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Record W2468843769 · doi:10.18043/ncm.71.1.9

The Administration of Psychotropic Medication to Children Ages 0–4 in North Carolina: An Exploratory Analysis

2010· article· en· W2468843769 on OpenAlexaboutno aff
Alan R. Ellis

Bibliographic record

VenueNorth Carolina Medical Journal · 2010
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
Fundersnot available
KeywordsReceiptMedicaidQuarter (Canadian coin)Catchment areaMedicineMental healthMedical prescriptionDemographyEnvironmental healthGerontologyPsychiatryFamily medicineHealth careGeographyDrainage basinNursing

Abstract

fetched live from OpenAlex

BACKGROUND: The increasing use of psychotropic medication among preschool children raises concern because there are insufficient clinical guidelines and possible disparities. METHODS: This study explored published administrative data (2007-2006) on the receipt of psychotropic medication by North Carolina Medicaid enrollees ages 0-4 by mental health catchment area. Quarterly prevalence statistics were examined and potential predictors of receipt were identified for future study. RESULTS: During the study period the state's quarterly prevalence ranged from 2.3 to 3.0 recipients per 1,000 enrollees (range in catchment areas: 0.5 to 9.8). The state rate peaked at 3.0 in the third quarter of 2002 and at 2.9 in the third quarter of 2004. LIMITATIONS: The data are aggregated to a large area level and limited to Medicaid enrollees. The small number of catchment areas (36) limits the utility of statistical associations. CONCLUSIONS: Prevalence rates are high enough to deserve further exploration. Geographic variation exists. Psychotropic medication prescriptions for preschool children should be included as the state's mental health practitioners, policymakers, and planners discuss the service system and the mental health of children in our communities.

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)0.001
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 score0.047
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.303
Teacher spread0.290 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

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