Biomedical risk assessment as an aid for smoking cessation.

BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH STRATEGY: We systematically searched the Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials 2008 Issue 4, MEDLINE (1966 to January 2009), and EMBASE (1980 to January 2009). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. Results were expressed as a relative risk (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate a pooled effect was estimated using a Mantel-Haenszel fixed effect method. MAIN RESULTS: We included eleven trials using a variety of biomedical tests. Two pairs of trials had sufficiently similar recruitment, setting and interventions to calculate a pooled effect; there was no evidence that CO measurement in primary care (RR 1.06, 95% CI 0.85 to 1.32) or spirometry in primary care (RR 1.18, 95% CI 0.77 to 1.81) increased cessation rates. We did not pool the other seven trials. One trial in primary care detected a significant benefit of lung age feedback after spirometry (RR 2.12; 95% CI 1.24 to 3.62). One trial that used ultrasonography of carotid and femoral arteries and photographs of plaques detected a benefit (RR 2.77; 95% CI 1.04 to 7.41) but enrolled a population of light smokers. Five trials failed to detect evidence of a significant effect. One of these tested CO feedback alone and CO + genetic susceptibility as two different intervention; none of the three possible comparisons detected significant effects. Three others used a combination of CO and spirometry feedback in different settings, and one tested for a genetic marker. AUTHORS' CONCLUSIONS: There is little evidence about the effects of most types of biomedical tests for risk assessment. Spirometry combined with an interpretation of the results in terms of 'lung age' had a significant effect in a single good quality trial. Mixed quality evidence does not support the hypothesis that other types of biomedical risk assessment increase smoking cessation in comparison to standard treatment. Only two pairs of studies were similar enough in term of recruitment, setting, and intervention to allow meta-analysis.

Biomedical risk assessment as an aid for smoking cessation.

BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. We reviewed systematically data on smoking cessation rates from controlled trials that used biomedical risk assessment and feedback. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH STRATEGY: We systematically searched he Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (1966 to 2004), and EMBASE (1980 to 2004). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. MAIN RESULTS: From 4049 retrieved references, we selected 170 for full text assessment. We retained eight trials for data extraction and analysis. One of the eight used CO alone and CO + Genetic Susceptibility as two different intervention groups, giving rise to three possible comparisons. Three of the trials isolated the effect of exhaled CO on smoking cessation rates resulting in the following odds ratios (ORs) and 95% confidence intervals (95% CI): 0.73 (0.38 to 1.39), 0.93 (0.62 to 1.41), and 1.18 (0.84 to 1.64). Combining CO measurement with genetic susceptibility gave an OR of 0.58 (0.29 to 1.19). Exhaled CO measurement and spirometry were used together in three trials, resulting in the following ORs (95% CI): 0.6 (0.25 to 1.46), 2.45 (0.73 to 8.25), and 3.50 (0.88 to 13.92). Spirometry results alone were used in one other trial with an OR of 1.21 (0.60 to 2.42).Two trials used other motivational feedback measures, with an OR of 0.80 (0.39 to 1.65) for genetic susceptibility to lung cancer alone, and 3.15 (1.06 to 9.31) for ultrasonography of carotid and femoral arteries performed in light smokers (average 10 to 12 cigarettes a day). AUTHORS' CONCLUSIONS: Due to the scarcity of evidence of sufficient quality, we can make no definitive statements about the effectiveness of biomedical risk assessment as an aid for smoking cessation. Current evidence of lower quality does not however support the hypothesis that biomedical risk assessment increases smoking cessation in comparison with standard treatment. Only two studies were similar enough in term of recruitment, setting, and intervention to allow pooling of data and meta-analysis.

Transparency and trust in government (2007-2014): a comparative study

In a 2000 report entitled "Trust in government. Ethics measures in OECD countries," OECD Secretary-General Donald J. Johnston emphasized the fact that public ethics are considered as a keystone of good governance. Moreover, public ethics are a prerequisite to public trust, which is in turn vital not only to any public service, but also to any society in general. At the same time, transparency reforms have flourished over the last few years and have several times been designed as a response to public distrust. Therefore, ethics, transparency and trust are closely linked together in a supposed virtuous circle where transparency works as a factor of better public ethics and leads to more trust in government on the citizens' side. This article explores the links between transparency and levels of trust in 10 countries between 2007 and 2014, using open data indexes and access to information requests as proxies for transparency. A national ranking of transparency, based on requests submitted by citizens to the administration and open data indexes, is then proposed. Key findings show that there is no sharp decline of trust in government in all countries considered in this article, and that transparency and trust in government are not systematically positively associated. Therefore, this article challenges the common assumption, mostly found in the normative literature, about a positive interrelation between the two, where trust in government is conceived as a beneficial effect of administrative transparency.