Raquel Paz Castro

Efficacy of a Web- and Text Messaging-Based Intervention to Reduce Problem Drinking in Adolescents: Results of a Cluster-Randomized Controlled Trial

Objective: To test the efficacy of a combined web- and text messaging-based intervention to reduce problem drinking in young people compared to assessment only. Method: Two-arm, parallel-group, cluster-randomized controlled trial with assessments at baseline and 6-month follow up. The automated intervention included online feedback, based on the social norms approach, and individually tailored text messages addressing social norms, outcome expectations, motivation, self-efficacy, and planning processes, provided over 3 months. The main outcome criterion was the prevalence of risky single-occasion drinking (RSOD, defined as drinking at least 5 standard drinks on a single occasion in men and 4 in women) in the past 30 days. Irrespective of alcohol consumption, 1,355 students from 80 Swiss vocational and upper secondary school classes, all of whom owned a mobile phone, were invited to participate in the study. Of these, 1,041 (76.8%) students participated in the study. Results: Based on intention-to-treat analyses, RSOD prevalence decreased by 5.9% in the intervention group and increased by 2.6% in the control group, relative to that of baseline assessment (odds ratio [OR] = 0.62, 95% confidence interval [CI] = 0.44–0.87). No significant group differences were observed for the following secondary outcomes: RSOD frequency, quantity of alcohol consumed, estimated peak blood alcohol concentration, and overestimation of peer drinking norms. Conclusions: The intervention program reduced RSOD, which is a major indicator of problem drinking in young people, effectively.

Moderators of outcome in a technology-based intervention to prevent and reduce problem drinking among adolescents

Introduction Moderators of outcome are investigated in a technology-based intervention that has been shown to effectively reduce binge drinking among adolescents. Methods Secondary data analyses were performed on socio-demographic, health-related, and socio-cognitive moderators of intervention efficacy. Students attending 80 vocational and upper secondary school classes with different levels of alcohol use were randomized to either a web- and text messaging-based intervention (n = 547) or an assessment-only control group (n = 494). Moderators of outcome were analysed across the entire sample, and separately for lower-risk and higher-risk drinkers. Results Based on an intention-to-treat analysis, we identified smoking status and educational level to moderate the intervention effectiveness across the total sample and in the lower-risk subsample, with a greater reduction in binge-drinking prevalence in smokers versus non-smokers, and in more highly-educated versus less-educated adolescents. Conclusions Technology-based interventions targeting heavy drinking might be especially effective in smokers and highly-educated adolescents. Interventions can prevent low-risk drinkers that smoke from developing a problematic alcohol use.

Efficacy of a technology-based, integrated smoking cessation and alcohol intervention for smoking cessation in adolescents: Results of a cluster-randomised controlled trial

OBJECTIVE To test the efficacy of a technology-based integrated smoking cessation and alcohol intervention versus a smoking cessation only intervention in adolescents. METHODS This was a two-arm, parallel-group, cluster-randomised controlled trial with assessments at baseline and six months follow-up. Subjects in both groups received tailored mobile phone text messages to support smoking cessation for 3months, and the option of registering for a program incorporating strategies for smoking cessation centred around a self-defined quit date. Subjects in the integrated intervention group also received tailored feedback regarding their consumption of alcohol and, for binge drinkers, tailored mobile phone text messages encouraging them to maintain their drinking within low-risk limits over a 3-month period. Primary outcome measures were the 7-day point prevalence of smoking abstinence and change in cigarette consumption. RESULTS In 360 Swiss vocational and upper secondary school classes, 2127 students who smoked tobacco regularly and owned a mobile phone were invited to participate in the study. Of these, 1471 (69.2%) participated and 6-month follow-up data were obtained for 1116 (75.9%). No significant group differences were observed for any of the primary or secondary outcomes. Moderator analyses revealed beneficial intervention effects concerning 7-day smoking abstinence in participants with higher versus lower alcohol consumption. CONCLUSIONS Overall, the integrated smoking cessation and alcohol intervention exhibited no advantages over a smoking cessation only intervention, but it might be more effective for the subgroup of adolescent smokers with higher alcohol consumption. Providing a combined smoking cessation and alcohol intervention might be recommended for adolescent smokers with higher-level alcohol consumption.

A Mobile Phone-Based Life Skills Training Program for Substance Use Prevention Among Adolescents: Pre-Post Study on the Acceptance and Potential Effectiveness of the Program, Ready4life

Background Substance use and misuse often first emerge during adolescence. Generic life skills training that is typically conducted within the school curriculum is effective at preventing the onset and escalation of substance use among adolescents. However, the dissemination of such programs is impeded by their large resource requirements in terms of personnel, money, and time. Life skills training provided via mobile phones might be a more economic and scalable approach, which additionally matches the lifestyle and communication habits of adolescents. Objective The aim of this study was to test the acceptance and initial effectiveness of an individually tailored mobile phone–based life skills training program in vocational school students. Methods The fully automated program, named ready4life, is based on social cognitive theory and addresses self-management skills, social skills, and substance use resistance skills. Program participants received up to 3 weekly text messages (short message service, SMS) over 6 months. Active program engagement was stimulated by interactive features such as quiz questions, message- and picture-contests, and integration of a friendly competition with prizes in which program users collected credits with each interaction. Generalized estimating equation (GEE) analyses were used to investigate for changes between baseline and 6-month follow-up in the following outcomes: perceived stress, self-management skills, social skills, at-risk alcohol use, tobacco smoking, and cannabis use. Results The program was tested in 118 school classes at 13 vocational schools in Switzerland. A total of 1067 students who owned a mobile phone and were not regular cigarette smokers were invited to participate in the life skills program. Of these, 877 (82.19%, 877/1067; mean age=17.4 years, standard deviation [SD]=2.7; 58.3% females) participated in the program and the associated study. A total of 43 students (4.9%, 43/877) withdrew their program participation during the intervention period. The mean number of interactive program activities that participants engaged in was 15.5 (SD 13.3) out of a total of 39 possible activities. Follow-up assessments were completed by 436 of the 877 (49.7%) participants. GEE analyses revealed decreased perceived stress (odds ratio, OR=0.93; 95% CI 0.87-0.99; P=.03) and increases in several life skills addressed between baseline and the follow-up assessment. The proportion of adolescents with at-risk alcohol use declined from 20.2% at baseline to 15.5% at follow-up (OR 0.70, 95% CI 0.53-0.93; P=.01), whereas no significant changes were obtained for tobacco (OR 0.94, 95% CI 0.65-1.36; P=.76) or cannabis use (OR 0.91, 95% CI 0.67-1.24; P=.54). Conclusions These results reveal high-level acceptance and promising effectiveness of this interventional approach, which could be easily and economically implemented. A reasonable next step would be to test the efficacy of this program within a controlled trial.

Drinking goal trajectories and their association with client characteristics and outcomes among clients in outpatient alcohol treatment

ABSTRACT Background: Drinking goal preferences could change over time in alcohol treatment and during follow up. Objectives: To examine the stability of drinking goals over time, types of drinking goal trajectory, and the associations between drinking goal trajectories and baseline client characteristics and treatment outcomes. Methods: We performed secondary analysis of a dataset from a multicenter longitudinal study on the effectiveness of outpatient alcohol treatment (n = 543). Drinking goals (abstinence, controlled drinking, nonrestricted drinking, undecided) and alcohol use were assessed at treatment admission, discharge, and 6- and 12-month follow up. Results: At admission, 32% of the subjects aimed for abstinence and 57% for controlled drinking, while 10% were undecided, and 1% did not want to restrict themselves. The proportions of clients aiming for abstinence and controlled drinking were relatively stable across the four assessments, and the proportion of clients who changed their drinking goal from abstinence to controlled drinking did not differ significantly from the number who changed in the opposite direction. Clients with abstinence-focused trajectories reported higher baseline alcohol use than those focused primarily on controlled drinking. Meanwhile, attaining nonhazardous drinking and reduced alcohol use at 12-month follow up were more likely among clients with abstinence-focused trajectories than those focused on controlled drinking. Conclusions: Since the majority of clients maintain their initially selected drinking goal, counsellors might inform them at treatment admission about the various probabilities of achieving nonhazardous drinking depending on their selected drinking goal.

Quality of life of parents of mentally-ill children: a systematic review and meta-analysis

AIMS: To examine the quality of life (QOL) of parents of children with a specific mental disorder (any age). METHODS: Relevant articles were searched using different databases. Articles were included that compared the QOL of parents with mentally-ill children to parents of healthy controls or norm values or provided the required data for this comparison. A meta-analysis was conducted to obtain an overall mean effect size estimate. Additional analyses were performed to assess publication bias and moderation. RESULTS: Twenty-six out of 10 548 articles met the pre-defined inclusion criteria. Most of these studies focused on attention-deficit/hyperactivity disorder or autism spectrum disorder, used clinical samples that mainly included males and young children and studied the QOL of mothers. The meta-analysis revealed that parents of mentally-ill children are experiencing a clinically relevant reduction in their QOL relative to parents of healthy children and norm values (g = -0.66). CONCLUSIONS: The compromised QOL of parents of mentally-ill children needs to be considered and addressed by health professionals who are in contact with them. The paper provides insights into existing research gaps and suggests improvements for subsequent work.

Efficacy of a web‐based intervention with and without guidance for employees with risky drinking: results of a three‐arm randomized controlled trial

Abstract Aims To test the efficacy of a web‐based alcohol intervention with and without guidance. Design Three parallel groups with primary end‐point after 6 weeks. Setting Open recruitment in the German working population. Participants Adults (178 males/256 females, mean age 47 years) consuming at least 21/14 weekly standard units of alcohol (SUA) and scoring ≥ 8/6 on the Alcohol Use Disorders Identification Test. Intervention Five web‐based modules including personalized normative feedback, motivational interviewing, goal setting, problem‐solving and emotion regulation during 5 weeks. One intervention group received an unguided self‐help version (n=146) and the second received additional adherence‐focused guidance by eCoaches (n=144). Controls were on a waiting list with full access to usual care (n=144). Measurements Primary outcome was weekly consumed SUA after 6 weeks. SUA after 6 months was examined as secondary outcome, next to numbers of participants drinking within the low‐risk range, and general and work‐specific mental health measures. Findings All groups showed reductions of mean weekly SUA after 6 weeks (unguided: −8.0; guided: −8.5; control: −3.2). There was no significant difference between the unguided and guided intervention (P=0.324). Participants in the combined intervention group reported significantly fewer SUA than controls [B=−4.85, 95% confidence interval (CI)=−7.02 to −2.68, P < 0.001]. The intervention groups also showed significant reductions in SUA consumption after 6 months (B=−5.72, 95% CI=−7.71 to −3.73, P < 0.001) and improvements regarding general and work‐related mental health outcomes after 6 weeks and 6 months. Conclusions A web‐based alcohol intervention, administered with or without personal guidance, significantly reduced mean weekly alcohol consumption and improved mental health and work‐related outcomes in the German working population.

Engagement within a mobile phone–based smoking cessation intervention for adolescents and its association with participant characteristics and outcomes

Background Although mobile phone–delivered smoking cessation programs are a promising way to promote smoking cessation among adolescents, little is known about how adolescents might actually use them. Objective The aim of this study was to determine adolescents’ trajectories of engagement with a mobile phone–delivered smoking cessation program over time and the associations these trajectories have with baseline characteristics and treatment outcomes. Methods We performed secondary data analysis on a dataset from a study that compared a mobile phone–delivered integrated smoking cessation and alcohol intervention with a smoking cessation only intervention for adolescents recruited in vocational and upper secondary school classes (N=1418). Throughout the 3-month intervention, participants in both intervention groups received one text message prompt per week that either assessed smoking-related target behaviors or encouraged participation in a quiz or a message contest. Sequence analyses were performed to identify engagement trajectories. Analyses were conducted to identify predictors of engagement trajectory and associations between engagement trajectories and treatment outcomes. Results Three engagement trajectories emerged: (1) stable engagement (646/1418, 45.56%), (2) decreasing engagement (501/1418, 35.33%), and (3) stable nonengagement (271/1418, 19.11%). Adolescents who were younger, had no immigrant background, perceived more benefits of quitting smoking, and reported binge drinking preceding the baseline assessment were more likely to exhibit stable engagement. Due to different reach of more engaged and less engaged participants at follow-up, three statistical models (complete-cases, last-observation-carried-forward, and multiple imputation) for the associations of engagement trajectory and smoking outcome were tested. For 7-point smoking abstinence, no association was revealed to be statistically significant over all three models. However, decreasing engagement with the program was associated over all three models, with greater reductions in daily tobacco use than nonengagement. Conclusions The majority of tobacco-smoking adolescents engaged extensively with a mobile phone–based smoking cessation program. However, not only stable engagement but also decreasing engagement with a program might be an indicator of behavioral change. Measures to avoid nonengagement among adolescents appear especially necessary for older smokers with an immigrant background who do not drink excessively. In addition, future studies should not only examine the use of specific program components but also users’ engagement trajectories to better understand the mechanisms behind behavioral change.