Evidence map›Paper›PMID 37057059›Full record

ArticleTobacco induced diseases2023

Evaluation of the smoking cessation effects of QuitAction, a smartphone WeChat platform.

Jianghua H Xie, Yanfang F Qiu, Lei Zhu, Yina Hu, Xiaochang Chang, Wei Wang, Lemeng M Zhang, Ouying Y Chen, Xianmin Zhong, Xinhua Yu and 2 more

Abstract read
In one paragraph

Article in Tobacco induced diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Early childhood caries detection using smartphone artificial intelligence.European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry · 2024
    Article
  5. Article
  6. Article
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

12 authors.

Jianghua H XieHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Yanfang F QiuHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Lei ZhuHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Yina HuSchool of Nursing and Health Management, Wuhan Donghu University, Wuhan, China.
Xiaochang ChangHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Wei WangHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Lemeng M ZhangHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Ouying Y ChenSchool of Nursing, Hunan University of Chinese Medicine, China.
Xianmin ZhongHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Xinhua YuHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Yanhui ZouHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.
Rui ZhongHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMany smokers in China desire to quit, though the success rate among adults is low. This study evaluated the effects of QuitAction, a WeChat smoking cessation platform, summarized the intervention experience of the smoking cessation platform, identified aspects of the platform that necessitated improvement, and provided references for further optimization of the smoking cessation platform.

methodsThis single-arm study was conducted in Hunan, China, from September 2020 to October 2021. Regular smokers, who were aged ≥15 years and willing to quit smoking using QuitAction, were recruited. An in-application questionnaire evaluated participants' baseline smoking status and intention to quit smoking. The QuitAction program included questionnaires regarding the participants' ongoing smoking cessation status at 24 hours, one week, one month and three months after quitting. The smoking cessation procedure was discontinued if the participant had no intention of continuing. The smoking cessation rate, influencing success factors, frequency of use satisfaction, and helpfulness of QuitAction were recorded.

resultsA total of 303 participants registered and logged into the QuitAction program, including 59 with incomplete information and 64 with no intention of quitting. The study finally included 180 participants. The smoking cessation rate was 33.9% at 24 hours, 27.2% at one week, 26.1% at one month, and 25.0% at three months. QuitAction was reported as helpful by 94.9% of participants and 95.7% were satisfied with the program. Participants with a quitting difficulty score of 80-100 were less likely to quit smoking than participants with a difficulty score of 0-60 (OR=0.28; 95% CI: 0.10-0.78; p=0.015). Participants using the platform ≥5 times were more likely to quit smoking than those who used the platform <5 times (OR=3.59; 95% CI: 1.51-8.52; p=0.004).

conclusionsThe QuitAction platform provides smoking cessation services that can improve smokers' success rate and improve user experience satisfaction.

Indexed as

evaluationmobile medical treatmentsmoking cessationWeChat mini program

Identifiers

PMID37057059
PMCPMC10088363

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.