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Affective Prosody and Depression After Stroke: A Pilot Study.

Marie Villain1, Charlotte Cosin2, Bertrand Glize1

  • 1From the Université de Bordeaux, INCIA, CNRS UMR5287, Talence, France (M.V., C.C., J.S., I.S., W.M.); Ecole Pratique des Hautes Etudes, Paris, France (M.V., C.C., J.S.); CHU Bordeaux, Pôle de Neurosciences Cliniques, Hôpital Pellegrin, Bordeaux, France (B.G., I.S.); and CESP, Université Paris Sud, Institut Mutualiste Montsouris, Paris, France (S.B.).

Stroke
|August 11, 2016
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Summary

Early voice changes like voice breaks and shimmer can predict poststroke depression (PSD). This finding offers a new way to identify individuals at higher risk for depression after a stroke.

Keywords:
anxietydepressiondiscriminant analysisquality of lifestroke

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Area of Science:

  • Neurology
  • Psychiatry
  • Speech-Language Pathology

Background:

  • Poststroke depression (PSD) is a common complication impacting stroke survivors' quality of life and functional recovery.
  • Altered affective prosody, the emotional tone of voice, is observed in individuals with major depression.
  • Identifying predictive markers for PSD is crucial for timely intervention and improved patient outcomes.

Purpose of the Study:

  • To identify specific prosodic voice markers that can predict the development of poststroke depression.
  • To investigate the relationship between baseline vocal characteristics and the onset of PSD.

Main Methods:

  • Patient voices were recorded at baseline and three months post-stroke.
  • Prosodic parameters including fundamental frequency, voice breaks, and shimmer were extracted.
  • Depression and anxiety symptoms were assessed at three months to diagnose PSD.

Main Results:

  • 22.5% of the 49 included patients developed PSD within three months.
  • A significant decrease in fundamental frequency was noted in patients who developed PSD.
  • Discriminant analysis revealed that initial voice breaks and shimmer were strong predictors of subsequent PSD.

Conclusions:

  • Early alterations in affective prosody are linked to an increased risk of developing PSD.
  • This physiological approach to voice analysis offers a novel, objective method for predicting PSD.
  • This method may overcome limitations of traditional clinical assessments for PSD prediction.