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Record W4399053485 · doi:10.1080/03004430.2024.2356241

Early detection of mental disorders in child psychiatry: the accuracy of parental concerns

2024· article· en· W4399053485 on OpenAlexaff
Florence Valade, Marie‐Julie Béliveau, Chantale Breault, Fannie Labelle

Bibliographic record

VenueEarly Child Development and Care · 2024
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsHôpital Rivière-des-PrairiesCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité de Montréal
Fundersnot available
KeywordsMedical diagnosisPsychologyChild and adolescent psychiatryLogistic regressionPredictive valuePsychiatryPredictive validityClinical psychologyMedicine

Abstract

fetched live from OpenAlex

This study examines the reliability of parental concern (PC) as an indicator for mental disorders in preschool-aged children in a clinical setting, aiming to establish sensitivity and specificity, evaluate PC’s predictive value for specific diagnoses, and explore the influence of child age on predictions. The sample comprises 574 children referred to child psychiatry services (mean age 47 months, 73% boys). Analyses of sensitivity and specificity for five distinct PC were conducted, while logistic regressions explored the predictive value of PC for corresponding diagnoses, accounting for child age. Language-related concerns emerged as the most frequent and accurate. Sensitivity ranged from 7% to 72%, while specificity ranged from 57% to 97%. PC demonstrated predictive validity for their corresponding diagnoses, except for motor disorders. Child age did not substantially influence these predictions. Findings suggest that systematically incorporating PC into the assessment process for preschool-aged children consulting in child psychiatry 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.544

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)0.0000.000

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 head0.009
GPT teacher head0.255
Teacher spread0.247 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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