Enhancing digital CBT-I to improve adherence and reduce disparities

NIH RePORTER · NIH · R01 · $641,887 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY/ABSTRACT Insomnia is a debilitating condition that escalates risk of a myriad of disorders, and affects up to one third of adults. Although insomnia can be effectively treated with Cognitive Behavioral Therapy for Insomnia (CBT-I), there is a shortage of specialty providers trained in CBT-I. Consequently, most patients with insomnia are unable to receive CBT-I as the recommended first-line intervention for insomnia. To address this problem, CBT-I can now be delivered digitally (dCBT-I) with strong efficacy; however, the real-world effectiveness of dCBT-I is limited by poor engagement. Over 50% of patients do not complete the full course of dCBT-I, and 40% of those who persist in treatment do not adhere to critical components of dCBT-I. Moreover, treatment completion and adherence are 2-3 times worse in those with low socioeconomic status. Our pilot data indicate that the disparity in completion and adherence to dCBT-I is related to low health literacy, defined as the ability to find, understand, and use information and services to inform health-related decisions. Health literacy is especially critical for engagement with digital interventions that are self-guided, such as dCBT-I. This proposal responds to an announcement focused on improving patient adherence to treatments. We propose a large-scale intervention comparing enhanced dCBT-I to control dCBT-I in improving treatment completion and adherence in a sample stratified by socioeconomic status. We also propose to test the effect of enhanced dCBT-I on reducing socioeconomic disparities in treatment adherence and completion. An innovative component of this trial is the use of non-specialist coaches as a scaffold for low health literacy, and to enhance treatment motivation and self-efficacy. Furthermore, those who are at-risk for treatment non- completion are shifted to telehealth coaching focused on one single critical behavioral component tailored for ease of assimilation into the patient’s daily life. The adaptive component provides patients two different treatment modalities to maximize engagement and both approaches leverage technology to increase accessibility. Our long-term goal is to ensure equitable effectiveness of digital insomnia treatments. To that end, our overall objective is to determine how adherence and completion in dCBT-I can be improved, particularly in those with low SES as a health disparities population. Based on pilot data, our central hypothesis is that, compared to control dCBT-I, enhanced dCBT-I will increase engagement by providing targeted support for those who need it.

Key facts

NIH application ID
10491349
Project number
5R01HL159180-02
Recipient
HENRY FORD HEALTH SYSTEM
Principal Investigator
Philip Cheng
Activity code
R01
Funding institute
NIH
Fiscal year
2022
Award amount
$641,887
Award type
5
Project period
2021-09-20 → 2026-08-31