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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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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ECT and Voice Recorded Group | This is an add-on study of voice samples to be gathered during ECT clinical treatments. The ONLY research procedures are four tasks on an online form, one text task and three voice recording tasks. These voice recordings will take place in a private room on the 5th floor of the Institute of Psychiatry on the same day of a patient's ECT treatment. The questionnaire will take less than 10 minutes. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Questionnaire | Other | 3 voice recording tasks and 1 text entry task will be performed. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Acoustic feature: zero crossing rate | crossings per second | Throughout a course of electroconvulsive therapy (ECT) which may last between 2 and 7 weeks. |
| Acoustic feature: energy and entropy | decibels | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Acoustic feature: spectral centroid, spectral spread, spectral entropy, spectral flux, spectral rolloff | hertz | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Acoustic feature: Mel-Frequency Cepstral Coefficients, Chroma Vectors, and Chroma Deviation | unitless | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Linguistic features: question ratio, filler ratio, number ratio, type token ratio | unitless ratio | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Linguistic features: verb frequency, noun frequency, pronoun frequency, adverb frequency, adjective frequency, particle frequency, conjunction frequency, pronoun frequency | percentage | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Linguistic features: standardized word entropy | decibels/log(total word count) |
| Measure | Description | Time Frame |
|---|---|---|
| Acoustic Feature Specific Changes between sessions | 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. | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
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INCLUSION CRITERIA:
EXCLUSION CRITERIA:
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Patients undergoing electroconvulsive therapy (ECT) at the Medical University of South Carolina on an outpatient or inpatient basis.
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| Name | Affiliation | Role |
|---|---|---|
| Sean Christensen, MD | Medical University of South Carolina | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Medical University of South Carolina | Charleston | South Carolina | 29425 | United States |
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| ID | Term |
|---|---|
| D003866 | Depressive Disorder |
| D001714 | Bipolar Disorder |
| ID | Term |
|---|---|
| D019964 | Mood Disorders |
| D001523 | Mental Disorders |
| D000068105 | Bipolar and Related Disorders |
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| ID | Term |
|---|---|
| D011795 | Surveys and Questionnaires |
| ID | Term |
|---|---|
| D003625 | Data Collection |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
| D017531 | Health Care Evaluation Mechanisms |
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| Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Linguistic features: Brunets index | W (lexical richness) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Linguistic features: Honores statistic | R (lexical richness) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Linguistic features: rate of speech | words per minute | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-features: fatigue | Machine learning approach to evaluate binary outcome: fatigued or awake | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-features: audio quality | Machine learning approach to evaluate binary outcome: bad or good | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-features: sentiment | Machine learning approach to evaluate binary outcome: sad or happy | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-features: stress | Machine learning approach to evaluate binary outcome: stressed or not stressed | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-features: gender | Machine learning approach to evaluate binary outcome: male or female | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-features: accent | Machine learning approach to evaluate a categorical outcome of accent region: england, indian, australian, etc. | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-features: length | seconds | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-features: age | Machine learning approach to evaluate estimated decade-age: 10s, 20s, 30s, 40s, 50s, 60s, 70s, 80s, 90s, etc. | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Comparing the voice feature(s) with greatest statistically significant change to Patient Health Questionnaire (PHQ)-9 scores | 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 | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Acoustic Feature Specific Changes within and across sessions | Generalized mixed linear model will be used to evaluate which acoustic features change with P value threshold of <0.05 | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Linguistic Feature Specific Changes within and across sessions | Generalized mixed linear model will be used to evaluate which linguistic features change with P value threshold of <0.05 | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-Feature Specific Changes within and across sessions | Generalized mixed linear model will be used to evaluate which meta features change with P value threshold of <0.05 | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Linguistic Feature Specific Changes between sessions | 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. | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Meta-Feature Specific Changes between sessions | 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. | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Age | years | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: inpatient/outpatient status | binary: inpatient or outpatient | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: gender | male, female, unspecified | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: race | african american, caucasian, hispanic, asian american, etc. | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Psychiatric diagnosis for ECT | Diagnosis indicated for receiving ECT | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: PHQ-9 score at each session | Total (0-27) on 9 question scale | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Psychiatric hospitalizations | Number | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Past Psychiatric Medication Trials | Number | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Current Psychiatric Medication Trials | Number | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Classes of Current Psychiatric Medications | Categorical: Sedative, Selective Serotonin Reuptake Inhibitor, etc. | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Suicidal Ideation at ECT consult | Binary: yes/no | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Past Suicide Attempts | Number | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Psychiatric Review of Systems | Descriptive, categorical | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Family Psychiatric History | Categorical regarding psychiatric diagnoses of family members | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Number of non-psychiatric medical diagnoses | Number | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Past non-psychiatric medication trials | Number | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Current non-psychiatric Medications | Number | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Tobacco use history | Binary (yes/no) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Tobacco use pack year | pack-year (total years smoked*average packs per day) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Prior ECT treatment | Binary (yes/no) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: total # of prior ECT treatments for response in the past | Numerical | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Prior transcranial magnetic stimulation (TMS) treatment | Binary (yes/no) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data: Prior response to ECT or TMS | Categorical | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Patient Chart Review Data against voice features | 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). | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Generating ROC curves: stress | 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) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Generating ROC curves: fatigue | 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) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| Generating ROC curves: sentiment | 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) | Throughout a course of electroconvulsive therapy which may last between 2 and 7 weeks. |
| D011787 | Quality of Health Care |
| D017530 | Health Care Quality, Access, and Evaluation |
| D011634 | Public Health |
| D004778 | Environment and Public Health |