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Record W4289525180 · doi:10.1007/s10578-022-01393-w

The Tutor of Resilience Program with Children Who Have Experienced Maltreatment: Mothers’ Involvement Matters

2022· article· en· W4289525180 on OpenAlexaff
Francesca Giordano, C. Taurelli Salimbeni, Philip Jefferies

Bibliographic record

VenueChild Psychiatry & Human Development · 2022
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsDalhousie University
FundersUniversità Cattolica del Sacro Cuore
KeywordsAngerClinical psychologyPsychological interventionAnxietyPsychological resiliencePsychologyIntervention (counseling)DistressDepression (economics)MedicinePsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Resilience is a dynamic process involving the presence and interaction of personal and environmental factors that modify the impact of adversity. Resilience-building interventions are therefore important for improving trauma-related outcomes in children and caregivers exposed to adversity. This study examines the impact of the Tutor of Resilience (TOR) program on beneficiaries' trauma-related symptoms and on mother-child interactions in a group of children exposed to maltreatment (N = 186; mean age = 11.95; SD = 2.50). Assessments were completed at baseline and post-intervention. RM-ANOVAs indicated significant improvements for most trauma symptoms (anxiety, anger, post-traumatic stress, and disassociation, but not depression) in the intervention group relative to a control group (N = 88; mean age = 10.76; SD = 2.57), and indicated further improvements to anxiety and dissociation for the intervention group when mothers were involved. Mother-child interactions also improved over time, as did their overall trauma symptoms and distress. Findings support the effectiveness of the ToR, especially when involving mothers.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.272
Teacher spread0.259 · 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 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

Citations5
Published2022
Admission routes1
Has abstractyes

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