Evidence map›Paper›PMID 37040111›Full record

ArticleJAMA network open2023

Comparative Effectiveness of Digital Cognitive Behavioral Therapy vs Medication Therapy Among Patients With Insomnia.

Menglin Lu, Yaoyun Zhang, Junhang Zhang, Songfang Huang, Fei Huang, Tingna Wang, Fei Wu, Hongjing Mao, Zhengxing Huang

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
7.4field-weighted citation impact, top 2% of its field
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

17 citing papers in PubMed, 29 citations in OpenAlex.

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  17. Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024
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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

9 authors at 3 institutions in 1 country.

Menglin LuZhejiang University, Hangzhou, China.
Yaoyun ZhangAlibaba Damo Academy, Hangzhou, China.
Junhang ZhangHangzhou Seventh People's Hospital, Hangzhou, China.
Songfang HuangAlibaba Damo Academy, Hangzhou, China.
Fei HuangAlibaba Damo Academy, Hangzhou, China.
Tingna WangHangzhou slan-health Co, Ltd, Hangzhou, China.
Fei WuZhejiang University, Hangzhou, China.
Hongjing MaoZhejiang University, Hangzhou, China.
Zhengxing HuangZhejiang University, Hangzhou, China.
Alibaba Group (China) · CNZhejiang University · CNHangzhou Seventh Peoples Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Although digital cognitive behavioral therapy for insomnia (dCBT-I) has been studied in many randomized clinical trials and is recommended as a first-line treatment option, few studies have systematically examined its effectiveness, engagement, durability, and adaptability in clinical settings. Objective: To evaluate the clinical effectiveness, engagement, durability, and adaptability of dCBT-I. Design, Setting, and Participants: This retrospective cohort study was conducted using longitudinal data collected via a mobile app named Good Sleep 365 between November 14, 2018, and February 28, 2022. Three therapeutic modes (ie, dCBT-I, medication, and their combination) were compared at month 1, month 3, and month 6 (primary). Inverse probability of treatment weighting (IPTW) using propensity scores was applied to enable homogeneous comparisons between the 3 groups. Exposures: Treatment with dCBT-I, medication therapy, or combination therapy according to prescriptions. Main Outcomes and Measures: The Pittsburgh Sleep Quality Index (PSQI) score and its essential subitems were used as the primary outcomes. Effectiveness on comorbid somnolence, anxiety, depression, and somatic symptoms were used as secondary outcomes. Cohen d effect size, P value, and standardized mean difference (SMD) were used to measure differences in treatment outcomes. Changes in outcomes and response rates (≥3 points change in PSQI score) were also reported. Results: A total of 4052 patients (mean [SD] age, 44.29 [12.01] years; 3028 [74.7%] female participants) were selected for dCBT-I (n = 418), medication (n = 862), and their combination (n = 2772). Compared with the change in PSQI score at 6 months for participants receiving medication alone (from a mean [SD] of 12.85 [3.49] to 8.92 [4.03]), both dCBT-I (from a mean [SD] of 13.51 [3.03] to 7.15 [3.25]; Cohen d, -0.50; 95% CI, -0.62 to -0.38; P < .001; SMD = 0.484) and combination therapy (from a mean [SD] of 12.92 [3.49] to 6.98 [3.43]; Cohen d, 0.50; 95% CI, 0.42 to 0.58; P < .001; SMD = 0.518) were associated with significant reductions; dCBT-I had a comparable effect as combination therapy (Cohen d, 0.05; 95% CI, -0.05 to 0.15; P = .66; SMD = 0.05), but showed unstable durability. Outcomes of dCBT-I improved steadily and rapidly during the first 3 months, and then fluctuated. The response rates with dCBT-I and combination therapy were higher than with medication. Changes in secondary outcomes indicated statistically significant benefits from dCBT-I and combination therapy. The results of subgroup analysis were consistent with the main findings, demonstrating the superiority of dCBT-I vs medication therapy in various subpopulations. Conclusions and Relevance: In this study, clinical evidence suggested that combination therapy was optimal, and dCBT-I was more effective than medication therapy, with long-term benefits for insomnia. Future studies are needed to analyze its clinical effectiveness and reliability in distinct subpopulations.

Indexed as

Cognitive Behavioral TherapySleep Initiation and Maintenance DisordersAdultCohort StudiesFemaleHumansMaleReproducibility of ResultsRetrospective StudiesSleep

Identifiers

PMID37040111
PMCPMC10091171
OpenAlexW4364352157

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.