Avoiding gambling harm: An evidence-based set of safe gambling practices for consumers
Autoři:
Nerilee Hing aff001; Matthew Browne aff001; Alex M. T. Russell aff002; Matthew Rockloff aff001; Vijay Rawat aff003; Fiona Nicoll aff004; Garry Smith aff004
Působiště autorů:
Experimental Gambling Research Laboratory, School of Health, Medical and Applied Sciences, CQUniversity, Bundaberg, Queensland, Australia
aff001; Experimental Gambling Research Laboratory, School of Health, Medical and Applied Sciences, CQUniversity, Sydney, New South Wales, Australia
aff002; Experimental Gambling Research Laboratory, School of Health, Medical and Applied Sciences, CQUniversity, Melbourne, Victoria, Australia
aff003; University of Alberta, Edmonton, Canada
aff004
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0224083
Souhrn
Prior studies have identified self-regulatory strategies that are infrequently used by problem-gamblers, but which might be protective if used. However, guidelines with evidence-based safe gambling practices (SGPs) that prevent gambling-related harm are lacking. This study aimed to: 1) identify a parsimonious set of evidence-based SGPs that best predict non-harmful gambling amongst gamblers who are otherwise most susceptible to experiencing gambling harm; 2) examine how widely are they used; and 3) assess whether their use differs by gambler characteristics. A sample of 1,174 regular gamblers in Alberta Canada completed an online survey measuring uptake of 43 potential SGPs, gambling harms and numerous risk factors for harmful gambling. Elastic net regression identified a sub-sample of 577 gamblers most susceptible to gambling harm and therefore most likely to benefit from the uptake of SGPs. A second elastic net predicted gambling harm scores in the sub-sample, using the SGPs as candidate predictors. Nine SGPs best predicted non-harmful gambling amongst this sub-sample. The behaviour most strongly associated with increased harm was using credit to gamble. The behaviour most strongly associated with reduced harm was ‘If I’m not having fun gambling, I stop’. These SGPs form the basis of evidence-based safe gambling guidelines which can be: 1) promoted to consumers, 2) form the basis of self-assessment tests, 3) used to measure safe gambling at a population level, and 4) inform supportive changes to policy and practice. The guidelines advise gamblers to: stop if they are not having fun, keep a household budget, keep a dedicated gambling budget, have a fixed amount they can spend, engage in other leisure activities, avoid gambling when upset or depressed, not use credit for gambling, avoid gambling to make money, and not think that strategies can help you win. These guidelines are a promising initiative to help reduce gambling-related harm.
Klíčová slova:
Behavior – Budgets – Gambling addiction – Child psychiatry – Impulsivity – Sports – Surveys – Gambling
Zdroje
1. Browne M, Langham E, Rawat V, Greer N, Li E, Rose J, et al. Assessing gambling-related harm in Victoria: a public health perspective. Melbourne: Victorian Responsible Gambling Foundation; 2016.
2. Browne M, Bellringer M, Greer N, Kolandai-Matchett K, Rawat V, Langham E, et al. Measuring the burden of gambling harm in New Zealand. Wellington: New Zealand Ministry of Health; 2017.
3. Williams RJ, Volberg RA, Stevens RM. The population prevalence of problem gambling: Methodological influences, standardized rates, jurisdictional differences, and worldwide trends. Guelph: Ontario Problem Gambling Research Centre; 2012.
4. Hancock L, Smith G. Critiquing the Reno model I-IV international influence on regulators and governments (2004–2015)—the distorted reality of “responsible gambling”. Int J Ment Health Addict. 2017; 15(6): 1151–1176.
5. Hancock L, Smith G. Replacing the Reno Model with a robust public health approach to “responsible gambling”: Hancock and Smith’s response to commentaries on our original reno model critique. Int J Ment Health Addict. 2017; 15(6): 1209–1220.
6. Livingstone C, Rintoul A, Francis L. What is the evidence for harm minimisation measures in gambling venues. Evidence Base. 2014. doi: 10.4225/50/558112A877C5D
7. Reith G. Gambling and the contradictions of consumption: A genealogy of the ‘pathological’ subject. American Behavioral Scientist. 2007. doi: 10.1177/0002764207304856
8. Reith G. Reflections on responsibility. Journal of Gambling Issues. 2008. doi: 10.4309/jgi.2008.22.12
9. Browne M, Greer N, Rawat V, Rockloff M. (2017). A population-level metric for gambling-related harm. International Gambling Studies. 2017. doi: 10.1080/14459795.2017.1304973
10. Browne M, Rawat V, Greer N, Langham E, Rockloff M, Hanley C. What is the harm? Applying a public health methodology to measure the impact of gambling problems and harm on quality of life. Journal of Gambling Issues. 2017. doi: 10.4309/jgi.2017.36.2
11. Korn DA. Examining gambling issues from a public health perspective. Journal of Gambling Issues. 2001. doi: 10.4309/jgi.2001.4.9
12. Korn DA, Shaffer HJ. Gambling and the health of the public: Adopting a public health perspective. J Gamb Stud. 1999. doi: 10.1023/A:1023005115932
13. Hing N, Russell AMT, Hronis A. Behavioural indicators of responsible gambling consumption. Melbourne: Victorian Responsible Gambling Foundation; 2016.
14. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th ed. Arlington, VA: American Psychiatric Publishing; 2013
15. Ferris J, Wynne H. The Canadian Problem Gambling Index: Final Report. Ottowa: Canadian Centre on Substance Abuse; 2001.
16. Wood RT, Griffiths MD. Understanding positive play: An exploration of playing experiences and responsible gambling practices. J Gambl Stud. 2015. doi: 10.1007/s10899-014-9489-7 25209455
17. Hing N, Russell AMT, Hronis A. What behaviours and cognitions support responsible consumption of gambling? Results from an expert survey. Int J Ment Health Addict. 2017. doi: 10.1007/s11469-017-9793-4
18. Hing N, Sproston K, Tran K, Russell AMT. Gambling responsibly: Who does it and to what end? J Gambl Stud. 2017. doi: 10.1007/s10899-016-9615-9 27150462
19. Wood RT, Wohl MJ, Tabri N, Philander K. Measuring responsible gambling amongst players: Development of the Positive Play Scale. Front Psychol. 2017. doi: 10.3389/fpsyg.2017.00227 28280472
20. Rodda SN, Bagot KL, Cheetham A, Hodgins DC, Hing N, Lubman DI. Types of change strategies for limiting or reducing gambling behaviours and their perceived helpfulness: A factor analysis. Psychol Addict Behav. 2018. doi: 10.1037/adb0000393 30211588
21. Rodda SN, Bagot KL, Manning V, Lubman DI. ‘Only take the money you want to lose’ strategies for sticking to limits in electronics venues. International Gambling Studies. 2019. doi: 10.1080/14459795.2019.1617330
22. Browne M, Goodwin B, Rockloff M. Validation of the Short Gambling Harm Screen (SGHS): A tool for assessment of harms from gambling. J Gambl Stud. 2018. doi: 10.1007/s10899-017-9698-y 28578519
23. Flack M, Morris M. The temporal stability and predictive ability of the Gambling Outcome Expectancies Scale (GOES): A prospective study. J Gambl Stud. 2016. doi: 10.1007/s10899-015-9581-7 26518686
24. Raylu N, Oei T. The gambling urge scale: Development, confirmatory factor validation, and psychometric properties. Psychol Addict Behav. 2004. doi: 10.1037/0893-164X.18.2.100 15238051
25. Wood R, Williams R. Internet gambling: Prevalence, patterns, problems, and policy options. Ontario: Ontario Problem Gambling Research Centre; 2009.
26. Kleim S, MÖßle T, Rehbein F, Hellmann D, Zenger M, Brähler E. A brief form of the Perceived Social Support Questionnaire (F-SozU). J Clin Epidemiol. 2015. doi: 10.1016/j.jclinepi.2014.11.003 25499982
27. Kessler R, Green J, Gruber M, Sampson N, Bromet E, Cuitan M, et al. Screening for serious mental illness in the general population with the K6 screening scale: Results from the WHO World Mental Health (WMH) survey initiative. Int J Methods Psychaitr Res. 2010. doi: 10.1002/mpr.310 20527002
28. Steinberg L, Sharp C, Stanford M, Tharp A. New tricks for an old measure: The development of the Barratt Impulsiveness Scale-Brief (BIS-Brief). Psychol Assess. 2013. doi: 10.1037/a0030550 23148649
29. Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Series B Stat Methodol. 2005; 67(2): 301–320.
30. Breiman L. Bagging predictors. J Mach Learn Res. 1996; 24(2): 123–140.
31. Hoerl A, Kennard R. Ridge regression. In: Encyclopedia of Statistical Sciences. New York, Wiley; 1988.
32. Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc Series B Stat Methodol. 1996; 58(1): 267–288.
33. Rodda SN, Bagot K.L, Manning V, Lubman DI. “It was terrible. I didn’t set a limit”. Proximal and distal prevention strategies for reducing the risk of a bust in gambling venues. J Gambl Stud. 2019. doi: 10.1007/s10899-019-09829-0 30694401
34. Dickerson M. Exploring the limits of ‘responsible gambling’: Harm minimisation or consumer protection? Gambling Research. 2003; 15: 29–44.
35. Parke J, Rigbye J, Parke A. Cashless and card-based technologies in gambling: A review of the literature. London: UK Gambling Commission; 2008.
36. Sniehotta FF, Scholz U, Schwarzer R. Bridging the intention–behaviour gap: Planning, self-efficacy, and action control in the adoption and maintenance of physical exercise. Psychology & Health. 2005. doi: 10.1080/08870440512331317670
37. Sniehotta FF, Schwarzer R, Scholz U, Schüz B. Action planning and coping planning for long-term lifestyle change: Theory and assessment. European Journal of Social Psychology. 2005. doi: 10.1002/ejsp.258
38. Rodda SN, Hing N, Hodgins DC, Cheetham A, Dickins M, Lubman DI. Behaviour change strategies for problem gambling: an analysis of online posts. International Gambling Studies. 2018.
39. World Health Organization. Ottawa charter for health promotion. 1986 [cited 9 July 2019]. http://www.who.int/healthpromotion/conferences/previous/ottawa/en/index1.html
40. Abbott MW. Beyond Reno: A critical commentary on Hancock and Smith. Int J Ment Health Addict. 2017; 15(6): 1177–1186.
41. Delfabbro P, King DL. Blame it on Reno: A commentary on Hancock and Smith. Int J Ment Health Addict. 2017; 15(6): 1203–1208.
Článek vyšel v časopise
PLOS One
2019 Číslo 10
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Je libo čepici místo mozkového implantátu?
- Pomůže v budoucnu s triáží na pohotovostech umělá inteligence?
- AI může chirurgům poskytnout cenná data i zpětnou vazbu v reálném čase
- Nová metoda odlišení nádorové tkáně může zpřesnit resekci glioblastomů
Nejčtenější v tomto čísle
- Correction: Low dose naltrexone: Effects on medication in rheumatoid and seropositive arthritis. A nationwide register-based controlled quasi-experimental before-after study
- Combining CDK4/6 inhibitors ribociclib and palbociclib with cytotoxic agents does not enhance cytotoxicity
- Experimentally validated simulation of coronary stents considering different dogboning ratios and asymmetric stent positioning
- Risk factors associated with IgA vasculitis with nephritis (Henoch–Schönlein purpura nephritis) progressing to unfavorable outcomes: A meta-analysis
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy