title: Identifying Longitudinal Patterns for Individuals and Subgroups: An Example with Adherence to Treatment for Obstructive Sleep Apnea.
abstract: To improve complex behaviors such as adherence to medical recommendations, a better understanding of behavior change over time is needed. The focus of this study was adherence to treatment for obstructive sleep apnea (OSA). Adherence to the most common treatment for OSA is poor. This study involved a sample of 161 participants, each with approximately 180 nights of data. First, a time series analysis was performed for each individual. Time series parameters included the mean (average hours of use per night), level, slope, variance, and autocorrelation. Second, a dynamic cluster analysis was performed to find homogenous subgroups of individuals with similar adherence patterns. A four-cluster solution was found, and the subgroups were labeled: Great Users (17.2%; high mean and level, no slope), Good Users (32.8%; moderate mean and level, no slope), Low Users (22.7%; low mean and level, negative slope), and Slow Decliners (moderate mean and level, negative slope, high variance). Third, participants in the identified subgroups were compared to establish external validity. These steps represent a Typology of Temporal Patterns (TTP) approach. Combining time series analysis and dynamic cluster analysis is a useful way to evaluate longitudinal patterns at both the individual level and subgroup level.
authors.affiliation: a Department of Psychology, Geisel School of Medicine at Dartmouth.
authors.forename: Steven F
authors.initials: SF
authors.lastname: Babbin
authors.affiliation: b Cancer Prevention Research Center , University of Rhode Island.
authors.forename: Wayne F
authors.initials: WF
authors.lastname: Velicer
authors.affiliation: c National Jewish Health and Philips/Respironics, Inc.
authors.forename: Mark S
authors.initials: MS
authors.lastname: Aloia
authors.affiliation: d Stanford Sleep Medicine Center.
authors.forename: Clete A
authors.initials: CA
authors.lastname: Kushida
mesh_terms: D000328:Adult; D000368:Aged; D016000:Cluster Analysis; D045422:Continuous Positive Airway Pressure / Q000379:methods; D005260:Female; D006801:Humans; D065186:Interrupted Time Series Analysis; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D010349:Patient Compliance / Q000706:statistics & numerical data; D020181:Sleep Apnea, Obstructive / Q000628:therapy*; D013997:Time Factors; D055815:Young Adult