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Record W2124463231 · doi:10.1098/rstb.2008.0030

Understanding development and prevention of chronic physical aggression: towards experimental epigenetic studies

2008· review· en· W2124463231 on OpenAlexaff
Richard E. Tremblay

Bibliographic record

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2008
Typereview
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité de MontréalChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsPsychological interventionAggressionDevelopmental psychopathologyBiopsychosocial modelMedicineEpigeneticsIntervention (counseling)PsychologyDevelopmental psychologyPsychopathologyClinical psychologyPsychiatryBiology

Abstract

fetched live from OpenAlex

The aim of this paper was to highlight how developmental psychopathology, epigenetics and prevention experiments are starting to blend together to explain the developmental causes of chronic physical aggression (CPA) and, more importantly, to help prevent CPA and its associated physical, mental and social problems. After defining the keywords (prevention, chronic and physical aggression), a selected review of published studies is used to answer the following four questions: when should we attempt to prevent onset of CPA? What are the risk factors for CPA? Have early childhood interventions been shown to prevent CPA? Can early preventive interventions benefit from epigenetic studies? The last section of this paper gives two examples of experimental prevention designs that integrate present knowledge of CPA development, risk factors, early childhood preventive interventions and epigenetic programming of brain development during pregnancy and early childhood. I conclude that randomized control trials of preventive interventions during pregnancy and early childhood with a specific focus on epigenetic effects are the research design most likely to advance our understanding of the biopsychosocial mechanisms that lead to CPA, and the only research design that can identify effective interventions for preventing the development of CPA.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.417
GPT teacher head0.432
Teacher spread0.015 · 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 designOther design
Domainnot available
GenreReview

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

Citations74
Published2008
Admission routes1
Has abstractyes

Explore more

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