Health News

Digital cognitive therapy has beneficial effect for patients with insomnia

Digital cognitive therapy has beneficial effect for patients with insomnia

Digital cognitive behavioral therapy for insomnia (dCBT-I) is effective for patients with insomnia, with the optimal treatment including a combination of medication and dCBT-I, according to a study published online April 11 in JAMA Network Open.

Menglin Lu, from Zhejiang University in Hangzhou, China, and colleagues conducted a retrospective cohort study to examine the clinical effectiveness, engagement, durability, and adaptability of dCBT-I. A total of 4,052 patients were selected for treatment with dCBT-I, medication, or combination therapy (418, 862, and 2,722, respectively); outcomes were compared at months 1, 3, and 6.

The researchers found that participants receiving both dCBT-I and combination therapy had significant reductions compared with the change in the Pittsburgh Sleep Quality Index score at six months for patients receiving medication alone (from a mean of 13.51 to 7.15 and 12.92 to 6.98, respectively, versus 12.85 to 8.92); the effect of dCBT-I was comparable to that of combination therapy but showed unstable durability. During the first three months, the outcomes of dCBT-I improved steadily and rapidly, then fluctuated. Higher response rates were seen with dCBT-I and combination therapy compared with medication. Significant benefits were seen from dCBT-I and combination therapy in secondary outcomes.

“These positive findings provide clinical evidence that dCBT-I contributes to meaningful sleep improvements,” the authors write. “Given the unstable durability of dCBT-I at six-month follow-up, the design, implementation, and delivery of dCBT-I in the practice setting warrants further investigation.”

One author disclosed financial ties to Hangzhou slan-health.

More information:
Menglin Lu et al, Comparative Effectiveness of Digital Cognitive Behavioral Therapy vs Medication Therapy Among Patients With Insomnia, JAMA Network Open (2023). DOI: 10.1001/jamanetworkopen.2023.7597

Journal information:
JAMA Network Open

Source: Read Full Article