At-risk Users Research Articles

Systematic review: The relationship between gabapentinoids, etizolam, and drug related deaths in Scotland.

In recent years Scotland has been experiencing a disproportionally high number of drug related deaths compared to other European countries, causing significant individual, societal and economic burden. A possible cause of this is the increase in average number of substances involved in Scottish drug related deaths, as well as the changing pattern of substances involved. Opioids, cocaine, and alcohol have been consistently involved in the culture of drug use in Scotland, however recently National Records Scotland have identified that designer benzodiazepines such as etizolam, and prescription drugs such as gabapentinoids are increasingly being detected in Scottish toxicology reports. A systematic literature review following PRISMA guidelines was conducted through searching PubMed and Google Scholar to identify peer-reviewed articles published in English between 2013 and 2023 that investigated Scottish population data on gabapentinoids and etizolam to establish their contribution to the rise in Scottish drug related deaths. 18 studies were included in the review. A high use prevalence of etizolam and gabapentinoids in Scotland has been identified, with both substance-related deaths showing recent increase, marked since 2015. This pattern is replicated in the Scottish prison system. There has also been a significant increase of gabapentinoids prescriptions in Scotland. Polydrug use was identified as the most common determinant of both etizolam and gabapentinoids related adverse effects and fatality in Scotland, especially concurrent opioid use. The results indicate the literature on individual characteristics of Scottish at-risk users of gabapentinoids and etizolam is limited, however the data shows both substances are being used by older cohort, with adverse effects seen more in older women.

Inclusive Involvement of At-Risk Users in Cybersecurity Research

Inclusive Involvement of At-Risk Users in Cybersecurity Research

Attacking Connection Tracking Frameworks as used by Virtual Private Networks

VPNs (Virtual Private Networks) have become an essential privacy-enhancing technology, particularly for at-risk users like dissidents, journalists, NGOs, and others vulnerable to targeted threats. While previous research investigating VPN security has focused on cryptographic strength or traffic leakages, there remains a gap in understanding how lower-level primitives fundamental to VPN operations, like connection tracking, might undermine the security and privacy that VPNs are intended to provide. In this paper, we examine the connection tracking frameworks used in common operating systems, identifying a novel exploit primitive that we refer to as the port shadow. We use the port shadow to build four attacks against VPNs that allow an attacker to intercept and redirect encrypted traffic, de-anonymize a VPN peer, or even portscan a VPN peer behind the VPN server. We build a formal model of modern connection tracking frameworks and identify that the root cause of the port shadow lies in five shared, limited resources. Through bounded model checking, we propose and verify six mitigations in terms of enforcing process isolation. We hope our work leads to more attention on the security aspects of lower-level systems and the implications of integrating them into security-critical applications.

Problematic Internet use among adults: A longitudinal European study.

There are few cross-cultural studies utilizing longitudinal analysis to explore problematic internet use (PIU), and almost none among adults. The present follow-up study compared three waves across 12-month period every six months and observed the natural course and trajectory of PIU in a European multi-country sample of adults from 11 countries (Finland, Germany, Italy, Spain, France, Switzerland, Hungary, Poland, UK, Norway, Belgium). A total of 139 participants (45.5% females) provided data across all three waves with an average age of 26.14 years (SD = 5.92). There were longitudinal effects in PIU, with statistical differences between at-risk users compared to healthy users in Waves 1 and 2, and Waves 1 and 3. The analyses of variance showed a longitudinal effect of waves on the PIU symptoms. PIU was significantly affected by time and type of user, with those classed as at-risk having higher scores than healthy users, although PIU decreased over time. In addition, the type of PIU detected in adults contained mild addictive symptoms. In conclusion, this study demonstrated that PIU was generally low among European adult population and tended to decrease over the one-year period, what contrasts with adolescent population findings.

Attitudes of nurses and nurse managers towards violence risk assessment and management: A cross-sectional study in psychiatric inpatient settings.

Workplace violence is a significant challenge in psychiatric hospital care. Some existing practices of violence risk assessment and management are based on nurses' intuition and clinical experience instead of structured tools. Nurses and nurse managers consider violence risk assessment and management their responsibility. Still, nurses and nurse managers have mixed attitudes towards the use of validated risk assessment tools. The attitudes towards service users' positive risk-taking in nurses and nurse managers vary, with some nurses and nurse managers supporting its importance. Change in nurses' and nurse managers' attitudes towards risk assessment tools is required before their implementation into practice. More profound change in practices towards recovery-oriented care is required also in risk assessment. INTRODUCTION: Workplace violence is a prevalent issue in psychiatric inpatient care. Prevention efforts require the identification of at-risk service users using validated violence risk assessment tools. The shift in violence prevention emphasises preventive measures and collaborative risk assessment together with service users. Nurses have a central role in this process. Therefore, their attitudes are crucial when implementing evidence-based methods. To assess the attitudes of nurses and nurse managers towards violence risk assessment and management. A cross-sectional online survey in Finnish psychiatric inpatient care. Data analysis was conducted with statistical methods. The STROBE guideline was used in reporting. Nurses (n = 142) valued risk assessment and felt that it was their responsibility. Attitudes towards service users' risk-taking as part of their recovery varied. Nurses had mixed attitudes regarding the effectiveness of risk assessment tools. Older participants and nurse managers had more positive attitudes towards risk assessment tools. The study findings highlight a feeling of responsibility of nurses towards violence risk assessment and at the same time their preference towards their own clinical judgement. Understanding nurses' attitudes is crucial in training and implementation processes to address concerns, provide support and enhance positive attitudes.

Factors Associated with PrEP Persistence and Loss of Follow-Up: A 5-Year Historic Cohort.

HIV Pre-Exposure Prophylaxis (PrEP) has been used in France since 2016. Its effectiveness is no longer to be demonstrated. However, follow-up and adherence remain the main pitfalls. The main objective of this study was to identify factors associated with persistence or loss of PrEP follow-up. An historic cohort of PrEP users was compiled from the database of consultations in the Indre-et-Loire dedicated sexual health centers (CeGIDD) from June 2016 to June 2021. Kaplan-Meier curves were performed to compare the group of persistent PrEP users to the discontinuation group. Factors associated with PrEP discontinuation were identified using Cox modelling, considering time-dependent variables. Final variables included in the model were selected based on the Akaike Information Criterion (AIC) and clinical relevance. Over the period, 568 PrEP users were included in the cohort. Median follow-up was 2.3 years. A quarter of users were lost to follow-up within 3 months after PrEP initiation. Sexual risk reduction AIDS community-based support (HR = 0.65[0.42;0.99]), being in a couple (HR = 0.51[0.38;0.68]), and history of syphilis (HR = 0.57[0.40;0.81]) were significantly associated with persistence of follow-up. Remote consultations (HR = 2.74[1.63;4.61]), chemsex practices (HR = 2.01[1.29;3.14]), and side effects (HR=1.72[1.03;2.88]) were significantly associated with a loss of follow-up. These results suggest that more sexual risk reduction AIDS community-based counseling could be a key, necessary for supporting PrEP users in their follow-up pathway. Indeed, AIDS community-based support could be used to build a basis for developing safe pathways. Remote consultations could represent a response to the issue of access to PrEP. To create a significant impact on global HIV incidence, the PrEP offer must be extended, and at-risk PrEP users supported to maintain PrEP use.

Evaluation of the Effectiveness of Suicide.ca, Quebec's Digital Suicide Prevention Strategy Platform: Cross-Sectional Descriptive Study.

In 2017, the Quebec government assigned the Association québécoise de prévention du suicide (AQPS) to develop a digital suicide prevention strategy (DSPS). The AQPS responded by creating a centralized website that provides information on suicide and mental health, identifies at-risk individuals on the internet, and offers direct crisis intervention support via chat and text. This study aims to evaluate the effectiveness of suicide.ca, Quebec's DSPS platform. This study used a cross-sectional descriptive design. The study population comprised internet users from Quebec, Canada, who visited the suicide.ca platform between October 2020 and October 2021. Various data sources, such as Google Analytics, Firebase Console, and Customer Relation Management data, were analyzed to document the use of the platform. To understand the profile of suicide.ca users, frequency analyses were conducted using data from the self-assessment module questionnaires, the intervention service's triage questionnaire, and the counselors' intervention reports. The effectiveness of the platform's promotional activities on social media was assessed by examining traffic peaks. Google Analytics was used to evaluate the effectiveness of AQPS' strategy for identifying at-risk internet users. The impact of the intervention service was evaluated through an analysis of counselors' intervention reports and postintervention survey results. The platform received traffic from a diverse range of sources, with promotional efforts on social media directly contributing to the increased traffic. The requirement of a user account posed a barrier to the use of the mobile app, and a triage question that involved personal information led to a substantial number of dropouts during the intervention service triage. AdWords campaigns and fact sheets addressing suicide risk factors played a crucial role in driving traffic to the platform. With regard to the profile of suicide.ca users, the findings revealed that the platform engaged individuals with diverse levels of suicidal risk. Notably, users of the chat service displayed a higher suicide risk than those who used the self-assessment module. Crisis chat counselors reported a positive impact on approximately half of the contacts, and overall, intervention service users expressed satisfaction with the support they received. A centralized digital platform can be used to implement a DSPS, effectively reaching the general population, individuals with risk factors for suicide, and those facing suicidal issues.

LoST: A Mental Health Dataset of Low Self-esteem in Reddit Posts.

Low self-esteem and interpersonal needs (i.e., thwarted belongingness (TB) and perceived burden-someness (PB)) have a major impact on depression and suicide attempts. Individuals seek social connectedness on social media to boost and alleviate their loneliness. Social media platforms allow people to express their thoughts, experiences, beliefs, and emotions. Prior studies on mental health from social media have focused on symptoms, causes, and disorders. Whereas an initial screening of social media content for interpersonal risk factors and low self-esteem may raise early alerts and assign therapists to at-risk users of mental disturbance. Standardized scales measure self-esteem and interpersonal needs from questions created using psychological theories. In the current research, we introduce a psychology-grounded and expertly annotated dataset, LoST: Low Self esTeem, to study and detect low self-esteem on Reddit. Through an annotation approach involving checks on coherence, correctness, consistency, and reliability, we ensure gold standard for supervised learning. We present results from different deep language models tested using two data augmentation techniques. Our findings suggest developing a class of language models that infuses psychological and clinical knowledge.

Problematic Pornography Use: Can It Be Accurately Measured via the Problematic Pornography Use Scale?

AbstractPornography use has increased its popularity worldwide, raising concerns about potential disordered use. Considering the lack of recognition in diagnostic manuals, conceptual clarification and the validation of robust instruments assessing this problem are much needed. The current study is aimed at assessing the psychometric properties of the Problematic Pornography Use Scale (PPUS). Exploratory and confirmatory analyses (EFA and CFA) were used to assess a four-factor and a bifactor solution. Additionally, this study used latent profile (LPA) and sensitivity analyses to determine suggested cut-off values to identify at-risk users. A large sample of adult pornography users completed the PPUS online (N = 1149). A four-factor solution as proposed by Kor and colleagues (Addictive Behaviors, 39(5), 861-868, Kor et al., Addictive Behaviors 39:861–868, 2014) was identified as the optimal factorial structure. Participants were classified into five profiles, with 3.9% identified as at-risk users, 19.9% as moderate to high risk. A cut-off value of 33 was suggested to accurately identify at-risk users. The PPUS is a multidimensional instrument, showing good adept ability to detect users at risk of problematic pornography use.

Patient motivation and preferences in changing co-occurring health risk behaviors in general hospital patients

ObjectivesMore than 60% of general hospital patients report ≥ 2 health risk behaviors (HRBs), i.e. tobacco smoking, at-risk alcohol use, unhealthy diet, and/or insufficient physical activity. This study investigates a) the association between numbers of HRBs and motivation to change, b) patient preferences for receiving feedback on HRBs, and c) patients’ expected gain in quality of life if behavior change made. MethodsIn 2020/2021, 256 18–64-year-old general hospital patients (72.1% of eligibles) reported on their motivation to change each of their HRBs. Associations between HRB number and motivation were assessed using multivariate linear regressions. Participants ranked HRBs concerning their interest in receiving feedback and concerning their expected gain in quality of life if behavior change occurred. ResultsHigher HRB number was negatively related to motivation among at-risk alcohol users (p = 0.034); 24.6% expected gain in their quality of life from behavior change. Participants overall appeared more favorable to feedback about vegetable/fruit intake and physical activity. ConclusionsUnhealthier lifestyle may be accompanied by decreased motivation to change in at-risk alcohol users. In case of co-occurring HRBs, asking patients for expected gain in quality of life may help guiding intervention target. Practice implicationsRelying on patient selection only, may often leave substance-use unaddressed.

Profiles of Pornography Use Based on Addictive Mechanisms and Psychopathological Features.

Studies using person-centered approaches to further explore the profiles of pornography users throw their psychiatric features are lacking. This study was designed to examine the different profiles of pornography users based on the addictive dimensions of Problematic Pornography Use (PPU) and to characterize these profiles according to psychopathological variables such as depression, anxiety, attention deficit hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD). A sample of 1001 French adults participated to a survey containing scales related to psychopathological variables, cybersexual addiction and PPU. PPU was assessed with the French Version of Problematic Pornography Consumption Scale (Fr-PPCS-18). An Agglomerative Hierarchical Classification was performed on the basis of FR-PPCS-18. A student's t-test was used to observe PPU and psychopathological differences between profiles. Findings revealed three profiles of users: non-problematic users (66.5%), at-risk users (29.9%), and problematic users (3.6%). There were significant differences between the three profiles concerning levels of global PPU, PPU mechanisms, cybersexual addiction symptoms, ADHD symptomatology and depressive symptomatology. Results confirmed the existence of different levels of severity of pornography use corresponding to three different profiles. Also, findings revealed the influence of ADHD symptoms, obsessive-compulsive symptoms and depressive symptoms on PPU.

Learning Users Inner Thoughts and Emotion Changes for Social Media Based Suicide Risk Detection

Suicide has become a serious problem, hurting the well-being of human society. Thanks to social media, from peopleslinguistic posts, suicide risk detection has achieved good performance. The aim of this study is to investigate whether more significantaccuracy could be achieved. Motivated by the observation that the prior solutions strived to detect suicide risk based on users explicitouter post expressions on social media, and no attempt was made to infer users inner true thoughts and emotion changes from theirnormal open posts for suicide risk detection, we propose to firstly learn the correlations between users normal open posts and hiddencomments, trying to understand users inner true thoughts and emotion changes from his open posts, and then detect users suiciderisk upon the generated intermediate results. The performance study on the microblog dataset (3,652 at-risk microblog users and 3,652ordinary microblog users) and forum dataset (392 at-risk forum users and 108 ordinary forum users) shows that, based on the inferredhidden thoughts and inner emotion changes, the proposed approach can achieve 95% and 90% detection accuracy, respectively.

Study protocol for approach bias retraining for nicotine addiction among dual combustible and electronic cigarette users

BackgroundElectronic cigarette (ECIG) use has become a popular method for nicotine delivery. Combustible cigarette (CC) cessation or reduction are the primary reasons for ECIG uptake among adults. Yet, most CC smokers who initiate ECIG use do not fully transition from CC to ECIG, despite intending to quit CC completely. Retraining approach bias, or the approach action tendency toward stimuli related to the substance of interest, has been effective in alcohol and CC use treatments. However, approach bias retraining for both CC and (ECIG) users has not been explored. Therefore, the objective of the study is to evaluate the initial efficacy of approach bias retraining among dual CC and ECIG users. MethodsEligible dual CC/ECIG using adults (N = 90) will complete a phone-screener, baseline assessment, 4 treatment sessions over 2 weeks, ecological momentary assessments (EMAs) post-intervention, and follow-ups at 4- and 6-week post-intervention. Participants will be assigned to one of three conditions at baseline: (1) CC + ECIG retraining; (2) CC only retraining; and (3) sham retraining. Participants will engage in a self-guided quit attempt to abstain from all nicotine products starting at treatment session 4. ConclusionsThe study may lead to a more effective treatment for at-risk nicotine users while simultaneously isolating explanatory mechanisms. The findings should guide advances in the theoretical conceptualization of nicotine addiction for dual users and mechanisms involved in maintaining and abstaining from CC and ECIG, and provide initial effect size data for a brief intervention, thus providing necessary data for a large-scale follow-up trial.Clinical Trials ID: NCT05306158

Enabling New Strategies to Prevent Problematic Online Gambling: A Machine Learning Approach for Identifying At-risk Online Gamblers in France

ABSTRACT Gambling activities are rapidly migrating online. Algorithms that effectively detect at-risk users could improve the prevention of online gambling-related harms. We sought to identify machine learning algorithms capable of detecting self-reported gambling problems using demographic and behavioral data. Online gamblers were recruited from all licensed online gambling platforms in France by the French Online Gambling Regulatory Authority (ARJEL). Participants completed the Problem Gambling Severity Index (PGSI), and these data were merged and synchronized with past-year online gambling behaviors recorded on the operators’ websites. Among all participants (N = 9,306), some users reported betting exclusively on sports (N = 1,183), horseracing (N = 1,711), or poker (N = 2,442) activities. In terms of Area Under the Receiver Operating Characteristic Curve (AUC), our algorithms showed excellent performance in classifying individuals at a moderate-to-high (PGSI 5+; AUC = 83.20%), or high (PGSI 8+; AUC = 87.70%) risk for experiencing gambling-related harms. Further, these models identified novel behavioral markers of harmful online gambling for future research. We conclude that machine learning can be used to detect online gamblers at-risk for experiencing gambling problems. Using algorithms like these, operators and regulators can develop targeted harm prevention and referral-to-treatment initiatives for at-risk users.

Impulsivity, inhibition, and internet addiction in medical students of North of Iran.

Internet addiction, a serious psychological disorder, has rapidly increased among students and caused substantial interpersonal impairments. On the other hand, some evidence has indicated that impulsivity is associated with addictive behaviors. There are a few studies concerning the relationship between internet addiction and impulsivity in Iranian students. Therefore, this study aimed to evaluate the relationship between impulsivity and internet addiction in the medical students of Golestan University of Medical Sciences, Golestan, Iran, within 2020-2021. In a cross-sectional study, 260 medical students at Golestan University of Medical Sciences in 2021 completed demographic, Barratt Impulsiveness Scale, and Young questionnaires and participated in a Go/No-Go computer test. Based on Young test scores, the students were divided into three groups of normal users, at-risk users, and users requiring treatment and compared regarding impulsivity and inhibition ability. Data was analyzed using SPSS v 23. The mean age of the participants was 24.16 years. The results showed a significant correlation between impulsivity and internet addiction (p = 0.001), which was established in all contextual indicators. A significant correlation was also shown between impulsivity and internet addiction (r = 0.602 and p = 0.001), both in male and female student. However, restraint index was correlated with internet addiction only in females (r = 0.187 and p = 0.033). Based on these findings, impulsivity increases alongside the rising of the internet addiction severity and does not influence by gender.

Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study.

BackgroundEffective suicide risk assessments and interventions are vital for suicide prevention. Although assessing such risks is best done by health care professionals, people experiencing suicidal ideation may not seek help. Hence, machine learning (ML) and computational linguistics can provide analytical tools for understanding and analyzing risks. This, therefore, facilitates suicide intervention and prevention.ObjectiveThis study aims to explore, using statistical analyses and ML, whether computerized language analysis could be applied to assess and better understand a person’s suicide risk on social media.MethodsWe used the University of Maryland Suicidality Dataset comprising text posts written by users (N=866) of mental health–related forums on Reddit. Each user was classified with a suicide risk rating (no, low, moderate, or severe) by either medical experts or crowdsourced annotators, denoting their estimated likelihood of dying by suicide. In language analysis, the Linguistic Inquiry and Word Count lexicon assessed sentiment, thinking styles, and part of speech, whereas readability was explored using the TextStat library. The Mann-Whitney U test identified differences between at-risk (low, moderate, and severe risk) and no-risk users. Meanwhile, the Kruskal-Wallis test and Spearman correlation coefficient were used for granular analysis between risk levels and to identify redundancy, respectively. In the ML experiments, gradient boost, random forest, and support vector machine models were trained using 10-fold cross validation. The area under the receiver operator curve and F1-score were the primary measures. Finally, permutation importance uncovered the features that contributed the most to each model’s decision-making.ResultsStatistically significant differences (P<.05) were identified between the at-risk (671/866, 77.5%) and no-risk groups (195/866, 22.5%). This was true for both the crowd- and expert-annotated samples. Overall, at-risk users had higher median values for most variables (authenticity, first-person pronouns, and negation), with a notable exception of clout, which indicated that at-risk users were less likely to engage in social posturing. A high positive correlation (ρ>0.84) was present between the part of speech variables, which implied redundancy and demonstrated the utility of aggregate features. All ML models performed similarly in their area under the curve (0.66-0.68); however, the random forest and gradient boost models were noticeably better in their F1-score (0.65 and 0.62) than the support vector machine (0.52). The features that contributed the most to the ML models were authenticity, clout, and negative emotions.ConclusionsIn summary, our statistical analyses found linguistic features associated with suicide risk, such as social posturing (eg, authenticity and clout), first-person singular pronouns, and negation. This increased our understanding of the behavioral and thought patterns of social media users and provided insights into the mechanisms behind ML models. We also demonstrated the applicative potential of ML in assisting health care professionals to assess and manage individuals experiencing suicide risk.

Social media addiction profiles and their antecedents using latent profile analysis: The contribution of social anxiety, gender, and age

The prevalence of social media addiction has increased with the intensive use of technologically-mediated communication in everyday life. Most studies on social media addiction are based on the variable-centered approach with very few taking a person-centered approach. Since only one previous study has investigated the profiles of social media addiction based on a psychopathological model, it is important to bring a complementary view by exploring psychosocial traits associated with the different levels of maladaptive social media use, as well as antecedents of these profiles in terms of sociodemographic variables. To fill this gap, the present study explored social media addiction profiles based on a psychosocial model. The profile indicators were social media addiction, need to belong, anxious attachment, and social media intensity use (SMIU). Data were collected from 705 participants (61% females, age range 18–54 years, Mage = 30.2 years). Latent profile analysis (LPA) showed three distinct profiles: ‘low risk of addiction’ (61.3%), ‘moderate risk of addiction’ (29.6%), and ‘high risk of addiction’ (9.1%). Social anxiety, gender, and age were antecedents of the profiles. These results based on mixture modeling approach are meaningful to the field, bringing a complementary view to the previous findings obtained in a psychopathological framework. The findings could aid practitioners in the development of targeting at-risk social media users, namely social anxious young adult females with an unmet need to belong and anxious attachment, and designing programs to help them to develop rewarding social relationships and healthy social media use.

Did the New French Regulation of Zolpidem Decrease the Problematic Consumption of Zolpidem? A Field Study among Users.

Background: The French national drug regulatory authority stated, in 2017, that a secured prescription pad must be used for zolpidem prescriptions. This study aimed to evaluate the evolution of the problematic consumption of zolpidem at the individual level since the new regulation. Methods: Two nationwide populations of at-risk users of zolpidem were recruited: one in general practitioner (GP) offices and one in specialized care centers dedicated to drug dependence (SCDDs). Participants were asked about their zolpidem consumption before and after the regulation change. The primary outcome was the evolution of problematic zolpidem consumption, as defined by at least one of the following criteria: overconsumption, fraudulent ways of obtaining, effects sought other than hypnotic, and modes of administration other than oral. Results: A total of 243 participants were included: 125 from GP offices and 118 from SCDDs. In the GP population, the prevalence of patients who were identified as problematic consumers decreased from 24.8% to 20.8% (p = 0.593), whereas the prevalence decreased from 73.7% to 51.7% in the SCDD population (p < 0.001). The most prevalent criteria for problematic status were overconsumption and fraudulent ways. Conclusions: The new French regulation of zolpidem had different impacts among two different populations of at-risk zolpidem consumers.

"I Want to Be Stepping in More" - Professional Online Forum Moderators' Experiences of Supporting Individuals in a Suicide Crisis.

IntroductionIndividuals experiencing suicidal crises increasingly turn to online mental health forums for support. Support can come from peers but also from online moderators, many of whom are trained health professionals. Much is known about users' forum experiences; however, the experiences of professional moderators who work to keep users safe has been overlooked. The beneficial nature of online forums cannot be fully realized until there is a clearer understanding of both parties' participation. This study explored the experiences of professional online forum moderators engaged in suicide prevention.Materials and MethodsA purposive sample of professionally qualified moderators was recruited from three online mental health organizations. In-depth semi-structured, video-recorded interviews were conducted with 15 moderators (3 male, 12 female), to explore their experiences and perceptions of working in online suicide prevention spaces. Data was analyzed using inductive thematic analysis.ResultsFive themes were identified related to the experiences and challenges for moderators. These were the sense of the unknown, the scope of the role, limitations of the written word, volume of tasks, and balancing individual vs. community needs.DiscussionFindings indicate that the professionally qualified moderator role is complex and multifaceted, with organizations failing to recognize these aspects. Organizations restrict moderators from using their full therapeutic skill set, limiting them to only identifying and re-directing at-risk users to crisis services. The benefits of moderated online forums could be enhanced by allowing moderators to use more of their skills. To facilitate this, in-situ research is needed that examines how moderators use their skills to identify at-risk users.

At-risk alcohol users have disrupted valence discrimination during reward anticipation.

Alcohol use disorder is characterised by disrupted reward learning, underpinned by dysfunctional cortico‐striatal reward pathways, although relatively little is known about the biology of reward processing in populations who engage in risky alcohol use. Cues that trigger reward anticipation can be categorized according to their learnt valence (i.e., positive vs. negative outcomes) and motivational salience (i.e., incentive vs. neutral cues). Separating EEG signals associated with these dimensions is challenging because of their inherent collinearity, but the recent application of machine learning methods to single EEG trials affords a solution. Here, the Alcohol Use Disorders Identification Test (AUDIT) was used to quantify risky alcohol use, with participants split into high alcohol (HA) (n = 22, mean AUDIT score: 13.82) and low alcohol (LA) (n = 22, mean AUDIT score: 5.77) groups. We applied machine learning multivariate single‐trial classification to the electroencephalography (EEG) data collected during reward anticipation. The LA group demonstrated significant valence discrimination in the early stages of reward anticipation within the cue‐P3 time window (400–550 ms), whereas the HA group was insensitive to valence within this time window. Notably, the LA, but not the HA group demonstrated a relationship between single‐trial variability in the early valence component and reaction times for gain and loss trials. This study evidences disrupted hypoactive valence sensitivity in the HA group, revealing potential neurophysiological markers for risky drinking behaviours which place individuals at‐risk of adverse health events.