scholarly journals Engagement and Participant Experiences With Consumer Smartwatches for Health Research: Longitudinal, Observational Feasibility Study (Preprint)

2019 ◽  
Author(s):  
Anna L Beukenhorst ◽  
Kelly Howells ◽  
Louise Cook ◽  
John McBeth ◽  
Terence W O'Neill ◽  
...  
Keyword(s):  
Data Collection ◽  
Knee Osteoarthritis ◽  
Patient Reported Outcomes ◽  
Health Data ◽  
Self Report ◽  
Sensor Data ◽  
Battery Life ◽  
Activity Data ◽  
Technical Problems ◽  
Patient Reported

BACKGROUND Wearables provide opportunities for frequent health data collection and symptom monitoring. The feasibility of using consumer cellular smartwatches to provide information both on symptoms and contemporary sensor data has not yet been investigated. OBJECTIVE This study aimed to investigate the feasibility and acceptability of using cellular smartwatches to capture multiple patient-reported outcomes per day alongside continuous physical activity data over a 3-month period in people living with knee osteoarthritis (OA). METHODS For the KOALAP (Knee OsteoArthritis: Linking Activity and Pain) study, a novel cellular smartwatch app for health data collection was developed. Participants (age ≥50 years; self-diagnosed knee OA) received a smartwatch (Huawei Watch 2) with the KOALAP app. When worn, the watch collected sensor data and prompted participants to self-report outcomes multiple times per day. Participants were invited for a baseline and follow-up interview to discuss their motivations and experiences. Engagement with the watch was measured using daily watch wear time and the percentage completion of watch questions. Interview transcripts were analyzed using grounded thematic analysis. RESULTS A total of 26 people participated in the study. Good use and engagement were observed over 3 months: most participants wore the watch on 75% (68/90) of days or more, for a median of 11 hours. The number of active participants declined over the study duration, especially in the final week. Among participants who remained active, neither watch time nor question completion percentage declined over time. Participants were mainly motivated to learn about their symptoms and enjoyed the self-tracking aspects of the watch. Barriers to full engagement were battery life limitations, technical problems, and unfulfilled expectations of the watch. Participants reported that they would have liked to report symptoms more than 4 or 5 times per day. CONCLUSIONS This study shows that capture of patient-reported outcomes multiple times per day with linked sensor data from a smartwatch is feasible over at least a 3-month period. INTERNATIONAL REGISTERED REPORT RR2-10.2196/10238

scholarly journals Engagement and Participant Experiences With Consumer Smartwatches for Health Research: Longitudinal, Observational Feasibility Study

10.2196/14368 ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. e14368 ◽  
Author(s):  
Anna L Beukenhorst ◽  
Kelly Howells ◽  
Louise Cook ◽  
John McBeth ◽  
Terence W O'Neill ◽  
...  
Keyword(s):  
Data Collection ◽  
Knee Osteoarthritis ◽  
Patient Reported Outcomes ◽  
Health Data ◽  
Self Report ◽  
Sensor Data ◽  
Battery Life ◽  
Activity Data ◽  
Technical Problems ◽  
Patient Reported

Background Wearables provide opportunities for frequent health data collection and symptom monitoring. The feasibility of using consumer cellular smartwatches to provide information both on symptoms and contemporary sensor data has not yet been investigated. Objective This study aimed to investigate the feasibility and acceptability of using cellular smartwatches to capture multiple patient-reported outcomes per day alongside continuous physical activity data over a 3-month period in people living with knee osteoarthritis (OA). Methods For the KOALAP (Knee OsteoArthritis: Linking Activity and Pain) study, a novel cellular smartwatch app for health data collection was developed. Participants (age ≥50 years; self-diagnosed knee OA) received a smartwatch (Huawei Watch 2) with the KOALAP app. When worn, the watch collected sensor data and prompted participants to self-report outcomes multiple times per day. Participants were invited for a baseline and follow-up interview to discuss their motivations and experiences. Engagement with the watch was measured using daily watch wear time and the percentage completion of watch questions. Interview transcripts were analyzed using grounded thematic analysis. Results A total of 26 people participated in the study. Good use and engagement were observed over 3 months: most participants wore the watch on 75% (68/90) of days or more, for a median of 11 hours. The number of active participants declined over the study duration, especially in the final week. Among participants who remained active, neither watch time nor question completion percentage declined over time. Participants were mainly motivated to learn about their symptoms and enjoyed the self-tracking aspects of the watch. Barriers to full engagement were battery life limitations, technical problems, and unfulfilled expectations of the watch. Participants reported that they would have liked to report symptoms more than 4 or 5 times per day. Conclusions This study shows that capture of patient-reported outcomes multiple times per day with linked sensor data from a smartwatch is feasible over at least a 3-month period. International Registered Report Identifier (IRRID) RR2-10.2196/10238

scholarly journals Collecting Symptoms and Sensor Data With Consumer Smartwatches (the Knee OsteoArthritis, Linking Activity and Pain Study): Protocol for a Longitudinal, Observational Feasibility Study (Preprint)

2018 ◽  
Author(s):  
Anna L Beukenhorst ◽  
Matthew J Parkes ◽  
Louise Cook ◽  
Rebecca Barnard ◽  
Sabine N van der Veer ◽  
...  
Keyword(s):  
Data Analysis ◽  
Knee Osteoarthritis ◽  
Data Quality ◽  
Patient Reported Outcomes ◽  
Qualitative Data ◽  
Sensor Data ◽  
System Level ◽  
Patient Reported ◽  
Information Governance ◽  
The University

BACKGROUND The Knee OsteoArthritis, Linking Activity and Pain (KOALAP) study is the first to test the feasibility of using consumer-grade cellular smartwatches for health care research. OBJECTIVE The overall aim was to investigate the feasibility of using consumer-grade cellular smartwatches as a novel tool to capture data on pain (multiple times a day) and physical activity (continuously) in patients with knee osteoarthritis. Additionally, KOALAP aimed to investigate smartwatch sensor data quality and assess whether engagement, acceptability, and user experience are sufficient for future large-scale observational and interventional studies. METHODS A total of 26 participants with self-diagnosed knee osteoarthritis were recruited in September 2017. All participants were aged 50 years or over and either lived in or were willing to travel to the Greater Manchester area. Participants received a smartwatch (Huawei Watch 2) with a bespoke app that collected patient-reported outcomes via questionnaires and continuous watch sensor data. All data were collected daily for 90 days. Additional data were collected through interviews (at baseline and follow-up) and baseline and end-of-study questionnaires. This study underwent full review by the University of Manchester Research Ethics Committee (#0165) and University Information Governance (#IGRR000060). For qualitative data analysis, a system-level security policy was developed in collaboration with the University Information Governance Office. Additionally, the project underwent an internal review process at Google, including separate reviews of accessibility, product engineering, privacy, security, legal, and protection regulation compliance. RESULTS Participants were recruited in September 2017. Data collection via the watches was completed in January 2018. Collection of qualitative data through patient interviews is still ongoing. Data analysis will commence when all data are collected; results are expected in 2019. CONCLUSIONS KOALAP is the first health study to use consumer cellular smartwatches to collect self-reported symptoms alongside sensor data for musculoskeletal disorders. The results of this study will be used to inform the design of future mobile health studies. Results for feasibility and participant motivations will inform future researchers whether or under which conditions cellular smartwatches are a useful tool to collect patient-reported outcomes alongside passively measured patient behavior. The exploration of associations between self-reported symptoms at different moments will contribute to our understanding of whether it may be valuable to collect symptom data more frequently. Sensor data–quality measurements will indicate whether cellular smartwatch usage is feasible for obtaining sensor data. Methods for data-quality assessment and data-processing methods may be reusable, although generalizability to other clinical areas should be further investigated. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/10238

scholarly journals Comparative Effectiveness Study of Home-Based Interventions to Prevent CA-MRSA Infection Recurrence

Antibiotics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1105
Author(s):  
Jonathan N. Tobin ◽  
Suzanne Hower ◽  
Brianna M. D’Orazio ◽  
María Pardos de la Gándara ◽  
Teresa H. Evering ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Patient Reported Outcomes ◽  
Health Workers ◽  
Home Visits ◽  
Self Report ◽  
Household Member ◽  
Surveillance Culture ◽  
Home Based ◽  
Patient Reported ◽  
Household Members

Recurrent skin and soft tissue infections (SSTI) caused by Community-Associated Methicillin-Resistant Staphylococcus aureus (CA-MRSA) or Methicillin-Sensitive Staphylococcus aureus (CA-MSSA) present treatment challenges. This community-based trial examined the effectiveness of an evidence-based intervention (CDC Guidelines, topical decolonization, surface decontamination) to reduce SSTI recurrence, mitigate household contamination/transmission, and improve patient-reported outcomes. Participants (n = 186) were individuals with confirmed MRSA(+)/MSSA(+) SSTIs and their household members. During home visits; Community Health Workers/Promotoras provided hygiene instructions; a five-day supply of nasal mupirocin; chlorhexidine for body cleansing; and household disinfecting wipes (Experimental; EXP) or Usual Care Control (UC CON) pamphlets. Primary outcome was six-month SSTI recurrence from electronic health records (EHR). Home visits (months 0; 3) and telephone assessments (months 0; 1; 6) collected self-report data. Index patients and participating household members provided surveillance culture swabs. Secondary outcomes included household surface contamination; household member colonization and transmission; quality of life; and satisfaction with care. There were no significant differences in SSTI recurrence between EXP and UC in the intent-to-treat cohort (n = 186) or the enrolled cohort (n = 119). EXP participants showed reduced but non-significant colonization rates. EXP and UC did not differ in household member transmission, contaminated surfaces, or patient-reported outcomes. This intervention did not reduce clinician-reported MRSA/MSSA SSTI recurrence. Taken together with other recent studies that employed more intensive decolonization protocols, it is possible that a promotora-delivered intervention instructing treatment for a longer or repetitive duration may be effective and should be examined by future studies.

scholarly journals Sleep Tracking and Exercise in Patients With Type 2 Diabetes Mellitus (Step-D): Pilot Study to Determine Correlations Between Fitbit Data and Patient-Reported Outcomes (Preprint)

2017 ◽  
Author(s):  
James Weatherall ◽  
Yurek Paprocki ◽  
Theresa M Meyer ◽  
Ian Kudel ◽  
Edward A Witt
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Pilot Study ◽  
Patient Reported Outcomes ◽  
Sleep Problems ◽  
Health Data ◽  
Patient Reported

BACKGROUND Few studies assessing the correlation between patient-reported outcomes and patient-generated health data from wearable devices exist. OBJECTIVE The aim of this study was to determine the direction and magnitude of associations between patient-generated health data (from the Fitbit Charge HR) and patient-reported outcomes for sleep patterns and physical activity in patients with type 2 diabetes mellitus (T2DM). METHODS This was a pilot study conducted with adults diagnosed with T2DM (n=86). All participants wore a Fitbit Charge HR for 14 consecutive days and completed internet-based surveys at 3 time points: day 1, day 7, and day 14. Patient-generated health data included minutes asleep and number of steps taken. Questionnaires assessed the number of days of exercise and nights of sleep problems per week. Means and SDs were calculated for all data, and Pearson correlations were used to examine associations between patient-reported outcomes and patient-generated health data. All respondents provided informed consent before participating. RESULTS The participants were predominantly middle-aged (mean 54.3, SD 13.3 years), white (80/86, 93%), and female (50/86, 58%). Use of oral T2DM medication correlated with the number of mean steps taken (r=.35, P=.001), whereas being unaware of the glycated hemoglobin level correlated with the number of minutes asleep (r=−.24, P=.04). On the basis of the Fitbit data, participants walked an average of 4955 steps and slept 6.7 hours per day. They self-reported an average of 2.0 days of exercise and 2.3 nights of sleep problems per week. The association between the number of days exercised and steps walked was strong (r=.60, P<.001), whereas the association between the number of troubled sleep nights and minutes asleep was weaker (r=.28, P=.02). CONCLUSIONS Fitbit and patient-reported data were positively associated for physical activity as well as sleep, with the former more strongly correlated than the latter. As extensive patient monitoring can guide clinical decisions regarding T2DM therapy, passive, objective data collection through wearables could potentially enhance patient care, resulting in better patient-reported outcomes.

scholarly journals Measuring the outcomes of using person-generated health data: a case study of developing a PROM item bank

2019 ◽  
Vol 26 (1) ◽  
pp. e100070 ◽  
Author(s):  
Gerardo Luis Dimaguila ◽  
Kathleen Gray ◽  
Mark Merolli
Keyword(s):  
Stroke Rehabilitation ◽  
Best Practice ◽  
Patient Reported Outcome Measures ◽  
Health Condition ◽  
Health Data ◽  
Item Bank ◽  
Self Report ◽  
Development Method ◽  
Patient Reported

IntroductionPatient-reported outcome measures (PROMs) allow patients to self-report the status of their health condition or experience independently. A key area for PROMs to contribute in building the evidence base is in understanding the effects of using person-generated health data (PGHD), and using PROMs to measure outcomes of using PGHD has been suggested in the literature. Key considerations inherent in the stroke rehabilitation context makes the measurement of PGHD outcomes in home-based poststroke rehabilitation, which uses body-tracking technologies, an important use case.ObjectiveThis paper describes the development of a preliminary item bank of a PROM-PGHD for Kinect-based stroke rehabilitation systems (K-SRS), or PROM-PGHD for K-SRS.MethodsThe authors designed a method to develop PROMs of using PGHD, or PROM-PGHD. The PROM-PGHD Development Method was designed by augmenting a key PROM development process, the Qualitative Item Review, and follows PROM development best practice. It has five steps, namely, literature review; binning and winnowing; initial item revision; eliciting patient input and final item Revision.ResultsA preliminary item bank of the PROM-PGHD for K-SRS is presented. This is the result of implementing the first three steps of the PROM-PGHD Development Method within the domains of interest, that is, stroke and Kinect-based simulated rehabilitation.ConclusionsThis paper has set out a case study of our method, showing what needs to be done to ensure that the PROM-PGHD items are suited to the health condition and technology category. We described it as a case study because we argue that it is possible for the PROM-PGHD method to be used by others to measure effects of PGHD utilisation in other cases of health conditions and technology categories. Hence, it offers generalisability and has broader clinical relevance for evidence-based practice with PGHD. This paper is the first to offer a case study of developing a PROM-PGHD.

scholarly journals The HOPE Pilot Study: Harnessing Patient-Reported Outcomes and Biometric Data to Enhance Cancer Care

2018 ◽  
pp. 1-12 ◽  
Author(s):  
Alexi A. Wright ◽  
Nikita Raman ◽  
Patrick Staples ◽  
Stephanie Schonholz ◽  
Angel Cronin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Status ◽  
Clinical Outcomes ◽  
Mobile Health ◽  
Symptom Management ◽  
Patient Reported Outcomes ◽  
Perceived Effectiveness ◽  
Activity Data ◽  
Patient Reported ◽  
Wearable Accelerometers

Purpose Integrating patient-reported outcomes (PROs) into clinical practice is an increasingly promising strategy for improving patients’ symptoms, communication, and clinical outcomes. The objective of the current study was to assess the feasibility, acceptability, and perceived effectiveness of a mobile health intervention that was designed to collect PROs and activity data as a measure of health status. Patients and Methods This work was a pilot intervention with 10 patients with gynecologic cancers who received palliative chemotherapy. The HOPE (Helping Our Patients Excel) study used wearable accelerometers to assess physical activity and the Beiwe research platform to collect PROs, stratify patient responses by risk, provide tailored symptom management, and notify patients and clinicians of high-risk symptoms. Feasibility and acceptability were assessed through enrollment and adherence rates, and perceived effectiveness was evaluated by patients and oncologists at study completion. Results The approach-to-consent rate was 100%, and participants were 90% and 70% adherent to the wearable accelerometers and smartphone surveys, respectively. Participants’ mean daily step count was 3,973 (standard deviation [SD], 2,305 steps) and increased from week 1 (mean, 3,520 steps; SD, 1,937 steps) to week 3 (mean, 4,136 steps; SD, 1,578 steps). Active monitoring of participants’ heart rates, daily steps, and PROs throughout the study identified anomalies in participants’ behavior patterns that suggested poor health for two patients (20%). Patients and clinicians indicated that the intervention improved physical activity, communication, and symptom management. Conclusion A mobile health intervention that collects PROs and activity data as a measure of health status is feasible, acceptable, and was perceived to be effective in improving symptom management in patients with advanced gynecologic cancers. A larger, multisite, randomized clinical trial to assess the efficacy of the HOPE intervention on patients’ symptoms, health-related quality of life, clinical outcomes, and health care use is warranted.

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