Evidence map›Paper›PMID 35270285›Full record

ArticleInternational journal of environmental research and public health2022

Distinguishing Different Types of Mobile Phone Addiction: Development and Validation of the Mobile Phone Addiction Type Scale (MPATS) in Adolescents and Young Adults.

Qing-Qi Liu, Xiao-Pan Xu, Xiu-Juan Yang, Jie Xiong, Yu-Ting Hu

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In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
17.0field-weighted citation impact, top 1% 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 48 citations in OpenAlex.

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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

5 authors at 5 institutions in 1 country.

Qing-Qi LiuCollege of Education for the Future, Beijing Normal University at Zhuhai, Zhuhai 519087, China.ORCID 0000-0001-5169-8689
Xiao-Pan XuInstitute for Public Policy and Social Management Innovation, College of Political Science and Public Administration, Henan Normal University, Xinxiang 453007, China.
Xiu-Juan YangSchool of Psychology, Central China Normal University, Wuhan 430079, China.
Jie XiongCenter for Mental Health, Wuhan University of Technology, Wuhan 430063, China.
Yu-Ting HuSchool of Business, Jiangnan University, Wuxi 214122, China.
Beijing Normal University · CNCentral China Normal University · CNHenan Normal University · CNJiangnan University · CNWuhan University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Researchers have developed various versions of scales to measure mobile phone addiction. Existing scales, however, focus primarily on the overall level of mobile phone addiction but do not distinguish the potential differences between different types of mobile phone addiction. There is a lack of established scales that can measure different types of mobile phone addiction. The present study aimed to uncover the specific types of mobile phone addiction and develop a Mobile Phone Addiction Type Scale (MPATS) for adolescents and young adults. Adolescents and young adults from two high schools and two universities in Central and South China participated in our study. A total of 108 mobile phone addicts (M

Indexed as

Behavior, AddictiveCell PhoneMobile ApplicationsVideo GamesAdolescentFemaleHumansMaleReproducibility of ResultsSurveys and QuestionnairesTechnology AddictionYoung Adultadolescentsmobile phone addiction typereliabilityvalidityyoung adults

Identifiers

PMID35270285
PMCPMC8909301
OpenAlexW4213413043

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.