Navigating the garden of forking paths for data exclusions in fear conditioning research
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Abstract
In this report, we illustrate the considerable impact of researcher degrees of freedom with respect to exclusion of participants in paradigms with a learning element. We illustrate this empirically through case examples from human fear conditioning research, in which the exclusion of 'non-learners' and 'non-responders' is common - despite a lack of consensus on how to define these groups. We illustrate the substantial heterogeneity in exclusion criteria identified in a systematic literature search and highlight the potential problems and pitfalls of different definitions through case examples based on re-analyses of existing data sets. On the basis of these studies, we propose a consensus on evidence-based rather than idiosyncratic criteria, including clear guidelines on reporting details. Taken together, we illustrate how flexibility in data collection and analysis can be avoided, which will benefit the robustness and replicability of research findings and can be expected to be applicable to other fields of research that involve a learning element.
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SCR exclusion criteria were relatively similar across studies in the current meta-analysis.
“While there is substantial heterogeneity in the exclusion criteria used for SCR nonresponse and nonlearning in the field (74), for the current meta-analysis, SCR exclusion criteria were relatively similar across studies.”
From I Doubt It Is Safe: A Meta-analysis of Self-reported Intolerance of Uncertainty and Threat Extinction Training (2021) · cites this paper as [74]
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Whose Signals Are Being Amplified? Towards a More Equitable Clinical PsychophysiologyPreprint
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Trait anxiety is associated with hidden state inference during aversive reversal learningPreprint
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- Authors
- Lonsdorf, T. B., Klingelhöfer-Jens, M., Andreatta, M., Beckers, T., Chalkia, A., Gerlicher, A., Jentsch, V. L., Meir Drexler, S., Mertens, G., Richter, J., Sjouwerman, R., Wendt, J., & Merz, C. J.
- Affiliations
- University Medical Center Hamburg-Eppendorf (DE)
- University of Würzburg (DE)
- KU Leuven (BE)
- University of Amsterdam (NL)
- Ruhr University Bochum (DE)
- Institute of Cognitive Neuroscience, Department of Cognitive Psychology, Ruhr University Bochum, Bochum, Germany
- Department of Psychology, Utrecht University, Utrecht, Netherlands
- Universität Greifswald (DE)
- University of Potsdam (DE)
- ORCID
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2019-12-16
- Volume
- 8
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC6989118
- OpenAlex
- W2995231114
- Cited by
- 164
- References
- 85
- Citations by year
- 2026: 16 · 2025: 23 · 2024: 15 · 2023: 27 · 2022: 26 · 2021: 33 · 2020: 21 · 2019: 1 · 2018: 1
- FWCI
- 2.56
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion, cc-by)
- Lirias (submittedVersion, other-oa)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- publish.UP (University of Potsdam) (submittedVersion)
- PUB – Publications at Bielefeld University (Bielefeld University) (submittedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
- PsyArXiv (OSF Preprints) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Deutsche Forschungsgemeinschaft (LO 1980/2-1, LO 1980/1-1, Project B07 44541416, 316803389 - SFB1280, WE 5873/1-1, WE 5873/5-1)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- researcher degrees of freedom, data exclusion, fear conditioning, non-responders, exclusion criteria, learning paradigms, reporting guidelines, replicability, robustness of results
- MeSH terms
- Adult, Conditioning, Psychological, Fear, Female, Humans, Male
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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