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Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression
Published on: April 26, 2024
Outcome in depression (II): beyond the Hamilton Depression Rating Scale
Koen Demyttenaere1, Glenn Kiekens1, Ronny Bruffaerts1
1Department of Neurosciences, Faculty of Medicine, University Psychiatric Center KU Leuven and Research Group Psychiatry, University of Leuven, Leuven, Belgium.
Background:
The Leuven Affect and Pleasure Scale (LAPS) was developed as an outcome measure in major depressive disorder (MDD) tha treflects patient treatment expectations. The present report investigates whether the LAPS negative affect, the LAPS positive affect, and the LAPS hedonic tone have added value on top of the Hamilton Depression Rating Scale (HAMD) in explaining generic as well as patient-centered outcomes.
Methods:
A total of 109 outpatients with Diagnostic and Statistical Manual of Mental Disorders, fifth edition, criteria for MDD were assessed over 8 weeks of antidepressant treatment. At baseline and after 2, 4, and 8 weeks, the LAPS, HAMD, Snaith-Hamilton Pleasure Scale (SHAPS), Positive and Negative Affect Scale (PANAS), and Sheehan Disability Scale were administered. The Clinical Global Impression of Improvement (CGI-I) and the Patient Global Impression of Improvement (PGI-I) were also administered at endpoint.
Results:
Changes in LAPS negative affect, LAPS positive affect, and LAPS hedonic tone explain 14% of the additional variance in CGI-I, 21% in PGI-I, 37% in cognitive functioning, 32% in overall functioning, 31% in "my life is meaningful," and 45% in "I feel happy." Compared to standard scales (PANAS and SHAPS), the LAPS negative affect, LAPS positive affect, and LAPS hedonic tone differentiate better between different levels of CGI-I or PGI-I.
Conclusions:
The LAPS has added value (on top of the HAMD) in explaining changes in both generic outcomes (CGI-I/PGI-I) and patient-centered dimensions. The LAPS negative and positive affects and the LAPS hedonic tone differentiate CGI-I and PGI-I scores better than corresponding scales supposed to cover the same domains.
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