| 1. |
- Abbott, Max, et al.
(författare)
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Conceptual Framework of Harmful Gambling: An International Collaboration (Revised Edition)
- 2015
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Although it is seen by many as a form of leisure and recreation, gambling can have serious repercussions for individuals, families, and society as a whole. The harmful effects of gambling have been studied for decades in an attempt to understand individual differences in gambling engagement and the life-course of gambling-related problems. In this publication, we present a comprehensive, internationally relevant conceptual framework of “harmful gambling” that moves beyond a symptoms-based view of harm and addresses a broad set of factors related to population risk, community and societal effects. Interactive factors depicted in the framework represent major themes in gambling that range from specific (gambling environment, exposure, types, and resources) to general (cultural, social, psychological, and biological). The framework has been created by international interdisciplinary experts and stakeholders— including researchers, treatment providers, operators, policy makers, as well as individuals and their families—in order to facilitate an understanding of harmful gambling. It reflects the state of knowledge related to factors influencing harmful gambling; and serves a secondary purpose as a guide for the development of future research programs and education of policy makers on issues related to harmful gambling. Gambling Research Exchange Ontario (GREO) (formerly the Ontario Problem Gambling Research Centre (OPGRC) located in Guelph, Ontario, Canada) has facilitated the development of the Conceptual Framework of Harmful Gambling and will retain responsibility for keeping it up-to-date.
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| 2. |
- Fröberg, Frida, 1973-, et al.
(författare)
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The Incidence of Problem Gambling in a Representative Cohort of Swedish Female and Male 16-24 Year-Olds by Socio-demographic Characteristics, in Comparison with 25-44 Year-Olds
- 2015
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Ingår i: Journal of Gambling Studies. - : Springer Nature. - 1050-5350 .- 1573-3602. ; 31:3, s. 621-641
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Tidskriftsartikel (refereegranskat)abstract
- We aimed to estimate the incidence of a first episode of problem gambling among Swedish 16-24 year-olds by demographic and socio-economic characteristics, and to compare the incidence between 16-24 and 25-44 year-olds, and between young women and men. Other aims were to estimate the proportions of recovery and incidence in recurrent problem gambling, and prevalence of problem gambling among 16-44 year-olds in Sweden. We selected 4,358 participants aged 16-44 from the nationally representative Swedish Longitudinal Gambling Study in 2008/2009 and 2009/2010. The primary outcome measure was a first episode of problem gambling during 12 months before the follow-up as measured by the Problem Gambling Severity Index among participants without a history of problem gambling at baseline. The incidence proportion of a first episode of problem gambling among 16-24 year-olds was 2.26% (95% confidence interval 1.52-3.36); three times lower among females (1.14; 0.42-3.07%) than males (3.32; 2.19-5.01%). Young age and household financial problems were associated with first episode problem gambling among young women. Among 25-44 year-olds, the incidence proportion of a first episode of problem gambling was 0.81% (0.41-1.56). Recovery from problem gambling was high, in particular among females. Individual transitions from problem gambling to recovery and to recurrent problem gambling, between baseline and follow-up, were common regardless of age. This study adds further evidence to research suggesting that there is a high mobility in and out of problem gambling over time on an individual level. The high incidence of first episode problem gambling among youth in Sweden stresses the importance of prevention of problem gambling at an early age.
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| 3. |
- Parmar, Priya, et al.
(författare)
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The Stroke Riskometer (TM) App: Validation of a data collection tool and stroke risk predictor
- 2015
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Ingår i: International Journal of Stroke. - : SAGE Publications. - 1747-4949 .- 1747-4930. ; 10:2, s. 231-244
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the mass' approach), the high risk' approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer(TM), has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods. Methods752 stroke outcomes from a sample of 9501 individuals across three countries (New Zealand, Russia and the Netherlands) were utilized to investigate the performance of a novel stroke risk prediction tool algorithm (Stroke Riskometer(TM)) compared with two established stroke risk score prediction algorithms (Framingham Stroke Risk Score [FSRS] and QStroke). We calculated the receiver operating characteristics (ROC) curves and area under the ROC curve (AUROC) with 95% confidence intervals, Harrels C-statistic and D-statistics for measure of discrimination, R-2 statistics to indicate level of variability accounted for by each prediction algorithm, the Hosmer-Lemeshow statistic for calibration, and the sensitivity and specificity of each algorithm. ResultsThe Stroke Riskometer(TM) performed well against the FSRS five-year AUROC for both males (FSRS=750% (95% CI 723%-776%), Stroke Riskometer(TM)=740(95% CI 713%-767%) and females [FSRS=703% (95% CI 679%-728%, Stroke Riskometer(TM)=715% (95% CI 690%-739%)], and better than QStroke [males - 597% (95% CI 573%-620%) and comparable to females=711% (95% CI 690%-731%)]. Discriminative ability of all algorithms was low (C-statistic ranging from 051-056, D-statistic ranging from 001-012). Hosmer-Lemeshow illustrated that all of the predicted risk scores were not well calibrated with the observed event data (P<0006). ConclusionsThe Stroke Riskometer(TM) is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke Riskometer(TM) will be continually developed and validated to address the need to improve the current stroke risk scoring systems to more accurately predict stroke, particularly by identifying robust ethnic/race ethnicity group and country specific risk factors.
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