Understanding how a smoking cessation intervention changes beliefs, self-efficacy, and intention to quit: a secondary analysis of a pragmatic randomized controlled trial

Pardavila‐Belio, Miren Idoia; Canga‐Armayor, Ana; Duaso, María; Pueyo‐Garrigues, Sara; Pueyo‐Garrigues, María; Canga‐Armayor, Navidad

doi:10.1093/tbm/ibx070

Cited by 9 publications

(5 citation statements)

References 47 publications

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“…In addition, we found that the more components of the e-information model the participants received in the past 2 months, the higher was the proportion of participants planning to quit smoking within 1 month. In addition, several previous studies reported that planning to quit is a key predictor of successful quitting 33,34 . Thus, whether the e-information model can increase the quit rate of smoking patients should be verified by large randomized controlled clinical trials in the future.…”

Section: Discussionmentioning

confidence: 99%

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

Chu¹,

Liang²,

Jing³

et al. 2019

Tob. Induc. Dis.

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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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Section: Discussionmentioning

confidence: 99%

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

Chu¹,

Liang²,

Jing³

et al. 2019

Tob. Induc. Dis.

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“…Additionally, this study measured the intention to quit rather than actual cessation behaviors, although a strong intention to quit is ultimately expressed in cessation behaviors. According to Pardavila-Belio [44], the intention to quit only partially regulates the rate of successful cessation (by 36.2%), and cessation self-efficacy is related to actual cessation behaviors. Another study reported that self-efficacy is positively associated with the intention to quit smoking but negatively related to risk perception, which weakens its effect on the overall intention to quit [45].…”

Section: Factors Affecting Smoking Behaviors and Intentions To Quit S...mentioning

confidence: 99%

Depression is a predictor for both smoking and quitting intentions among male coronary artery disease patients

Wei

Huang

Tsai

et al. 2023

IJPHS

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Coronary artery disease (CAD) is the third most prominent cause of death globally, and smoking is the most common risk factors for CAD. However, few studies have examined both smoking and smoking cessation intentions in patients with CAD. The study aims to explore the predictors for smoking and quitting intentions among male CAD patients. This was a cross-sectional study. A total of 368 male CAD patients were recruited and classified into never smoked, quit smoking, and continuing to smoke three groups. Demographic information, level of nicotine dependence, carbon monoxide concentration, depression, and resilience were analyzed by using t-test, one- way analysis of variance (ANOVA), and least significant difference (LSD) post-hoc test and the multiple logistic regression analysis. The results revealed that among participants, 23.1% had never smoked, 40.5% had quit smoking, and 36.4% continued to smoke. Multiple logistic regression analysis revealed that age (OR=0.95, 95% CI=0.90–0.99), carbon monoxide (OR=1.74, 95% CI=1.51–2.01), and depression (OR=1.13, 95% CI=1.04–1.23) predicted participants who continued to smoke. Among the 134 participants who continued to smoke, 35.8% exhibited no intention to quit, and 64.2% planned to quit. Nicotine dependence (OR=0.79, 95% CI=0.66–0.94) and depression (OR=1.10, 95% CI=1.02–1.20) were significant predictors in participants who intended to quit smoking. The study demonstrates that depression is a significant predictor for both smoking and quitting intentions among male CAD patients.

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“…The findings from the current study suggest that increasing self-efficacy may help smokers move toward being ready to quit. Several studies have found that the increase in self-efficacy in smoking cessation treatment is linked with higher cessation rates (e.g., [24,48,49]), highlighting the important role of self-efficacy in the process of smoking cessation. However, the above studies did not assess whether the increase in self-efficacy is associated with an increase in readiness to quit.…”

Section: Journal Of Smoking Cessationmentioning

confidence: 99%

Relationships among Self-Efficacy, Quality of Life, Perceived Vulnerability, and Readiness to Quit Smoking in People Living with HIV

et al. 2021

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Smoking-related diseases (e.g., lung cancer) are the leading cause of mortality in HIV-infected patients. While many PLWH who smoke report a desire to quit, a majority of them have low readiness to quit. This study used logistic and linear regression to examine the relations among two (continuous vs. binary) measures of readiness to quit, smoking cessation self-efficacy (SE), quality of life (QoL), and perceived vulnerability (PV) using baseline data from 100 PLWH who smoke who participated in a clinical trial. Results showed no significant main effects (SE, QoL, and PV) or interaction effects ( SE × QoL and SE × PV ) on a continuous measure of readiness to quit. However, a follow-up analysis revealed that SE had a curvilinear effect on readiness to quit such that self-efficacy was positively associated with readiness to quit except at the highest levels of self-efficacy where readiness to quit declined. Greater SE significantly increased the likelihood of reporting readiness to quit (yes/no) among those with low QoL or high PV. For PLWH who smoke, improving self-efficacy may increase readiness to quit especially among those with lower quality of life. Psychoeducation tailored to PLWH designed to reduce unrealistic invulnerability to smoking-related diseases along with interventions that target self-efficacy may improve readiness to quit.

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Understanding how a smoking cessation intervention changes beliefs, self-efficacy, and intention to quit: a secondary analysis of a pragmatic randomized controlled trial

Cited by 9 publications

References 47 publications

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

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

Depression is a predictor for both smoking and quitting intentions among male coronary artery disease patients

Relationships among Self-Efficacy, Quality of Life, Perceived Vulnerability, and Readiness to Quit Smoking in People Living with HIV

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