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Applying multiverse analysis to experience sampling data: Investigating whether preprocessing choices affect

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Multiverse analyses show that preprocessing choices for experience sampling method (ESM) data, like data exclusion, do not alter conclusions. However, calculating negative affect using mean versus median/mode impacts findings on stress reactivity and emotional inertia in psychosis.

Keywords:
Ambulatory assessmentEcological momentary assessmentExperience sampling methodsMultiversePreprocessingResearcher degrees of freedom

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Area of Science:

  • Psychology
  • Psychiatry
  • Computational Social Science

Background:

  • The experience sampling method (ESM) allows psychological research in naturalistic settings.
  • Significant researcher variability exists in preprocessing ESM data, potentially impacting scientific reproducibility.
  • Standardized preprocessing protocols are needed to ensure the reliability of ESM findings.

Purpose of the Study:

  • To investigate the impact of varying data preprocessing choices on established group differences in affective processes between individuals with and without psychosis.
  • To assess the robustness of conclusions regarding negative affect, stress reactivity, and emotional inertia using multiverse analyses.
  • To provide guidance on best practices for preprocessing ESM data.

Main Methods:

  • Multiverse analysis was employed to reanalyze data from five studies comprising 233 individuals with psychosis and 223 healthy controls (26,892 assessments).
  • Preprocessing variations included data exclusion criteria (compliance levels, first-day exclusion) and construct calculation methods (mean, median, mode).
  • Group differences in negative affect, stress reactivity, and emotional inertia were compared across preprocessing scenarios.

Main Results:

  • Data exclusion choices did not alter the main conclusions regarding group differences.
  • Calculating negative affect using the mean, compared to the median or mode, significantly affected group differences in stress reactivity and emotional inertia.
  • These discrepancies were linked to variations in the within- and between-factor structure of negative affect.

Conclusions:

  • Observed differences in affective processes between individuals with and without psychosis are generally robust to data exclusion preprocessing choices.
  • The choice of central tendency measure (mean vs. median/mode) can influence conclusions, highlighting the importance of the within- and between-factor structure of constructs.
  • Multiverse analysis is recommended for experience sampling method research to ensure and demonstrate the robustness of findings across different preprocessing decisions.