Reducing the Burden of Psychological Questionnaire Measures Through Selective Item Re-Weighting

Toby Wise; Nura Sidarus

doi:10.1098/rsos.241857

Reducing the Burden of Psychological Questionnaire Measures Through Selective Item Re-Weighting

Toby Wise^*
, Nura Sidarus

^*Corresponding author for this work

Neuroimaging

Royal Holloway, University of London

Research output: Contribution to journal › Article › peer-review

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Abstract

Questionnaire measures are central to many areas of study within the psychological sciences. However, they often place a heavy burden on participants; questionnaires are frequently lengthy and unengaging, and with participants often required to complete multiple measures within a single study, this results in lower data quality, increased cost and a poor participant experience. Here, we introduce a straightforward method for creating short versions of existing measures that are able to accurately determine participants' sum scores, subscale scores or factor scores. Our method, referred to as Factor Score Item Reduction with Lasso Estimator, uses Lasso-regularized regression to select items and weight them such that true scores can be predicted accurately from a reduced item set. We demonstrate the performance of this method on an example dataset, and provide code and guidance for implementing the approach.

Original language	English
Article number	241857
Journal	Royal Society open science
Volume	12
Issue number	4
Early online date	16 Apr 2025
DOIs	https://doi.org/10.1098/rsos.241857
Publication status	E-pub ahead of print - 16 Apr 2025

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10.1098/rsos.241857Licence: CC BY

Reducing the burden of_WISE_Publishednline16April2025_GOLD_VoR (CC BY)Final published version, 2.34 MBLicence: CC BY

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Reducing the Burden of Psychological Questionnaire Measures Through Selective Item Re-Weighting

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