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> -wrap-foot> There were substantial normative misperceptions in this general population sample of problem drinkers.
Strengths of the trial include a rigorous research design, excellent follow-up rates, a conservative analytic approach, the use of a no-intervention control group and the recruitment of a general population sample of problem drinkers with different levels of severity of alcohol problems.
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Instead, professors often select a representative sample of problems or topics and test the students on only those.
From the results obtained in this research, it is observed that genetic algorithms (GA) have performed in general less efficiently than the Integer Goal Programming system for the sample of problems analysed.
This is consistent with a meta-analysis of community-representative samples of problem gamblers (Lorains et al., 2011).
The findings relating to psychiatric co-morbidity in treatment-seeking samples of problem gamblers are important in understanding individual treatment needs and outcomes (Lorains et al., 2011).
Thus, depression-specific dysfunctional attitudes relate to alcohol problems, also problematic alcohol consumption, directly or via the level of and changes in depression, and may be an important factor to include also in samples of problem drinkers.
Although they generally employ non-random samples, treatment-seeking studies generally comprise larger samples of problem gamblers, which allows for the investigation of lower prevalence co-morbid disorders and an investigation of how the level of gambling severity co-varies with co-morbid disorders (Westphal and Johnson, 2007).
A systematic review and meta-analysis of co-morbid disorders in population-representative samples of problem gamblers revealed high rates of psychiatric disorders, including nicotine dependence (60%), alcohol and substance use disorders (58%), mood disorders (38%) and anxiety disorders (37%) (Lorains et al., 2011).
As a consequence of case specificity, reliability and content validity of an examination are dependent on a broad sampling of problems.
These evaluation methods, however, are all resource-intensive, thus making it difficult to provide the representative sampling of problems necessary to circumvent the problem of case specificity, which predicts that success in solving one clinical presentation does not predict success in another [ 1].
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