Abstract
Participation in gambling is rising in older adults. Indeed, in the coming years, engagement in gambling as a social activity is expected to increase more sharply in the elderly than in any other age group. Due to their exposure to powerful age-specific risk factors such as isolation, inactivity and failing health, older people are highly vulnerable to gambling-related problems. This study aimed to explore the existence of empirical clusters related to gambling habits in a sample of elderly participants from the general population. The sample included n = 361 participants, age range 50–90 years (mean 73.8, SD 8.4). Empirical clusters were identified through a two-step clustering analysis based on a broad set of indicators, including sociodemographic features, psychopathological state, substance use, life events, gambling preferences and scores on screening measures of gambling severity. The prevalence of GD in the study was 1.4%. Two clusters were identified: (a) cluster 1 (labeled as “low risk of gambling problems”, n = 265, 73.4%), which included the higher proportion of non-gamblers or individuals who engage only in non-strategic gambling, women, widowed, and lower levels of education (no individual into this group met criteria for GD); and (b) cluster 2 (labeled as “higher risk of gambling problems”, n = 96, 26.6%), which included the higher proportion of men, who reported both non-strategic and strategic gambling preferences (all participants diagnosed of GD were grouped into this cluster), older age, longer history of gambling, higher gambling severity, higher use of substances and worse psychopathological state. The elderly constitute a heterogeneous group with regard to gambling phenotypes. The results of this study may prove particularly useful for developing reliable screening tools able to identify older patients at a high risk of gambling problems, and for designing effective prevention and intervention programs.
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Acknowledgments
This manuscript and research were supported by grants from the Ministerio de Economía y Competitividad (PSI2015-68701-R). The research was funded by the Delegación del Gobierno para el Plan Nacional sobre Drogas (2017I067), Instituto de Salud Carlos III (ISCIII) (FIS PI14/00290 and PI17/01167) and co-funded by FEDER funds/European Regional Development Fund (ERDF), a way to build Europe. CIBERobn and CIBERSAM are both initiatives of ISCIII. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Support was received from the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia. TMM, CVA and MLM are supported by a predoctoral grant awarded by the Ministerio de Educación, Cultura y Deporte (FPU16/02087; FPU16/01453; FPU15/02911). We thank the CERCA Programme/Generalitat de Catalunya for institutional support.
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