%0 Journal Article
%T Re-examining the factor structure of the Insomnia Severity Index (ISI) and defining the meaningful within-individual change (MWIC) for subjects with insomnia disorder in two phase III clinical trials of the efficacy of lemborexant.
%A Lenderking WR
%A Savva Y
%A Atkinson MJ
%A Campbell R
%A Chabot I
%A Moline M
%A Meier G
%A Morin CM
%J J Patient Rep Outcomes
%V 8
%N 1
%D 2024 Jun 29
%M 38951287
暂无%R 10.1186/s41687-024-00744-6
%X <B>BACKGROUND: </B>The Insomnia Severity Index (ISI) is a widely used measure of insomnia severity. Various ISI research findings suggest different factor solutions and meaningful within-individual change (MWIC) to detect treatment response in patients with insomnia. This study examined an ISI factor solution and psychometric indices to define MWIC in a robust patient sample from clinical trial settings.<BR><B>METHODS: </B>We endeavored to improve upon previous validation of ISI by examining structural components of confirmatory factor analysis (CFA) models using two large, placebo-controlled clinical trials of lemborexant for insomnia. Using the best-fitting two-factor solution, we evaluated anchor-based, distribution-based and receiver operating characteristic (ROC) curve methods to derive an estimate of the MWIC.<BR><B>RESULTS: </B>The model structure for the 7-item scale proposed in other research did not fit the observed data from our two lemborexant clinical trials (N = 1956) as well as a two-factor solution based on 6 items did. Using triangulation of anchor-based, distribution-based, and ROC methods, we determined that a 5-point reduction using 6 items best represented a clinically meaningful improvement in individuals with insomnia in our patient sample.<BR><B>CONCLUSIONS: </B>A 6-item two-factor scale had better psychometric properties than the 7-item scale in this patient sample. On the 6-item scale, a reduction of 5 points in the ISI total score represented the MWIC. Generalizability of the proposed MWIC may be limited to patient populations with similar demographic and clinical characteristics.