Brief Summary
The objective of this study is to conduct a randomized controlled trial (RCT) to compare the adapted and refined ASTHMAXcel Voice platform to usual care (UC). It is hypothesized by the investigator team that ASTHMAXcel Voice will be associated with improved clinical and process outcomes, asthma quality of life (QOL), medication adherence, and self-efficacy as compared to UC.
Brief Title
ASTHMAXcel Voice Study
Detailed Description
Poor outcomes for minority patients with asthma have been linked to poverty and other social determinants of health (SDOH), environmental exposures, and poor self-management. In a previous Agency for Healthcare Research and Quality (AHRQ)-funded study, the researchers developed and pilot tested ASTHMAXcel PRO, a mobile app that promotes self-management of asthma (NCT03847142). The app was optimized for outpatient settings and promoted asthma self-management through the collection of patient-reported outcomes (PROs), animated videos, goal setting, personalized algorithms, and push notifications. The use of the app led to significant decreases in the need for steroids, visits for asthma to the emergency department, and hospitalizations for asthma.
In this current research, ASTHMAXcel Voice, an app developed and refined during enhancement of ASTHMAXcel PRO, will make use of voice biomarkers to detect worsening symptoms. This technology uses machine learning to assess respiratory dysfunction, including asthma, based on a 6-second voice sample. From the sample, a Respiratory Symptoms Risk Score (RSRS) is calculated that correlates with the speaker's risk of respiratory impairment. The updated platform will calculate the patient's RSRS; facilitate shared decision making, screen for SDoH, and referrals; improve the ability of patients to self-manage; and allow for remote care coordination.
This program draws upon the Common Sense Model (CSM) of Self-Regulation which describes a cognitive processing system that includes situational stimuli (asthma symptoms), objective representation of the health threat (illness representations) with its treatment decision (controller medication use), and appraisal of outcomes (asthma control) for the success/failure of those treatment decisions. The model contains a feedback loop with illness representations changing over time as patients gain experience with asthma management. Social Determinants of Health (SDoH) may also affect the representation of the health threat, treatment decisions, and appraisal of outcomes. As an example, a patient with depression, a poor social support network, insecure housing, and financial stress may view asthma as an acute disease that is uncontrollable, which in turn leads to negative beliefs about medications and low self-efficacy towards asthma management. ASTHMAXcel Voice strives to shift illness representations away from the belief that asthma only exists when there are active symptoms and change behavior towards daily controller medication use over the long term to prevent asthma symptoms. Realtime feedback based on voice samples that yield a RSRS (voice biomarker) will help the patient to accurately detect perceived threats and manage asthma exacerbations during earlier stages. ASTHMAXcel Voice is also based on the SEM that addresses causes of poor asthma control across four interconnected domains: community, medical system, interpersonal, and individual level factors. ASTHMAXcel Voice is a multilevel approach to address these barriers with intervention components that are directly applied at each level.
There is growing recognition that mobile health interventions can be applied across all these levels to facilitate health behavior change through the use of push notifications and interactive educational content. ASTHMAXcel Voice works on the individual and interpersonal levels by providing targeted asthma education and push notifications to assist with medication adherence and asthma management. Worse outcomes assessed by PROs (asthma control) and voice biomarkers may heighten the perceived threat level of asthma and prompt Just-in-Time Adaptive Interventions (JITAIs) to seek out the educational content more frequently to improve asthma control. On the organizational (medical system) level, ASTHMAXcel Voice will facilitate shared decision-making and ongoing communication between the patient, Community Health Worker (CHW) or Social Worker (SW), and Health Care Provider (HCP). For example, a monthly visual dashboard display will increase HCP awareness of deteriorating trends assessed from PROs and voice biomarkers. On the community level, the CHW or SW will provide patients with SDoH relevant community resources (e.g., pest remediation services, smoking cessation programs, support groups, food pantries) to address SDoH concerns reported in the mobile platform. Finally, to inform more effective design and implementation of ASTHMAXcel Voice, the study team will use the Unified Theory of Acceptance and use of Technology (UTAUT) health IT framework in determining a user's technology acceptance and adoption behavior.
In this current research, ASTHMAXcel Voice, an app developed and refined during enhancement of ASTHMAXcel PRO, will make use of voice biomarkers to detect worsening symptoms. This technology uses machine learning to assess respiratory dysfunction, including asthma, based on a 6-second voice sample. From the sample, a Respiratory Symptoms Risk Score (RSRS) is calculated that correlates with the speaker's risk of respiratory impairment. The updated platform will calculate the patient's RSRS; facilitate shared decision making, screen for SDoH, and referrals; improve the ability of patients to self-manage; and allow for remote care coordination.
This program draws upon the Common Sense Model (CSM) of Self-Regulation which describes a cognitive processing system that includes situational stimuli (asthma symptoms), objective representation of the health threat (illness representations) with its treatment decision (controller medication use), and appraisal of outcomes (asthma control) for the success/failure of those treatment decisions. The model contains a feedback loop with illness representations changing over time as patients gain experience with asthma management. Social Determinants of Health (SDoH) may also affect the representation of the health threat, treatment decisions, and appraisal of outcomes. As an example, a patient with depression, a poor social support network, insecure housing, and financial stress may view asthma as an acute disease that is uncontrollable, which in turn leads to negative beliefs about medications and low self-efficacy towards asthma management. ASTHMAXcel Voice strives to shift illness representations away from the belief that asthma only exists when there are active symptoms and change behavior towards daily controller medication use over the long term to prevent asthma symptoms. Realtime feedback based on voice samples that yield a RSRS (voice biomarker) will help the patient to accurately detect perceived threats and manage asthma exacerbations during earlier stages. ASTHMAXcel Voice is also based on the SEM that addresses causes of poor asthma control across four interconnected domains: community, medical system, interpersonal, and individual level factors. ASTHMAXcel Voice is a multilevel approach to address these barriers with intervention components that are directly applied at each level.
There is growing recognition that mobile health interventions can be applied across all these levels to facilitate health behavior change through the use of push notifications and interactive educational content. ASTHMAXcel Voice works on the individual and interpersonal levels by providing targeted asthma education and push notifications to assist with medication adherence and asthma management. Worse outcomes assessed by PROs (asthma control) and voice biomarkers may heighten the perceived threat level of asthma and prompt Just-in-Time Adaptive Interventions (JITAIs) to seek out the educational content more frequently to improve asthma control. On the organizational (medical system) level, ASTHMAXcel Voice will facilitate shared decision-making and ongoing communication between the patient, Community Health Worker (CHW) or Social Worker (SW), and Health Care Provider (HCP). For example, a monthly visual dashboard display will increase HCP awareness of deteriorating trends assessed from PROs and voice biomarkers. On the community level, the CHW or SW will provide patients with SDoH relevant community resources (e.g., pest remediation services, smoking cessation programs, support groups, food pantries) to address SDoH concerns reported in the mobile platform. Finally, to inform more effective design and implementation of ASTHMAXcel Voice, the study team will use the Unified Theory of Acceptance and use of Technology (UTAUT) health IT framework in determining a user's technology acceptance and adoption behavior.
Central Contacts
Central Contact Role
Contact
Central Contact Phone
609-937-1023
Central Contact Email
sjariwal@montefiore.org
Central Contact Role
Contact
Central Contact Phone
718-862-1722
Central Contact Email
juliana.rodríguez@einsteinmed.edu
Completion Date
Completion Date Type
Estimated
Conditions
ASTHMA
Eligibility Criteria
Inclusion Criteria:
* English speaking
* Persistent asthma (diagnosed by a healthcare provider) on a daily controller medication
* Able to provide informed consent
* Smartphone access (iOS or Android) with data plan
Exclusion Criteria:
* Pregnancy
* Severe psychiatric or cognitive problems that would prohibit completion of protocol
* English speaking
* Persistent asthma (diagnosed by a healthcare provider) on a daily controller medication
* Able to provide informed consent
* Smartphone access (iOS or Android) with data plan
Exclusion Criteria:
* Pregnancy
* Severe psychiatric or cognitive problems that would prohibit completion of protocol
Inclusion Criteria
Inclusion Criteria:
* English speaking
* Persistent asthma (diagnosed by a healthcare provider) on a daily controller medication
* Able to provide informed consent
* Smartphone access (iOS or Android) with data plan
* English speaking
* Persistent asthma (diagnosed by a healthcare provider) on a daily controller medication
* Able to provide informed consent
* Smartphone access (iOS or Android) with data plan
Gender
All
Gender Based
false
Keywords
Mobile Health Application
Asthma Management
Asthma Control
Healthy Volunteers
No
Last Update Post Date
Last Update Post Date Type
Actual
Last Update Submit Date
Minimum Age
18 Years
NCT Id
NCT06935084
Org Class
Other
Org Full Name
Montefiore Medical Center
Org Study Id
2025-16587
Overall Status
Recruiting
Phases
Not Applicable
Primary Completion Date
Primary Completion Date Type
Estimated
Official Title
Conducting a Randomized Controlled Trial for A Novel Patient-Facing Mobile Platform to Collect and Implement Patient-Reported Outcomes and Voice Biomarkers in Underserved Adult Patients With Asthma
Primary Outcomes
Outcome Description
Change in asthma control will be assessed and measured using the Asthma Control Test (ACT). The ACT is a 5-item questionnaire administered to assess asthma control. Participants will score each item on the ACT based on a 5-point Likert scale ranging from 1 (poor control) to 5 (excellent control) yielding an overall possible scoring range of 5-25, such that higher overall scores are associated with increased levels of asthma control. Change in ACT scores will be summarized by study arm using basic descriptive statistics. Paired t-tests will also be used to compare ACT scores between baseline and 2 months and baseline and 6 months within each arm.
Outcome Measure
Change in Asthma Control
Outcome Time Frame
Change from Baseline to 6 months after randomization
Secondary Outcomes
Outcome Description
Change in asthma control will be assessed and measured using the Asthma Control Test (ACT). The ACT is a 5-item questionnaire administered to assess asthma control. Participants will score each item on the ACT based on a 5-point Likert scale ranging from 1 (poor control) to 5 (excellent control) yielding an overall possible scoring range of 5-25, such that higher overall scores are associated with increased levels of asthma control. Change in ACT scores will be summarized by study arm using basic descriptive statistics. Paired t-tests will also be used to compare ACT scores between baseline and 2 months and baseline and 6 months within each arm.
Outcome Time Frame
Change from Baseline to 2 months after randomization
Outcome Measure
Change in Asthma Control
Outcome Description
Change in user acceptance of the application will be assessed using the Unified Theory of Acceptance and User of Technology (UTAUT) Questionnaire. The UTAUT considers 4 constructs: performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC), as most influential in determining technology acceptance and adoption behavior. Each of the 4 constructs consists of 4 statements which are evaluated on a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree), with higher scores indicating a greater likelihood of technology acceptance and use, reflecting stronger perceptions of PE, EE, SI, and FC. Scores for all items are summed and then the total score is divided by 16 to calculate a mean or average score. Scores will be summarized by using basic descriptive statistics. Paired t-tests will also be used to assess changes in user acceptance between baseline and 2 months and baseline and 6 months within the arm.
Outcome Time Frame
Baseline, 2 months, and 6 months after randomization
Outcome Measure
Change in User Acceptance of ASTHMAXcel Voice Application
Outcome Description
Change in User satisfaction of Interaction with the application will be assessed using Version 7 of the Questionnaire for User Interface Satisfaction (QUIS). The QUIS is a measurement tool designed to assess a computer user's subjective satisfaction with specific aspects of the human-computer interface. QUIS measures specific interface factors such as screen visibility, terminology and system information, learning factors, system capabilities, usability and user interface, and system clutter, across 32 questions. Each QUIS question is measured on an ascending scale ranging from 0-9, wherein higher scores are associated with more favorable user impression of aspects of the interface. Scores for all items are summed and divided by the number of items answered to calculate a mean or average score. Scores will be summarized by using basic descriptive statistics. Paired t-tests will also be used to assess changes between baseline and 2 months and baseline and 6 months within the arm.
Outcome Time Frame
Baseline, 2 months, and 6 months after randomization
Outcome Measure
Change in User Satisfaction of Interaction with the ASTHMAXcel Voice application
Outcome Description
ASTHMAXcel Voice application usage will be evaluated using analytics within the "Admin Panel" of the application. Specifically, the number of logins to ASTHMAXcel Voice will be determined and considered as a proxy for usage. Usage will be summarized using basic descriptive statistics.
Outcome Time Frame
2 months and 6 months after randomization
Outcome Measure
ASTHMAXcel Voice application Usage
Outcome Description
Overall User Satisfaction will be assessed using the 8-item Client Satisfaction Questionnaire (CSQ-8). The CSQ-8 is a brief global measure of client satisfaction which contains four response choices (1-4), where "1" indicates the lowest degree of satisfaction and "4," the highest. Scores are summed across each item once. Responses to items 2, 4, 5, and 8 are reverse scored. Total overall scores range from 8-32, where in higher scores are indicative of greater overall user satisfaction. Scores will be summarized by using basic descriptive statistics. Paired t-tests will also be used to assess changes between post-refinement baseline and 2 months and baseline and 6 months within the arm.
Outcome Time Frame
Baseline, 2 months, and 6 months after randomization
Outcome Measure
Change in Overall User Satisfaction
Outcome Description
Patient-reported degree of shared decision making will be assessed using the 9-item Shared Decision-Making Questionnaire (SDM-Q-9). The SDM-Q-9 consists of 9 statements which asks the patient to assess the extent to which they agree or disagree with elements and perceptions of shared decision-making during clinical encounters. Each statement on the SDM-Q-9 is scored on a 6-point Likert scale ranging from 0 (completely disagree) to 5 (completely agree). Scores are summed to yield an overall possible scoring range of 0-45, with higher values being indicative of greater perceived shared decision making. Scores will be summarized by study arm using basic descriptive statistics. Paired t-tests will also be used to assess changes between post-refinement baseline and 2 months and 6 months within the arm
Outcome Time Frame
Baseline to 2 months and 6 months after randomization
Outcome Measure
Change in Shared Decision Making
Outcome Description
Change in Asthma-related Quality of Life will be assessed using the Mini Asthma Quality of Life Questionnaire (MiniAQLQ). The MiniAQLQ is a 15-item questionnaire that assesses asthma-related quality of life. Participants are asked to evaluate each of the questions/statements to describe how much (relative) time has been spent attending to symptoms of asthma or how much asthma has limited activities over the past 2 weeks. Each of the 15 items is scored on a 7-point Likert scale ranging from 1 (severe impairment) to 7 (no impairment), such that higher scores are associated with a better overall quality of life. Scores for the 15-items are summed and divided by 15 to express as a score out of 7 (mean or average score). Change in asthma quality of life scores will be summarized by study arm using basic descriptive statistics. Paired t-tests will also be used to assess changes in asthma-related quality of life between baseline and 2 months and baseline and 6 months within each arm.
Outcome Time Frame
Baseline to 2 months and 6 months after randomization
Outcome Measure
Change in Asthma-related Quality of Life
Outcome Description
The number of asthma-related ED visits at 2 months and 6-months post-randomization will be summarized by study arm using basic descriptive statistics.
Outcome Time Frame
2 months and 6 months after randomization
Outcome Measure
Asthma Healthcare Utilization - Emergency Department (ED) Visits
Outcome Description
The number of asthma-related hospitalizations at 2 months and 6-months post-randomization will be summarized by study arm using basic descriptive statistics.
Outcome Time Frame
2 months and 6 months after randomization
Outcome Measure
Asthma Healthcare Utilization - Hospitalizations
Outcome Description
Self-efficacy for managing chronic diseases will be evaluated using the Self-Efficacy for Managing Chronic Disease 6-Item (SEMCD-6) Scale. The SEMCD-6 assesses the level of confidence in managing six areas related to chronic disease: fatigue, physical discomfort/pain, emotional distress, other symptoms/health problems, tasks/activities needed to manage health conditions, and things other than just taking medication. Each question is rated on a 10-point scale ranging from 1 (not confident at all) to 10 (totally confident). Scores for all six items are summed, and then the total score is divided by six to calculate a mean or average score. Higher scores are associated with greater self-efficacy. Group scores will be summarized by study arm using basic descriptive statistics. Paired t-tests will also be used to assess changes between post-refinement baseline and 2 months and 6 months within the arm.
Outcome Time Frame
Baseline to 2 months and 6 months after randomization
Outcome Measure
Change in Self-efficacy for managing chronic diseases
Outcome Description
Medication Adherence will be evaluated using the 5-Item Medication Adherence Report Scale (MARS-5). The MARS-5 is a self-reported tool used to assess medication adherence and consists of 5 questions including items related to forgetting, changing dosage, stopping, skipping, and taking less medication. Each question is answered on a 5-point Likert scale (1=always, 2=often, 3=sometimes, 4=rarely, and 5=never), resulting in an overall possible score of 5-25, with higher scores indicating a higher level of adherence. Group scores will be summarized by study arm using basic descriptive statistics. Paired t-tests will also be used to assess changes between post-refinement baseline and 2 months and 6 months within the arm
Outcome Time Frame
Baseline to 2 months and 6 months after randomization
Outcome Measure
Change in Self-reported Medication Adherence
Outcome Description
SDoH Screening will be determined by the number of SDoH positive screens over the prior month. Group scores will be summarized by study arm using basic descriptive statistics.
Outcome Time Frame
2 months and 6 months after randomization
Outcome Measure
SDoH Screening
Outcome Description
SDoH Referral will be determined by the number of completed SDoH referrals over the prior month. Group scores will be summarized by study arm using basic descriptive statistics.
Outcome Time Frame
2 months and 6 months after randomization
Outcome Measure
SDoH Referral
Outcome Description
SDoH Referral Completion Rate will be assessed by the number of SDoH referral completions over the prior month. Group scores will be summarized by study arm using basic descriptive statistics.
Outcome Time Frame
2 months and 6 months after randomization
Outcome Measure
Referral Completion Rate
Start Date
Start Date Type
Actual
Status Verified Date
First Post Date
First Post Date Type
Actual
First Submit Date
First Submit QC Date
Std Ages
Adult
Older Adult
Maximum Age Number (converted to Years and rounded down)
999
Minimum Age Number (converted to Years and rounded down)
18
Investigators
Investigator Type
Principal Investigator
Investigator Name
Sunit Jariwala
Investigator Email
sjariwal@montefiore.org
Investigator Department
Medicine
Investigator Division
Allergy & Immunology
Investigator Sponsor Organization
External
Study Department
Medicine
Study Division
Allergy & Immunology
Categories Mesh Debug
Asthma and Other Respiratory Diseases --- BRONCHIAL DISEASES
Lung --- BRONCHIAL DISEASES
Asthma and Other Respiratory Diseases --- RESPIRATORY TRACT DISEASES
COVID-19 --- RESPIRATORY TRACT DISEASES
Lung --- RESPIRATORY TRACT DISEASES
Lung --- LUNG DISEASES, OBSTRUCTIVE
COVID-19 --- LUNG DISEASES
Lung --- LUNG DISEASES
Asthma and Other Respiratory Diseases --- RESPIRATORY HYPERSENSITIVITY
Lung --- RESPIRATORY HYPERSENSITIVITY
Immune System --- IMMUNE SYSTEM DISEASES
MeSH Terms
ASTHMA
BRONCHIAL DISEASES
RESPIRATORY TRACT DISEASES
LUNG DISEASES, OBSTRUCTIVE
LUNG DISEASES
RESPIRATORY HYPERSENSITIVITY
HYPERSENSITIVITY, IMMEDIATE
HYPERSENSITIVITY
IMMUNE SYSTEM DISEASES