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Record W4323270120 · doi:10.1080/02699052.2023.2184871

Association between pediatric TBI and mental health and substance use disorders: A scoping review

2023· review· en· W4323270120 on OpenAlexaff
Nasrin Adams, Danielle Dawson, Mark Hutchison, Peter Selby

Bibliographic record

VenueBrain Injury · 2023
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsYork UniversityUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsMental healthTraumatic brain injuryMedicineSubstance usePsychiatryConfoundingMEDLINEClinical psychologyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: The relationship between pediatric Traumatic Brain Injury (TBI) and long-term mental health and substance use disorders is not well known, resulting in inadequate prevention and management strategies. The aim of this scoping review is to review the evidence on pediatric TBI and the development of mental health disorders and substance use later in life and to identify gaps in the literature to inform future research. METHODS: We searched multiple databases for original articles published between September 2002 and September 2022 on TBI-related mental health and/or substance use disorders in children and youth. Two independent reviewers performed the screening using Arksey and O'Malley and Levac et al.'s scoping review framework. RESULTS: A total of six papers are included in this scoping review. Studies included are comprised of cross-sectional and prospective longitudinal cohort studies. DISCUSSION: A correlation between pediatric TBI and development of certain mental health disorders and substance use is suggested, although much of the current evidence is mixed and does not account for confounding variables. Future studies should aim to closely examine these links and identify modifiers that can influence these relationships.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.523
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.188
GPT teacher head0.458
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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations2
Published2023
Admission routes1
Has abstractyes

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