Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Depressive Disorders: MDD and Dysthymia01:27

Depressive Disorders: MDD and Dysthymia

564
Depressive disorders are a group of mental health conditions characterized by pervasive feelings of sadness, diminished pleasure in life, and a significant impact on daily functioning. These conditions are most prevalent in individuals during their 30s and affect women at twice the rate of men. Contrary to popular belief, younger individuals are generally more susceptible to these disorders than older adults. Two key types of depressive disorders include Major Depressive Disorder (MDD) and...
564
Depression: Overview01:18

Depression: Overview

741
Depression is a prevalent mental illness marked by persistent sadness and lack of interest in previously enjoyable activities. It can take several forms, including major depression, persistent depressive disorder, and bipolar I and II disorders. Symptoms range from emotional changes like chronic worry to physical changes like sleep disturbances and suicidal thoughts. From a neurobiological perspective, depression is believed to be triggered by abnormalities in the brain's prefrontal cortex,...
741
Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

408
Depressive disorders result from a complex interplay of biological, psychological, and sociocultural factors, each contributing uniquely to the development and persistence of the condition. Understanding these factors provides critical insight into the multifaceted nature of depression.
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
408
  1. Home
  3. Research Domains
  5. Language, Communication And Culture
  7. Cultural Studies
  9. Postcolonial Studies
  11. Speech Analysis For Detecting Depression In Older Adults: A Systematic Review

Speech analysis for detecting depression in older adults: a systematic review

Israel Martínez-Nicolás1, Diego Criado1, Fernando Gordillo1

  • 1Faculty of Psychology, University of Salamanca, Salamanca, Spain.

Frontiers in Psychology
|December 29, 2025

Related Experiment Videos

Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing
06:58

Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing

Published on: January 24, 2020

7.7K
Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression
04:33

Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression

Published on: April 26, 2024

1.2K
An Experimental Paradigm for Measuring the Effects of Ageing on Sentence Processing
04:30

An Experimental Paradigm for Measuring the Effects of Ageing on Sentence Processing

Published on: October 25, 2019

6.0K

View abstract on PubMed

Summary
This summary is machine-generated.

Speech analysis offers a reliable, non-invasive method for detecting depression in older adults. Key speech markers like slower rate and altered pauses show significant diagnostic potential.

Area of Science:

  • Gerontology
  • Psychiatry
  • Speech-Language Pathology

Background:

  • Depression is more common in older adults than the general population.
  • Traditional depression assessments have limitations in older adults, including subjectivity and overlap with aging.
  • Speech analysis presents a promising, objective, non-invasive method for depression assessment in this demographic.

Purpose of the Study:

  • To systematically review speech characteristics associated with depression in older adults.
  • To evaluate the clinical potential of speech analysis for diagnosing depression in this age group.

Main Methods:

  • A systematic literature search was conducted across multiple databases (Medline, CINAHL, PsychINFO, IEEE, Web of Science) for studies published in the last 10 years.
  • Included studies focused on adults over 55 with depression and acoustic speech variables.
Keywords:
acoustic analysiscognitive impairmentdepressionolder adults

Related Experiment Videos

Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing
06:58

Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing

Published on: January 24, 2020

7.7K
Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression
04:33

Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression

Published on: April 26, 2024

1.2K
An Experimental Paradigm for Measuring the Effects of Ageing on Sentence Processing
04:30

An Experimental Paradigm for Measuring the Effects of Ageing on Sentence Processing

Published on: October 25, 2019

6.0K
  • Sixteen studies were selected, with quality assessed using JBI tools and speech parameters extracted.

    • Main Results:

    • Depressed older adults exhibited slower speech rates, increased pause duration and variability, reduced intensity, and altered voice quality.
    • Machine learning models achieved 76-95% accuracy in predicting depression, especially when controlling for age and gender.
    • Findings on fundamental frequency (F0) and formants were inconsistent, with some sex-specific differences observed.

    Conclusions:

    • Speech analysis is a reliable, non-invasive, and cost-effective tool for identifying depression in older adults.
    • Temporal, prosodic, and spectral speech features demonstrate strong diagnostic potential.
    • Further research with larger, diverse samples is needed to validate speech biomarkers as adjuncts to current assessments.
    speech