Applying advanced psychometric approaches yields differential randomized trial effect sizes: secondary analysis of individual participant data from antidepressant studies using the Hamilton rating scale for depression

This study aimed to determine if using advanced psychometrics methods would inform any clinically or statistically important differences in clinical trial outcomes when compared to original findings. We applied factor analysis (FA), item response theory (IRT), and network analysis (NA) to the most commonly used measure of depression in clinical settings - the Hamilton Rating Scale for Depression (HRSD) - to identify and remove nonperforming survey items and calculate weighted item scores. We found that the efficacy reported in trials increased when using FA to removed items, but decreased when using NA. There was almost no change in efficacy when using IRT. Using weighted scores based on respective models offered no additional utility in terms of increasing or decreasing efficacy outcomes.

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Publication Details

Journal
Journal of Clinical Epidemiology
Published
2025-03-24
DOI
https://doi.org/10.1016/j.jclinepi.2025.111762
Citations
3
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
6.35

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article

Applying advanced psychometric approaches yields differential randomized trial effect sizes: secondary analysis of individual participant data from antidepressant studies using the Hamilton rating scale for depression

David Hevey, Susan Brannick, David F. Byrne, Pim J. Cuijpers et al.
3 citations
Journal of Clinical Epidemiology
Mental Health Research Topics
6.35
article

Applying advanced psychometric approaches yields differential randomized trial effect sizes: secondary analysis of individual participant data from antidepressant studies using the Hamilton rating scale for depression

David Hevey, Susan Brannick, David F. Byrne, Pim J. Cuijpers, Robert M. Carney, Emma K. Wallace, Kenneth E. Freedland, Suzanne Guérin, Bishember Kathuria, Frank Doyle, Fiona Boland, Alexandra Lelia Dima
article en
3 citations

Abstract

This study aimed to determine if using advanced psychometrics methods would inform any clinically or statistically important differences in clinical trial outcomes when compared to original findings. We applied factor analysis (FA), item response theory (IRT), and network analysis (NA) to the most commonly used measure of depression in clinical settings - the Hamilton Rating Scale for Depression (HRSD) - to identify and remove nonperforming survey items and calculate weighted item scores. We found that the efficacy reported in trials increased when using FA to removed items, but decreased when using NA. There was almost no change in efficacy when using IRT. Using weighted scores based on respective models offered no additional utility in terms of increasing or decreasing efficacy outcomes.

Journal of Clinical EpidemiologyVol. 183
University College Dublin (IE), Mercy Medical Center (US), Washington University in St. Louis (US), Trinity College Dublin (IE), University College Cork (IE), Sant Joan de Déu Research Foundation (ES), Novartis (Ireland) (IE), Vrije Universiteit Amsterdam (NL)
Eli Lilly and Company, Pfizer, GlaxoSmithKline, Irish Research Council
Openalex Percentile: Top 5%
Mental Health Research Topics
6.35
DOIOpen Access PDFOpenAlex
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