Search

Abstract Current pharmacological agents for depression have limited efficacy in achieving remission. Developing and validating new medications is challenging due to limited biological targets. This study aimed to link electrophysiological data and symptom improvement to better understand mechanisms underlying treatment response. Longitudinal changes in neural oscillations were assessed using resting-state electroencephalography (EEG) data from two Canadian Biomarker Integration Network in Depression studies, involving pharmacological and cognitive behavioral therapy (CBT) trials. Patients in the pharmacological trial received eight weeks of escitalopram, with treatment response defined as ≥ 50% decrease in Montgomery–Åsberg Depression Rating Scale (MADRS). Early (baseline to week 2) and late (baseline to week 8) changes in neural oscillation were investigated using relative power spectral measures. An association was found between an initial increase in theta and symptom improvement after 2 weeks. Additionally, late increases in delta and theta, along with a decrease in alpha, were linked to a reduction in MADRS after 8 weeks. These late changes were specifically observed in responders. To assess specificity, we extended our analysis to the independent CBT cohort. Responders exhibited an increase in delta and a decrease in alpha after 2 weeks. Furthermore, a late (baseline to week 16) decrease in alpha was associated with symptom improvement following CBT. Results suggest a common late decrease in alpha across both treatments, while modulatory effects in theta may be specific to escitalopram treatment. This study offers insights into electrophysiological markers indicating a favorable response to antidepressants, enhancing our comprehension of treatment response mechanisms in depression.

Abstract Monitoring sleep and activity through wearable devices such as wrist-worn actigraphs has the potential for long-term measurement in the individual’s own environment. Long periods of data collection require a complex approach, including standardized pre-processing and data trimming, and robust algorithms to address non-wear and missing data. In this study, we used a data-driven approach to quality control, pre-processing and analysis of longitudinal actigraphy data collected over the course of 1 year in a sample of 95 participants. We implemented a data processing pipeline using open-source packages for longitudinal data thereby providing a framework for treating missing data patterns, non-wear scoring, sleep/wake scoring, and conducted a sensitivity analysis to demonstrate the impact of non-wear and missing data on the relationship between sleep variables and depressive symptoms. Compliance with actigraph wear decreased over time, with missing data proportion increasing from a mean of 4.8% in the first week to 23.6% at the end of the 12 months of data collection. Sensitivity analyses demonstrated the importance of defining a pre-processing threshold, as it substantially impacts the predictive value of variables on sleep-related outcomes. We developed a novel non-wear algorithm which outperformed several other algorithms and a capacitive wear sensor in quality control. These findings provide essential insight informing study design in digital health research.

Abstract Background Major depressive disorder (MDD) is a recurrent psychiatric condition that presents challenges in responding to treatment and achieving long-term remission. To improve outcomes, a shared decision-making treatment approach with patient and healthcare practitioner (HCP) engagement is vital. PatientsLikeMe (PLM), a peer community of patients, provides information on MDD, symptoms, and treatment through forums and resources, helping patients stay engaged in their treatment journey. Data on PLM can be harnessed to gain insights into patient perspectives on MDD symptom management, medication switches, and treatment goals and measures. Methods This ongoing, decentralized, longitudinal, observational, prospective study is being conducted using the PLM platform in two parts, enrolling up to 500 patients with MDD in the United States aged ≥ 18 years to compare vortioxetine with other monotherapy antidepressants. The first qualitative component consists of a webinar and discussion forum with PLM community members with MDD, followed by a pilot for functionality testing to improve the study flow and questions in the quantitative survey. The quantitative component follows on the PLM platform, utilizing patient-reported assessments, over a 24-week period. Three surveys will be conducted at baseline and weeks 12 and 24 to collect data on patient global impression of improvement, depression severity, cognitive function, quality of life (QoL) and well-being, medication satisfaction, emotional blunting, symptoms of anhedonia and resilience, as well as goal attainment. Quantitative results will be compared between groups. The qualitative component is complete; patient recruitment is underway for the quantitative component, with results expected in late 2023. Discussion These results will help HCPs understand patient perspectives on the effectiveness of vortioxetine versus other monotherapy antidepressants in alleviating symptoms of MDD and improvements in QoL. Data from the PLM platform will support a patient goal-based treatment approach, as results can be shared by patients with their HCPs, providing them with insights on patient-centric goals, treatment management and adherence, as well as allowing them to observe changes in patient-related outcomes scores. Findings from the study will also help to optimize the PLM platform to build scalable solutions and connectivity within the community to better serve patients with MDD.

Background: The objective of this paper is to discuss perceived clinical utility and impact on physician-patient relationship of a novel, artificial-intelligence (AI) enabled clinical decision support system (CDSS) for use in treating adults with major depression. Methods: A single arm, naturalistic follow-up study aimed at assessing the acceptability and useability of the software. Patients had a baseline appointment, followed by a minimum of two appointments with the CDSS. Study exit questionnaires and interviews were conducted to assess perceived clinical utility, impact on patient-physician relationship, and understanding and trust. 7 physicians and 17 patients, of which 14 completed, consented to participate. Results: 86 % of physicians (6/7) felt the information provided by the CDSS provided more comprehensive understanding of patient situations. 71 % (5/7) felt the information was helpful. 86 % of physicians (6/7) reported the AI/predictive model was useful when deciding treatment. 62 % of patients (8/13) reported improved care due to the tool, and 46 %(6/13) reported a significantly or somewhat improved physician-patient relationship 54 % reported no change. 71 % of physicians (5/7) and 62 % of patients (8/13) rated trusting the tool. Limitations: Small sample size and treatment changes prior to CDSS introduction limits ability to verify impact on outcomes. Conclusions: Qualitative results from 12 patient exit interviews are analyzed and presented. Findings suggest physicians perceived the tool as useful in conducting appointments and used it while deciding treatment. Physicians and patients generally found the tool trustworthy, and it may have positive effects on physician-patient relationships. (Study identifier: NCT04061642).

Abstract Background Electroconvulsive therapy (ECT) is a procedural treatment that is potentially life-saving for some patients with severe psychiatric illness. At the start of the global coronavirus disease 2019 (COVID-19) pandemic, ECT practice was remarkably disrupted, putting vulnerable individuals at increased risk of symptom exacerbation and death by suicide. This study aimed to capture the self-reported experiences of psychiatrists based at healthcare facilities across Canadian provinces who were delivering ECT treatments during the first phase of the COVID-19 pandemic (i.e., from mid-March 2020 to mid-May 2020). Methods A multidisciplinary team of experts developed a survey focusing on five domains: ECT unit operations, decision-making, hospital resources, ECT procedure, and mitigating patient impact. Responses were collected from psychiatrists providing ECT at 67 ECT centres in Canada, grouped by four geographical regions (Ontario, Quebec, Atlantic Canada, and Western Canada). Results Clinical operations of ECT programs were disrupted across all four regions – however, centres in Atlantic Canada were able to best preserve outpatient and maintenance care, while centres in Western Canada were able to best preserve inpatient and acute care. Similarly, Atlantic and Western Canada demonstrated the best decision-making practices of involving the ECT team and clinical ethicists in the development of pandemic-related guidelines. Across all four regions, ECT practice was affected by the redeployment of professionals, the shortage of personal protective equipment, and the need to enforce social distancing. Attempts to introduce modifications to the ECT delivery room and minimize bag-valve-mask ventilation were consistently reported. All four regions developed a new patient prioritization framework, and Western Canada, notably, aimed to provide ECT to only the most severe cases. Conclusions The results suggest that ECT provision was disproportionately affected across different parts of Canada. Possible factors that could explain these interregional differences include population, distribution of urban vs. rural areas, pre-pandemic barriers in access to ECT, number of cases, ability to control the spread of infection, and the general reduction in physicians’ activities across different areas of health care. Studying these factors in the future will inform how medical centres should respond to public health emergencies and pandemic-related circumstances in the context of procedural treatments.

BackgroundThe use of novel rapid-acting antidepressants for psychiatric disorders is expanding. The web-based Ketamine and Related Compounds International Journal Club (KIJC) was created during the COVID-19 pandemic by UK academic psychiatrists and trainees for interested global professionals to discuss papers related to the topic of ketamine for the treatment of psychiatric disorders. The KIJC aimed to facilitate bidirectional discussions, sharing of ideas, and networking among participants. ObjectiveThe aim of this study is a preliminary evaluation of the journal club’s format for satisfaction and impact after the first year of running. MethodsA website, email, and word of mouth were used for recruitment. The journal club was held twice per month using videoconferencing software in 3 parts: a 20-minute presentation, a 15-minute chaired question and answer session, and a 25-minute informal discussion with participants’ cameras on. The first 2 parts were recorded and uploaded to the website alongside links to the corresponding papers. In total, 24 speakers presented from 8 countries, typically within 2 (SD 2) months of publication. The average attendance was 51 (SD 20) audience members, and there were 63 (SD 50) views of each subsequent recording. Two anonymous web-based cross-sectional surveys were conducted from November 2021 to February 2022, one for speakers and another for audience members, separately. Various survey statements, 14 for speakers and 12 for the audience, were categorized according to satisfaction and impact, alongside obtaining participants’ primary career roles and requesting optional written feedback. Responses were compared between both groups and analyzed, including an inductive thematic analysis and a summary of lessons learned. ResultsA total of 30 survey responses were obtained, demonstrating overall agreement with the statements. In total, 12 (50%) out of 24 speakers and 18 (35%) out of an average of 51 (SD 20) audience members regarded the journal club’s format as satisfying and impactful. The majority (26/30, 87%) of respondents identified as clinicians (9/30, 30%), researchers (9/30, 30%), and clinician-researchers (8/30, 27%). Additionally, 11 (37%) of the 30 respondents also provided optional written feedback: 3 (10%) speakers and 8 (27%) audience members. From the written feedback, 5 main themes were derived: engagement with the journal club, desire for active participation, improving the platform, positive learning experiences, and suggestions for future sessions. ConclusionsThe journal club successfully reached its intended audience and developed into a web-based community. The majority of the participants were satisfied with the format and found it impactful. Overall, the journal club appears to be a valuable tool for knowledge sharing and community building in the field of ketamine use for the treatment of psychiatric disorders. A larger sample size and additional testing methods are required to support the generalizability of the journal club’s format.

Abstract Cytochrome P450 drug-metabolizing enzymes may contribute to interindividual differences in antidepressant outcomes. We investigated the effects of CYP2C19 and CYP2D6 gene variants on response, tolerability, and serum concentrations. Patients (N = 178) were treated with escitalopram (ESC) from weeks 0–8 (Phase I), and at week 8, either continued ESC if they were responders or were augmented with aripiprazole (ARI) if they were non-responders (

Pharmacotherapies for the treatment of major depressive disorder were serendipitously discovered almost seven decades ago. From this discovery, scientists pinpointed the monoaminergic system as the primary target associated with symptom alleviation. As a result, most antidepressants have been engineered to act on the monoaminergic system more selectively, primarily on serotonin, in an effort to increase treatment response and reduce unfavorable side effects. However, slow and inconsistent clinical responses continue to be observed with these available treatments. Recent findings point to the glutamatergic system as a target for rapid acting antidepressants. Investigating different cohorts of depressed individuals treated with serotonergic and other monoaminergic antidepressants, we found that the expression of a small nucleolar RNA, SNORD90, was elevated following treatment response. When we increased Snord90 levels in the mouse anterior cingulate cortex (ACC), a brain region regulating mood responses, we observed antidepressive-like behaviors. We identified neuregulin 3 (NRG3) as one of the targets of SNORD90, which we show is regulated through the accumulation of N6-methyladenosine modifications leading to YTHDF2-mediated RNA decay. We further demonstrate that a decrease in NRG3 expression resulted in increased glutamatergic release in the mouse ACC. These findings support a molecular link between monoaminergic antidepressant treatment and glutamatergic neurotransmission.

Abstract Background Major depressive disorder (MDD) is the leading cause of disability worldwide. Response to pharmacologic treatment is generally evaluated by traditional clinician- and patient-reported rating scales. Assessing therapeutic efficacy using the Goal Attainment Scale offers a complementary measure that focuses on recovery-oriented outcomes that patients consider valuable and vital to their well-being. This study aimed to examine outcomes using the Goal Attainment Scale adapted for depression (GAS-D). Methods A phase 4, single-arm, open-label, multicenter study enrolled patients with MDD who were switching antidepressant medication. Patients received vortioxetine 10–20 mg over 12 weeks. Three specific, measurable, attainable, relevant, and time-bound goals were collaboratively set by patients with their clinicians. One goal was determined by the patient’s self-defined objectives; 2 were related to predefined domain categories. Prespecified domains included psychological, motivational, emotional, physical/functional, and cognitive categories. The primary endpoint was the proportion of patients who achieved a GAS-D score ≥ 50 at week 12. Secondary and exploratory endpoints included changes from baseline in several clinical and patient-reported measures of depression and cognitive function. Safety and tolerability were also assessed. Results At week 12, of the 122 adults participating in the study, 57.8% achieved a GAS-D score ≥ 50. Depression severity, cognitive function, cognitive performance, well-being, employment, and quality of life also significantly improved. Treatment response and remission rates were 65 and 40%, respectively. Vortioxetine was well tolerated, with adverse events consistent with product labeling. Conclusions A majority of patients with MDD switching to vortioxetine achieved their treatment goals, including improvement in specific functional outcomes relating to physical and emotional goals, as assessed by the GAS-D and standard patient- and clinician-reported measures. When assayed for convergent validity in a separate analysis, changes in goal scores on the GAS-D were statistically significantly correlated with multiple commonly used clinical measures of depression assessed in this study. The GAS-D approach provides a new patient-centric paradigm for the collaborative development and assessment of progress toward meaningful treatment goals, contributing to a comprehensive evaluation of treatment outcomes in patients with MDD. Longer studies against a control intervention are justified. Trial registration ClinicalTrials.gov identifier: NCT02972632 . Registered 21 November 2016.

Abstract Identifying biomarkers of antidepressant response may advance personalized treatment of major depressive disorder (MDD). We aimed to identify longitudinal changes in gene expression associated with response to antidepressants in a sample of MDD patients treated with escitalopram. Patients (N = 153) from the CAN-BIND-1 cohort were treated for 8 weeks, and depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale at 0, 2, 4, 6, and 8 weeks. We identified three groups of patients according to response status: early responders (22.9%), later responders (32.0%), and nonresponders (45.1%). RNA sequencing was performed in blood obtained at weeks 0, 2, and 8. RNA expression was modeled using growth models, and differences in the longitudinal changes in expression according to response were investigated using multiple regression models. The expression of RNAs related to response was investigated in the brains of depressed individuals, as well as in neuronal cells in vitro. We identified four RNAs (CERCAM, DARS-AS1, FAM228B, HBEGF) whose change over time was independently associated with a response status. For all except HBEGF, responders showed higher expression over time, compared to nonresponders. While the change in all RNAs differentiated early responders from nonresponders, changes in DARS-AS1 and HBEGF also differentiated later responders from nonresponders. Additionally, HBEGF was downregulated in the brains of depressed individuals, and increased in response to escitalopram treatment in vitro. In conclusion, using longitudinal assessments of gene expression, we provide insights into biological processes involved in the intermediate stages of escitalopram response, highlighting several genes with potential utility as biomarkers of antidepressant response.

Background: Although there is substantial research demonstrating the effects of duration and quality of sleep on outcomes in major depressive disorder (MDD), there is little research examining whether rhythmicity of sleep can also affect outcomes in MDD. The objective of our study was to investigate the relationship between rhythmicity of sleep and clinical outcomes in MDD Methods: The prospective study (N = 208) included MDD patients treated with escitalopram for 8-weeks. Rhythmicity of sleep was assessed with Biological Rhythms Interview for Assessment in Neuropsychiatry (BRIAN) at baseline and after 8-weeks. Depression was assessed with Montgomery-Asberg Depression Rating Scale (MADRS) and Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) throughout 8-weeks. Outcomes were depression severity over 8-weeks and remission of depression after 8-weeks. Mixed effect models (MMRMs) and logistic regression models were conducted Results: Baseline BRIAN sleep score predicted MADRS (Adjusted B = 0.34;95%CI:0.01–0.66,p = 0.04) and QIDS-SR (Adjusted B = 0.19;95%CI:0.02–0.36,p = 0.03) scores over time in MMRMs. BRIAN falling asleep (Adjusted B = 0.44;95%CI:0.01–0.86,p = 0.04) and switching off (Adjusted B = 0.50;95%CI:0.03–0.97,p = 0.04) items predicted QIDS-SR scores over time. BRIAN sleep score predicted remission with MADRS (Adjusted OR:0.87;95%CI:0.76–0.99) and QIDS-SR (Adjusted OR:0.76;95%CI:0.64–0.90) in logistic regression models. BRIAN falling asleep item predicted remission with MADRS (Adjusted OR:0.71;95%CI:0.64–0.90) and QIDS-SR (Adjusted OR:0.62;95%CI:0.42–0.92). BRIAN switching off item predicted remission with QIDS-SR (Adjusted OR:0.62;95%CI:0.40–0.96) Limitations: Did not examine for circadian rhythm sleep-wake disorders or social conditions that causes circadian disturbances (e.g., shiftwork) Conclusions: A disturbed rhythmicity of sleep, particularly in the ability to switch off when resting and falling asleep, may increase the risk of poor clinical outcomes in MDD.

Abstract Objective To report side effect frequency and severity in patients with major depressive disorder (MDD) receiving escitalopram and aripiprazole adjunctive therapy and to examine whether pretreatment anxious depression is associated with the number and presence of specific side effects. Methods 188 of the 211 trial participants provided information on side effects during treatment with escitalopram (10–20 mg) for 8 weeks, and nonresponders received further augmentation on aripiprazole (2–10 mg) adjunctive therapy for another 8 weeks, whereas responders remained on escitalopram. Participants completed the Toronto Side Effects Scale at weeks 2, 4, 10, and 12. Covariate‐adjusted negative binomial regression and Wilcoxon tests examined the association between anxious depression (GAD‐7 ≥ 10) and number of side effects. Covariate‐adjusted logistic regression and chi‐square tests explored the association between anxious depression and specific side effects. Results For both therapies, the most frequent side effects were also the most severe. They mostly related to the central nervous system (CNS) (i.e., drowsiness and nervousness). Between baseline and week 2, the number of side effects participants experienced (incidence rate ratio [IRR] = 1.38, p = .010) or had trouble with (IRR = 1.34, p = .026) was significantly higher among those with anxious depression for escitalopram but not adjunctive aripiprazole. Further, odds of experiencing and having trouble with nervousness and agitation were also significantly higher in anxious depression for escitalopram only (p

The Ontario Brain Institute's “Brain-CODE” is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).

Abstract Background Previous research suggests that the 17-item Hamilton Depression Rating Scale (HAM-D17) is less sensitive in detecting differences between active treatment and placebo for major depressive disorder (MDD) than is the HAM-D6 scale, which focuses on six core depression symptoms. Whether HAM-D6 shows greater sensitivity when comparing two active MDD treatment arms is unknown. Methods This post hoc analysis used data from the intent-to-treat (ITT) cohort (N = 1541) of the Genomics Used to Improve DEpression Decisions (GUIDED) trial, a rater- and patient-blinded randomized controlled trial. GUIDED compared combinatorial pharmacogenomics-guided care with treatment as usual (TAU) in patients with MDD. Percent of symptom improvement, response rate and remission rate from baseline to week 8 were evaluated using both scales. Analyses were performed for the full cohort and for the subset of patients who at baseline were taking medications predicted by the test to have moderate or significant gene-drug interactions. A Mokken scale analysis was conducted to compare the homogeneity of HAM-D17 with that of HAM-D6. Results At week 8, the guided-care arm demonstrated statistically significant benefit over TAU when the HAM-D6 (∆ = 4.4%, p = 0.023) was used as the continuous measure of symptom improvement, but not when using the HAM-D17 (∆ = 3.2%, p = 0.069). Response rates increased significantly for guided-care compared with TAU when evaluated using both HAM-D6 (∆ = 7.0%, p = 0.004) and HAM-D17 (∆ = 6.3%, p = 0.007). Remission rates also were significantly greater for guided-care versus TAU using both measures (HAM-D6 ∆ = 4.6%, p = 0.031; HAM-D17 ∆ = 5.5%, p = 0.005). Patients in the guided-care arm who at baseline were taking medications predicted to have gene-drug interactions showed further increased benefit over TAU at week 8 for symptom improvement (∆ = 7.3%, p = 0.004) response (∆ = 10.0%, p = 0.001) and remission (∆ = 7.9%, p = 0.005) using HAM-D6. All outcomes showed continued improvement through week 24. Mokken scale analysis demonstrated the homogeneity and unidimensionality of HAM-D6, but not of HAM-D17, across treatment arms. Conclusions The HAM-D6 scale identified a statistically significant difference in symptom improvement between combinatorial pharmacogenomics-guided care and TAU, whereas the HAM-D17 did not. The demonstrated utility of pharmacogenomics-guided treatment over TAU as detected by the HAM-D6 highlights its value for future biomarker-guided trials comparing active treatment arms. Trial registration Clinicaltrials.gov: NCT02109939. Registered 10 April 2014.

Abstract Graphical Abstract

Abstract Objective This work was undertaken to define and characterize the role of currently available somatic treatments in psychiatry in either increasing or reducing the risk for suicide. Methods Members of the Suicide Prevention Task Group of the National Network of Depression Centers performed a literature review of somatic treatments known to increase or reduce the risk for suicide. The reviews ventured to include all relevant information about the risk for both suicide ideation and completed suicides. Results Lithium and clozapine are the only two somatic treatments that have high‐quality data documenting their antisuicide effects in mood disorders and schizophrenia, respectively. Lithium discontinuation is also associated with increased suicide risk. Ketamine and esketamine may have a small, but immediate, antisuicide effect. Despite the recent Food and Drug Administration approval of esketamine use in depressed suicidal patients, the small disproportional overrepresentation of suicide in subjects who had received esketamine versus placebo (3 vs. 0 among > 3500 subjects) requires ongoing evaluation. The purported antisuicide effect of electroconvulsive therapy is based on low‐quality data. The effect of antidepressants is not at all clear. There appears to be direct evidence for antidepressants increasing suicidal ideation and the risk for suicide over the short‐term in young people, but indirect (low quality) evidence that antidepressants reduce suicide risk over the long term. Conclusions Clinicians have an expanding pharmacopeia to address suicide potential in their patients. Some of the agents with documented antisuicide effects may also increase suicidality under specific circumstances.

BackgroundApproximately two-thirds of patients with major depressive disorder do not achieve remission during their first treatment. There has been increasing interest in the use of digital, artificial intelligence–powered clinical decision support systems (CDSSs) to assist physicians in their treatment selection and management, improving the personalization and use of best practices such as measurement-based care. Previous literature shows that for digital mental health tools to be successful, the tool must be easy for patients and physicians to use and feasible within existing clinical workflows. ObjectiveThis study aims to examine the feasibility of an artificial intelligence–powered CDSS, which combines the operationalized 2016 Canadian Network for Mood and Anxiety Treatments guidelines with a neural network–based individualized treatment remission prediction. MethodsOwing to the COVID-19 pandemic, the study was adapted to be completed entirely remotely. A total of 7 physicians recruited outpatients diagnosed with major depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Patients completed a minimum of one visit without the CDSS (baseline) and 2 subsequent visits where the CDSS was used by the physician (visits 1 and 2). The primary outcome of interest was change in appointment length after the introduction of the CDSS as a proxy for feasibility. Feasibility and acceptability data were collected through self-report questionnaires and semistructured interviews. ResultsData were collected between January and November 2020. A total of 17 patients were enrolled in the study; of the 17 patients, 14 (82%) completed the study. There was no significant difference in appointment length between visits (introduction of the tool did not increase appointment length; F2,24=0.805; mean squared error 58.08; P=.46). In total, 92% (12/13) of patients and 71% (5/7) of physicians felt that the tool was easy to use; 62% (8/13) of patients and 71% (5/7) of physicians rated that they trusted the CDSS. Of the 13 patients, 6 (46%) felt that the patient-clinician relationship significantly or somewhat improved, whereas 7 (54%) felt that it did not change. ConclusionsOur findings confirm that the integration of the tool does not significantly increase appointment length and suggest that the CDSS is easy to use and may have positive effects on the patient-physician relationship for some patients. The CDSS is feasible and ready for effectiveness studies. Trial RegistrationClinicalTrials.gov NCT04061642; http://clinicaltrials.gov/ct2/show/NCT04061642

Abstract The need for patient-centered care has become a focal point of healthcare improvement initiatives. Shared decision making—in which patients and clinicians communicate about various treatment options and goals and patient input is considered when making treatment decisions—has been associated with improved health and quality of life. A method of treatment evaluation allowing incorporation of patient-specific goals and perspectives is of increasing interest to healthcare providers, payers, and patients. An approach that allows incorporation of shared goal setting is possible via use of an instrument called the Goal Attainment Scale (GAS). This scale provides the structure for measuring progress toward treatment goals set through patient–clinician collaboration. The goal attainment approach has been used as a primary outcomes measure in numerous studies but not in major depressive disorder (MDD). As MDD is a complex, multidimensional disorder affecting each patient differently, the use of GAS methodology is a relevant framework for setting personalized meaningful treatment goals. Initial research into the feasibility of using the GAS in MDD (GAS-D) to measure patient-centric outcomes that may be neglected when more traditional scales are used has been encouraging. The objective of this Commentary is to provide background and rationale for implementation of the GAS-D in clinical practice. Funding Takeda Pharmaceutical Company, Ltd., and Lundbeck LLC.

Abstract Background Ensuring equitable and timely access to Cognitive Behaviour Therapy (CBT) is challenging within Canada’s service delivery model. The current study aims to determine acceptability and effectiveness of 4-session, large, Cognitive Behaviour Therapy with Mindfulness (CBTm) classes. Methods A retrospective chart review of adult outpatients (n = 523) who attended CBTm classes from 2015 to 2016. Classes were administered in a tertiary mental health clinic in Winnipeg, Canada and averaged 24 clients per session. Primary outcomes were (a) acceptability of the classes and retention rates and (b) changes in anxiety and depressive symptoms using Generalized Anxiety Disorder 7-item (GAD-7) and Patient Health Questionnaire 9-item (PHQ-9) scales. Results Clients found classes useful and > 90% expressed a desire to attend future sessions. The dropout rate was 37.5%. A mixed-effects linear regression demonstrated classes improved anxiety symptoms (GAD-7 score change per class = − 0.52 [95%CI, − 0.74 to − 0.30], P

Background Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction. Aims Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician–patient interaction. Method Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback. Results All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician–patient interaction. Conclusions The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician–patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.

Antidepressant drugs are the most common treatment for depressive episodes but only a fraction of patients experience adequate response. Here the authors find dysregulation of miRNAs in peripheral blood samples from depressed patients after antidepressant treatment, and show that the miRNAs are regulators of psychiatrically relevant signalling pathways.

Introduction: Continuing Medical Education (CME) has been considered as a lifelong commitment for doctors to provide the optimal care for patients. Despite a long history of creating CME programs, outcomes are far from ideal. The present qualitative study aims to clarify the barriers affecting effectiveness of the CME programs in Iran based on the experiences of general practitioners. Methods: Sixteen general practitioners were recruited to participate in in-depth interviews and field observations concerning experiences with CME. The study was performed using a qualitative content analysis method. The codes, categories and themes were explored through an inductive process in which the researchers moved from specific to general. Results: The participants’ experiences identified a number of barriers, particularly insufficient interaction with the instructors; additional problems included the teachers’ use of an undifferentiated approach; unreal and abstract CME; and ignorance of the diverse reasons to participate in CME. Conclusion: Based on the study results, there are multiple barriers to effective implementation of CME in Iran. The key barriers include insufficient interaction between the trainees and providers, which must be considered by other stakeholders and program designers. Such interactions would facilitate improved program design, invite more specific tailoring of the education to the participants, allow for more effective educational methods and set the stage for outcome evaluation from the learners actually applying their new knowledge in practice. Replication of these findings with another sample would improve confidence in these recommendations, but these findings are broadly consistent with findings in the educational literature on improving the efficacy of CME.