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Record W2034402901 · doi:10.12927/hcq.2011.22360

Improving Mental Health Outcomes for Children and Youth Exposed to Abuse and Neglect

2011· article· en· W2034402901 on OpenAlexaboutno aff
Ene Underwood

Bibliographic record

VenueHealthcare Quarterly · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
Fundersnot available
KeywordsNeglectMental healthIntervention (counseling)WelfarePsychiatryMedicineChild abuseChild neglectPsychologyNursingSuicide preventionPoison controlEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

Children exposed to abuse and neglect are at significantly higher risk of developing mental health conditions than are children who grow up in stable families. Multiple complexities arise in supporting the needs of these vulnerable children: complex family circumstances; the need to balance the goals of protecting the children and strengthening family connections; and the involvement of multiple players from biological families to foster parents to case workers to children's mental health professionals. This article draws on case studies, the literature and proven initiatives that have been implemented in a number of children's aid societies in Ontario to demonstrate four strategies that can improve mental health outcomes for children exposed to abuse and neglect. These strategies are increasing admission prevention and early intervention to support at-risk youth at home; supporting transitions from intensive residential treatment back to the community; ensuring youth transitioning to the adult system have the supports they need; and increasing integration in service delivery between children's mental health and child welfare.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.994

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.304
Teacher spread0.271 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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