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Understanding gambling related harm: a proposed definition, conceptual framework, and taxonomy of harms

Overview of attention for article published in BMC Public Health, January 2016
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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 (87th percentile)

Mentioned by

policy
1 policy source
twitter
12 tweeters

Citations

dimensions_citation
165 Dimensions

Readers on

mendeley
127 Mendeley
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Title
Understanding gambling related harm: a proposed definition, conceptual framework, and taxonomy of harms
Published in
BMC Public Health, January 2016
DOI 10.1186/s12889-016-2747-0
Pubmed ID
Authors

Erika Langham, Hannah Thorne, Matthew Browne, Phillip Donaldson, Judy Rose, Matthew Rockloff

Abstract

Harm from gambling is known to impact individuals, families, and communities; and these harms are not restricted to people with a gambling disorder. Currently, there is no robust and inclusive internationally agreed upon definition of gambling harm. In addition, the current landscape of gambling policy and research uses inadequate proxy measures of harm, such as problem gambling symptomology, that contribute to a limited understanding of gambling harms. These issues impede efforts to address gambling from a public health perspective. Data regarding harms from gambling was gathered using four separate methodologies, a literature review, focus groups and interviews with professionals involved in the support and treatment of gambling problems, interviews with people who gamble and their affected others, and an analysis of public forum posts for people experiencing problems with gambling and their affected others. The experience of harm related to gambling was examined to generate a conceptual framework. The catalogue of harms experienced were organised as a taxonomy. The current paper proposes a definition and conceptual framework of gambling related harm that captures the full breadth of harms that gambling can contribute to; as well as a taxonomy of harms to facilitate the development of more appropriate measures of harm. Our aim is to create a dialogue that will lead to a more coherent interpretation of gambling harm across treatment providers, policy makers and researchers.

Twitter Demographics

The data shown below were collected from the profiles of 12 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 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Unknown 126 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 23 18%
Student > Master 21 17%
Researcher 15 12%
Student > Ph. D. Student 11 9%
Other 9 7%
Other 24 19%
Unknown 24 19%
Readers by discipline Count As %
Psychology 27 21%
Social Sciences 26 20%
Medicine and Dentistry 20 16%
Nursing and Health Professions 14 11%
Business, Management and Accounting 4 3%
Other 12 9%
Unknown 24 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 August 2019.
All research outputs
#1,816,020
of 16,298,542 outputs
Outputs from BMC Public Health
#2,150
of 11,194 outputs
Outputs of similar age
#42,932
of 345,670 outputs
Outputs of similar age from BMC Public Health
#1
of 1 outputs
Altmetric has tracked 16,298,542 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,194 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one has done well, scoring higher than 80% 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 345,670 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 87% of its contemporaries.
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