate practical findings useful for professional psychologists. Thus, recommendations for enhancing the psychometric adequacy of the McGill Pain Questionnaire (MPQ) were proposed in light of many misclassified pain descriptors. Personality-Stress Inventory (PSI) data showed that personality, stress and constitutional predisposition acted synergistically to produce significantly higher mortality rates among former concentration camp inmates. A 20- year prospective study showed that psychological self-regulation significantly influenced the adverse effects of alcohol on health. A 15-year prospective intervention study revealed that personality and stress acted synergistically as risk factors for breast cancer (prophylactic benefits of autonomy training also were demonstrated). Likewise, analyses of Australian Twin Registry data revealed significantly increased hypertension when personality, stress and lifestyle variables acted synergistically. An Icelandic epidemiological study showed that social anxiety phobias accounted for most variance (related to phobias). Differential Emotions Scale (DES-IV) data revealed significantly elevated negative mood states around time of menstruation (for depressed women). As well, General Health Questionnaire (GHQ-28), Profile o f Mood States (POMS), Eysenck Personality Questionnaire (EPQ-R) and MDQ data showed that peri-menopausal women on hormone replacement therapy (HRT) reporte'd significantly reduced negative moods and symptoms than untreated controls (MDQ structure was validated in a separate study via exploratory, congeneric and confirmatory factor analyses).In summary, a major reduction in number of taxonomic psychological constructs has been achieved through the systematic application of factor analysis. In future work, it is planned to construct a comprehensive set of modern psychometric instruments based on the reduced set of factors that has been elucidated. Specifically, it is intended to construct objective test measures, thereby avoiding the serious drawback of item-transparent, self-report questionnaires, currently so prevalent within the personality assessment field. As well, several empirical studies have investigated a wide variety of psychometric instruments, with the aim of generating practical findings useful for professional psychologists. Thus, this thesis not only summarises an extensive body of past research efforts, but also provides the point of departure for significant future works, involving improved psychometric test construction.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.024
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.061
GPT teacher head0.345
Teacher spread0.284 · 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

Citations56
Published2006
Admission routes1
Has abstractyes

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