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Record W4327593030 · doi:10.1192/bja.2023.14

Stopping inappropriate medication of children with intellectual disability, autism or both: the STOMP–STAMP initiative

2023· article· en· W4327593030 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBJPsych Advances · 2023
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsIntellectual disabilityAutismPsychiatryPosition statementMedicineAntipsychoticPediatricsFamily medicineSchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

SUMMARY Children with intellectual disability are often prescribed psychotropic medication to manage behaviours that challenge. Unfortunately, many receive medication with potentially serious long-term side-effects that has been prescribed inappropriately or for longer than is necessary. NHS England launched STOMP (stopping the over-medication of people with intellectual disability, autism or both with psychotropic medicines) in 2016 to reduce the inappropriate prescribing in adults. This was broadened to include children in 2018 by the addition of STAMP (supporting treatment and appropriate medication in paediatrics). In this article we review the rationale for STOMP–STAMP, highlight the Royal College of Psychiatrists’ position statement on STOMP–STAMP and give clinical advice for psychiatrists who treat children with intellectual disability, autism and/or attention-deficit hyperactivity disorder (ADHD). Importantly, it is essential to consider that ADHD may have been missed and that by diagnosing and treating it, the need for inappropriate antipsychotic medication may be reduced.

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.

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)0.001
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 score0.642
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.064
GPT teacher head0.350
Teacher spread0.286 · 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