Is There a Dose-Response Relationship Between Cannabis Use and Violence? A Longitudinal Study in Individuals with Severe Mental Disorders.

Introduction: Recent longitudinal studies point toward the existence of a positive relationship between cannabis use and violence in people with severe mental disorders (SMD). However, the existence of a dose-response relationship between the frequency/severity of cannabis use and violence has seldom been investigated. Therefore, this study aims to determine if such a relationship exists in a psychiatric population. Methods: To do so, a total of 98 outpatients (81 males and 17 females, all over 18 years of age) with SMD were recruited at the Institut universitaire de santé mentale de Montréal (Montréal, Canada) and included in the analyses. Clinical evaluations were conducted every 3 months for a year. Substance use, violent behaviors, and potential covariables were assessed through self-reported assessments, urinary testing, as well as clinical, criminal, and police records. Using generalized estimating equations, the association between cannabis use frequency (nonusers, occasional, regular, and frequent users) and violence was investigated, as well as the association between the severity of cannabis use and violent behaviors. Results: It was found that cannabis use frequency and severity were significant predictors of violent behaviors. After adjustment for time, age, sex, ethnicity, diagnoses, impulsivity, and use of alcohol and stimulants, odds ratios were of 1.91 (p<0.001) between each frequency profile and 1.040 (p<0.001) for each increase of one point of the severity of cannabis use score (ranging from 0 to 79). Conclusions: Despite the high attrition rate, these findings may have important implications for clinicians as cannabis use may have serious consequences in psychiatric populations. Nevertheless, the mechanisms underlying this association remain unclear.

Exploration of the role of emotional expression of treatment-resistant schizophrenia patients having followed virtual reality therapy: a content analysis.

BACKGROUND: Emotional responses are an important component of psychotherapeutic processes. Avatar therapy (AT) is a virtual reality-based therapy currently being developed and studied for patients suffering from treatment resistant schizophrenia. Considering the importance of identifying emotions in therapeutical processes and their impact on the therapeutic outcome, an exploration of such emotions is needed. METHODS: The aim of this study is to identify the underlying emotions at the core of the patient-Avatar interaction during AT by content analysis of immersive sessions transcripts and audio recordings. A content analysis of AT transcripts and audio recordings using iterative categorization was conducted for 16 patients suffering from TRS who underwent AT between 2017 and 2022 (128 transcripts and 128 audio recordings). An iterative categorization technique was conducted to identify the different emotions expressed by the patient and the Avatar during the immersive sessions. RESULTS: The following emotions were identified in this study: Anger, Contempt/ Disgust, Fear, Sadness, Shame/ Embarrassment, Interest, Surprise, Joy and Neutral. Patients expressed mostly neutral, joy and anger emotions whereas the Avatar expressed predominantly interest, disgust/contempt, and neutral emotions. CONCLUSIONS: This study portrays a first qualitative insight on the emotions that are expressed in AT and serves as a steppingstone for further investigation in the role of emotions in the therapeutic outcomes of AT.

Meta-review on the efficacy of psychological therapies for the treatment of substance use disorders.

This meta-review aimed to summarize the current state of knowledge provided by meta-analyzes on the efficacy of psychotherapies for substance use disorders. A systematic search was performed in PubMed, PsycINFO, Web of Science and Google Scholar. Meta-analyzes were included if they quantitatively examined the efficacy of a psychotherapy on substance use. Among the 6866 potential articles that were screened for eligibility, 23 meta-analyzes were eligible (78 effect sizes). Each meta-analysis included 2-156 studies, with samples ranging between approximately 130 to over 33,000 individuals. The quality of evidence was evaluated as being globally of low to moderate quality. Substances were categorized as: alcohol (k = 12), cannabis (k = 7), stimulants (k = 4), opioids (k = 3) and benzodiazepines (k = 1). Interventions comprised brief intervention, cognitive-behavioral therapy, contingency management, voucher-based reinforcement therapy, motivational interview, motivational enhancement therapy, significant other people involved in the treatment, and cue-expose therapy. Concerning solely significant results, small benefits were observed for significant other people involved in treatment, motivational interviewing, and the combination of cognitive-behavioral therapy with motivational interviewing for alcohol use disorder. Likewise, small-to-moderate effects were found for motivational approaches, and cognitive-behavioral therapy as well as the combination of cognitive-behavioral therapy and motivational enhancement therapy in the case of cannabis use disorder. Small effects were observed for contingency management as well as cognitive behavioral-therapy for amphetamine-type use disorder. Small effects were similarly found for contingency management for cocaine use disorder. Concerning opioid use disorder, moderate effects were observed for contingency management and voucher-based reinforcement intervention. For benzodiazepine use disorder, small effects were noted for cognitive-behavioral therapy with taper. Results often displayed small to moderate heterogeneity when reported and were generally compared to inactive controls, such as treatment-as-usual. In all, the psychosocial treatments for substance use disorders included in this meta-review have shown to be at best moderately effective over inactive controls in the short term. Nevertheless, further trials are needed as well as meta-analyzes on interventions not included in this meta-review.

Avatar Intervention for Cannabis Use Disorder in Individuals with Severe Mental Disorders: A Pilot Study.

Cannabis use disorder (CUD) is a complex issue, even more so when it is comorbid with a severe mental disorder (SMD). Available interventions are at best slightly effective, and their effects are not maintained over time. Therefore, the integration of virtual reality (VR) may increase efficacy; however, it has not yet been investigated in the treatment of CUD. A novel approach, avatar intervention for CUD, uses existing therapeutic techniques from other recommended therapies (e.g., cognitive behavioral methods, motivational interviewing) and allows participants to practice them in real-time. During immersive sessions, participants are invited to interact with an avatar representing a significant person related to their drug use. This pilot clinical trial aimed to evaluate the short-term efficacity of avatar intervention for CUD on 19 participants with a dual diagnosis of SMD and CUD. Results showed a significant moderate reduction in the quantity of cannabis use (Cohen's d = 0.611, p = 0.004), which was confirmed via urinary quantification of cannabis use. Overall, this unique intervention shows promising results. Longer-term results, as well as comparison with classical interventions in a larger sample, are warranted through a future single-blind randomized controlled trial.

Dyadic Interactions of Treatment-Resistant Schizophrenia Patients Having Followed Virtual Reality Therapy: A Content Analysis.

(1) Background: Very little is known about the inner therapeutic processes of psychotherapy interventions for patients suffering from treatment-resistant schizophrenia. Avatar therapy (AT) is one such modalities in which the patient is undergoing immersive sessions in which they interact with an Avatar representing their main persistent auditory verbal hallucination. The aim of this study is to identify the most prevalent dyadic interactions between the patient and the Avatar in AT for patient's suffering from TRS. (2) Methods: A content analysis of 256 verbatims originating from 32 patients who completed AT between 2017 and 2022 at the Institut universitaire en santé mentale de Montréal was conducted to identify dyadic interactions between the patients and their Avatar. (3) Results: Five key dyads were identified to occur on average more than 10 times for each participant during the immersive sessions across their AT: (Avatar: Reinforcement, Patient: Self-affirmation), (Avatar: Provocation, Patient: Self-affirmation), (Avatar: Coping mechanisms, Patient: Prevention), (Patient: Self-affirmation, Avatar: Reinforcement), and (Patient: Self-appraisal, Avatar: Reinforcement). (4) Conclusion: These dyads offer a first qualitative insight to the interpersonal dynamics and patient-avatar relationships taking place during AT. Future studies on the implication of such dyadic interactions with the therapeutic outcome of AT should be conducted considering the importance of dyadic relationships in psychotherapy.

Association Between Cannabis and Violence in Community-Dwelling Patients With Severe Mental Disorders: A Cross-sectional Study Using Machine Learning.

ABSTRACT: The objective of this cross-sectional study was to identify cannabis-related features and other characteristics predictive of violence using a data-driven approach in patients with severe mental disorders (SMDs). A Least Absolute Shrinkage and Selection Operator regularization regression model was used on the database consisting of 97 patients with SMD who completed questionnaires measuring substance use and violence. Cannabis use, particularly related to patients' decision to consume or time spent using, was a key predictor associated with violence. Other patterns of substance use and personality traits were identified as strong predictors. Regular patterns of cannabis use and interpersonal issues related to cannabis/stimulant abuse were inversely correlated to violence. This study identified the effect of several predictors correlated to violence in patients with SMD using a regularization regression model. Findings open the door to better identify the profiles of patients that may be more susceptible to perpetrate violent behaviors.

The Potential Paradoxical Neurocognitive Effects of Cannabis Use in Patients with Psychotic Disorders: A Critical Meta-Review of Meta-Analytical Evidence.

Background: The association between cannabis and cognitive functions has been thoroughly studied in psychotic disorders, but conflictual/paradoxical results have emerged. This critical meta-review examined the magnitude of effects of cannabis on neurocognitive functions in patients with psychotic disorders provided by meta-analyses and evaluated the quality of evidence. Methods: A systematic search of meta-analyses was performed in PubMed, PsycINFO, Web of Science, and Google Scholar. Results: The search retrieved six meta-analyses. Quality of evidence varied from very low to moderate quality. No neurocognitive difference was observed between cannabis users and nonusers in first episode of psychosis samples. Limited evidence showed no significant difference in language, psychomotor functioning, and verbal/visual learning/memory, apart from improvements in verbal and visual memory (recognition). Findings showed better neurocognitive performances in cannabis-using patients for planning/reasoning and working memory. There were tendencies toward significance for processing speed and attention. Most effect sizes showed small to moderate degrees of outperformances in cannabis users. Individuals with lifetime use appeared to show better neurocognitive functions. Conclusion: Evidence indicated nonuniform effects of cannabis use across cognitive domains, with some areas suggesting better cognitive performances in cannabis users, entitled the paradoxical effect of the dually diagnosed. Clinical significance of these findings should be interpreted cautiously.

Implementation of a machine learning algorithm for automated thematic annotations in avatar: A linear support vector classifier approach.

Avatar Therapy (AT) is a modern therapeutic alternative for patients with schizophrenia suffering from persistent auditory verbal hallucinations. Its intrinsic therapeutical process is currently qualitatively analyzed via human coders that annotate session transcripts. This process is time and resource demanding. This creates a need to find potential algorithms that can operate on small datasets and perform such annotations. The first objective of this study is to conduct the automated text classification of interactions in AT and the second objective is to assess if this classification is comparable to the classification done by human coders. A Linear Support Vector Classifier was implemented to perform automated theme classifications on Avatar Therapy session transcripts with the use of a limited dataset with an accuracy of 66.02% and substantial classification agreement of 0.647. These results open the door to additional research such as predicting the outcome of a therapy.

The impacts of the COVID-19 pandemic on treatment-resistant schizophrenia patients having followed virtual reality therapy or cognitive behavioural therapy: a content analysis.

PURPOSE: The COVID-19 pandemic led to exacerbation of mental health symptoms and deterioration in psychological well-being in individuals suffering from schizophrenia. The primary objective of this study is to evaluate the impacts of the COVID-19 pandemic on patients suffering from treatment-resistant schizophrenia (TRS) with auditory verbal hallucinations (AVH) having undergone virtual reality therapy (VRT) or cognitive behavioural therapy (CBT) on their symptomatology. The secondary objective is to identify the differences and similarities in relation to the response to the COVID 19 pandemic between these two groups of patients. METHODS: Qualitative analysis of semi-structured interviews was conducted with 42 patients suffering from TRS who had previously followed VRT or CBT. All interviews were recorded, transcribed, and analysed. RESULTS: Four themes emerged in this study: Psychotherapeutic Interventions, Impact of COVID-19 and Public health and safety policies, Substance use and Psychiatric follow-up. Participants from both groups reported that their therapy was beneficial in controlling AVH. Patients having followed CBT reported more depressive symptoms whereas patients having followed VRT reported more anxious symptoms. CONCLUSIONS: This study offers a first qualitative insight in patients suffering from TRS and the impacts of COVID-19 on them and opens the door to the protective factors of CBT and VRT for this specific population.

A systematic review of relational-based therapies for the treatment of auditory hallucinations in patients with psychotic disorders.

BACKGROUND: Auditory hallucinations in patients with psychotic disorders may be very distressing. Unfortunately, a large proportion of individuals are resistant to pharmacological interventions and the gold-standard cognitive-behavioral therapy for psychosis offers at best modest effects. To improve therapeutic outcomes, several therapies have been created to establish a relationship between voice-hearers and their voices. With increasing literature, we conducted a systematic review of dialogical therapies and examined the evidence behind their efficacy. METHODS: A systematic search was performed in PubMed, PsycINFO, Web of Science, and Google Scholar. Articles were included if they discussed the effects of dialogical interventions for patients with psychotic disorders. RESULTS: A total of 17 studies were included within this systematic review. Cumulative evidence from various therapies has shown that entering in a dialog with voices is beneficial to patients, even those who are resistant to current pharmacological treatments. Heightened benefits have been mainly observed with Relating Therapy and Avatar Therapy/Virtual Reality assisted Therapy, with evidence generally of moderate quality. Both these interventions have shown large to very large effects on voices and voice-related distress as well as moderate to large magnitude improvements on affective symptoms. Though, cognitive-behavioral therapy for command hallucinations and making sense of voices noted no improvements on voices. CONCLUSIONS: Literature on relational-based interventions with a strong emphasis on the relational aspects of voice hearing has shown positive effects. Results suggest that these dialogical therapies might surpass the efficacy of current gold-standard approaches.

The defense of mental disorder and crimes against the person committed under the influence of cannabis: A Canadian perspective.

The legalization of cannabis raises many queries, one of which regards the criminal liability of users under the influence of cannabis when crimes against the person are committed. This perspective review consequently aims to examine the defense of mental disorder (also referred to as the insanity defense) in Canadian criminal law and revise court decisions involving cases with cannabis use rendered in the field between 1995 and 2021. The purpose was to specify the factors allowing Canadian criminal courts to grant or refuse the defense of mental disorder to help further operationalize the jurisprudential criteria for forensic practice. We noted that presence of a severe and persistent primary psychopathology was the most decisive factor when determining the verdict of the accused who consumed cannabis.

Evidence on the acute and residual neurocognitive effects of cannabis use in adolescents and adults: a systematic meta-review of meta-analyses.

BACKGROUND: Cannabis is among the most consumed psychoactive substances world-wide. Considering changing policy trends regarding the substance, it is crucial to understand more clearly its potential acute and residual adverse effects from a public health viewpoint. Cognitive function is one of the targeted areas with conflicting findings. This meta-review measured the magnitude of acute and residual effects of cannabis on cognition in adolescents and adults provided by meta-analyses and evaluated quality of evidence. METHODS: A systematic search was performed in PubMed, PsycINFO, Web of Science and Google Scholar. Meta-analyses were included if they quantitatively examined the performances of users from the general population on cognitive tasks. RESULTS: The search retrieved 10 eligible meta-analyses (71 effects sizes, n = 43 761) with evidence ranging from low to moderate quality, which were categorized into domains of cognitive functions: executive functions (k = 7), learning and memory (k = 5), attention (k = 4), processing speed (k = 5), perceptual motor function (k = 2) and language (k = 2). Verbal learning and memory displayed the most robust evidence and were most impaired by acute cannabis intoxication that persisted after intoxication passed. Small-to-moderate acute and residual adverse effects were reported for executive functioning. Cannabis use led to small deficits in inhibitory processes and flexibility, whereas small-to-moderate deficits were reported for working memory and decision-making. Evidence regarding processing speed and attention has shown that cannabis administration induced small-to-moderate adverse effects and residual neurocognitive deficits were observed in heavy cannabis-using youths. Results showed no significant difference between cannabis users and non-users on language, and small-to-moderate effects for simple motor skills. CONCLUSION: Meta-analytical data on the acute effects of cannabis use on neurocognitive function have shown that cannabis intoxication leads to small to moderate deficits in several cognitive domains. These acute impairments accord with documented residual effects, suggesting that the detrimental effects of cannabis persist beyond acute intake.

Solitary Confinement of Inmates Associated With Relapse Into Any Recidivism Including Violent Crime: A Systematic Review and Meta-Analysis.

Recidivism among released inmates is associated with a substantial societal burden given the financial and medical consequences of victimization. Among incarcerated North Americans, approximately 7% are housed in solitary confinement (SC). Studies show SC can lead to psychological deterioration and dispute it can effectively reduce institutional misconduct or recidivism. This meta-analysis aims to clarify the impact of SC on postrelease recidivism, which we hypothesized would increase following SC. A meta-analysis was conducted using PubMed, PsycINFO, Web of Science, and Google Scholar databases from inception until December 2019. Studies on adult inmates in correctional settings were included if they met an operational definition of SC, measured recidivism, and included a comparison group in general inmate population. Random-effect models were used to assess the impact of SC on multiple types of recidivism. Of the 2,713 identified records, 12 met inclusion criteria (n = 194,078). A moderate association was found between SC and any recidivism (odds ratio [OR] = 1.67, 95% confidence interval [1.41, 1.97]), which persisted in controlled studies (OR = 1.41). This association was replicated across types of recidivism comprising violence (OR = 1.41), rearrests (OR = 1.37), and reincarceration (OR = 1.67). Moreover, a more recent exposure to SC increased recidivism risk (OR = 2.02), and a dose-response relationship was found between days in SC and recidivism. The overall database presented high heterogeneity but no publication bias. Findings show a small to moderate association between SC and future crime/violence. Considering the societal costs associated with antisocial behaviors following SC, mental health and psychosocial programming facilitating inmates' successful reentry into society should be implemented and rigorously evaluated in strong research design.

[Improving Quality of Life in Patients with Refractory Schizophrenia After Virtual Reality-assisted Therapy: A Content Analysis]. / L'amélioration de la qualité de vie chez les patients atteints d'une schizophrénie réfractaire ayant suivi la Thérapie assistée par la Réalité Virtuelle : une analyse de contenu.

Objectives Schizophrenia, particularly treatment-resistant schizophrenia (TRS), is one of the most disabling psychiatric disorders in terms of adverse effects on the quality of life (QOL) of patients. Subjective QOL has become a particularly crucial target that should be improved with treatment, since improved QOL may lead to recovery in patients with schizophrenia. However, there is little evidence on the efficacy of recommended psychosocial interventions on non-symptomatic measures such as QOL. In this regard, the treatment of schizophrenia can be enhanced if, in addition to the treatment of symptoms, therapeutic emphasis is placed on other areas of importance to patients. With advancements in technology, Virtual Reality assisted Therapy (VRT) allows voice hearers to enter in a direct dialogue with an avatar, fully animated by the therapist, who represents their most persecuting voice. This is in the aim to allow them to gain better control over their voices and to work on their self-esteem. Beyond symptomatology, the results of the pilot projects on this innovative therapy have shown significant results on QOL. Method To refine the observed quantitative results, this article will explore emerging themes from a content analysis arising from the spontaneous discourse of 10 patients who responded well to TRV. Results Four general themes emerged: (i) impact of therapy on voices, (ii) interpersonal relationships, (iii) psychological well-being, and (iv) lifestyle. This content analysis has identified several spheres of life that are further improved in patients with TRS using TRV. Conclusion TRV highlights the future of patient-oriented approaches that integrate several relevant processes to potentially improve QOL. TRV can have potentially immense implications for the health and quality of life of patients. This study was a first step towards exploring the subjective effects of TRV on the lives of patients beyond the symptoms.

Use of Automated Thematic Annotations for Small Data Sets in a Psychotherapeutic Context: Systematic Review of Machine Learning Algorithms.

BACKGROUND: A growing body of literature has detailed the use of qualitative analyses to measure the therapeutic processes and intrinsic effectiveness of psychotherapies, which yield small databases. Nonetheless, these approaches have several limitations and machine learning algorithms are needed. OBJECTIVE: The objective of this study is to conduct a systematic review of the use of machine learning for automated text classification for small data sets in the fields of psychiatry, psychology, and social sciences. This review will identify available algorithms and assess if automated classification of textual entities is comparable to the classification done by human evaluators. METHODS: A systematic search was performed in the electronic databases of Medline, Web of Science, PsycNet (PsycINFO), and Google Scholar from their inception dates to 2021. The fields of psychiatry, psychology, and social sciences were selected as they include a vast array of textual entities in the domain of mental health that can be reviewed. Additional records identified through cross-referencing were used to find other studies. RESULTS: This literature search identified 5442 articles that were eligible for our study after the removal of duplicates. Following abstract screening, 114 full articles were assessed in their entirety, of which 107 were excluded. The remaining 7 studies were analyzed. Classification algorithms such as naive Bayes, decision tree, and support vector machine classifiers were identified. Support vector machine is the most used algorithm and best performing as per the identified articles. Prediction classification scores for the identified algorithms ranged from 53%-91% for the classification of textual entities in 4-7 categories. In addition, 3 of the 7 studies reported an interjudge agreement statistic; these were consistent with agreement statistics for text classification done by human evaluators. CONCLUSIONS: A systematic review of available machine learning algorithms for automated text classification for small data sets in several fields (psychiatry, psychology, and social sciences) was conducted. We compared automated classification with classification done by human evaluators. Our results show that it is possible to automatically classify textual entities of a transcript based solely on small databases. Future studies are nevertheless needed to assess whether such algorithms can be implemented in the context of psychotherapies.

Systematic Review on the Mental Health and Treatment Impacts of COVID-19 on Neurocognitive Disorders.

Objectives. The COVID-19 pandemic has had many public health impacts, especially on vulnerable individuals including adults with neurocognitive disorders (NCD). With increasing literature, this systematic literature review aimed to address the mental health effects of COVID-19 on people with NCD in addition to examine the impact of the pandemic on treatments/resources for NCD. Methods. A literature search was conducted in the electronic databases of PubMed, PsycINFO, Web of Science and Google Scholar. Studies were included so long as they assessed the mental health or therapeutic effects of COVID-19 on NCD. Results. Among the retrieved articles, 59 met eligibility criteria. First, the pandemic and resulting self-isolation led to many detrimental effects on psychological well-being. Exacerbation and relapses of neurocognitive and behavioral symptoms were observed, as well as emergences of new psychological symptoms (i.e., depression, anxiety). Second, therapeutic and community services for individuals suffering from NCD, such as social support services and outpatient clinics, were disrupted or reduced leading to postponed appointments and evaluations, as well as reduced access to medications. These issues were somewhat palliated with the growth of telemedicine. Conclusions. This systematic review highlights the extent of the effects of the pandemic, and the topics addressed should be taken into consideration by healthcare practitioners, institutions, and policymakers to ensure that proper measures are employed to protect this population from additional harm.

One-year randomized trial comparing virtual reality-assisted therapy to cognitive-behavioral therapy for patients with treatment-resistant schizophrenia.

The gold-standard cognitive-behavioral therapy (CBT) for psychosis offers at best modest effects. With advances in technology, virtual reality (VR) therapies for auditory verbal hallucinations (AVH), such as AVATAR therapy (AT) and VR-assisted therapy (VRT), are amid a new wave of relational approaches that may heighten effects. Prior trials have shown greater effects of these therapies on AVH up to a 24-week follow-up. However, no trial has compared them to a recommended active treatment with a 1-year follow-up. We performed a pilot randomized comparative trial evaluating the short- and long-term efficacy of VRT over CBT for patients with treatment-resistant schizophrenia. Patients were randomized to VRT (n = 37) or CBT (n = 37). Clinical assessments were administered before and after each intervention and at follow-up periods up to 12 months. Between and within-group changes in psychiatric symptoms were assessed using linear mixed-effects models. Short-term findings showed that both interventions produced significant improvements in AVH severity and depressive symptoms. Although results did not show a statistically significant superiority of VRT over CBT for AVH, VRT did achieve larger effects particularly on overall AVH (d = 1.080 for VRT and d = 0.555 for CBT). Furthermore, results suggested a superiority of VRT over CBT on affective symptoms. VRT also showed significant results on persecutory beliefs and quality of life. Effects were maintained up to the 1-year follow-up. VRT highlights the future of patient-tailored approaches that may show benefits over generic CBT for voices. A fully powered single-blind randomized controlled trial comparing VRT to CBT is underway.

The therapeutic processes of avatar therapy: A content analysis of the dialogue between treatment-resistant patients with schizophrenia and their avatar.

OBJECTIVE: Because the therapeutic processes of Avatar Therapy remain equivocal, the current study aims to further extend our previous findings by analysing the evolution of the avatars' and patients' speech and changes in patient responses as sessions progressed. DESIGN: Eighteen patients with treatment-resistant schizophrenia were selected from two clinical trials on Avatar Therapy. Three coders analysed both the avatars' and patients' discourse during immersive therapy sessions using content analysis methods. RESULTS: Our analyses enabled the categorization of the avatar discourse into confrontational techniques (e.g., provocation) and positive techniques (e.g., reinforcement). Patients responded to these utterances using coping mechanism or by expressing emotions, beliefs, self-perceptions or aspirations. Through identification of mutual changes in the interaction between the patient and their avatar, a shift was observed over the sessions from confrontation to a constructive dialogue. Assertiveness, emotional responses and prevention strategies seemed to be central to the therapeutic process, and these usually occur in response to positive techniques. CONCLUSION: Investigating AT's therapeutic process may help to identify components to achieve positive outcomes and can enable the development of more effective treatments. Further studies should explore the association between these themes and therapeutic response to help predict which patients will better respond to Avatar Therapy.

Aggression and delinquent behavior in a large representative sample of high school students: Cannabis use and victimization as key discriminating factors.

PURPOSE: Since conduct problems (CP) vary distinctly across youths, better subtyping CP may be an important vehicle to study specific risk factors associated to differential patterns of CP. In a sample of 63,196 adolescents, we employed a two-step method to the identify such CP patterns and to help classify youths based on several sociodemographic and psychopathological risk factors associated with CP. METHODS: K-means clustering methods were first used to reduce the heterogeneity of CP by analyzing patterns of aggressive (AGG) and rule-breaking (RB) behaviors. A multi-class Classification and Regression Tree approach was further employed to examine the hierarchical interactions between risk factors specific to the emergence of different CP patterns. RESULTS: Results revealed a three-cluster solution: (i) Low AGG-RB, (ii) High AGG and low RB, and (iii) High AGG-RB. The frequency of cannabis use, level of victimization and hyperactivity symptoms were the three factors best discriminating youths' membership to distinct patterns of CP. The model displayed a moderate to strong discriminatory capacity. CONCLUSION: Although this study provides evidence of key factors that may increase the risk of youths following specific patterns of disruptive behavior, additional research is necessary to clarify the etiology, longitudinal trajectories and outcomes related to these patterns.

Violence and Cannabis Use: A Focused Review of a Forgotten Aspect in the Era of Liberalizing Cannabis.

There has been a shift surrounding societal and legal perspectives on cannabis reflecting changing public attitudes towards the perceived safety and social acceptability of cannabis use. With cannabis liberalization internationally, the focus of most cannabis-related harms has been on effects with users themselves. Harm-to-others including injuries from violence have nevertheless been unfortunately largely overlooked. While studies remain heterogeneous, there is meta-analytical evidence pointing towards an association. The aims of this focused review are two-fold: (I) review the evidence from meta-analyses on the association between cannabis and violence; and (II) provide an overview of possible mechanisms relating cannabis use to violence. First, evidence from meta-analytical studies in youths, intimate partners, and individuals with severe mental disorders have shown that there is a global moderate association between cannabis use and violence, which is stronger in the latter more at-risk population. Preliminary data has even highlighted a potential dose-response relationship with larger effects in more frequent users. Although of importance, this subject has remained essentially forgotten as a public health concern. While literature remains inconclusive, data has suggested potential increases in cannabis use following liberalization policies. This may increase violent outcomes if the effect is directly related to the use of cannabis by means of its psychophysiological modifications. However, for the moment, the mechanisms associating cannabis use and violence remain to be clearly resolved. Considering the recency of policy changes on cannabis, further methodologically sound research using longitudinal designs should examine the effects that cannabis use may have on different forms of violence and the trends that emerge, while evaluating the effects of possible confounding factors (e.g. other substance use). In addition, as evidence-based research from meta-analyses have shown that cannabis use is associated with violence, measures must be taken to mitigate the risks.