Time series analysis of treatment adherence patterns in individuals with obstructive sleep apnea

Annals of Behavioral Medicine : a Publication of the Society of Behavioral Medicine
Mark S AloiaRichard P Millman

Abstract

Adherence to medical recommendations is often suboptimal, making examination of adherence data an important scientific concern. Studies that attempt to predict or modify adherence often face the problem that adherence as a dependent variable is complex and non-normally distributed. Traditional statistical approaches to adherence data may mask individual variability that may guide clinician and researcher's development of adherence interventions. In this study, we employ time series analysis to examine adherence patterns objectively in patients with obstructive sleep apnea (OSA). Although treatment adherence is poor in OSA, state-of-the-art adherence monitoring allows a comprehensive examination of objective data. The purpose of the study is to determine the number and types of adherence patterns seen in a sample of patients with OSA receiving positive airway pressure (PAP). Seventy-one moderate to severe OSA participants with 365 days of treatment data were studied. Adherence patterns could be classified into seven categories: (1) Good Users (24%), (2) Slow Improvers (13%), (3) Slow Decliners (14%), (4) Variable Users (17%), (5) Occasional Attempters (8%), (6) Early Drop-outs (13%), and (7) Non-Users (11%). Time series analysis...Continue Reading

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Citations

Sep 17, 2010·Sleep & Breathing = Schlaf & Atmung·Kelly Glazer BaronChristopher R Jones
Apr 17, 2008·Behavior Research Methods·Matthew S GoodwinStephen S Intille
Apr 17, 2012·Journal of Clinical Sleep Medicine : JCSM : Official Publication of the American Academy of Sleep Medicine·Nimesh PatelSairam Parthasarathy
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