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Social influences normalize gambling-related harm among higher risk gamblers
BACKGROUND AND AIMS: Social influences are key drivers of gambling, and can begin in youth through parental modeling and facilitation. Over time, social influence from friends and colleagues also becomes important. Social network analysis provides a method to measure the combined nature of these soc...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Akadémiai Kiadó
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376388/ https://www.ncbi.nlm.nih.gov/pubmed/30596469 http://dx.doi.org/10.1556/2006.7.2018.139 |
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author | Russell, Alex M. T. Langham, Erika Hing, Nerilee |
author_facet | Russell, Alex M. T. Langham, Erika Hing, Nerilee |
author_sort | Russell, Alex M. T. |
collection | PubMed |
description | BACKGROUND AND AIMS: Social influences are key drivers of gambling, and can begin in youth through parental modeling and facilitation. Over time, social influence from friends and colleagues also becomes important. Social network analysis provides a method to measure the combined nature of these social influences. This study aimed to compare social influences across gambling risk groups, by examining key characteristics of the social networks, among Australian adults. METHODS: A total of 784 respondents (egos) reported their demographics, gambling behavior and gambling risk, as well as those of the 20 most influential people in their lives (alters). Egos also reported the strength of the connection between themselves and each of their alters, and between each pair of alters. Data were analyzed using egocentric social network analysis approaches. RESULTS: Egos in higher risk groups reported more alters who gamble, including a higher proportion experiencing gambling-related harm. Relationship strength indicated that egos in higher risk groups tended to feel closer to their alters, regardless of whether the alter gambles or not. Network density (interconnectedness between alters) was greater for egos in higher risk groups. DISCUSSION AND CONCLUSIONS: The findings indicate that both gambling behavior and gambling-related harm are normalized through social connections. Greater interconnectedness in the networks of higher risk gamblers indicates difficulties in reducing or removing these influences. The findings indicate limitations of individualised interventions, and instead highlight the important role of changing norms within society, which can be transmitted throughout these networks. |
format | Online Article Text |
id | pubmed-6376388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Akadémiai Kiadó |
record_format | MEDLINE/PubMed |
spelling | pubmed-63763882019-02-21 Social influences normalize gambling-related harm among higher risk gamblers Russell, Alex M. T. Langham, Erika Hing, Nerilee J Behav Addict Full-Length Report BACKGROUND AND AIMS: Social influences are key drivers of gambling, and can begin in youth through parental modeling and facilitation. Over time, social influence from friends and colleagues also becomes important. Social network analysis provides a method to measure the combined nature of these social influences. This study aimed to compare social influences across gambling risk groups, by examining key characteristics of the social networks, among Australian adults. METHODS: A total of 784 respondents (egos) reported their demographics, gambling behavior and gambling risk, as well as those of the 20 most influential people in their lives (alters). Egos also reported the strength of the connection between themselves and each of their alters, and between each pair of alters. Data were analyzed using egocentric social network analysis approaches. RESULTS: Egos in higher risk groups reported more alters who gamble, including a higher proportion experiencing gambling-related harm. Relationship strength indicated that egos in higher risk groups tended to feel closer to their alters, regardless of whether the alter gambles or not. Network density (interconnectedness between alters) was greater for egos in higher risk groups. DISCUSSION AND CONCLUSIONS: The findings indicate that both gambling behavior and gambling-related harm are normalized through social connections. Greater interconnectedness in the networks of higher risk gamblers indicates difficulties in reducing or removing these influences. The findings indicate limitations of individualised interventions, and instead highlight the important role of changing norms within society, which can be transmitted throughout these networks. Akadémiai Kiadó 2018-12-29 2018-12 /pmc/articles/PMC6376388/ /pubmed/30596469 http://dx.doi.org/10.1556/2006.7.2018.139 Text en © 2018 The Author(s) http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated. |
spellingShingle | Full-Length Report Russell, Alex M. T. Langham, Erika Hing, Nerilee Social influences normalize gambling-related harm among higher risk gamblers |
title | Social influences normalize gambling-related harm among higher risk gamblers |
title_full | Social influences normalize gambling-related harm among higher risk gamblers |
title_fullStr | Social influences normalize gambling-related harm among higher risk gamblers |
title_full_unstemmed | Social influences normalize gambling-related harm among higher risk gamblers |
title_short | Social influences normalize gambling-related harm among higher risk gamblers |
title_sort | social influences normalize gambling-related harm among higher risk gamblers |
topic | Full-Length Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376388/ https://www.ncbi.nlm.nih.gov/pubmed/30596469 http://dx.doi.org/10.1556/2006.7.2018.139 |
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