bring your own device

BACKGROUND: People living with multiple sclerosis (MS) face a higher likelihood of being diagnosed with a depressive disorder than the general population. Although many low-cost screening tools and evidence-based interventions exist, depression in people living with MS is underreported, underascertained by clinicians, and undertreated. OBJECTIVE: This study aims to design a closed-loop tool to improve depression care for these patients. It would support regular depression screening, tie into the point of care, and support shared decision-making and comprehensive follow-up...

BACKGROUND: Falls are common in people with multiple sclerosis (MS), causing injuries, fear of falling, and loss of independence. Although targeted interventions (physical therapy) can help, patients underreport and clinicians undertreat this issue. Patient-generated data, combined with clinical data, can support the prediction of falls and lead to timely intervention (including referral to specialized physical therapy). To be actionable, such data must be efficiently delivered to clinicians, with care customized to the patient's specific context...

Floodlight Open was a global, open-access, digital-only study designed to understand the drivers and barriers in deployment and use of a smartphone app in a naturalistic setting and broad study population of people with and without multiple sclerosis (MS). The study utilised the Floodlight Open app: a 'bring-your-own-device' solution that remotely measures a user's mood, cognition, hand motor function, and gait and postural stability via smartphone sensor-based tests requiring active user input ('active tests')...

Delayed functional recovery after injury is associated with significant personal and socioeconomic burden. Identification of patients at risk for a prolonged recovery after a musculoskeletal injury is thus of high relevance. The aim of the current study was to show the feasibility of using a machine learning assisted model to predict functional recovery based on the pre- and immediate post injury patient activity as measured with wearable systems in trauma patients. Patients with a pre-existing wearable (smartphone and/or body-worn sensor), data availability of at least 7 days prior to their injury, and any musculoskeletal injury of the upper or lower extremity were included in this study...

This study aims to investigate the impact of using synchronized computer-mediated communication (SCMC) in a face-to-face (FTF) classroom on reducing foreign language anxiety (FLA) and enhancing the learning experience. Fifty Chinese college students participated in a learning activity under three modes: normal FTF classroom (the blank sample), pure SCMC, and hybrid SCMC (BYOD). Smartphones, PCs, open internet, and the bring-your-own-device (BYOD) concept were used for SCMC applications. After completing the learning activity, the students completed Foreign Language Classroom Anxiety Scale (FLCAS) questionnaires...

BACKGROUND: By eliminating the requirement for participants to make frequent visits to research sites, mobile phone applications ("apps") may help to decentralize clinical trials. Apps may also be an effective mechanism for capturing patient-reported outcomes and other endpoints, helping to optimize patient care during and outside of clinical trials. OBJECTIVES: We report on the usability of Digital BioMarkers for Clinical Impact (DigiBioMarC™ (DBM)), a novel smartphone-based app used by cancer patients in conjunction with a wearable device (Apple Watch®)...

The ISPOR Task Force on measurement comparability between modes of data collection for patient-reported outcome measures (PROMs) has updated the good practice recommendations from the 2009 ISPOR electronic patient-reported outcome and 2014 patient-reported outcome mixed modes Good Research Practices Task Force reports in light of accumulated evidence of measurement comparability among different modes of PROM data collection. Furthermore, with the increasing use of electronic formats of clinical outcome assessments in clinical trials and the US Food and Drug Administration's encouragement of electronic data collection, this new task force report provides stakeholders with best practice recommendations reflecting the current body of evidence and enables them to respond to future developments in research and technology...

OBJECTIVE: The popularity of the ​"bring your own device (BYOD)" ​concept has grown in recent years, and its application has extended to the healthcare field. This study was aimed at examining nurses' acceptance of a BYOD-supported system after a 9-month implementation period. METHODS: We used the technology acceptance model to develop and validate a structured questionnaire as a research tool. All nurses ( n  ​= ​18) responsible for the BYOD-supported wards during the study period were included in our study...

Background and Objectives : Outcome data from wearable devices are increasingly used in both research and clinics. Traditionally, a dedicated device is chosen for a given study or clinical application to collect outcome data as soon as the patient is included in a study or undergoes a procedure. The current study introduces a new measurement strategy, whereby patients' own devices are utilized, allowing for both a pre-injury baseline measure and ability to show achievable results. Materials and Methods : Patients with a pre-existing musculoskeletal injury of the upper and lower extremity were included in this exploratory, proof-of-concept study...

Although mobile devices support physicians in a variety of ways in everyday clinical practice, the use of (personal) mobile devices poses potential risks for information security, data protection, and patient safety in hospitals. We used a cross-sectional survey-based study design to assess the current state of smartphone use among resident physicians in hospitals and to investigate the relationships between working conditions, current smartphone usage patterns, and security-related behavior. In total, data from 343 participating physicians could be analyzed...

The National Institutes of Health's (NIH) All of Us Research Program aims to enroll at least one million US participants from diverse backgrounds; collect electronic health record (EHR) data, survey data, physical measurements, biospecimens for genomics and other assays, and digital health data; and create a researcher database and tools to enable precision medicine research [1]. Since inception, digital health technologies (DHT) have been envisioned as essential to achieving the goals of the program [2]. A "bring your own device" (BYOD) study for collecting Fitbit data from participants' devices was developed with integration of additional DHTs planned in the future [3]...

OBJECTIVE: To quantitatively compare equivalence and compliance of patient-reported outcome (PRO) data collected via provisioned device (PD) versus bring your own device (BYOD). METHODS: Participants with stable chronic obstructive pulmonary disease (COPD) completed the EXAcerbations of Chronic Pulmonary Disease Tool (EXACT® ) daily and COPD Assessment Test™ (CAT) and Patient Global Impression of Severity (PGIS) of COPD weekly on either PD or BYOD for 15 days, then switched device types for 15 days...

Studies using remote cognitive testing must make a critical decision: whether to allow participants to use their own devices or to provide participants with a study-specific device. Bring-your-own-device (BYOD) studies have several advantages including increased accessibility, potential for larger sample sizes, and reduced participant burden. However, BYOD studies offer little control over device performance characteristics that could potentially influence results. In particular, response times measured by each device not only include the participant's true response time, but also latencies of the device itself...

Background: Digital health technologies are attracting attention as novel tools for data collection in clinical research. They present alternative methods compared to in-clinic data collection, which often yields snapshots of the participants' physiology, behavior, and function that may be prone to biases and artifacts, e.g., white coat hypertension, and not representative of the data in free-living conditions. Modern digital health technologies equipped with multi-modal sensors combine different data streams to derive comprehensive endpoints that are important to study participants and are clinically meaningful...

OBJECTIVE: Healthcare professionals are known to use their personal devices extensively for work purposes (Bring-Your-Own-Device). However, it is also a source of major concern for healthcare organisations, given the heavy reliance of patient data privacy on clinician's usage behaviour and higher risk of data breaches. Previous research into hospital BYOD security has been scarce and fragmented. Therefore, the aim of this paper is to understand the preferences, behaviour, and knowledge of Australian hospital clinical staff with respect to BYOD security through a survey...

BACKGROUND: There is interest in participants using their own smartphones or tablets ("bring your own device"; BYOD) to complete patient-reported outcome (PRO) measures in clinical studies. Our study aimed to qualitatively evaluate participants' experience using a provisioned device (PD) versus their own smartphone (BYOD) for this purpose. METHODS: Participants with chronic obstructive pulmonary disease (COPD) were recruited for this observational, cross-over study and completed PRO measures daily on one device type for 15 days, then switched to the other device type to complete the same measures for another 15 days...

BACKGROUND: The use of digital technology to assess patients remotely can reduce clinical study costs. In the European Union, the 2D matrix code on prescription drug packaging serves as a unique identifier of a given package of medication, and thus, also of the patient receiving that medication. Scanning of the 2D matrix code may therefore allow remote patient authentication in clinical studies. OBJECTIVE: The aim of the DePRO study was to assess the feasibility of a fully digital data-capture workflow, the authentication of participants via drug packaging 2D matrix codes, in patients with type 2 diabetes mellitus (T2DM) who use metformin...

BACKGROUND: Smartphones provide opportunities for musculoskeletal research: they are integrated in participants' daily lives and can be used to collect patient-reported outcomes as well as sensor data from large groups of people. As the field of research with smartphones and smartwatches matures, it has transpired that some of the advantages of this modern technology are in fact double-edged swords. BODY: In this narrative review, we illustrate the advantages of using smartphones for data collection with 18 studies from various musculoskeletal domains...

Bring-your-own-device (BYOD) methods for collecting patient-reported outcome (PRO) data in clinical trials can decrease patient burden and improve data quality. However, adoption of BYOD in clinical trials is limited by the absence of publicly available case studies where BYOD PRO data supported regulatory medical product approvals. Anecdotally, we are aware of multiple examples where efficacy and safety label claims were based on BYOD PRO data; however-except for one-these examples have not been made public...

To investigate the feasibility of utilizing electronically provided patient-reported outcomes(ePRO)to detect adverse events, we conducted a single-center prospective study targeting patients with advanced cancers who were receiving chemotherapy at our outpatient clinic. Participants were asked to respond to 71 relevant items from the PRO-CTCAE once a week for 8 consecutive weeks. An outpatient nurse evaluated the corresponding items on the CTCAE. Forty of 85 outpatients were enrolled. Thirty-four patients were excluded because of Bring Your Own Device(BYOD)restrictions and 11 were excluded for other reasons, including poor physical conditions...