366 Predictors of Dropout in University Students Participating in an 8-week E-mail Based Cognitive Behavioral Therapy for Insomnia. (3rd May 2021)

• Record Type: Journal Article
• Authors: Nam, Hyojin; Chang, Jinyoung; Manber, Rachel; Trockel, Mickey; Okajima, Isa; Yang, Chien-Ming; Li, Shirley; Suh, Sooyeon
• Is Part Of: Sleep. Volume 44(2021)Supplement 2
• Page Start: A145
• Page End: A146
• Publication Date: 2021-05-03
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsab072.365
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: As dropout from treatment potentially diminishes its therapeutic effect and poses clinical concern, it is important to find out which characteristics of participants are suitable for online-based treatment. Therefore, we aimed to identify factors that predicted a dropout in the e-mail based cognitive behavioral therapy (REFRESH) developed by Stanford University for the purpose of psychological intervention for insomnia. Methods: Participants who participated in the REFRESH program consisted of 158 university and graduate students aged 18 to 30 in Hong Kong and Korea who scored higher than 10 on the Insomnia Severity Index (ISI), and the intervention was delivered in 8 weekly sessions sent via weekly e-mails. Among them, 110 were women (70%) and the average age was 22 (±2.71) years old. All participants were asked to answer the following self-reporting questionnaires before and after the intervention: Insomnia Severity Index; ISI, Depression Anxiety Stress Scale 21; DASS-21, Sleep Hygiene Practice Scale; SHPS, Dysfunctional Beliefs and Attitude about Sleep 16; DBAS-16. Descriptive statistics and ROC decision tree analysis were conducted to address our aim. Results: Of the 158 participants, 68 completed the program, and 90 participants (57%) dropped out. The best predictor of dropout was DASS score with an optimal cup-point of <34. Of the 107 participants who reported DASS <30, 70(65.4%) dropped out. In contrast, of the 50 participants who reported DASS ≥34, 12(38%) dropped out. The second-level predictor was expectations for sleep score with a cut-point of <18. Among participants with DASS <34 and expectations for sleep score <18, 57(73.1%) dropped out. Of the 29 participants who reported DASS <34 and expectations for sleep score ≥18, 13(44.8%) dropped out. Conclusion: Mild levels of depression, anxiety and stress and expectations for sleep appear to be predictive of dropout in an e-mail based intervention. People with mild symptoms may experience less distress and impairment, which may result in lower motivation to receive treatment. This may lead to inability to complete treatment and higher rates of dropout. Support (if any):