The ability of the UK population surveys to capture the true nature of the extent of gambling‐related harm
2022; Wiley; Volume: 117; Issue: 7 Linguagem: Inglês
10.1111/add.15864
ISSN1360-0443
AutoresAmanda Roberts, Steve Sharman, Henrietta Bowden‐Jones,
Tópico(s)Homelessness and Social Issues
ResumoAddictionEarly View LETTER TO THE EDITORFree Access The ability of the UK population surveys to capture the true nature of the extent of gambling-related harm Amanda Roberts, Corresponding Author Amanda Roberts aroberts@lincoln.ac.uk orcid.org/0000-0002-2889-9551 School of Psychology, University of Lincoln, Lincoln, UK Correspondence Amanda Roberts, School of Psychology, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK. Email: aroberts@lincoln.ac.uk Contribution: Investigation (equal)Search for more papers by this authorSteve Sharman, Steve Sharman orcid.org/0000-0001-9816-7981 National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK Contribution: Investigation (equal)Search for more papers by this authorHenrietta Bowden-Jones, Henrietta Bowden-Jones National Problem Gambling Clinic, London, UK Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Cambridge, UK Contribution: Conceptualization (lead), Investigation (equal)Search for more papers by this author Amanda Roberts, Corresponding Author Amanda Roberts aroberts@lincoln.ac.uk orcid.org/0000-0002-2889-9551 School of Psychology, University of Lincoln, Lincoln, UK Correspondence Amanda Roberts, School of Psychology, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK. Email: aroberts@lincoln.ac.uk Contribution: Investigation (equal)Search for more papers by this authorSteve Sharman, Steve Sharman orcid.org/0000-0001-9816-7981 National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK Contribution: Investigation (equal)Search for more papers by this authorHenrietta Bowden-Jones, Henrietta Bowden-Jones National Problem Gambling Clinic, London, UK Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Cambridge, UK Contribution: Conceptualization (lead), Investigation (equal)Search for more papers by this author First published: 08 March 2022 https://doi.org/10.1111/add.15864AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat The UK government is undergoing consultation to reform the UK 2005 Gambling Act. Gambling behaviour in the general population was measured via the British Gambling Prevalence Survey (BGPS), (1999, 2007 and 2010) [1] and, since 2010, via the Health Survey England (HSE) and Scottish Health Survey (SHeS) [2], and more recently by small telephone surveys carried out quarterly by the Gambling Commission (GC) [3]. The GC telephone surveys involve only a small non-representative sample and rely upon respondents answering a number they do not recognize. Similarly, although BGPS and HSE data provide a cross-sectional snapshot of gambling behaviour, such surveys are subject to methodological limitations. For example, both surveys exclude people who do not have a residential address, such as those who are experiencing homelessness, and also fail to include people who reside at institutional addresses such as hospitals, prisons, military barracks and student halls of residence. Such populations are likely to have higher rates of gambling problems [4, 5]. As a consequence, both surveys are likely to significantly under-report gambling-related harm. Such methodological limitations are not limited to gambling surveys; a recent article regarding measuring heroin use via general population surveys (the US National Survey on Drug Use and Health) drew the conclusion that such methodological limitations are likely to lead to significant underestimation of the disorder [6]. Similarly, prevalence surveys rely upon subjective self-reports and are prone to error [7], such as selective non-response or selection bias [6, 8] and socially desirable responding [9]. Even the largest surveys have been shown to rely upon the responses of a small number of the overall populace [6]. Research has shown that people may be less likely to take part in research and to disclose problematic gambling for reasons such as stigma [10]. Furthermore, data collected by prevalence surveys are cross-sectional, which do not capture the episodic nature of disordered gambling [11, 12] or the harms experienced beyond the individual. Gambling harms can impact the health and wellbeing of individuals, as well as families, communities and society as a whole [13]. Additionally, both surveys use the Problem Gambling Severity Index (PGSI), which has reliable properties for detecting gambling disorder but is less appropriate for measuring individuals who are 'at-risk' of problematic gambling [14], although at-risk gamblers are estimated to account for approximately 85% of the burden of gambling harm at population level [15, 16]. The primary focus of the BGPS was gambling behaviour; however, the number of gambling questions has been reduced in the broader HSE and SHeS [2]. Consequently, key topics which would provide vital evidence are lacking. In addition, the health surveys include gambling questions towards the end of the survey which can reduce data quality, due to decreases in concentration and enthusiasm towards latter sections of a questionnaire [17]. Similarly, positioning gambling questions at the end of a long survey to detect a population with high impulsivity levels is a significant issue, as it is unlikely that respondents work their way consistently to the end [18]. Gambling questions in health surveys have correspondingly been demonstrated to show a much lower prevalence than gambling-specific questionnaires [19]. Akin to the foundation of the formulation of substance use policy, it is crucial that we quantify and recognize the extent of harms attributable to gambling. This is unlikely to be achieved by cross-sectional surveys alone. There is need for a gambling-specific, longitudinal prevalence study that utilizes more comprehensive and inclusive data collection methodologies and more clearly understands the true extent of wider gambling harms. These data can then be triangulated with existing large-scale data sets such as those held by the financial sector, health and social care records and criminal justice systems. Although a large task with multiple obstacles, better cohesion across sectors is essential to move towards a more effective use of data that can support the identification, minimization and prevention of gambling-related harms. ACKNOWLEDGEMENTS The content of this letter is solely the responsibility of the authors. DECLARATION OF INTERESTS A.R. has received funding from the Society for the Study of Addiction (SSA) and the Gambling Research Exchange Ontario (GREO). S.S. has received funding from the Society for the Study of Addiction (SSA), the King's Prize Fellowship Scheme funded by the Wellcome Trust Institutional Strategic Support Fund and as part of the NIHR Biomedical Research Centre funding for the National Addiction Centre. H.B.-D. is the Director of The National Problem Gambling Clinic which receives funds from the National Health Service and GambleAware. After 21 March 2022 the clinic will only receive funds from the National Health Service. She is also board member of the International Society for the Study of Behavioural Addictions, President of the Royal Society of Medicine Psychiatry Section and Trustee of the RSM Elected Board of Science member at the British Medical Association. AUTHOR CONTRIBUTIONS Amanda Roberts: Investigation. Steve Sharman: Investigation. Henrietta Bowden-Jones: Conceptualization; investigation. REFERENCES 1Wardle H, Moody A, Spence S, Orford J, Volberg R, Jotangia D, et al. British Gambling Prevalence Survey 2010. London, UK: National Centre for Social Research; 2011. Available at: https://www.academia.edu/446044/Wardle_H_Moody_A_Spence_S_Orford_J_Volberg_R_Jotangia_D_Griffiths_M_Hussey_D_and_Dobbie_F_2011_British_Gambling_Prevalence_Survey_2010_London_The_Stationery_Office. Accessed 14 Jan 2022. Google Scholar 2 Health Survey for England. Adults' health-related behaviours. Health and Social Care Information Centre; 2018. Available at: https://digital.nhs.uk/data-and-information/publications/statistical/health-survey-for-england/2018. Accessed 14 Jan 2022. Google Scholar 3 Gambling Commission. Gambling behaviour in 2021: findings from the quarterly telephone survey; 2021. Available at: https://www.gamblingcommission.gov.uk/statistics-and-research/publication/year-to-March-2021. Accessed 14 Jan 2022. Google Scholar 4Sharman S, Dreyer J, Aitken M, Clark L, Bowden-Jones H. Rates of problematic gambling in a British homeless sample: a preliminary study. J Gambl Stud. 2015; 31: 525– 32. CrossrefPubMedWeb of Science®Google Scholar 5Sharman S, Butler K, Roberts A. Psychosocial risk factors in disordered gambling: a descriptive systematic overview of vulnerable populations. Addict Behav. 2019;(99):106071. CrossrefGoogle Scholar 6Reuter P, Caulkins JP, Midgette G. Heroin use cannot be measured adequately with a general population survey. Addiction. 2021; 116: 2600– 9. Wiley Online LibraryPubMedWeb of Science®Google Scholar 7Rosenman R, Tennekoon V, Hill LG. Measuring bias in self-reported data. Int J Behav Healthcare Res. 2011; 2: 320– 32. Available at: https://www.inderscienceonline.com/doi/abs/10.1504/IJBHR.2011.043414. Accessed 14 Jan 2022. CrossrefPubMedGoogle Scholar 8Cheung KL, Peter M, Smit C, de Vries H, Pieterse ME. The impact of non-response bias due to sampling in public health studies: a comparison of voluntary versus mandatory recruitment in a Dutch national survey on adolescent health. BMC Public Health. 2017; 17: 1– 10. CrossrefPubMedWeb of Science®Google Scholar 9Goldstein AL, Vilhena-Churchill N, Munroe M, Stewart SH, Flett GL, Hoaken PN. Understanding the effects of social desirability on gambling self-reports. Int J Ment Health Addict. 2017; 15: 1342– 59. CrossrefWeb of Science®Google Scholar 10Roberts A, Bowden-Jones H, Roberts D, Sharman S. Should GPs routinely screen for gambling disorders? Br J Gen Pract. 2019; 69: 226– 7. CrossrefGoogle Scholar 11Reith G, Dobbie F. Gambling careers: a longitudinal, qualitative study of gambling behaviour. Addict Res Theory. 2013; 21: 376– 90. CrossrefWeb of Science®Google Scholar 12Williams RJ, Hann RG, Schopflocher DP, West BL, McLaughlin P, White N, et al. Quinte longitudinal study of gambling and problem gambling. Ontario Problem Gambling Research Centre; 2015. Available at: https://hdl.handle.net/10133/3641. Accessed 14 Jan 2022. Google Scholar 13Wardle H, Reith G, Best D, McDaid D, Platt S. Measuring gambling-related harms: a framework for action. Gambling Commission, Birmingham, UK; 2018. Available at: https://www.gamblingcommission.gov.uk/PDF/Measuring-gambling-related-harms.pdf. Accessed 14 Jan 2022. Google Scholar 14Currie SR, Hodgins DC, Casey DM. Validity of the problem gambling severity index interpretive categories. J Gambl Stud. 2013; 29: 311– 27. CrossrefPubMedWeb of Science®Google Scholar 15Williams RJ, Volberg RA. The classification accuracy of four problem gambling assessment instruments in population research. Int Gambl Stud. 2014; 14: 15– 28. CrossrefWeb of Science®Google Scholar 16Browne M, Greer N, Rawat V, Rockloff M. A population-level metric for gambling-related harm. Int Gambl Stud. 2017; 17: 163– 75. CrossrefWeb of Science®Google Scholar 17O'Reilly-Shah VN. Factors influencing healthcare provider respondent fatigue answering a globally administered in-app survey. Peer J. 2017;(5):e3785. CrossrefGoogle Scholar 18Ioannidis K, Hook R, Wickham K, Grant JE, Chamberlain SR. Impulsivity in gambling disorder and problem gambling: a meta-analysis. Neuropsychopharmacology. 2019; 44: 1354– 61. CrossrefPubMedWeb of Science®Google Scholar 19Williams RJ, Volberg RA. Impact of survey description, administration format, and exclusionary criteria on population prevalence rates of problem gambling. Int Gambl Stud. 2009; 9: 101– 17. CrossrefGoogle Scholar Early ViewOnline Version of Record before inclusion in an issue ReferencesRelatedInformation
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