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Background: Social distancing measures during the COVID‐19 pandemic forced an abrupt transformation of treatment delivery for mental health care. In mid‐March 2020, nearly all in‐person contact was replaced with video conferencing. The pandemic thus offered a natural experiment and a unique opportunity to conduct an observational study of whether alcohol use disorder treatment through video conferencing is non‐inferior to in‐person treatment. Methods: In a large urban substance use disorder treatment center in the Netherlands, treatment evaluation is routine practice. Outcome data are regularly collected to support shared decision making and monitor patient progress. For this study, pre‐test and post‐test data on alcohol use (Measurements in the Addictions for Triage and Evaluation), psychopathology (Depression Anxiety Stress Scales), and quality of life (Manchester Short Assessment of Quality of Life) were used to compare outcomes of cognitive behavioral therapy treatment for three cohorts: patients who received treatment for a primary alcohol use disorder performed prior to (n = 628), partially during (n = 557), and entirely during (n = 653) the COVID‐19 lockdown. Results: Outcome was similar across the three cohorts: No inferior outcomes were found for treatments that were conducted predominantly through video conferencing during lockdown or treatments that started in‐person, but were continued through video conferencing, compared to in‐person treatments that were conducted prior to COVID‐19. The number of drop‐outs were also similar between cohorts. However, there was a difference in average treatment intensity between cohorts, with treatment partially or fully conducted during the COVID‐19 pandemic lasting longer. Conclusions: Treatment for a primary alcohol use disorder, provided partially or predominantly through video conferencing during the COVID‐19 pandemic resulted in abstinence rates and secondary outcomes similar to traditional in‐person care, in spite of the potentially negative effects of the COVID‐related lockdown measures themselves. These results from everyday clinical practice corroborate findings of randomized controlled studies and meta‐analyses in which video conferencing appeared non‐inferior to in‐person care in clinical effectiveness. [ABSTRACT FROM AUTHOR]

Aims: To test the effectiveness of a digital intervention to reduce cannabis use (ICan) with adherence‐focused guidance compared with educational cannabis information. Design: This was a single‐blind randomized controlled trial. Follow‐up clinical outcome measurements took place 3 and 6 months after randomization. Setting: The trial was conducted in the Netherlands. The intervention and guidance took place on‐line, with recruitment via Facebook/Instagram advertisement campaigns. Participants: Inclusion criteria were ≥ 18 years, cannabis use on ≥ 3 days/week, the desire to reduce/quit cannabis and using a smartphone. Participants were allocated to either ICan (n = 188) or control (n = 190) (69% male, mean age = 27.5 years). Intervention and comparator: ICan is a mobile (web‐)application based on motivational interviewing and cognitive behavioural therapy and includes three main components: screening, brief intervention (six modules) and referral to treatment. The control condition consisted of non‐interactive educational cannabis information. Measurements Primary outcome was the number of cannabis use days in the 7 days prior to the 6‐month follow‐up measurement. Secondary outcome measures at 3‐ and 6‐month follow‐up were the number of grams of cannabis used and attitudes towards seeking professional help for cannabis use related problems. Findings Intention‐to‐treat analysis showed that 6 months after randomization the mean number of cannabis use days in the past 7 days was reduced in both conditions (time P < 0.001), with no significant group × time interaction effect [ICan = 4.17 days, control = 4.31 days, Cohen's dbetween = 0.06, 95% confidence interval (CI) = −0.15, 0.26, P = 0.93]. Three months after randomization the mean number of grams used in the past 7 days was reduced in both conditions, with a significantly larger reduction in the ICan condition (P = 0.009, Cohen's dbetween = 0.15). At 6‐month follow‐up the significant group × time interaction effect was no longer present (P = 0.30). In both conditions, attitudes towards seeking professional help remained virtually unchanged over time. Conclusions: A digital intervention to reduce cannabis use (ICan) was more effective than non‐interactive educational cannabis information in reducing grams of cannabis used over 3 months, but not more effective at reducing cannabis use days at 6‐month follow‐up. Cannabis use reductions were maintained in both conditions between 3 and 6 months' follow‐up. [ABSTRACT FROM AUTHOR]

Background: Digital self-help interventions for reducing the use of alcohol tobacco and other drugs (ATOD) have generally shown positive but small effects in controlling substance use and improving the quality of life of participants. Nonetheless, low adherence rates remain a major drawback of these digital interventions, with mixed results in (prolonged) participation and outcome. To prevent non-adherence, we developed models to predict success in the early stages of an ATOD digital self-help intervention and explore the predictors associated with participant's goal achievement. Methods: We included previous and current participants from a widely used, evidence-based ATOD intervention from the Netherlands (Jellinek Digital Self-help). Participants were considered successful if they completed all intervention modules and reached their substance use goals (i.e., stop/reduce). Early dropout was defined as finishing only the first module. During model development, participants were split per substance (alcohol, tobacco, cannabis) and features were computed based on the log data of the first 3 days of intervention participation. Machine learning models were trained, validated and tested using a nested k-fold cross-validation strategy. Results: From the 32,398 participants enrolled in the study, 80% of participants did not complete the first module of the intervention and were excluded from further analysis. From the remaining participants, the percentage of success for each substance was 30% for alcohol, 22% for cannabis and 24% for tobacco. The area under the Receiver Operating Characteristic curve was the highest for the Random Forest model trained on data from the alcohol and tobacco programs (0.71 95%CI 0.69–0.73) and (0.71 95%CI 0.67–0.76), respectively, followed by cannabis (0.67 95%CI 0.59–0.75). Quitting substance use instead of moderation as an intervention goal, initial daily consumption, no substance use on the weekends as a target goal and intervention engagement were strong predictors of success. Discussion: Using log data from the first 3 days of intervention use, machine learning models showed positive results in identifying successful participants. Our results suggest the models were especially able to identify participants at risk of early dropout. Multiple variables were found to have high predictive value, which can be used to further improve the intervention. [ABSTRACT FROM AUTHOR]

Background: Smoking cessation (SC) interventions may contribute to better treatment outcomes and the general well-being of cancer survivors.Objective: This study aims to evaluate the effectiveness, cost-effectiveness, and cost-utility of a digital interactive SC intervention compared with a noninteractive web-based information brochure for cancer survivors.Methods: A health economic evaluation alongside a pragmatic 2-arm parallel-group randomized controlled trial was conducted with follow-ups at 3, 6, and 12 months. The study was conducted in the Netherlands over the internet from November 2016 to September 2019. The participants were Dutch adult smoking cancer survivors with the intention to quit smoking. In total, 165 participants were included and analyzed: 83 (50.3%) in the MyCourse group and 82 (49.7%) in the control group. In the intervention group, participants had access to a newly developed, digital, minimally guided SC intervention (MyCourse-Quit Smoking). Control group participants received a noninteractive web-based information brochure on SC. Both groups received unrestricted access to usual care. The primary outcome was self-reported 7-day smoking abstinence at the 6-month follow-up. Secondary outcomes were quality-adjusted life years gained, number of cigarettes smoked, nicotine dependence, and treatment satisfaction. For the health economic evaluation, intervention costs, health care costs, and costs stemming from productivity losses were assessed over a 12-month horizon.Results: At the 6-month follow-up, the quit rates were 28% (23/83) and 26% (21/82) in the MyCourse and control groups, respectively (odds ratio 0.47, 95% CI 0.03-7.86; P=.60). In both groups, nicotine dependence scores were reduced at 12 months, and the number of smoked cigarettes was reduced by approximately half. The number of cigarettes decreased more over time, and the MyCourse group demonstrated a significantly greater reduction at the 12-month follow-up (incidence rate ratio 0.87; 95% CI 0.76-1.00; P=.04). Intervention costs were estimated at US $193 per participant for the MyCourse group and US $74 for the control group. The mean per-participant societal costs were US $25,329 (SD US $29,137) and US $21,836 (SD US $25,792), respectively. In the cost-utility analysis, MyCourse was not preferred over the control group from a societal perspective. With smoking behavior as the outcome, the MyCourse group led to marginally better results per reduced pack-year against higher societal costs, with a mean incremental cost-effectiveness ratio of US $52,067 (95% CI US $32,515-US $81,346).Conclusions: At 6 months, there was no evidence of a differential effect on cessation rates; in both groups, approximately a quarter of the cancer survivors quit smoking and their number of cigarettes smoked was reduced by half. At 12 months, the MyCourse intervention led to a greater reduction in the number of smoked cigarettes, albeit at higher costs than for the control group. No evidence was found for a differential effect on quality-adjusted life years.Trial Registration: The Netherlands Trial Register NTR6011; https://www.trialregister.nl/trial/5434.International Registered Report Identifier (irrid): RR2-10.1186/s12885-018-4206-z. [ABSTRACT FROM AUTHOR]

Background: Alcohol moderation (AM) interventions may contribute to better treatment outcomes and the general well-being of cancer survivors.Objective: This study evaluates the effectiveness, cost-effectiveness, and cost-utility of MyCourse, a digital AM intervention, compared with a noninteractive digital information brochure for cancer survivors.Methods: A health economic evaluation alongside a pragmatic 2-arm parallel-group randomized controlled trial was conducted with follow-ups at 3, 6, and 12 months after randomization. The study was conducted on the web in the Netherlands from 2016 to 2019. Participants were adult 10-year cancer survivors drinking over the Dutch-recommended drinking guidelines (≤7 standard units [10 g of alcohol] per week) with the intention to moderate or quit drinking. Overall, 103 participants were randomized and analyzed: 53 (51.5%) in the MyCourse group and 50 (48.5%) in the control group. In the MyCourse group, participants had access to a newly developed, digital, minimally guided AM intervention, MyCourse-Moderate Drinking. The primary outcome was the self-reported number of standard drinks (10 g of ethanol) consumed in the past 7 days at the 6-month follow-up. The secondary outcome measures were alcohol-related problems as measured by the Alcohol Use Disorders Identification Test (AUDIT) and treatment satisfaction. For the health economic evaluation, health care costs, costs because of productivity losses, and intervention costs were assessed over a 12-month horizon.Results: Alcohol use at the 6-month follow-up decreased by 38% in the MyCourse group and by 33% in the control group. No difference in 7-day alcohol use was found between the groups (B=2.1, 95% CI -7.6 to 3.1; P=.22) at any of the follow-ups. AUDIT scores for alcohol-related problems decreased over time in both groups, showing no significant difference between the groups (Cohen d=0.3, 95% CI -0.1 to 0.6; P=.21). Intervention costs per participant were estimated at US $279 for the MyCourse group and US $74 for the control group. The mean societal costs were US $18,092 (SD 25,662) and US $23,496 (SD 34,327), respectively. The MyCourse group led to fewer gained quality-adjusted life years at lower societal costs in the cost-utility analysis. In the cost-effectiveness analysis, the MyCourse group led to a larger reduction in drinking units over time at lower societal costs (incremental cost-effectiveness ratio per reduced drink: US $ -1158, 95% CI -1609 to -781).Conclusions: At 6 months, alcohol use was reduced by approximately one-third in both groups, with no significant differences between the digital intervention MyCourse and a noninteractive web-based brochure. At 12 months, cost-effectiveness analyses showed that MyCourse led to a larger reduction in drinking units over time, at lower societal costs. The MyCourse group led to marginally fewer gained quality-adjusted life years, also at lower societal costs.Trial Registration: Netherlands Trial Register NTR6010; https://www.trialregister.nl/trial/5433.International Registered Report Identifier (irrid): RR2-10.1186/s12885-018-4206-z. [ABSTRACT FROM AUTHOR]

• Stress reduction did not explain reduction in smoking behavior in our sample of pregnant women. • Motivation to quit smoking moderated the intervention effect on the number of smoking days per week and number of cigarettes smoked on average on a weekly basis. • The dose–response effect of program use on smoking frequency, and smoking quantity suggests that the eHealth intervention consists of effective components. Prenatal smoking and stress are associated with adverse health effects for women themselves and are risk factors for adverse outcomes of the child. Effective interventions are needed to support women with smoking cessation and reducing stress. The aims were (1) to test the effectiveness of an 8-week eHealth intervention targeting stress reduction and smoking cessation; (2) to examine whether stress reduction mediated the intervention effect on smoking behavior; (3) to test motivation to quit as a moderator; and (4) to investigate a dose–response effect of program usage. Pregnant women were included if they were >18 years of age, < 28 weeks pregnant at recruitment, and currently smoking. In total, 156 consenting participants were randomly assigned to the intervention or active control condition. Study outcomes on smoking (yes/no, frequency, and quantity) were collected via online questionnaires at pre-intervention (baseline; t0), post-intervention (8 weeks after t0; t1), and follow up at two weeks (t2) and three months (t3) after birth. Smoking and stress reduced over the 8-week period in both conditions. The intervention effect on smoking was not mediated by stress reduction. Motivation to quit was found to moderate the intervention effect (smoking frequency and quantity) and a dose–response effect was found for program usage in the intervention for the reduction on smoking frequency and quantity. Program usage and motivation to quit are important for smoking reduction in pregnant women. Further research is needed to examine how the intervention could be improved to increase treatment effectiveness. [ABSTRACT FROM AUTHOR]