Mobile Parkinson Observatory for Worldwide, Evidence-based Research (mPower) (mPower)

The purpose of this study is to understand variation in the symptoms of Parkinson disease. This study uses an iPhone app to record these symptoms through questionnaires and sensors.

Study Overview

• Status: Unknown
• Conditions: Brain Diseases; Central Nervous System Diseases; Parkinson Disease; Parkinsonian Disorders; Basal Ganglia Diseases; Movement Disorders; Neurodegenerative Diseases
• Intervention / Treatment: Behavioral: Participant self-assessment surveys; Behavioral: Phonation; Behavioral: Gait and balance; Behavioral: Memory; Behavioral: Dexterity; Behavioral: Participant open-response writing; Other: Parkinson mPower mobile application

Detailed Description

Living with Parkinson disease means coping with symptoms that change every day. Yet these changes are not tracked frequently enough. Most people with Parkinson disease see a clinician only once or twice a year. This study measures changes in Parkinson disease symptoms in real time using an app. The app remotely monitors Parkinson disease symptoms using surveys and the sensors on mobile devices. This study may contribute to increasing our understanding of the variability in Parkinson disease symptoms. This knowledge could be used to improve quality of life for people living with Parkinson disease.

• Study Type: Interventional
• Enrollment (Anticipated): 20000
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Lara Mangravite, PhD; Phone Number: 2066672102; Email: lara.mangravite@sagebase.org
• Study Contact Backup: Name: Christine Suver, PhD; Phone Number: 2066672128; Email: christine.suver@sagebase.org

Study Locations

• United States
  • Washington
    • Seattle, Washington, United States, 98109
      • Recruiting
      • Sage Bionetworks
      • Contact: Christine Suver, PhD; Phone Number: 206-667-2128; Email: christine.suver@sagebase.org

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

1. Age 18 years
2. Have a personal (i.e., not shared) iPhone (4s or newer running iOS 8.0 or later)
3. Be able to read and understand an official language of the country of participation
4. Be able to provide informed consent (i.e., pass assessment quiz)
5. Be willing to follow study procedures

Exclusion Criteria:

1. Age 17 years or younger
2. Not a resident of the of a country where the app is approved for use
3. Not have a personal (i.e., not shared) iPhone (4s or newer running iOS 8.0 or later)
4. Not be able to read and understand an official language of the country of participation
5. Not be able to give informed consent
6. Not be willing to follow study procedures

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: Non-Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Participants with Parkinson disease; People who report a diagnosis of Parkinson disease. Participants are invited via the Parkinson mPower mobile application to complete the following behavioral interventions: Participant self-assessment surveys, Phonation, Gait and balance, Memory, Dexterity, and Participant open-response writing.	Behavioral: Participant self-assessment surveys; At enrollment, participants are asked to complete a baseline health history and a participant-reported symptom inventory. Thereafter, participants are asked to respond to commonly used questions that assess Parkinson Disease symptoms and quality of life at regular intervals.; Behavioral: Phonation; Participants are asked to record themselves saying "Aaah" for 10 seconds using the iPhone microphone. This activity is designed to assess vocal features, including vocal tremor. The investigators extract features from the digital audio signals of these sustained phonations. The investigators apply feature selection and classifier algorithms and analyze these phonations using methods similar to those employed in the Parkinson Voice Initiative.; Behavioral: Gait and balance; Participants are asked to walk back and forth for 30 seconds and then stand still for 30 seconds. Gait and balance are measured by gyroscope and accelerometer sensors. The investigators examine step-dependent and sequence-dependent features from these sensors. The investigators apply feature selection and classifier algorithms to analyze these data.; Behavioral: Memory; Participants are asked to complete a visuospatial short-term memory game related to the Corsi block tapping test [Corsi, P.M. (1972)] as adapted by Kate Possin, PhD of the University of California San Francisco Memory and Aging Center (personal communication, 2015). In this activity, participants are presented with a grid of objects that change color in a set pattern. Participants are then asked to tap the objects in that same pattern. The investigators assess the sequence length completed.; Behavioral: Dexterity; Participants are asked to tap on the phone screen with alternating fingers. This test can be done with either or both hands. The investigators record the rhythm, speed, and location of these taps using the touch sensors of the iPhone screen. The investigators assess participant dexterity through a combination of steadiness, speed, and tap precision.; Behavioral: Participant open-response writing; Qualitative participant feedback is used to assess participant engagement with, understanding of, and acceptance of app-based research.; Other: Parkinson mPower mobile application; Participants complete all described behavioral interventions via a dedicated iPhone app, Parkinson mPower.
Experimental: Participants without Parkinson disease; People who do not report a diagnosis of Parkinson disease. Participants are invited via the Parkinson mPower mobile application to complete the following behavioral interventions: Participant self-assessment surveys, Phonation, Gait and balance, Memory, Dexterity, and Participant open-response writing.	Behavioral: Participant self-assessment surveys; At enrollment, participants are asked to complete a baseline health history and a participant-reported symptom inventory. Thereafter, participants are asked to respond to commonly used questions that assess Parkinson Disease symptoms and quality of life at regular intervals.; Behavioral: Phonation; Participants are asked to record themselves saying "Aaah" for 10 seconds using the iPhone microphone. This activity is designed to assess vocal features, including vocal tremor. The investigators extract features from the digital audio signals of these sustained phonations. The investigators apply feature selection and classifier algorithms and analyze these phonations using methods similar to those employed in the Parkinson Voice Initiative.; Behavioral: Gait and balance; Participants are asked to walk back and forth for 30 seconds and then stand still for 30 seconds. Gait and balance are measured by gyroscope and accelerometer sensors. The investigators examine step-dependent and sequence-dependent features from these sensors. The investigators apply feature selection and classifier algorithms to analyze these data.; Behavioral: Memory; Participants are asked to complete a visuospatial short-term memory game related to the Corsi block tapping test [Corsi, P.M. (1972)] as adapted by Kate Possin, PhD of the University of California San Francisco Memory and Aging Center (personal communication, 2015). In this activity, participants are presented with a grid of objects that change color in a set pattern. Participants are then asked to tap the objects in that same pattern. The investigators assess the sequence length completed.; Behavioral: Dexterity; Participants are asked to tap on the phone screen with alternating fingers. This test can be done with either or both hands. The investigators record the rhythm, speed, and location of these taps using the touch sensors of the iPhone screen. The investigators assess participant dexterity through a combination of steadiness, speed, and tap precision.; Behavioral: Participant open-response writing; Qualitative participant feedback is used to assess participant engagement with, understanding of, and acceptance of app-based research.; Other: Parkinson mPower mobile application; Participants complete all described behavioral interventions via a dedicated iPhone app, Parkinson mPower.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Results of participant self-assessment surveys	Results of participant self-assessment surveys will be analyzed using descriptive statistics. These results may also be compared with other intervention results.	Through study completion, an average of 1 year
Digital audio signals of sustained phonation from phonation intervention	The investigators extract features from the digital audio signals of sustained phonations. The investigators apply feature selection and classifier algorithms and analyze these phonations using methods similar to those employed in the Parkinson Voice Initiative (http://www.parkinsonsvoice.org/science.php). These results may also be compared with other intervention results.	Through study completion, an average of 1 year
Gyroscope and accelerometer sensor measurements from gait and balance intervention	The investigators examine step-dependent and sequence-dependent features from gyroscope and accelerometer sensors. The investigators apply feature selection and classifier algorithms to analyze these data. These results may also be compared with other intervention results.	Through study completion, an average of 1 year
Sequence length from memory intervention	The investigators assess the sequence length completed in the Memory intervention. These results may also be compared with other intervention results.	Through study completion, an average of 1 year
iPhone screen touch sensor data on rhythm, speed, and location of taps from dexterity intervention	The investigators assess participant dexterity through a combination of steadiness, speed, and tap precision. These results may also be compared with other intervention results.	Through study completion, an average of 1 year
App usage data for assessment of participant engagement	App usage data is used to gauge participant engagement throughout the study period. These results may also be compared with other intervention results.	Through study completion, an average of 1 year
Qualitative analysis of participant open-response and app usage data to assess participant acceptance of app-based research	App usage data and qualitative participant feedback are used to assess participant understanding and acceptance of app-based research. These results may also be compared with other intervention results.	Through study completion, an average of 1 year

Collaborators and Investigators

• Sponsor: Sage Bionetworks
• Collaborators: Robert Wood Johnson Foundation
• Investigators: Principal Investigator: Lara Mangravite, PhD, Sage Bionetworks

Publications and helpful links

General Publications

• Kessels RP, van Zandvoort MJ, Postma A, Kappelle LJ, de Haan EH. The Corsi Block-Tapping Task: standardization and normative data. Appl Neuropsychol. 2000;7(4):252-8. doi: 10.1207/S15324826AN0704_8.
• Corsi, P.M. (1972). Human memory and the medial temporal region of the brain (Ph.D.). McGill University.
• Klucken J, Barth J, Kugler P, Schlachetzki J, Henze T, Marxreiter F, Kohl Z, Steidl R, Hornegger J, Eskofier B, Winkler J. Unbiased and mobile gait analysis detects motor impairment in Parkinson's disease. PLoS One. 2013;8(2):e56956. doi: 10.1371/journal.pone.0056956. Epub 2013 Feb 19.
• Chaibub Neto E, Bot BM, Perumal T, Omberg L, Guinney J, Kellen M, Klein A, Friend SH, Trister AD. PERSONALIZED HYPOTHESIS TESTS FOR DETECTING MEDICATION RESPONSE IN PARKINSON DISEASE PATIENTS USING iPHONE SENSOR DATA. Pac Symp Biocomput. 2016;21:273-84.

Helpful Links

• mPower study website

Study record dates

Study Major Dates

• Study Start: March 1, 2015
• Primary Completion (Anticipated): February 1, 2018
• Study Completion (Anticipated): February 1, 2018

Study Registration Dates

• First Submitted: February 23, 2016
• First Submitted That Met QC Criteria: March 1, 2016
• First Posted (Estimate): March 2, 2016

Study Record Updates

• Last Update Posted (Actual): October 24, 2017
• Last Update Submitted That Met QC Criteria: October 20, 2017
• Last Verified: October 1, 2017

More Information

Terms related to this study

• Keywords: Health app research; mHealth research; Mobile health research; Mobile application health research
• Additional Relevant MeSH Terms: Pathologic Processes; Synucleinopathies; Disease; Parkinson Disease; Nervous System Diseases; Brain Diseases; Neurodegenerative Diseases; Movement Disorders; Parkinsonian Disorders; Central Nervous System Diseases; Basal Ganglia Diseases
• Other Study ID Numbers: 201410711; 20141369 (Other Identifier: Western Instiutional Review Board)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: Yes
• IPD Plan Description: Coded data authorized for sharing by participants will be made available for research purposes via Synapse, Sage Bionetworks' analysis platform. Coded data is study data that does not include participants names or other directly identifying information.

Study Data/Documents

1. Data description
   Information comments: Here we present data from mPower, a clinical observational study about Parkinson disease conducted purely through an iPhone app interface. The study interrogated aspects of this movement disorder through surveys and frequent sensor-based recordings from participants with and without Parkinson disease. Benefitting from large enrollment and repeated measurements on many individuals, these data may help establish baseline variability of real-world activity measurement collected via mobile phones, and ultimately may lead to quantification of the ebbs-and-flows of Parkinson symptoms. App source code for these data collection modules are available through an open source license for use in studies of other conditions. We hope that releasing data contributed by engaged research participants will seed a new community of analysts working collaboratively on understanding mobile health data to advance human health.