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Record W4410234295 · doi:10.18357/ijcyfs161202522340

EFFECTIVENESS OF THE GROUP TRIPLE P (POSITIVE PARENTING PROGRAM) IN AN ORPHANAGE CONTEXT IN LAHORE, PAKISTAN

2025· article· en· W4410234295 on OpenAlexvenueno aff
Amina Khalid, Alina Morawska, Karen Turner

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
FundersPunjab Educational Endowment FundUniversity of Queensland
KeywordsContext (archaeology)PsychologyGroup (periodic table)Developmental psychologyGeographyPhysicsArchaeology

Abstract

fetched live from OpenAlex

An inadequate caregiving environment in an orphanage can negatively impact children’s well-being, while a lack of specialized training can induce work-related stress and lower self-efficacy among caregivers. This study examined the effectiveness of the Group Triple P (positive parenting program) with caregivers of children in Pakistani orphanages. Fourteen caregivers across three orphanages completed self-report questionnaires and took part in Group Triple P. A repeated measures ANOVA indicated that the personal well-being of the caregivers improved following intervention. There was also a significant increase in caregivers’ parenting efficacy and a decrease in the use of dysfunctional parenting practices. The frequency and number of children’s challenging behaviors was reported to decrease significantly, along with a significant increase in warmth and reduction in negativity in caregiver–child relationships. This study was the first to implement Group Triple P in an orphanage context. The outcomes support the use of an evidence-based parenting intervention with orphanage caregivers who are in a proxy parenting role.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.036
GPT teacher head0.403
Teacher spread0.367 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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