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Background: Users of new psychoactive substances including 4-fluoroamphetamine (4-FA/4-FMP) frequently share their experiences or opinions in online drug forums. We have tested the potential of computerised analysis of drug users' forum posts for monitoring and early detection of trends. Specifically, we tested whether changes in the volume of 4-FA related posts and sentiments expressed in those posts can be observed around the time 4-FA was increasingly reported by Dutch drug monitoring sources (2012-2017).Methods: Opening posts from two popular Dutch internet-based drug discussion forums, written between January 1 st, 2012 and January 1 st, 2018 were scraped: Portions of the forum posts about 4-FA were collected. To contrast 4-FA findings against other categories of forum posts, we also collected posts on two other substances (ecstasy and cocaine) and posts not related to a specific substance. Sentiments expressed in these posts were inferred using text recognition software, and analysed for trends using linear mixed modelling.Results: The number of 4-FA posts increased between 2012 and 2015: 76 posts in 2012, 138 in 2013, 322 in 2014, 323 in 2015, and decreased thereafter: 264 in 2016 and 135 in 2017; X2(5) = 271.8, p < .001. Over time, a decrease in positive sentiment towards 4-FA can be observed starting in 2015, compared to the period before 2015, coinciding with more news searches and reports on adverse events related to 4-FA use. Linear mixed modelling analysis confirmed a significantly higher sentiment score in 2015 compared to 2017 for 4-FA, B = 0.062; SE = 0.023; t(1252) = 2.70; p = 0.007, but not for posts on other substances.Conclusion: Changes in the volume and sentiments of forum posts coincided with news media exposure related to 4-FA and with trends observed by established drug monitoring sources. Hence, internet forum monitoring facilitates early discovery of trends in the popularity, prevalence and adverse events related to new psychoactive substances. [ABSTRACT FROM AUTHOR]

Introduction: In this study, penalized imputation (PI), a common approach to handle missing smoking status data and sometimes referred to as "missing=smoking," is compared with other missing data approaches using data from internet-based smoking cessation trials. Two hypotheses were tested: (1) PI leads to more conservative effect estimates than complete observations analysis; and (2) PI and multiple imputation (MI) lead to similar effect estimates under balanced (equal missingness proportions among the trial arms) and unbalanced missingness.Methods: First, the outcomes of 22 trials included in a recent Cochrane review on internet-based smoking cessation interventions were reanalyzed using only the complete observations, and after applying PI. Second, in a simulation study outcomes under PI, complete observations analysis, and two types of MI were compared. For this purpose, individual patient data from one of the Cochrane review trials were used. Results of the missing data approaches were compared with reference data without missing observations, upon which balanced and unbalanced missingness scenarios were imposed.Results: In the reanalysis of 22 trials, relative risks (RR = 1.15 [1.00; 1.33]) after PI were nearly identical to those under complete observations analysis (RR = 1.14 [0.98; 1.32]). In the simulation study, PI was the only approach that led to deviations from the reference data beyond its 95% confidence interval.Conclusions: Analyses after PI led to pooled results equivalent to complete observations analyses. PI also led to significant deviations from the reference in the simulation studies. PI biases the reported effects of interventions, favoring the condition with the lowest proportion of missingness. Therefore, more sophisticated missing data approaches than PI should be applied. [ABSTRACT FROM AUTHOR]

Background: Depression and harmful alcohol use are two of the top five leading causes of years of life lost to disability in high-income countries. Integrated treatment targeting both at the same time is often considered more complicated and difficult and, therefore, more expensive. Consequently, integrated internet-based interventions could be a valuable addition to traditional care.Methods: A three-arm randomized controlled trial was conducted comparing the effectiveness of (1) an integrated, minimal-guidance, adherence-focused self-help intervention designed to reduce both alcohol use and depression symptoms (AFGE-AD); (2) a similar intervention designed to reduce alcohol use only (AFGE-AO), and (3) internet access as usual (IAU) as a control condition, in at least moderately depressed alcohol misusers from February 2016-March 2020. We recruited 689 alcohol misusers (51.6 % males, mean age = 42.8 years) with at least moderate depression symptoms not otherwise in treatment from the general population. Six months after baseline, 288 subjects (41.8 %) were reachable for the final assessment.Results: All interventions yielded reduced alcohol-use after six months (AFGE-AD: -16.6; AFGE-AO: -19.8; IAU: -13.2). Those who undertook active-interventions reported significantly fewer standard drinks than controls (AFGE-AD: p = .048, d=0.10; AFGE-AO: p = .004, d=0.20). The two active-intervention groups also reported significantly less severe depression symptoms than controls (AFGE-AD: p = .006, d=0.41; AFGE-AO: p = .008, d=0.43). Testing revealed noninferiority between the two interventions.Conclusions: This study documented sustained effectiveness of the first integrated, fully internet-based self-help intervention developed for the reduction of both alcohol use and depression symptoms in at least moderately depressed adult alcohol misusers recruited from the general population. [ABSTRACT FROM AUTHOR]