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Record W2089326664 · doi:10.3109/00207454.2014.895003

Test–retest reliability of frontal alpha electroencephalogram (EEG) and electrocardiogram (ECG) measures in adolescents: a pilot study

2014· article· en· W2089326664 on OpenAlexafffund
Adira K. Winegust, Karen J. Mathewson, Louis A. Schmidt

Bibliographic record

VenueInternational Journal of Neuroscience · 2014
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsElectroencephalographyPsychologyReliability (semiconductor)Alpha (finance)AudiologyTest (biology)Physical medicine and rehabilitationMedicinePsychometricsNeuroscienceDevelopmental psychologyCronbach's alpha

Abstract

fetched live from OpenAlex

A number of studies have shown that the pattern of resting frontal EEG alpha power and asymmetry and heart rate are predictive of individual differences in affective style in children and adults. Although test-retest reliability of frontal electrocortical and autonomic measures has been established in adult and child and some clinical populations, few studies have examined test-retest reliability of these measures in adolescents. Here, we conducted a pilot study to examine the test-retest reliability of frontal EEG alpha power and asymmetry and heart period and heart rate in 10 typically developing adolescent participants (M age = 15.9 years) over a 1 month period. We found acceptable test-retest reliability using Pearson and intra-class correlations in left and right mid-frontal alpha power and asymmetry and heart period and heart rate over 1 month. These results provide initial evidence for acceptable levels of test-retest reliability in central and peripheral psychophysiological measures in adolescents used to index affective style in children and adults. Future studies are needed with a larger sample to ensure the reliability of these results.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.398
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 head0.016
GPT teacher head0.281
Teacher spread0.265 · 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

Citations20
Published2014
Admission routes2
Has abstractyes

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