Shortening of the Pittsburgh Sleep Quality Index Survey Using Factor Analysis.

ABSTRACT:

Objective/introduction

Lengthy surveys have the potential to burden users and can lead to inaccuracies. Conducting analyses to shorten existing validated surveys is beneficial. The objective, therefore, was to shorten the Pittsburgh Quality Sleep Index (PSQI) for young adults.

Methods

PSQI data from 1246 college students were used. An exploratory factor analysis (FA) was utilized to shorten survey after dropping select items. Nonparametric correlation analysis (Spearman's rho) was conducted between the global sleep scores of the shortened and original surveys. Agreements tests (Kappa and McNemar's test) measured the agreement of the surveys and sensitivity and specificity were evaluated.

Results

Six factors were examined using maximum likelihood factoring method, appl

SUBMITTER: Famodu OA 

PROVIDER: S-EPMC5925150 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature