2023 - Improve Data Reliability from MADRS and HAM-D Assessments in Clinical Trials: Scientific and Operational Recommendations
Date2023-10-18
Deadline2023-10-18
VenueWebinar, USA - United States
KeywordsClinical Trials; Clinical Research; Depression
Topics/Call fo Papers
For clinical trials in mood disorders, two of the most widely leveraged and long-standing assessments of depression severity are the Montgomery–Åsberg depression rating scale (MADRS) and the Hamilton depression rating scale (HDRS or HAM-D). Both are complex clinician-administered assessments. When used in clinical trials, it is always recommended that raters follow the associated structured clinical interview guides for each scale — structured interview guide for MADRS (SIGMA) and structured interview guide for HDRS (SIGH-D). If not administered properly, the nuances in these scales can lead to data issues around inter-rater reliability and cause potential risks in the validity of study data such as in response to efficacy and safety questions.
In this webinar, three clinical trial experts with years of experience supporting and utilizing these psychiatric measures will share both scientific and operational considerations to achieve high-quality data collection from MADRS and HAM-D administrations.
Join this webinar and learn from their experiences about what makes an excellent rater for these scales, how to take a targeted and tailored rater training approach based on common administration errors, and ways to catch rater drift before it becomes problematic. The presenters will also describe an approach called central rating that can increase quality and consistency while reducing site burden and heightening diversity.
In this webinar, three clinical trial experts with years of experience supporting and utilizing these psychiatric measures will share both scientific and operational considerations to achieve high-quality data collection from MADRS and HAM-D administrations.
Join this webinar and learn from their experiences about what makes an excellent rater for these scales, how to take a targeted and tailored rater training approach based on common administration errors, and ways to catch rater drift before it becomes problematic. The presenters will also describe an approach called central rating that can increase quality and consistency while reducing site burden and heightening diversity.
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Last modified: 2023-08-28 23:55:41