Internet-Based Photoaging Within Australian Pharmacies to Promote Smoking Cessation: Randomized Controlled Trial
ABSTRACT Tobacco smoking leads to death or disability and a drain on national resources. The literature suggests that cigarette smoking continues to be a major modifiable risk factor for a variety of diseases and that smokers aged 18-30 years are relatively resistant to antismoking messages due to their widely held belief that they will not be lifelong smokers.
To conduct a randomized controlled trial (RCT) of a computer-generated photoaging intervention to promote smoking cessation among young adult smokers within a community pharmacy setting.
A trial was designed with 80% power based on the effect size observed in a published pilot study; 160 subjects were recruited (80 allocated to the control group and 80 to the intervention group) from 8 metropolitan community pharmacies located around Perth city center in Western Australia. All participants received standardized smoking cessation advice. The intervention group participants were also digitally photoaged by using the Internet-based APRIL Face Aging software so they could preview images of themselves as a lifelong smoker and as a nonsmoker. Due to the nature of the intervention, the participants and researcher could not be blinded to the study. The main outcome measure was quit attempts at 6-month follow-up, both self-reported and biochemically validated through testing for carbon monoxide (CO), and nicotine dependence assessed via the Fagerström scale.
At 6-month follow-up, 5 of 80 control group participants (6.3%) suggested they had quit smoking, but only 1 of 80 control group participants (1.3%) consented to, and was confirmed by, CO validation. In the intervention group, 22 of 80 participants (27.5%) reported quitting, with 11 of 80 participants (13.8%) confirmed by CO testing. This difference in biochemically confirmed quit attempts was statistically significant (χ(2) 1=9.0, P=.003). A repeated measures analysis suggested the average intervention group smoking dependence score had also significantly dropped compared to control participants (P<.001). These differences remained statistically significant after adjustment for small differences in gender distribution and nicotine dependence between the groups. The mean cost of implementing the intervention was estimated at AU $5.79 per participant. The incremental cost-effectiveness ratio was AU $46 per additional quitter. The mean cost that participants indicated they were willing to pay for the digital aging service was AU $20.25 (SD 15.32).
Demonstrating the detrimental effects on facial physical appearance by using a computer-generated simulation may be both effective and cost-effective at persuading young adult smokers to quit.
Australian New Zealand Clinical Trials Registry: ACTRN12609000885291; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12609000885291 (Archived by WebCite at http://www.webcitation.org/6F2kMt3kC).
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ABSTRACT: Smoking cessation is a potentially appropriate role for community pharmacists because they are encouraged to advise on the correct use of nicotine replacement therapy (NRT) products and to provide behavioural support to aid smoking cessation. This review assessed the effectiveness of interventions by community pharmacy personnel to assist clients to stop smoking. A search was made of the Cochrane Tobacco Addiction Group database for smoking cessation studies conducted in the community pharmacy setting, using the search terms pharmacist* or pharmacy or pharmacies. Date of the most recent search: March 2003. Randomized trials which compared interventions by community pharmacy personnel to promote smoking cessation amongst their clients who were smokers compared to usual pharmacy support or any less intensive programme. The main outcome measure was smoking cessation rates at six months or more after the start of the intervention. Data were extracted by one author and checked by the second, noting: the country of the trial, details of participant community pharmacies, method of subject recruitment, smoking behaviour and characteristics of participants on recruitment, method of randomization, description of the intervention and of any pharmacy personnel training, and the outcome measures. Methodological quality was assessed according to the extent to which the allocation to intervention or control was concealed. Because of the potentially important cluster effects, we also rated trials according to whether they checked for or adjusted for these but, in the absence of consensus on how to pool cluster level data, we adopted a narrative approach to synthesizing the data, rather than a formal meta-analysis. We identified two trials which met our selection criteria. They included a total of 976 smokers. Both trials were set in the UK and involved a training intervention which included the Stages of Change Model; they then compared a support programme involving counselling and record keeping against a control receiving usual pharmacy support. In both studies a high proportion of intervention and control participants began using NRT. Both studies reported smoking cessation outcomes at three time points. However, the follow-up points were not identical (three, six and 12 months in one, and one, four and nine months in the other), and the trend in abstinence over time was not linear in either study, so the data could not be combined. One study showed a significant difference in self-reported cessation rates at 12 months: 14.3% versus 2.7% (p < 0.001); the other study showed a positive trend at each follow-up with 12.0% versus 7.4% (p = 0.09) at nine months. The limited number of studies to date suggests that trained community pharmacists, providing a counselling and record keeping support programme for their customers, may have a positive effect on smoking cessation rates. The strength of evidence is limited because only one of the trials showed a statistically significant effect.Cochrane database of systematic reviews (Online) 02/2004; DOI:10.1002/14651858.CD003698.pub2 · 5.94 Impact Factor
Tobacco control 03/2012; 21(2):252-7. DOI:10.1136/tobaccocontrol-2011-050348 · 5.15 Impact Factor
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ABSTRACT: To estimate health expectancy--that is, the average lifetime in good health--among never smokers, ex-smokers, and smokers in Denmark. A method suggested by Peto and colleagues in 1992 for estimating smoking attributable mortality rates was used to construct a life table for never smokers. This life table and relative risks for death for ex-smokers and smokers versus never smokers were used to estimate life tables for ex-smokers and smokers. Life tables and prevalence rates of health status were combined and health expectancy was calculated by Sullivan's method. The Danish adult population. The expected lifetime in self rated good health or without longstanding illness for never smokers and smokers. The expected lifetime of a 20 year old man who will never begin to smoke is 56.7 years, 48.7 (95% confidence interval (CI), 46.8 to 50.7) years of which are expected to be in self rated good health. The corresponding figures for a man who smokes heavily are 49.5 years, 36.5 (95% CI 35.0 to 38.1 ) years of which are in self rated good health. A 20 year old woman who will never begin to smoke can expect to live a further 60.9 years, with 46.4 (95% CI 44.9 to 47.8) years in self rated good health; if she is a lifelong heavy smoker, her expected lifetime is reduced to 53.8 years, 33.8 (95% CI 31.7 to 35.9) years of which are in self rated good health. Health expectancy based on long standing illness is reduced for smokers when compared with never smokers. Smoking reduces the expected lifetime in good health and increases the expected lifetime in poor health.Tobacco Control 10/2001; 10(3):273-8. DOI:10.1136/tc.10.3.273 · 5.15 Impact Factor