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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.
Purpose
The aim is to investigate the associations of the mother’s socioeconomic and lifestyle factors and life satisfaction with the delivery of a small for gestational age (SGA) infant.
Methods
Data from 4598 participants of the population-based birth cohort study Survey of Neonates in Pomerania (SniP) including comprehensive information on pregnancies, mothers, and their offspring in Western Pomerania, Germany were used in this study. The associations were analyzed using linear and logistic regression models.
Results
After logistic regression analysis adjusted for height of the mother, women who delivered SGA infants, had lower education (p < 0.01) and smoked more frequently during pregnancy (p < 0.01) compared with mothers of adequate for gestational age (AGA) neonates. A mother with less than 10 years of education and one who continued smoking during pregnancy had an odds ratio (OR) of 2.23 [95% confidence interval (CI) = 1.44 to 3.46] and 2.68 (95% CI = 2.06–3.49) of having an SGA infant, respectively. There was no association between the employment of the mother (p = 0.28), the monthly income (p = 0.09), the family status (p = 0.80), the number of friendships outside the household that the mother would not wish to relinquish (p = 0.47), the number of people that she could rely on in case of an emergency (p = 0.75), or alcohol consumption prior to (p = 0.14) or during the pregnancy (p = 0.99) with SGA. Finally, women who delivered SGA infants were more frequently dissatisfied with their employment (p = 0.03) and financial status (p < 0.01).
Conclusions
Women who delivered SGA infants had more associated socioeconomic and lifestyle risk factors and were more frequently dissatisfied with their life conditions than mothers of AGA neonates.
Background
Missing data are ubiquitous in randomised controlled trials. Although sensitivity analyses for different missing data mechanisms (missing at random vs. missing not at random) are widely recommended, they are rarely conducted in practice. The aim of the present study was to demonstrate sensitivity analyses for different assumptions regarding the missing data mechanism for randomised controlled trials using latent growth modelling (LGM).
Methods
Data from a randomised controlled brief alcohol intervention trial was used. The sample included 1646 adults (56% female; mean age = 31.0 years) from the general population who had received up to three individualized alcohol feedback letters or assessment-only. Follow-up interviews were conducted after 12 and 36 months via telephone. The main outcome for the analysis was change in alcohol use over time. A three-step LGM approach was used. First, evidence about the process that generated the missing data was accumulated by analysing the extent of missing values in both study conditions, missing data patterns, and baseline variables that predicted participation in the two follow-up assessments using logistic regression. Second, growth models were calculated to analyse intervention effects over time. These models assumed that data were missing at random and applied full-information maximum likelihood estimation. Third, the findings were safeguarded by incorporating model components to account for the possibility that data were missing not at random. For that purpose, Diggle-Kenward selection, Wu-Carroll shared parameter and pattern mixture models were implemented.
Results
Although the true data generating process remained unknown, the evidence was unequivocal: both the intervention and control group reduced their alcohol use over time, but no significant group differences emerged. There was no clear evidence for intervention efficacy, neither in the growth models that assumed the missing data to be at random nor those that assumed the missing data to be not at random.
Conclusion
The illustrated approach allows the assessment of how sensitive conclusions about the efficacy of an intervention are to different assumptions regarding the missing data mechanism. For researchers familiar with LGM, it is a valuable statistical supplement to safeguard their findings against the possibility of nonignorable missingness.
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.
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.
Little is known about the (co-)occurrence of smoking, alcohol at-risk drinking, physical inactivity and overweight, and the motivation to change these behavioral health risk factors (HRFs) in older general hospital patients with cardiovascular disease. Between October and December 2016, all consecutively admitted patients aged 50 to 79 years were proactively recruited on 3 cardiology wards and asked to participate in a survey on HRFs and behavior change motivation. Of the eligible patients, 80.4% participated in the survey (n = 328). The mean age was 66.5 years (standard deviation 9.0), and 65.5% were male. At least 1 HRF was present in 91.8% (n = 280), at least 2 HRFs in 54.4% (n = 166), and 3 or 4 HRFs in 12.1% (n = 37) of participants. The proportion of older adults who contemplated or were changing or planning to change their behavior to meet health behavior recommendations ranged between 66.0% (smoking) and 93.2% (alcohol consumption). The results indicate a notable co-occurrence of behavioral HRFs in older patients with cardiovascular disease. The majority of older adults were at least considering changing the respective behavior. To prevent and treat diseases efficiently, hospitalization may be a suitable moment for systematic multiple HRF screening and intervention.
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.
Objectives: To investigate the co-occurrence of 4 behavioral health risk factors (BHRFs), namely tobacco smoking, alcohol at-risk drinking, physical inactivity and unhealthy diet and their association with sick days prior to hospitalization in general hospital patients.
Methods: Over 10 weeks (11/2020-04/2021), all 18-64-year-old patients admitted to internal medicine, general and trauma surgery, and otorhinolaryngology wards of a tertiary care hospital were systematically approached. Among 355 eligible patients, 278 (78.3%) participated, and 256 (72.1%) were analyzed. Three BHRF sum scores were determined, including current tobacco smoking, alcohol use, physical inactivity and 1 of 3 indicators of unhealthy diet. Associations between BHRF sum scores and sick days in the past 6 months were analyzed using multivariate zero-inflated negative binomial regressions.
Results: Sixty-two percent reported multiple BHRFs (≥2). The BHRF sum score was related to the number of sick days if any (p = 0.009) with insufficient vegetable and fruit intake as diet indicator.
Conclusion: The majority of patients disclosed multiple BHRFs. These were associated with sick days prior to admission. The findings support the need to implement interventions targeting multiple BHRFs in general hospitals.
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.
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.
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.