Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
57,070
result(s) for
"Psychiatry methods."
Sort by:
Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder
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. This section on “Special Populations” is the sixth of six guidelines articles.
Results:
Recent studies inform the treatment of MDD in children and adolescents, pregnant and breastfeeding women, women in perimenopause or menopause, and the elderly. Evidence for efficacy of treatments in these populations is more limited than for the general adult population, however, and risks of treatment in these groups are often poorly studied and reported.
Conclusions:
Despite the limited evidence base, extant data and clinical experience suggest that each of these special populations can benefit from the systematic application of treatment guidelines for treatment of MDD.
Journal Article
Resting state functional brain connectivity in child and adolescent psychiatry: where are we now?
Approaching the 30th anniversary of the discovery of resting state functional magnetic resonance imaging (rsfMRI) functional connectivity, we reflect on the impact of this neuroimaging breakthrough on the field of child and adolescent psychiatry. The study of intrinsic functional brain architecture that rsfMRI affords across a wide range of ages and abilities has yielded numerous key insights. For example, we now know that many neurodevelopmental conditions are associated with more widespread circuit alterations across multiple large-scale brain networks than previously suspected. The emergence of population neuroscience and effective data-sharing initiatives have made large rsfMRI datasets publicly available, providing sufficient power to begin to identify brain-based subtypes within heterogeneous clinical conditions. Nevertheless, several methodological and theoretical challenges must still be addressed to fulfill the promises of personalized child and adolescent psychiatry. In particular, incomplete understanding of the physiological mechanisms driving developmental changes in intrinsic functional connectivity remains an obstacle to further progress. Future directions include cross-species and multimodal neuroimaging investigations to illuminate such mechanisms. Data collection and harmonization efforts that span multiple countries and diverse cohorts are urgently needed. Finally, incorporating naturalistic fMRI paradigms such as movie watching should be a priority for future research efforts.
Journal Article
Clinical guidelines for the management of treatment-resistant depression: French recommendations from experts, the French Association for Biological Psychiatry and Neuropsychopharmacology and the fondation FondaMental
Background
Clear guidance for successive antidepressant pharmacological treatments for non-responders in major depression is not well established.
Method
Based on the RAND/UCLA Appropriateness Method, the French Association for Biological Psychiatry and Neuropsychopharmacology and the fondation FondaMental developed expert consensus guidelines for the management of treatment-resistant depression. The expert guidelines combine scientific evidence and expert clinicians’ opinions to produce recommendations for treatment-resistant depression. A written survey comprising 118 questions related to highly-detailed clinical presentations was completed on a risk-benefit scale ranging from 0 to 9 by 36 psychiatrist experts in the field of major depression and its treatments. Key-recommendations are provided by the scientific committee after data analysis and interpretation of the results of the survey.
Results
The scope of these guidelines encompasses the assessment of pharmacological resistance and situations at risk of resistance, as well as the pharmacological and psychological strategies in major depression.
Conclusion
The expert consensus guidelines will contribute to facilitate treatment decisions for clinicians involved in the daily assessment and management of treatment-resistant depression across a number of common and complex clinical situations.
Journal Article
A primer on the use of machine learning to distil knowledge from data in biological psychiatry
Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely
G
uidelines for
RE
porting
M
achine
L
earning
I
nvestigations in
N
europsychiatry (
GREMLIN
), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (
MLPsych
) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.
Journal Article
Feasibility, satisfaction, and goal attainment in routine telemedicine consultation in child and adolescent psychiatry and psychotherapy
Telehealth services were rapidly adopted during the COVID-19 pandemic, but evidence regarding the effectiveness and feasibility of telehealth services in child and adolescent mental healthcare is sparse. This study aims to investigate feasibility, satisfaction, and goal attainment in video-delivered consultations in routine care child and adolescent psychiatry and psychotherapy. A total of 1046 patients from four university child and adolescent outpatient psychiatric clinics and one university outpatient unit for child and adolescent psychotherapy were screened for study participation. We examined a) the percentage of patients considered eligible for video-delivered consultation, b) clinicians’, parents’ and patients’ satisfaction with video consultation, c) clinicians’ ratings of goal attainment in video consultation, and d) factors associated with satisfaction and goal attainment. 59% of the screening sample (
n
= 621) fulfilled eligibility criteria and were considered eligible for video consultation. A total of 267 patients consented to participate in the study and received a video consultation. Clinicians reported high levels of satisfaction with video consultation and high levels of goal attainment in video consultations, especially for patients scheduled for initial patient assessments. Parents and patients were also highly satisfied with the video consultations, especially if patients had less severe emotional and behavioral problems. The present findings suggest that video consultations are a feasible and well-accepted alternative to in-person consultations in child and adolescent mental health care, especially for children with less severe symptoms and for children in early phases of assessment and treatment. Limitations include the lack of a control group. The study was registered at the German Clinical Trials Registry (DRKS00023525).
Journal Article