WeChat Mini Program
Old Version Features

Challenges Related to the Implementation of Measurement-Based Care for the Treatment of Major Depressive Disorder: A Feasibility Study.

Emytis Tavakoli, Angela Xiang, Mohamed I Husain,Daniel M Blumberger,Stefan Kloiber,Daniel J Mueller,Abigail Ortiz, Athina Perivolaris,Benoit H Mulsant

Pharmacopsychiatry(2025)

Cited 0|Views2
Abstract
Measurement-based care (MBC) involves systematically assessing patients' symptoms and adverse events using standardized scales to guide treatment. While MBC has been shown to enhance the quality of care and outcomes in the pharmacotherapy of major depressive disorder (MDD), it is still rarely used in clinical practice. In this study, the feasibility of implementing MBC was assessed for patients with MDD seen in a large outpatient psychiatry clinic.Adults diagnosed with MDD were assessed at baseline and during a 12-week follow-up by phone or via emailed links with: the 9-item Patient Health Questionnaire (PHQ-9), an adverse effect rating scale, and a published suicide risk management protocol (SRMP). Antidepressants were recommended based on preferences expressed by the participant and treating psychiatrist; dosages were adjusted by the treating psychiatrist based on symptomatic improvement and adverse events.Over 2 years, 52 (21.2%) of 246 patients referred to the study were enrolled, 28 (53.8%) completed all assessments at all follow-up visits, 45 (87.0%) participants were prescribed one of the recommended antidepressants, and 22 (42.3%) remitted. Of the 27 participants presenting with suicidal ideation, 18 (66.6%) experienced a full resolution of these ideations.These findings highlight the challenges in implementing MBC for the pharmacotherapy of MDD and confirm some barriers to its broad adoption in clinical practice. The study also highlights its benefits in the selected group of patients who engage in MBC. Future studies need to continue to explore innovative ways to facilitate its broader implementation.
More
Translated text
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined