Evidence map›Paper›PMID 39551939›Full record

ArticleBrain and behavior2024

Smartphone Application-Based Addiction Scale: Psychometric Evidence Across Nine Asian Regions Using Advanced Analytic Methods.

I-Hua Chen, Iqbal Pramukti, Wan Ying Gan, Kamolthip Ruckwongpatr, Le An Pham, Po-Ching Huang, Mohammed A Mamun, Irfan Ullah, Haitham A Jahrami, Chung-Ying Lin and 1 more

Abstract read
In one paragraph

Article in Brain and behavior, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

11 authors.

I-Hua ChenChinese Academy of Education Big Data, Qufu Normal University, Qufu, China.ORCID https://orcid.org/0000-0001-6999-6406
Iqbal PramuktiDepartment of Community Health Nursing, Faculty of Nursing, Universitas Padjadjaran, Sumedang, West Java, Indonesia.
Wan Ying GanDepartment of Nutrition, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
Kamolthip RuckwongpatrInstitute of Allied Health Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Le An PhamCenter of Family Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam.
Po-Ching HuangSchool of Physical Therapy, Graduate Institute of Rehabilitation Science, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Mohammed A MamunDepartment of Public Health and Informatics, Jahangirnagar University, Dhaka, Bangladesh.ORCID https://orcid.org/0000-0002-1728-8966
Irfan UllahKabir Medical College, Gandhara University, Peshawar, Pakistan.ORCID https://orcid.org/0000-0003-1100-101X
Haitham A JahramiDepartment of Community Health Nursing, Faculty of Nursing, Universitas Padjadjaran, Sumedang, West Java, Indonesia.
Chung-Ying LinDepartment of Community Health Nursing, Faculty of Nursing, Universitas Padjadjaran, Sumedang, West Java, Indonesia.ORCID https://orcid.org/0000-0002-2129-4242
Amir H PakpourDepartment of Nursing, School of Health and Welfare, Jönköping University, Jönköping, Sweden.ORCID https://orcid.org/0000-0002-8798-5345

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionA smartphone is a device with various functions, including wifi, application functions, mobile networks, ease of mobility, and the capability of using mobile data. Because of the aforementioned functions, people may use smartphones frequently. The Smartphone Application-Based Addiction Scale (SABAS) is a six-item questionnaire assessing smartphone addiction with promising psychometric properties. However, it is unclear if the SABAS possesses the strong psychometric properties across Asian regions. The present study aimed to examine the factor structure of the SABAS across nine Asian regions.

methodsUsing datasets collected from Asian regions of Bangladesh, China, Indonesia, Iran, Malaysia, Pakistan, Taiwan, Thailand, and Vietnam, data from 10,397 participants (mean age = 22.40 years; 44.8% men) were used for analyses. All participants completed the SABAS using an online survey or paper-and-pencil mode.

resultsFindings from confirmatory factor analysis, Rasch analysis, and network analysis all indicate a one-factor structure for the SABAS. Moreover, the one-factor structure of the SABAS was measurement invariant across age (21 years or less vs. above 21 years) and gender (men vs. women) in metric, scalar, and strict invariance. The one-factor structure was invariant across regions in metric but not scalar or strict invariance.

conclusionThe present study findings showed that the SABAS possesses a one-factor structure across nine Asian regions; however, noninvariant findings in scalar and strict levels indicate that people in the nine Asian regions may interpret the importance of each SABAS item differently. Age group and gender group comparisons are comparable because of the invariance evidence for the SABAS found in the present study. However, cautions should be made when comparing SABAS scores across Asian regions.

Indexed as

PsychometricsSmartphoneAdultAsiaFactor Analysis, StatisticalFemaleHumansInternet Addiction DisorderMaleMobile ApplicationsSurveys and QuestionnairesYoung Adultproblematic smartphone usepsychometricsSABASsmartphone addictionsmartphone dependency

Identifiers

PMID39551939
PMCPMC11570418

What Socratic holds

Textmetadata
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.