The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Standardization Within Individuals: A Simple Method to Neutralize Individual Differences in Skin Conductance
Abstract
The present paper suggests a method to neutralize individual differences in skin conductance responsivity. The method suggested is a standardization of the responses within individuals. This method was compared to the range correction transformation suggested previously. The comparison was based on data from two experiments which evaluated differences between electrodermal responses to relevant and neutral stimuli in information detection tasks. In the first experiment the range correction transformation used the maximal skin conductance response evoked by the subject to one of the regular stimuli presented in the information detection task. The second experiment included responses to unpleasant tones and the range correction transformation was defined as the skin conductance response evoked by the subject to a given stimulus, divided by the response to the unpleasant stimulus. A bootstrap analysis was carried out on five data sets gathered from the two experiments, to statistically compare the transformations. In all cases standard scores better discriminated relevant and neutral stimuli, than range corrected scores. The advantage of standardization was much more salient in the second experiment, where only standard scores produced a statistically significant difference between strong and weak experimental conditions. The analysis demonstrated that the advantage of the method of standard scores is related mainly to its reliance upon the mean, which is a more stable and reliable statistic than the maximal response.
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“SCR magnitudes were square root transformed to reduce skew and z-scored within-subjects to control for interindividual differences in skin conductance responsiveness (Ben-Shakhar, 1985).”
From The Impact of Intolerance of Uncertainty and Cognitive Behavioural Instructions on Safety Learning (2020) · cites this paper as Ben-Shakhar, 1985
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Metadata
- Authors
- Ben‐Shakhar, G.
- Affiliations
- Hebrew University of Jerusalem (IL)
- Corresponding author
- Ben‐Shakhar, Gershon
- ORCID
- Ben‐Shakhar, Gershon
- Venue
- Psychophysiology
- Publisher
- Wiley
- Published
- 1985-05
- Volume
- 22
- Issue
- 3
- Pages
- 292-299
- ISSN
- 0048-5772 (ISSN-L)
- 1469-8986
- OpenAlex
- W2045186928
- Cited by
- 249
- References
- 19
- Citations by year
- 2026: 12 · 2025: 14 · 2024: 9 · 2023: 6 · 2022: 13 · 2021: 12 · 2020: 18 · 2019: 21 · 2018: 12 · 2017: 13 · 2016: 8 · 2015: 7 · 2014: 9 · 2013: 9 · 2012: 7
- FWCI
- 2.79
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychophysiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
- Keywords
- skin conductance, electrodermal activity, individual differences, Z-score, information detection
- MeSH terms
- Adolescent, Child, Galvanic Skin Response, Humans, Individuality
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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