5th Edition of International Neurology Conference 2026

Abstract

Insomnia is a highly prevalent condition associated with significant impairments in cognitive performance, emotional regulation, and daily functioning. Beyond its clinical impact, poor sleep has been consistently linked to reduced workplace productivity, increased absenteeism, and diminished overall quality of life. Digital Cognitive Behavioral Therapy for Insomnia (dCBT-I) has emerged as a scalable solution capable of delivering evidence-based treatment to large populations, yet data on its real-world effectiveness across functional and productivity outcomes remain limited.

The present study aimed to evaluate longitudinal changes in health, well-being, and work-related functioning among users of a digital CBT-I program in a real-world setting. We conducted an observational analysis using routinely collected data from individuals engaging with a digital sleep intervention platform. Participants completed repeated self-reported assessments throughout program use, generating multiple observations per individual (mean observations per user = 2.71, SD = 0.94).

Primary outcomes included perceived productivity impairment and work hours lost due to sleep-related difficulties, while secondary outcomes included self-rated general health and life satisfaction. Productivity-related measures were adapted from the Work Productivity and Activity Impairment (WPAI) questionnaire. To account for within-subject correlations over time, linear mixed-effects models were used to estimate longitudinal changes across program engagement.

A total of 3,267 users completed the baseline assessment, with a progressive decrease in participation across follow-up time points (visit 5 n=216). The sample was predominantly female (66%). Across all outcomes, statistically significant improvements were observed over time (all p<0.001). Perceived productivity impairment showed a substantial reduction, decreasing from a mean of 5.31 at baseline to 3.08 at later assessments, corresponding to a 42% relative reduction (β = −0.709 per visit). Similarly, work hours lost due to sleep-related issues decreased from 24.02 to 16.44 hours (β = −3.152 per visit), indicating an average recovery of approximately 9–10 working hours per week per participant.

In addition to productivity gains, participants reported meaningful improvements in overall well-being. Self-rated general health increased from 1.58 to 2.00 (β = +0.118), and life satisfaction improved from 6.24 to 6.94 (β = +0.244), suggesting that benefits extended beyond sleep-specific outcomes into broader domains of health and quality of life.

These findings provide robust real-world evidence supporting the effectiveness of digital CBT-I as a scalable intervention capable of improving both clinical and functional outcomes. The magnitude of observed productivity gains highlights the potential of digital sleep interventions not only as a healthcare solution but also as a strategy to enhance workforce performance and societal well-being.