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Developing a tablet computer-based application (‘App’) to measure self-reported alcohol consumption in Indigenous Australians

Overview of attention for article published in BMC Medical Informatics and Decision Making, January 2018
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Title
Developing a tablet computer-based application (‘App’) to measure self-reported alcohol consumption in Indigenous Australians
Published in
BMC Medical Informatics and Decision Making, January 2018
DOI 10.1186/s12911-018-0583-0
Pubmed ID
Authors

KS Kylie Lee, Scott Wilson, Jimmy Perry, Robin Room, Sarah Callinan, Robert Assan, Noel Hayman, Tanya Chikritzhs, Dennis Gray, Edward Wilkes, Peter Jack, Katherine M. Conigrave

Abstract

The challenges of assessing alcohol consumption can be greater in Indigenous communities where there may be culturally distinct approaches to communication, sharing of drinking containers and episodic patterns of drinking. This paper discusses the processes used to develop a tablet computer-based application ('App') to collect a detailed assessment of drinking patterns in Indigenous Australians. The key features of the resulting App are described. An iterative consultation process was used (instead of one-off focus groups), with Indigenous cultural experts and clinical experts. Regular (weekly or more) advice was sought over a 12-month period from Indigenous community leaders and from a range of Indigenous and non-Indigenous health professionals and researchers. The underpinning principles, selected survey items, and key technical features of the App are described. Features include culturally appropriate questioning style and gender-specific voice and images; community-recognised events used as reference points to 'anchor' time periods; 'translation' to colloquial English and (for audio) to traditional language; interactive visual approaches to estimate quantity of drinking; images of specific brands of alcohol, rather than abstract description of alcohol type (e.g. 'spirits'); images of make-shift drinking containers; option to estimate consumption based on the individual's share of what the group drank. With any survey platform, helping participants to accurately reflect on and report their drinking presents a challenge. The availability of interactive, tablet-based technologies enables potential bridging of differences in culture and lifestyle and enhanced reporting.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 17%
Student > Ph. D. Student 5 14%
Student > Master 4 11%
Researcher 3 9%
Other 3 9%
Other 6 17%
Unknown 8 23%
Readers by discipline Count As %
Medicine and Dentistry 8 23%
Psychology 5 14%
Nursing and Health Professions 3 9%
Computer Science 3 9%
Arts and Humanities 2 6%
Other 6 17%
Unknown 8 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 07 March 2018.
All research outputs
#7,914,274
of 12,612,351 outputs
Outputs from BMC Medical Informatics and Decision Making
#789
of 1,137 outputs
Outputs of similar age
#194,543
of 344,237 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 12,612,351 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,137 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 20th percentile – i.e., 20% 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 344,237 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them