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Completed

NCT Number: NCT04420793

Voice Changes During ECT

Depressed patients talk differently when they are depressed compared to when they are well. But it is hard to actually measure what the differences are. The study team will record voice samples from patients with mood disturbances, like depression, over the course of their receiving an electroconvulsive therapy (ECT) series. The study team will try and measure or quantify exactly what has changed in their speech and voice. The study team will choose ECT as it is one of the most effective and rapid treatment for depression. The study team will use a service provided by a company, NeuroLex, who has complex computer programs (artificial intelligence, AI) to analyze the voice samples.

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Key information

Conditions

Unipolar Depression Bipolar Depression Bipolar Disorder Bipolar Disorder, Manic Bipolar and Related Disorders Depressive Disorder Mental Disorders Mood Disorders

Age range

18 year–89 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Medical University of South Carolina

Charleston, South Carolina, 29425, United States

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Any candidate for electroconvulsive therapy who is about to initiate their ECT course at Medical University of South Carolina (MUSC) for a clinically indicated diagnosis
  • Age 18 to 90 years old
  • Able to speak and understand English
  • Able to give consent to participate in the study

Exclusion criteria

  • Any medical condition that limits the ability to speak or speak clearly, for example a history of head and/or neck cancer, spinal cord injury affecting speech, amyotrophic lateral sclerosis, or those with absence of critical anatomical structures involved in speech.
  • Any voice characteristics that may limit the ability to speak English clearly including speech impediments or heavy accents (as evidenced by the pronunciation of the English language in such a non-standard way that research staff). If study staff have significant difficulty understanding the participant's responses in conversation, this may warrant exclusion.
  • Patients who are receiving ECT by involuntary order, by order of their guardian, or by a court order, as evidenced by patient report or brief chart review.
  • Patients who elect to not receive their full course of ECT at MUSC.

Treatment and study plan

Questionnaire

Other

3 voice recording tasks and 1 text entry task will be performed.

Primary outcomes

  1. Acoustic feature: zero crossing rate

    Time frame: Throughout a course of electroconvulsive therapy (ECT) which may last between 2 and 7 weeks.

    crossings per second

  2. Acoustic feature: energy and entropy

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    decibels

  3. Acoustic feature: spectral centroid, spectral spread, spectral entropy, spectral flux, spectral rolloff

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    hertz

  4. Acoustic feature: Mel-Frequency Cepstral Coefficients, Chroma Vectors, and Chroma Deviation

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    unitless

  5. Linguistic features: question ratio, filler ratio, number ratio, type token ratio

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    unitless ratio

  6. Linguistic features: verb frequency, noun frequency, pronoun frequency, adverb frequency, adjective frequency, particle frequency, conjunction frequency, pronoun frequency

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    percentage

  7. Linguistic features: standardized word entropy

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    decibels/log(total word count)

  8. Linguistic features: Brunets index

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    W (lexical richness)

  9. Linguistic features: Honores statistic

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    R (lexical richness)

  10. Linguistic features: rate of speech

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    words per minute

  11. Meta-features: fatigue

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Machine learning approach to evaluate binary outcome: fatigued or awake

  12. Meta-features: audio quality

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Machine learning approach to evaluate binary outcome: bad or good

  13. Meta-features: sentiment

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Machine learning approach to evaluate binary outcome: sad or happy

  14. Meta-features: stress

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Machine learning approach to evaluate binary outcome: stressed or not stressed

  15. Meta-features: gender

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Machine learning approach to evaluate binary outcome: male or female

  16. Meta-features: accent

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Machine learning approach to evaluate a categorical outcome of accent region: england, indian, australian, etc.

  17. Meta-features: length

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    seconds

  18. Meta-features: age

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Machine learning approach to evaluate estimated decade-age: 10s, 20s, 30s, 40s, 50s, 60s, 70s, 80s, 90s, etc.

  19. Comparing the voice feature(s) with greatest statistically significant change to Patient Health Questionnaire (PHQ)-9 scores

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    The voice feature(s) found to have changed most significantly will be compared to Patient Health Questionnaire-9 scores which approach a total score that is less than 8, indicative of reduced depressive symptoms throughout Electroconvulsive Therapy

  20. Acoustic Feature Specific Changes within and across sessions

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Generalized mixed linear model will be used to evaluate which acoustic features change with P value threshold of <0.05

  21. Linguistic Feature Specific Changes within and across sessions

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Generalized mixed linear model will be used to evaluate which linguistic features change with P value threshold of <0.05

  22. Meta-Feature Specific Changes within and across sessions

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Generalized mixed linear model will be used to evaluate which meta features change with P value threshold of <0.05

Secondary outcomes

  1. Acoustic Feature Specific Changes between sessions

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Acoustic voice features will be evaluated using continuous averages using one sample t-tests and we will be testing the difference over time to a null hypothesis of 0 (for no change) in the one sample t-test.

  2. Linguistic Feature Specific Changes between sessions

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Linguistic voice features will be evaluated using continuous averages using one sample t-tests and we will be testing the difference over time to a null hypothesis of 0 (for no change) in the one sample t-test.

  3. Meta-Feature Specific Changes between sessions

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Meta-voice features will be evaluated using continuous averages using one sample t-tests and we will be testing the difference over time to a null hypothesis of 0 (for no change) in the one sample t-test.

  4. Patient Chart Review Data: Age

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    years

  5. Patient Chart Review Data: inpatient/outpatient status

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    binary: inpatient or outpatient

  6. Patient Chart Review Data: gender

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    male, female, unspecified

  7. Patient Chart Review Data: race

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    african american, caucasian, hispanic, asian american, etc.

  8. Patient Chart Review Data: Psychiatric diagnosis for ECT

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Diagnosis indicated for receiving ECT

  9. Patient Chart Review Data: PHQ-9 score at each session

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Total (0-27) on 9 question scale

  10. Patient Chart Review Data: Psychiatric hospitalizations

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Number

  11. Patient Chart Review Data: Past Psychiatric Medication Trials

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Number

  12. Patient Chart Review Data: Current Psychiatric Medication Trials

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Number

  13. Patient Chart Review Data: Classes of Current Psychiatric Medications

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Categorical: Sedative, Selective Serotonin Reuptake Inhibitor, etc.

  14. Patient Chart Review Data: Suicidal Ideation at ECT consult

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Binary: yes/no

  15. Patient Chart Review Data: Past Suicide Attempts

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Number

  16. Patient Chart Review Data: Psychiatric Review of Systems

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Descriptive, categorical

  17. Patient Chart Review Data: Family Psychiatric History

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Categorical regarding psychiatric diagnoses of family members

  18. Patient Chart Review Data: Number of non-psychiatric medical diagnoses

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Number

  19. Patient Chart Review Data: Past non-psychiatric medication trials

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Number

  20. Patient Chart Review Data: Current non-psychiatric Medications

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Number

  21. Patient Chart Review Data: Tobacco use history

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Binary (yes/no)

  22. Patient Chart Review Data: Tobacco use pack year

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    pack-year (total years smoked*average packs per day)

  23. Patient Chart Review Data: Prior ECT treatment

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Binary (yes/no)

  24. Patient Chart Review Data: total # of prior ECT treatments for response in the past

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Numerical

  25. Patient Chart Review Data: Prior transcranial magnetic stimulation (TMS) treatment

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Binary (yes/no)

  26. Patient Chart Review Data: Prior response to ECT or TMS

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Categorical

  27. Patient Chart Review Data against voice features

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    We will evaluate voice features with statistically significant changes against respective participant chart review data using a general linear model with a clustering component for repeated measures which may also be applied to contrast statements evaluating overall change over time (from baseline to end).

  28. Generating ROC curves: stress

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Clinically determined stress level (mood) will be compared to meta-feature extractions of stressed vs. not stressed from voice recordings will be used to calculate an area under the receiver operating curve (AUOC)

  29. Generating ROC curves: fatigue

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Clinically determined fatigue (motor) will be compared to meta-feature extractions of fatigued vs. awake from voice recordings will be used to calculate an area under the receiver operating curve (AUOC)

  30. Generating ROC curves: sentiment

    Time frame: Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks.

    Clinically determined sentiment (affect and mood) will be compared to meta-feature extractions of happy vs. sad from voice recordings will be used to calculate an area under the receiver operating curve (AUOC)

Sponsors and collaborators

Lead sponsor

Medical University of South Carolina

Other

Registry information

Official study title

Voice Analysis in Patients Receiving Electroconvulsive Therapy

Acronym: VAPRE

Important dates

Study start
2019
Primary completion
2021
Study completion
2021
First posted
Jun 9, 2020
Registry last updated
Oct 24, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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