MétaCan
Menu
Retour à la cohorte
Enregistrement W2781984705 · doi:10.14264/uql.2017.627

Scientific analysis of personality and individual differences

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

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomainePsychology
ThématiqueEducation, Achievement, and Giftedness
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsychologyConfirmatory factor analysisMultivariate statisticsContext (archaeology)Exploratory factor analysisStructural equation modelingPersonalityCognitionVariance (accounting)Cognitive psychologyPsychometricsSocial psychologyApplied psychologyDevelopmental psychologyStatisticsMathematics

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,061
Tête enseignante GPT0,345
Écart entre enseignants0,284 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations56
Publié2006
Routes d'admission1
Résumé présentoui

Explorer davantage

Même sujetEducation, Achievement, and GiftednessTravaux en français237 207