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Pritwani S, Pandey S, Shrivastava P, Kumar A, Malhotra R, Maddison R, Devasenapathy N. Challenges in rehabilitation and continuum of care provision after knee replacement: a mixed-methods study from a low- and middle-income country. Disabil Rehabil 2024; 46:2890-2900. [PMID: 37461195 DOI: 10.1080/09638288.2023.2236012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 07/07/2023] [Indexed: 06/20/2024]
Abstract
PURPOSE Continuum-of-care is crucial following knee replacement. This is an understudied area in the context of low- and middle-income countries. We report findings of a mixed-methods study conducted to understand patient's postoperative experiences in following unsupervised home-based physiotherapy protocols and healthcare provider's experiences in providing rehabilitation care. METHODS Consecutive adults (n = 79) scheduled or had undergone knee replacement, attending an urban tertiary care hospital in India completed a 22-item questionnaire to gauge attitude towards physical rehabilitation. We conducted in-depth interviews with nine patients, ten physiotherapists, and three surgeons using a phenomenology approach. Data were interpreted using the capability, opportunity, and motivation-behaviour (COM-B) framework. RESULTS Patients were motivated to do exercises and valued family support during the recovery period. However, they desired physiotherapy support, especially during the early recovery period due to post-operative pain. Healthcare providers reported poor adherence with the exercise regimen and desired a mechanism to monitor patient progress after discharge. Patients and health care providers identified accessibility to rehabilitation centre as a major barrier in availing affordable and reliable physiotherapy services. CONCLUSION There is a need for a continuum of care to improve patient experience during recovery and for health care providers to monitor progress and provide personalised progressive exercise therapy.
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Affiliation(s)
| | - Shruti Pandey
- The George Institute for Global Health India, Delhi, India
| | | | - Ajit Kumar
- Department of Orthopaedics, All India Institute of Medical Sciences, Delhi, India
| | - Rajesh Malhotra
- Department of Orthopaedics, All India Institute of Medical Sciences, Delhi, India
| | - Ralph Maddison
- Department of School of Exercise & Nutrition, Institute for Physical Activity and Nutrition, Deakin University, Geelong, Australia
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Karas M, Olsen J, Straczkiewicz M, Johnson SA, Burke KM, Iwasaki S, Lahav A, Scheier ZA, Clark AP, Iyer AS, Huang E, Berry JD, Onnela J. Tracking amyotrophic lateral sclerosis disease progression using passively collected smartphone sensor data. Ann Clin Transl Neurol 2024; 11:1380-1392. [PMID: 38816946 PMCID: PMC11187949 DOI: 10.1002/acn3.52050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/03/2024] [Accepted: 03/05/2024] [Indexed: 06/01/2024] Open
Abstract
BACKGROUND Passively collected smartphone sensor data provide an opportunity to study physical activity and mobility unobtrusively over long periods of time and may enable disease monitoring in people with amyotrophic lateral sclerosis (PALS). METHODS We enrolled 63 PALS who used Beiwe mobile application that collected their smartphone accelerometer and GPS data and administered the self-entry ALS Functional Rating Scale-Revised (ALSFRS-RSE) survey. We identified individual steps from accelerometer data and used the Activity Index to summarize activity at the minute level. Walking, Activity Index, and GPS outcomes were then aggregated into day-level measures. We used linear mixed effect models (LMMs) to estimate baseline and monthly change for ALSFRS-RSE scores (total score, subscores Q1-3, Q4-6, Q7-9, Q10-12) and smartphone sensor data measures, as well as the associations between them. FINDINGS The analytic sample (N = 45) was 64.4% male with a mean age of 60.1 years. The mean observation period was 292.3 days. The ALSFRS-RSE total score baseline mean was 35.8 and had a monthly rate of decline of -0.48 (p-value <0.001). We observed statistically significant change over time and association with ALSFRS-RSE total score for four smartphone sensor data-derived measures: walking cadence from top 1 min and log-transformed step count, step count from top 1 min, and Activity Index from top 1 min. INTERPRETATION Smartphone sensors can unobtrusively track physical changes in PALS, potentially aiding disease monitoring and future research.
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Affiliation(s)
- Marta Karas
- Department of Biostatistics, Harvard T.H. Chan School of Public HealthHarvard University677 Huntington Ave.BostonMassachusetts02115USA
| | - Julia Olsen
- Department of Biostatistics, Harvard T.H. Chan School of Public HealthHarvard University677 Huntington Ave.BostonMassachusetts02115USA
| | - Marcin Straczkiewicz
- Department of Biostatistics, Harvard T.H. Chan School of Public HealthHarvard University677 Huntington Ave.BostonMassachusetts02115USA
| | - Stephen A. Johnson
- Department of NeurologyMayo Clinic13400 E. Shea Blvd.ScottsdaleArizona85259USA
| | - Katherine M. Burke
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Satoshi Iwasaki
- Mitsubishi Tanabe Pharma Holdings America, Inc.525 Washington Blvd.Jersey CityNew Jersey07310USA
| | - Amir Lahav
- Mitsubishi Tanabe Pharma Holdings America, Inc.525 Washington Blvd.Jersey CityNew Jersey07310USA
| | - Zoe A. Scheier
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Alison P. Clark
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Amrita S. Iyer
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Emily Huang
- Department of Statistical SciencesWake Forest UniversityWinston‐SalemNorth Carolina27106USA
| | - James D. Berry
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Jukka‐Pekka Onnela
- Department of Biostatistics, Harvard T.H. Chan School of Public HealthHarvard University677 Huntington Ave.BostonMassachusetts02115USA
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Huang M, Ye Y. "A Matter of Life and Death": Mitigating the Gray Digital Divide in Using Health Information Technologies in the Post-Pandemic Era. HEALTH COMMUNICATION 2024:1-11. [PMID: 38808629 DOI: 10.1080/10410236.2024.2358279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2024]
Abstract
A pervasive issue in healthcare is that elderly populations have fallen far behind in using healthcare technologies, a phenomenon known as the gray digital divide. Even more concerningly, the COVID-19 pandemic has dramatically catalyzed health digitization with the potential for lasting demographic-wide impacts. Against this backdrop and drawing on both the digital divide literature and the unified theory of acceptance and use of technology (UTAUT2), we investigated elderly populations' usage of healthcare technologies through analyzing HINTS 6 (2022) survey data. Results show a widespread first- and second-level digital divide in using health information technologies (HITs) between people aged 65 and up and people aged 18-64, including Internet access, health-related Internet use, health-related social media use, health app use, use of wearable electronic health devices, telehealth visits, and accessing online medical records. Moreover, this study finds that education consistently positively predicts Internet use and use of various HITs by the elderly; income is the next reliable predictor but not as consistent as education. Health-related variables are less consistent in predicting the elderly's use of HITs. Theoretical and practical implications of these results are discussed to inform the mitigation of the gray digital divide in healthcare.
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Affiliation(s)
- Maxwell Huang
- Noble and Greenough School, Incoming Freshman at Harvard University
| | - Yinjiao Ye
- Department of Communication Studies, Harrington School of Communication and Media, University of Rhode Island
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Phipps J, Passage B, Sel K, Martinez J, Saadat M, Koker T, Damaso N, Davis S, Palmer J, Claypool K, Kiley C, Pettigrew RI, Jafari R. Early adverse physiological event detection using commercial wearables: challenges and opportunities. NPJ Digit Med 2024; 7:136. [PMID: 38783001 PMCID: PMC11116498 DOI: 10.1038/s41746-024-01129-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 04/26/2024] [Indexed: 05/25/2024] Open
Abstract
Data from commercial off-the-shelf (COTS) wearables leveraged with machine learning algorithms provide an unprecedented potential for the early detection of adverse physiological events. However, several challenges inhibit this potential, including (1) heterogeneity among and within participants that make scaling detection algorithms to a general population less precise, (2) confounders that lead to incorrect assumptions regarding a participant's healthy state, (3) noise in the data at the sensor level that limits the sensitivity of detection algorithms, and (4) imprecision in self-reported labels that misrepresent the true data values associated with a given physiological event. The goal of this study was two-fold: (1) to characterize the performance of such algorithms in the presence of these challenges and provide insights to researchers on limitations and opportunities, and (2) to subsequently devise algorithms to address each challenge and offer insights on future opportunities for advancement. Our proposed algorithms include techniques that build on determining suitable baselines for each participant to capture important physiological changes and label correction techniques as it pertains to participant-reported identifiers. Our work is validated on potentially one of the largest datasets available, obtained with 8000+ participants and 1.3+ million hours of wearable data captured from Oura smart rings. Leveraging this extensive dataset, we achieve pre-symptomatic detection of COVID-19 with a performance receiver operator characteristic (ROC) area under the curve (AUC) of 0.725 without correction techniques, 0.739 with baseline correction, 0.740 with baseline correction and label correction on the training set, and 0.777 with baseline correction and label correction on both the training and the test set. Using the same respective paradigms, we achieve ROC AUCs of 0.919, 0.938, 0.943 and 0.994 for the detection of self-reported fever, and 0.574, 0.611, 0.601, and 0.635 for detection of self-reported shortness of breath. These techniques offer improvements across almost all metrics and events, including PR AUC, sensitivity at 75% specificity, and precision at 75% recall. The ring allows continuous monitoring for detection of event onset, and we further demonstrate an improvement in the early detection of COVID-19 from an average of 3.5 days to an average of 4.1 days before a reported positive test result.
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Affiliation(s)
- Jesse Phipps
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | - Bryant Passage
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | - Kaan Sel
- Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jonathan Martinez
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | - Milad Saadat
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Teddy Koker
- Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Natalie Damaso
- Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Shakti Davis
- Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Jeffrey Palmer
- Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Kajal Claypool
- Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | | | | | - Roozbeh Jafari
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA.
- Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
- Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
- School of Engineering Medicine, Texas A&M University, Houston, TX, USA.
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Tandon A, Avari Silva JN, Bhatt AB, Drummond CK, Hill AC, Paluch AE, Waits S, Zablah JE, Harris KC. Advancing Wearable Biosensors for Congenital Heart Disease: Patient and Clinician Perspectives: A Science Advisory From the American Heart Association. Circulation 2024; 149:e1134-e1142. [PMID: 38545775 DOI: 10.1161/cir.0000000000001225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Wearable biosensors (wearables) enable continual, noninvasive physiologic and behavioral monitoring at home for those with pediatric or congenital heart disease. Wearables allow patients to access their personal data and monitor their health. Despite substantial technologic advances in recent years, issues with hardware design, data analysis, and integration into the clinical workflow prevent wearables from reaching their potential in high-risk congenital heart disease populations. This science advisory reviews the use of wearables in patients with congenital heart disease, how to improve these technologies for clinicians and patients, and ethical and regulatory considerations. Challenges related to the use of wearables are common to every clinical setting, but specific topics for consideration in congenital heart disease are highlighted.
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Zhou W, Cho Y, Pu J, Shang S. Trends in wearable device use among cancer survivors in the United States from 2019 to 2022. J Geriatr Oncol 2024; 15:101729. [PMID: 38360455 DOI: 10.1016/j.jgo.2024.101729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/29/2024] [Accepted: 02/09/2024] [Indexed: 02/17/2024]
Affiliation(s)
- Weijiao Zhou
- School of Nursing, Peking University, Beijing, China
| | - Youmin Cho
- Youmin Cho, Chungnam National University College of Nursing, Daejeon, South Korea
| | - Junlan Pu
- School of Nursing, Peking University, Beijing, China
| | - Shaomei Shang
- School of Nursing, Peking University, Beijing, China.
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Tanaka M, Ishii S, Matsuoka A, Tanabe S, Matsunaga S, Rahmani A, Dutt N, Rasouli M, Nyamathi A. Perspectives of Japanese elders and their healthcare providers on use of wearable technology to monitor their health at home: A qualitative exploration. Int J Nurs Stud 2024; 152:104691. [PMID: 38262231 DOI: 10.1016/j.ijnurstu.2024.104691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 11/20/2023] [Accepted: 01/04/2024] [Indexed: 01/25/2024]
Abstract
BACKGROUND With 24 million Japanese elderly aging at home, the challenges of managing chronic conditions are significant. As many Japanese elders manage multiple chronic conditions, investigating the usefulness of wearable health devices for this population is warranted. AIM The purpose of this qualitative study, using grounded theory, was to explore the perspectives of Japanese elders, their caretakers, and their healthcare providers on the use of technology and wearable devices to monitor health conditions and keep Japanese elders safe at home. METHODS In conducting this study, a community advisory board was first established to guide the research design; six focus groups and two one-on-one interviews were conducted, with a total of 21 participants. RESULTS Four major themes emerged from the analysis: 1) Current Status of Health Issues Experienced by Japanese Elders and Ways of Being Monitored; 2) Current Use of Monitoring Technology and Curiosity about Use of the Latest Digital Technology to Keep Elderly Healthy at Home; 3) Perceived Advantages of Wearing Sensor Technology; and 4) Perceived Disadvantages of Wearing Technology. Many of the elderly participants were interested in using monitoring devices at home, particularly if not complicated. Healthcare workers found monitoring technologies particularly useful during the isolation of the COVID-19 pandemic. Elderly participants felt cost and technical issues could be barriers to using monitoring devices. CONCLUSION While there are challenges to utilizing monitoring devices, the potential to aid the aging population of Japan justifies further investigation into the effectiveness of these devices. This study was not registered with a research trial registry.
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Affiliation(s)
- Mika Tanaka
- School of Nursing, Kitasato University, Sagamihara, Kanagawa, Japan
| | - Shinobu Ishii
- School of Nursing, Kitasato University, Sagamihara, Kanagawa, Japan
| | - Akiko Matsuoka
- School of Nursing, Kitasato University, Sagamihara, Kanagawa, Japan
| | - Sachiko Tanabe
- School of Nursing, Kitasato University, Sagamihara, Kanagawa, Japan
| | - Shota Matsunaga
- Graduate School of Medical Sciences, Kitasato University, Sagamihara, Kanagawa, Japan
| | - Amir Rahmani
- Sue & Bill Gross School of Nursing, University of California, Irvine, Irvine, CA, United States of America
| | - Nikil Dutt
- Bren School of Information and Computer Sciences, University of California, Irvine, Irvine, CA, United States of America
| | - Mahkameh Rasouli
- Sue & Bill Gross School of Nursing, University of California, Irvine, Irvine, CA, United States of America
| | - Adeline Nyamathi
- Sue & Bill Gross School of Nursing, University of California, Irvine, Irvine, CA, United States of America.
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8
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Hindelang M, Wecker H, Biedermann T, Zink A. Continuously monitoring the human machine? - A cross-sectional study to assess the acceptance of wearables in Germany. Health Informatics J 2024; 30:14604582241260607. [PMID: 38900846 DOI: 10.1177/14604582241260607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Background: Wearables have the potential to transform healthcare by enabling early detection and monitoring of chronic diseases. This study aimed to assess wearables' acceptance, usage, and reasons for non-use. Methods: Anonymous questionnaires were used to collect data in Germany on wearable ownership, usage behaviour, acceptance of health monitoring, and willingness to share data. Results: Out of 643 respondents, 550 participants provided wearable acceptance data. The average age was 36.6 years, with 51.3% female and 39.6% residing in rural areas. Overall, 33.8% reported wearing a wearable, primarily smartwatches or fitness wristbands. Men (63.3%) and women (57.8%) expressed willingness to wear a sensor for health monitoring, and 61.5% were open to sharing data with healthcare providers. Concerns included data security, privacy, and perceived lack of need. Conclusion: The study highlights the acceptance and potential of wearables, particularly for health monitoring and data sharing with healthcare providers. Addressing data security and privacy concerns could enhance the adoption of innovative wearables, such as implants, for early detection and monitoring of chronic diseases.
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Affiliation(s)
- Michael Hindelang
- TUM School of Medicine and Health, Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany; Pettenkofer School of Public Health, Munich, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology - IBE, LMU Munich, Munich, Germany
| | - Hannah Wecker
- TUM School of Medicine and Health, Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany
| | - Tilo Biedermann
- TUM School of Medicine and Health, Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany
| | - Alexander Zink
- TUM School of Medicine and Health, Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany; Division of Dermatology and Venereology, Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden
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Lee JS, Browning E, Hokayem J, Albrechta H, Goodman GR, Venkatasubramanian K, Dumas A, Carreiro SP, O'Cleirigh C, Chai PR. Smartphone and Wearable Device-Based Digital Phenotyping to Understand Substance use and its Syndemics. J Med Toxicol 2024; 20:205-214. [PMID: 38436819 PMCID: PMC10959908 DOI: 10.1007/s13181-024-01000-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/08/2024] [Accepted: 02/20/2024] [Indexed: 03/05/2024] Open
Abstract
Digital phenotyping is a process that allows researchers to leverage smartphone and wearable data to explore how technology use relates to behavioral health outcomes. In this Research Concepts article, we provide background on prior research that has employed digital phenotyping; the fundamentals of how digital phenotyping works, using examples from participant data; the application of digital phenotyping in the context of substance use and its syndemics; and the ethical, legal and social implications of digital phenotyping. We discuss applications for digital phenotyping in medical toxicology, as well as potential uses for digital phenotyping in future research. We also highlight the importance of obtaining ground truth annotation in order to identify and establish digital phenotypes of key behaviors of interest. Finally, there are many potential roles for medical toxicologists to leverage digital phenotyping both in research and in the future as a clinical tool to better understand the contextual features associated with drug poisoning and overdose. This article demonstrates how medical toxicologists and researchers can progress through phases of a research trajectory using digital phenotyping to better understand behavior and its association with smartphone usage.
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Affiliation(s)
- Jasper S Lee
- Department of Emergency Medicine, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, USA
- The Fenway Institute, Fenway Health, Boston, USA
| | - Emma Browning
- The Fenway Institute, Fenway Health, Boston, USA
- Department of Community Health, Tufts University, Boston, USA
| | | | | | - Georgia R Goodman
- Department of Emergency Medicine, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, USA
- The Fenway Institute, Fenway Health, Boston, USA
| | | | - Arlen Dumas
- Department of Computer Science and Statistics, University of Rhode Island, Kingston, USA
| | - Stephanie P Carreiro
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Boston, USA
| | - Conall O'Cleirigh
- Department of Psychiatry, Massachusetts General Hospital, Boston, USA
- The Fenway Institute, Fenway Health, Boston, USA
| | - Peter R Chai
- Department of Emergency Medicine, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA.
- The Fenway Institute, Fenway Health, Boston, USA.
- Department of Psychosocial Oncology and Palliative Care, Dana Farber Cancer Institute, Boston, USA.
- The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology, Boston, USA.
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Kasl P, Keeler Bruce L, Hartogensis W, Dasgupta S, Pandya LS, Dilchert S, Hecht FM, Gupta A, Altintas I, Mason AE, Smarr BL. Utilizing Wearable Device Data for Syndromic Surveillance: A Fever Detection Approach. SENSORS (BASEL, SWITZERLAND) 2024; 24:1818. [PMID: 38544080 PMCID: PMC10975930 DOI: 10.3390/s24061818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 02/29/2024] [Accepted: 03/06/2024] [Indexed: 04/01/2024]
Abstract
Commercially available wearable devices (wearables) show promise for continuous physiological monitoring. Previous works have demonstrated that wearables can be used to detect the onset of acute infectious diseases, particularly those characterized by fever. We aimed to evaluate whether these devices could be used for the more general task of syndromic surveillance. We obtained wearable device data (Oura Ring) from 63,153 participants. We constructed a dataset using participants' wearable device data and participants' responses to daily online questionnaires. We included days from the participants if they (1) completed the questionnaire, (2) reported not experiencing fever and reported a self-collected body temperature below 38 °C (negative class), or reported experiencing fever and reported a self-collected body temperature at or above 38 °C (positive class), and (3) wore the wearable device the nights before and after that day. We used wearable device data (i.e., skin temperature, heart rate, and sleep) from the nights before and after participants' fever day to train a tree-based classifier to detect self-reported fevers. We evaluated the performance of our model using a five-fold cross-validation scheme. Sixteen thousand, seven hundred, and ninety-four participants provided at least one valid ground truth day; there were a total of 724 fever days (positive class examples) from 463 participants and 342,430 non-fever days (negative class examples) from 16,687 participants. Our model exhibited an area under the receiver operating characteristic curve (AUROC) of 0.85 and an average precision (AP) of 0.25. At a sensitivity of 0.50, our calibrated model had a false positive rate of 0.8%. Our results suggest that it might be possible to leverage data from these devices at a public health level for live fever surveillance. Implementing these models could increase our ability to detect disease prevalence and spread in real-time during infectious disease outbreaks.
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Affiliation(s)
- Patrick Kasl
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, San Diego, CA 92093-0021, USA;
| | - Lauryn Keeler Bruce
- UC San Diego Health Department of Biomedical Informatics, University of California San Diego, San Diego, CA 92093-0021, USA;
| | - Wendy Hartogensis
- UCSF Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA 92093-0021, USA; (W.H.); (L.S.P.); (F.M.H.); (A.E.M.)
| | - Subhasis Dasgupta
- San Diego Supercomputer Center, University of California San Diego, San Diego, CA 92093-0021, USA; (S.D.); (A.G.); (I.A.)
| | - Leena S. Pandya
- UCSF Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA 92093-0021, USA; (W.H.); (L.S.P.); (F.M.H.); (A.E.M.)
| | - Stephan Dilchert
- Department of Management, Zicklin School of Business, Baruch College, The City University of New York, New York, NY 10010, USA;
| | - Frederick M. Hecht
- UCSF Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA 92093-0021, USA; (W.H.); (L.S.P.); (F.M.H.); (A.E.M.)
| | - Amarnath Gupta
- San Diego Supercomputer Center, University of California San Diego, San Diego, CA 92093-0021, USA; (S.D.); (A.G.); (I.A.)
- Halıcıoğlu Data Science Institute, University of California San Diego, San Diego, CA 92093-0021, USA
| | - Ilkay Altintas
- San Diego Supercomputer Center, University of California San Diego, San Diego, CA 92093-0021, USA; (S.D.); (A.G.); (I.A.)
- Halıcıoğlu Data Science Institute, University of California San Diego, San Diego, CA 92093-0021, USA
| | - Ashley E. Mason
- UCSF Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA 92093-0021, USA; (W.H.); (L.S.P.); (F.M.H.); (A.E.M.)
| | - Benjamin L. Smarr
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, San Diego, CA 92093-0021, USA;
- Halıcıoğlu Data Science Institute, University of California San Diego, San Diego, CA 92093-0021, USA
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11
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Materia FT, Smyth JM. Acceptability and concerns about innovative wearable health sensors in persons with and without chronic disease diagnosis. Internet Interv 2024; 35:100702. [PMID: 38221944 PMCID: PMC10787257 DOI: 10.1016/j.invent.2023.100702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 11/19/2023] [Accepted: 12/17/2023] [Indexed: 01/16/2024] Open
Abstract
Advances in biomedical engineering continue to produce innovative wearable health sensors capable of real-time ambulatory assessments (e.g., of physiology, the environment), holding great potential for advancing precision monitoring and interventions through the integration of such devices and data into eHealth systems. As with any novel device, however, user views on acceptability and concerns about the technology must be evaluated to facilitate widespread implementation and user adoption of such devices. One factor that may strongly influence user views is the potential relevance to, and need for, self-care for chronic disease management. We examined if acceptability and concerns regarding innovative wearable devices differed between individuals living with or without chronic disease. A U.S. adult sample (N = 448; 20-70 yrs.; 34 % Female; 60 % White, 35 % Hispanic) completed a web-based survey regarding their thoughts/opinions related to innovative wearable sensors. Two-thirds (67 %, N = 298) reported at least one chronic disease; one-third (33 %, N = 150) reported no chronic health conditions. Participants viewed learning modules about two innovative devices: a watch to detect environmental gases for respiratory health, and a chest-patch monitoring real-time ECG. For each device, participants rated acceptability across multiple dimensions, and then rated potential concerns (including general concerns and specific worries about negative health impacts). Respondents with and without chronic disease differed in education, race, and ethnicity. Controlling for these differences, individuals with chronic disease reported significantly higher acceptability for the watch and for the chest-patch. Healthy participants reported significantly higher general concerns about technology. However, when concern questions were asked specifically about the potential negative impacts of the two study devices on physical health and well-being, participants with chronic disease reported significantly higher concerns. Overall, results show that living with chronic disease influences acceptability and concerns associated with adoption of innovative sensors. These findings suggest it is essential to take potential users' health status into account when studying the design and implementation of innovative wearable sensors. Dissemination strategies may benefit from emphasizing the beneficial features of these devices, addressing hesitations, and customizing implementation approaches by user group.
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Affiliation(s)
- Frank T. Materia
- Departments of Otolaryngology and Population Health, University of Kansas Medical Center, Kansas City, KS, United States of America
| | - Joshua M. Smyth
- Department of Psychology, The Ohio State University, Columbus, OH, United States of America
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Dainty KN, Yng Ng Y, Pin Pek P, Koster RW, Eng Hock Ong M. Wolf creek XVII part 4: Amplifying lay-rescuer response. Resusc Plus 2024; 17:100547. [PMID: 38292468 PMCID: PMC10827540 DOI: 10.1016/j.resplu.2023.100547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024] Open
Abstract
Introduction Amplifying lay-rescuer response is a key priority to increase survival from out-of-hospital cardiac arrest (OHCA). We describe the current state of lay-rescuer response, how we envision the future, and the gaps, barriers, and research priorities that will amplify response to OHCA. Methods 'Amplifying Lay-Rescuer Response' was one of six focus topics for the Wolf Creek XVII Conference held on June 14-17, 2023, in Ann Arbor, Michigan, USA. Conference invitees included international thought leaders and scientists in the field of cardiac arrest resuscitation from academia and industry. Participants submitted via online survey knowledge gaps, barriers to translation and research priorities for each focus topic. Expert panels used the survey results and their own perspectives and insights to create and present a preliminary unranked list for each category that was debated, revised and ranked by all attendees to identify the top 5 for each category. Results The top five knowledge gaps as ranked by the panel, reflected a recognition of the need to better understand the psycho-social aspects of lay response. The top five barriers to translation reflected issues at the individual, community, societal, structural, and governmental levels. The top five research priorities were focused on understanding the social/psychological and emotional barriers to action, finding the most effective/cost-effective strategies to educate lay persons and implement community life-saving interventions, evaluation of new technological solutions and how to enhance the role of dispatch working with lay-rescuers. Conclusion Future research in lay rescuer response should incorporate technology innovations, understand the "humanity" of the situation, leverage implementation science and systems thinking to save lives. This will require the field of resuscitation to engage with scholars outside our traditional ranks and to be open to new ways of thinking about old problems.
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Affiliation(s)
- Katie N. Dainty
- Patient-Centered Outcomes, North York General Hospital Institute of Health Policy, Management and Evaluation, University of Toronto, Canada
| | - Yih Yng Ng
- Digital and Smart Health Office, Ng Teng Fong Centre for Healthcare Innovation Department of Preventive and Population Medicine, Tan Tock Seng Hospital Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Pin Pin Pek
- Prehospital and Emergency Research Centre, Health Services and Systems Research, Duke-NUS Medical School Department of Emergency Medicine, Singapore General Hospital Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Rudolph W. Koster
- Department of Cardiology, Amsterdam University Medical Centers, The Netherlands
| | - Marcus Eng Hock Ong
- Department of Emergency Medicine, Singapore General Hospital Health Services and Systems Research, Duke-NUS Medical School, Singapore
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Gardner CL, Raps SJ, Kasuske L. Cross-sectional Analysis of Health Behavior Tracking, Perceived Health, Fitness, and Health Literacy Among Active-Duty Air Force Personnel. Comput Inform Nurs 2024; 42:176-183. [PMID: 37580053 DOI: 10.1097/cin.0000000000001060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
There is a paucity of evidence connecting health literacy, perceived wellness, self-reported fitness activity, or military readiness to wearable devices. Moreover, we do not currently know the prevalence and impact of health tracker device use in the active-duty Air Force population. This prospective cross-sectional survey assessed self-reported fitness activity, health-related quality of life, health literacy, and health behavior tracking practices and preferences among active-duty Air Force service members. Four hundred twenty-eight respondents completed an online survey, with 247 selecting tracking a health behavior and 181 selecting that they did not track a health behavior. Demographic characteristics of the sample showed no significant differences in age, sex distribution, or mode of service. We found that there were no significant differences in self-reported aerobic and strength training frequency, health literacy, or health-related quality of life. More than half of nontracking respondents either had not considered or had no interest in tracking health behaviors. Nearly three-quarters of tracking respondents tracked more than one health behavior. Further research could explore the extent to which these technologies improve fitness, health outcomes, and overall readiness in the military, involving longitudinal studies tracking fitness improvements and health outcomes among service members using wearable devices.
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Affiliation(s)
- Cubby L Gardner
- Author Affiliations: Daniel K. Inouye Graduate School of Nursing, Uniformed Services University of the Health Sciences, Bethesda, MD (Drs Gardner and Kasuske); and Nurse Scientist, Joint Base San Antonio, TX (Dr Raps)
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Deguchi N, Osuka Y, Kojima N, Motokawa K, Iwasaki M, Inagaki H, Miyamae F, Okamura T, Hirano H, Awata S, Sasai H. Sex-specific factors associated with acceptance of smartwatches among urban older adults: the Itabashi longitudinal study on aging. Front Public Health 2024; 12:1261275. [PMID: 38476490 PMCID: PMC10929614 DOI: 10.3389/fpubh.2024.1261275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 02/06/2024] [Indexed: 03/14/2024] Open
Abstract
Smartwatches (SW) are wearable devices that support daily life and monitor an individual's health and activity status. This information is utilized to promote behavior modification, which could help prevent chronic diseases and manage the health of older adults. Despite being interested in SWs, older adults tend to decrease their SW usage as they age. Therefore, understanding the acceptance of SWs among older individuals can facilitate individual health management through digital health technology. This study investigated the factors associated with the acceptance of SWs among older adults in Japan and the variations in the factors by sex. This study utilized data from the 2022 Itabashi Longitudinal Study on Aging, an ongoing cohort study conducted by the Tokyo Metropolitan Institute for Geriatrics and Gerontology. We included 899 eligible individuals aged ≥65 years. Participants were classified into three groups: possessing SW (possessor group), not possessing SW but interested in possession in the future (interest group), and not interested in possession in the future (non-interest group) using a self-administered questionnaire. The level of SW acceptance was operationally defined as follows: low (non-interest group), medium (interest group), and high (possessor group). Further, we evaluated the association of acceptance and purchase intentions of SWs with sociodemographic variables, technology literacy, and health variables. Among the participants, 4.2% possessed SWs, with no significant sex difference (men, 4.2%; women, 4.3%). Among men, age < 75 years, obesity, diabetes, and dyslipidemia were significantly associated with SW acceptance level. Contrastingly, among women, age < 75 years, living alone, higher household income, and a high score for new device use in the technology literacy category were significantly associated with SW acceptance level. Health-related factors were associated with SW acceptance in men, while technology literacy and sociodemographic factors were associated with SW acceptance in women. Our findings may inform the development of sex-specific interventions and policies for increasing SW utilization among older adults in Japan.
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Affiliation(s)
- Naoki Deguchi
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Yosuke Osuka
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
- Department of Frailty Research, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Narumi Kojima
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Keiko Motokawa
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Masanori Iwasaki
- Division of Preventive Dentistry, Department of Oral Health Science, Graduate School of Dental Medicine, Hokkaido University, Sapporo, Japan
| | - Hiroki Inagaki
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Fumiko Miyamae
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Tsuyoshi Okamura
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Hirohiko Hirano
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Shuichi Awata
- Integrated Research Initiative for Living Well with Dementia, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Hiroyuki Sasai
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
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Shandhi MMH, Singh K, Janson N, Ashar P, Singh G, Lu B, Hillygus DS, Maddocks JM, Dunn JP. Assessment of ownership of smart devices and the acceptability of digital health data sharing. NPJ Digit Med 2024; 7:44. [PMID: 38388660 PMCID: PMC10883993 DOI: 10.1038/s41746-024-01030-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 02/05/2024] [Indexed: 02/24/2024] Open
Abstract
Smart portable devices- smartphones and smartwatches- are rapidly being adopted by the general population, which has brought forward an opportunity to use the large volumes of physiological, behavioral, and activity data continuously being collected by these devices in naturalistic settings to perform research, monitor health, and track disease. While these data can serve to revolutionize health monitoring in research and clinical care, minimal research has been conducted to understand what motivates people to use these devices and their interest and comfort in sharing the data. In this study, we aimed to characterize the ownership and usage of smart devices among patients from an expansive academic health system in the southeastern US and understand their willingness to share data collected by the smart devices. We conducted an electronic survey of participants from an online patient advisory group around smart device ownership, usage, and data sharing. Out of the 3021 members of the online patient advisory group, 1368 (45%) responded to the survey, with 871 female (64%), 826 and 390 White (60%) and Black (29%) participants, respectively, and a slight majority (52%) age 58 and older. Most of the respondents (98%) owned a smartphone and the majority (59%) owned a wearable. In this population, people who identify as female, Hispanic, and Generation Z (age 18-25), and those completing higher education and having full-time employment, were most likely to own a wearable device compared to their demographic counterparts. 50% of smart device owners were willing to share and 32% would consider sharing their smart device data for research purposes. The type of activity data they are willing to share varies by gender, age, education, and employment. Findings from this study can be used to design both equitable and cost-effective digital health studies, leveraging personally-owned smartphones and wearables in representative populations, ultimately enabling the development of equitable digital health technologies.
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Affiliation(s)
| | - Karnika Singh
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Perisa Ashar
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Geetika Singh
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Baiying Lu
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - D Sunshine Hillygus
- Department of Political Science, Trinity College of Arts & Sciences, Duke University, Durham, NC, USA
- Sanford School of Public Policy, Duke University, Durham, NC, USA
| | | | - Jessilyn P Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Duke University, Department of Biostatistics & Bioinformatics, Durham, NC, USA.
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Lin AC, Lee J, Gabriel MK, Arbet RN, Ghawaa Y, Ferguson AM. The Pharmacy 5.0 framework: A new paradigm to accelerate innovation for large-scale personalized pharmacy care. Am J Health Syst Pharm 2024; 81:e141-e147. [PMID: 37672000 DOI: 10.1093/ajhp/zxad212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Indexed: 09/07/2023] Open
Affiliation(s)
- Alex C Lin
- Division of Pharmacy Practice and Administrative Sciences, The James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH, USA
| | - Jay Lee
- A. James Clark School of Engineering, Maryland Robotics Center, University of Maryland, Baltimore, Maryland
- College of Engineering and Applied Science, University of Cincinnati, Cincinnati, OH, USA
| | - Mina K Gabriel
- Division of Pharmacy Practice and Administrative Sciences, The James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH, USA
| | | | - Yazeed Ghawaa
- Division of Pharmacy Practice and Administrative Sciences, The James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Andrew M Ferguson
- Division of Pharmacy Practice and Administrative Sciences, The James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH
- The Center for Addiction Research, Division of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Straiton N, Moons P, Verstrael A, Liu M, Winter MM. Beyond Validation: Getting Wearable Activity Trackers into Cardiovascular Care - A Discussion Paper. Eur J Cardiovasc Nurs 2024:zvae019. [PMID: 38345842 DOI: 10.1093/eurjcn/zvae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 02/06/2024] [Accepted: 02/08/2024] [Indexed: 04/24/2024]
Abstract
This paper addresses the challenge of integrating wearable activity trackers into cardiovascular disease care. Despite evidence supporting the use of trackers for monitoring and promoting physical activity, implementation challenges persist in clinical settings. The paper emphasises the lack of systematic, evidence-based implementation approaches for integrating trackers. It underscores the urgent need for stakeholder collaboration between clinicians, patients, implementation scientists, researchers, health and technology partners, and the use of proven implementation science methodologies. This is crucial for bridging the gap and ensuring effective translation of wearable activity trackers into cardiovascular disease care, meeting the increasing demand from patients and clinicians.
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Affiliation(s)
- Nicola Straiton
- Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne, Australian Catholic University, New South Wales, Australia
| | - Philip Moons
- KU Leuven Department of Public Health and Primary Care, KU Leuven - University of Leuven, Kapucijnenvoer 7 PB7001, 3000 Leuven, Belgium
- Institute of Health and Care Sciences, University of Gothenburg, Arvid Wallgrens backe 1, 413 46 Gothenburg, Sweden
- Department of Paediatrics and Child Health, University of Cape Town, Klipfontein Rd, Rondebosch, 7700 Cape Town, South Africa
| | - Axel Verstrael
- ESC Patient's Platform, European Society of Cardiology, Sophia Antipolis Cedex, France
| | - Mark Liu
- Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne, Australian Catholic University, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney
| | - Michiel M Winter
- University of Amsterdam, Heart Center; Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Meibergdreef 9, Amsterdam, The Netherlands
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Ong JL, Golkashani HA, Ghorbani S, Wong KF, Chee NIYN, Willoughby AR, Chee MWL. Selecting a sleep tracker from EEG-based, iteratively improved, low-cost multisensor, and actigraphy-only devices. Sleep Health 2024; 10:9-23. [PMID: 38087674 DOI: 10.1016/j.sleh.2023.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 11/01/2023] [Accepted: 11/11/2023] [Indexed: 03/01/2024]
Abstract
AIMS Evaluate the performance of 6 wearable sleep trackers across 4 classes (EEG-based headband, research-grade actigraphy, iteratively improved consumer tracker, low-cost consumer tracker). FOCUS TECHNOLOGY Dreem 3 headband, Actigraph GT9X, Oura Ring Gen3, Fitbit Sense, Xiaomi Mi Band 7, Axtro Fit3. REFERENCE TECHNOLOGY In-lab polysomnography with 3-reader, consensus sleep scoring. SAMPLE Sixty participants (26 males) across 3 age groups (18-30, 31-50, and 51-70years). DESIGN Overnight in a sleep laboratory from habitual sleep time to wake time. CORE ANALYTICS Discrepancy and epoch-by-epoch analyses for sleep/wake (2-stage) and sleep-stage (4-stage; wake/light/deep/rapid eye movement) classification (devices vs. polysomnography). CORE OUTCOMES EEG-based Dreem performed the best (2-stage kappa=0.76, 4-stage kappa=0.76-0.86) with the lowest total sleep time, sleep efficiency, sleep onset latency, and wake after sleep onset discrepancies vs. polysomnography. This was followed by the iteratively improved consumer trackers: Oura (2-stage kappa=0.64, 4-stage kappa=0.55-0.70) and Fitbit (2-stage kappa=0.58, 4-stage kappa=0.45-0.60) which had comparable total sleep time and sleep efficiency discrepancies that outperformed accelerometry-only Actigraph (2-stage kappa=0.47). The low-cost consumer trackers had poorest overall performance (2-stage kappa<0.31, 4-stage kappa<0.33). IMPORTANT ADDITIONAL OUTCOMES Proportional biases were driven by nights with poorer sleep (longer sleep onset latencies and/or wake after sleep onset). CORE CONCLUSION EEG-based Dreem is recommended when evaluating poor quality sleep or when highest accuracy sleep-staging is required. Iteratively improved non-EEG sleep trackers (Oura, Fitbit) balance classification accuracy with well-tolerated, and economic deployment at-scale, and are recommended for studies involving mostly healthy sleepers. The low-cost trackers, can log time in bed but are not recommended for research use.
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Affiliation(s)
- Ju Lynn Ong
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Hosein Aghayan Golkashani
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Shohreh Ghorbani
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Kian F Wong
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Nicholas I Y N Chee
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Adrian R Willoughby
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael W L Chee
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
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Li M, Huang J, Budhathoki C, Li Q, Samuel L, Szanton SL, Schrack JA, Li J. Social Factors and Older Adults' Use of Wearable Activity Trackers: Before and During the First Wave of the COVID-19 Pandemic. J Appl Gerontol 2024; 43:182-193. [PMID: 37863099 DOI: 10.1177/07334648231205417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2023] Open
Abstract
Wearable activity trackers (WAT) have shown high potential to improve health in the aging population. Evidence links various social factors with WAT use in older adults, but mainly within small samples and the prevalence of their WAT use during the COVID-19 is unknown. We reported WAT use prevalence before and during the first wave of COVID-19 and examined social factors associated with WAT use frequency using a nationally representative sample of 3302 U.S. older adults. We used Multinomial Logistic Regression to identify social factors associated with WAT use frequency. Only 10.3% of pre-COVID-19 and 10.9% of first-wave subsamples were frequent WAT users. Older adults aged 75 and above and those with low incomes were less likely to frequently use WATs. Our findings suggest socioeconomic and age disparities in WAT use among older Americans. Future studies should focus on enhancing low-income older adults' WAT adoption to enable equal access to WAT-related health benefits.
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Affiliation(s)
- Mengchi Li
- Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Jing Huang
- Johns Hopkins University, Baltimore, MD, USA
| | | | - Qiwei Li
- California State University, Baltimore, MD, USA
| | | | | | | | - Junxin Li
- Johns Hopkins University, Baltimore, MD, USA
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Robinson SA, Shimada SL, Zocchi MS, Etingen B, Smith B, McMahon N, Cutrona SL, Harmon JS, Wilck NR, Hogan TP. Factors Associated with Veteran Self-Reported Use of Digital Health Devices. J Gen Intern Med 2024; 39:79-86. [PMID: 38252248 PMCID: PMC10937849 DOI: 10.1007/s11606-023-08479-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/12/2023] [Indexed: 01/23/2024]
Abstract
BACKGROUND Digital health devices (DHDs), technologies designed to gather, monitor, and sometimes share data about health-related behaviors or symptoms, can support the prevention or management of chronic conditions. DHDs range in complexity and utility, from tracking lifestyle behaviors (e.g., pedometer) to more sophisticated biometric data collection for disease self-management (e.g., glucometers). Despite these positive health benefits, supporting adoption and sustained use of DHDs remains a challenge. OBJECTIVE This analysis examined the prevalence of, and factors associated with, DHD use within the Veterans Health Administration (VHA). DESIGN National survey. PARTICIPANTS Veterans who receive VHA care and are active secure messaging users. MAIN MEASURES Demographics, access to technology, perceptions of using health technologies, and use of lifestyle monitoring and self-management DHDs. RESULTS Among respondents, 87% were current or past users of at least one DHD, and 58% were provided a DHD by VHA. Respondents 65 + years were less likely to use a lifestyle monitoring device (AOR 0.57, 95% CI [0.39, 0.81], P = .002), but more likely to use a self-management device (AOR 1.69, 95% [1.10, 2.59], P = .016). Smartphone owners were more likely to use a lifestyle monitoring device (AOR 2.60, 95% CI [1.42, 4.75], P = .002) and a self-management device (AOR 1.83, 95% CI [1.04, 3.23], P = .037). CONCLUSIONS The current analysis describes the types of DHDs that are being adopted by Veterans and factors associated with their adoption. Results suggest that various factors influence adoption, including age, access to technology, and health status, and that these relationships may differ based on the functionalities of the device. VHA provision of devices was frequent among device users. Providing Veterans with DHDs and the training needed to use them may be important factors in facilitating device adoption. Taken together, this knowledge can inform future implementation efforts, and next steps to support patient-team decision making about DHD use.
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Affiliation(s)
- Stephanie A Robinson
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA.
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA.
- The Pulmonary Center, Boston University School of Medicine, Boston, MA, USA.
| | - Stephanie L Shimada
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Department of Health Law, Policy, & Management, Boston University School of Public Health, Boston, MA, USA
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Mark S Zocchi
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Heller School for Social Policy and Management, Brandeis University, Waltham, MA, USA
| | - Bella Etingen
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center of Innovation for Complex Chronic Healthcare, Hines Veterans Affairs Hospital, Hines, IL, USA
| | - Bridget Smith
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center of Innovation for Complex Chronic Healthcare, Hines Veterans Affairs Hospital, Hines, IL, USA
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Nicholas McMahon
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
| | - Sarah L Cutrona
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Julie S Harmon
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Office of Connected Care, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC, USA
| | - Nancy R Wilck
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Office of Connected Care, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC, USA
| | - Timothy P Hogan
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Peter O'Donnell Jr School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
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Babu M, Lautman Z, Lin X, Sobota MHB, Snyder MP. Wearable Devices: Implications for Precision Medicine and the Future of Health Care. Annu Rev Med 2024; 75:401-415. [PMID: 37983384 DOI: 10.1146/annurev-med-052422-020437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Wearable devices are integrated analytical units equipped with sensitive physical, chemical, and biological sensors capable of noninvasive and continuous monitoring of vital physiological parameters. Recent advances in disciplines including electronics, computation, and material science have resulted in affordable and highly sensitive wearable devices that are routinely used for tracking and managing health and well-being. Combined with longitudinal monitoring of physiological parameters, wearables are poised to transform the early detection, diagnosis, and treatment/management of a range of clinical conditions. Smartwatches are the most commonly used wearable devices and have already demonstrated valuable biomedical potential in detecting clinical conditions such as arrhythmias, Lyme disease, inflammation, and, more recently, COVID-19 infection. Despite significant clinical promise shown in research settings, there remain major hurdles in translating the medical uses of wearables to the clinic. There is a clear need for more effective collaboration among stakeholders, including users, data scientists, clinicians, payers, and governments, to improve device security, user privacy, data standardization, regulatory approval, and clinical validity. This review examines the potential of wearables to offer affordable and reliable measures of physiological status that are on par with FDA-approved specialized medical devices. We briefly examine studies where wearables proved critical for the early detection of acute and chronic clinical conditions with a particular focus on cardiovascular disease, viral infections, and mental health. Finally, we discuss current obstacles to the clinical implementation of wearables and provide perspectives on their potential to deliver increasingly personalized proactive health care across a wide variety of conditions.
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Affiliation(s)
- Mohan Babu
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
| | - Ziv Lautman
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
- Department of Bioengineering, Stanford University School of Medicine, Stanford, California, USA
| | - Xiangping Lin
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
| | - Milan H B Sobota
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
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22
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Badolato E, Little A, Le VND. Improving heart rate monitoring in the obese with time-of-flight photoplethysmography (TOF-PPG): a quantitative analysis of source-detector-distance effect. OPTICS EXPRESS 2024; 32:4446-4456. [PMID: 38297646 DOI: 10.1364/oe.510977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 01/15/2024] [Indexed: 02/02/2024]
Abstract
Commercial photoplethysmography (PPG) sensors rely on the measurement of continuous-wave diffuse reflection signals (CW-DRS) to monitor heart rate. Using Monte Carlo modeling of light propagation in skin, we quantitatively evaluate the dependence of continuous-wave photoplethysmography (CW-PPG) in commercial wearables on source-detector distance (SDD). Specifically, when SDD increases from 0.5 mm to 3.3 mm, CW-PPG signal increases by roughly 846% for non-obese (NOB) skin and roughly 683% for morbidly obese (MOB) skin. Ultimately, we introduce the concept of time-of-flight PPG (TOF-PPG) which can significantly improve heart rate signals. Our model shows that the optimized TOF-PPG improves heart rate monitoring experiences by roughly 47.9% in NOB and 93.2% in MOB when SDD = 3.3 mm is at green light. Moving forward, these results will provide a valuable source for hypothesis generation in the scientific community to improve heart rate monitoring.
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Hegeman P, Vader D, Kamke K, El-Toukhy S. Patterns of digital health access and use among US adults: A latent class analysis. RESEARCH SQUARE 2024:rs.3.rs-3895228. [PMID: 38352382 PMCID: PMC10862941 DOI: 10.21203/rs.3.rs-3895228/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Background Digital technologies allow users to engage in health-related behaviors associated with positive outcomes. We aimed to identify classes of US adults with distinct digital technologies access and health use patterns and characterize class composition. Data came from Health Information National Trends Survey Wave 5 Cycles 1-4, a nationally representative cross-sectional survey of US adults ( N = 13,993). We used latent class analysis to identify digital technologies access and health use patterns based on 32 behaviors and access to requisite technologies and platforms that include the internet, internet-enabled devices, health monitors, and electronic health records (EHRs). We ran a multinomial logistic regression to identify sociodemographic and health correlates of class membership ( n = 10,734). Results Ten classes captured patterns of digital technology access and health use among US adults. This included a digitally isolated, a mobile-dependent, and a super user class, which made up 8.9%, 7.8%, and 13.6% of US adults, respectively, and captured access patterns from only basic cellphones and health monitors to near complete access to web-, mobile-, and EHR-based platforms. Half of US adults belonged to classes that lacked access to EHRs and relied on alternative web-based tools typical of patient portals. The proportion of class members who used digital technologies for health purposes varied from small to large. Older and less educated adults had lower odds of belonging to classes characterized by access or engagement in health behaviors. Hispanic and Asian adults had higher odds of belonging to the mobile-dependent class. Individuals without a regular healthcare provider and those who had not visited a provider in the past year were more likely to belong to classes with limited digital technologies access or health use. Discussion Only one third of US adults belonged to classes that had near complete access to digital technologies and whose members engaged in almost all health behaviors examined. Sex, age, and education were associated with membership in classes that lacked access to 1 + digital technologies or exhibited none to limited health uses of such technologies. Results can guide efforts to improve access and health use of digital technologies to maximize associated health benefits and minimize disparities.
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Kainec KA, Caccavaro J, Barnes M, Hoff C, Berlin A, Spencer RMC. Evaluating Accuracy in Five Commercial Sleep-Tracking Devices Compared to Research-Grade Actigraphy and Polysomnography. SENSORS (BASEL, SWITZERLAND) 2024; 24:635. [PMID: 38276327 PMCID: PMC10820351 DOI: 10.3390/s24020635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/12/2024] [Accepted: 01/16/2024] [Indexed: 01/27/2024]
Abstract
The development of consumer sleep-tracking technologies has outpaced the scientific evaluation of their accuracy. In this study, five consumer sleep-tracking devices, research-grade actigraphy, and polysomnography were used simultaneously to monitor the overnight sleep of fifty-three young adults in the lab for one night. Biases and limits of agreement were assessed to determine how sleep stage estimates for each device and research-grade actigraphy differed from polysomnography-derived measures. Every device, except the Garmin Vivosmart, was able to estimate total sleep time comparably to research-grade actigraphy. All devices overestimated nights with shorter wake times and underestimated nights with longer wake times. For light sleep, absolute bias was low for the Fitbit Inspire and Fitbit Versa. The Withings Mat and Garmin Vivosmart overestimated shorter light sleep and underestimated longer light sleep. The Oura Ring underestimated light sleep of any duration. For deep sleep, bias was low for the Withings Mat and Garmin Vivosmart while other devices overestimated shorter and underestimated longer times. For REM sleep, bias was low for all devices. Taken together, these results suggest that proportional bias patterns in consumer sleep-tracking technologies are prevalent and could have important implications for their overall accuracy.
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Affiliation(s)
- Kyle A. Kainec
- Neuroscience & Behavior Program, French Hall, University of Massachusetts Amherst, 230 Stockbridge Road, Amherst, MA 01003, USA;
- Institute for Applied Life Sciences, Life Science Laboratories, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003, USA; (M.B.); (C.H.)
| | - Jamie Caccavaro
- Department of Psychological and Brain Sciences, Tobin Hall, University of Massachusetts Amherst, 135 Hicks Way, Amherst, MA 01003, USA
| | - Morgan Barnes
- Institute for Applied Life Sciences, Life Science Laboratories, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003, USA; (M.B.); (C.H.)
- Department of Psychological and Brain Sciences, Tobin Hall, University of Massachusetts Amherst, 135 Hicks Way, Amherst, MA 01003, USA
| | - Chloe Hoff
- Institute for Applied Life Sciences, Life Science Laboratories, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003, USA; (M.B.); (C.H.)
- Department of Psychological and Brain Sciences, Tobin Hall, University of Massachusetts Amherst, 135 Hicks Way, Amherst, MA 01003, USA
| | - Annika Berlin
- Institute for Applied Life Sciences, Life Science Laboratories, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003, USA; (M.B.); (C.H.)
- Department of Psychological and Brain Sciences, Tobin Hall, University of Massachusetts Amherst, 135 Hicks Way, Amherst, MA 01003, USA
| | - Rebecca M. C. Spencer
- Neuroscience & Behavior Program, French Hall, University of Massachusetts Amherst, 230 Stockbridge Road, Amherst, MA 01003, USA;
- Institute for Applied Life Sciences, Life Science Laboratories, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003, USA; (M.B.); (C.H.)
- Department of Psychological and Brain Sciences, Tobin Hall, University of Massachusetts Amherst, 135 Hicks Way, Amherst, MA 01003, USA
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Golbus JR, Jeganathan VSE, Stevens R, Ekechukwu W, Farhan Z, Contreras R, Rao N, Trumpower B, Basu T, Luff E, Skolarus LE, Newman MW, Nallamothu BK, Dorsch MP. A Physical Activity and Diet Just-in-Time Adaptive Intervention to Reduce Blood Pressure: The myBPmyLife Study Rationale and Design. J Am Heart Assoc 2024; 13:e031234. [PMID: 38226507 PMCID: PMC10926831 DOI: 10.1161/jaha.123.031234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 09/13/2023] [Indexed: 01/17/2024]
Abstract
BACKGROUND Smartphone applications and wearable devices are promising mobile health interventions for hypertension self-management. However, most mobile health interventions fail to use contextual data, potentially diminishing their impact. The myBPmyLife Study is a just-in-time adaptive intervention designed to promote personalized self-management for patients with hypertension. METHODS AND RESULTS The study is a 6-month prospective, randomized-controlled, remotely administered trial. Participants were recruited from the University of Michigan Health in Ann Arbor, Michigan or the Hamilton Community Health Network, a federally qualified health center network in Flint, Michigan. Participants were randomized to a mobile application with a just-in-time adaptive intervention promoting physical activity and lower-sodium food choices as well as weekly goal setting or usual care. The mobile study application encourages goal attainment through a central visualization displaying participants' progress toward their goals for physical activity and lower-sodium food choices. Participants in both groups are followed for up for 6 months with a primary end point of change in systolic blood pressure. Exploratory analyses will examine the impact of notifications on step count and self-reported lower-sodium food choices. The study launched on December 9, 2021, with 484 participants enrolled as of March 31, 2023. Enrollment of participants was completed on July 3, 2023. After 6 months of follow-up, it is expected that results will be available in the spring of 2024. CONCLUSIONS The myBPmyLife study is an innovative mobile health trial designed to evaluate the effects of a just-in-time adaptive intervention focused on improving physical activity and dietary sodium intake on blood pressure in diverse patients with hypertension. REGISTRATION URL: https://www.clinicaltrials.gov; Unique identifier: NCT05154929.
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Affiliation(s)
- Jessica R. Golbus
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
- Michigan Integrated Center for Health Analytics and Medical PredictionUniversity of MichiganAnn ArborMIUSA
| | - V. Swetha E. Jeganathan
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Rachel Stevens
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Weena Ekechukwu
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Zahera Farhan
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Rocio Contreras
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Nikhila Rao
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Brad Trumpower
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Tanima Basu
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Evan Luff
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
| | - Lesli E. Skolarus
- Division of Vascular Neurology, Department of Neurology–Internal MedicineNorthwestern UniversityEvanstonILUSA
| | - Mark W. Newman
- School of Information and Computer Science, College of EngineeringUniversity of MichiganAnn ArborMIUSA
| | - Brahmajee K. Nallamothu
- Division of Cardiovascular Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborMIUSA
- Michigan Integrated Center for Health Analytics and Medical PredictionUniversity of MichiganAnn ArborMIUSA
- The Center for Clinical Management and ResearchAnn ArborMIUSA
| | - Michael P. Dorsch
- Department of Clinical Pharmacy, College of PharmacyUniversity of MichiganAnn ArborMIUSA
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Fischer RP, Volpert A, Antonino P, Ahrens TD. Digital patient twins for personalized therapeutics and pharmaceutical manufacturing. Front Digit Health 2024; 5:1302338. [PMID: 38250053 PMCID: PMC10796488 DOI: 10.3389/fdgth.2023.1302338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 12/13/2023] [Indexed: 01/23/2024] Open
Abstract
Digital twins are virtual models of physical artefacts that may or may not be synchronously connected, and that can be used to simulate their behavior. They are widely used in several domains such as manufacturing and automotive to enable achieving specific quality goals. In the health domain, so-called digital patient twins have been understood as virtual models of patients generated from population data and/or patient data, including, for example, real-time feedback from wearables. Along with the growing impact of data science technologies like artificial intelligence, novel health data ecosystems centered around digital patient twins could be developed. This paves the way for improved health monitoring and facilitation of personalized therapeutics based on management, analysis, and interpretation of medical data via digital patient twins. The utility and feasibility of digital patient twins in routine medical processes are still limited, despite practical endeavors to create digital twins of physiological functions, single organs, or holistic models. Moreover, reliable simulations for the prediction of individual drug responses are still missing. However, these simulations would be one important milestone for truly personalized therapeutics. Another prerequisite for this would be individualized pharmaceutical manufacturing with subsequent obstacles, such as low automation, scalability, and therefore high costs. Additionally, regulatory challenges must be met thus calling for more digitalization in this area. Therefore, this narrative mini-review provides a discussion on the potentials and limitations of digital patient twins, focusing on their potential bridging function for personalized therapeutics and an individualized pharmaceutical manufacturing while also looking at the regulatory impacts.
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27
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Yao X, Attia ZI, Behnken EM, Hart MS, Inselman SA, Weber KC, Li F, Stricker NH, Stricker JL, Friedman PA, Noseworthy PA. Realtime Diagnosis from Electrocardiogram Artificial Intelligence-Guided Screening for Atrial Fibrillation with Long Follow-Up (REGAL): Rationale and design of a pragmatic, decentralized, randomized controlled trial. Am Heart J 2024; 267:62-69. [PMID: 37913853 DOI: 10.1016/j.ahj.2023.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 10/17/2023] [Accepted: 10/21/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Atrial fibrillation (AF) is associated with increased risks of stroke and dementia. Early diagnosis and treatment could reduce the disease burden, but AF is often undiagnosed. An artificial intelligence (AI) algorithm has been shown to identify patients with previously unrecognized AF; however, monitoring these high-risk patients has been challenging. Consumer wearable devices could be an alternative to enable long-term follow-up. OBJECTIVES To test whether Apple Watch, used as a long-term monitoring device, can enable early diagnosis of AF in patients who were identified as having high risk based on AI-ECG. DESIGN The Realtime diagnosis from Electrocardiogram (ECG) Artificial Intelligence (AI)-Guided Screening for Atrial Fibrillation (AF) with Long Follow-up (REGAL) study is a pragmatic trial that will accrue up to 2,000 older adults with a high likelihood of unrecognized AF determined by AI-ECG to reach our target of 1,420 completed participants. Participants will be 1:1 randomized to intervention or control and will be followed up for 2 years. Patients in the intervention arm will receive or use their existing Apple Watch and iPhone and record a 30-second ECG using the watch routinely or if an abnormal heart rate notification is prompted. The primary outcome is newly diagnosed AF. Secondary outcomes include changes in cognitive function, stroke, major bleeding, and all-cause mortality. The trial will utilize a pragmatic, digitally-enabled, decentralized design to allow patients to consent and receive follow-up remotely without traveling to the study sites. SUMMARY The REGAL trial will examine whether a consumer wearable device can serve as a long-term monitoring approach in older adults to detect AF and prevent cognitive function decline. If successful, the approach could have significant implications on how future clinical practice can leverage consumer devices for early diagnosis and disease prevention. CLINICALTRIALS GOV: : NCT05923359.
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Affiliation(s)
- Xiaoxi Yao
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
| | - Zachi I Attia
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Emma M Behnken
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN
| | - Melissa S Hart
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Shealeigh A Inselman
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Kayla C Weber
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Fan Li
- Department of Biostatistics, Yale School of Public Health, New Haven, CT
| | - Nikki H Stricker
- Division of Neurocognitive Disorders, Mayo Clinic, Rochester, MN
| | | | - Paul A Friedman
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
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Sun S, Jiang L, Zhou Y. Associations between perceived usefulness and willingness to use smart healthcare devices among Chinese older adults: The multiple mediating effect of technology interactivity and technology anxiety. Digit Health 2024; 10:20552076241254194. [PMID: 38812850 PMCID: PMC11135081 DOI: 10.1177/20552076241254194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/25/2024] [Indexed: 05/31/2024] Open
Abstract
Objective This study aims to explore the mediating roles of technological interactivity and technological anxiety in the relationship between perceived usefulness and the willingness to use a smart health device to provide insight into the decision-making process of older adults in relation to the adoption of smart devices. Methods A cross-sectional survey was conducted in Jiangsu, China involving 552 older adults. The study utilized structural equation modeling (SEM) to analyze the relationship between the independent variable 'perceived usefulness' and the dependent variable 'willingness to use.' It also examined the multiple mediating effects of technological interactivity and technological anxiety between the independent and dependent variables. Results The results indicate that the direct effect of perceived usefulness on willingness to use was insignificant. However, technological interactivity completely mediated the relationship between perceived usefulness and willingness to use. Additionally, technological interactivity and technological anxiety were found to have a serial mediating effect on the impact of perceived usefulness on willingness to use smart healthcare devices. Conclusions These findings suggest that increasing older adults' intention to use smart healthcare devices requires not only raising awareness of their usefulness, but also addressing technological anxiety and enhancing the interactivity of these devices to improve the overall user experience.
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Affiliation(s)
- Sheng Sun
- Department of Sociology, School of Law, Jiangnan University, Wuxi, China
| | - Lan Jiang
- Department of Sociology, School of Law, Jiangnan University, Wuxi, China
| | - Yue Zhou
- Department of Sociology, School of Law, Jiangnan University, Wuxi, China
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Van Wier MF, Urry E, Lissenberg-Witte BI, Kramer SE. User characteristics associated with use of wrist-worn wearables and physical activity apps by adults with and without impaired speech-in-noise recognition: a cross-sectional analysis. Int J Audiol 2024; 63:49-56. [PMID: 36373621 DOI: 10.1080/14992027.2022.2135031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 10/07/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To study weekly use of smartwatches, fitness watches and physical activity apps among adults with and without impaired speech-in-noise (SIN) recognition, to identify subgroups of users. DESIGN Cross-sectional study. STUDY SAMPLE Adults (aged 28-80 years) with impaired (n = 384) and normal SIN recognition (n = 341) as measured with a web-based digits-in-noise test, from the Netherlands Longitudinal Study on Hearing. Multiple logistic regression analyses were used to study differences and to build an association model. RESULTS Employed adults in both groups are more likely to use each type of fitness technology (all ORs >3.4, all p-values < 0.004). Specific to fitness watch use, adults living with others use it more (OR 2.5, 95%CI 1.1;5.8, p = 0.033) whereas those abstaining from alcohol (OR 0.3, 95%CI 0.1;0.6) or consuming >2 glasses/week (OR 0.4, 95%CI 0.2;0.81, overall p = 0.006) and hearing aid users (OR 0.5, 95%CI 0.2;0.9, p = 0.024) make less use. CONCLUSIONS Subgroups of adults more and less likely to use fitness technology exist, but do not differ between adults with and without impaired SIN recognition. More research is needed to confirm these results and to develop interventions to increase physical activity levels among adults with hearing loss.
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Affiliation(s)
- Marieke F Van Wier
- Otolaryngology-Head and Neck Surgery, Section Ear & Hearing, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Quality of Care, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Emily Urry
- Research & Development, Sonova AG, Stäfa, Switzerland
| | - Birgit I Lissenberg-Witte
- Epidemiology and Data Science, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sophia E Kramer
- Otolaryngology-Head and Neck Surgery, Section Ear & Hearing, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Quality of Care, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
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Choi S, Sajib MRUZ, Manzano J, Chlebek CJ. mHealth Technology Experiences of Middle-Aged and Older Individuals With Visual Impairments: Cross-Sectional Interview Study. JMIR Form Res 2023; 7:e52410. [PMID: 38145472 PMCID: PMC10775026 DOI: 10.2196/52410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 11/25/2023] [Accepted: 11/30/2023] [Indexed: 12/26/2023] Open
Abstract
BACKGROUND Current mobile health (mHealth) technology is predominantly designed with a visual orientation, often resulting in user interfaces that are inaccessible to visually impaired users. While mHealth technology offers potential for facilitating chronic illness management and enhancing health behaviors among visually impaired older populations, understanding its usage remains limited. OBJECTIVE This qualitative research aimed to explore the mHealth technology experiences of middle-aged and older individuals with visual impairments including the accessibility and usability issues they faced. METHODS The qualitative exploration was structured using the mHealth for Older Users framework. Cross-sectional interviews were conducted via Zoom between June 1 and July 31, 2023, using an interview protocol for data collection. A thematic analysis approach was employed to analyze the transcribed interview scripts. RESULTS Of the 7 participants who took part in the Zoom interviews, 3 were men and 4 were women, with ages ranging from 53 to 70 years. Most participants adopted mHealth apps and wearable devices for promoting health. They exhibited 3 distinct adoption patterns. Seven themes were emerged from the perceived challenges in using mHealth technologies: (1) a scarcity of accessible user manuals, (2) user interfaces that are not visually impaired-friendly, (3) health data visualizations that are not accessible, (4) unintuitive arrangement of app content, (5) health information that is challenging to comprehend, (6) cognitive overload caused by an excess of audible information, and (7) skepticism regarding the accuracy of health records. mHealth technologies seem to positively affect the health and health management of participants. CONCLUSIONS Design considerations for mHealth technologies should consider individuals' disabilities and chronic conditions and should emphasize the importance of providing accessible manuals and training opportunities when introducing new mHealth solutions.
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Affiliation(s)
- Soyoung Choi
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Md Refat Uz Zaman Sajib
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Jenna Manzano
- College of Liberal Arts and Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Christian Joseph Chlebek
- College of Liberal Arts and Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States
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Oba T, Takano K, Katahira K, Kimura K. Use Patterns of Smartphone Apps and Wearable Devices Supporting Physical Activity and Exercise: Large-Scale Cross-Sectional Survey. JMIR Mhealth Uhealth 2023; 11:e49148. [PMID: 37997790 PMCID: PMC10690103 DOI: 10.2196/49148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/17/2023] [Accepted: 08/18/2023] [Indexed: 11/25/2023] Open
Abstract
Background Physical inactivity is a global health issue, and mobile health (mHealth) apps are expected to play an important role in promoting physical activity. Empirical studies have demonstrated the efficacy and efficiency of app-based interventions, and an increasing number of apps with more functions and richer content have been released. Regardless of the success of mHealth apps, there are important evidence gaps in the literature; that is, it is largely unknown who uses what app functions and which functions are associated with physical activity. Objective This study aims to investigate the use patterns of apps and wearables supporting physical activity and exercise in a Japanese-speaking community sample. Methods We recruited 20,573 web-based panelists who completed questionnaires concerning demographics, regular physical activity levels, and use of apps and wearables supporting physical activity. Participants who indicated that they were using a physical activity app or wearable were presented with a list of app functions (eg, sensor information, goal setting, journaling, and reward), among which they selected any functions they used. Results Approximately one-quarter (n=4465) of the sample was identified as app users and showed similar demographic characteristics to samples documented in the literature; that is, compared with app nonusers, app users were younger (odds ratio [OR] 0.57, 95% CI 0.50-0.65), were more likely to be men (OR 0.83, 95% CI 0.77-0.90), had higher BMI scores (OR 1.02, 95% CI 1.01-1.03), had higher levels of education (university or above; OR 1.528, 95% CI 1.19-1.99), were more likely to have a child (OR 1.16, 95% CI 1.05-1.28) and job (OR 1.28, 95% CI 1.17-1.40), and had a higher household income (OR 1.40, 95% CI 1.21-1.62). Our results revealed unique associations between demographic variables and specific app functions. For example, sensor information, journaling, and GPS were more frequently used by men than women (ORs <0.84). Another important finding is that people used a median of 2 (IQR 1-4) different functions within an app, and the most common pattern was to use sensor information (ie, self-monitoring) and one other function such as goal setting or reminders. Conclusions Regardless of the current trend in app development toward multifunctionality, our findings highlight the importance of app simplicity. A set of two functions (more precisely, self-monitoring and one other function) might be the minimum that can be accepted by most users. In addition, the identified individual differences will help developers and stakeholders pave the way for the personalization of app functions.
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Affiliation(s)
- Takeyuki Oba
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan
| | - Keisuke Takano
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan
| | - Kentaro Katahira
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan
| | - Kenta Kimura
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan
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Dobson R, Stowell M, Warren J, Tane T, Ni L, Gu Y, McCool J, Whittaker R. Use of Consumer Wearables in Health Research: Issues and Considerations. J Med Internet Res 2023; 25:e52444. [PMID: 37988147 DOI: 10.2196/52444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 10/23/2023] [Accepted: 10/26/2023] [Indexed: 11/22/2023] Open
Abstract
As wearable devices, which allow individuals to track and self-manage their health, become more ubiquitous, the opportunities are growing for researchers to use these sensors within interventions and for data collection. They offer access to data that are captured continuously, passively, and pragmatically with minimal user burden, providing huge advantages for health research. However, the growth in their use must be coupled with consideration of their potential limitations, in particular, digital inclusion, data availability, privacy, ethics of third-party involvement, data quality, and potential for adverse consequences. In this paper, we discuss these issues and strategies used to prevent or mitigate them and recommendations for researchers using wearables as part of interventions or for data collection.
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Affiliation(s)
- Rosie Dobson
- School of Population Health, University of Auckland, Auckland, New Zealand
- Institute for Innovation and Improvement, Te Whatu Ora Waitematā, Auckland, New Zealand
| | - Melanie Stowell
- School of Population Health, University of Auckland, Auckland, New Zealand
| | - Jim Warren
- School of Computer Science, University of Auckland, Auckland, New Zealand
| | - Taria Tane
- School of Population Health, University of Auckland, Auckland, New Zealand
| | - Lin Ni
- School of Population Health, University of Auckland, Auckland, New Zealand
| | - Yulong Gu
- School of Health Sciences, Stockton University, Galloway, NJ, United States
| | - Judith McCool
- School of Population Health, University of Auckland, Auckland, New Zealand
| | - Robyn Whittaker
- School of Population Health, University of Auckland, Auckland, New Zealand
- Institute for Innovation and Improvement, Te Whatu Ora Waitematā, Auckland, New Zealand
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Qu M, Zhao J, Zhang Y, Xu Z, Ma C, Cui H. Utilizing the visual analogue scale (VAS) to monitor and manage pain in post-operative skin wounds after thoracic surgery. Int Wound J 2023; 21:e14503. [PMID: 37969025 PMCID: PMC10898399 DOI: 10.1111/iwj.14503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 11/01/2023] [Accepted: 11/07/2023] [Indexed: 11/17/2023] Open
Abstract
Due to the global increase in thoracic interventions, there is greater emphasis on refining post-operative care. The purpose of this study was to validate the visual analogue scale (VAS) as the valid method for measuring post-operative pain in thoracic surgery patients. From January 2020 to June 2022, this cross-sectional study investigated 240 adult patients who underwent elective thoracic surgeries in Thoracic Surgery Department of Heilongjiang Provincial Hospital. The participants were instructed to rate their discomfort using VAS at predetermined intervals after surgery. The following demographic and clinical information was recorded: age, gender, type of thoracic surgery, and history of chronic pain. Results showed a progressive decline in post-operative VAS scores over 72 h: 8.2 immediately after surgery, 6.0 at 24 h, 5.4 at 48 h, and 3.6 by 72 h. There were notable correlations between VAS scores and chronic pain history, with moderately positive correlation of 0.40 being observed. Mean scores for males and females were 3.8 and 3.9, respectively. The analysis by age revealed comparable mean scores for age categories below and above 40. With the exception of thoracic wall resection, which resulted in an average VAS score of 4.1 ± 1.0 (p < 0.05), the type of surgery had the minimal effect on variability of pain scores. The VAS is a reliable method for evaluating post-thoracic surgery discomfort. Given the substantial impact of pain history on VAS scores, there is an urgent need for personalized pain management strategies to improve post-operative care.
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Affiliation(s)
- Mingyue Qu
- Department of Cardiothoracic SurgeryHeilongjiang provincial hospitalHarbinChina
| | - Jialai Zhao
- Department of Cardiothoracic SurgeryHeilongjiang provincial hospitalHarbinChina
| | - Yiling Zhang
- Department of Cardiothoracic SurgeryHeilongjiang provincial hospitalHarbinChina
| | - Zigeng Xu
- Department of Cardiothoracic SurgeryHeilongjiang provincial hospitalHarbinChina
| | - Chenguang Ma
- Department of Cardiothoracic SurgeryHeilongjiang provincial hospitalHarbinChina
| | - Hanwen Cui
- Department of Cardiothoracic SurgeryHeilongjiang provincial hospitalHarbinChina
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Simonson JK, Anderson M, Polacek C, Klump E, Haque SN. Characterizing Real-World Implementation of Consumer Wearables for the Detection of Undiagnosed Atrial Fibrillation in Clinical Practice: Targeted Literature Review. JMIR Cardio 2023; 7:e47292. [PMID: 37921865 PMCID: PMC10656655 DOI: 10.2196/47292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 09/25/2023] [Accepted: 09/27/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND Atrial fibrillation (AF), the most common cardiac arrhythmia, is often undiagnosed because of lack of awareness and frequent asymptomatic presentation. As AF is associated with increased risk of stroke, early detection is clinically relevant. Several consumer wearable devices (CWDs) have been cleared by the US Food and Drug Administration for irregular heart rhythm detection suggestive of AF. However, recommendations for the use of CWDs for AF detection in clinical practice, especially with regard to pathways for workflows and clinical decisions, remain lacking. OBJECTIVE We conducted a targeted literature review to identify articles on CWDs characterizing the current state of wearable technology for AF detection, identifying approaches to implementing CWDs into the clinical workflow, and characterizing provider and patient perspectives on CWDs for patients at risk of AF. METHODS PubMed, ClinicalTrials.gov, UpToDate Clinical Reference, and DynaMed were searched for articles in English published between January 2016 and July 2023. The searches used predefined Medical Subject Headings (MeSH) terms, keywords, and search strings. Articles of interest were specifically on CWDs; articles on ambulatory monitoring tools, tools available by prescription, or handheld devices were excluded. Search results were reviewed for relevancy and discussed among the authors for inclusion. A qualitative analysis was conducted and themes relevant to our study objectives were identified. RESULTS A total of 31 articles met inclusion criteria: 7 (23%) medical society reports or guidelines, 4 (13%) general reviews, 5 (16%) systematic reviews, 5 (16%) health care provider surveys, 7 (23%) consumer or patient surveys or interviews, and 3 (10%) analytical reports. Despite recognition of CWDs by medical societies, detailed guidelines regarding CWDs for AF detection were limited, as was the availability of clinical tools. A main theme was the lack of pragmatic studies assessing real-world implementation of CWDs for AF detection. Clinicians expressed concerns about data overload; potential for false positives; reimbursement issues; and the need for clinical tools such as care pathways and guidelines, preferably developed or endorsed by professional organizations. Patient-facing challenges included device costs and variability in digital literacy or technology acceptance. CONCLUSIONS This targeted literature review highlights the lack of a comprehensive body of literature guiding real-world implementation of CWDs for AF detection and provides insights for informing additional research and developing appropriate tools and resources for incorporating these devices into clinical practice. The results should also provide an impetus for the active involvement of medical societies and other health care stakeholders in developing appropriate tools and resources for guiding the real-world use of CWDs for AF detection. These resources should target clinicians, patients, and health care systems with the goal of facilitating clinician or patient engagement and using an evidence-based approach for establishing guidelines or frameworks for administrative workflows and patient care pathways.
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Tolentino DA, Costa DK, Jiang Y. Determinants of American Adults' Use of Digital Health and Willingness to Share Health Data to Providers, Family, and Social Media: A Cross-sectional Study. Comput Inform Nurs 2023; 41:892-902. [PMID: 37310724 PMCID: PMC10713855 DOI: 10.1097/cin.0000000000001025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
With the global pandemic driving the adoption of digital health, understanding the predictors or determinants of digital health usage and information sharing gives an opportunity to advocate for broader adoption. We examined the prevalence and predictors of digital health usage and information-sharing behaviors among American adults. Data were from the Health Information National Trends Survey 5 Cycle 4. More than two-thirds used a digital resource for health-related activities (eg, to check test results). About 81% were willing to share their digital data with their provider, 75% with family, and 58% with friends. Only 14% shared health information on social media. Gender, education, device types, and performance expectancy of digital health were common factors associated with both digital health usage and information-sharing behaviors. Other predictors included rurality, patient portal access, income, and having a chronic disease. Of note, we found that Asian American Pacific Islanders, compared with Whites, were less likely to share information with providers. Performance expectancy was a significant determinant of information sharing. Those diagnosed with diabetes were 4% less likely to share information with their providers. With the growing digital divide, there is a need to advocate for more usable and accessible digital health to assist with person-centered care.
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Affiliation(s)
| | | | - Yun Jiang
- School of Nursing, University of Michigan, Ann Arbor
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Lee MA, Song M, Bessette H, Roberts Davis M, Tyner TE, Reid A. Use of wearables for monitoring cardiometabolic health: A systematic review. Int J Med Inform 2023; 179:105218. [PMID: 37806179 DOI: 10.1016/j.ijmedinf.2023.105218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/28/2023] [Accepted: 09/15/2023] [Indexed: 10/10/2023]
Abstract
INTRODUCTION Cardiometabolic disorders (CMD) such as hyperglycemia, obesity, hypertension, and dyslipidemia are the leading causes of mortality and significant public health concerns worldwide. With the advances in wireless technology, wearables have become popular for health promotion, but its impact on cardiometabolic health is not well understood. PURPOSE A systematic literature review aimed to describe the features of wearables used for monitoring cardiometabolic health and identify the impact of using wearables on those cardiometabolic health indicators. METHODS A systematic search of PubMed, CINAHL, Academic Search Complete, and Science and Technology Collection databases was performed using keywords related to CMD risk indicators and wearables. The wearables were limited to sensors for blood pressure (BP), heart rate (HR), electrocardiogram (ECG), glucose, and cholesterol. INCLUDED STUDIES 1) were published from 2016 to March 2021 in English, 2) focused on wearables external to the body, and 3) examined wearable use by individuals in daily life (not by health care providers). Protocol, technical, and non-empirical studies were excluded. RESULTS Out of 53 studies, the types of wearables used were smartwatches (45.3%), patches (34.0%), chest straps (22.6%), wristbands (13.2%), and others (9.4%). HR (58.5%), glucose (28.3%), and ECG (26.4%) were the predominant indicators. No studies tracked BP or cholesterol. Additional features of wearables included physical activity, respiration, sleep, diet, and symptom monitoring. Twenty-two studies primarily focused on the use of wearables and reported direct impacts on cardiometabolic indicators; seven studies used wearables as part of a multi-modality approach and presented outcomes affected by a primary intervention but measured through CMD-sensor wearables; and 24 validated the precision and usability of CMD-sensor wearables. CONCLUSION The impact of wearables on cardiometabolic indicators varied across the studies, indicating the need for further research. However, this body of literature highlights the potential of wearables to promote cardiometabolic health.
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Affiliation(s)
- Mikyoung A Lee
- Texas Woman's University, College of Nursing, Dallas, TX, United States.
| | - MinKyoung Song
- Oregon Health & Science University, School of Nursing, Portland, OR, United States.
| | - Hannah Bessette
- Oregon Health & Science University, School of Nursing, Portland, OR, United States
| | - Mary Roberts Davis
- Oregon Health & Science University, School of Nursing, Portland, OR, United States
| | - Tracy E Tyner
- Texas Woman's University, College of Nursing, Dallas, TX, United States
| | - Amy Reid
- Texas Woman's University, College of Nursing, Dallas, TX, United States
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Artese AL, Rawat R, Sung AD. The use of commercial wrist-worn technology to track physiological outcomes in behavioral interventions. Curr Opin Clin Nutr Metab Care 2023; 26:534-540. [PMID: 37522804 DOI: 10.1097/mco.0000000000000970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/01/2023]
Abstract
PURPOSE OF REVIEW The aim of this review is to provide an overview of the use of commercial wrist-worn mobile health devices to track and monitor physiological outcomes in behavioral interventions as well as discuss considerations for selecting the optimal device. RECENT FINDINGS Wearable technology can enhance intervention design and implementation. The use of wrist-worn wearables provides the opportunity for tracking physiological outcomes, thus providing a unique approach for assessment and delivery of remote interventions. Recent findings support the utility, acceptability, and benefits of commercial wrist-worn wearables in interventions, and they can be used to continuously monitor outcomes, remotely administer assessments, track adherence, and personalize interventions. Wrist-worn devices show acceptable accuracy when measuring heart rate, blood pressure, step counts, and physical activity; however, accuracy is dependent on activity type, intensity, and device brand. These factors should be considered when designing behavioral interventions that utilize wearable technology. SUMMARY With the continuous advancement in technology and frequent product upgrades, the capabilities of commercial wrist-worn devices will continue to expand, thus increasing their potential use in intervention research. Continued research is needed to examine and validate the most recent devices on the market to better inform intervention design and implementation.
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Affiliation(s)
| | - Rahul Rawat
- Division of Hematologic Malignancies and Cellular Therapy, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA
| | - Anthony D Sung
- Division of Hematologic Malignancies and Cellular Therapy, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA
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Elkefi S. Supporting patients' workload through wearable devices and mobile health applications, a systematic literature review. ERGONOMICS 2023:1-17. [PMID: 37830977 DOI: 10.1080/00140139.2023.2270780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 08/25/2023] [Indexed: 10/14/2023]
Abstract
Patients face a challenging workload in their course of care. In this study, we investigate the impact of using mobile health technologies in supporting this workload and identify the system challenges of its application through a systematic review of the literature published in the last two decades following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Reviews and Meta-Analysis guidelines PRISMA guidelines. Twenty-two studies that satisfied the inclusion criteria were included. The review revealed various mobile health and wearable devices used to support mental demand, physical demand, frustration, and performance. Better outcomes were related to mobile health use in healthcare for patients in different settings. There were no applications of health that supported the temporal demand of patients. Some populations, such as cancer patients, need more than only physical demand. Mhealth devices are important in supporting the patients' workload in their daily activities and clinical settings.Practitioner summary: This review study shows the importance of mHealth and wearables in supporting patients' workload (physical, mental, emotional) but not the temporal load.
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Affiliation(s)
- Safa Elkefi
- Nursing School, Columbia University, New York, NY, USA
- HPHACTORS Lab, NYC, USA
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39
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Li X, Mao JJ, Garland SN, Root J, Li SQ, Ahles T, Liou KT. Comparing sleep measures in cancer survivors: Self-reported sleep diary versus objective wearable sleep tracker. RESEARCH SQUARE 2023:rs.3.rs-3407984. [PMID: 37886444 PMCID: PMC10602054 DOI: 10.21203/rs.3.rs-3407984/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Purpose Cancer survivors are increasingly using wearable fitness trackers, but it's unclear if they match traditional self-reported sleep diaries. We aimed to compare sleep data from Fitbit and the Consensus Sleep Diary (CSD) in this group. Methods We analyzed data from two randomized clinical trials, using both CSD and Fitbit to collect sleep outcomes: total sleep time (TST), wake time after sleep onset (WASO), number of awakenings (NWAK), time in bed (TIB) and sleep efficiency (SE). Insomnia severity was measured by Insomnia Severity Index (ISI). We used the Wilcoxon Singed Ranks Test, Spearman's rank correlation coefficients, and the Mann-Whitney Test to compare sleep outcomes and assess their ability to distinguish insomnia severity levels between CSD and Fitbit data. Results Among 62 participants, compared to CSD, Fitbit recorded longer TST by an average of 14.6 (SD = 84.9) minutes, longer WASO by an average of 28.7 (SD = 40.5) minutes, more NWAK by an average of 16.7 (SD = 6.6) times per night, and higher SE by an average of 7.1% (SD = 14.4); but shorter TIB by an average of 24.4 (SD = 71.5) minutes. All the differences were statistically significant (all p < 0.05), except for TST (p = 0.38). Moderate correlations were found for TST (r = 0.41, p = 0.001) and TIB (r = 0.44, p < 0.001). Compared to no/mild insomnia group, participants with clinical insomnia reported more NWAK (p = 0.009) and lower SE (p = 0.029) as measured by CSD, but Fitbit outcomes didn't. Conclusions TST was the only similar outcome between Fitbit and CSD. Our study highlights the advantages, disadvantages, and clinical utilization of sleep trackers in oncology.
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Affiliation(s)
| | - Jun J Mao
- Memorial Sloan Kettering Cancer Center
| | | | | | | | - Tim Ahles
- Memorial Sloan Kettering Cancer Center
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40
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Roos LG, Slavich GM. Wearable technologies for health research: Opportunities, limitations, and practical and conceptual considerations. Brain Behav Immun 2023; 113:444-452. [PMID: 37557962 PMCID: PMC11233111 DOI: 10.1016/j.bbi.2023.08.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/31/2023] [Accepted: 08/06/2023] [Indexed: 08/11/2023] Open
Abstract
One of the most notable limitations of laboratory-based health research is its inability to continuously monitor health-relevant physiological processes as individuals go about their daily lives. As a result, we have generated large amounts of data with unknown generalizability to real-world situations and also created a schism between where data are collected (i.e., in the lab) and where we need to intervene to prevent disease (i.e., in the field). Devices using noninvasive wearable technology are changing all of this, however, with their ability to provide high-frequency assessments of peoples' ever-changing physiological states in daily life in a manner that is relatively noninvasive, affordable, and scalable. Here, we discuss critical points that every researcher should keep in mind when using these wearables in research, spanning device and metric decisions, hardware and software selection, and data quality and sampling rate issues, using research on stress and health as an example throughout. We also address usability and participant acceptability issues, and how wearable "digital biomarker" and behavioral data can be integrated to enhance basic science and intervention studies. Finally, we summarize 10 key questions that should be addressed to make every wearable study as strong as possible. Collectively, keeping these points in mind can improve our ability to study the psychobiology of human health, and to intervene, precisely where it matters most: in peoples' daily lives.
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Affiliation(s)
- Lydia G Roos
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.
| | - George M Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
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Willoughby AR, Alikhani I, Karsikas M, Chua XY, Chee MWL. Country differences in nocturnal sleep variability: Observations from a large-scale, long-term sleep wearable study. Sleep Med 2023; 110:155-165. [PMID: 37595432 DOI: 10.1016/j.sleep.2023.08.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 07/10/2023] [Accepted: 08/09/2023] [Indexed: 08/20/2023]
Abstract
STUDY OBJECTIVES Country or regional differences in sleep duration are well-known, but few large-scale studies have specifically evaluated sleep variability, either across the work week, or in terms of differences in weekday and weekend sleep. METHODS Sleep measures, obtained over 50 million night's sleep from ∼220,000 wearable device users in 35 countries, were analysed. Each person contributed an average of ∼242 nights of data. Multiple regression was used to assess the impact country of residence had on sleep duration, timing, efficiency, weekday sleep variability, weekend sleep extension and social jetlag. RESULTS Nocturnal sleep was shorter and had a later onset in Asia than other regions. Despite this, sleep efficiency was lower and weekday sleep variability was higher. Weekend sleep extension was longer in Europe and the USA than in Asia, and was only partially related to weekday sleep duration. There were also cross-country differences in social jetlag although the regional differences were less distinct than for weekend sleep extension. CONCLUSIONS In addition to regional differences in sleep duration, cross-country differences in sleep variability and weekend sleep extension suggest that using the latter as an indicator of sleep debt may need to be reconsidered. In countries exhibiting both short sleep and high weekday sleep variability, a culturally different means of coping with inadequate sleep is likely. Country or region differences in culture, particularly those related to work, merit closer examination as factors influencing the variability in normative sleep patterns around the world.
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Affiliation(s)
- Adrian R Willoughby
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, 12 Science Drive 2, Singapore, 117549, Singapore
| | - Iman Alikhani
- Oura Health Oy, Oulu, Elektroniikkatie 10, 90590, Finland
| | - Mari Karsikas
- Oura Health Oy, Oulu, Elektroniikkatie 10, 90590, Finland
| | - Xin Yu Chua
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, 12 Science Drive 2, Singapore, 117549, Singapore
| | - Michael W L Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, 12 Science Drive 2, Singapore, 117549, Singapore.
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Bond A, Mccay K, Lal S. Artificial intelligence & clinical nutrition: What the future might have in store. Clin Nutr ESPEN 2023; 57:542-549. [PMID: 37739704 DOI: 10.1016/j.clnesp.2023.07.082] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 07/02/2023] [Accepted: 07/17/2023] [Indexed: 09/24/2023]
Abstract
Artificial Intelligence (AI) is a rapidly emerging technology in healthcare that has the potential to revolutionise clinical nutrition. AI can assist in analysing complex data, interpreting medical images, and providing personalised nutrition interventions for patients. Clinical nutrition is a critical aspect of patient care, and AI can help clinicians make more informed decisions regarding patients' nutritional requirements, disease prevention, and management. AI algorithms can analyse large datasets to identify novel associations between diet and disease outcomes, enabling clinicians to make evidence-based nutritional recommendations. AI-powered devices and applications can also assist in tracking dietary intake, providing feedback, and motivating patients towards healthier food choices. However, the adoption of AI in clinical nutrition raises several ethical and regulatory concerns, such as data privacy and bias. Further research is needed to assess the clinical effectiveness and safety of AI-powered nutrition interventions. In conclusion, AI has the potential to transform clinical nutrition, but its integration into clinical practice should be carefully monitored to ensure patient safety and benefit. This article discusses the current and future applications of AI in clinical nutrition and highlights its potential benefits.
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Affiliation(s)
- Ashley Bond
- Intestinal Failure Unit, Salford Royal Foundation Trust, UK; University of Manchester, Manchester, UK.
| | - Kevin Mccay
- Manchester Metropolitan University, Manchester, UK; Northern Care Alliance NHS Foundation Trust, Salford Royal Hospital, Salford, UK
| | - Simon Lal
- Intestinal Failure Unit, Salford Royal Foundation Trust, UK; University of Manchester, Manchester, UK
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El-Toukhy S, Pike JR, Zuckerman G, Hegeman P. Decision Trade-Offs in Ecological Momentary Assessments and Digital Wearables Uptake: Protocol for a Discrete Choice Experiment. JMIR Res Protoc 2023; 12:e47567. [PMID: 37747771 PMCID: PMC10562974 DOI: 10.2196/47567] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/05/2023] [Accepted: 08/07/2023] [Indexed: 09/26/2023] Open
Abstract
BACKGROUND Ecological momentary assessments (EMAs) and digital wearables (DW) are commonly used remote monitoring technologies that capture real-time data in people's natural environments. Real-time data are core to personalized medical care and intensively adaptive health interventions. The utility of such personalized care is contingent on user uptake and continued use of EMA and DW. Consequently, it is critical to understand user preferences that may increase the uptake of EMA and DW. OBJECTIVE The study aims to quantify users' preferences of EMA and DW, examine variations in users' preferences across demographic and behavioral subgroups, and assess the association between users' preferences and intentions to use EMA and DW. METHODS We will administer 2 discrete choice experiments (DCEs) paired with self-report surveys on the internet to a total of 3260 US adults through Qualtrics. The first DCE will assess participants' EMA preferences using a choice-based conjoint design that will ask participants to compare the relative importance of prompt frequency, number of questions per prompt, prompt type, health topic, and assessment duration. The second DCE will measure participants' DW preferences using a maximum difference scaling design that will quantify the relative importance of device characteristics, effort expectancy, social influence, and facilitating technical, health care, and market factors. Hierarchical Bayesian multinomial logistic regression models will be used to generate subject-specific preference utilities. Preference utilities will be compared across demographic (ie, sex, age, race, and ethnicity) and behavioral (ie, substance use, physical activity, dietary behavior, and sleep duration) subgroups. Regression models will determine whether specific utilities are associated with attitudes toward or intentions to use EMA and DW. Mixture models will determine the associations of attitudes toward and intentions to use EMA and DW with latent profiles of user preferences. RESULTS The institutional review board approved the study on December 19, 2022. Data collection started on January 20, 2023, and concluded on May 4, 2023. Data analysis is currently underway. CONCLUSIONS The study will provide evidence on users' preferences of EMA and DW features that can improve initial uptake and potentially continued use of these remote monitoring tools. The sample size and composition allow for subgroup analysis by demographics and health behaviors and will provide evidence on associations between users' preferences and intentions to uptake EMA and DW. Limitations include the cross-sectional nature of the study, which limits our ability to measure direct behavior. Rather, we capture behavioral intentions for EMA and DW uptake. The nonprobability sample limits the generalizability of the results and introduces self-selection bias related to the demographic and behavioral characteristics of participants who belong to web-based survey panels. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/47567.
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Affiliation(s)
- Sherine El-Toukhy
- Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Rockville, MD, United States
| | - James Russell Pike
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Gabrielle Zuckerman
- Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Rockville, MD, United States
| | - Phillip Hegeman
- Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Rockville, MD, United States
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Anik AR, Hasan K, Islam MM, Hasan MM, Ali MF, Das SK. Non-Invasive Portable Technologies for Monitoring Breast Cancer Related Lymphedema to Facilitate Telehealth: A Scoping Review. IEEE J Biomed Health Inform 2023; 27:4524-4535. [PMID: 37247315 DOI: 10.1109/jbhi.2023.3280196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Breast cancer related lymphedema (BCRL) is a common, debilitating condition that can affect up to one in five breast cancer surviving patients (BCSP). BCRL can significantly reduce the quality of life (QOL) of patients and poses a significant challenge to healthcare providers. Early detection and continuous monitoring of lymphedema is crucial for the development of client-centered treatment plans for post-cancer surgery patients. Therefore, this comprehensive scoping review aimed to investigate the current technology methods used for the remote monitoring of BCRL and their potential to facilitate telehealth in the treatment of lymphedema. Initially, five electronic databases were systematically searched and analyzed following the PRISMA flow diagram. Studies were included, specifically if they provided data on the effectiveness of the intervention and were designed for the remote monitoring of BCRL. A total of 25 included studies reported 18 technological solutions to remotely monitor BCRL with significant methodological variation. Additionally, the technologies were categorized by method of detection and wearability. The findings of this comprehensive scoping review indicate that state-of-the-art commercial technologies were found to be more appropriate for clinical use than home monitoring, with portable 3D imaging tools being popular (SD 53.40) and accurate (correlation 0.9, p 0.05) for evaluating lymphedema in both clinic and home settings with expert practitioners and therapists. However, wearable technologies showed the most future potential for accessible and clinical long-term lymphedema management with positive telehealth outcomes. In conclusion, the absence of a viable telehealth device highlights the need for urgent research to develop a wearable device that can effectively track BCRL and facilitate remote monitoring, ultimately improving the quality of life for patients following post-cancer treatment.
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Jiang Y, Zeng K, Yang R. Wearable device use in older adults associated with physical activity guideline recommendations: Empirical research quantitative. J Clin Nurs 2023; 32:6374-6383. [PMID: 36740763 DOI: 10.1111/jocn.16631] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 11/11/2022] [Accepted: 01/06/2023] [Indexed: 02/07/2023]
Abstract
AIMS AND OBJECTIVES To (1) describe the socio-demographic and behavioural characteristics of older adults who use wearable devices for physical activity monitoring and (2) explore whether wearable device use increases the possibilities of meeting physical activity guideline recommendations among older adults and older adults with known cardiovascular disease or risk. BACKGROUND Finding ways to increase physical activity and reduce cardiovascular disease risk among older adults is a public health priority. Wearable technology has great potential for promoting physical activity among older adults. DESIGN A secondary analysis of the national data. METHODS A nationally representative sample of older adults aged 65 years and older (mean age = 73.79 years, N = 1484) and a subsample of older adults with known cardiovascular disease or cardiovascular disease risk (mean = 74.32 years, N = 1098) was used in the analysis. All analyses were weighted to account for the complex survey design. This study was reported according to the STROBE checklist. RESULTS The overall prevalence of wearable device use among older adults and older adults with cardiovascular disease risk was 16% and 14%, respectively. Older adults with higher household incomes, better self-rated health, and greater exercise enjoyment were more likely to use wearable devices. Compared with non-users, older adult users were more likely to meet the recommended levels of moderate (55% vs. 31%) and strengthening activity guidelines (46% vs. 25%), but not of the sedentary behaviour guideline (69% vs. 62%). Similar findings were also seen in older adults with known cardiovascular disease or risk. CONCLUSION The uptake of wearable devices in older adults, particularly those with known cardiovascular disease or risk is still low. The use of wearable devices is an important facilitator of physical activity. It is critical to provide individualised support for their engagement. RELEVANCE TO CLINICAL PRACTICE Age-friendly design and individualised support are recommended to increase older adults' adoption of wearable devices to improve their physical health. PATIENT OR PUBLIC CONTRIBUTION No patient or public contribution was involved in this study since we used publicly available data.
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Affiliation(s)
- Yun Jiang
- School of Nursing, University of Michigan, Ann Arbor, Michigan, USA
| | - Kai Zeng
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Rumei Yang
- School of Nursing, Nanjing Medical University, Nanjing, China
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Feng G, Parthipan M, Breunis H, Timilshina N, Soto-Perez-de-Celis E, Mina DS, Emmenegger U, Finelli A, Krzyzanowska MK, Clarke H, Puts M, Alibhai SMH. Daily physical activity monitoring in older adults with metastatic prostate cancer on active treatment: Feasibility and associations with toxicity. J Geriatr Oncol 2023; 14:101576. [PMID: 37421787 DOI: 10.1016/j.jgo.2023.101576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 06/26/2023] [Accepted: 06/28/2023] [Indexed: 07/10/2023]
Abstract
INTRODUCTION Physical activity may be associated with cancer treatment toxicity, but generalizability to geriatric oncology is unclear. As many older adults have low levels of physical activity and technology use, this area needs further exploration. We evaluated the feasibility of daily step count monitoring and the association between step counts and treatment-emergent symptoms. MATERIALS AND METHODS Adults aged 65+ starting treatment (chemotherapy, enzalutamide/abiraterone, or radium-223) for metastatic prostate cancer were enrolled in a prospective cohort study. Participants reported step counts (measured via smartphone) and symptoms (Edmonton Symptom Assessment Scale) daily for one treatment cycle (i.e., 3-4 weeks). Embedded semi-structured interviews were performed upon completion of the study. The feasibility of daily monitoring was evaluated with descriptive statistics and thematic analysis. The predictive validity of a decline in daily steps (compared to pre-treatment baseline) for the emergence of symptoms was examined using sensitivity and positive predictive value (PPV). Associations between a 15% decline in steps and the emergence of moderate (4-6/10) to severe (7-10/10) symptoms and pain in the next 24 h were assessed using logistic regression. RESULTS Of 90 participants, 47 engaged in step count monitoring (median age = 75, range = 65-88; 52.2% participation rate). Daily physical activity monitoring was found to be feasible (94% retention rate; 90.5% median response rate) with multiple patient-reported benefits including increased self-awareness and motivation to engage in physical activity. During the first treatment cycle, instances of a 15% decline in steps were common (n = 37, 78.7%), as was the emergence of moderate to severe symptoms overall (n = 40, 85.1%) and pain (n = 26, 55.3%). The predictive validity of a 15% decline in steps on the emergence of moderate to severe symptoms was good (sensitivity = 81.8%, 95% confidence interval [CI] = 68.7-95.0; PPV = 73.0%, 95% CI = 58.7-87.3), although the PPV for pain was poor (sensitivity = 77.8%, 95% CI = 58.6-97.0; PPV = 37.8%, 95% CI = 22.2-53.5). In the regression models, changes in daily physical activity were not associated with symptoms or pain. DISCUSSION Changes in physical activity had modest ability to predict moderate to severe symptoms overall. Although participation was suboptimal, daily activity monitoring in older adults with cancer appears feasible and may have other uses such as improving physical activity levels. Further studies are warranted.
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Affiliation(s)
- Gregory Feng
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Milothy Parthipan
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Henriette Breunis
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Narhari Timilshina
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Enrique Soto-Perez-de-Celis
- Department of Geriatrics, Salvador Zubirán National Institute of Medical Science and Nutrition, Mexico City, Mexico
| | - Daniel Santa Mina
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, Canada
| | - Urban Emmenegger
- Division of Medical Oncology, Odette Cancer Centre, Toronto, Ontario, Canada
| | - Antonio Finelli
- Division of Urology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Monika K Krzyzanowska
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Hance Clarke
- Department of Anesthesia, Toronto General Hospital, Toronto, Ontario, Canada
| | - Martine Puts
- Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada
| | - Shabbir M H Alibhai
- Department of Medicine, University Health Network, Toronto, Ontario, Canada.
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Schalkamp AK, Peall KJ, Harrison NA, Sandor C. Wearable movement-tracking data identify Parkinson's disease years before clinical diagnosis. Nat Med 2023; 29:2048-2056. [PMID: 37400639 DOI: 10.1038/s41591-023-02440-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 06/05/2023] [Indexed: 07/05/2023]
Abstract
Parkinson's disease is a progressive neurodegenerative movement disorder with a long latent phase and currently no disease-modifying treatments. Reliable predictive biomarkers that could transform efforts to develop neuroprotective treatments remain to be identified. Using UK Biobank, we investigated the predictive value of accelerometry in identifying prodromal Parkinson's disease in the general population and compared this digital biomarker with models based on genetics, lifestyle, blood biochemistry or prodromal symptoms data. Machine learning models trained using accelerometry data achieved better test performance in distinguishing both clinically diagnosed Parkinson's disease (n = 153) (area under precision recall curve (AUPRC) 0.14 ± 0.04) and prodromal Parkinson's disease (n = 113) up to 7 years pre-diagnosis (AUPRC 0.07 ± 0.03) from the general population (n = 33,009) compared with all other modalities tested (genetics: AUPRC = 0.01 ± 0.00, P = 2.2 × 10-3; lifestyle: AUPRC = 0.03 ± 0.04, P = 2.5 × 10-3; blood biochemistry: AUPRC = 0.01 ± 0.00, P = 4.1 × 10-3; prodromal signs: AUPRC = 0.01 ± 0.00, P = 3.6 × 10-3). Accelerometry is a potentially important, low-cost screening tool for determining people at risk of developing Parkinson's disease and identifying participants for clinical trials of neuroprotective treatments.
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Affiliation(s)
- Ann-Kathrin Schalkamp
- Division of Psychological Medicine and Clinical Neuroscience, UK Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Kathryn J Peall
- Division of Psychological Medicine and Clinical Neurosciences, Neuroscience and Mental Health Innovation Institute, Cardiff, UK
| | - Neil A Harrison
- Division of Psychological Medicine and Clinical Neurosciences, Neuroscience and Mental Health Innovation Institute, Cardiff, UK
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff, UK
| | - Cynthia Sandor
- Division of Psychological Medicine and Clinical Neuroscience, UK Dementia Research Institute, Cardiff University, Cardiff, UK.
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Pedersen K, Schlichter BR. Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review. Interact J Med Res 2023; 12:e40205. [PMID: 37471129 PMCID: PMC10401197 DOI: 10.2196/40205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 11/01/2022] [Accepted: 06/09/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND Lifestyle-related diseases caused by inadequate diet and physical activity cause premature death, loss of healthy life years, and increased health care costs. Randomized controlled trial (RCT) studies indicate that preventive digital health interventions (P-DHIs) can be effective in preventing these health problems, but the results of these studies are mixed. Adoption studies have identified multiple factors related to individuals and the context in which they live that complicate the transfer of positive results from RCT studies to practical use. Implementation studies have revealed barriers to the large-scale implementation of mobile health (mHealth) solutions in general. Consequently, there is no clear path to delivering predictable outcomes from P-DHIs and achieving effectiveness when scaling up interventions to reduce health problems in society. OBJECTIVE This research aimed to expand our understanding of how to increase the outcome predictability of P-DHIs by focusing on physical activity and diet behaviors and amplify our understanding of how to improve effectiveness in large-scale implementations. METHODS The research objective was pursued through a multidisciplinary scoping review. This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) as a guide. A comprehensive search of Web of Science and PubMed limited to English-language journal articles published before January 2022 was conducted. Google Scholar was used for hand searches. Information systems theory was used to identify key constructs influencing outcomes of IT in general. Public health and mHealth literature were used to identify factors influencing the adoption of, outcomes from, and implementation of P-DHIs. Finally, the P-DHI investment model was developed based on information systems constructs and factors from the public health and mHealth literature. RESULTS In total, 203 articles met the eligibility criteria. The included studies used a variety of methodologies, including literature reviews, interviews, surveys, and RCT studies. The P-DHI investment model suggests which constructs and related factors should be emphasized to increase the predictability of P-DHI outcomes and improve the effectiveness of large-scale implementations. CONCLUSIONS The research suggests that outcome predictability could be improved by including descriptions of the constructs and factors in the P-DHI investment model when reporting from empirical studies. Doing so would increase our understanding of when and why P-DHIs succeed or fail. The effectiveness of large-scale implementations may be improved by using the P-DHI investment model to evaluate potential difficulties and possibilities in implementing P-DHIs to create better environments for their use before investing in them and when designing and implementing them. The cost-effectiveness of large-scale implementations is unknown; implementations are far more complicated than just downloading and using apps, and there is uncertainty accompanying implementations given the lack of coordinated control over the constructs and factors that influence the outcome.
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Affiliation(s)
- Keld Pedersen
- Information Systems, Department of Management, Aarhus University, Aarhus C, Denmark
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Petek BJ, Al-Alusi MA, Moulson N, Grant AJ, Besson C, Guseh JS, Wasfy MM, Gremeaux V, Churchill TW, Baggish AL. Consumer Wearable Health and Fitness Technology in Cardiovascular Medicine: JACC State-of-the-Art Review. J Am Coll Cardiol 2023; 82:245-264. [PMID: 37438010 PMCID: PMC10662962 DOI: 10.1016/j.jacc.2023.04.054] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/26/2023] [Accepted: 04/28/2023] [Indexed: 07/14/2023]
Abstract
The use of consumer wearable devices (CWDs) to track health and fitness has rapidly expanded over recent years because of advances in technology. The general population now has the capability to continuously track vital signs, exercise output, and advanced health metrics. Although understanding of basic health metrics may be intuitive (eg, peak heart rate), more complex metrics are derived from proprietary algorithms, differ among device manufacturers, and may not historically be common in clinical practice (eg, peak V˙O2, exercise recovery scores). With the massive expansion of data collected at an individual patient level, careful interpretation is imperative. In this review, we critically analyze common health metrics provided by CWDs, describe common pitfalls in CWD interpretation, provide recommendations for the interpretation of abnormal results, present the utility of CWDs in exercise prescription, examine health disparities and inequities in CWD use and development, and present future directions for research and development.
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Affiliation(s)
- Bradley J Petek
- Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA; Cardiovascular Performance Program, Massachusetts General Hospital, Boston, Massachusetts, USA; Knight Cardiovascular Institute, Oregon Health and Science University, Portland, Oregon, USA
| | - Mostafa A Al-Alusi
- Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Nathaniel Moulson
- Division of Cardiology and Sports Cardiology BC, University of British Columbia, Vancouver, British Columbia, Canada
| | - Aubrey J Grant
- Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA; Cardiovascular Performance Program, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Cyril Besson
- Swiss Olympic Medical Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland; Institute for Sport Science, University of Lausanne (ISSUL), Lausanne, Switzerland
| | - J Sawalla Guseh
- Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA; Cardiovascular Performance Program, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Meagan M Wasfy
- Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA; Cardiovascular Performance Program, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Vincent Gremeaux
- Swiss Olympic Medical Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland; Institute for Sport Science, University of Lausanne (ISSUL), Lausanne, Switzerland
| | - Timothy W Churchill
- Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA; Cardiovascular Performance Program, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Aaron L Baggish
- Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA; Cardiovascular Performance Program, Massachusetts General Hospital, Boston, Massachusetts, USA; Swiss Olympic Medical Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland; Institute for Sport Science, University of Lausanne (ISSUL), Lausanne, Switzerland.
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Scheid JL, Reed JL, West SL. Commentary: Is Wearable Fitness Technology a Medically Approved Device? Yes and No. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6230. [PMID: 37444078 PMCID: PMC10341580 DOI: 10.3390/ijerph20136230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 05/08/2023] [Accepted: 06/22/2023] [Indexed: 07/15/2023]
Abstract
Wearable technologies, i.e., activity trackers and fitness watches, are extremely popular and have been increasingly integrated into medical research and clinical practice. To assist in optimizing health, wellness, or medical care, these devices require collaboration between researchers, healthcare providers, and wearable technology companies in order to clarify their clinical capabilities and educate consumers on the utilities and limitations of the wide-ranging wearable devices. Interestingly, activity trackers and fitness watches often track both health/wellness and medical information within the same device. In this commentary, we will focus our discussions regarding wearable technology on (1) defining and explaining the technical differences between tracking health, wellness, and medical information; (2) providing examples of health and wellness compared to medical tracking; (3) describing the potential medical benefits of wearable technology and its applications in clinical populations; and (4) elucidating the potential risks of wearable technology. We conclude that while wearable devices are powerful and informative tools, further research is needed to improve its clinical applications.
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Affiliation(s)
- Jennifer L. Scheid
- Department of Physical Therapy, Daemen University, Amherst, NY 14226, USA
| | - Jennifer L. Reed
- Exercise Physiology and Cardiovascular Health Lab, Division of Cardiac Prevention and Rehabilitation, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON K1Y 4W7, Canada
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON K1Y 4W7, Canada
| | - Sarah L. West
- Department of Kinesiology, Trent University, Peterborough, ON K9L 0G2, Canada
- Department of Biology, Trent University, Peterborough, ON K9L 0G2, Canada
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