MétaCan
Menu
Back to cohort
Record W2221800564 · doi:10.1080/13854046.2015.1061057

Neuropsychological Profile of Children, Adolescents and Adults Experiencing Maltreatment: A Meta-analysis

2015· review· en· W2221800564 on OpenAlexaff
Marjolaine Masson, Ève-Line Bussières, Caroline East‐Richard, Alexandra R-Mercier, Caroline Cellard

Bibliographic record

VenueThe Clinical Neuropsychologist · 2015
Typereview
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsCentre Jeunesse de QuebecUniversité Laval
Fundersnot available
KeywordsPsychologyNeuropsychologyCognitionNeuropsychological assessmentPoison controlMeta-analysisClinical psychologyCognitive skillDevelopmental psychologyInjury preventionPsychiatryMedicineMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: Few studies have attempted to describe the range of cognitive impairments affecting people who have experienced child maltreatment. The aim of this meta-analysis was to examine the neuropsychological profile of these people and to determine the cognitive impacts of maltreatment from childhood to adulthood. METHOD: Fifty-two publications from 1970 to 2013 were included. RESULTS: The affected cognitive domains were working memory (g = -.65), attention (g = -.63), intelligence (g = -.56) and speed of processing (g = -.49). The impact of maltreatment was greater in young children (g = -.71) and less pronounced in adults (g = -.26). CONCLUSIONS: These results suggest that exposure to maltreatment has an impact on specific cognitive processes, regardless of age.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.020
Bibliometrics0.0050.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.296
GPT teacher head0.476
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations67
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueThe Clinical NeuropsychologistSame topicChild Abuse and TraumaFrench-language works237,207