Literature DB >> 27780895

Utilizing Lung Cancer Risk Prediction Models to Promote Smoking Cessation: Two Randomized Controlled Trials.

Frances C Sherratt1, Michael W Marcus2, Jude Robinson3, John K Field2.   

Abstract

PURPOSE: The current project sought to examine whether delivery of lung cancer risk projections (calculated using the Liverpool Lung Project [LLP] risk model) predicted follow-up smoking status.
DESIGN: Two single-blinded randomized controlled trials.
SETTING: Stop Smoking Services in Liverpool (United Kingdom). PARTICIPANTS: Baseline current smokers (N = 297) and baseline recent former smokers (N = 216) were recruited. INTERVENTION: Participants allocated to intervention groups were provided with personalized lung cancer risk projections, calculated using the LLP risk model. MEASURES: Baseline and follow-up questionnaires explored sociodemographics, smoking behavior, and lung cancer risk perceptions. ANALYSIS: Bivariate analyses identified significant differences between randomization groups, and logistic regression models were developed to investigate the intervention effect on the outcome variables.
RESULTS: Lung cancer risk projections were not found to predict follow-up smoking status in the trial of baseline current smokers; however, they did predict follow-up smoking status in the trial of baseline recent former smokers (odds ratio: 1.91; 95% confidence interval: 1.03-3.55).
CONCLUSION: The current study suggests that lung cancer risk projections may help maintain abstinence among individuals who have quit smoking, but the results did not provide evidence to suggest that lung cancer risk projections motivate current smokers to quit.

Entities:  

Keywords:  cancer of lung; cigarette smoking; lung cancer; risk perception; smoking; smoking cessation

Mesh:

Year:  2016        PMID: 27780895     DOI: 10.1177/0890117116673820

Source DB:  PubMed          Journal:  Am J Health Promot        ISSN: 0890-1171


  3 in total

Review 1.  Effect of interventions incorporating personalised cancer risk information on intentions and behaviour: a systematic review and meta-analysis of randomised controlled trials.

Authors:  Juliet A Usher-Smith; Barbora Silarova; Stephen J Sharp; Katie Mills; Simon J Griffin
Journal:  BMJ Open       Date:  2018-01-23       Impact factor: 2.692

2.  A randomised controlled trial of the effect of providing online risk information and lifestyle advice for the most common preventable cancers: study protocol.

Authors:  Juliet A Usher-Smith; Golnessa Masson; Katie Mills; Stephen J Sharp; Stephen Sutton; William M P Klein; Simon J Griffin
Journal:  BMC Public Health       Date:  2018-06-26       Impact factor: 3.295

3.  Effect of interventions including provision of personalised cancer risk information on accuracy of risk perception and psychological responses: A systematic review and meta-analysis.

Authors:  Max Bayne; Madi Fairey; Barbora Silarova; Simon J Griffin; Stephen J Sharp; William M P Klein; Stephen Sutton; Juliet A Usher-Smith
Journal:  Patient Educ Couns       Date:  2019-08-11
  3 in total

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