The effect of e-mental health interventions on academic performance in university and college students:A meta-analysis of randomized controlled trials

Background: Mental health symptoms are common among college and university students and these can affect their academic performance. E-mental health interventions have proven effective in addressing mental health complaints but their effect on academic performance has not been synthesized yet. Objectives: To synthesize the evidence from randomized controlled trials for the effectiveness of e-mental health interventions on academic performance in college and university students compared to inactive controls. Data sources and eligibility criteria: We searched six databases (PubMed, Cochrane library, CINAHL, ERIC, PsycINFO, Web of Science) during the period January 2000 until September 2019 for randomized controlled trials that reported on e-mental health interventions (guided or unguided) for college and university students and measured academic performance (e.g. grade point average). Study appraisal and synthesis methods: Study and participant characteristics and the academic performance measures at post-intervention were extracted. The latter were pooled and Hedges' g was calculated as the effect size. Heterogeneity and publication bias were investigated. Results: Six studies containing 2428 participants were included in the meta-analysis. These focussed on either mood and anxiety or alcohol and tobacco use. The pooling of data resulted in a small but non-significant effect of g = 0.26 (95% CI, −0.00, 0.52; p = .05) on academic performance, favouring e-mental health interventions over inactive controls. Interventions had positive effects on depression (g = −0.24) and anxiety (g = −0.2). Heterogeneity was high. Discussion: Despite the small and non-significant effect, our meta-analysis points to a promising direction for the effectiveness of e-mental health interventions on academic performance. Yet, these results must be interpreted with caution, as heterogeneity was high and few studies on the effectiveness of e-mental health interventions for students reported academic performance measures

Effectiveness of a web-based self-help tool to reduce problem gambling: A randomized controlled trial.

Problem gambling constitutes a public health concern associated with psychopathological comorbidity, substance use, and financial difficulties. Most individuals with gambling problems avoid counseling services due to perceived stigma and their preference for self-reliance. Treatment accessibility could be improved through web-based interventions. We recruited 360 individuals with gambling problems and randomized them to a web-based intervention (n = 185) or an active control group consisting of a self-help manual for problem gambling (n = 175). The primary outcome was the number of days of gambling in the last 30 days. Secondary outcomes included money spent in the last 30 days, time gambling in the last 7 days, gambling-related problems, consumption of alcohol and cigarettes, and psychopathological comorbidity measured at posttreatment and 6-month follow-up. The primary outcome decreased significantly for both groups, with no significant difference between the groups. There were significant group × time interactions according to the Gambling Symptom Assessment Scale (F = 8.83, p <0 .001), the Problem Gambling Severity Index (F = 3.54, p = 0.030), for cigarettes smoked in the last 7 days (F = 26.68, p < 0.001), the Patient Health Questionnaire-9 (F = 19.41, p <0 .001), and the Generalized Anxiety Disorder-7 (F = 41.09, p <0 .001) favoring the intervention group. We experienced an overall high dropout rate (76%). Win Back Control seems to be an effective low-threshold treatment option for individuals with gambling problems that might otherwise be unapproachable for outpatient treatment services. Nevertheless, the high dropout rate should be considered when interpreting the study results, as they may have introduced a degree of variability

Internet interventions for adult illicit substance users: a meta-analysis

BACKGROUND AND AIMS: Research has shown that internet interventions can be effective for dependent users of various substances. However, less is known about the effects of these interventions on users of opioids, cocaine and amphetamines than for other substances. We aimed to investigate the effectiveness of internet interventions in decreasing the usage of these types of substances. METHODS: We conducted a systematic literature search in the databases of PubMed, PsycINFO, Embase and the Cochrane Library to identify randomized controlled trials examining the effectiveness of internet interventions compared with control conditions in reducing the use of opioids, cocaine and amphetamines. No setting restrictions were applied. The risk of bias of the included studies was examined according to the Cochrane Risk of Bias assessment tool. The primary outcome was substance use reduction assessed through toxicology screening, self-report or both at post-treatment and at the follow-up assessment. RESULTS: Seventeen studies with 2836 adult illicit substance users were included. The risk of bias varied across the included studies. Internet interventions decreased significantly opioid [four studies, n = 606, g = 0.36; 95% confidence interval (CI) = 0.20-0.53, P < 0.001] and any illicit substance use (nine studies, n = 1749, g = 0.35; 95% CI = 0.24-0.45, P < 0.001) at post-treatment. Conversely, the effect of internet intervention for stimulant users was small and non-significant (four studies, n = 481, P = 0.164). Overall, internet interventions decreased substance significantly use at post-treatment (17 studies, n = 2836, g = 0.31; 95% CI = 0.23-0.39, P < 0.001) and at the follow-up assessments (nine studies, n = 1906, g = 0.22; 95% CI = 0.07-0.37; P = 0.003). CONCLUSIONS: Internet interventions demonstrate small but significant effects in decreasing substance use among various target populations at post-treatment and at the follow-up assessment. However, given the small number of available studies for certain substances, the findings should be interpreted with caution

A mobile intervention to promote low-risk drinking habits in young adults: Protocol for a randomized controlled trial

© 2021 JMIR Publications Inc. All rights reserved.Background: Young adults' drinking habits commonly exceed recommendations for low-risk drinking, which may have a negative effect on their mental, social, and physical health. As smartphones are highly accessible to young adults, mobile apps could be used to support young adults to develop low-risk drinking habits and improve their general health. Objective: The objective of this study is to evaluate the effectiveness of Boozebuster, a self-guided mobile app based on healthy lifestyle-related components that aim to develop and maintain low-risk drinking habits among young adults. Methods: This two-arm, parallel-group randomized controlled trial will investigate whether a 6-week self-guided mobile intervention (Boozebuster) targeting drinking behavior is more effective than a minimal intervention consisting of an educational website on alcohol use and its consequences for young adults. We will recruit 506 young adults (aged 18-30 years) from the Netherlands via an open recruitment strategy by using an open access website. All outcomes will be self-assessed through questionnaires. The primary outcome is the quantity and frequency of alcohol consumption in standard drinks (10 g ethanol per standard drink) per month (timeline follow-back [TLFB]). Secondary outcomes include binge-drinking sessions per month, alcohol-related problem severity (Rutgers Alcohol Problem Index), cannabis use frequency and quantity in grams (TLFB), depressive symptoms (Center for Epidemiological Studies Depression Scale), perceived stress (Perceived Stress Scale), engagement (Twente Engagement with eHealth Technologies Scale), readiness to change (Readiness to Change Questionnaire), mental well-being (Warwick-Edinburgh Mental Wellbeing Scale), trauma and COVID-19-related trauma (Short-Form Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, 5th Edition), impulsivity (Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency Impulsive Behavior Scale), study or work performance (Individual Work Performance Questionnaire), and treatment adherence. Baseline (T0), 6-week postbaseline (T1), and 3-month postbaseline (T2) assessments will be conducted and analyzed on the basis of the intention-to-treat principle using multilevel mixed modeling analyses. Results: Recruitment began in September 2020. We received 933 registrations via our study information website; 506 participants have completed the T0 assessment, 336 participants have completed the T1 assessment, and 308 participants have completed the T2 assessment as of May 2021. The study is still in progress, and results will be reported in 2021 and 2022. Conclusions: Self-guided mobile interventions based on a lifestyle approach might be an attractive approach for young adults due to their preference on self-reliance, healthy living, and increased perceived anonymity. Such interventions are yet understudied, and it is known that interventions addressing solely problem drinking are less appealing to young adults. We hypothesize that the Boozebuster mobile app will effectively reduce drinking levels compared to an alcohol educational website (control condition). If effective, our intervention could be an inexpensive and scalable public health intervention to improve drinking habits in young adults

The effectiveness of a mobile intervention to reduce young adults’ alcohol consumption to not exceed low-risk drinking guidelines

2022 Schulte, Boumparis, Kleiboer, Wind, Olff, Huizink and Riper.Background: Young adults’ drinking habits often exceed low-risk drinking guidelines. As young adults show increased access, use, and interest in personalized content related to physical and mental well-being, mobile applications might be a suitable tool to reach this target group. This study investigates the effectiveness of “Boozebuster”, a self-guided mobile application incorporating various therapeutic principles to reduce young adults’ alcohol consumption to not exceeding low-risk drinking guideline levels, compared to an educational website condition. Method: Young adults aged 18–30 wanting to reduce their alcohol consumption entered a two-arm, parallel-group RCT. There were no minimum drinking severity inclusion criteria. Primary outcomes included alcohol consumption quantity and frequency. Secondary outcomes included binge drinking frequency and alcohol-related problem severity. Baseline, 6-week postbaseline, and 3-month post-baseline assessments were analyzed using linear mixed model analyses. Sex, treatment adherence, experienced engagement and motivation to change alcohol use behavior were investigated as moderators. Sub-group analyses contained problem drinkers and binge drinkers. Results: 503 participants were randomized to the intervention or control condition. Results showed no intervention effects on primary or secondary outcomes compared to the control group. Both groups showed within-group reductions on all outcomes. Sub-group analyses in problem drinkers or binge drinkers showed similar results. Motivation to change drinking behavior and experienced engagement with the application significantly moderated the intervention effect regarding the quantity or frequency of alcohol consumption, respectively. Exploratory analyses showed that participants who indicated they wanted to change their drinking patterns during the initial PNF/MI module showed a significantly greater reduction in drinking quantity compared to those who indicated not wanting to change their drinking patterns. Conclusion: The intervention group did not show a greater reduction in alcohol-related outcomes compared to the control group, but both groups showed a similar decrease. Potential explanations include similar effectiveness of both condition due to using a minimal active control in participants predominantly in the action stage of motivation to change. Future research should further explore the effectiveness of using mobile application to reduce young adults’ drinking behavior to not exceed low-risk drinking guideline levels and identify factors that motivate participants to engage with such an intervention