Evidence map›Paper›PMID 40756740›Full record

ArticleNature and science of sleep2025

Accuracy Bias and Factors Influencing Polysomnography and Consumer Sleep-Monitoring Device Measuring of Total Sleep Time: A Mixed-Methods Study.

Jing Yang, Dongmei Xu, Huanhuan Lu, Xuwen Yin, Haiyan Song, Weiwei Zong, Dandan Xu, Xiaohui Lu, Lan Wei, Hong Zhu and 2 more

Abstract read
In one paragraph

Article in Nature and science of sleep, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. 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

12 authors.

Jing Yang *School of Nursing, Nanjing University of Chinese Medicine, Nanjing, People's Republic of China.
Dongmei Xu *Rheumatology and Immunology Department, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Huanhuan LuSchool of Nursing, Nanjing Medical University, Nanjing, People's Republic of China.
Xuwen YinSchool of Nursing, Nanjing University of Chinese Medicine, Nanjing, People's Republic of China.ORCID 0000-0003-1485-5475
Haiyan SongSchool of Nursing, Nanjing University of Chinese Medicine, Nanjing, People's Republic of China.ORCID 0009-0004-9053-7289
Weiwei ZongCardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Dandan XuCardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Xiaohui LuCardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Lan WeiCardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Hong ZhuCardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Shiyin ZhaiCardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Zejuan GuSchool of Nursing, Nanjing University of Chinese Medicine, Nanjing, People's Republic of China.ORCID 0000-0002-2893-1697

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The Huawei Band 9 (HWB 9), a consumer sleep-monitoring device with a high market share and a large user base in China, can provide sleep staging parameters and has broad representativeness in sleep monitoring applications. This study aims to compare the accuracy bias of polysomnography (PSG) and consumer sleep-monitoring devices, specifically the HWB 9, in measuring total sleep time (TST) and explore the factors affecting accuracy bias. Methods: This study employed a sequential explanatory mixed-methods design, with quantitative research comprising 108 samples and qualitative research comprising 18 samples. Select hospitalized patients who required polysomnographic monitoring due to their condition from November 2024 to March 2025 were chosen as the research subjects, and who used PSG and HWB 9 for synchronous sleep monitoring throughout the night. Quantitative data analysis was conducted using descriptive statistics, the Wilcoxon test, Bland-Altman plots, univariate analysis, and multiple linear regression analysis. Qualitative content data were analyzed using NVivo 14.0 software. Results: The statistical analysis showed a significant difference (P < 0.05) between the HWB 9 and PSG in measuring TST. The Bland-Altman plot showed that the measured values deviated from the consistency interval, indicating systematic overestimation bias. The multiple linear regression analysis showed that turning frequency and sleep posture were significant factors affecting measurement bias. Two main themes were found in the qualitative research: sleep habits and environmental factors, and individual differences and psychological perceptions. Conclusion: Considering the significant variations in individuals, data from such devices should be used with caution in clinical practice.

Indexed as

accuracy biasconsumer sleep-monitoring devicesinfluencing factorsmixed-methodsPSGTST

Identifiers

PMID40756740
PMCPMC12318514

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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.