Evaluating the effectiveness of a mobile app-based self-guided psychological interventions to reduce relapse in substance use disorder: protocol for a randomized controlled trial.

Background: Substance Use Disorder (SUD) persists as a significant public health challenge worldwide, with an estimated prevalence of approximately 10-15% across the global populace. This condition is characterized by a notably high risk of lapses and relapses, even subsequent to treatment interventions. Mobile health interventions, owing to their widespread accessibility, emerge as a promising approach to diminish the risk of relapse post-treatment and to broaden the scope of care, especially in regions with a scarcity of trained medical professionals. Method: This study is designed to assess the effectiveness of mobile interventions in mitigating cravings and preventing lapses among individuals diagnosed with SUD. Employing a two-armed, randomized controlled trial framework, the study will evaluate a self-administered psychological intervention delivered through a mobile application, Nalogometr 2.0. Over a period of three months, participants will engage with intervention modules that primarily incorporate mindfulness techniques and Cognitive Behavioral Therapy (CBT) principles. Ecological Momentary Assessment (EMA) will be utilized to gather longitudinal data on a range of variables that are indicative of craving intensity and the risk of lapse. In addition to this, a monthly-administered battery of questionnaires will be employed to gauge the severity of substance dependence, as well as to measure levels of anxiety, depression, and overall life satisfaction. Results: Results will be submitted for publication in peer-reviewed journals. Clinical trial registration: https://clinicaltrials.gov/, identifier [NCT05730504].

Cannabidiol usage, efficacy, and side effects: analyzing the impact of health conditions, medications, and cannabis use in a cross-sectional online pilot study.

Background: Products containing cannabidiol (CBD) are attracting attention because of their potential therapeutic benefits and positive impacts on well-being and mental health. Although additional research is needed to understand their effectiveness in treating mental disorders, cross-sectional studies may help identify the factors influencing CBD use patterns. This study examined the impact of variables such as health status, medication use, medical supervision, gender, age, and cannabis use on CBD consumption patterns. Materials and methods: A self-selected sample (n =267) of current or former CBD users was recruited via social media and participated in an online survey designed to collect data on basic demographics, health status, cannabis use, and CBD usage patterns. Results: The sample (n = 267) consisted of 68.5% women with an average age of 30.21 years, of which 25.8% reported diagnosed psychiatric disorders and 49.4% reported cannabis use. The top five reasons for using CBD were self-reported stress (65.3%), sleep problems (51.7%), overall improvement in well-being (52.5%), improved mood (44.9%), and anxiety relief (40.9%). Our findings suggest that individuals with psychiatric disorders and those taking psychotropic medications are more likely to use CBD to relieve stress and anxiety. Overall, nearly 70% of the individuals found CBD products to be effective. Sublingual administration was more popular among non-cannabis users, while cannabis users preferred smoking and vaping to CBD administration. Conclusion: Our results indicate that individuals using CBD for health and wellness reasons believe that it has potential health benefits. Further research using rigorous longitudinal designs is needed to delve deeper into the effectiveness of low-dose CBD and to better understand the therapeutic potential of CBD.

Evaluating the effectiveness of mobile app-based self-guided psychological intervention to reduce craving and lapse risk in problematic substance use and behaviors: Protocol for a randomized control trial in the general population.

Background: The prevalence of substance and behavioral addiction is estimated between 10 and 15% of the global population and remains a severe public health concern. Moreover, addiction treatment has several barriers, such as a lack of access to professional treatment or stigmatization. Mobile health interventions emerge as a promising solution. Methods: This two-armed randomized controlled trial (RCT) aims to assess the efficacy of a mobile app-based self-guided psychological intervention delivered via a smartphone app (Nalogometr) in reducing craving and lapse risk in problematic behaviors and substance use compared to a control condition. Participant recruitment and data collection will start in June 2022 and end in September 2022. Due to the nature of the study, i.e., a nationwide study of problematic substance use and behaviors, we will aim to recruit all individuals willing to participate. The four-week intervention condition includes short-term and long-term modules based mainly on mindfulness and cognitive behavioral therapy. Longitudinal data on several variables related to craving and lapse risk are collected daily using ecological momentary assessment (EMA). The primary outcomes of interest will be the self-reported number of lapses and craving level in daily EMA. Moreover, a questionnaire battery assessment is administered at baseline in the first week following onboarding, after five weeks, and after six months. The secondary outcome measures will include the severity of problematic substance use or behaviors, anxiety and depression, and life satisfaction. Results: Results will be submitted for publication in peer-reviewed journals. Clinical trial registration: [https://clinicaltrials.gov/], identifier [NCT054 34,429].

Who Is at Risk of Developing Cannabis Dependence? Findings From an Extensive Online Study on Cannabis Users.

OBJECTIVES: Although frequency of cannabis use is considered to be the strongest risk factor for developing cannabis dependence, only up to half of daily users become dependent. In this study, we explored an array of risk factors and moderators of cannabis dependence symptoms from the International Classification of Diseases, Tenth Edition endorsed by participants. METHODS: A sample of 1,635 cannabis users completed an Internet survey consisting of measures of cannabis and other drug use. Multiple linear regression with a backward elimination method was employed to identify predictors of cannabis dependence symptoms. After that, a series of hierarchical multiple regression analyses were performed to test the predictive validity of the interactions between frequency of cannabis use and other predictors. RESULTS: Frequency of cannabis use appeared to be the strongest predictor of developing cannabis dependence symptoms; other significant predictors of cannabis dependence symptoms were substance-dependency-related treatment seeking, mental health problems in the family and pattern of substance use. Duration of cannabis use, relationship status, and drug use history in the family were identified as significant moderators of the relationship between frequency of cannabis use and the number of cannabis dependence symptoms. CONCLUSIONS: This study confirms that the frequency of cannabis use is the strongest predictor of cannabis dependence symptoms but this relationship is significantly moderated by three abovementioned factors.

Theta and Alpha Oscillatory Activity During Working Memory Maintenance in Long-Term Cannabis Users: The Importance of the Polydrug Use Context.

Background: Impairments in various subdomains of memory have been associated with chronic cannabis use, but less is known about their neural underpinnings, especially in the domain of the brain's oscillatory activity. Aims: To investigate neural oscillatory activity supporting working memory (WM) in regular cannabis users and non-using controls. We focused our analyses on frontal midline theta and posterior alpha asymmetry as oscillatory fingerprints for the WM's maintenance process. Methods: 30 non-using controls (CG) and 57 regular cannabis users-27 exclusive cannabis users (CU) and 30 polydrug cannabis users (PU) completed a Sternberg modified WM task with a concurrent electroencephalography recording. Theta, alpha and beta frequency bands were examined during WM maintenance. Results: When compared to non-using controls, the PU group displayed increased frontal midline theta (FMT) power during WM maintenance, which was positively correlated with RT. The posterior alpha asymmetry during the maintenance phase, on the other hand, was negatively correlated with RT in the CU group. WM performance did not differ between groups. Conclusions: Both groups of cannabis users (CU and PU), when compared to the control group, displayed differences in oscillatory activity during WM maintenance, unique for each group (in CU posterior alpha and in PU FMT correlated with performance). We interpret those differences as a reflection of compensatory strategies, as there were no differences between groups in task performance. Understanding the psychophysiological processes in regular cannabis users may provide insight on how chronic use may affect neural networks underlying cognitive processes, however, a polydrug use context (i.e., combining cannabis with other illegal substances) seems to be an important factor.

Psychophysiological, but Not Behavioral, Indicator of Working Memory Capacity Predicts Video Game Proficiency.

Visual working memory (VWM) is the ability to actively maintain visual information over short periods of time and is strongly related to global fluid intelligence and overall cognitive ability. In our study, we used two indices of visual working memory capacity: the behavioral estimate of capacity (K) and contralateral delay activity (CDA) in order to check whether training in a Real-Time Strategy (RTS) video game StarCraft II can influence the VWM capacity measured by the change detection task. We also asked a question whether individual differences in behavioral and psychophysiological indices of VWM can predict the effectiveness of video game training. Sixty-two participants (non-players) were recruited to the experiment. Participants were randomly assigned to either experimental (Variable environment), active control (Fixed environment), and passive control groups. Experimental and active control groups differed in the type of training received. Training consisted of 30 h of playing the StarCraft II game. Participants took part in two EEG sessions (pre- and post-training) during which they performed the VWM task. Our results showed that working memory capacity (K calculated according to Pashler's formula) increases after training in both experimental groups, but not in a control group. We have also found a correlation between average visual working memory capacity (calculated as K) and mean CDA amplitude no matter which group we are looking at. And, last but not least, we have found that we can predict the amount of improvement in the RTS video game by looking at the psychophysiological indices (CDA amplitude) recorded at baseline (before training), but only in the experimental group. We think that the strength of the psychophysiological indicator of VWM capacity might be a marker of the future success in video game acquisition.

Not Just a Pot: Visual Episodic Memory in Cannabis Users and Polydrug Cannabis Users: ROC and ERP Preliminary Investigation.

Background While research has consistently identified an association between long-term cannabis use and memory impairments, few studies have examined this relationship in a polydrug context (i.e., when combining cannabis with other substances). Aims: In this preliminary study, we used event-related potentials to examine the recognition process in a visual episodic memory task in cannabis users (CU) and cannabis polydrug users (PU). We hypothesized that CU and PU will have both-behavioral and psychophysiological-indicators of memory processes affected, compared to matched non-using controls with the PU expressing more severe changes. Methods 29 non-using controls (CG), 24 CU and 27 PU were enrolled into the study. All participants completed a visual learning recognition task while brain electrical activity was recorded. Event-related potentials were calculated for familiar (old) and new images from a signal recorded during a subsequent recognition test. We used receiver operating characteristic curves for behavioral data analysis. Results The groups did not differ in memory performance based on receiver operating characteristic method in accuracy and discriminability indicators nor mean reaction times for old/new images. The frontal old/new effect expected from prior research was observed for all participants, while a parietal old/new effect was not observed. While, the significant differences in the late parietal component (LPC) amplitude was observed between CG and PU but not between CG and CU nor CU and PU. Linear regression analysis was used to examine the mean amplitude of the LPC component as a predictor of memory performance accuracy indicator. LPC amplitude predicts recognition accuracy only in the CG. Conclusion The results showed alterations in recognition memory processing in CU and PU groups compared to CG, which were not manifested on the behavioral level, and were the most prominent in cannabis polydrug users. We interpret it as a manifestation of the cumulative effect of multiple drug usage in the PU group.