Effects of Recreational Cannabis Legalization on Mental Health: Scoping Review.

OBJECTIVE: Recreational cannabis legalization (RCL) is expanding rapidly. RCL's effects on mental health issues are of particular concern because cannabis use is more frequent among people receiving psychiatric care and is associated with several psychiatric disorders. The authors conducted a scoping review to examine the evidence and discern gaps in the literature concerning the effects of RCL on mental health and to assess the factors responsible for an observed heterogeneity in research results. METHODS: This scoping literature review followed PRISMA guidelines. Five databases-MEDLINE, CINAHL, Embase, APA PsycInfo, and Web of Science-were searched for English- or French-language reports published between January 1, 2012, and April 30, 2023. RESULTS: Twenty-eight studies from the United States and Canada were found. The studies were classified by category of the study's data (patients receiving psychiatric care [k=1], death records [k=4], emergency department or hospital records [k=10], and the general population [k=13]) and by the diagnosis (schizophrenia or psychoses, mood disorders, anxiety disorders and symptoms, suicide or suicidal ideation, or other mental health issues) examined. The review findings revealed a paucity of research and indicated mixed and largely inconclusive results of the studies examined. Research gaps were found in the examination of potential changes in cannabis use patterns among people receiving psychiatric care and in the availability of longitudinal studies. CONCLUSIONS: Clinicians, researchers, and policy makers need to collaborate to address the research gaps and to develop evidence-based policies that reflect a thorough understanding of the effects associated with RCL.

Structural brain abnormalities and aggressive behaviour in schizophrenia: Mega-analysis of data from 2095 patients and 2861 healthy controls via the ENIGMA consortium.

Background: Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome. Methods: This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale. Results: Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control. Conclusions: This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.

The Signature Biobank: A longitudinal biopsychosocial repository of psychiatric emergency patients.

The Signature Biobank is a longitudinal repository of biospecimen, psychological, sociodemographic, and diagnostic data that was created in 2012. The Signature Consortium represents a group of approximately one hundred Quebec-based transdisciplinary clinicians and research scientists with various expertise in the field of psychiatry. The objective of the Signature Biobank is to investigate the multi-faceted underpinnings of psychiatric disorders among patients in crisis. The Signature Consortium is expanding and includes new active members that seek to highlight the contributions made by Signature Biobank since its inception. This article details our research protocol, directions, and summarizes contributions. To date, we have collected biological samples (n = 1,986), and questionnaire data (n = 2,085) from psychiatric emergency patients of the Institut universitaire en santé mentale de Montréal (Quebec, Canada), with a large proportion from whom both data types were collected (n = 1,926). In addition to this, a subsample of patients was followed-up at hospital discharge, and two additional outpatient clinic appointments (n = 958 with at least one follow-up). In addition, a socio-demographically matched comparison group of individuals who were not hospitalized for psychiatric disorders (n = 149) was recruited from the surrounding catchment area. To summarize, a systematic review of the literature shows that the Signature Biobank has contributed to better characterizing psychiatric comorbidities, biological profiles, and psychosocial functioning across some of the most common psychiatric disorders, including psychosis, mood, anxiety, and substance use disorders. The Signature Biobank is now one of the world's largest repositories of data collected from patients receiving care at a psychiatric emergency unit.

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.

Auditory Steady-State Responses in Schizophrenia: An Updated Meta-Analysis.

This meta-analysis investigates auditory steady-state responses (ASSRs) as potential biomarkers of schizophrenia, focusing on previously unexplored clinical populations, frequencies, and variables. We examined 37 studies, encompassing a diverse cohort of 1788 patients with schizophrenia, including 208 patients with first-episode psychosis, 281 at-risk individuals, and 1603 healthy controls. The results indicate moderate reductions in 40 Hz ASSRs in schizophrenia patients, with significantly greater reductions in first-episode psychosis patients and minimal changes in at-risk individuals. These results call into question the expected progression of ASSR alterations across all stages of schizophrenia. The analysis also revealed the sensitivity of ASSR alterations at 40 Hz to various factors, including stimulus type, level of analysis, and attentional focus. In conclusion, our research highlights ASSRs, particularly at 40 Hz, as potential biomarkers of schizophrenia, revealing varied implications across different stages of the disorder. This study enriches our understanding of ASSRs in schizophrenia, highlighting their potential diagnostic and therapeutic relevance, particularly in the early stages of the disease.

Enhancing Predictive Power: Integrating a Linear Support Vector Classifier with Logistic Regression for Patient Outcome Prognosis in Virtual Reality Therapy for Treatment-Resistant Schizophrenia.

(1) Background: Approximately 30% of schizophrenia patients are known to be treatment-resistant. For these cases, more personalized approaches must be developed. Virtual reality therapeutic approaches such as avatar therapy (AT) are currently undergoing investigations to address these patients' needs. To further tailor the therapeutic trajectory of patients presenting with this complex presentation of schizophrenia, quantitative insight about the therapeutic process is warranted. The aim of the study is to combine a classification model with a regression model with the aim of predicting the therapeutic outcomes of patients based on the interactions taking place during their first immersive session of virtual reality therapy. (2) Methods: A combination of a Linear Support Vector Classifier and logistic regression was conducted over a dataset comprising 162 verbatims of the immersive sessions of 18 patients who previously underwent AT. As a testing dataset, 17 participants, unknown to the dataset, had their first immersive session presented to the combinatory model to predict their clinical outcome. (3) Results: The model accurately predicted the clinical outcome for 15 out of the 17 participants. Classification of the therapeutic interactions achieved an accuracy of 63%. (4) Conclusion: To our knowledge, this is the first attempt to predict the outcome of psychotherapy patients based on the content of their interactions with their therapist. These results are important as they open the door to personalization of psychotherapy based on quantitative information about the interactions taking place during AT.

Regional cerebral blood flow at rest in schizophrenia and major depressive disorder: A functional neuroimaging meta-analysis.

Severe mental disorders (SMDs) such as schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BD) are associated with altered brain function. Neuroimaging studies have illustrated spontaneous activity alterations across SMDs, but no meta-analysis has directly compared resting-state regional cerebral blood flow (rCBF) with one another. We conducted a meta-analysis of PET, SPECT and ASL neuroimaging studies to identify specific alterations of rCBF at rest in SMDs. Included are 20 studies in MDD, and 18 studies in SCZ. Due to the insufficient number of studies in BD, this disorder was left out of the analyses. Compared to controls, the SCZ group displayed reduced rCBF in the triangular part of the left inferior frontal gyrus and in the medial orbital part of the bilateral superior frontal gyrus. After correction, only a small cluster in the right inferior frontal gyrus exhibited reduced rCBF in MDD, compared to controls. Differences were found in these brain regions between SCZ and MDD. SCZ displayed reduced rCBF at rest in regions associated with default-mode, reward processing and language processing. MDD was associated with reduced rCBF in a cluster involved in response inhibition. Our meta-analysis highlights differences in the resting-state rCBF alterations between SCZ and MDD.

Alpha and theta oscillations during the cognitive reappraisal of aversive pictures: A spatio-temporal qEEG investigation.

CONTEXT: Emotion regulation is a set of processes responsible for controlling, evaluating and adjusting reactions to achieve a goal. Results derived from magnetic resonance imaging agreed on the involvement of frontal and limbic structures in this process. Findings using cognition and physiology interactions are still scarce but suggest a role of alpha rhythm in emotional induction and for theta in regulation. OBJECTIVES AND HYPOTHESES: Our goal was to investigate alpha and theta rhythm during the reappraisal of aversive stimuli. We hypothesized that an implication of alpha rhythm in emotional induction only and an increase in prefrontal theta rhythm positively correlated with successful regulation. METHOD: Twenty-four healthy participants were recorded with 64 EEG electrodes while asked to watch or reappraise negative pictures passively. Theta and alpha rhythms were compared across maintain, decrease and increase regulation conditions, and a source localization estimated the generators. RESULTS: Theta activity was consistently higher in the upregulation than in the maintenance condition (p = .04) for the entire control period, but mainly at the beginning of regulation (1-3 s) for low-theta and later (5-7 s) for high-theta. Moreover, our results confirm that a low-theta generator correlated with mainly the middle frontal gyrus and the anterior dorsal cingulate cortex during upregulation. Theta was sensitive to emotion upregulation, whereas the alpha oscillation was non-sensitive to emotion induction and regulation. CONCLUSION: Theta rhythm was involved explicitly in emotion upregulation processes that occur at a definite time during reappraisal, whereas the alpha rhythm was not altered by emotion induction and regulation.

Clinical Assessment of Judgment in Adults and the Elderly: Development and Validation of the Three Domains of Judgment Test-Clinical Version (3DJT-CV).

(1) Background: This article discusses the first two phases of development and validation of the Three Domains of Judgment Test (3DJT). This computer-based tool, co-constructed with users and capable of being administered remotely, aims to assess the three main domains of judgment (practical, moral, and social) and learn from the psychometric weaknesses of tests currently used in clinical practice. (2) Method: First, we presented the 3DJT to experts in cognition, who evaluated the tool as a whole as well as the content validity, relevance, and acceptability of 72 scenarios. Second, an improved version was administered to 70 subjects without cognitive impairment to select scenarios with the best psychometric properties in order to build a future clinically short version of the test. (3) Results: Fifty-six scenarios were retained following expert evaluation. Results support the idea that the improved version has good internal consistency, and the concurrent validity primer shows that 3DJT is a good measure of judgment. Furthermore, the improved version was found to have a significant number of scenarios with good psychometric properties to prepare a clinical version of the test. (4) Conclusion: The 3DJT is an interesting alternative tool for assessing judgment. However, more studies are needed for its implementation in a clinical context.

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.

Unsupervised Machine Learning Driven Analysis of Verbatims of Treatment-Resistant Schizophrenia Patients Having Followed Avatar Therapy.

(1) Background: The therapeutic mechanisms underlying psychotherapeutic interventions for individuals with treatment-resistant schizophrenia are mostly unknown. One of these treatment techniques is avatar therapy (AT), in which the patient engages in immersive sessions while interacting with an avatar representing their primary persistent auditory verbal hallucination. The aim of this study was to conduct an unsupervised machine-learning analysis of verbatims of treatment-resistant schizophrenia patients that have followed AT. The second aim of the study was to compare the data clusters obtained from the unsupervised machine-learning analysis with previously conducted qualitative analysis. (2) Methods: A k-means algorithm was performed over the immersive-session verbatims of 18 patients suffering from treatment-resistant schizophrenia who followed AT to cluster interactions of the avatar and the patient. Data were pre-processed using vectorization and data reduction. (3): Results: Three clusters of interactions were identified for the avatar's interactions whereas four clusters were identified for the patient's interactions. (4) Conclusion: This study was the first attempt to conduct unsupervised machine learning on AT and provided a quantitative insight into the inner interactions that take place during immersive sessions. The use of unsupervised machine learning could yield a better understanding of the type of interactions that take place in AT and their clinical implications.

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.

Changes in Quality of Life in Treatment-Resistant Schizophrenia Patients Undergoing Avatar Therapy: A Content Analysis.

Avatar Therapy has a significant impact on symptoms, beliefs, and quality of life of patients with treatment-resistant schizophrenia. However, little is known about how these changes are implemented into their lives and to which aspects of their lives these improvements relate. Ten consecutive patients enrolled in an ongoing clinical trial were assessed using semi-guided interviews before as well as three months after Avatar Therapy. These encounters have been recorded and transcribed so that the discourse could be thoroughly analyzed, leading to the generation of an extensive theme grid. As the cases were analyzed, the grid was adapted in a back-and-forth manner until data saturation occurred. The content analysis allowed the identification of nine main themes representing different aspects of the patients' lives, each of which was subdivided into more specific codes. By analyzing the evolution of their frequency, it was observed that, following therapy, patients presented with fewer psychotic symptoms, better self-esteem, more hobbies and projects, and an overall improved lifestyle and mood. Finally, investigating the impact of Avatar Therapy on quality of life allows for a deeper understanding of how people with treatment-resistant schizophrenia can achieve meaningful changes and move towards a certain recovery process.

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.

Dysconnectivity between the anterior insula and the dorsal anterior cingulate cortex during an emotion go/nogo paradigm is associated with aggressive behaviors in male schizophrenia patients.

This study aimed to investigate the association between past-reported violent/aggressive behaviors and brain functional connectivity in male patients suffering from schizophrenia using a task modeling the interaction between negative emotion processing and response inhibition. Forty-four male patients with schizophrenia and twenty-two healthy male controls performed an emotional go/no-go task using angry and neutral faces during a functional magnetic resonance imaging session. Generalized psycho-physiological interaction was conducted to explore task-based functional connectivity and a negative binomial regression was used to evaluate the relationship between neural alterations and violent/aggressive behaviors. Regions involved in response inhibition and emotion regulation, such as the anterior insula, dorsal anterior cingulate cortex (dACC) and dorsolateral prefrontal cortex (DLPFC), were used as seed regions. During emotion-related response inhibition, patients with schizophrenia displayed altered connectivity between the anterior insula and amygdala, the DLPFC and lateral orbitofrontal cortex (OFC), as well as the anterior insula and the dACC when compared to healthy individuals. The latter was negatively associated with aggressive behaviors in participants with schizophrenia (Wald χ2 = 9.51; p < 0.05, p-FDR corrected). Our results highlight alterations in functional connectivity in brain regions involved in cognitive control and emotion processing which are associated with aggressive behaviors in schizophrenia.

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.