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Record W4304762085 · doi:10.3390/children9101547

Internalizing–Externalizing Comorbidity and Impaired Functioning in Children

2022· article· en· W4304762085 on OpenAlexafffund
Megan Dol, Madeline Reed, Mark A. Ferro

Bibliographic record

VenueChildren · 2022
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Waterloo
FundersHamilton Health Sciences
KeywordsComorbidityNational Comorbidity SurveyPsychosocialMental healthPsychiatryClinical psychologyPsychologyExternalizationMedicineDistress

Abstract

fetched live from OpenAlex

BACKGROUND: The comorbidity of mental illnesses is common in child and adolescent psychiatry. Children with internalizing-externalizing comorbidity often experience worse health outcomes compared to children with a single diagnosis. Greater knowledge of functioning among children with internalizing-externalizing comorbidity can help improve mental health care. OBJECTIVE: The objective of this exploratory study was to examine whether internalizing-externalizing comorbidity was associated with impaired functioning in children currently receiving mental health services. METHODS: The data came from a cross-sectional clinical sample of 100 children aged 4-17 with mental illness and their parents recruited from an academic pediatric hospital. The current mental illnesses in children were measured using the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID), and the level of functioning was measured using the World Health Organization Disability Assessment Schedule (WHODAS) 2.0. Linear regression was used to estimate the association between internalizing-externalizing comorbidity and level of functioning, adjusting for demographic, psychosocial, and geographic covariates. RESULTS: = 0.049) were associated with worse functioning in children. CONCLUSIONS: Health professionals should be mindful that children with internalizing-externalizing comorbidity may experience worsening functioning that is disruptive to daily activities and should use this information when making decisions about care. Given the exploratory nature of this study, additional research with larger and more diverse samples of children is warranted.

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 categoriesInsufficient 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 score0.013
Threshold uncertainty score0.999

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)0.0020.000

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 head0.018
GPT teacher head0.264
Teacher spread0.246 · 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

Citations13
Published2022
Admission routes2
Has abstractyes

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