Evidence map›Paper›PMID 38228400›Full record

ReviewPsychophysiology2024

The psychometric upgrade psychophysiology needs.

Peter E Clayson

Abstract readReview
In one paragraph

Review in Psychophysiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Development and psychometric validation of the short-form thai version of the spine oncology study group outcomes questionnaire (TH-SOSGOQ-8D).European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Article
  3. Article
  4. Article
  5. Beyond classical metrics: Generalizability theory across psychophysiological modalities.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2026
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Peter E ClaysonDepartment of Psychology, University of South Florida, Tampa, Florida, USA.ORCID 0000-0003-4437-6598

Funding

PsyRAT: Extensible Open-Source Software for Applying Generalizability Theory to Assess Psychometric Reliability of Trial-Wise Scores and Optimize Tasks for RDoCR01MH128208 · NIMH · UNIVERSITY OF SOUTH FLORIDA · PI Peter Eugene Clayson · 2022 to 2026
$3.0M
NIMH NIH HHS R01 MH128208NIMH NIH HHS R01MH128208
6 · The paper itself

Abstract

Although biological measurements are constrained by the same fundamental psychometric principles as self-report measurements, these essential principles are often neglected in most fields of neuroscience, including psychophysiology. Potential reasons for this neglect could include a lack of understanding of appropriate measurement theory or a lack of accessible software for psychometric analysis. Generalizability theory is a flexible and multifaceted measurement theory that is well suited to handling the nuances of psychophysiological data, such as the often unbalanced number of trials and intraindividual variability of scores of event-related brain potential (ERP) data. The ERP Reliability Analysis Toolbox (ERA Toolbox) was designed for psychophysiologists and is tractable software that can support the routine evaluation of psychometrics using generalizability theory. Psychometrics can guide task refinement, data-processing decisions, and selection of candidate biomarkers for clinical trials. The present review provides an extensive treatment of additional psychometric characteristics relevant to studies of psychophysiology, including validity and validation, standardization, dimensionality, and measurement invariance. Although the review focuses on ERPs, the discussion applies broadly to psychophysiological measures and beyond. The tools needed to rigorously assess psychometric reliability and validate psychophysiological measures are now readily available. With the profound implications that psychophysiological research can have on understanding brain-behavior relationships and the identification of biomarkers, there is simply too much at stake to ignore the crucial processes of evaluating psychometric reliability and validity.

Indexed as

Evoked PotentialsPsychophysiologyBiomarkersHumansPsychometricsReproducibility of ResultsBiomarkersbiomarkerERP psychometric reliabilityevent-related potentials (ERPs)generalizability theorypsychophysiologyvalidity

Identifiers

PMID38228400
PMCPMC10922751

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.