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Record W2885745774 · doi:10.1177/1077559518790695

Moderating Role of the Form of Maltreatment Experienced by Children on the Effectiveness of a Parent Training Program

2018· article· en· W2885745774 on OpenAlexaffabout
Roxanne Sicotte, Marie‐Josée Letarte, Sonia Hélie, Isabelle‐Ann Leclair Mallette

Bibliographic record

VenueChild Maltreatment · 2018
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsNeglectChild abusePsychologyChild neglectPoison controlInjury preventionParent trainingSuicide preventionAgency (philosophy)Human factors and ergonomicsDevelopmental psychologyClinical psychologyOccupational safety and healthMedicinePsychiatryMedical emergencyIntervention (counseling)

Abstract

fetched live from OpenAlex

The study examines whether the form of maltreatment experienced by the child moderates the effects of a parent training program (PTP) on the probability that the child's case will be closed. This study involved 736 children on whom the Montreal child protective services (CPS) agency had an active file between 2007 and 2015. The experimental group was composed of all children with a parent who participated in the PTP Incredible Years ( n = 368). A control group was matched with the experimental group based on a propensity score. Cox regression revealed that once parents have participated in the PTP, the probability that their children's cases will be closed increases more for children being followed because of neglect than for those being followed because of emotional maltreatment. Results show that a parent's participating in a PTP is associated with an increase of the probability that his or her child's CPS case will be closed and hence with a reduction of the length of time that the child must receive protective services.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.296
Teacher spread0.275 · 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 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

Citations11
Published2018
Admission routes2
Has abstractyes

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