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Record W2341122985 · doi:10.3109/15622975.2016.1174300

Resting state vagal tone in attention deficit (hyperactivity) disorder: A meta-analysis

2016· review· en· W2341122985 on OpenAlexaff
Julian Koenig, Joshua A. Rash, Andrew H. Kemp, Reiner Buchhorn, Julian F. Thayer, Michael Kaess

Bibliographic record

VenueThe World Journal of Biological Psychiatry · 2016
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of Calgary
FundersFundação de Amparo à Pesquisa do Estado de São PauloUniversität HeidelbergBoehringer Ingelheim FondsOhio State University
KeywordsAttention deficit hyperactivity disorderMeta-analysisResting state fMRIPsychologyHeart rate variabilityVagal toneCINAHLPsycINFOClinical psychologyPsychiatryMedicineHeart rateAudiologyInternal medicineMEDLINENeuroscienceBlood pressure

Abstract

fetched live from OpenAlex

OBJECTIVES: To quantify evidence on resting-state vagal activity in patients with attention deficit hyperactivity disorder (ADHD) relative to controls using meta-analysis. METHODS: Three electronic databases (PubMed, PsycINFO, CINAHL Plus) were reviewed to identify studies. Studies reporting on any measure of short-term, vagally mediated heart rate variability during resting state in clinically diagnosed ADHD patients as well as non-ADHD healthy controls were eligible for inclusion. RESULTS: Eight studies reporting on 587 participants met inclusion criteria. Random-effect meta-analysis revealed no significant main effect comparing individuals with ADHD (n = 317) and healthy controls (n = 270) (Hedges' g = 0.06, 95% CI: 0.18-0.29, Z = 0.48, P = 0.63; k = 8). Sub-group analysis showed consistent results among studies in adults (k = 2) and children (k = 6) with ADHD. CONCLUSIONS: Unlike a variety of internalising psychiatric disorders, ADHD is not associated with altered short-term measures of resting-state vagal tone.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.024
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0180.034
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.147
GPT teacher head0.414
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations39
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe World Journal of Biological PsychiatrySame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207