Clinical trial NCT05455905: Voice Biomarkers Predictive of Depression and Anxiety
Official title: Voice Biomarkers Predictive of Depression and Anxiety: An Observational Study
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Depression, Anxiety
Healthy
Mental Health Wellness 1
Keywords: mental health
depression
anxiety
Artificial Intelligence
Lead sponsor: Kintsugi Mindful Wellness, Inc.
Sponsor class: INDUSTRY
First posted: 2022-07-13
Enrollment: 19533
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study population will include males and females fluent in English over the age of 18 in the United States and Canada. Participants both with and without a personal history of depression and/or anxiety are eligible to participate in the study. Participants will require access to a laptop, smartphone, or tablet with a functioning microphone and provide stated willingness to comply with all study procedures and availability for the duration of the study. Participants with a visual or motor impairment that would make it difficult to use the web-based survey will be excluded from the study.

Brief summary: The objective of this study is to collect data to improve the sensitivity and specificity of Kintsugi Voice's (formerly KiVATM) predictions on audio files. A web-based audio recording tool will be used to record voice sample and ask participants the PHQ-9 and GAD-7 questions. A voluntary subset of participants will then be assessed by mental health professionals with the Hamilton Depression Rating Scale (HAM-D) and Hamilton Anxiety Rating Scale (HAM-A) scores.

Detailed description: Participants will be recruited via various online mediums to participate in a voluntary observational study. Completing the consent and survey on their smart-phone, tablet, or computer, the participant will be asked to provide a 1-minute response to an audio prompt "How was your day?" After recording their response, the participant will be asked to complete the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 measures independently.

In a second voluntary phase of the study, participants who indicated a score higher than 20, will be contacted by the research team via email to determine if they are interested in a voluntary follow-up to their initial study participation. Participants who would like to take part in the additional survey will complete additional voice recording responses to prompts and complete the Patient History Questionnaire and Generalized Anxiety Disorder-7. These participants will be contacted by a Mental Health Professional to discuss seeking mental health resources and clinicians, as well as, complete the Hamilton Depression Rating Scale and Hamilton Anxiety Rating Scale via the telephone.

Eligibility criteria: Inclusion Criteria:

* Adult males and or females over the age of 18 at the time of informed consent. Adults with a known history of depression and/or anxiety and adults without a known history of depression and/or anxiety will be included in this study.
* Access to a laptop, smart-phone or tablet with a functioning microphone
* Stated willingness to comply with all study procedures and availability for the duration of the study
* Fluency in English

Exclusion Criteria:

* Visual impairment that would make it difficult for the participant to see the web-based survey
* Motor impairment that would make it difficult for the participant to use the web-based survey

Primary outcomes:
measure: Hamilton Depression Rating Scale
timeFrame: Through study completion, on average 12months
measure: Hamilton Anxiety Rating Scale
timeFrame: Through study completion, on average 12 months
Secondary outcomes:
Other outcomes:
Locations:
city: Berkeley
country: United States
facility: Kintsugi Mindful Wellness, Inc.
state: California
Study officials:
affiliation: Kintsugi Mindful Wellness, Inc.
name: Mei-Hsin Cheng, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Czeisler ME, Lane RI, Petrosky E, Wiley JF, Christensen A, Njai R, Weaver MD, Robbins R, Facer-Childs ER, Barger LK, Czeisler CA, Howard ME, Rajaratnam SMW. Mental Health, Substance Use, and Suicidal Ideation During the COVID-19 Pandemic - United States, June 24-30, 2020. MMWR Morb Mortal Wkly Rep. 2020 Aug 14;69(32):1049-1057. doi: 10.15585/mmwr.mm6932a1.
citation: ADAA. Facts & statistics: Anxiety and Depression Association of America. Retrieved March 05, 2021, from https://adaa.org/about-adaa/press-room/facts-statistics
citation: Low 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.
citation: Mundt 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.
citation: Zhang 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.
citation: Espinola, CW, Gomes, JC, Pereira, JMS et. al. Detection of major depressive disorder using vocal acoustic analysis and machine learning-an exploratory study. Res. Biomed. Eng. 2021; 37: 53-64.
citation: Wang J, Zhang L, Liu T, Pan W, Hu B, Zhu T. Acoustic differences between healthy and depressed people: a cross-situation study. BMC Psychiatry. 2019 Oct 15;19(1):300. doi: 10.1186/s12888-019-2300-7.
citation: He L, Cao C. Automated depression analysis using convolutional neural networks from speech. J Biomed Inform. 2018 Jul;83:103-111. doi: 10.1016/j.jbi.2018.05.007. Epub 2018 May 29.
citation: Ozkanca 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.
citation: Yi H, Smiljanic R, Chandrasekaran B. The Effect of Talker and Listener Depressive Symptoms on Speech Intelligibility. J Speech Lang Hear Res. 2019 Nov 18;62(12):4269-4281. doi: 10.1044/2019_JSLHR-S-19-0112. Print 2019 Dec 18.
citation: Stassen HH, Bomben G, Gunther E. Speech characteristics in depression. Psychopathology. 1991;24(2):88-105. doi: 10.1159/000284700.
citation: Taguchi T, Tachikawa H, Nemoto K, Suzuki M, Nagano T, Tachibana R, Nishimura M, Arai T. Major depressive disorder discrimination using vocal acoustic features. J Affect Disord. 2018 Jan 1;225:214-220. doi: 10.1016/j.jad.2017.08.038. Epub 2017 Aug 16.
citation: Low LS, Maddage NC, Lech M, Sheeber LB, Allen NB. Detection of clinical depression in adolescents' speech during family interactions. IEEE Trans Biomed Eng. 2011 Mar;58(3):574-86. doi: 10.1109/TBME.2010.2091640. Epub 2010 Nov 11.
citation: Tuka A, Mohammad G, and James G. Detecting Depression with Audio/Text Sequence Modeling of Interviews. Interspeech. 2018; 2522.
citation: Pan W, Flint J, Shenhav L, Liu T, Liu M, Hu B, Zhu T. Re-examining the robustness of voice features in predicting depression: Compared with baseline of confounders. PLoS One. 2019 Jun 20;14(6):e0218172. doi: 10.1371/journal.pone.0218172. eCollection 2019.
citation: Xu, M, Duan, LY, Cai, J, Chia, LT, Xu, C, & Tian, Q. HMM-based audio keyword generation. In Pacific-Rim Conference on Multimedia. 2004; November: 566-574. Springer, Berlin, Heidelberg.
citation: Aizawa IK, Nakamura Y, Satoh S, et. al. Advances in Multimedia Information Processing - PCM 2004: 5th Pacific Rim Conference on Multimedia. Springer. ISBN 978-3-540-23985-7.
citation: Crockford, D. (2001, April). Introducing JSON. JavaScript Object Notation. https://www.json.org/json-en.html
citation: HAMILTON M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960 Feb;23(1):56-62. doi: 10.1136/jnnp.23.1.56. No abstract available.
citation: Trajkovic G, Starcevic V, Latas M, Lestarevic M, Ille T, Bukumiric Z, Marinkovic J. Reliability of the Hamilton Rating Scale for Depression: a meta-analysis over a period of 49 years. Psychiatry Res. 2011 Aug 30;189(1):1-9. doi: 10.1016/j.psychres.2010.12.007. Epub 2011 Jan 26.
citation: HAMILTON M. The assessment of anxiety states by rating. Br J Med Psychol. 1959;32(1):50-5. doi: 10.1111/j.2044-8341.1959.tb00467.x. No abstract available.