Time Series Analysis of Treatment Adherence Patterns in Individuals with Obstructive Sleep Apnea

Abstract

Time series analysis provides a useful method for examining adherence while maintaining a focus on individual differences. Implications for future research are discussed.

Identifying Longitudinal Patterns for Individuals and Subgroups: An Example with Adherence to Treatment for Obstructive Sleep Apnea

“…One approach to better understanding adherence is to consider individual differences in patterns of adherence rather than just group-level statistics (Aloia et al, 2008;DunbarJacob & Sereika, 2001), since group-level statistics do not fully capture the complexity of within-individual variability. The value of group-level analysis versus individual-level analysis involves the distinction between nomothetic and idiographic methods (Hamaker & Dolan, 2009;Molenaar, 2004;2008).…”

“…Developmental processes, for example, are never ergodic (Molenaar, 2008) as such processes always have time-varying generating functions. Thus to fully explore the complexities of adherence to OSA, a complex behavior that often varies greatly among individuals (Aloia et al, 2008), statistical techniques reflecting an idiographic approach are warranted. Idiographic methods offer unique ways to think about research questions because they emphasize intraindividual variation rather than just interindividual variation.…”

“…In this article we are referring to this general approach as a Typology of Temporal Patterns (TTP). There are many examples of TTP in the literature including studies of patterns of daily smoking (Chandra, Shiffman, Scharf, Dang, & Shadel, 2007;Hoeppner, Goodwin, Velicer, Mooney, & Hatsukami, 2008), daily alcohol use (Harrington, Velicer, & Ramsey, 2014), and OSA (Aloia et al, 2008).…”

“…Time series methodology has previously been utilized to study participants prescribed PAP machines for OSA. In Aloia et al (2008), the authors used time series analysis to examine adherence patterns in 71 participants with OSA. A separate time series analysis was performed for each participant, and the authors looked at four parameters, which are also considered in the present study: level of the series, variance of the series, slope of the series, and autocorrelation.…”

Self-efficacy contributes to individual differences in subjective improvements using CPAP

“…It also allows some ability to test directionality of effects. We focused on adherence early in patients experience with CPAP because several studies have reported that early adherence is a predictor of later adherence [7,21,22].…”