ArticleTobacco induced diseases2019
Patients' self-reported receipt of brief smoking cessation interventions based on a decision support tool embedded in the healthcare information system of a large general hospital in China.
Article in Tobacco induced diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Usage, acceptability, and preliminary effectiveness of an mHealth-based integrated modality for smoking cessation interventions in Western China.Tobacco induced diseases · 2023Article
- The estimated influence of assumed physicians' advice for tobacco smoking cessation among current smokers in Shanghai, China: A cross-sectional study.Tobacco induced diseases · 2022Article
- Smoking behaviour among adult patients presenting to health facilities in four provinces of Vietnam.BMC public health · 2021Article
- Impact of the ENSP eLearning platform on improving knowledge, attitudes and self-efficacy for treating tobacco dependence: An assessment across 15 European countries.Tobacco induced diseases · 2020Article
- Relationships among smoking abstinence self-efficacy, trait coping style and nicotine dependence of smokers in Beijing.Tobacco induced diseases · 2020Article
- Smoking cessation advice from healthcare professionals helps those in the contemplation and preparation stage: An application with transtheoretical model underpinning in a community-based program.Tobacco induced diseases · 2020Review
- Impact of tobacco control auxiliary resources on the 5As behavior in nursing interns: Self-reports from students.Tobacco induced diseases · 2020Article
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5 authors.
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Abstract
introductionHealthcare information systems (HIS) are used to aid healthcare providers delivering brief smoking cessation interventions. However, evidence regarding the effectiveness of intervention models in developing countries remains limited. A smoking cessation intervention model based on a decision support tool embedded in HIS (an 'e-information model', including Ask, Advise, Assess, Inform, Refer and Print components) was applied in a large urban general hospital in Beijing, China. The current study was a preliminary evaluation of the implementation and effectiveness of this model.
methodsWe conducted a retrospective investigation in the outpatient department of the hospital in the period June-July 2017. Using a paper questionnaire, patients' self-reported receipt of the e-information model in the past 2 months and their plans to quit within 1 month were collected. Multivariate logistic regression analysis was used to examine the association between receiving the e-information model and patients' plans to quit.
resultsAmong 656 currently smoking patients, the proportion of patients receiving the Ask, Advise, Assess, Refer and Print components were 73.2%, 65.4%, 49.8%, 16.0% and 10.4%, respectively. The results revealed a dose-response relationship between the number of components received and the proportion of patients planning to quit (p-trend=0.006). The likelihood of patients planning to quit within 1 month was highest among those receiving all five components (OR=2.79, 95% CI: 1.31-5.94). Moreover, a simplified model composed of two or three components also revealed a potential effect on increasing the proportion of patients planning to quit.
conclusionsThe e-information model was applied effectively in the study hospital and appeared to encourage patients to plan to quit smoking. This model could be generalized to other hospitals in China and other developing countries. However, many components of this model were less utilized, and comprehensive measures will be required to improve its application in the future.
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