Mind, Body and Machine: Preliminary Study to Explore Predictors of Treatment Response After a Sleep Robot Intervention for Adults with Insomnia

Abstract

Introduction

The study aimed to explore characteristics of responders to a sleep robot intervention for adults with insomnia, and the likelihood that participants responded to the intervention.

Methods

Data from the intervention and the control group in a randomized waitlist-controlled trial (n = 44) were pooled together after both had undergone the intervention. A repeated measures ANOVA and Friedman tests were used to explore changes over time. Differences in baseline characteristics between responders (n = 13), defined as a reduction of −5 on the Insomnia Severity Index from pre- to post-intervention, and non-responders (n = 31) were analyzed with t-tests and chi-square tests. Finally, logistic regression models were estimated.

Results

Baseline anxiety was the only statistically significant difference between responders and non-responders (p = 0.03). A logistic regression model with anxiety and sleep quality as predictors was statistically significant, correctly classifying 83.3% of cases.

Discussion

The results imply that people with lower anxiety and higher sleep quality at baseline are more likely to report clinically significant improvements in insomnia from the sleep robot intervention.

Keywords:

• anxiety
• depression
• insomnia
• sleep
• sleep diary
• sleep robot
• treatment response

Data Sharing Statement

Data are available from the corresponding author upon reasonable request.

Acknowledgments

The research group would like to thank the participants for their time.

Disclosure

The authors have no conflicts of interest to declare.