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Record W2903341026 · doi:10.5964/ejop.v14i4.1450

The prospective association between the Five Factor personality model with health behaviors and health behavior clusters

2018· article· en· W2903341026 on OpenAlexaff
Chelsea Joyner, Ryan E. Rhodes, Paul D. Loprinzi

Bibliographic record

VenueEurope’s Journal of Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsConscientiousnessAgreeablenessExtraversion and introversionPsychologyPersonalityOpenness to experienceBig Five personality traitsClinical psychologyHierarchical structure of the Big FiveHealth psychologyPublic healthMedicineSocial psychology

Abstract

fetched live from OpenAlex

To examine the prospective association of personality with individual behavior, multibehavior and clustered health behavior profiles. A prospective study design was employed. Two hundred young adults provided baseline data and 126 (mean age: 21.6 yrs) provide complete data for a 5-month follow-up assessment (63% response rate). Personality and health behaviors (and covariates) were assessed via validated questionnaires. A multibehavior index variable was created ranging from 0-5; two separate health behavior cluster indices were created, including high (4-5 behaviors) vs. low (2 or fewer) behavior adoption and an energy balance cluster (MVPA and diet). When examining MVPA as a continuous variable, the personality trait conscientiousness was prospectively associated with MVPA and a healthy diet. Extraversion was prospectively associated with high (vs. low) behavioral clustering (OR = 1.18; 95% CI: 1.00-1.40) and conscientiousness was prospectively associated with energy balance clustering (OR = 1.09; 95% CI: 1.01-1.17). Extraversion, conscientiousness, openness to experience, and agreeableness were associated with select health-related behaviors. Further, extraversion and conscientiousness were associated with health behavior clustering.

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)0.002
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 score0.044
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.058
GPT teacher head0.405
Teacher spread0.348 · 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

Citations27
Published2018
Admission routes1
Has abstractyes

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