Who is at risk for dropout from group cognitive-behavior therapy for insomnia?

Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Journal of Psychosomatic Research (Impact Factor: 2.74). 05/2008; 64(4):419-25. DOI: 10.1016/j.jpsychores.2007.10.009
Source: PubMed


The aim of the present study was to identify characteristics of patients who are at risk for dropout from a seven-session group cognitive-behavior therapy for insomnia (CBT-I) in a clinical setting using the receiver operating characteristic curve (ROC) approach.
Two separate ROC analyses were conducted using predictor variables taken from questionnaire packets and sleep diaries collected at baseline including age, gender, Beck Depression Inventory (BDI), Morningness-Eveningness Questionnaire, Beliefs and Attitudes about Sleep, use of sleep medication, sleep onset latency, wake time after sleep onset, and total sleep time (TST).
The first ROC analysis was conducted on the entire sample of 528 patients with treatment completion vs. dropout (noncompletion) as the outcome variable. No significant predictor variables were found in this analysis. The second ROC analysis was conducted on the 211 patients who did not complete treatment with early termination (prior to fourth session) vs. late termination (at or after fourth session) as the outcome variable. The results revealed that patients who reported an average baseline TST <3.65 h were at greatest risk for early termination. Sixty percent of patients in this group terminated early compared to 9.3% of patients with TST > or =3.65 h. Among patients with TST > or =3.65 h, 22% of those with BDI scores > or =16 were early dropouts compared to 4.3% of those who reported BDI <16.
These findings indicate that short sleep duration and elevated symptoms of depression at baseline are associated with increased risk of early termination from CBT-I.

Download full-text


Available from: Jason C Ong
  • Source
    • "Similarly, Sleep Restriction Therapy and Stimulus Control have been associated with postive outcomes among patient-reported use of CBT-I (Harvey, Inglis, & Espie, 2002). Conversely, short sleep duration, symptom severity and elevated baseline depressive symptoms have been associated with attrition in various forms of CBT-I (Hebert, Vincent, Lewycky, & Walsh, 2010; Ong, Kuo, & Manber, 2008). However, insomnia treatments being perceived as either ineffective or unattractive by patients may be Downloaded by [University of Sydney] at 16:56 24 March 2013 a possible reason for the under-treatment of insomnia (Hogan, Clark & Scott, 2003; Stinson, Tang & Harvey, 2006). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Insomnia is a common sleep disorder associated with substantial direct and indirect costs, yet there is a strong propensity among patients to self-medicate which often delays professional help. Understanding the process which underpins the initiation, engagement and adherence to insomnia treatment(s) is a vital step for understanding this phenomenon. The current paper explores how the patient perspective has been conceptualized in the research literature and its implications for insomnia treatment and health care delivery. A literature search was conducted using Embase, Medline and PsycINFO databases. Articles have been thematically organized into patient correlates of health behaviors, patient experiences and treatment attitudes. Deferral of professional help among insomnia patients is partially related to barriers embedded in the health care system and patient health beliefs.
    Full-text · Article · Jun 2012 · Behavioral Sleep Medicine
  • Source
    • "They also have altered health indices, functional ability, health services utilization, and elevated mortality rates (Ganguli et al., 2002). Individuals may in fact have symptoms shortly before they die (Katona and Shankar, 2004) or drop out of studies (Casey et al., 2008; Ong et al., 2008). The course and relationships of depressive symptoms in these individuals may therefore differ substantially from those observed in individuals who complete the study. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Attrition from mortality is common in longitudinal studies of the elderly. Ignoring the resulting non-response or missing data can bias study results. 1260 elderly participants underwent biennial follow-up assessments over 10 years. Many missed one or more assessments over this period. We compared three statistical models to evaluate the impact of missing data on an analysis of depressive symptoms over time. The first analytic model (generalized mixed model) treated non-response as data missing at random. The other two models used shared parameter methods; each had different specifications for dropout but both jointly modeled both outcome and dropout through a common random effect. The presence of depressive symptoms was associated with being female, having less education, functional impairment, using more prescription drugs, and taking antidepressant drugs. In all three models, the same variables were significantly associated with depression and in the same direction. However, the strength of the associations differed widely between the generalized mixed model and the shared parameter models. Although the two shared parameter models had different assumptions about the dropout process, they yielded similar estimates for the outcome. One model fitted the data better, and the other was computationally faster. Dropout does not occur randomly in longitudinal studies of the elderly. Thus, simply ignoring it can yield biased results. Shared parameter models are a powerful, flexible, and easily implemented tool for analyzing longitudinal data while minimizing bias due to nonrandom attrition.
    Full-text · Article · Apr 2009 · International Psychogeriatrics
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The Receiver Operating Characteristic (ROC) analysis has been long used in Signal Detection Theory to depict the tradeoff between hit rates and false alarm rates of classifiers. In the last years, ROC analysis has become largely used in the medical community for visualizing and analyzing the performance of diagnostic tests. Our article points out some fundamental aspects of ROC analysis underlying the importance of using ROC analysis in evaluating the diagnostic validity of tests commonly used in clinical psychology. The main statistical programs available for this type of analysis, with their advantages and deficiencies are also discussed. In order to illustrate how ROC analysis works in clinical research, we also describe an application of ROC analysis in evaluating scales generally related to depression.
    Full-text · Article · Mar 2009 · Journal of Cognitive and Behavioral Psychotherapies
Show more