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Introduction: The aim of this study was to test whether brief alcohol interventions at general hospitals work equally well for males and females and across age-groups.
Methods: The current study includes a reanalysis of data reported in the PECO study (testing delivery channels of individualized motivationally tailored alcohol interventions among general hospital patients: in PErson vs. COmputer-based) and is therefore of exploratory nature. At-risk drinking general hospital patients aged 18–64 years (N = 961) were randomized to in-person counseling, computer-generated individualized feedback letters, or assessment only. Both interventions were delivered on the ward and 1 and 3 months later. Follow-ups were conducted at months 6, 12, 18, and 24. The outcome was grams of alcohol/day. Study group × sex and study group × age interactions were tested as predictors of change in grams of alcohol/day over 24 months in latent growth models. If rescaled likelihood ratio tests indicated improved model fit due to the inclusion of interactions, moderator level-specific net changes were calculated.
Results: Model fit was not significantly improved due to the inclusion of interaction terms between study group and sex (χ2[6] = 5.9, p = 0.439) or age (χ2[6] = 5.5, p = 0.485).
Discussion: Both in-person counseling and computer-generated feedback letters may work equally well among males and females as well as among different age-groups. Therefore, widespread delivery of brief alcohol interventions at general hospitals may be unlikely to widen sex and age inequalities in alcohol-related harm.
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.
Background:
Social equity in the efficacy of behavior change intervention is much needed. While the efficacy of brief alcohol interventions (BAIs), including digital interventions, is well established, particularly in health care, the social equity of interventions has been sparsely investigated.
Objective:
We aim to investigate whether the efficacy of computer-based versus in-person delivered BAIs is moderated by the participants’ socioeconomic status (ie, to identify whether general hospital patients with low-level education and unemployed patients may benefit more or less from one or the other way of delivery compared to patients with higher levels of education and those that are employed).
Methods:
Patients with nondependent at-risk alcohol use were identified through systematic offline screening conducted on 13 general hospital wards. Patients were approached face-to-face and asked to respond to an app for self-assessment provided by a mobile device. In total, 961 (81% of eligible participants) were randomized and received their allocated intervention: computer-generated and individually tailored feedback letters (CO), in-person counseling by research staff trained in motivational interviewing (PE), or assessment only (AO). CO and PE were delivered on the ward and 1 and 3 months later, were based on the transtheoretical model of intentional behavior change and required the assessment of intervention data prior to each intervention. In CO, the generation of computer-based feedback was created automatically. The assessment of data and sending out feedback letters were assisted by the research staff. Of the CO and PE participants, 89% (345/387) and 83% (292/354) received at least two doses of intervention, and 72% (280/387) and 54% (191/354) received all three doses of intervention, respectively. The outcome was change in grams of pure alcohol per day after 6, 12, 18, and 24 months, with the latter being the primary time-point of interest. Follow-up interviewers were blinded. Study group interactions with education and employment status were tested as predictors of change in alcohol use using latent growth modeling.
Results:
The efficacy of CO and PE did not differ by level of education (P=.98). Employment status did not moderate CO efficacy (Ps≥.66). Up to month 12 and compared to employed participants, unemployed participants reported significantly greater drinking reductions following PE versus AO (incidence rate ratio 0.44, 95% CI 0.21-0.94; P=.03) and following PE versus CO (incidence rate ratio 0.48, 95% CI 0.24–0.96; P=.04). After 24 months, these differences were statistically nonsignificant (Ps≥.31).
Conclusions:
Computer-based and in-person BAI worked equally well independent of the patient’s level of education. Although findings indicate that in the short-term, unemployed persons may benefit more from BAI when delivered in-person rather than computer-based, the findings suggest that both BAIs have the potential to work well among participants with low socioeconomic status.
Introduction
The co-occurrence of health risk behaviours (HRBs, ie, tobacco smoking, at-risk alcohol use, insufficient physical activity and unhealthy diet) increases the risks of cancer, other chronic diseases and mortality more than additively; and applies to more than half of adult general populations. However, preventive measures that target all four HRBs and that reach the majority of the target populations, particularly those persons most in need and hard to reach are scarce. Electronic interventions may help to efficiently address multiple HRBs in healthcare patients. The aim is to investigate the acceptance of a proactive and brief electronic multiple behaviour change intervention among general hospital patients with regard to reach, retention, equity in reach and retention, satisfaction and changes in behaviour change motivation, HRBs and health.
Methods and analysis
A pre–post intervention study with four time points is conducted at a general hospital in Germany. All patients, aged 18–64 years, admitted to participating wards of five medical departments (internal medicine A and B, general surgery, trauma surgery, ear, nose and throat medicine) are systematically approached and invited to participate. Based on behaviour change theory and individual HRB profile, 175 participants receive individualised and motivation-enhancing computer-generated feedback at months 0, 1 and 3. Intervention reach and retention are determined by the proportion of participants among eligible patients and of participants who continue participation, respectively. Equity in reach and retention are measured with regard to school education and other sociodemographics. To investigate satisfaction with the intervention and subsequent changes, a 6-month follow-up is conducted. Descriptive statistics, multivariate regressions and latent growth modelling are applied.
Ethics and dissemination
The local ethics commission and data safety appointee approved the study procedures. Results will be disseminated via publication in international scientific journals and presentations on scientific conferences.
Trial registration numberNCT05365269.
Copattern of depression and alcohol use in medical care patients: cross- sectional study in Germany
(2020)
Objective
To predict depressive symptom severity and presence of major depression along the full alcohol use continuum.
Design
Cross-sectional study.
Setting
Ambulatory practices and general hospitals from three sites in Germany.
Participants
Consecutive patients aged 18–64 years were proactively approached for an anonymous health screening (participation rate=87%, N=12 828). Four continuous alcohol use measures were derived from an expanded Alcohol Use Disorder Identification Test (AUDIT): alcohol consumption in grams per day and occasion, excessive consumption in days per months and the AUDIT sum score. Depressive symptoms were assessed for the worst 2-week period in the last 12 months using the Patient Health Questionnaire (PHQ-8). Negative binomial and logistic regression analyses were used to predict depressive symptom severity (PHQ-8 sum score) and presence of major depression (PHQ-8 sum score≥10) by the alcohol use measures.
Results
Analyses revealed that depressive symptom severity and presence of major depression were significantly predicted by all alcohol use measures after controlling for sociodemographics and health behaviours (p<0.05). The relationships were curvilinear: lowest depressive symptom severity and odds of major depression were found for alcohol consumptions of 1.1 g/day, 10.5 g/occasion, 1 excessive consumption day/month, and those with an AUDIT score of 2. Higher depressive symptom severity and odds of major depression were found for both abstinence from and higher levels of alcohol consumption. Interaction analyses revealed steeper risk increases in women and younger individuals for most alcohol use measures.
Conclusion
Findings indicate that alcohol use and depression in medical care patients are associated in a curvilinear manner and that moderation by gender and age is present.
This study aims to analyze psychometric properties and validity of the Compulsive Internet Use Scale (CIUS) and the Internet Addiction Test (IAT) and, second, to determine a threshold for the CIUS which matches the IAT cut-off for detecting problematic Internet use. A total of 292 subjects with problematic or pathological gambling (237 men, 55 women) aged 14-63 years and with private Internet use for at least 1 h per working or weekend day were recruited via different recruitment channels. Results include that both scales were internally consistent (Cronbach's α = 0.9) and had satisfactory convergent validity (r = 0.75; 95% CI 0.70-0.80). The correlation with duration of private Internet use per week was significantly higher for the CIUS (r = 0.54) compared to the IAT (r = 0.40). Among all participants, 25.3% were classified as problematic Internet users based on the IAT with a cut-off ≥40. The highest proportion of congruent classified cases results from a CIUS cut-off ≥18 (sensitivity 79.7%, specificity 79.4%). However, a higher cut-off (≥21) seems to be more appropriate for prevalence estimation of problematic Internet use.