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Factors influencing the impact of pharmacogenomic prescribing on adherence to nicotine replacement therapy: A qualitative study of participants from a randomized controlled trial.

Overview of attention for article published in Translational Behavioral Medicine, January 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

blogs
1 blog
twitter
9 tweeters

Citations

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2 Dimensions

Readers on

mendeley
16 Mendeley
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Title
Factors influencing the impact of pharmacogenomic prescribing on adherence to nicotine replacement therapy: A qualitative study of participants from a randomized controlled trial.
Published in
Translational Behavioral Medicine, January 2018
DOI 10.1093/tbm/ibx008
Pubmed ID
Authors

Wright, Alison J, Sutton, Stephen, Armstrong, David, Aveyard, Paul, Kinmonth, Ann Louise, Marteau, Theresa M, Wright, AJ, Sutton, S, Armstrong, D, Aveyard, P, Kinmonth, AL, Marteau, TM

Abstract

Pharmacogenomics may improve health outcomes in two ways: by more precise and therefore more effective prescribing, tailored to genotype, and by increasing perceived effectiveness of treatments and so motivation for adherence. Little is known about patients' experiences of, and reactions to, receiving pharmacogenomically tailored treatments. The aim of this study was to explore the impact of pharmacogenomic prescribing of nicotine replacement therapy (NRT) on smokers' initial expectations of quit success, adherence, and perceived important differences from previous quit attempts. Semi-structured interviews were conducted with 40 smokers, purposively sampled from the Personalized Extra Treatment (PET) trial (ISRCTN 14352545). Together with NRT patches, participants were prescribed doses of oral NRT based on either mu-opioid receptor (OPRM1) genotype or nicotine dependence questionnaire score (phenotype). Data were analyzed using framework analysis, comparing views of participants in the two trial arms. Although most participants understood the basis for their prescribed NRT dose, it little influenced their views. The salient features of this quit attempt were the individualized behavioral support and combined NRT, not pharmacogenomic tailoring. Participants' initial expectations of success were mostly based on prior experiences of quitting. They attributed taking medication to nurse advice to do so, and attributed reducing or stopping it to side effects, forgetfulness, or practical difficulties. Intentional nonadherence appeared very rare. Pharmacogenomic NRT prescribing was not especially remarkable to participants and did not seem to influence adherence. Where services already tailor prescriptions to phenotype and provide individualized behavioral support for treatment adherence, pharmacogenomic prescribing may have limited additional benefit.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Other 3 19%
Student > Ph. D. Student 3 19%
Unspecified 2 13%
Student > Bachelor 2 13%
Student > Doctoral Student 2 13%
Other 4 25%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 4 25%
Unspecified 3 19%
Social Sciences 3 19%
Psychology 3 19%
Medicine and Dentistry 2 13%
Other 1 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 September 2018.
All research outputs
#1,145,893
of 13,500,498 outputs
Outputs from Translational Behavioral Medicine
#83
of 604 outputs
Outputs of similar age
#45,666
of 348,485 outputs
Outputs of similar age from Translational Behavioral Medicine
#6
of 28 outputs
Altmetric has tracked 13,500,498 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 604 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 348,485 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.