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 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

A sociolinguistic analysis of the use of English loanwords inflected with Arabic morphemes as slang in Amman, Jordan

2019 ◽  
Vol 2019 (260) ◽  
pp. 155-175
Author(s):  
Aseel Zibin ◽  
Khawlah M. AL-Tkhayneh
Keyword(s):  
Data Analysis ◽  
Qualitative Data ◽  
Group Membership ◽  
Economic Status ◽  
Structured Interviews ◽  
Socio Economic Status ◽  
Linguistic Behaviour ◽  
Major Factors ◽  
The University ◽  
Insight Into

Abstract This study aims to examine the use of English loanwords inflected with Arabic morphemes by young people in Amman, Jordan. It adopts a quantitative corpus-based approach supported by qualitative data. We collected data from young Facebook male and female users who come from families with different socio-economic status, and we conducted semi-structured interviews with 60 students at the University of Jordan to get more insight into the attitudes of young individuals in Jordan who use these English loanwords, and to account for the reasons that drive these individuals to use them. Data analysis shows that the participants’ gender and socioeconomic status are major factors that affect the use of these loanwords. Data analysis also reveals that these English loanwords could be used as a form of slang by a certain group of young individuals in Amman to claim a specific social identity and an in-group membership that distinguishes them from another group of young individuals who do not use these words. We argued that a number of symbolic values could be attached to the use of English loanwords inflected with Arabic morphemes by that group and analysed the reasons behind such linguistic behaviour.

scholarly journals Smartphone-Based Application “quizizz” as a Learning Media

2019 ◽  
Vol 14 (2) ◽  
pp. 244-253
Author(s):  
Ramadhan Prasetya Wibawa ◽  
Rohana Intan Astuti ◽  
Bayu Aji Pangestu
Keyword(s):  
Data Analysis ◽  
Student Learning ◽  
Learning Outcomes ◽  
Qualitative Data ◽  
Student Learning Outcomes ◽  
Economic Education ◽  
Interactive Method ◽  
Analysis Technique ◽  
Improving Student Learning ◽  
The University

This study aims to find out the application and contribution of smartphone-based application ““quizizz”” as learning media in the University of PGRI Madiun. The method used in this research is descriptive qualitative. Data analysis technique used is an interactive method, including the process of collecting data, reducing data (compiling data in patterns, categories and specific issues), presenting data (compiling data in the form of matrices, graphs, networks, certain charts) and drawing conclusions. This research was conducted at the University of PGRI Madiun. The subjects of this study were students in Accounting and Economic Education. The results showed that the usage of smartphone-based application “quizizz” as learning media can make students enthusiastic in participating in learning, so students can focus and maximize the use of smartphones as a fun learning media. The concept of maximum learning will have an impact on improving student learning outcomes.

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