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Digital insomnia therapy: planned time may shape symptom improvement

Across trials, longer planned therapy time was linked with greater symptom improvement before gains leveled off. Modeling did not establish a schedule that works best for everyone.

By 100HP editorialAbstract-based explanation checked

Based on the published abstract. The full paper may contain additional methods, results and limitations.

The 30-second takeaway

The analysis suggests that additional planned therapy time was associated with larger modeled improvements in insomnia symptoms up to a plateau. This supports closer study of treatment duration, but the model does not establish an ideal schedule for every patient. Planned minutes also do not show how much therapy people actually completed.

Keep in mind

The abstract does not detail controls, symptom-assessment timing, or actual therapy completion. This abstract-based account cannot establish whether modeled differences would hold in direct trials comparing treatment durations.

THE NUMBERS, WITH CONTEXT

What researchers found

-5.77 points

Modeled maximum reduction in Insomnia Severity Index score

Digital therapy versus control; 95% credible interval -7.51 to -4.68. Outcome-assessment timing was not reported.

Behav Res Ther, 2026 · Original source ↓

Planned time versus participation

Treatment time meant the scheduled session count multiplied by minutes per session. That describes the intended commitment in each protocol. It does not establish how long participants actually engaged with the digital therapy.

Understanding the symptom score

The Insomnia Severity Index measures symptom severity. The negative estimate indicates a modeled reduction in symptoms compared with control. It describes the model's estimated maximum effect, rather than an improvement every participant can expect.

CHECK THE ORIGINAL

The original publication

Defining the dose-response curve of digital CBT for insomnia: a model-based network meta-analysis of treatment duration and clinical effectiveness.

Huang YB, Yuan L, Zhu Y et al.
Behav Res Ther · 2026

PubMed ID
41830655
Record checked

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