Evidence map›Paper›PMID 32898191›Full record

ArticlePloS one2020

Factors associated with smartphone addiction: A comparative study between Japanese and Thai high school students.

Arunrat Tangmunkongvorakul, Patou Masika Musumari, Yukie Tsubohara, Pisittawoot Ayood, Kriengkrai Srithanaviboonchai, Teeranee Techasrivichien, S Pilar Suguimoto, Masako Ono-Kihara, Masahiro Kihara

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
8.7field-weighted citation impact, top 2% 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

14 citing papers in PubMed, 47 citations in OpenAlex.

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  9. Food Addiction and Emotional Eating Behaviors Co-Occurring with Problematic Smartphone Use in Adolescents?International journal of environmental research and public health · 2022
    Article
  10. Article
  11. An Investigation into Smartphone Addiction with Personality and Sleep Quality among University Students.International journal of environmental research and public health · 2021
    Article
  12. Article
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  14. Observational
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

9 authors at 2 institutions in 2 countries.

Arunrat TangmunkongvorakulResearch Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand.
Patou Masika MusumariResearch Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0002-8203-4532
Yukie TsuboharaResearch Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand.
Pisittawoot AyoodSankampang Hospital, Chiang Mai, Thailand.
Kriengkrai SrithanaviboonchaiResearch Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand.
Teeranee TechasrivichienDepartment of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan.
S Pilar SuguimotoDepartment of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan.
Masako Ono-KiharaGlobal Health Interdisciplinary Unit, Center for the Promotion of Interdisciplinary Education and Research, Kyoto University, Kyoto, Japan.
Masahiro KiharaDepartment of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan.
Kyoto University · JPChiang Mai University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSmartphone addiction is a growing social problem with adverse health outcomes. There are few comparative studies in Asia that examine factors associated with smartphone addiction. The current study aimed to address this research gap by presenting a comparative analysis of factors associated with smartphone addiction in Japan and Thailand, two countries heterogeneous in both their level of economic development and culture.

methodsParticipant data were collected using two population-based surveys. Participants were high school students in grade 11, aged 16-17 years old, and were selected using quota sampling in Japan in 2014 and random sampling in Thailand in 2016. The outcome of interest was smartphone addiction, measured using a modified version of the Young Diagnostic Questionnaire for Internet Addiction. Multiple logistic regression analysis was performed to determine factors associated with smartphone addiction (gender; nationality; family connectedness; and average time spent on smartphone per day).

resultsThis study included a total of 7694 students, 6585 students from Japan and 1109 students from Thailand. The prevalence of smartphone addiction was 35.9% among Thai students and 12% among Japanese students. Thai students were more likely to have smartphone addiction than Japanese students (AOR 2.76; 95% CI: 2.37-3.30). Being female was associated with increased odds of smartphone addiction in both Japanese (AOR 1.53; 95% CI: 1.32-1.78) and Thai students (AOR 1.34; 95% CI: 1.01-1.78). The parental connectedness variables "my parents noticed when I was unhappy" (AOR 0.77; 95% CI: 0.62-0.96) and "my parents noticed when I did something good" (AOR 0.78, 95% CI: 0.61-0.99) were associated with lower odds of smartphone addiction among Japanese students.

conclusionSmartphone addiction was more prevalent among Thai adolescents than Japanese adolescents, and more prevalent among females than males in both countries. Interventions for reducing smartphone addiction should take into account both context and gender, and should leverage the protective effect of parental connectedness.

Indexed as

AdolescentAdolescent BehaviorBehavior, AddictiveFemaleHumansJapanMaleParentsPrevalenceSmartphoneStudentsSurveys and QuestionnairesThailand

Identifiers

PMID32898191
PMCPMC7478618
OpenAlexW3084307740

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.