Evidence map›Paper›PMID 41246294›Full record

ReviewSleep medicine: X2025

Internet-delivered cognitive behavioral therapy for insomnia: The future of insomnia treatment with large language models.

Chenxing Lin, Chen Cheng, Yu Xia, Ruoyun Wang, Luying Zhang, Lintong Han, Darong Hai, Chenyue Dai, Tianen Dai, Luhuan Cao and 12 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Sleep medicine: X, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Chenxing LinOujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision, and Brain Health), 325000, China.
Chen ChengThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Yu XiaThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Ruoyun WangThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Luying ZhangThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Lintong HanSchool of Sports Science, Qufu Normal University, Qufu, Jining, 273165, China.
Darong HaiSchool of Nursing, Wenzhou Medical University, Wenzhou, 325000, China.
Chenyue DaiSchool of Nursing, Wenzhou Medical University, Wenzhou, 325000, China.
Tianen DaiThe Second Clinical Medical College of Wenzhou Medical University, Wenzhou, 325000, China.
Luhuan CaoSchool of Nursing, Wenzhou Medical University, Wenzhou, 325000, China.
Xingyu ZhuThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Hao ChenThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Li ZengThe Second Clinical Medical College of Wenzhou Medical University, Wenzhou, 325000, China.
Chufan RenThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Dongren YangThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Yijun WangThe Second Clinical Medical College of Wenzhou Medical University, Wenzhou, 325000, China.
Meijia ZhangThe First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, 325000, China.
Zefei MoSchool of Biomedical Engineering, School of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, 325000, China.
Yinda ChenSchool of Electrical and Information Engineering, Quzhou University, Quzhou, 324000, China.
Jianwei ShuaiWenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, 325000, China.
Rongwen YuWenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, 325000, China.
Yuming PengDepartment of General Practice, Central Hospital of Karamay, Xinjiang, 834000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rise in the prevalence of insomnia, cognitive behavioral therapy for insomnia (CBT-I) has become an important non-pharmacological approach to the treatment of insomnia patients. Traditional CBT-I faces challenges such as low patient acceptance and long treatment cycles. To address these issues, Internet-delivered Cognitive Behavioral Therapy for Insomnia (eCBT-I) emerged as a digital treatment modality with greater flexibility, accessibility and cost-effectiveness. However, eCBT-I still faces issues such as digital literacy and patient engagement. With the development of artificial intelligence (AI) technology, especially the application of large language models (LLM), AI-driven CBT-I is becoming an important direction for future therapy. The LLM is able to provide personalized treatment recommendations based on patient feedback, improving treatment outcomes and patient engagement. This paper reviews the application status and challenges of CBT-I and eCBT-I, focuses on the potential and prospect of LLM in CBT-I therapy, and proposes future research directions, including multi-source data fusion and privacy protection issues, to promote the innovation and development of CBT-I.

Indexed as

Artificial intelligenceCognitive behavioral therapy for insomniaInsomnia treatmentInternet-delivered cognitive behavioral therapy for insomniaLarge language models

Identifiers

PMID41246294
PMCPMC12615300

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.