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Predicting the onset of hazardous alcohol drinking in primary care: development and validation of a simple risk algorithm

Overview of attention for article published in British Journal of General Practice, March 2017
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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
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72 Mendeley
Title
Predicting the onset of hazardous alcohol drinking in primary care: development and validation of a simple risk algorithm
Published in
British Journal of General Practice, March 2017
DOI 10.3399/bjgp17x690245
Pubmed ID
Authors

Juan Ángel Bellón, Juan de Dios Luna, Michael King, Irwin Nazareth, Emma Motrico, María Josefa GildeGómez-Barragán, Francisco Torres-González, Carmen Montón-Franco, Marta Sánchez-Celaya, Miguel Ángel Díaz-Barreiros, Catalina Vicens, Patricia Moreno-Peral

Abstract

Little is known about the risk of progressing to hazardous alcohol use in abstinent or low-risk drinkers. To develop and validate a simple brief risk algorithm for the onset of hazardous alcohol drinking (HAD) over 12 months for use in primary care. Prospective cohort study in 32 health centres from six Spanish provinces, with evaluations at baseline, 6 months, and 12 months. Forty-one risk factors were measured and multilevel logistic regression and inverse probability weighting were used to build the risk algorithm. The outcome was new occurrence of HAD during the study, as measured by the AUDIT. From the lists of 174 GPs, 3954 adult abstinent or low-risk drinkers were recruited. The 'predictAL-10' risk algorithm included just nine variables (10 questions): province, sex, age, cigarette consumption, perception of financial strain, having ever received treatment for an alcohol problem, childhood sexual abuse, AUDIT-C, and interaction AUDIT-C*Age. The c-index was 0.886 (95% CI = 0.854 to 0.918). The optimal cutoff had a sensitivity of 0.83 and specificity of 0.80. Excluding childhood sexual abuse from the model (the 'predictAL-9'), the c-index was 0.880 (95% CI = 0.847 to 0.913), sensitivity 0.79, and specificity 0.81. There was no statistically significant difference between the c-indexes of predictAL-10 and predictAL-9. The predictAL-10/9 is a simple and internally valid risk algorithm to predict the onset of hazardous alcohol drinking over 12 months in primary care attendees; it is a brief tool that is potentially useful for primary prevention of hazardous alcohol drinking.

X Demographics

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The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 72 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 14%
Student > Bachelor 10 14%
Student > Ph. D. Student 7 10%
Student > Master 7 10%
Student > Doctoral Student 5 7%
Other 11 15%
Unknown 22 31%
Readers by discipline Count As %
Medicine and Dentistry 13 18%
Psychology 8 11%
Nursing and Health Professions 5 7%
Social Sciences 5 7%
Computer Science 2 3%
Other 12 17%
Unknown 27 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 April 2018.
All research outputs
#7,188,412
of 22,963,381 outputs
Outputs from British Journal of General Practice
#2,329
of 4,295 outputs
Outputs of similar age
#114,892
of 308,948 outputs
Outputs of similar age from British Journal of General Practice
#59
of 98 outputs
Altmetric has tracked 22,963,381 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 4,295 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.5. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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 308,948 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.