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1.
Int J Environ Res Public Health ; 19(14)2022 Jul 06.
Article in English | MEDLINE | ID: covidwho-1917489

ABSTRACT

Technology has played a critical role during the COVID-19 pandemic. Despite affording a safe way for people to connect with others, the potential for problematic device usage (e.g., overuse, addiction) should be considered. The goal of this study was to examine mobile device use during the COVID-19 pandemic among rural and urban people in Canada. Based on an online survey conducted in the summer of 2021 in British Columbia (n = 465), participants self-reported spending more hours per day (M = 8.35 h) using technology during the pandemic compared to prior (M = 6.02 h), with higher increases among urban participants (p < 0.001). Mobile device usage scores were highest for reasons of social connectedness and productivity, with no rural/urban differences; however, urban participants reported higher use of mobile devices for their mental well-being (p = 0.001), but also reported higher, continuous use (p < 0.001), addiction (p < 0.001), and detrimental impacts on their physical health (p < 0.001) compared to rural participants. Because urban participants were more vulnerable to mobile device overuse and addiction during the pandemic, researchers and policy makers should consider the ongoing role and positive/negative impacts of mobile device use, paying particular attention to urban populations.


Subject(s)
COVID-19 , Pandemics , Adult , British Columbia/epidemiology , COVID-19/epidemiology , Computers, Handheld , Humans , Rural Population
2.
BMJ Open ; 12(6): e061917, 2022 06 21.
Article in English | MEDLINE | ID: covidwho-1902021

ABSTRACT

INTRODUCTION: Rheumatoid arthritis (RA) generally requires lifelong treatment; however, its medication complexity might affect non-adherence. Pharmacist-led telehealth services were as effective as face-to-face services and reduced potential side effects in outpatients with chronic diseases. This study aims to analyse the effect of a telepharmacy service with a customised mobile device in comparison with the usual pharmacist service on the humanistic and clinical outcomes in patients with RA. METHODS AND ANALYSIS: The study is designed as a prospective, randomised, open-label, and controlled trial to compare the humanistic and clinical outcomes of the pharmaceutical care service with monthly telecommunications and a customised mobile application (telepharmacy care group) against the usual service by community pharmacists (usual care group) in 256 patients with RA and prescribed at least one of the disease-modifying antirheumatic drugs. Participants will be recruited from a tertiary hospital in Republic of Korea with written informed consent. The primary outcome will be the changes in health-related quality of life as measured by the Korean version of the EuroQoL's five-dimensional questionnaire at 6 months compared with baseline. The secondary outcomes will be the changes in the following: scores of the Korean version of the Compliance Questionnaire-Rheumatology and medication knowledge at 3 and 6 months compared with baseline; scores of the Korean version of the Pharmacy Service Questionnaire at 6 months compared with baseline; clinical parameters such as erythrocyte sedimentation rate, C reactive protein level, and pain score at 3 and 6 months compared with baseline; frequency of acute care utilisation over 6 months. Analysis will be carried out with intent-to-treat and per-protocol principles. ETHICS AND DISSEMINATION: The study protocol was reviewed and approved by the Institutional Review Board (IRB) of Daegu Catholic University Medical Center (IRB no. CR-21-082-L, 14 July 2021). The study findings will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: KCT0006508.


Subject(s)
Arthritis, Rheumatoid , Pharmaceutical Services , Arthritis, Rheumatoid/drug therapy , Computers, Handheld , Humans , Prospective Studies , Quality of Life , Randomized Controlled Trials as Topic
3.
Sensors (Basel) ; 22(7)2022 Mar 25.
Article in English | MEDLINE | ID: covidwho-1785895

ABSTRACT

Heart rate (HR) and respiratory rate (fR) can be estimated by processing videos framing the upper body and face regions without any physical contact with the subject. This paper proposed a technique for continuously monitoring HR and fR via a multi-ROI approach based on the spectral analysis of RGB video frames recorded with a mobile device (i.e., a smartphone's camera). The respiratory signal was estimated by the motion of the chest, whereas the cardiac signal was retrieved from the pulsatile activity at the level of right and left cheeks and forehead. Videos were recorded from 18 healthy volunteers in four sessions with different user-camera distances (i.e., 0.5 m and 1.0 m) and illumination conditions (i.e., natural and artificial light). For HR estimation, three approaches were investigated based on single or multi-ROI approaches. A commercially available multiparametric device was used to record reference respiratory signals and electrocardiogram (ECG). The results demonstrated that the multi-ROI approach outperforms the single-ROI approach providing temporal trends of both the vital parameters comparable to those provided by the reference, with a mean absolute error (MAE) consistently below 1 breaths·min-1 for fR in all the scenarios, and a MAE between 0.7 bpm and 6 bpm for HR estimation, whose values increase at higher distances.


Subject(s)
Electrocardiography , Respiratory Rate , Computers, Handheld , Heart Rate , Humans , Monitoring, Physiologic , Respiratory Rate/physiology , Signal Processing, Computer-Assisted
5.
Health Place ; 72: 102679, 2021 11.
Article in English | MEDLINE | ID: covidwho-1440041

ABSTRACT

Transportation disruptions caused by COVID-19 have exacerbated difficulties in health care delivery and access, which may lead to changes in health care use. This study uses mobile device data from SafeGraph to explore the temporal patterns of visits to health care points of interest (POIs) during 2020 and examines how these patterns are associated with socio-demographic and spatial characteristics at the Census Block Group level in North Carolina. Specifically, using the K-medoid time-series clustering method, we identify three distinct types of temporal patterns of visits to health care facilities. Furthermore, by estimating multinomial logit models, we find that Census Block Groups with higher percentages of elderly persons, minorities, low-income individuals, and people without vehicle access are areas most at-risk for decreased health care access during the pandemic and exhibit lower health care access prior to the pandemic. The results suggest that the ability to conduct in-person medical visits during the pandemic has been unequally distributed, which highlights the importance of tailoring policy strategies for specific socio-demographic groups to ensure equitable health care access and delivery.


Subject(s)
COVID-19 , Telemedicine , Aged , Computers, Handheld , Health Services Accessibility , Humans , Pandemics , SARS-CoV-2
7.
Am J Cardiol ; 153: 125-128, 2021 08 15.
Article in English | MEDLINE | ID: covidwho-1293528

ABSTRACT

Mobile electrocardiogram (mECG) devices are being used increasingly, supplying recordings to providers and providing automatic rhythm interpretation. Given the intermittent nature of certain cardiac arrhythmias, mECGs allow instant access to a recording device. In the current COVID-19 pandemic, efforts to limit in-person patient interactions and avoid overwhelming emergency and inpatient services would add value. Our goal was to evaluate whether a mECG device would reduce healthcare utilization overall, particularly those of urgent nature. We identified a cohort of KardiaMobile (AliveCor, USA) mECG users and compared their healthcare utilization 1 year prior to obtaining the device and 1 year after. One hundred and twenty-eight patients were studied (mean age 64, 47% female). Mean duration of follow-up pre-intervention was 9.8 months. One hundred and twenty-three of 128 individuals completed post-intervention follow-up. Patients were less likely to have cardiac monitors ordered (30 vs 6; p <0.01), outpatient office visits (525 vs 382; p <0.01), cardiac-specific ED visits (51 vs 30; p <0.01), arrhythmia related ED visits (45 vs 20; p <0.01), and unplanned arrhythmia admissions (34 vs 11; p <0.01) in the year after obtaining a KardiaMobile device compared to the year prior to obtaining the device. Mobile technology is available for heart rhythm monitoring and can give feedback to the user. This study showed a reduction of in-person, healthcare utilization with mECG device use. In conclusion, this strategy would be expected to decrease the risk of exposure to patients and providers and would avoid overwhelming emergency and inpatient services.


Subject(s)
Arrhythmias, Cardiac/diagnosis , COVID-19/epidemiology , Computers, Handheld/statistics & numerical data , Electrocardiography/instrumentation , Monitoring, Physiologic/methods , Outpatients/statistics & numerical data , Pandemics , Patient Acceptance of Health Care/statistics & numerical data , Arrhythmias, Cardiac/epidemiology , Arrhythmias, Cardiac/physiopathology , Comorbidity , Female , Humans , Male , Middle Aged , Retrospective Studies , United States/epidemiology
8.
Comput Inform Nurs ; 39(9): 477-483, 2021 Apr 26.
Article in English | MEDLINE | ID: covidwho-1201542

ABSTRACT

The world has seen an explosion in mobile device technology over the past decade, in addition to the impact that COVID-19 has placed on nursing education programs. More specifically, mobile devices have afforded users with endless possibilities. This upsurge in mobile technology has altered the way people use and interact with their device. One such example is how these devices are being utilized for the purposes of learning due to social distancing guidelines. Thus, it becomes important to explore and understand those factors that will influence the use of mobile devices for learning. The purpose of this study was to explore variables that might influence the adoption of mobile devices among nursing faculty. The Unified Theory of Acceptance and Use of Technology served as the theoretical basis for this study and guiding framework. An exploratory quantitative survey research design was utilized to explore specific variables and their impact on mobile device adoption among participants. It was found that 85%, six of the seven research variables were statistically significant predictors of mobile device adoption. Mobile devices have the potential to leverage a wealth of resources for both users and faculty. Therefore, recommendations for developing increased use of mobile device technology for teaching and learning will be suggested.


Subject(s)
COVID-19 , Education, Nursing , Mobile Applications , Computers, Handheld , Humans , SARS-CoV-2
9.
Eur Rev Med Pharmacol Sci ; 25(7): 3116-3121, 2021 04.
Article in English | MEDLINE | ID: covidwho-1194852

ABSTRACT

OBJECTIVE: Since minimally invasive surgery and general anesthesia are both aerosol-generating procedures, their use became controversial during the outbreak of coronavirus disease 2019 (COVID-19). Moreover, social distancing resulted in serious psychological consequences for inpatients. This case report investigates pain distraction during awake laparotomy, as well as new possibilities for emotional postoperative support to inpatients. PATIENTS AND METHODS: A 72-year-old man affected by middle rectal adenocarcinoma underwent lower anterior resection plus total mesorectal excision under combined spinal-epidural anesthesia. A 3D mobile theatre (3DMT) was intraoperatively used for pain distraction. A postoperative "Cuddle delivery" service was instituted: video-messages from relatives and close friends were delivered daily to the patient through the 3DMT. Emotional correlations were investigated through a clinical interview by the psychologist of our Hospital. RESULTS: Intraoperative, as well as postoperative pain, resulted well-controlled: visual analogue scale (VAS) ≤3. Conversion to general anesthesia and postoperative intensive support/monitoring were unnecessary. The "Cuddle delivery" initiative positively fed our patient's mood and attitude, strengthening his bond to life. CONCLUSIONS: During pandemic, awake laparotomy under loco-regional anesthesia may be a crucial option in delivering acute care surgery to selected patients when intensive care beds are unavailable. Our procedure introduces potential ways to optimize this approach.


Subject(s)
Adenocarcinoma/surgery , Computers, Handheld , Family , Pain Management/methods , Pain, Postoperative/therapy , Pain, Procedural/therapy , Rectal Neoplasms/surgery , Video Recording , Aged , Anesthesia, Epidural/methods , Anesthesia, Spinal/methods , COVID-19/prevention & control , Humans , Laparotomy/methods , Male , Motion Pictures , Pain Measurement , Postoperative Care , Proctectomy/methods , SARS-CoV-2 , Wakefulness
10.
Nurs Leadersh (Tor Ont) ; 34(1): 30-37, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1175768

ABSTRACT

In the field of digital health research, nurse leaders have an opportunity to be integral to the design, implementation and evaluation of virtual care interventions. This case study details the experiences of two emerging nurse leaders during the COVID-19 pandemic in providing research and clinical leadership for a national virtual health trial. These nurse leaders trained and led a national team of 70 nurses across eight participating centres delivering the virtual care and remote monitoring intervention, using the normalization process theory. This case study presents a theoretically informed approach to training and leadership and discusses the experiences and lessons learned.


Subject(s)
Aftercare/trends , Leadership , Monitoring, Ambulatory/methods , Nurse-Patient Relations , Patient Discharge/standards , Remote Consultation/instrumentation , COVID-19/epidemiology , Canada/epidemiology , Computers, Handheld/supply & distribution , Humans , Pandemics , Randomized Controlled Trials as Topic , SARS-CoV-2 , Surgical Procedures, Operative
11.
Sci Rep ; 11(1): 5943, 2021 03 15.
Article in English | MEDLINE | ID: covidwho-1135693

ABSTRACT

Mobile phones have been used to monitor mobility changes during the COVID-19 pandemic but surprisingly few studies addressed in detail the implementation of practical applications involving whole populations. We report a method of generating a "mobility-index" and a "stay-at-home/resting-index" based on aggregated anonymous Call Detail Records of almost all subscribers in Hungary, which tracks all phones, examining their strengths and weaknesses, comparing it with Community Mobility Reports from Google, limited to smartphone data. The impact of policy changes, such as school closures, could be identified with sufficient granularity to capture a rush to shops prior to imposition of restrictions. Anecdotal reports of large scale movement of Hungarians to holiday homes were confirmed. At the national level, our results correlated well with Google mobility data, but there were some differences at weekends and national holidays, which can be explained by methodological differences. Mobile phones offer a means to analyse population movement but there are several technical and privacy issues. Overcoming these, our method is a practical and inexpensive way forward, achieving high levels of accuracy and resolution, especially where uptake of smartphones is modest, although it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring.


Subject(s)
Big Data , COVID-19/epidemiology , Computers, Handheld , SARS-CoV-2 , Social Mobility/statistics & numerical data , COVID-19/prevention & control , COVID-19/virology , Contact Tracing , Geography, Medical , Humans , Hungary/epidemiology , Public Health Surveillance
12.
J Med Internet Res ; 23(3): e23984, 2021 03 15.
Article in English | MEDLINE | ID: covidwho-1133814

ABSTRACT

The collection of data from a personal digital device to characterize current health conditions and behaviors that determine how an individual's health will evolve has been called digital phenotyping. In this paper, we describe the development of and early experiences with a comprehensive digital phenotyping platform: Health Outcomes through Positive Engagement and Self-Empowerment (HOPES). HOPES is based on the open-source Beiwe platform but adds a wider range of data collection, including the integration of wearable devices and further sensor collection from smartphones. Requirements were partly derived from a concurrent clinical trial for schizophrenia that required the development of significant capabilities in HOPES for security, privacy, ease of use, and scalability, based on a careful combination of public cloud and on-premises operation. We describe new data pipelines to clean, process, present, and analyze data. This includes a set of dashboards customized to the needs of research study operations and clinical care. A test use case for HOPES was described by analyzing the digital behavior of 22 participants during the SARS-CoV-2 pandemic.


Subject(s)
Data Collection/methods , Machine Learning , Wearable Electronic Devices , Computers, Handheld , Humans , Mobile Applications , Phenotype , Research Design , Schizophrenia/diagnosis , Schizophrenia/therapy , Smartphone
13.
CMAJ Open ; 9(1): E142-E148, 2021.
Article in English | MEDLINE | ID: covidwho-1115548

ABSTRACT

BACKGROUND: After nonelective (i.e., semiurgent, urgent and emergent) surgeries, patients discharged from hospitals are at risk of readmissions, emergency department visits or death. During the coronavirus disease 2019 (COVID-19) pandemic, we are undertaking the Post Discharge after Surgery Virtual Care with Remote Automated Monitoring Technology (PVC-RAM) trial to determine if virtual care with remote automated monitoring (RAM) compared with standard care will increase the number of days adult patients remain alive at home after being discharged following nonelective surgery. METHODS: We are conducting a randomized controlled trial in which 900 adults who are being discharged after nonelective surgery from 8 Canadian hospitals are randomly assigned to receive virtual care with RAM or standard care. Outcome adjudicators are masked to group allocations. Patients in the experimental group learn how to use the study's tablet computer and RAM technology, which will measure their vital signs. For 30 days, patients take daily biophysical measurements and complete a recovery survey. Patients interact with nurses via the cellular modem-enabled tablet, who escalate care to preassigned and available physicians if RAM measurements exceed predetermined thresholds, patients report symptoms, a medication error is identified or the nurses have concerns they cannot resolve. The primary outcome is number of days alive at home during the 30 days after randomization. INTERPRETATION: This trial will inform management of patients after discharge following surgery in the COVID-19 pandemic and offer insights for management of patients who undergo nonelective surgery in a nonpandemic setting. Knowledge dissemination will be supported through an online multimedia resource centre, policy briefs, presentations, peer-reviewed journal publications and media engagement. TRIAL REGISTRATION: ClinicalTrials.gov, no. NCT04344665.


Subject(s)
Aftercare/trends , Monitoring, Ambulatory/methods , Patient Discharge/standards , Remote Consultation/instrumentation , Adult , COVID-19/diagnosis , COVID-19/epidemiology , Canada/epidemiology , Computers, Handheld/supply & distribution , Humans , Middle Aged , Postoperative Period , SARS-CoV-2/genetics , User-Computer Interface
14.
J Am Med Inform Assoc ; 27(7): 1102-1109, 2020 07 01.
Article in English | MEDLINE | ID: covidwho-1066356

ABSTRACT

OBJECTIVE: To reduce pathogen exposure, conserve personal protective equipment, and facilitate health care personnel work participation in the setting of the COVID-19 pandemic, three affiliated institutions rapidly and independently deployed inpatient telemedicine programs during March 2020. We describe key features and early learnings of these programs in the hospital setting. METHODS: Relevant clinical and operational leadership from an academic medical center, pediatric teaching hospital, and safety net county health system met to share learnings shortly after deploying inpatient telemedicine. A summative analysis of their learnings was re-circulated for approval. RESULTS: All three institutions faced pressure to urgently standup new telemedicine systems while still maintaining secure information exchange. Differences across patient demographics and technological capabilities led to variation in solution design, though key technical considerations were similar. Rapid deployment in each system relied on readily available consumer-grade technology, given the existing familiarity to patients and clinicians and minimal infrastructure investment. Preliminary data from the academic medical center over one month suggested positive adoption with 631 inpatient video calls lasting an average (standard deviation) of 16.5 minutes (19.6) based on inclusion criteria. DISCUSSION: The threat of an imminent surge of COVID-19 patients drove three institutions to rapidly develop inpatient telemedicine solutions. Concurrently, federal and state regulators temporarily relaxed restrictions that would have previously limited these efforts. Strategic direction from executive leadership, leveraging off-the-shelf hardware, vendor engagement, and clinical workflow integration facilitated rapid deployment. CONCLUSION: The rapid deployment of inpatient telemedicine is feasible across diverse settings as a response to the COVID-19 pandemic.


Subject(s)
Betacoronavirus , Coronavirus Infections/therapy , Inpatients , Pneumonia, Viral/therapy , Telemedicine , Academic Medical Centers , COVID-19 , California , Computers, Handheld , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Hospitals, County , Hospitals, Pediatric , Humans , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , SARS-CoV-2 , Safety-net Providers , Teaching Rounds
17.
J Grad Med Educ ; 12(6): 789, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-1005988
18.
J R Soc Interface ; 17(173): 20200344, 2020 12.
Article in English | MEDLINE | ID: covidwho-978651

ABSTRACT

One approach to delaying the spread of the novel coronavirus (COVID-19) is to reduce human travel by imposing travel restriction policies. Understanding the actual human mobility response to such policies remains a challenge owing to the lack of an observed and large-scale dataset describing human mobility during the pandemic. This study uses an integrated dataset, consisting of anonymized and privacy-protected location data from over 150 million monthly active samples in the USA, COVID-19 case data and census population information, to uncover mobility changes during COVID-19 and under the stay-at-home state orders in the USA. The study successfully quantifies human mobility responses with three important metrics: daily average number of trips per person; daily average person-miles travelled; and daily percentage of residents staying at home. The data analytics reveal a spontaneous mobility reduction that occurred regardless of government actions and a 'floor' phenomenon, where human mobility reached a lower bound and stopped decreasing soon after each state announced the stay-at-home order. A set of longitudinal models is then developed and confirms that the states' stay-at-home policies have only led to about a 5% reduction in average daily human mobility. Lessons learned from the data analytics and longitudinal models offer valuable insights for government actions in preparation for another COVID-19 surge or another virus outbreak in the future.


Subject(s)
COVID-19/prevention & control , Computers, Handheld , Pandemics , SARS-CoV-2 , Travel , COVID-19/epidemiology , Data Interpretation, Statistical , Geographic Information Systems , Humans , Longitudinal Studies , Models, Statistical , Pandemics/prevention & control , Physical Distancing , Travel/legislation & jurisprudence , Travel/statistics & numerical data , Travel/trends , United States/epidemiology
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