Background: The Canadian Network for Mood and Anxiety Treatments (CANMAT) conducted a revision of the 2009 guidelines by updating the evidence and recommendations. The scope of the 2016 guidelines remains the management of major depressive disorder (MDD) in adults, with a target audience of psychiatrists and other mental health professionals. Methods: Using the question-answer format, we conducted a systematic literature search focusing on systematic reviews and meta-analyses. Evidence was graded using CANMAT-defined criteria for level of evidence. Recommendations for lines of treatment were based on the quality of evidence and clinical expert consensus. ''Pharmacological Treatments'' is the third of six sections of the 2016 guidelines. With little new information on older medications, treatment recommendations focus on second-generation antidepressants.Results: Evidence-informed responses are given for 21 questions under 4 broad categories: 1) principles of pharmacological management, including individualized assessment of patient and medication factors for antidepressant selection, regular and

Objective: Suicide is a growing public health concern with a global prevalence of approximately 800,000 deaths per year. The current process of evaluating suicide risk is highly subjective, which can limit the efficacy and accuracy of prediction efforts. Consequently, suicide detection strategies are shifting toward artificial intelligence platforms that can identify patterns within ‘big data’ to generate risk algorithms that can determine the effects of risk (and protective) factors on suicide outcomes, predict suicide outbreaks and identify at-risk individuals or populations. In this review, we summarize the role of artificial intelligence in optimizing suicide risk prediction and behavior management. Methods: This paper provides a general review of the literature. A literature search was conducted in OVID Medline, EMBASE and PsycINFO databases with coverage from January 1990 to June 2019. Results were restricted to peer-reviewed, English-language articles. Conference and dissertation proceedings, case reports, protocol papers and opinion pieces were excluded. Reference lists were also examined for additional articles of relevance. Results: At the individual level, prediction analytics help to identify individuals in crisis to intervene with emotional support, crisis and psychoeducational resources, and alerts for emergency assistance. At the population level, algorithms can identify at-risk groups or suicide hotspots, which help inform resource mobilization, policy reform and advocacy efforts. Artificial intelligence has also been used to support the clinical management of suicide across diagnostics and evaluation, medication management and behavioral therapy delivery. There could be several advantages of incorporating artificial intelligence into suicide care, which includes a time- and resource-effective alternative to clinician-based strategies, adaptability to various settings and demographics, and suitability for use in remote locations with limited access to mental healthcare supports. Conclusion: Based on the observed benefits to date, artificial intelligence has a demonstrated utility within suicide prediction and clinical management efforts and will continue to advance mental healthcare forward.

This review offers a perspective on the question as to whether attention-deficit hyperactivity disorder (ADHD) is being overdiagnosed in adults. Considering underlying causes as well as consequences, we conclude that the diagnosis of adult ADHD should be made cautiously, making use of multiple sources of information, including self-report, clinical interviews, collateral information, childhood documentation, and neuropsychological testing. Routine screening with symptom checklists is insufficient, and stimulant response is diagnostically uninformative. The causes of overdiagnosis may include changes in diagnostic thresholds, poor diagnostic practices, and advertising by the pharmaceutical industry. Overdiagnosis leads to overtreatment, and dramatic increases in prescriptions for adult ADHD during the last decade should arouse concern.