A Novel Smartphone Application for "Smart" Trials

NCT04052282 | Completed

• 1 other identifier: IRB #:13237
• Study Type: observational
• Target: 20
• Locations: 1 country
• Sites: 1

Brief Summary

The overarching goal is to develop a mHealth App that can use smartphone embedded sensors to objectively collect physical function data in healthy individuals in the context of daily life.

Conditions

Healthy

Keywords

Technology; Physical Function

Outcome Measures

Primary Outcomes (12)

• Numeric Rating Scale - TEST RETEST (clinical setting)

  A Numeric Rating Scale (NRS) will be applied to measure both knee pain. NRS is a well recognized tool to measure the intensity of pain that visually represents the intensity of pain that the individual believes to present. The scale will be displayed on the app and will have a range of 0 to 10, with 0 being the complete absence of pain and 10, the maximum intensity of pain reported by the individual.

  Day 1

• Numeric Rating Scale - TEST RETEST (clinical setting)

  A Numeric Rating Scale (NRS) will be applied to measure both knee pain. NRS is a well recognized tool to measure the intensity of pain that visually represents the intensity of pain that the individual believes to present. The scale will be displayed on the app and will have a range of 0 to 10, with 0 being the complete absence of pain and 10, the maximum intensity of pain reported by the individual.

  7 days after day 1

• Numeric Rating Scale - DIURNAL CHANGE (home setting)

  At home, a Numeric Rating Scale (NRS) will be applied to measure both knee pain. NRS is a well recognized tool to measure the intensity of pain that visually represents the intensity of pain that the individual believes to present. The scale will be displayed on the app and will have a range of 0 to 10, with 0 being the complete absence of pain and 10, the maximum intensity of pain reported by the individual.

  Day 1, day 3, and day 5 (within a week Mon, Wed, Fri)

• The Get up and Go - TEST RETEST (clinical setting)

  In the clinical setting, the clinician asks the patient to stand up from a chair, walk 3 meters, turn around, return and sit back in the chair. The time on the test is used as a predictor of functional independence: below 20 seconds is considered normal and over 30 seconds as potentially indicative of increased risk for falls and functional dependence. For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will pre-determine and tell the patient how many steps to take to achieve the distance of 3 meters. After the test is completed, the data will be automatically sent to the cloud system.

  Day 1

• The Get up and Go - TEST RETEST (clinical setting)

  In the clinical setting, the clinician asks the patient to stand up from a chair, walk 3 meters, turn around, return and sit back in the chair. The time on the test is used as a predictor of functional independence: below 20 seconds is considered normal and over 30 seconds as potentially indicative of increased risk for falls and functional dependence. For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will pre-determine and tell the patient how many steps to take to achieve the distance of 3 meters. After the test is completed, the data will be automatically sent to the cloud system.

  7 days after day 1

• The Get up and Go - DIURNAL CHANGE (home setting)

  At home, for the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will pre-determine and tell the patient how many steps to take to achieve the distance of 3 meters. After the test is completed, the data will be automatically sent to the cloud system.

  Day 1, day 3, and day 5 (within a week Mon, Wed, Fri)

• The 30 Seconds Sit to Stand - TEST RETEST (clinical setting)

  In the clinical setting, the clinician asks the patient to sit in the middle of the chair, with the back straight, feet apart resting on the floor and in line with the shoulders. The patient has to rise from a sitting to a standing position as many times as possible in 30 seconds. With the results of this test, it is possible to evaluate a wide variety of skill levels, with scores ranging from 0 (for those unable to complete one repetition) to more than 20 repetitions (for the most physically fit individuals). For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically count the total sit to stand repetitions within a 30 seconds period. After the test is completed, the data will be automatically sent to the cloud system.

  Day 1

• The 30 Seconds Sit to Stand - TEST RETEST (clinical setting)

  In the clinical setting, the clinician asks the patient to sit in the middle of the chair, with the back straight, feet apart resting on the floor and in line with the shoulders. The patient has to rise from a sitting to a standing position as many times as possible in 30 seconds. With the results of this test, it is possible to evaluate a wide variety of skill levels, with scores ranging from 0 (for those unable to complete one repetition) to more than 20 repetitions (for the most physically fit individuals). For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically count the total sit to stand repetitions within a 30 seconds period. After the test is completed, the data will be automatically sent to the cloud system.

  7 days after day 1

• The 30 Seconds Sit to Stand - DIURNAL CHANGE (home setting)

  At home, for the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically count the total sit to stand repetitions within a 30 seconds period. After the test is completed, the data will be automatically sent to the cloud system.

  Day 1, day 3, and day 5 (within a week Mon, Wed, Fri)

• The 20-meter Walk - TEST RETEST (clinical setting)

  This test assesses gait speed and changes in patient's physical function over time. The clinician asks the patient to walk at a comfortable pace in a 20-meter unobstructed course and measures the time to perform the test. For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a standing position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically determine when the 20-meter distance is reached and will say to the patient to gradually stop, measuring the total time to complete the test. After the test is completed, the data will be automatically sent to the cloud system.

  Day 1

• The 20-meter Walk - TEST RETEST (clinical setting)

  This test assesses gait speed and changes in patient's physical function over time. The clinician asks the patient to walk at a comfortable pace in a 20-meter unobstructed course and measures the time to perform the test. For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a standing position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically determine when the 20-meter distance is reached and will say to the patient to gradually stop, measuring the total time to complete the test. After the test is completed, the data will be automatically sent to the cloud system.

  7 days after day 1

• The 20-meter Walk - DIURNAL CHANGE (home setting)

  At home, for the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a standing position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically determine when the 20-meter distance is reached and will say to the patient to gradually stop, measuring the total time to complete the test. After the test is completed, the data will be automatically sent to the cloud system.

  Day 1, day 3, and day 5 (within a week Mon, Wed, Fri)

Study Arms (1)

Mobile Health App - Healthy Individuals

Mobile health App - Test Beta Testing 1: The Beta test 1 will be performed with participants inside the Research Center. The purpose of this phase is to increase usability, acceptability and reliability of the mHealth App in participants. Beta Testing 2: The Beta test 2 will be performed with patients outside the Research Center, at their houses. The purpose is to focus on the mHealth App remote usability, acceptability, and data collection.

Device: Mobile Health App

Interventions

Mobile Health App DEVICE

There is no intervention

Mobile Health App - Healthy Individuals

Eligibility Criteria

• Age: 50 Years - 85 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

This study includes healthy subjects who are equal or greater than 50 years old.

You may qualify if:

• Male or female subjects at least 50 years old with symptomatic knee osteoarthritis
• English Speaker
• Be able to walk 20 meters without an assistive device, such as a cane, walker or crutches.
• Have an iPhone 6 or higher with internet connection.

You may not qualify if:

• Prior surgery on either knee within 6 months of enrollment
• Received corticosteroid injection in the knee within 3 months of enrollment
• Evidence or history of knee disease or trauma

Sponsors & Collaborators

• Universidade Federal de Sao Carlos: lead
• Tufts Medical Center: collaborator

Study Sites (1)

Federal University of São Carlos

São Carlos, São Paulo, 13565905, Brazil

Location

Study Officials

• Lucas O Dantas, PT

  Universidade Federal de Sao Carlos

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Co-Principal Investigator

Study Record Dates

• First Submitted: August 5, 2019
• First Posted: August 9, 2019
• Study Start: September 3, 2019
• Primary Completion: July 1, 2021
• Study Completion: August 1, 2021
• Last Updated: September 29, 2021

Record last verified: 2021-09

Locations

BR (1)