Transtheoretical model-based passive smoking prevention programme among pregnant women and mothers of young children

Huang, Chun‐Kai; Wu, Hsein Lin; Huang, Shu He; Chien, Li Yin; Guo, Jong Long

doi:10.1093/eurpub/cks177

Cited by 42 publications

(66 citation statements)

References 18 publications

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“…[20][21][22][23][24][25]28,29,[31][32][33]84,85,88,90,91,93,96 One study did not report the number of sessions. 34 …”

Section: Intervention Intensitymentioning

confidence: 99%

“…[20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][83][84][85][86][87][88][89][90][91][92][93][94][95][96][97] The trials were published between 1994 and 2013. A flowchart describing the identification process is presented in Fig 1. Study characteristics of included trials are presented in Tables 1 and 2. …”

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confidence: 99%

“…21,28,29,32,[85][86][87]90,[92][93][94]96 Fidelity Seven studies reported high fidelity, with at least 80% of participants receiving the full intervention 23,24,27,84,88,93,96 ; 6 studies had moderate fidelity, with 50% to 79% of participants receiving the intervention 25,[29][30][31][32][33] ; and the remaining 17 studies did not report fidelity. [20][21][22]26,28,34,83,[85][86][87][89][90][91][92]94,95,97 Intervention Effects …”

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confidence: 99%

“…83 1. PREP at follow-up.Seventeen studies (n = 6820), 20,23,[28][29][30][31][32][83][84][85][86]88,[90][91][92][93][94] were included in the analysis of PREP at follow-up (Fig 2A). Benefit was apparent in 88.2% (15/17) of studies, with 29.4% (5/ 17) showing a statistically significant advantage to the intervention group.…”

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confidence: 99%

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Meta-analysis of Parental Protection of Children From Tobacco Smoke Exposure

Rosen¹,

Myers²,

Hovell

et al. 2014

Pediatrics

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BACKGROUND AND OBJECTIVE: Worldwide, roughly 40% of children are exposed to the damaging and sometimes deadly effects of tobacco smoke. Interventions aimed at reducing child tobacco smoke exposure (TSE) have shown mixed results. The objective of this study was to perform a systematic review and meta-analysis to quantify effects of interventions aimed at decreasing child TSE.METHODS: Data sources included Medline, PubMed, Web of Science, PsycNet, and Embase. Controlled trials that included parents of young children were selected. Two reviewers extracted TSE data, as assessed by parentally-reported exposure or protection (PREP) and biomarkers. Risk ratios and differences were calculated by using the DerSimonian and Laird random-effects model. Exploratory subgroup analyses were performed.RESULTS: Thirty studies were included. Improvements were observed from baseline to follow-up for parentally-reported and biomarker data in most intervention and control groups. Interventions demonstrated evidence of small benefit to intervention participants at follow-up (PREP: 17 studies, n = 6820, relative risk 1.12, confidence interval [CI] 1.07 to 1.18], P , .0001). Seven percent more children were protected in intervention groups relative to control groups. Intervention parents smoked fewer cigarettes around children at follow-up than did control parents (P = .03). Biomarkers (13 studies, n = 2601) at follow-up suggested lower child exposure among intervention participants (RD 20.05, CI 20.13 to 0.03, P = .20).CONCLUSIONS: Interventions to prevent child TSE are moderately beneficial at the individual level. Widespread child TSE suggests potential for significant population impact. More research is needed to improve intervention effectiveness and child TSE measurement. KEY WORDS secondhand smoke exposure, tobacco smoke exposure, metaanalysis, systematic review, child ABBREVIATIONS CCR-cotinine/creatinine ratio CI-confidence interval CT-controlled trial PREP-parentally reported exposure or protection RCT-randomized controlled trial RD-relative difference RR-relative risk SHS-secondhand smoke THS-thirdhand smoke TSE-tobacco smoke exposure Dr Rosen conceptualized and designed the study, oversaw all aspects of the research, performed the systematic review of the literature, extracted data from the original studies, contributed to the statistical analysis, wrote sections of the manuscript, and edited the entire manuscript; Ms Myers contributed to systematically reviewing the literature, extracted data from the original articles, contributed to the data analysis, and contributed to the writing of the manuscript; Dr Hovell contributed to the design of the meta-analysis and interpretation of the data and edited the manuscript for scientific content; Dr Zucker assisted with various statistical issues in the analysis of the manuscript and edited the manuscript; Ms Ben Noach contributed to the design of the study, the systematic review of the literature, data extraction, data analysis, data interpretation, and writing of the m...

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“…[20][21][22][23][24][25]28,29,[31][32][33]84,85,88,90,91,93,96 One study did not report the number of sessions. 34 …”

Section: Intervention Intensitymentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Meta-analysis of Parental Protection of Children From Tobacco Smoke Exposure

Rosen¹,

Myers²,

Hovell

et al. 2014

Pediatrics

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“…Although it has existed over 20 years ago, it is still famously applied in many smoking cessation behavioural research (Paiva et al, 2012;Campbell et al, 2013;Huang et al, 2013). This model includes five stages of change through which a smoker progresses during the quitting process: pre-contemplation, contemplation, preparation, action and maintenance.…”

Section: Introductionmentioning

confidence: 99%

Testing the Transtheoretical Model in Predicting Smoking Relapse among Malaysian Adult Smokers Receiving Assistance in Quitting

Yasin

Masilamani

Moy

et al. 2013

Asian Pacific Journal of Cancer Prevention

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The role of The Transtheoretical Model (TTM) in predicting relapse is limited. We aimed to assess whether this model can be utilised to predict relapse during the action stage. The participants included 120 smokers who had abstained from smoking for at least 24 hours following two Malaysian universities' smoking cessation programme. The smokers who relapsed perceived significantly greater advantages related to smoking and increasing doubt in their ability to quit. In contrast, former smokers with greater self-liberation and determination to abstain were less likely to relapse. The findings suggest that TTM can be used to predict relapse among quitting smokers.

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