Evidence map›Paper›PMID 42528701›Full record

ArticleFrontiers in public health2026

Relationships of mobile phone duration and unlock counts with sleep: double machine learning and traditional statistical methods.

Lei Zhang, Mingyang Wu, Zhe Wang, Xue Wang, Xiaoxiao Yuan, Le Ma, Wenhua Wang

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Lei Zhang *School of General Medicine, Xi'an Medical University, Xi'an, China.
Mingyang Wu *Xiangya School of Public Health, Central South University, Changsha, China.
Zhe WangShaanxi Medical Association, Xi'an, China.
Xue WangSchool of General Medicine, Xi'an Medical University, Xi'an, China.
Xiaoxiao YuanSchool of General Medicine, Xi'an Medical University, Xi'an, China.
Le MaSchool of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Wenhua WangSchool of General Medicine, Xi'an Medical University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The association between mobile phone use and sleep is still contested, especially for youth. While most existing studies predominantly rely on self-reported smartphone duration using traditional statistical methods, the potential association between mobile phone unlock counts and sleep has been neglected in prior studies primarily due to the difficulty of estimating the data. This relationship has been largely overlooked due to objective measurement challenges. Aims: To examine the associations of mobile phone duration and unlock counts with sleep quality and sleep time. Methods: This multi-center investigation included 16,668 participants from six Chinese universities. Objective mobile phone duration and unlock counts were assessed by mobile phone use record screenshots. The Pittsburgh Sleep Quality Index was used to assess sleep quality and time. Double Machine Learning (DML), linear regression, and restricted cubic splines (RCS) models were applied. Results: DML revealed that a 7-h/week increase in mobile phone duration was associated with higher PSQI scores ( Conclusion: Both mobile phone duration and unlock counts are associated with sleep quality and sleep time. Mobile phone duration exhibited non-linear associations with sleep time and poor sleep, showing an inverted U-shaped relationship with sleep time. Mobile phone unlock counts exhibited a non-linear relationship with sleep time, but a predominantly monotonic inverse relationship with odds of poor sleep.

Indexed as

Cell PhoneCell Phone UseMachine LearningSleepSleep QualityAdultChinaFemaleHumansMaleSleep DurationTime FactorsUniversitiesYoung Adultdouble machine learningmobile phone durationmobile phone unlock countssleep qualitysleep time

Identifiers

PMID42528701
PMCPMC13414734

What Socratic 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 Socratic graph.