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Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial

BACKGROUND: The quality of user interaction with therapeutic tools has been positively associated with treatment response; however, no studies have investigated these relationships for voice-based digital tools. OBJECTIVE: This study evaluated the relationships between objective and subjective user...

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Autores principales: Lv, Nan, Kannampallil, Thomas, Xiao, Lan, Ronneberg, Corina R, Kumar, Vikas, Wittels, Nancy E, Ajilore, Olusola A, Smyth, Joshua M, Ma, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660207/
https://www.ncbi.nlm.nih.gov/pubmed/37930781
http://dx.doi.org/10.2196/49715
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author Lv, Nan
Kannampallil, Thomas
Xiao, Lan
Ronneberg, Corina R
Kumar, Vikas
Wittels, Nancy E
Ajilore, Olusola A
Smyth, Joshua M
Ma, Jun
author_facet Lv, Nan
Kannampallil, Thomas
Xiao, Lan
Ronneberg, Corina R
Kumar, Vikas
Wittels, Nancy E
Ajilore, Olusola A
Smyth, Joshua M
Ma, Jun
author_sort Lv, Nan
collection PubMed
description BACKGROUND: The quality of user interaction with therapeutic tools has been positively associated with treatment response; however, no studies have investigated these relationships for voice-based digital tools. OBJECTIVE: This study evaluated the relationships between objective and subjective user interaction measures as well as treatment response on Lumen, a novel voice-based coach, delivering problem-solving treatment to patients with mild to moderate depression or anxiety or both. METHODS: In a pilot trial, 42 adults with clinically significant depression (Patient Health Questionnaire-9 [PHQ-9]) or anxiety (7-item Generalized Anxiety Disorder Scale [GAD-7]) symptoms or both received Lumen, a voice-based coach delivering 8 problem-solving treatment sessions. Objective (number of conversational breakdowns, ie, instances where a participant’s voice input could not be interpreted by Lumen) and subjective user interaction measures (task-related workload, user experience, and treatment alliance) were obtained for each session. Changes in PHQ-9 and GAD-7 scores at each ensuing session after session 1 measured the treatment response. RESULTS: Participants were 38.9 (SD 12.9) years old, 28 (67%) were women, 8 (19%) were Black, 12 (29%) were Latino, 5 (12%) were Asian, and 28 (67%) had a high school or college education. Mean (SD) across sessions showed breakdowns (mean 6.5, SD 4.4 to mean 2.3, SD 1.8) decreasing over sessions, favorable task-related workload (mean 14.5, SD 5.6 to mean 17.6, SD 5.6) decreasing over sessions, neutral-to-positive user experience (mean 0.5, SD 1.4 to mean 1.1, SD 1.3), and high treatment alliance (mean 5.0, SD 1.4 to mean 5.3, SD 0.9). PHQ-9 (P(trend)=.001) and GAD-7 scores (P(trend)=.01) improved significantly over sessions. Treatment alliance correlated with improvements in PHQ-9 (Pearson r=–0.02 to –0.46) and GAD-7 (r=0.03 to –0.57) scores across sessions, whereas breakdowns and task-related workload did not. Mixed models showed that participants with higher individual mean treatment alliance had greater improvements in PHQ-9 (β=–1.13, 95% CI –2.16 to –0.10) and GAD-7 (β=–1.17, 95% CI –2.13 to –0.20) scores. CONCLUSIONS: The participants had fewer conversational breakdowns and largely favorable user interactions with Lumen across sessions. Conversational breakdowns were not associated with subjective user interaction measures or treatment responses, highlighting how participants adapted and effectively used Lumen. Individuals experiencing higher treatment alliance had greater improvements in depression and anxiety. Understanding treatment alliance can provide insights on improving treatment response for this new delivery modality, which provides accessibility, flexibility, comfort with disclosure, and cost-related advantages compared to conventional psychotherapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT04524104; https://clinicaltrials.gov/study/NCT04524104
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spelling pubmed-106602072023-11-06 Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial Lv, Nan Kannampallil, Thomas Xiao, Lan Ronneberg, Corina R Kumar, Vikas Wittels, Nancy E Ajilore, Olusola A Smyth, Joshua M Ma, Jun JMIR Hum Factors Original Paper BACKGROUND: The quality of user interaction with therapeutic tools has been positively associated with treatment response; however, no studies have investigated these relationships for voice-based digital tools. OBJECTIVE: This study evaluated the relationships between objective and subjective user interaction measures as well as treatment response on Lumen, a novel voice-based coach, delivering problem-solving treatment to patients with mild to moderate depression or anxiety or both. METHODS: In a pilot trial, 42 adults with clinically significant depression (Patient Health Questionnaire-9 [PHQ-9]) or anxiety (7-item Generalized Anxiety Disorder Scale [GAD-7]) symptoms or both received Lumen, a voice-based coach delivering 8 problem-solving treatment sessions. Objective (number of conversational breakdowns, ie, instances where a participant’s voice input could not be interpreted by Lumen) and subjective user interaction measures (task-related workload, user experience, and treatment alliance) were obtained for each session. Changes in PHQ-9 and GAD-7 scores at each ensuing session after session 1 measured the treatment response. RESULTS: Participants were 38.9 (SD 12.9) years old, 28 (67%) were women, 8 (19%) were Black, 12 (29%) were Latino, 5 (12%) were Asian, and 28 (67%) had a high school or college education. Mean (SD) across sessions showed breakdowns (mean 6.5, SD 4.4 to mean 2.3, SD 1.8) decreasing over sessions, favorable task-related workload (mean 14.5, SD 5.6 to mean 17.6, SD 5.6) decreasing over sessions, neutral-to-positive user experience (mean 0.5, SD 1.4 to mean 1.1, SD 1.3), and high treatment alliance (mean 5.0, SD 1.4 to mean 5.3, SD 0.9). PHQ-9 (P(trend)=.001) and GAD-7 scores (P(trend)=.01) improved significantly over sessions. Treatment alliance correlated with improvements in PHQ-9 (Pearson r=–0.02 to –0.46) and GAD-7 (r=0.03 to –0.57) scores across sessions, whereas breakdowns and task-related workload did not. Mixed models showed that participants with higher individual mean treatment alliance had greater improvements in PHQ-9 (β=–1.13, 95% CI –2.16 to –0.10) and GAD-7 (β=–1.17, 95% CI –2.13 to –0.20) scores. CONCLUSIONS: The participants had fewer conversational breakdowns and largely favorable user interactions with Lumen across sessions. Conversational breakdowns were not associated with subjective user interaction measures or treatment responses, highlighting how participants adapted and effectively used Lumen. Individuals experiencing higher treatment alliance had greater improvements in depression and anxiety. Understanding treatment alliance can provide insights on improving treatment response for this new delivery modality, which provides accessibility, flexibility, comfort with disclosure, and cost-related advantages compared to conventional psychotherapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT04524104; https://clinicaltrials.gov/study/NCT04524104 JMIR Publications 2023-11-06 /pmc/articles/PMC10660207/ /pubmed/37930781 http://dx.doi.org/10.2196/49715 Text en ©Nan Lv, Thomas Kannampallil, Lan Xiao, Corina R Ronneberg, Vikas Kumar, Nancy E Wittels, Olusola A Ajilore, Joshua M Smyth, Jun Ma. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 06.11.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on https://humanfactors.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Lv, Nan
Kannampallil, Thomas
Xiao, Lan
Ronneberg, Corina R
Kumar, Vikas
Wittels, Nancy E
Ajilore, Olusola A
Smyth, Joshua M
Ma, Jun
Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial
title Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial
title_full Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial
title_fullStr Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial
title_full_unstemmed Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial
title_short Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial
title_sort association between user interaction and treatment response of a voice-based coach for treating depression and anxiety: secondary analysis of a pilot randomized controlled trial
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660207/
https://www.ncbi.nlm.nih.gov/pubmed/37930781
http://dx.doi.org/10.2196/49715
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