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Record W4318069739 · doi:10.1037/pla0000195

Play completion predicts fewer child psychological difficulties: A longitudinal study of mentalizing processes.

2023· article· en· W4318069739 on OpenAlexaff
Lina Normandin, Jordan Bate, Michaël Bégin, Peter Fonagy, Karin Ensink

Bibliographic record

VenueInternational Journal of Play Therapy · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPsychologyMentalizationLongitudinal studyDevelopmental psychologyPsychotherapistClinical psychology

Abstract

fetched live from OpenAlex

Play therapy is widely used with children, including children who experienced sexual abuse. This longitudinal study examined whether more pretend play completion (PPC) at Time 1 predicted fewer child difficulties when this was assessed 3 years later at Time 2. Participants were 91 children (aged 3–8 at Time 1), including 51 children who experienced sexual abuse (child sexual abuse [CSA]). Play was coded with the Children’s Play Therapy Instrument, and child psychological difficulties were assessed with the Child Behavior Checklist. More PPC at Time 1 predicted fewer child psychological difficulties 3 years later at Time 2. This was the case in children who had experienced CSA as well as the comparison group, showing that PPC is predicts better psychological adjustment in both abused and nonabused children. The study provides the first longitudinal evidence of the important role of pretend play narrative completion in predicting less internalizing and externalizing difficulties. The findings have important clinical implications for play therapists. It suggests that interventions that encourage children to elaborate and complete their play narratives could facilitate agency and psychological adjustment, as well as recovery after trauma. This is in line with the idea that through play children discover that they can “play with reality” and gain control over how they tell their stories. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.776

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)0.0010.000

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 head0.069
GPT teacher head0.370
Teacher spread0.302 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

Explore more

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