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Interpreting Null Findings from Trials of Alcohol Brief Interventions

Overview of attention for article published in Frontiers in Psychiatry, July 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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1 policy source
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Title
Interpreting Null Findings from Trials of Alcohol Brief Interventions
Published in
Frontiers in Psychiatry, July 2014
DOI 10.3389/fpsyt.2014.00085
Pubmed ID
Authors

Nick Heather

Abstract

The effectiveness of alcohol brief intervention (ABI) has been established by a succession of meta-analyses but, because the effects of ABI are small, null findings from randomized controlled trials are often reported and can sometimes lead to skepticism regarding the benefits of ABI in routine practice. This article first explains why null findings are likely to occur under null hypothesis significance testing (NHST) due to the phenomenon known as "the dance of the p-values." A number of misconceptions about null findings are then described, using as an example the way in which the results of the primary care arm of a recent cluster-randomized trial of ABI in England (the SIPS project) have been misunderstood. These misinterpretations include the fallacy of "proving the null hypothesis" that lack of a significant difference between the means of sample groups can be taken as evidence of no difference between their population means, and the possible effects of this and related misunderstandings of the SIPS findings are examined. The mistaken inference that reductions in alcohol consumption seen in control groups from baseline to follow-up are evidence of real effects of control group procedures is then discussed and other possible reasons for such reductions, including regression to the mean, research participation effects, historical trends, and assessment reactivity, are described. From the standpoint of scientific progress, the chief problem about null findings under the conventional NHST approach is that it is not possible to distinguish "evidence of absence" from "absence of evidence." By contrast, under a Bayesian approach, such a distinction is possible and it is explained how this approach could classify ABIs in particular settings or among particular populations as either truly ineffective or as of unknown effectiveness, thus accelerating progress in the field of ABI research.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 21%
Student > Master 6 13%
Student > Ph. D. Student 4 8%
Student > Doctoral Student 4 8%
Librarian 3 6%
Other 9 19%
Unknown 12 25%
Readers by discipline Count As %
Psychology 16 33%
Medicine and Dentistry 9 19%
Social Sciences 5 10%
Nursing and Health Professions 3 6%
Agricultural and Biological Sciences 1 2%
Other 3 6%
Unknown 11 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 08 January 2020.
All research outputs
#5,857,921
of 24,036,420 outputs
Outputs from Frontiers in Psychiatry
#2,622
of 11,270 outputs
Outputs of similar age
#52,034
of 231,084 outputs
Outputs of similar age from Frontiers in Psychiatry
#18
of 54 outputs
Altmetric has tracked 24,036,420 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,270 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has done well, scoring higher than 76% 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 231,084 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 77% of its contemporaries.
We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.