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Record W1481180959 · doi:10.1089/cap.2014.0106

Psychotropic Medication Use Among Adolescents and Young Adults with an Autism Spectrum Disorder: Parent Views About Medication Use and Healthcare Services

2015· article· en· W1481180959 on OpenAlexafffund
Johanna Lake, Vanessa M. Vogan, Amanda Sawyer, Jonathan A. Weiss, Yona Lunsky

Bibliographic record

VenueJournal of Child and Adolescent Psychopharmacology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAutism spectrum disorderPsychiatryYoung adultAutismMental healthHealth careMedicinePsychotropic medicationClinical psychologyPsychologyGerontology

Abstract

fetched live from OpenAlex

OBJECTIVE: Psychotropic medications are frequently used to treat mental health and behavioral issues in adolescents and adults with an autism spectrum disorder (ASD). Although parents of individuals with ASD frequently take on medication management for their child, there is limited literature on parent perspectives of their child's medication use or their views about the healthcare services they receive, particularly in adulthood. The current study examined and compared parents of adolescents and of young adults with ASD regarding their child's psychotropic medication use and their views about healthcare services. METHODS: One hundred parents of adolescents and young adults with ASD (ages 12-30 years) completed an online survey about their experience with their child's healthcare services and medication use. RESULTS: Parents of young adults were less likely to use nonpharmacological services before using a psychotropic medication than were parents of adolescents. Parents of young adults were also less likely to believe that their prescribing healthcare provider had adequate expertise in ASD, and were less satisfied with how their prescriber monitored their child's medication use. CONCLUSION: Findings highlight the need to build capacity among healthcare providers supporting individuals with ASD as they transition into adulthood. There is also a need for improved medication monitoring and increased awareness of the different mental health challenges that individuals with ASD encounter as they age.

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 score0.026
Threshold uncertainty score0.972

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 communication0.0000.001
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 head0.031
GPT teacher head0.332
Teacher spread0.301 · 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

Citations15
Published2015
Admission routes2
Has abstractyes

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