Sick days in general hospital patients two years after brief alcohol intervention: Secondary outcomes from a randomized controlled trial

A mobile phone intervention to reduce heavy drinking: a preliminary analysis of anchoring heuristics

BACKGROUND

Preliminary evidence has been presented for interventions focused on preventing alcohol consumption or reducing the occurrence of episodes of excessive drinking. The anchoring text message intervention is a newly proposed theory-based approach to reducing heavy drinking among youth. The current study tests the preliminary efficacy of this intervention for reducing heavy drinking among Mexican youth.

METHODS

Focusing on a sample of sixteen Mexican youths-nine not-heavy drinkers and seven heavy drinkers-the participants completed a survey on alcohol consumption and anchoring heuristics. Pretest and post-test questionnaire data were collected to evaluate the effectiveness of the intervention. The anchoring text messages consisted of strategies to limit alcohol use and feedback reminder messages. Assessments were conducted at baseline, four weeks of intervention, and post-intervention.

RESULTS

Logistic regression analyses indicated a significant effect on heavy drinking episodes post-intervention. The post-intervention anchoring effects among the heavy drinker participants were different from those among the non-heavy drinkers in terms of reporting heavy drinking and future drinking. The anchoring heuristic-based intervention reduced the quantity of drinking and the future estimation of drinking and improved the ability to reject alcohol in the heavy drinker group.

CONCLUSIONS

These findings provide preliminary support for the effectiveness of the anchoring heuristic-based intervention, conducted through text messages sent by mobile phone to reduce alcohol consumption. The intervention promoted a reduction in alcohol consumption. Future research should be directed toward investigating the anchoring effects among heavy drinkers.

Do in-person and computer-based brief alcohol interventions reduce tobacco smoking among general hospital patients? Secondary outcomes from a randomized controlled trial

BACKGROUND

At-risk alcohol use and tobacco smoking often co-occur. We investigated whether brief alcohol interventions (BAIs) among general hospital patients with at-risk alcohol use may also reduce tobacco smoking over 2 years. We also investigated whether such effects vary by delivery mode; i.e. in-person versus computer-based BAI.

METHODS

A proactively recruited sample of 961 general hospital patients with at-risk alcohol use aged 18 to 64 years was allocated to three BAI study groups: in-person BAI, computer-based BAI, and assessment only. In-person- and computer-based BAI included motivation-enhancing intervention contacts to reduce alcohol use at baseline and 1 and 3 months later. Follow-ups were conducted after 6, 12, 18 and 24 months. A two-part latent growth model, with self-reported smoking status (current smoking: yes/no) and number of cigarettes in smoking participants as outcomes, was estimated.

RESULTS

Smoking participants in computer-based BAI smoked fewer cigarettes per day than those assigned to assessment only at month 6 (meannet change = - 0.02; 95% confidence interval = - 0.08-0.00). After 2 years, neither in-person- nor computer-based BAI significantly changed smoking status or number of cigarettes per day in comparison to assessment only or to each other (ps ≥ 0.23).

CONCLUSIONS

While computer-based BAI also resulted in short-term reductions of number of cigarettes in smoking participants, none of the two BAIs were sufficient to evoke spill-over effects on tobacco smoking over 2 years. For long-term smoking cessation effects, multibehavioural interventions simultaneously targeting tobacco smoking along with at-risk alcohol use may be more effective.

TRIAL REGISTRATION NUMBER

NCT01291693.

Patient motivation and preferences in changing co-occurring health risk behaviors in general hospital patients

OBJECTIVES

More than 60% of general hospital patients report ≥ 2 health risk behaviors (HRBs), i.e. tobacco smoking, at-risk alcohol use, unhealthy diet, and/or insufficient physical activity. This study investigates a) the association between numbers of HRBs and motivation to change, b) patient preferences for receiving feedback on HRBs, and c) patients' expected gain in quality of life if behavior change made.

METHODS

In 2020/2021, 256 18-64-year-old general hospital patients (72.1% of eligibles) reported on their motivation to change each of their HRBs. Associations between HRB number and motivation were assessed using multivariate linear regressions. Participants ranked HRBs concerning their interest in receiving feedback and concerning their expected gain in quality of life if behavior change occurred.

RESULTS

Higher HRB number was negatively related to motivation among at-risk alcohol users (p = 0.034); 24.6% expected gain in their quality of life from behavior change. Participants overall appeared more favorable to feedback about vegetable/fruit intake and physical activity.

CONCLUSIONS

Unhealthier lifestyle may be accompanied by decreased motivation to change in at-risk alcohol users. In case of co-occurring HRBs, asking patients for expected gain in quality of life may help guiding intervention target.

PRACTICE IMPLICATIONS

Relying on patient selection only, may often leave substance-use unaddressed.

Investigating the Association Between the Co-Occurrence of Behavioral Health Risk Factors and Sick Days in General Hospital Patients

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.

Proactive automatised lifestyle intervention (PAL) in general hospital patients: study protocol of a single-group trial

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 NUMBER

NCT05365269.

Social Equity in the Efficacy of Computer-Based and In-Person Brief Alcohol Interventions Among General Hospital Patients With At-Risk Alcohol Use: A Randomized Controlled Trial

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.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01291693; https://clinicaltrials.gov/ct2/show/NCT01291693.

Effects of a brief alcohol intervention addressing the full spectrum of drinking in an adult general population sample: a randomized controlled trial

BACKGROUND AND AIMS

Evidence for efficacy of brief alcohol interventions (BAIs) is mainly limited to primary care and at-risk drinkers. The aim was to test the efficacy of a BAI addressing the full spectrum of alcohol use in a general population sample and across alcohol risk groups.

DESIGN

Two-parallel-group randomized controlled trial (allocation ratio 1:1) with post-baseline assessments at months 3, 6 and 12.

SETTING

One municipal registry office in Germany responsible for registration, passport and vehicle admission issues.

PARTICIPANTS

A total of 1646 proactively recruited 18-64-year-old adults with past year alcohol use (56% women, 66% low-risk drinkers) were randomized to intervention (n = 815) or control (n = 831).

INTERVENTION AND COMPARATOR

The intervention consisted of assessment plus computer-generated individualized feedback letters at baseline and months 3 and 6. Comparator was assessment only.

MEASUREMENTS

Primary outcome was change in the self-reported number of drinks/week from baseline to 12 months. Changes at 3 and 6 months were secondary outcomes. Moderator was alcohol risk group (low-risk versus at-risk drinking) according to the Alcohol Use Disorders Identification Test-Consumption, with scores from 1-3 (women) and from 1-4 (men) indicating low-risk drinking.

FINDINGS

For the whole sample, significant group differences were observed neither at 12-month follow-up [incidence rate ratio (IRR) = 1.01, 95% confidence interval (CI) = 0.87-1.17, Bayes factor (BE) = 0.52] nor at previous assessments (month 3: IRR = 1.01, 95% CI = 0.92-1.12, BE = 0.41; month 6: IRR = 0.93, 95% CI = 0.81-1.07, BE = 1.10). Moderator analyses revealed that low-risk drinkers were more likely to benefit from BAI only at month 6 than at-risk drinkers (IRR = 0.77, 95% CI = 0.70-0.86).

CONCLUSIONS

In a randomized controlled trial, there was no clear evidence for efficacy of a computer-based brief alcohol intervention in a general population sample, but there was some evidence of medium-term benefits in the large but understudied group of low-risk drinkers.