Kintsugi Voice Device Pilot Study
Kintsugi Voice Device SCID-5-CT Pilot Study
1 other identifier
observational
500
1 country
1
Brief Summary
A prospective, single arm, non-randomized, pilot clinical validation study to evaluate the ability of the Kintsugi Voice Device (the Device) to aid clinical assessment for depression by comparing its output with a diagnosis made by a clinician using the Structured Clinical Interview for DSM-5 (SCID-5-CT) for up to 500 English speaking adult patients ages 22 and older living in the United States. Recruitment will occur for 1 year and participation will be for up to 2 weeks.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Mar 2024
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
March 22, 2024
CompletedFirst Submitted
Initial submission to the registry
April 9, 2024
CompletedFirst Posted
Study publicly available on registry
April 18, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 22, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
July 22, 2025
CompletedOctober 8, 2024
April 1, 2024
1 year
April 9, 2024
October 7, 2024
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Sensitivity and Specificity of Kintsugi Voice Device Relative to the SCID-5
Determine the performance of the KV Device in discriminating the presence of a current significant depressive episode using the SCID-5-CT diagnosis of current MDD and/or MDE using sensitivity and specificity.
Day 1
Secondary Outcomes (3)
PPV, NPV, AUC, F-Score of Kintsugi Voice Device Relative to the SCID-5
Day 1
Sensitivity, Specificity, PPV, NPV, AUC, F-Score of Kintsugi Voice Device Relative to the Severity of the SCID-5-CT
Day 1
Sensitivity, Specificity, PPV, NPV, AUC, F-Score of Kintsugi Voice Device Relative to the PHQ-9
Day 1
Study Arms (1)
Depressed
All study participants will undergo the same study procedures. All individuals will complete brief online assessments about their emotional and physical wellbeing, provide audio recorded voice responses to prompts, and complete the SCID-5-CT with a clinician licensed in their state of residence while being audio and video recorded for quality assurance purposes.
Interventions
The Kintsugi Voice Device is intended to be used to screen for the presence of voice signals consistent with a current moderate to severe depressive episode in patients aged 22 and older. The device is intended to be used by care providers licensed to screen for depression and in settings where the screening for depression occurs. The device is neither to be used in lieu of a complete patient evaluation nor to supplant any of the clinician's standard assessments for the screening or diagnosis of depression. The Kintsugi Voice Device is comprised of a software API and machine learning model that utilizes recorded voice samples as inputs and outputs the detection of signals consistent with current moderate to severe depressive episode as outputs.
Eligibility Criteria
This study will enroll up to 500 English speaking subjects \>22 years old. Only subjects who meet all eligibility criteria and sign the informed consent will be enrolled. Participants who do not meet the criteria required for participation will not be presented with the opportunity to participate. Screen failures will not be considered a part of this research study.
You may qualify if:
- Age \>22 at the time of informed consent
- Access to a laptop, smartphone, tablet, or other device with a functioning microphone and access to the Internet
- Stated willingness to be video and audio recorded as part of the study
- Stated willingness to comply with all study procedures and availability for the duration of the study
- Fluency in English
- Availability for the duration of the study
- Resides in the United States at the time of consent and during completion of study
- Contributes to the approximately 50/50 depressed/healthy study population distribution
You may not qualify if:
- Any impairment that impacts their ability to speak and/or use a computer to complete online surveys and/or a virtual clinician assessment (E.g., visual impairment, motor impairment, and/or hearing impairment)
- Any lifetime history of neurological disease that impacts their ability to speak and/or use a computer to complete online surveys and/or a virtual clinician assessment (E.g., Central Nervous System disorders, Multiple Sclerosis, Amyotrophic Lateral Sclerosis, and/or Parkinson's Disease)
- Any lifetime history of Stroke, cognitive defect (E.g., dementia or Alzheimer's disease), and/or Traumatic Brain Injury
- Presence of voice disorders that impacts their ability to speak (E.g., acute or chronic laryngitis, vocal cord paresis or paralysis, or spasmodic dysphonia)
- Past or active heavy smokers (an average of \>20 cigarettes per day)
- Subjects who have previously participated in any Kintsugi-sponsored study.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Kintsugi Mindful Wellness, Inc.lead
- Sonar Strategiescollaborator
- Vituity Psychiatrycollaborator
Study Sites (1)
Kintsugi Mindful Wellness Inc.
Berkeley, California, 94707, United States
Related Publications (31)
Evans-Lacko S, Aguilar-Gaxiola S, Al-Hamzawi A, Alonso J, Benjet C, Bruffaerts R, Chiu WT, Florescu S, de Girolamo G, Gureje O, Haro JM, He Y, Hu C, Karam EG, Kawakami N, Lee S, Lund C, Kovess-Masfety V, Levinson D, Navarro-Mateu F, Pennell BE, Sampson NA, Scott KM, Tachimori H, Ten Have M, Viana MC, Williams DR, Wojtyniak BJ, Zarkov Z, Kessler RC, Chatterji S, Thornicroft G. Socio-economic variations in the mental health treatment gap for people with anxiety, mood, and substance use disorders: results from the WHO World Mental Health (WMH) surveys. Psychol Med. 2018 Jul;48(9):1560-1571. doi: 10.1017/S0033291717003336. Epub 2017 Nov 27.
PMID: 29173244BACKGROUNDGBD Results Tool | GHDx. Accessed January 31, 2022. http://ghdx.healthdata.org/gbd-results-tool?params=gbd-api-2019-permalink/d780dffbe8a381b25e1416884959e88b
BACKGROUNDMajor Depression. National Institute of Mental Health. Published January 2022. Accessed January 31, 2022. https://www.nimh.nih.gov/health/statistics/major-depression
BACKGROUNDFacts & Statistics | Anxiety and Depression Association of America, ADAA. Accessed January 31, 2022. https://adaa.org/understanding-anxiety/facts-statistics
BACKGROUNDDomogauer JD, Colangelo N, Aggarwal R. Study of Total and Undiagnosed Depression in a Cancer Patient Population at an Urban Cancer Center. International Journal of Radiation Oncology*Biology*Physics. 2017;99(2):S10. doi:10.1016/J.IJROBP.2017.06.040
BACKGROUNDLewis K, Marrie RA, Bernstein CN, Graff LA, Patten SB, Sareen J, Fisk JD, Bolton JM; CIHR Team in Defining the Burden and Managing the Effects of Immune-Mediated Inflammatory Disease. The Prevalence and Risk Factors of Undiagnosed Depression and Anxiety Disorders Among Patients With Inflammatory Bowel Disease. Inflamm Bowel Dis. 2019 Sep 18;25(10):1674-1680. doi: 10.1093/ibd/izz045.
PMID: 30888037BACKGROUNDSorkin DH, Ngo-Metzger Q, Billimek J, August KJ, Greenfield S, Kaplan SH. Underdiagnosed and undertreated depression among racially/ethnically diverse patients with type 2 diabetes. Diabetes Care. 2011 Mar;34(3):598-600. doi: 10.2337/dc10-1825. Epub 2011 Jan 27.
PMID: 21273497BACKGROUNDMcDaid D, Park A la. Counting All the Costs: The Economic Impact of Comorbidity. Key Issues in Mental Health. 2015;179:23-32. doi:10.1159/000365941
BACKGROUNDDepression - Clinical Preventive Service Recommendation. American Academy of Family Physicians. Accessed February 1, 2022. https://www.aafp.org/family-physician/patient-care/clinical-recommendations/all-clinical-recommendations/depression.html
BACKGROUNDSiu AL; US Preventive Services Task Force (USPSTF); Bibbins-Domingo K, Grossman DC, Baumann LC, Davidson KW, Ebell M, Garcia FA, Gillman M, Herzstein J, Kemper AR, Krist AH, Kurth AE, Owens DK, Phillips WR, Phipps MG, Pignone MP. Screening for Depression in Adults: US Preventive Services Task Force Recommendation Statement. JAMA. 2016 Jan 26;315(4):380-7. doi: 10.1001/jama.2015.18392.
PMID: 26813211BACKGROUNDOlfson M, Kroenke K, Wang S, Blanco C. Trends in office-based mental health care provided by psychiatrists and primary care physicians. J Clin Psychiatry. 2014 Mar;75(3):247-53. doi: 10.4088/JCP.13m08834.
PMID: 24717378BACKGROUNDAboraya A. The Reliability of Psychiatric Diagnoses: Point-Our psychiatric Diagnoses are Still Unreliable. Psychiatry (Edgmont). 2007 Jan;4(1):22-5. No abstract available.
PMID: 20805925BACKGROUNDKraemer HC, Kupfer DJ, Clarke DE, Narrow WE, Regier DA. DSM-5: how reliable is reliable enough? Am J Psychiatry. 2012 Jan;169(1):13-5. doi: 10.1176/appi.ajp.2011.11010050. No abstract available.
PMID: 22223009BACKGROUNDMitchell AJ, Vaze A, Rao S. Clinical diagnosis of depression in primary care: a meta-analysis. Lancet. 2009 Aug 22;374(9690):609-19. doi: 10.1016/S0140-6736(09)60879-5. Epub 2009 Jul 27.
PMID: 19640579BACKGROUNDWilliams SZ, Chung GS, Muennig PA. Undiagnosed depression: A community diagnosis. SSM Popul Health. 2017 Jul 28;3:633-638. doi: 10.1016/j.ssmph.2017.07.012. eCollection 2017 Dec.
PMID: 29349251BACKGROUNDThomas JA, Burkhardt HA, Chaudhry S, Ngo AD, Sharma S, Zhang L, Au R, Hosseini Ghomi R. Assessing the Utility of Language and Voice Biomarkers to Predict Cognitive Impairment in the Framingham Heart Study Cognitive Aging Cohort Data. J Alzheimers Dis. 2020;76(3):905-922. doi: 10.3233/JAD-190783.
PMID: 32568190BACKGROUNDOzkanca Y, Ozturk MG, Ekmekci MN, Atkins DC, Demiroglu C, Ghomi RH. Depression Screening from Voice Samples of Patients Affected by Parkinson's Disease. Digit Biomark. 2019 May-Aug;3(2):72-82. doi: 10.1159/000500354. Epub 2019 Jun 12.
PMID: 31872172BACKGROUNDDi Y, Wang J, Liu X, Zhu T. Combining Polygenic Risk Score and Voice Features to Detect Major Depressive Disorders. Front Genet. 2021 Dec 20;12:761141. doi: 10.3389/fgene.2021.761141. eCollection 2021.
PMID: 34987547BACKGROUNDFagherazzi G, Fischer A, Ismael M, Despotovic V. Voice for Health: The Use of Vocal Biomarkers from Research to Clinical Practice. Digit Biomark. 2021 Apr 16;5(1):78-88. doi: 10.1159/000515346. eCollection 2021 Jan-Apr.
PMID: 34056518BACKGROUNDLin H, Karjadi C, Ang TFA, Prajakta J, McManus C, Alhanai TW, Glass J, Au R. Identification of digital voice biomarkers for cognitive health. Explor Med. 2020;1:406-417. doi: 10.37349/emed.2020.00028. Epub 2020 Dec 31.
PMID: 33665648BACKGROUNDTracy JM, Ozkanca Y, Atkins DC, Hosseini Ghomi R. Investigating voice as a biomarker: Deep phenotyping methods for early detection of Parkinson's disease. J Biomed Inform. 2020 Apr;104:103362. doi: 10.1016/j.jbi.2019.103362. Epub 2019 Dec 19.
PMID: 31866434BACKGROUNDZhang L, Duvvuri R, Chandra KKL, Nguyen T, Ghomi RH. Automated voice biomarkers for depression symptoms using an online cross-sectional data collection initiative. Depress Anxiety. 2020 Jul;37(7):657-669. doi: 10.1002/da.23020. Epub 2020 May 7.
PMID: 32383335BACKGROUNDDeng K, Li Y, Zhang H, Wang J, Albin RL, Guan Y. Heterogeneous digital biomarker integration out-performs patient self-reports in predicting Parkinson's disease. Commun Biol. 2022 Jan 17;5(1):58. doi: 10.1038/s42003-022-03002-x.
PMID: 35039601BACKGROUNDShin D, Cho WI, Park CHK, Rhee SJ, Kim MJ, Lee H, Kim NS, Ahn YM. Detection of Minor and Major Depression through Voice as a Biomarker Using Machine Learning. J Clin Med. 2021 Jul 8;10(14):3046. doi: 10.3390/jcm10143046.
PMID: 34300212BACKGROUNDKraepelin E. Manic Depressive Insanity and Paranoia. The Journal of Nervous and Mental Disease. 1921;53(4). https://journals.lww.com/jonmd/Fulltext/1921/04000/Manic_Depressive_Insanity_and_Paranoia.57.aspx
BACKGROUNDSzabadi E, Bradshaw CM, Besson JA. Elongation of pause-time in speech: a simple, objective measure of motor retardation in depression. Br J Psychiatry. 1976 Dec;129:592-7. doi: 10.1192/bjp.129.6.592.
PMID: 1000144BACKGROUNDGreden JF, Albala AA, Smokler IA, Gardner R, Carroll BJ. Speech pause time: a marker of psychomotor retardation among endogenous depressives. Biol Psychiatry. 1981 Sep;16(9):851-9.
PMID: 7295844BACKGROUNDMundt JC, Vogel AP, Feltner DE, Lenderking WR. Vocal acoustic biomarkers of depression severity and treatment response. Biol Psychiatry. 2012 Oct 1;72(7):580-7. doi: 10.1016/j.biopsych.2012.03.015. Epub 2012 Apr 26.
PMID: 22541039BACKGROUNDSingh R, Baker JT, Pennant L, Morency LP. Deducing the severity of psychiatric symptoms from the human voice. ArXiv. 2017;abs/1703.05344.
BACKGROUNDSalekin A, Eberle JW, Glenn JJ, Teachman BA, Stankovic JA. A Weakly Supervised Learning Framework for Detecting Social Anxiety and Depression. Proc ACM Interact Mob Wearable Ubiquitous Technol. 2018 Jun;2(2):81. doi: 10.1145/3214284.
PMID: 31187083BACKGROUNDLow DM, Bentley KH, Ghosh SS. Automated assessment of psychiatric disorders using speech: A systematic review. Laryngoscope Investig Otolaryngol. 2020 Jan 31;5(1):96-116. doi: 10.1002/lio2.354. eCollection 2020 Feb.
PMID: 32128436BACKGROUND
Biospecimen
A
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
April 9, 2024
First Posted
April 18, 2024
Study Start
March 22, 2024
Primary Completion
March 22, 2025
Study Completion
July 22, 2025
Last Updated
October 8, 2024
Record last verified: 2024-04
Data Sharing
- IPD Sharing
- Will not share
The study team does not current intend to publish the data associated with the study. Should the study team publish study data, the study data may be made available to other researchers.