Evidence map›Paper›PMID 37098499›Full record

ArticleBMC public health2023

Using the Unified Theory of Acceptance and Use of Technology (UTAUT) and e-health literacy(e-HL) to investigate the tobacco control intentions and behaviors of non-smoking college students in China: a cross-sectional investigation.

Yuanyuan Ma, Mengxia Zhou, Wenli Yu, Ziyue Zou, Pu Ge, Zheng Feei Ma, Yuting Tong, Wei Li, Qiyu Li, Yunshan Li and 3 more

Abstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Determinants of Smoking Among University Students in Northern Iraq.Journal of research in health sciences · 2025
    Article
  7. Article
  8. Article
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  10. Review
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

13 authors.

Yuanyuan MaSchool of Public Health, Shandong University, Jinan, 250012, China.
Mengxia ZhouSchool of Media and Communication, Shanghai Jiaotong University, Shanghai, 201100, China.
Wenli YuSchool of Foreign Languages, Weifang University of Science and Technology, Shouguang, 262700, China.
Ziyue ZouSchool of Public Health, Shandong University, Jinan, 250012, China.
Pu GeSchool of Management, Beijing University of Chinese Medicine, Beijing, 100029, China.
Zheng Feei MaCentre for Public Health and Wellbeing, School of Health and Social Wellbeing, College of Health, Science and Society, University of the West of England, Bristol, BS16 1QY, UK.
Yuting TongSchool of Public Health, Shandong University, Jinan, 250012, China.
Wei LiDepartment of Second Clinical Medical School, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Qiyu LiSchool of Humanities and Health Management, Jinzhou Medical University, Jinzhou, 121000, China.
Yunshan LiSchool of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China.
Siya ZhuSchool of Foreign Languages, Anhui University of Technology, Anhui, 243000, China.
Xinying SunSchool of Public Health, Peking University, Haidian District, 38 Xueyuan Road, Beijing, 100191, China. xysun@bjmu.edu.cn.
Yibo WuSchool of Public Health, Peking University, Haidian District, 38 Xueyuan Road, Beijing, 100191, China. bjmuwuyibo@outlook.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-smoking college students are starting to smoke in increasing numbers, which shows that their tobacco control situation seems not optimistic. The UTAUT and e-HL are commonly used models and theories to predict health behaviors, while there are few studies on tobacco control. This paper aims to study the influencing factors of tobacco control intention and behavior of non-smoking college students in China by combining the UTAUT and e-HL.

methodsBased on the stratified sampling method, 625 college students from 12 universities were selected. Data were collected using a self-made questionnaire designed based on the UTAUT and e-health literacy scales. Data were analyzed by SPSS 22 and AMOS 26, including descriptive statistics, one-way variance analysis and structural equation model analysis.

resultsThe results of one-way variance analysis showed that there were significant differences in the score of non-smoking college students' tobacco control intention or behavior by hometowns, monthly living expenses, and parents' smoking history. Performance expectancy, effort expectancy, social influence had direct positive effects on behavioral intention. Facilitating condition, behavioral intention had direct positive impacts on use behavior and e-HL had an indirect positive impact on use behavior.

conclusionsThe combination of the UTAUT and e-HL can be used as an appropriate framework to predict the influencing factors of non-smoking college students' intention and behavior of tobacco control. Improving performance expectancy, effort expectancy, and e-HL among non-smoking college students, creating positive social environments, and providing facilitating condition are key aspects of increasing their tobacco control intention and behavior. It is also beneficial to promote the implementation of smoke-free campus and smoke-free family projects.

Indexed as

Health LiteracyTobacco ControlChinaCross-Sectional StudiesHumansIntentionStudentsSurveys and QuestionnairesTechnologyE-health literacyNon-smoking college studentsStructural equation modelTobacco controlUTAUT

Identifiers

PMID37098499
PMCPMC10127360

What OpenQuestion 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 OpenQuestion graph.