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Exploring the multiverse of analysis options for the alcohol Stroop
Andrew Jones1, Elena Petrovskaya2, Tom Stafford3
1School of Psychology, Tom Reilly Building, Liverpool John Moore's University, Byrom Street, L3 3AF, Liverpool, UK. a.j.jones@ljmu.ac.uk.
Behavior Research Methods
|March 15, 2024
Summary
The alcohol Stroop task reliably detects attentional bias towards alcohol cues, even with varied analysis methods. This suggests the task
Area of Science:
- Addiction Science
- Cognitive Psychology
- Neuroscience
Background:
- The alcohol Stroop task measures attentional bias, a key factor in addiction.
- Previous findings are inconsistent due to diverse data analysis methods.
- Variations in handling reaction times and errors create ambiguity.
Purpose of the Study:
- To assess the robustness of the alcohol Stroop effect across different analysis pipelines.
- To investigate how analytical decisions impact the measurement of attentional bias.
- To enhance confidence in cognitive and addiction science research findings.
Main Methods:
- Specification curve analysis was applied to two alcohol Stroop datasets.
- Twenty-seven distinct analysis pipelines were evaluated.
- The impact of outlier identification and data exclusion criteria was examined.
Main Results:
- The alcohol Stroop effect was consistently observed across datasets and pipelines.
- Analysis of individual reaction time outliers introduced more variability than participant exclusion.
- Stricter outlier thresholds generally decreased the observed Stroop interference effect.
Conclusions:
- The alcohol Stroop effect is robust to variations in analytical approaches.
- Researchers should utilize specification curve analysis for reliable inferences.
- Standardized analytical methods will improve the validity of addiction science research.
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