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Record W2737804629 · doi:10.1016/j.chiabu.2017.06.026

Relationship and community factors related to better mental health following child maltreatment among adolescents

2017· article· en· W2737804629 on OpenAlexafffund
Kristene Cheung, Tamara Taillieu, Sarah Turner, Janique Fortier, Jitender Sareen, Harriet L. MacMillan, Michael H. Boyle, Tracie O. Afifi

Bibliographic record

VenueChild Abuse & Neglect · 2017
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsMcMaster UniversityUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsMental healthPsychological interventionSuicide preventionPoison controlPsychologyOccupational safety and healthInjury preventionHuman factors and ergonomicsClinical psychologyPsychiatryNational Comorbidity SurveyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Research on factors associated with good mental health following child maltreatment is often based on unrepresentative samples and focuses on individual-level factors. To address these gaps, the present study examined the association between relationship- and community-level factors and overall mental health status among adolescents with and without a history of maltreatment in a representative sample. Data were drawn from the National Comorbidity Survey of Adolescents (NCS-A; n=10,148; data collection 2001-2004); a large, cross-sectional, nationally representative sample of adolescents aged 13-17 years from the United States. Having supportive parent and family relationships were significantly associated with good mental health (AOR ranging from 2.1 to 7.1). Positive community and school experiences were also significantly associated with good mental health (AOR ranging from 2.0 to 9.8). In most models, support from friends and siblings was not related to better mental health. Factors to be tested for efficacy in interventions targeted to adolescents with a history of child maltreatment include encouraging supportive parent and family relationships, and fostering positive community and school experiences.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
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 studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.309
Teacher spread0.280 · 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

Citations34
Published2017
Admission routes2
Has abstractyes

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