Evidence map›Paper›PMID 41358214›Full record

ArticleFrontiers in public health2025

Mobile phone data analyses for public health research: a scoping review.

Xuening Cheng, Wei Jiang, Siyi Liu, Xuyan Lou, Yang Li, Lefan Liu, Molin Li, Xuyang Wang, Yan Cen, Alain Chong and 1 more

Abstract readScoping Review
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

11 authors.

Xuening ChengSchool of Economics, Faculty of Humanities and Social Sciences, University of Nottingham, Ningbo, China.
Wei JiangCollege of Accounting, Ningbo University of Finance and Economics, Ningbo, China.
Siyi LiuKelley School of Business, Indiana University, Bloomington, IN, United States.
Xuyan LouSchool of Economics, Faculty of Humanities and Social Sciences, University of Nottingham, Ningbo, China.
Yang LiSchool of Economics, Faculty of Humanities and Social Sciences, University of Nottingham, Ningbo, China.
Lefan LiuDepartment of Applied Health Sciences, University of Birmingham, Birmingham, United Kingdom.
Molin LiSchool of Economics, Faculty of Humanities and Social Sciences, University of Nottingham, Ningbo, China.
Xuyang WangSmartsteps Data Technology Co., Ltd., Beijing, China.
Yan CenSmartsteps Data Technology Co., Ltd., Beijing, China.
Alain ChongNottingham University Business School, University of Nottingham, Ningbo, China.
Zhuo ChenSchool of Economics, Faculty of Humanities and Social Sciences, University of Nottingham, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobile phone data provide high-resolution, near real-time measurements of population mobility and have become an increasingly valuable source for public health research, enabling rapid evaluation of policy impacts on human movement and pandemic control. However, the methodological challenges surrounding the extraction, governance, and validation of mobile phone data for the public health community remain insufficiently explored. Following the PRISMA-ScR framework, we conduct a scoping review to synthesize major research themes, opportunities, and challenges in the use of mobile phone data for public health, particularly pandemic-related studies. Our findings highlight limitations in the empirical use of these datasets, including demographic and population coverage, representativeness, and equity issues, as well as the transparency of data extraction and processing. We also provide guidance for future research, including the development of standardized frameworks for data curation and validation, a clear understanding of algorithms that extract mobility information, and rigorous interpretation of mobility metrics.

Indexed as

Cell PhoneData AnalysisPublic HealthHumansmobile phone datamobile signaling datapandemicpopulation mobilitypublic health

Identifiers

PMID41358214
PMCPMC12675487

What Socratic 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 Socratic graph.