ArticlePersonalized medicine2013
Bumps along the translational pathway: anticipating uptake of tailored smoking cessation treatment.
Article in Personalized medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Attitudes toward Precision Treatment of Smoking in the Southern Community Cohort Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019Article
- Clinical pharmacogenomics: patient perspectives of pharmacogenomic testing and the incidence of actionable test results in a chronic disease cohort.Personalized medicine · 2017Article
- Smokers' beliefs about the tobacco control potential of "a gene for smoking": a focus group study.BMC public health · 2014Article
- Commentary on Culverhouse et al. (2014): How genomics can bring us towards health equity.Addiction (Abingdon, England) · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
aimTo assess potential barriers to clinical integration of tailored smoking cessation treatment among African American and white smokers in the USA.
methodsA total of 392 smokers (203 white and 189 African American) identified within a national random digit dial survey (response rate: 40.1%; 81.2% among households with whom we were able to make contact) of 1200 African Americans and 1200 white Americans. Respondents answered several closed-ended survey items addressing beliefs regarding what influences a smoker's ability to quit, past pharmacotherapy use, and their willingness to undergo genetic assessment in order to be matched to optimal treatment, among other items.
resultsIn this first nationally representative survey of US smokers, 77% of respondents expressed willingness to undergo genetic testing in order to be matched to optimal pharmacotherapy, yet only 18% had ever used pharmacotherapy in a previous quit attempt. Smokers who rated 'medications and counseling' as very important in quitting were significantly more likely to endorse genetic testing (odds ratio [OR]: 8.94; 95% CI: 1.86-43.06), while those rating 'having God's help' as very important were significantly less likely to express willingness to undergo testing (OR: 0.11; 95% CI: 0.02-0.71). African American smokers were more likely than white smokers to express willingness to undergo genetic testing (OR: 3.80; 95% CI: 1.09-13.22), despite lower rates of previous pharmacotherapy use.
conclusionWhile smokers reported high rates of willingness to undergo genetic testing to be matched to optimal treatment, these results suggest that smokers' willingness to use medications indicated by genetic test results may prove a significant barrier to realizing the promise of tailored smoking cessation treatment. The role of spirituality in smokers' willingness to use medication is an area for further study.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.