Consistency checks to improve measurement with the Hamilton Rating Scale for Depression (HAM-D)

Jonathan Rabinowitz, Janet B.W. Williams, Ariana Anderson, Dong Jing Fu, Nanco Hefting, Bashkim Kadriu, Alan Kott, Atul Mahableshwarkar, Jan Sedway, David Williamson, Christian Yavorsky, Nina R. Schooler

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Background: Symptom manifestations in mood disorders can be subtle. Cumulatively, small imprecisions in measurement can limit our ability to measure treatment response accurately. Logical and statistical consistency checks between item responses (i.e., cross-sectionally) and across administrations (i.e., longitudinally) can contribute to improving measurement fidelity. Methods: The International Society for CNS Clinical Trials and Methodology convened an expert Working Group that assembled flags indicating consistency/inconsistency ratings for the Hamilton Rating Scale for Depression (HAM-D17), a widely-used rating scale in studies of depression. Proposed flags were applied to assessments derived from the NEWMEDS data repository of 95,468 HAM-D administrations from 32 registration trials of antidepressant medications and to Monte Carlo-simulated data as a proxy for applying flags under conditions of known inconsistency. Results: Two types of flags were derived: logical consistency checks and statistical outlier-response pattern checks. Almost thirty percent of the HAMD administrations had at least one logical scoring inconsistency flag. Seven percent had flags judged to suggest that a thorough review of rating is warranted. Almost 22% of the administrations had at least one statistical outlier flag and 7.9% had more than one. Most of the administrations in the Monte Carlo- simulated data raised multiple flags. Limitations: Flagged ratings may represent less-common presentations of administrations done correctly. Conclusions: Application of flags to clinical ratings may aid in detecting imprecise measurement. Reviewing and addressing these flags may improve reliability and validity of clinical trial data.

Original languageEnglish
Pages (from-to)273-279
Number of pages7
JournalJournal of Affective Disorders
Volume302
DOIs
StatePublished - 1 Apr 2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s)

Funding

The research leading to these results has received support from the Innovative Medicine Initiative Joint Undertaking under grant agreement no 115,008 of which resources are composed of European Federation of Pharmaceutical Industries and Associations (EFPIA) in-kind contribution and financial contribution from the European Union's Seventh Framework Program ( FP7/2007–2013 ) and the Elie Wiesel Chair at Bar Ilan University . Funding sources were not involved in the collection, analysis, and interpretation of data; in the writing of the report; and nor in the decision to submit the paper for publication. Funding source was not involved in the collection, analysis, and interpretation of data; in the writing of the report; and nor in the decision to submit the paper for publication. The research leading to these results has received support from the Innovative Medicine Initiative Joint Undertaking under grant agreement no 115008 of which resources are composed of European Federation of Pharmaceutical Industries and Associations (EFPIA) in-kind contribution and financial contribution from the European Union's Seventh Framework Program ( FP7/2007–2013 ) and the Elie Wiesel Chair at Bar Ilan University. Funding source was not involved in the collection, analysis, and interpretation of data; in the writing of the report; and nor in the decision to submit the paper for publication. The authors wish to acknowledge Zimri S. Yaseen for his helpful comments on this manuscript.

FundersFunder number
Seventh Framework Programme
Bar-Ilan University115008
Seventh Framework Programme

    Keywords

    • Careless ratings
    • Consistency of measurement
    • HAM-D17
    • Hamilton Rating Scale for Depression
    • Inconsistent ratings
    • NEWMEDS

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