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Record W2991497342 · doi:10.1017/s0954579419001342

Psychophysiological influences on personality trajectories in adolescent females exposed to child maltreatment

2019· article· en· W2991497342 on OpenAlexafffund
Raha Hassan, Harriet L. MacMillan, Masako Tanaka, Louis A. Schmidt

Bibliographic record

VenueDevelopment and Psychopathology · 2019
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsPsychologyNeuroticismExtraversion and introversionVagal tonePersonalityTemperamentDevelopmental psychologyPoison controlInjury preventionClinical psychologyBig Five personality traitsAutonomic nervous systemMedical emergencyHeart rateMedicineSocial psychologyBlood pressure

Abstract

fetched live from OpenAlex

Although child maltreatment is a major public health concern, which adversely affects psychological and physical development, we know relatively little concerning psychophysiological and personality factors that may modify risk in children exposed to maltreatment. Using a three-wave, short-term prospective design, we examined the influence of individual differences in two disparate psychophysiological measures of risk (i.e., resting frontal brain electrical activity and respiratory sinus arrhythmia) on the trajectories of extraversion and neuroticism in a sample of female adolescents (N = 55; M age = 14.02 years) exposed to child maltreatment. Adolescents exposed to child maltreatment with relatively higher left frontal absolute alpha power (i.e., lower brain activity) at rest exhibited increasing trajectories of extraversion, and adolescents exposed to child maltreatment with relatively lower respiratory sinus arrhythmia at rest displayed increasing trajectories of neuroticism over 1 year. Individual differences in psychophysiological measures indexing resting central and peripheral nervous system activity may therefore differentially influence personality characteristics in adolescent females exposed to child maltreatment.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.050
GPT teacher head0.313
Teacher spread0.263 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2019
Admission routes2
Has abstractyes

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