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Background
Few studies have assessed trajectories of alcohol use in the general population, and even fewer studies have assessed the impact of brief intervention on the trajectories. Especially for low-risk drinkers, it is unclear what trajectories occur, whether they benefit from intervention, and if so, when and how long. The aims were first, to identify alcohol use trajectories among at-risk and among low-risk drinkers, second, to explore potential effects of brief alcohol intervention and, third, to identify predictors of trajectories.
Methods
Adults aged 18-64 years were screened for alcohol use at a municipal registration office. Those with alcohol use in the past 12 months (N = 1646; participation rate: 67%) were randomized to assessment plus computer-generated individualized feedback letters or assessment only. Outcome was drinks/week assessed at months 3, 6, 12, and 36. Alcohol risk group (at-risk/low-risk) was determined using the Alcohol Use Disorders Identification Test–Consumption. Latent class growth models were estimated to identify alcohol use trajectories among each alcohol risk group. Sex, age, school education, employment status, self-reported health, and smoking status were tested as predictors.
Results
For at-risk drinkers, a light-stable class (46%), a medium-stable class (46%), and a high-decreasing class (8%) emerged. The light-stable class tended to benefit from intervention after 3 years (Incidence Rate Ratio, IRR=1.96; 95% Confidence Interval, CI: 1.14–3.37). Male sex, higher age, more years of school, and current smoking decreased the probability of belonging to the light-stable class (p-values<0.05). For low-risk drinkers, a very light-slightly increasing class (72%) and a light-increasing class (28%) emerged. The very light-slightly increasing class tended to benefit from intervention after 6 months (IRR=1.60; 95% CI: 1.12–2.28). Male sex and more years of school increased the probability of belonging to the light-increasing class (p-value < 0.05).
Conclusion
Most at-risk drinkers did not change, whereas the majority of low-risk drinkers increased alcohol use. There may be effects of alcohol feedback, with greater long-term benefits among persons with low drinking amounts. Our findings may help to identify refinements in the development of individualized interventions to reduce alcohol use.
Background/Aims: Only a small percentage of pathological gamblers utilizes professional treatment for gambling problems. Little is known about which social and gambling-related factors are associated with treatment utilization. The aim of this study was to look for factors associated with treatment utilization for pathological gambling. Methods: The study followed a sampling design with 3 different recruitment channels, namely (1) a general population-based telephone sample, (2) a gambling location sample and (3) a project telephone hotline. Pathological gambling was diagnosed in a telephone interview. Participants with pathological gambling (n = 395) received an in-depth clinical interview concerning treatment utilization, comorbid psychiatric disorders and social characteristics. Results: Variables associated with treatment were higher age [odds ratio (OR) 1.05, 95% confidence interval (CI) 1.03-1.08], an increased number of DSM-IV criteria for pathological gambling (OR 1.34, 95% CI 1.06-1.70), more adverse consequences from gambling (OR 1.10, 95% CI 1.03-1.16) and more social pressure from significant others (OR 1.17, 95% CI 1.07-1.27). Affective disorders were associated with treatment utilization in the univariate analysis (OR 1.81, 95% CI 1.19-2.73), but multivariate analysis showed that comorbid psychiatric disorders were not independently associated. Conclusion: These results indicate that individuals with more severe gambling problems utilize treatment at an older age when more adverse consequences have occurred. Further research should focus on proactive early interventions.
This study investigated whether tobacco smoking affected outcomes of brief alcohol interventions (BAIs) in at-risk alcohol-drinking general hospital patients. Between 2011 and 2012 among patients aged 18–64 years, 961 patients were allocated to in-person counseling (PE), computer-based BAI containing computer-generated individual feedback letters (CO), and assessment only. PE and CO included contacts at baseline, 1, and 3 months. After 6, 12, 18, and 24 months, self-reported reduction of alcohol use per day was assessed as an outcome. By using latent growth curve models, self-reported smoking status, and number of cigarettes per day were tested as moderators. In PE and CO, alcohol use was reduced independently of smoking status (IRRs ≤ 0.61, ps < 0.005). At month 24, neither smoking status nor number of cigarettes per day moderated the efficacy of PE (IRR = 0.69, ps > 0.05) and CO (IRR = 0.85, ps > 0.05). Up to month 12, among persons smoking ≤ 19 cigarettes per day, the efficacy of CO increased with an increasing number of cigarettes (ps < 0.05). After 24 months, the efficacy of PE and CO that have been shown to reduce drinking did not differ by smoking status or number of cigarettes per day. Findings indicate that efficacy may differ by the number of cigarettes in the short term.
Background/Aims: Only rather few data on the validity of screening questionnaires to detect problem drinking in adolescents exist. The aim of this study was to compare the performance of the Alcohol Use Disorders Identification Test (AUDIT), its short form AUDIT-C, the Substance Module of the Problem Oriented Screening Instrument for Teenagers (POSIT), and CRAFFT (acronym for car, relax, alone, forget, family, and friends). Methods: The questionnaires were filled in by 9th and 10th graders from two comprehensive schools. All students received an interview using the alcohol section of the Composite International Diagnostic Interview. Alcohol abuse and alcohol dependence according to DSM-IV as well as episodic heavy drinking served as criteria to validate the screening instruments. Results: All 9th and 10th graders (n = 225) of both schools participated. No significant differences were found for areas under the receiver operating characteristic curves ranging from 0.810 to 0.872. Cronbach’s alpha was satisfactory (0.77–0.80) but poor for CRAFFT (0.64). Different cut-offs are discussed. Conclusions: Considering validity as well as reliability, AUDIT, AUDIT-C and POSIT performed well; however, the POSIT is quite lengthy. AUDIT-C showed good psychometric properties and has clear advantages because of its brevity.