Utilization of wearable devices in pediatric oncology: A Scoping Review

Utilization of wearable devices in pediatric oncology: A Scoping Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Utilization of wearable devices in pediatric oncology: A Scoping Review Lane Collier, Sarah Grimshaw, Julian Stolper, Elyse Passmore, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6517066/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Jul, 2025 Read the published version in npj Digital Medicine → Version 1 posted 9 You are reading this latest preprint version Abstract This review summarizes the current literature on the use of wearable devices for collecting physiological data in pediatric oncology. Searches were conducted in MEDLINE, PubMed and Embase, focusing on pediatric patients (0–25 years) with a cancer diagnosis, and utilizing a wearable device during and/or after treatment. Of the 77 articles that met the inclusion criteria, 61 studies primarily used wearable devices as a tool to monitor physiological changes in an interventional or observational setting. Only 16 studies integrated wearable devices as an active component of the intervention. The most reported wearable device brands were ActiGraph (19 studies, 24.7%), FitBit (14 studies, 18.2%), Ambulatory Monitoring Inc. (11 studies, 14.3%) and Philips Respironics (10 studies, 13%). This scoping review offers valuable insights into the current use of wearable devices in pediatric oncology but also reveals notable gaps in the literature, particularly when compared to the body of research in adult oncology. Biological sciences/Cancer Health sciences/Health care Figures Figure 1 Introduction Wearable devices have rapidly diffused into consumer markets over the last decade, offering a unique opportunity to engage in managing health issues. A wearable device is a portable, non-invasive, body-adhered electronic tool designed to collect, monitor and transmit data related to physiological or behavioral parameters. These devices can monitor a wide range of physiological and activity metrics, including but not limited to, electrocardiograms (ECGs), heart rate, respiratory rate, blood oxygen saturation, and physical activity levels. Due to the capacity for real-time, continuous monitoring of patients, and the possibility of timely intervention to improve health outcomes advancements in wearable technology have generated considerable interest within the healthcare system. In adult oncology, wearable devices have gained significant traction when used to attain data for prognostication, and rehabilitation planning ( 1 ) – which is unsurprising given physical activity is the most readily available and recorded wearable data ( 2 ). A review of wearable devices in adult oncology identified 199 studies which utilized devices for oncology prognostication, treatment monitoring or rehabilitation ( 3 ). However, implementation in clinical application and early detection using continuously monitored data (e.g. blood oxygen saturation, ECGs) is limited. The Apple Heart Study, is the largest wearable device research project to date, led by Apple and Standford, to assess the utility of these data to identify early interventions. Over 400,000 participants across the United States of America were closely monitored for irregular heart rhythms (specifically atrial fibrillation), using the Apple Watch in built optical heart rate sensor ( 4 ). This groundbreaking clinical trial found that the wearable device could not only be used to identify irregular heart rhythms but also distinguished episodes of atrial fibrillation in adult participants ( 4 ). This technology is now readily available to the public, allowing individuals to continuously monitor their heart rhythm in real-time and share this information with the appropriate health professionals. In contrast, the use of wearable devices in pediatrics is limited with most wearable studies using activity trackers only. The gap, and potential for intervention with wearable devices, remains for children with chronic illnesses. Wearable devices are an opportunity for improving the long-term outcomes of children with cancer and has a number of potential clinical applications. Children with cancer experience in the first 12 weeks of treatment (on average) 2.5 adverse drug reactions. The most common are nausea, fatigue, vomiting and myelosuppression requiring blood product transfusions ( 5 ). Continuous monitoring of physiological data could allow the early identification of adverse drug reactions and guide earlier intervention. The aim of this scoping review is to understand how wearable devices are being utilized in pediatric oncology and the types of physiological data being collected. Furthermore, we aim to report on any potential benefits or inefficacies of the wearable devices. Results The search strategy (see methods) identified 4,860 records. After duplicates were removed 3,328 articles underwent title and abstract screening by two independent reviewers. Articles that did not meet the inclusion criteria were removed. Secondary selection involved the review of 239 full texts to establish article relevance. The main reasons for article exclusion during the full text review was due to the wearable device not collecting physiological and/or activity data, or the article was a conference abstract. Ultimately, 77 articles were in included in this scoping review (6–82) (Fig. 1). Many of the studies were conducted in the United States (USA) (33) or Europe (31), with 6 studies conducted in Australia, 3 in Canada, 2 in Türkiye, 1 in Japan and 1 in Taiwan. As shown in Table 1, 79.2% of the studies utilized the wearable device as a data collection tool in an observational study or to measure physiological and/or activity data following an intervention. Only 20.8% of the studies utilized the wearable device as part of the intervention itself. Nearly half of the studies (49.3%) were conducted while the patient was at home, 22.1% of the studies were conducted while the patient was in hospital, and 28.6% were conducted both in and out of a clinical setting. Sample sizes ranged from 2 to 1,378 participants (median = 37 participants). Table 1 Characteristics of included studies. Characteristic Subcategory Percentage of Studies Range Median Wearable device use Data collection tool 79.2% Intervention 20.8% Study setting Outpatient 49.3% Inpatient 22.1% Mixed 28.6% Sample size 2–1,378 37 While gender distribution varied across the 77 studies, females comprised of 50.5% of the overall participant population. 13 studies (16.9%) reported exclusively on patients with acute lymphoblastic leukemia (ALL), 9 studies (11.7%) reported on patients with central nervous system (CNS) tumors and 2 studies (2.6%) reported on patients with bone tumors. 52 studies (67.5%) reported on patients with any cancer diagnosis and 1 study (1.3%) did not state the exact cancer diagnosis of participants. As shown in Table 2, over half (55.8%) of the studies reported on cancer patients currently receiving treatment, 36.4% reported on patients who have completed treatment, and 7.8% of studies included a mixed cohort of patients on and off treatment. A full breakdown of study characteristics is available in Supplementary Material 1. Table 2 Participant Demographics Demographics Subcategory Number of Studies (%) Cancer Diagnosis Any 52 (67.5%) ALL 13 (16.9%) CNS Tumors 9 (11.7%) Bone Tumors 2 (2.6%) Unknown 1 (1.3%) Stage of Treatment On Treatment 43 (55.8%) Off Treatment 28 (36.4%) Both 6 (7.8%) The most reported brands of wearable devices were ActiGraph (19 studies, 24.7%), FitBit (14 studies, 18.2%), Ambulatory Monitoring Inc. (11 studies, 14.3%) and Philips Respironics (10 studies, 13%). Two studies connected one wearable device to another, to collect physiological information which would in turn influence the second device (83, 84). Table 3 lists all wearable device brands utilized across the 77 studies. Table 3 Wearable Device Brands Brand Number of Studies (%) ActiGraph 19 (24.7%) Fitbit 14 (18.2%) Ambulatory Monitoring, Inc. 11 (14.3%) Philips Respironics 10 (13%) Biofourmis 3 (3.9%) Oculus/Meta 3 (3.9%) Activinsights 2 (2.6%) Garmin 2 (2.6%) Movisens 2 (2.6%) Orthocare Innovations 2 (2.6%) Axivity 1 (1.3%) BlueSpark Technologies 1 (1.3%) BTL 1 (1.3%) greenTEG 1 (1.3%) Modus Health 1 (1.3%) SWA BodyMedia 1 (1.3%) Unspecified 6 (7.8%) Over half of the studies (42 studies, 55%) used wearable devices that were worn on the wrist/arm, with 18 studies (23.4%) providing participants with hip-worn devices. The remaining 17 studies used devices placed on the patient’s skin, clothes, chest or head. Most of the wearable devices utilized physical activity, step count and sleep detection capabilities (Table 4). In addition, only 11 (14.3%) studies utilized more advanced wearable device capabilities such as respiratory rate, blood oxygen, ECG, heart rhythm and eye movement. Table 4 Wearable device functionality. Functionality Number of Study Devices (%) Physical Activity 44 (57.1%) Steps 33 (42.9%) Sleep 29 (37.7%) Heart Rate 6 (7.8%) Temperature 6 (7.8%) Respiratory Rate 5 (6.5%) Blood Oxygen 3 (3.9%) ECG 1 (1.3%) Heart Rhythm 1 (1.3%) Eye Movement 1 (1.3%) Angular Velocity of the arm 1 (1.3%) The duration of time participants were asked to wear the wearable device ranged from 5 minutes to 1 year, however, the majority of studies utilized the wearable devices for less than 1 month. Only twenty-five studies reported on the wear time adherence, with studies reporting high adherence at the start of the study, but adherence decline over time, particularly for longer studies. Of the studies that reported an average wear time, the overall average was 12.35 hours/day. With an overall average wear duration of 5.76 days/week based on studies that reported this data. 20 (26%) studies reported patients had technical difficulties with the wearable devices during the study, with the most common problem being data syncing and/or connectivity issues. Four studies reported adverse effects as a direct result of the wearable device, with skin irritation being the most common. A full breakdown of wearable devices and reported benefits and inefficacies is available in Supplementary Material 2. Discussion The current scoping review summarizes the literature surrounding the use of wearable devices in pediatric oncology, the types of data collected, and the benefits and limitations of the technology. We have identified an appetite for using wearable devices within pediatric oncology, however with only 77 studies identified, it has highlighted a clear gap in the literature. In contrast, systematic reviews in adult oncology have identified 199 studies. Our analysis reveals that the predominant wearable device used in pediatric oncology is the ActiGraph (25% of studies). The ActiGraph is a wrist-worn device used to monitor and record physical activity or sleep behavior over time, with a long-standing presence in the wearable device market. ActiGraph is also the predominant device used in adult oncology, used in around 36% of studies ( 3 ). However, within adult oncology there is a wider variety of wearable device brands utilized when compared to pediatric oncology. In addition, given the size of the wearable device market, and it’s expected revenue of USD 138 billion in 2025 ( 85 ), commercial grade devices will become more accessible for oncology research. However, only 19 (25%) studies utilized a commercially available wearable device (e.g. FitBit, Oculus/Meta and Garmin). Of the types of wearable devices used, only Phillips Respironics devices have been validated and approved for use in pediatrics as a medical device. Other brands are research grade wearable devices. Validation of wearable device data in pediatrics is technically challenging because of the changes in physiology over the age span from neonates, through infancy, early and late childhood and adolescence. This poses a particular challenge for wearable devices where the desire is for timely intervention in given clinical states where ‘normal values’ change substantially in the first 2 decades of life. The best example of this is heart rate, starting at a median rate of 140 (beats per minute) BPM in neonates, before gradually decreasing during infancy (median 110BPM), early and late childhood (median 100BPM and 90BPM) and adolescence (median 70BPM) ( 86 ). However, in the context of short-term studies, baseline data can be established prior to treatment or intervention, allowing for individualized comparisons without the need to monitor across the entire pediatric age range. Within pediatric oncology, more research is required in the validation and feasibility of using commercially available products that are readily accessible on the consumer market. Testing of these products within the confines of robust and blinded clinical studies is needed to support the further implementation of wearable devices in this cohort. Whilst 77 studies used wearable devices for data collection, few monitored emerging functionalities such as heart rhythm monitoring, ECGs, respiratory rate, temperature and blood oxygen. Only 11 studies (14%) utilized these newer functionalities. Moreover, very few studies (21%) looked to implement the wearable device as an active part of the intervention ( 83 , 84 , 87 – 95 ). Of these, 7 studies (9%) utilized the wearable device for real-time data monitoring, with 2 studies (3%) using this real-time data to influence another wearable device in a bio-feedback loop ( 83 , 84 ). Despite, the paucity of studies using wearable devices for active intervention, those with lived experience are embracing the technology. One retrospective study analyzed electronic medical records to identify how many referrals to a pediatric arrythmia clinic were prompted by identification of abnormal heart rhythms using the Apple Watch device. Interestingly, in 71% of cases (n = 145) the Apple Watch electrocardiogram findings prompted the cardiology team to pursue further workup ( 96 ). In addition, health organizations across the United States of America have started to integrate wearable device data directly into patient electronic medical records to utilize real-time data to assist with patient care ( 97 ). These studies show the opportunities for early intervention that are consumer led rather than investigator-initiated trial lead. A total of 21 studies included in this scoping review assessed feasibility ( 88 , 90 , 92 , 93 , 98 – 114 ), with reported barriers to implementation including well-established issues in patient compliance, technical issues resulting in data failure, and the clinical validation of the device ( 115 , 116 ). However, it is important to note that compliance in pediatrics is dependent on the parent/guardian and patient. No studies in our scoping review reported on parental compliance of enforcing or facilitating wearable device wear and this remains a research gap. Another factor when considering a wearable device in pediatric oncology is the placement of the device and compliance with wearing it appropriately. There is a lower acceptability and compliance in this cohort for hip worn devices, especially with younger children ( 117 – 119 ). In this context, three studies reported on the lower compliance in younger children when using hip worn devices but didn’t specify how this differed from older participants. The reported information in a study by Hooke et al. was that the device on the hip make them feel “different”, whilst Wu et al. reported two participants withdrawing from the study due to discomfort of wearing the hip-worn device. Technical issues were a common barrier to wearable use in children. 26% of studies reported connectivity and data syncing problems that impacted the quality and/or quantity of data available to researchers. None of these studies reported on whether these issues were overcome prior to the conclusion of the study. Technical issues reported in the broader literature with respect to wearable technology include dropped connections, signal interference, pairing problems, low battery impacting connectivity, incompatible devices, environmental factors and software glitches ( 120 , 121 ). In assessing wearable devices in sensitive setting such as pediatric oncology, ease of use and careful study design to avoid these common technical issues is essential. Private healthcare providers with existing medical devices, such as Kaiser Permanente or Ochsner, have addressed these concerns by implementing on-site technology assistance, similar to the Apple 'Genius Bar', to troubleshoot any technical issues that may arise ( 116 ). This could be a viable solution to overcoming technical issues but should be explored in both public and private sectors, allowing access for all patients. Although 28 studies (36%) reported on the acceptability and ease of use of the wearable devices ( 83 , 88 , 90 – 93 , 95 , 98 – 100 , 103 – 110 , 117 – 119 , 122 – 128 ), none of them reported on the thoughts, attitudes and barriers identified from consumers around using the wearable device to detect diseases or adverse reactions. This is likely due to minimal studies exploring the wearable device as an independent, stand-alone intervention. This highlights a current gap in the literature which indicates another potential barrier to implementation. As such, more research is needed to determine the thoughts and attitudes of consumers in regards to disease detection using wearable devices. This scoping review offers valuable insights into the current use of wearable devices in pediatric oncology but also reveals notable gaps in the literature, particularly when compared to the substantial body of research in adult oncology. Barriers to implementation is an ongoing challenge within this area of research and needs to be explored further in the context of wearable devices being an independent intervention. This scoping review also highlights the need for more validation studies using consumer grade devices, which may make way for more accessible and viable option for research use. Moreover, modern consumer grade devices provide a unique opportunity for a rich dataset of continuous and real time data from patients, without interrupting day to day life and burdening pediatric patients ( 90 , 91 , 107 , 110 ). Methods This review was conducted according to the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement – Scoping Review (PRISMA-ScR) and registered with the OSF Registry (osf.io/fsdb9). Eligibility Criteria Studies were eligible for inclusion if they involved: Pediatric, adolescent and young adults aged between 0–25 years AND Participants had a cancer diagnosis or had received a hematopoietic stem cell transplant AND Included wearable devices collecting physiological and/or activity data during and/or after cancer treatment AND Articles published in English, full text (or have a translated version available) from 2014 onwards. Studies were excluded if they involved: Pre-cancerous conditions Invasive devices (e.g.: insulin pumps) Books, chapters, conferences, editorials, comments, theses, protocols, systematic reviews and guidelines If articles included participants both inside and outside this age range, the results needed to be clearly defined for the pediatric, adolescent and young adult cohorts, or report a median or mean age within the 0–25-year range. Wearable technology included non-invasive devices e.g. virtual reality devices; and excluded current medical technologies such as hearing aids. Search Methods Literature searches were conducted in June 2024 in the following electronic databases; Medline, Embase and PubMed, and restricted to the last 10 years. The search strategy consisted of a combination of Medical exploded Subject Headings (MeSH) and various keywords to identify the literature. MeSH terms applied in the database searches included: “Wearable Technology”, “Neoplasms”, “Stem Cell Translation”, “Pediatrics”, “Adolescents”, “Young Adults”. These terms were combined in their associated cluster groups with all word variations included in the search. The search strategy was adjusted to focus on pediatric, adolescent and young adults, with search terms removed if they were not appropriate for this search. To refine the search, the “AND” operator was applied to combine all distinct concepts and yield relevant results. This approach was consistently applied across all electronic databases used for this review, with adjustments tailored to each database’s subject thesaurus. An additional search was completed on reference lists of similar review articles to ensure all relevant literature was captured. A detailed search has been provided in Appendix 1. Article Appraisal Results were uploaded to the systematic review software Catchii. Catchii is a new web-based systematic review platform that streamlines the development of systematic reviews with a user-friendly interface on both computers and mobile devices ( 129 ). Catchii removed all duplicate articles before two reviewers independently reviewed title and abstracts against the predefined inclusion and exclusion criteria. Any discrepancies were resolved through collaborative discussion, prior to reviewers proceeding to screen the full text articles. Following the two-stage screening process, a further collaborative discussion was undertaken to reach consensus. One reviewer extracted the data from Catchii into an excel spreadsheet consisting of: Study title Author(s) Year published Country of study Setting (home/hospital/both) Data collection tool or Intervention (Wearable Device) Study design Study primary aim(s) Stage of treatment (on/off/mixed) Number of participants Age of participants Gender of participants Diagnosis of participants Wearable device brand Wearable device name Where wearable device was worn during study Expected wear time of wearable device Minimum wear time of wearable device for valid data? How is wear time calculated? Sampling frequency of wearable device Physiological and/or activity data collected via the wearable device Benefits of the wearable device Inefficacies of the wearable device A second reviewer independently checked the entered data. Data Analysis The primary outcome of this scoping review was the use of wearable devices in pediatric oncology, with the secondary outcome being its benefits or limitations. Data were analyzed to identify common themes related to these outcomes. Declarations Data availability Data supporting this scoping review is included within the article and supporting materials. Acknowledgments The first author (L.C) was awarded an Australian Government Research Training Program Scholarship (RTP) to cover PhD tuition fees. She is also funded by Cancer Therapies, Stem Cell Medicine, Murdoch Children’s Research Institute. EP was supported by the Murdoch Children’s Research Institute by a Clinician Scientist Fellowship. GB is supported by an NHMRC Investigator Grant (1194497) and the Royal Children’s Hospital Foundation. RC is supported by the Kids Cancer Project, The Royal Children’s Hospital Foundation, Cancer Co Lab (previously Victorian Paediatric Cancer Consortium), Medical Research Future Fund grant number GHMG: 2024900 and holds a Murdoch Children’s Research Institute (MCRI) Clinician Scientist Tier 2 Fellowship and a VESKI FAIR Fellowship. RC, JS and DAE are supported by Novo Nordisk Foundation grant number NNF21CC0073729. JS is funded by Cancer Co Lab (previously the Victorian Paediatric Cancer Consortium). SG holds an honorary appointment with The University of Melbourne and holds a Cancer Council Fellowship. The Murdoch Children’s Research Institute is supported by the Victorian Government’s Operational Infrastructure Support Program and Australian Government NHMRC Independent Research Institute Infrastructure Support Scheme. Author Contributions L.C, S.G, R.C, D.E were involved in the conceptualization, study design and methodology of this scoping review. L.C was responsible for completing the literature searches on all databases. L.C and S.G were responsible for title/abstract screening, full text screening and data extraction. LC was responsible for data analysis and wrote the original draft manuscript. S.G, R.C, D.E, G.B, E.P and J.S revised and provided edits for the manuscript. 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The effect of a biofeedback-based virtual reality game on pain, fear and anxiety levels during port catheter needle insertion in pediatric oncology patients: A randomized controlled study. 2024. Setoyama AIMKK. Objective assessment of sleep status and its correlates in hospitalized children with cancer: Exploratory study. Pediatrics international : official journal of the Japan Pediatric Society. 2016. Steur LMHGMAVSEJWVENKAVdSIMDN. High prevalence of parent-reported sleep problems in pediatric patients with acute lymphoblastic leukemia after induction therapy. Pediatr Blood Cancer. 2020. Steur LMHKGJLVSEJWVENKAVdSIMD. Sleep-wake rhythm disruption is associated with cancer-related fatigue in pediatric acute lymphoblastic leukemia. Sleep. 2020. Steur LMHKGJLvSEJWvENKAvdSIMD. The impact of maintenance therapy on sleep-wake rhythms and cancer-related fatigue in pediatric acute lymphoblastic leukemia. Support Care Cancer. 2020. Swartz MCTAKWSJHTFMMKMKLSCJMKS. 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Wearable Health Technology and Electronic Health Record Integration: Scoping Review and Future Directions. JMIR Mhealth Uhealth. 2019;7(9):e12861. Rosen G, Harris AK, Liu M, Dreyfus J, Krueger J, Messinger YH. The effects of dexamethasone on sleep in young children with acute lymphoblastic leukemia. Sleep Med. 2015;16(4):503-9. Rogers VE, Zhu S, Ancoli-Israel S, Hinds PS. Impairment in circadian activity rhythms occurs during dexamethasone therapy in children with leukemia. Pediatr Blood Cancer. 2014;61(11):1986-91. Misawa M, Bajin IY, Zhang B, Daibert-Nido M, Tchao D, Garcia-Giler E, et al. A telerehabilitation program to improve visual perception in children and adolescents with hemianopia consecutive to a brain tumor: a single-arm feasibility and proof-of-concept trial. EClinicalMedicine. 2024;78:102955. Ha L, Wakefield CE, Diaz C, Mizrahi D, Signorelli C, Yacef K, et al. Patterns of physical activity and sedentary behavior in child and adolescent cancer survivors assessed using wrist accelerometry: A cluster analysis approach. Health Informatics J. 2023;29(4):14604582231212525. Grydeland M, Bratteteig M, Rueegg CS, Lie HC, Thorsen L, Larsen EH, et al. Physical Activity Among Adolescent Cancer Survivors: The PACCS Study. Pediatrics. 2023;152(3). Hooke MC, Salisbury DL, Mathiason MA, Kunin-Batson AS, Blommer A, Hutter J, et al. Symptoms, Physical Activity, and Biomarkers in Children at the End of Leukemia Maintenance Therapy. J Pediatr Hematol Oncol Nurs. 2023;40(6):386-99. Grimshaw SL, Taylor NF, Conyers R, Shields N. Promoting positive physical activity behaviours in children undergoing acute cancer treatment: feasibility of the CanMOVE intervention. Brazilian Journal of Physical Therapy. 2024;28(1):100577. Williamson Lewis R, Howell KE, Effinger KE, Meacham LR, Wasilewski-Masker K, Mertens A, et al. Feasibility of Fitbit Use in Adolescent Survivors of Pediatric Cancer: Who Consistently Uses It and for How Long? J Adolesc Young Adult Oncol. 2023;12(4):529-36. Hoag JA, Bingen K, Karst J, Palou A, Yan K, Zhang J. Playing With a Purpose: The Impact of Therapeutic Recreation During Hospitalization. J Pediatr Hematol Oncol Nurs. 2022;39(1):6-14. Götte M, Kesting SV, Gerss J, Rosenbaum D, Boos J. Feasibility and effects of a home-based intervention using activity trackers on achievement of individual goals, quality of life and motor performance in patients with paediatric cancer. BMJ Open Sport Exerc Med. 2018;4(1):e000322. Koenig C, Ammann RA, Schneider C, Wyss J, Roessler J, Brack E. Continuous timely monitoring of core temperature with two wearable devices in pediatric patients undergoing chemotherapy for cancer - a comparison study. Support Care Cancer. 2024;32(3):188. Ha L, Wakefield CE, Mizrahi D, Diaz C, Cohn RJ, Signorelli C, et al. A Digital Educational Intervention With Wearable Activity Trackers to Support Health Behaviors Among Childhood Cancer Survivors: Pilot Feasibility and Acceptability Study. JMIR Cancer. 2022;8(3):e38367. Koenig C, Ammann RA, Kuehni CE, Roessler J, Brack E. Continuous recording of vital signs with a wearable device in pediatric patients undergoing chemotherapy for cancer-an operational feasibility study. Support Care Cancer. 2021;29(9):5283-92. Rogers VE, Mowbray C, Zhu S, Liu L, Ancoli-Israel S, Barr EA, et al. Circadian activity rhythms and fatigue of adolescent cancer survivors and healthy controls: a pilot study. J Clin Sleep Med. 2020;16(7):1141-7. Daniel LC, Venella KL, Woodard K, Poliakova P, Gross JY, Bercovitz IN, et al. Can extending time between vital sign checks improve sleep in hematopoietic stem cell transplant patients? Testing feasibility, acceptability, and preliminary efficacy. Pediatr Blood Cancer. 2024;71(4):e30832. Withycombe JS, McFatrich M, Hinds PS, Bennett A, Lin L, Maurer SH, et al. Can Steps per Day Reflect Symptoms in Children and Adolescents Undergoing Cancer Treatment? Cancer Nurs. 2022;45(5):345-53. Braam KI, van Dijk-Lokkart EM, Kaspers GJL, Takken T, Huisman J, Bierings MB, et al. Cardiorespiratory fitness and physical activity in children with cancer. Support Care Cancer. 2016;24(5):2259-68. Canali S, Schiaffonati V, Aliverti A. Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness. PLOS Digit Health. 2022;1(10):e0000104. Smuck M, Odonkor CA, Wilt JK, Schmidt N, Swiernik MA. The emerging clinical role of wearables: factors for successful implementation in healthcare. npj Digital Medicine. 2021;4(1):45. Gaser D, Peters C, Götte M, Oberhoffer-Fritz R, Feuchtinger T, Schmid I, et al. Analysis of self-reported activities of daily living, motor performance and physical activity among children and adolescents with cancer: Baseline data from a randomised controlled trial assessed shortly after diagnosis of leukaemia or non-Hodgkin lymphoma. Eur J Cancer Care (Engl). 2022;31(2):e13559. Hooke MC, Hoelscher A, Tanner LR, Langevin M, Bronas UG, Maciej A, et al. Kids Are Moving: A Physical Activity Program for Children With Cancer. J Pediatr Oncol Nurs. 2019;36(6):379-89. Wu WW, Yu TH, Jou ST, Hung GY, Tang CC. Factors associated with walking performance among adolescents undergoing cancer treatment: A correlational study. J Child Health Care. 2023;27(4):574-86. Huhn S, Axt M, Gunga HC, Maggioni MA, Munga S, Obor D, et al. The Impact of Wearable Technologies in Health Research: Scoping Review. JMIR Mhealth Uhealth. 2022;10(1):e34384. Roos LG, Slavich GM. Wearable technologies for health research: Opportunities, limitations, and practical and conceptual considerations. Brain, Behavior, and Immunity. 2023;113:444-52. Müller C, Krauth KA, Gerß J, Rosenbaum D. Physical activity and health-related quality of life in pediatric cancer patients following a 4-week inpatient rehabilitation program. Support Care Cancer. 2016;24(9):3793-802. Rehorst-Kleinlugtenbelt LB, Bekkering WP, van der Torre P, van der Net J, Takken T. Physical activity level objectively measured by accelerometery in children undergoing cancer treatment at home and in a hospital setting: A pilot study. Pediatric Hematology Oncology Journal. 2019;4(4):82-8. Swartz MC, Teague AK, Wells SJ, Honey T, Fu M, Mahadeo KM, et al. Feasibility and Acceptability Findings of an Energy Balance Data Repository of Children, Adolescents, and Young Adults with Cancer. J Clin Med. 2020;9(9). Dalla Santa E, Barton F, Downie P, De Graves S, Nicklen P, Farlie MK. Feasibility of a prospective physiotherapy model of care during the intense treatment phase of childhood cancer (FITChild): A mixed methods design. Pediatr Blood Cancer. 2023:e30488. van Hulst AM, van den Akker ELT, Verwaaijen EJ, Fiocco M, Rensen N, van Litsenburg RRL, et al. Hydrocortisone to reduce dexamethasone-induced neurobehavioral side-effects in children with acute lymphoblastic leukaemia-results of a double-blind, randomised controlled trial with cross-over design. Eur J Cancer. 2023;187:124-33. Long TM, Rath SR, Wallman KE, Howie EK, Straker LM, Bullock A, et al. Exercise training improves vascular function and secondary health measures in survivors of pediatric oncology related cerebral insult. PLoS One. 2018;13(8):e0201449. Zupanec S, Jones H, McRae L, Papaconstantinou E, Weston J, Stremler R. A Sleep Hygiene and Relaxation Intervention for Children With Acute Lymphoblastic Leukemia: A Pilot Randomized Controlled Trial. Cancer Nurs. 2017;40(6):488-96. Halman A, Oshlack A. Catchii: Empowering literature review screening in healthcare. Res Synth Methods. 2024;15(1):157-65. Appendix 1 Supplementary file Appendix 1 is not available with this version. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6517066","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":449380109,"identity":"10972fdb-b0b0-4d5d-aeaa-f99d5ac28958","order_by":0,"name":"Lane Collier","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYBACPigtw8cMJD8AMRsQS+DTwgalediAWhhnkKYFSDDzQHn4tbCfPfiAocaGh42d+dhn2xy7fD4G5oO3eRjsEhtwaeHJSzZgOJYGdBhb8uzcbcmWbQxsydY8DMm4tTDkmEkwNhwGauExZs7ddsCAjYHHTJqHgRm3Fv435j8gWvg/M1uCtfB/A2qpx61FIseMAWoLMzMjxBY2oJbDeLS8MZZIgPjFmLF3W7IBiGE5x+C4MS4t/Pw5hh8+1NjI8fMffszwc5udgXx788MbbyqqZXFpAYMEFB4oGTAY4FM/CkbBKBgFo4AQAACwYzyhsUxQHwAAAABJRU5ErkJggg==","orcid":"","institution":"Murdoch Children's Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Lane","middleName":"","lastName":"Collier","suffix":""},{"id":449380110,"identity":"083d799c-55f1-4b93-8fa4-3296ef60f358","order_by":1,"name":"Sarah Grimshaw","email":"","orcid":"","institution":"Murdoch Children's Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Grimshaw","suffix":""},{"id":449380111,"identity":"a8943a76-0e2a-4f40-9262-ba283b5f0704","order_by":2,"name":"Julian Stolper","email":"","orcid":"","institution":"Murdoch Children's Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Julian","middleName":"","lastName":"Stolper","suffix":""},{"id":449380112,"identity":"b3d7e077-189e-46f5-9535-4420b8cb48b4","order_by":3,"name":"Elyse Passmore","email":"","orcid":"","institution":"Murdoch Children's Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Elyse","middleName":"","lastName":"Passmore","suffix":""},{"id":449380113,"identity":"63a49bd9-56c4-418d-a47c-38636fbd286b","order_by":4,"name":"Gareth Ball","email":"","orcid":"","institution":"Murdoch Children's Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Gareth","middleName":"","lastName":"Ball","suffix":""},{"id":449380114,"identity":"27df48b8-5002-4501-9790-4b6e9588b968","order_by":5,"name":"David A. 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A wearable device is a portable, non-invasive, body-adhered electronic tool designed to collect, monitor and transmit data related to physiological or behavioral parameters. These devices can monitor a wide range of physiological and activity metrics, including but not limited to, electrocardiograms (ECGs), heart rate, respiratory rate, blood oxygen saturation, and physical activity levels. Due to the capacity for real-time, continuous monitoring of patients, and the possibility of timely intervention to improve health outcomes advancements in wearable technology have generated considerable interest within the healthcare system.\u003c/p\u003e \u003cp\u003eIn adult oncology, wearable devices have gained significant traction when used to attain data for prognostication, and rehabilitation planning (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \u0026ndash; which is unsurprising given physical activity is the most readily available and recorded wearable data (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). A review of wearable devices in adult oncology identified 199 studies which utilized devices for oncology prognostication, treatment monitoring or rehabilitation (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, implementation in clinical application and early detection using continuously monitored data (e.g. blood oxygen saturation, ECGs) is limited. The Apple Heart Study, is the largest wearable device research project to date, led by Apple and Standford, to assess the utility of these data to identify early interventions. Over 400,000 participants across the United States of America were closely monitored for irregular heart rhythms (specifically atrial fibrillation), using the Apple Watch in built optical heart rate sensor (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This groundbreaking clinical trial found that the wearable device could not only be used to identify irregular heart rhythms but also distinguished episodes of atrial fibrillation in adult participants (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This technology is now readily available to the public, allowing individuals to continuously monitor their heart rhythm in real-time and share this information with the appropriate health professionals.\u003c/p\u003e \u003cp\u003eIn contrast, the use of wearable devices in pediatrics is limited with most wearable studies using activity trackers only. The gap, and potential for intervention with wearable devices, remains for children with chronic illnesses. Wearable devices are an opportunity for improving the long-term outcomes of children with cancer and has a number of potential clinical applications. Children with cancer experience in the first 12 weeks of treatment (on average) 2.5 adverse drug reactions. The most common are nausea, fatigue, vomiting and myelosuppression requiring blood product transfusions (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Continuous monitoring of physiological data could allow the early identification of adverse drug reactions and guide earlier intervention.\u003c/p\u003e \u003cp\u003eThe aim of this scoping review is to understand how wearable devices are being utilized in pediatric oncology and the types of physiological data being collected. Furthermore, we aim to report on any potential benefits or inefficacies of the wearable devices.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe search strategy (see methods) identified 4,860 records. After duplicates were removed 3,328 articles underwent title and abstract screening by two independent reviewers. Articles that did not meet the inclusion criteria were removed. Secondary selection involved the review of 239 full texts to establish article relevance. The main reasons for article exclusion during the full text review was due to the wearable device not collecting physiological and/or activity data, or the article was a conference abstract. Ultimately, 77 articles were in included in this scoping review (6–82) (Fig. 1).\u003c/p\u003e\n\u003cp\u003eMany of the studies were conducted in the United States (USA) (33) or Europe (31), with 6 studies conducted in Australia, 3 in Canada, 2 in Türkiye, 1 in Japan and 1 in Taiwan. As shown in Table 1, 79.2% of the studies utilized the wearable device as a data collection tool in an observational study or to measure physiological and/or activity data following an intervention. Only 20.8% of the studies utilized the wearable device as part of the intervention itself. Nearly half of the studies (49.3%) were conducted while the patient was at home, 22.1% of the studies were conducted while the patient was in hospital, and 28.6% were conducted both in and out of a clinical setting. Sample sizes ranged from 2 to 1,378 participants (median = 37 participants).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eCharacteristics of included studies.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSubcategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage of Studies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eWearable device use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eData collection tool\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy setting\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2–1,378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eWhile gender distribution varied across the 77 studies, females comprised of 50.5% of the overall participant population. 13 studies (16.9%) reported exclusively on patients with acute lymphoblastic leukemia (ALL), 9 studies (11.7%) reported on patients with central nervous system (CNS) tumors and 2 studies (2.6%) reported on patients with bone tumors. 52 studies (67.5%) reported on patients with any cancer diagnosis and 1 study (1.3%) did not state the exact cancer diagnosis of participants. As shown in Table 2, over half (55.8%) of the studies reported on cancer patients currently receiving treatment, 36.4% reported on patients who have completed treatment, and 7.8% of studies included a mixed cohort of patients on and off treatment. A full breakdown of study characteristics is available in Supplementary Material 1.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eParticipant Demographics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDemographics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSubcategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of Studies (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer Diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAny\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52 (67.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCNS Tumors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (11.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBone Tumors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage of Treatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOn Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43 (55.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOff Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe most reported brands of wearable devices were ActiGraph (19 studies, 24.7%), FitBit (14 studies, 18.2%), Ambulatory Monitoring Inc. (11 studies, 14.3%) and Philips Respironics (10 studies, 13%). Two studies connected one wearable device to another, to collect physiological information which would in turn influence the second device (83, 84). Table 3 lists all wearable device brands utilized across the 77 studies.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eWearable Device Brands\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBrand\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of Studies (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActiGraph\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (24.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFitbit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmbulatory Monitoring, Inc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhilips Respironics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiofourmis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOculus/Meta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActivinsights\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGarmin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMovisens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOrthocare Innovations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAxivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlueSpark Technologies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBTL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egreenTEG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModus Health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSWA BodyMedia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnspecified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOver half of the studies (42 studies, 55%) used wearable devices that were worn on the wrist/arm, with 18 studies (23.4%) providing participants with hip-worn devices. The remaining 17 studies used devices placed on the patient’s skin, clothes, chest or head. Most of the wearable devices utilized physical activity, step count and sleep detection capabilities (Table 4). In addition, only 11 (14.3%) studies utilized more advanced wearable device capabilities such as respiratory rate, blood oxygen, ECG, heart rhythm and eye movement.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eWearable device functionality.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFunctionality\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of Study Devices (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical Activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSteps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29 (37.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTemperature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood Oxygen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eECG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart Rhythm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEye Movement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAngular Velocity of the arm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe duration of time participants were asked to wear the wearable device ranged from 5 minutes to 1 year, however, the majority of studies utilized the wearable devices for less than 1 month. Only twenty-five studies reported on the wear time adherence, with studies reporting high adherence at the start of the study, but adherence decline over time, particularly for longer studies. Of the studies that reported an average wear time, the overall average was 12.35 hours/day. With an overall average wear duration of 5.76 days/week based on studies that reported this data.\u003c/p\u003e\n\u003cp\u003e20 (26%) studies reported patients had technical difficulties with the wearable devices during the study, with the most common problem being data syncing and/or connectivity issues. Four studies reported adverse effects as a direct result of the wearable device, with skin irritation being the most common. A full breakdown of wearable devices and reported benefits and inefficacies is available in Supplementary Material 2.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current scoping review summarizes the literature surrounding the use of wearable devices in pediatric oncology, the types of data collected, and the benefits and limitations of the technology. We have identified an appetite for using wearable devices within pediatric oncology, however with only 77 studies identified, it has highlighted a clear gap in the literature. In contrast, systematic reviews in adult oncology have identified 199 studies.\u003c/p\u003e \u003cp\u003eOur analysis reveals that the predominant wearable device used in pediatric oncology is the ActiGraph (25% of studies). The ActiGraph is a wrist-worn device used to monitor and record physical activity or sleep behavior over time, with a long-standing presence in the wearable device market. ActiGraph is also the predominant device used in adult oncology, used in around 36% of studies (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, within adult oncology there is a wider variety of wearable device brands utilized when compared to pediatric oncology. In addition, given the size of the wearable device market, and it\u0026rsquo;s expected revenue of USD 138\u0026nbsp;billion in 2025 (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e), commercial grade devices will become more accessible for oncology research. However, only 19 (25%) studies utilized a commercially available wearable device (e.g. FitBit, Oculus/Meta and Garmin). Of the types of wearable devices used, only Phillips Respironics devices have been validated and approved for use in pediatrics as a medical device. Other brands are research grade wearable devices. Validation of wearable device data in pediatrics is technically challenging because of the changes in physiology over the age span from neonates, through infancy, early and late childhood and adolescence. This poses a particular challenge for wearable devices where the desire is for timely intervention in given clinical states where \u0026lsquo;normal values\u0026rsquo; change substantially in the first 2 decades of life. The best example of this is heart rate, starting at a median rate of 140 (beats per minute) BPM in neonates, before gradually decreasing during infancy (median 110BPM), early and late childhood (median 100BPM and 90BPM) and adolescence (median 70BPM) (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e). However, in the context of short-term studies, baseline data can be established prior to treatment or intervention, allowing for individualized comparisons without the need to monitor across the entire pediatric age range.\u003c/p\u003e \u003cp\u003eWithin pediatric oncology, more research is required in the validation and feasibility of using commercially available products that are readily accessible on the consumer market. Testing of these products within the confines of robust and blinded clinical studies is needed to support the further implementation of wearable devices in this cohort.\u003c/p\u003e \u003cp\u003eWhilst 77 studies used wearable devices for data collection, few monitored emerging functionalities such as heart rhythm monitoring, ECGs, respiratory rate, temperature and blood oxygen. Only 11 studies (14%) utilized these newer functionalities. Moreover, very few studies (21%) looked to implement the wearable device as an active part of the intervention (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan additionalcitationids=\"CR88 CR89 CR90 CR91 CR92 CR93 CR94\" citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e). Of these, 7 studies (9%) utilized the wearable device for real-time data monitoring, with 2 studies (3%) using this real-time data to influence another wearable device in a bio-feedback loop (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e). Despite, the paucity of studies using wearable devices for active intervention, those with lived experience are embracing the technology. One retrospective study analyzed electronic medical records to identify how many referrals to a pediatric arrythmia clinic were prompted by identification of abnormal heart rhythms using the Apple Watch device. Interestingly, in 71% of cases (n\u0026thinsp;=\u0026thinsp;145) the Apple Watch electrocardiogram findings prompted the cardiology team to pursue further workup (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e). In addition, health organizations across the United States of America have started to integrate wearable device data directly into patient electronic medical records to utilize real-time data to assist with patient care (\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e). These studies show the opportunities for early intervention that are consumer led rather than investigator-initiated trial lead.\u003c/p\u003e \u003cp\u003eA total of 21 studies included in this scoping review assessed feasibility (\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan additionalcitationids=\"CR99 CR100 CR101 CR102 CR103 CR104 CR105 CR106 CR107 CR108 CR109 CR110 CR111 CR112 CR113\" citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e), with reported barriers to implementation including well-established issues in patient compliance, technical issues resulting in data failure, and the clinical validation of the device (\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e). However, it is important to note that compliance in pediatrics is dependent on the parent/guardian and patient. No studies in our scoping review reported on parental compliance of enforcing or facilitating wearable device wear and this remains a research gap. Another factor when considering a wearable device in pediatric oncology is the placement of the device and compliance with wearing it appropriately. There is a lower acceptability and compliance in this cohort for hip worn devices, especially with younger children (\u003cspan additionalcitationids=\"CR118\" citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e). In this context, three studies reported on the lower compliance in younger children when using hip worn devices but didn\u0026rsquo;t specify how this differed from older participants. The reported information in a study by Hooke et al. was that the device on the hip make them feel \u0026ldquo;different\u0026rdquo;, whilst Wu et al. reported two participants withdrawing from the study due to discomfort of wearing the hip-worn device.\u003c/p\u003e \u003cp\u003eTechnical issues were a common barrier to wearable use in children. 26% of studies reported connectivity and data syncing problems that impacted the quality and/or quantity of data available to researchers. None of these studies reported on whether these issues were overcome prior to the conclusion of the study. Technical issues reported in the broader literature with respect to wearable technology include dropped connections, signal interference, pairing problems, low battery impacting connectivity, incompatible devices, environmental factors and software glitches (\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e, \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e). In assessing wearable devices in sensitive setting such as pediatric oncology, ease of use and careful study design to avoid these common technical issues is essential. Private healthcare providers with existing medical devices, such as Kaiser Permanente or Ochsner, have addressed these concerns by implementing on-site technology assistance, similar to the Apple 'Genius Bar', to troubleshoot any technical issues that may arise (\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e). This could be a viable solution to overcoming technical issues but should be explored in both public and private sectors, allowing access for all patients.\u003c/p\u003e \u003cp\u003eAlthough 28 studies (36%) reported on the acceptability and ease of use of the wearable devices (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan additionalcitationids=\"CR91 CR92\" citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan additionalcitationids=\"CR99\" citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e, \u003cspan additionalcitationids=\"CR104 CR105 CR106 CR107 CR108 CR109\" citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e, \u003cspan additionalcitationids=\"CR118\" citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan additionalcitationids=\"CR123 CR124 CR125 CR126 CR127\" citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e), none of them reported on the thoughts, attitudes and barriers identified from consumers around using the wearable device to detect diseases or adverse reactions. This is likely due to minimal studies exploring the wearable device as an independent, stand-alone intervention. This highlights a current gap in the literature which indicates another potential barrier to implementation. As such, more research is needed to determine the thoughts and attitudes of consumers in regards to disease detection using wearable devices.\u003c/p\u003e \u003cp\u003eThis scoping review offers valuable insights into the current use of wearable devices in pediatric oncology but also reveals notable gaps in the literature, particularly when compared to the substantial body of research in adult oncology. Barriers to implementation is an ongoing challenge within this area of research and needs to be explored further in the context of wearable devices being an independent intervention. This scoping review also highlights the need for more validation studies using consumer grade devices, which may make way for more accessible and viable option for research use. Moreover, modern consumer grade devices provide a unique opportunity for a rich dataset of continuous and real time data from patients, without interrupting day to day life and burdening pediatric patients (\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e This review was conducted according to the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement \u0026ndash; Scoping Review (PRISMA-ScR) and registered with the OSF Registry (osf.io/fsdb9).\u003c/p\u003e\n\u003ch3\u003eEligibility Criteria\u003c/h3\u003e\n\u003cp\u003eStudies were eligible for inclusion if they involved:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePediatric, adolescent and young adults aged between 0\u0026ndash;25 years AND\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eParticipants had a cancer diagnosis or had received a hematopoietic stem cell transplant AND\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncluded wearable devices collecting physiological and/or activity data during and/or after cancer treatment AND\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eArticles published in English, full text (or have a translated version available) from 2014 onwards.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eStudies were excluded if they involved:\u003c/p\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ePre-cancerous conditions\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eInvasive devices (e.g.: insulin pumps)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eBooks, chapters, conferences, editorials, comments, theses, protocols, systematic reviews and guidelines\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e \u003cp\u003eIf articles included participants both inside and outside this age range, the results needed to be clearly defined for the pediatric, adolescent and young adult cohorts, or report a median or mean age within the 0\u0026ndash;25-year range.\u003c/p\u003e \u003cp\u003eWearable technology included non-invasive devices e.g. virtual reality devices; and excluded current medical technologies such as hearing aids.\u003c/p\u003e\n\u003ch3\u003eSearch Methods\u003c/h3\u003e\n\u003cp\u003eLiterature searches were conducted in June 2024 in the following electronic databases; Medline, Embase and PubMed, and restricted to the last 10 years.\u003c/p\u003e \u003cp\u003eThe search strategy consisted of a combination of Medical exploded Subject Headings (MeSH) and various keywords to identify the literature. MeSH terms applied in the database searches included: \u0026ldquo;Wearable Technology\u0026rdquo;, \u0026ldquo;Neoplasms\u0026rdquo;, \u0026ldquo;Stem Cell Translation\u0026rdquo;, \u0026ldquo;Pediatrics\u0026rdquo;, \u0026ldquo;Adolescents\u0026rdquo;, \u0026ldquo;Young Adults\u0026rdquo;. These terms were combined in their associated cluster groups with all word variations included in the search. The search strategy was adjusted to focus on pediatric, adolescent and young adults, with search terms removed if they were not appropriate for this search.\u003c/p\u003e \u003cp\u003eTo refine the search, the \u0026ldquo;AND\u0026rdquo; operator was applied to combine all distinct concepts and yield relevant results. This approach was consistently applied across all electronic databases used for this review, with adjustments tailored to each database\u0026rsquo;s subject thesaurus. An additional search was completed on reference lists of similar review articles to ensure all relevant literature was captured. A detailed search has been provided in Appendix 1.\u003c/p\u003e\n\u003ch3\u003eArticle Appraisal\u003c/h3\u003e\n\u003cp\u003eResults were uploaded to the systematic review software Catchii. Catchii is a new web-based systematic review platform that streamlines the development of systematic reviews with a user-friendly interface on both computers and mobile devices (\u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e129\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCatchii removed all duplicate articles before two reviewers independently reviewed title and abstracts against the predefined inclusion and exclusion criteria. Any discrepancies were resolved through collaborative discussion, prior to reviewers proceeding to screen the full text articles. Following the two-stage screening process, a further collaborative discussion was undertaken to reach consensus. One reviewer extracted the data from Catchii into an excel spreadsheet consisting of:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eStudy title\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAuthor(s)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eYear published\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCountry of study\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSetting (home/hospital/both)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eData collection tool or Intervention (Wearable Device)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStudy design\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStudy primary aim(s)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStage of treatment (on/off/mixed)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eNumber of participants\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAge of participants\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eGender of participants\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDiagnosis of participants\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWearable device brand\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWearable device name\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWhere wearable device was worn during study\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eExpected wear time of wearable device\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMinimum wear time of wearable device for valid data?\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHow is wear time calculated?\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSampling frequency of wearable device\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePhysiological and/or activity data collected via the wearable device\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBenefits of the wearable device\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInefficacies of the wearable device\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eA second reviewer independently checked the entered data.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe primary outcome of this scoping review was the use of wearable devices in pediatric oncology, with the secondary outcome being its benefits or limitations. Data were analyzed to identify common themes related to these outcomes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eData supporting this scoping review is included within the article and supporting materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe first author (L.C) was awarded an Australian Government Research Training Program Scholarship (RTP) to cover PhD tuition fees. She is also funded by Cancer Therapies, Stem Cell Medicine, Murdoch Children\u0026rsquo;s Research Institute. EP was supported by the Murdoch Children\u0026rsquo;s Research Institute by a Clinician Scientist Fellowship. GB is supported by an NHMRC Investigator Grant (1194497) and the Royal Children\u0026rsquo;s Hospital Foundation. RC is supported by the Kids Cancer Project, The Royal Children\u0026rsquo;s Hospital Foundation, Cancer Co Lab (previously Victorian Paediatric Cancer Consortium), Medical Research Future Fund grant number GHMG: 2024900 and holds a Murdoch Children\u0026rsquo;s Research Institute (MCRI) Clinician Scientist Tier 2 Fellowship and a VESKI FAIR Fellowship. RC, JS and DAE are supported by Novo Nordisk Foundation grant number NNF21CC0073729. JS is funded by Cancer Co Lab (previously the Victorian Paediatric Cancer Consortium). SG holds an honorary appointment with The University of Melbourne and holds a Cancer Council Fellowship. The Murdoch Children\u0026rsquo;s Research Institute is supported by the Victorian Government\u0026rsquo;s Operational Infrastructure Support Program and Australian Government NHMRC Independent Research Institute Infrastructure Support Scheme.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eL.C, S.G, R.C, D.E were involved in the conceptualization, study design and methodology of this scoping review. L.C was responsible for completing the literature searches on all databases. L.C and S.G were responsible for title/abstract screening, full text screening and data extraction. LC was responsible for data analysis and wrote the original draft manuscript. S.G, R.C, D.E, G.B, E.P and J.S revised and provided edits for the manuscript. R.C, D.E, G.B and E.P provided supervision for the project. All Authors have read and approved the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChow R, Drkulec H, Im JHB, Tsai J, Nafees A, Kumar S, et al. The Use of Wearable Devices in Oncology Patients: A Systematic Review. The Oncologist. 2023;29(4):e419-e30.\u003c/li\u003e\n\u003cli\u003eBeauchamp UL, Pappot H, Holl\u0026auml;nder-Mieritz C. The Use of Wearables in Clinical Trials During Cancer Treatment: Systematic Review. JMIR Mhealth Uhealth. 2020;8(11):e22006.\u003c/li\u003e\n\u003cli\u003eChow R, Drkulec H, Im JHB, Tsai J, Nafees A, Kumar S, et al. The Use of Wearable Devices in Oncology Patients: A Systematic Review. Oncologist. 2024;29(4):e419-e30.\u003c/li\u003e\n\u003cli\u003eApple. Using Apple Watch for arrhythmia detection. 2020 December 2020.\u003c/li\u003e\n\u003cli\u003eConyers R, Halman A, Moore C, Stenta T, Felmingham B, Collier L, et al. Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children (MARVEL- PIC): protocol for a national randomised controlled trial of pharmacogenomics implementation. BMJ Open. 2024;14(5):e085115.\u003c/li\u003e\n\u003cli\u003eBraam KIvD-LEMKGJLTTHJBMBMJHMv. Cardiorespiratory fitness and physical activity in children with cancer. Support Care Cancer. 2016.\u003c/li\u003e\n\u003cli\u003eBratteteig MASARCSRETIKKSGM. Device-measured physical activity and cardiovascular disease risk in adolescent childhood cancer survivors. A physical activity in childhood cancer survivors (PACCS) study. Frontiers in pediatrics. 2022.\u003c/li\u003e\n\u003cli\u003eBratteteig MRCSRTGMTIKSCREASA. 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Exercise with nutrition education to improve quality of life of adolescent and young adult cancer survivors: A pilot study. 2021.\u003c/li\u003e\n\u003cli\u003eDevine KAVAL-RKMNBBCAXBO-SPMSF-AASO. Feasibility of FitSurvivor: A technology-enhanced group-based fitness intervention for adolescent and young adult survivors of childhood cancer. 2020.\u003c/li\u003e\n\u003cli\u003eFiuza-Luces CPJRS-MLS-SEQJVS-LAP-GHS-GFL-G. Exercise Intervention in Pediatric Patients with Solid Tumors: The Physical Activity in Pediatric Cancer Trial. 2017.\u003c/li\u003e\n\u003cli\u003eFuemmeler BFHESYDEKMCABJRPM\u0026Oslash;T. Mila Blooms: A Mobile Phone Application and Behavioral Intervention for Promoting Physical Activity and a Healthy Diet Among Adolescent Survivors of Childhood Cancer. Games for health journal. 2020.\u003c/li\u003e\n\u003cli\u003eGaser DPCGMO-FRFTSIvLIKS. 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The effect of an active video game intervention on physical activity, motor performance, and fatigue in children with cancer: a randomized controlled trial. Bmc Res Notes. 2019.\u003c/li\u003e\n\u003cli\u003eHoag JABKKJPAYKZJ. Playing With a Purpose: The Impact of Therapeutic Recreation During Hospitalization. Journal of pediatric hematology/oncology nursing. 2022.\u003c/li\u003e\n\u003cli\u003eHooke MCGLTLHNWJS. Use of a Fitness Tracker to Promote Physical Activity in Children With Acute Lymphoblastic Leukemia. 2016.\u003c/li\u003e\n\u003cli\u003eHooke MCHATLRLMBUGMAMMA. Kids Are Moving: A Physical Activity Program for Children With Cancer. 2019.\u003c/li\u003e\n\u003cli\u003eHooke MCSDLMMAK-BASBAHJMPMIWSTO. Symptoms, Physical Activity, and Biomarkers in Children at the End of Leukemia Maintenance Therapy. 2023.\u003c/li\u003e\n\u003cli\u003eHowell CRKKRPREK-LNSRLLHMMNKK. Randomized web-based physical activity intervention in adolescent survivors of childhood cancer. Pediatr Blood Cancer. 2018.\u003c/li\u003e\n\u003cli\u003eJacobs SMCCLMBAGCSEEMCYWJLDHP. Pilot Study of Massage to Improve Sleep and Fatigue in Hospitalized Adolescents With Cancer. Pediatric blood \u0026amp; cancer. 2016.\u003c/li\u003e\n\u003cli\u003eJohnson ARMT-HAHJEAA. Perceived Stress and the Fatigue Symptom Cluster in Childhood Brain Tumor Survivors. 2018.\u003c/li\u003e\n\u003cli\u003eKoenig CARAKCERJBE. Continuous recording of vital signs with a wearable device in pediatric patients undergoing chemotherapy for cancer-an operational feasibility study. 2021.\u003c/li\u003e\n\u003cli\u003eKoenig CARASCWJRJBE. Continuous timely monitoring of core temperature with two wearable devices in pediatric patients undergoing chemotherapy for cancer - a comparison study. 2024.\u003c/li\u003e\n\u003cli\u003eKrnavek NJASAECZMNMLPJNBGMM. Sensor-Based Frailty Assessment in Survivors of Childhood Cancer: A Pilot Study. J Frailty Aging. 2021.\u003c/li\u003e\n\u003cli\u003eLazar DRCSMDBCBMLFLAACMCZM. Anthracycline\u0026apos;s Effects on Heart Rate Variability in Children with Acute Lymphoblastic Leukemia: Early Toxicity Signs-Pilot Study. Journal of clinical medicine. 2023.\u003c/li\u003e\n\u003cli\u003eLe AMHRZDJRJFJTNKKK-LNS. A home-based physical activity intervention using activity trackers in survivors of childhood cancer: A pilot study. 2017.\u003c/li\u003e\n\u003cli\u003eLong TMRSRWKEHEKSLMBAWTSGNGC. Exercise training improves vascular function and secondary health measures in survivors of pediatric oncology related cerebral insult. Plos One. 2018.\u003c/li\u003e\n\u003cli\u003eMarmol-Perez AMJHU-GEG-CJJR-SAR-TAL-CFJLIO. Every Move Counts to Improve Bone Health at Clinical Sites in Young Pediatric Cancer Survivors: The iBoneFIT Project. 2024.\u003c/li\u003e\n\u003cli\u003eMatthews EENMCPFKN. Sleep in mother and child dyads during treatment for pediatric acute lymphoblastic leukemia. 2014.\u003c/li\u003e\n\u003cli\u003eMendoza JABKSMMAWKA-LMWACTCEJ. A Fitbit and Facebook mHealth intervention for promoting physical activity among adolescent and young adult childhood cancer survivors: A pilot study. 2017.\u003c/li\u003e\n\u003cli\u003eMerz ELRKBSHSFRKT-ML. Bedtime digital media use, sleep and fatigue among survivors of childhood cancer, their siblings and healthy control sibling pairs. Psychol Health Med. 2023.\u003c/li\u003e\n\u003cli\u003eMiller JMSKTSAAWNJHMBMTATLM. Cancer survivors exercise at higher intensity in outdoor settings: The GECCOS trial. Pediatr Blood Cancer. 2021.\u003c/li\u003e\n\u003cli\u003eMisawa MBIYZBD-NMTDG-GECKALNPRATU. A telerehabilitation program to improve visual perception in children and adolescents with hemianopia consecutive to a brain tumour: a single-arm feasibility and proof-of-concept trial. 2024.\u003c/li\u003e\n\u003cli\u003eMuller CKKAGJRD. Physical activity and health-related quality of life in pediatric cancer patients following a 4-week inpatient rehabilitation program. Support Care Cancer. 2016.\u003c/li\u003e\n\u003cli\u003eMuller CWCBJGGHJVVRD. Effects of an exercise intervention on bone mass in pediatric bone tumor patients. Int J Sports Med. 2014.\u003c/li\u003e\n\u003cli\u003eNessle CNFCSECSWTM. High-frequency temperature monitoring at home using a wearable device: A case series of early fever detection and antibiotic administration for febrile neutropenia with bacteremia. Pediatric blood \u0026amp; cancer. 2022.\u003c/li\u003e\n\u003cli\u003eNunes MDRNLCFAMBLDCCGALACABdA. Pain, sleep patterns and health-related quality of life in paediatric patients with cancer. 2019.\u003c/li\u003e\n\u003cli\u003eOrsey ADWDB. Does socioeconomic status impact physical activity and sleep among children with cancer? Pediatric blood \u0026amp; cancer. 2016.\u003c/li\u003e\n\u003cli\u003eOvans JAHMCBAETLR. Physical Therapist Coaching to Improve Physical Activity in Children With Brain Tumors: A Pilot Study. Pediatr Phys Ther. 2018.\u003c/li\u003e\n\u003cli\u003ePickering LMKMF-RUKMSAMRJP. Brain tumours in children and adolescents may affect the circadian rhythm and quality of life. Acta paediatrica (Oslo, Norway : 1992). 2021.\u003c/li\u003e\n\u003cli\u003ePitt ECCRSBN. Associations between Health Behaviors, Health Self-Efficacy, and Long-Term Outcomes in Survivors of Childhood Cancer: A Cross-Sectional Study. Seminars in oncology nursing. 2023.\u003c/li\u003e\n\u003cli\u003eRehorst-Kleinlugtenbelt LBBWPvdTPvdNJTT. Physical activity level objectively measured by accelerometery in children undergoing cancer treatment at home and in a hospital setting: A pilot study. 2019.\u003c/li\u003e\n\u003cli\u003eRogers VEMCZSLLA-ISBEAHPS. Circadian activity rhythms and fatigue of adolescent cancer survivors and healthy controls: a pilot study. Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine. 2020.\u003c/li\u003e\n\u003cli\u003eRogers VEZSA-ISHPS. Impairment in circadian activity rhythms occurs during dexamethasone therapy in children with leukemia. Pediatr Blood Cancer. 2014.\u003c/li\u003e\n\u003cli\u003eRogers VEZSA-ISLLMBNHPS. A pilot randomized controlled trial to improve sleep and fatigue in children with central nervous system tumors hospitalized for high-dose chemotherapy. Pediatr Blood Cancer. 2019.\u003c/li\u003e\n\u003cli\u003eRogers VEZSMBNA-ISLLHPS. Relationship between circadian activity rhythms and fatigue in hospitalized children with CNS cancers receiving high-dose chemotherapy. Support Care Cancer. 2020.\u003c/li\u003e\n\u003cli\u003eRosen GHAKLMDJKJMYH. The effects of dexamethasone on sleep in young children with acute lymphoblastic leukemia. Sleep Med. 2015.\u003c/li\u003e\n\u003cli\u003eSabel MSABJADSJMBKLBEI. Active video gaming improves body coordination in survivors of childhood brain tumours. Disabil Rehabil. 2016.\u003c/li\u003e\n\u003cli\u003eSavas EHSRSADBSBUH. A Biofeedback Based Virtual Reality Game for Pediatric Population (BioVirtualPed): A Feasibility Trial. 2024.\u003c/li\u003e\n\u003cli\u003eSavas EHSRBC. The effect of a biofeedback-based virtual reality game on pain, fear and anxiety levels during port catheter needle insertion in pediatric oncology patients: A randomized controlled study. 2024.\u003c/li\u003e\n\u003cli\u003eSetoyama AIMKK. 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Eur J Cancer. 2023.\u003c/li\u003e\n\u003cli\u003eVyhl\u0026iacute;dal TDJCF. Actigraphy-Based Characteristics of Sleep in Paediatric Cancer Patients in Remission and a Comparison with Their Healthy Peers in the Recovery Stay. Nature and science of sleep. 2022.\u003c/li\u003e\n\u003cli\u003eVyhlidal TDJHJCF. Accelerometry-based assessment of physical activity and sedentary behavior in adult survivors of childhood acute lymphoblastic leukemia and their healthy peers. Sci Rep. 2023.\u003c/li\u003e\n\u003cli\u003eVyhl\u0026iacute;dal TDJPJCF. Movement behaviours in paediatric cancer survivors during recovery and school weeks. Frontiers in oncology. 2022.\u003c/li\u003e\n\u003cli\u003eWang YMHJFFLDKLABDWCLEHJBSDF. Trajectory of Sleep, Depression, and Quality of Life in Pediatric HSCT Recipients. Transplantation and cellular therapy. 2024.\u003c/li\u003e\n\u003cli\u003eWilliamson Lewis RHKEEKEMLRW-MKMAGMJ. 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The effects of dexamethasone on sleep in young children with acute lymphoblastic leukemia. Sleep Med. 2015;16(4):503-9.\u003c/li\u003e\n\u003cli\u003eRogers VE, Zhu S, Ancoli-Israel S, Hinds PS. Impairment in circadian activity rhythms occurs during dexamethasone therapy in children with leukemia. Pediatr Blood Cancer. 2014;61(11):1986-91.\u003c/li\u003e\n\u003cli\u003eMisawa M, Bajin IY, Zhang B, Daibert-Nido M, Tchao D, Garcia-Giler E, et al. A telerehabilitation program to improve visual perception in children and adolescents with hemianopia consecutive to a brain tumor: a single-arm feasibility and proof-of-concept trial. EClinicalMedicine. 2024;78:102955.\u003c/li\u003e\n\u003cli\u003eHa L, Wakefield CE, Diaz C, Mizrahi D, Signorelli C, Yacef K, et al. Patterns of physical activity and sedentary behavior in child and adolescent cancer survivors assessed using wrist accelerometry: A cluster analysis approach. Health Informatics J. 2023;29(4):14604582231212525.\u003c/li\u003e\n\u003cli\u003eGrydeland M, Bratteteig M, Rueegg CS, Lie HC, Thorsen L, Larsen EH, et al. Physical Activity Among Adolescent Cancer Survivors: The PACCS Study. Pediatrics. 2023;152(3).\u003c/li\u003e\n\u003cli\u003eHooke MC, Salisbury DL, Mathiason MA, Kunin-Batson AS, Blommer A, Hutter J, et al. Symptoms, Physical Activity, and Biomarkers in Children at the End of Leukemia Maintenance Therapy. J Pediatr Hematol Oncol Nurs. 2023;40(6):386-99.\u003c/li\u003e\n\u003cli\u003eGrimshaw SL, Taylor NF, Conyers R, Shields N. Promoting positive physical activity behaviours in children undergoing acute cancer treatment: feasibility of the CanMOVE intervention. Brazilian Journal of Physical Therapy. 2024;28(1):100577.\u003c/li\u003e\n\u003cli\u003eWilliamson Lewis R, Howell KE, Effinger KE, Meacham LR, Wasilewski-Masker K, Mertens A, et al. Feasibility of Fitbit Use in Adolescent Survivors of Pediatric Cancer: Who Consistently Uses It and for How Long? J Adolesc Young Adult Oncol. 2023;12(4):529-36.\u003c/li\u003e\n\u003cli\u003eHoag JA, Bingen K, Karst J, Palou A, Yan K, Zhang J. Playing With a Purpose: The Impact of Therapeutic Recreation During Hospitalization. J Pediatr Hematol Oncol Nurs. 2022;39(1):6-14.\u003c/li\u003e\n\u003cli\u003eG\u0026ouml;tte M, Kesting SV, Gerss J, Rosenbaum D, Boos J. Feasibility and effects of a home-based intervention using activity trackers on achievement of individual goals, quality of life and motor performance in patients with paediatric cancer. BMJ Open Sport Exerc Med. 2018;4(1):e000322.\u003c/li\u003e\n\u003cli\u003eKoenig C, Ammann RA, Schneider C, Wyss J, Roessler J, Brack E. Continuous timely monitoring of core temperature with two wearable devices in pediatric patients undergoing chemotherapy for cancer - a comparison study. Support Care Cancer. 2024;32(3):188.\u003c/li\u003e\n\u003cli\u003eHa L, Wakefield CE, Mizrahi D, Diaz C, Cohn RJ, Signorelli C, et al. A Digital Educational Intervention With Wearable Activity Trackers to Support Health Behaviors Among Childhood Cancer Survivors: Pilot Feasibility and Acceptability Study. JMIR Cancer. 2022;8(3):e38367.\u003c/li\u003e\n\u003cli\u003eKoenig C, Ammann RA, Kuehni CE, Roessler J, Brack E. Continuous recording of vital signs with a wearable device in pediatric patients undergoing chemotherapy for cancer-an operational feasibility study. Support Care Cancer. 2021;29(9):5283-92.\u003c/li\u003e\n\u003cli\u003eRogers VE, Mowbray C, Zhu S, Liu L, Ancoli-Israel S, Barr EA, et al. Circadian activity rhythms and fatigue of adolescent cancer survivors and healthy controls: a pilot study. J Clin Sleep Med. 2020;16(7):1141-7.\u003c/li\u003e\n\u003cli\u003eDaniel LC, Venella KL, Woodard K, Poliakova P, Gross JY, Bercovitz IN, et al. Can extending time between vital sign checks improve sleep in hematopoietic stem cell transplant patients? Testing feasibility, acceptability, and preliminary efficacy. Pediatr Blood Cancer. 2024;71(4):e30832.\u003c/li\u003e\n\u003cli\u003eWithycombe JS, McFatrich M, Hinds PS, Bennett A, Lin L, Maurer SH, et al. Can Steps per Day Reflect Symptoms in Children and Adolescents Undergoing Cancer Treatment? Cancer Nurs. 2022;45(5):345-53.\u003c/li\u003e\n\u003cli\u003eBraam KI, van Dijk-Lokkart EM, Kaspers GJL, Takken T, Huisman J, Bierings MB, et al. Cardiorespiratory fitness and physical activity in children with cancer. Support Care Cancer. 2016;24(5):2259-68.\u003c/li\u003e\n\u003cli\u003eCanali S, Schiaffonati V, Aliverti A. Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness. PLOS Digit Health. 2022;1(10):e0000104.\u003c/li\u003e\n\u003cli\u003eSmuck M, Odonkor CA, Wilt JK, Schmidt N, Swiernik MA. The emerging clinical role of wearables: factors for successful implementation in healthcare. npj Digital Medicine. 2021;4(1):45.\u003c/li\u003e\n\u003cli\u003eGaser D, Peters C, G\u0026ouml;tte M, Oberhoffer-Fritz R, Feuchtinger T, Schmid I, et al. Analysis of self-reported activities of daily living, motor performance and physical activity among children and adolescents with cancer: Baseline data from a randomised controlled trial assessed shortly after diagnosis of leukaemia or non-Hodgkin lymphoma. Eur J Cancer Care (Engl). 2022;31(2):e13559.\u003c/li\u003e\n\u003cli\u003eHooke MC, Hoelscher A, Tanner LR, Langevin M, Bronas UG, Maciej A, et al. Kids Are Moving: A Physical Activity Program for Children With Cancer. J Pediatr Oncol Nurs. 2019;36(6):379-89.\u003c/li\u003e\n\u003cli\u003eWu WW, Yu TH, Jou ST, Hung GY, Tang CC. Factors associated with walking performance among adolescents undergoing cancer treatment: A correlational study. J Child Health Care. 2023;27(4):574-86.\u003c/li\u003e\n\u003cli\u003eHuhn S, Axt M, Gunga HC, Maggioni MA, Munga S, Obor D, et al. The Impact of Wearable Technologies in Health Research: Scoping Review. JMIR Mhealth Uhealth. 2022;10(1):e34384.\u003c/li\u003e\n\u003cli\u003eRoos LG, Slavich GM. Wearable technologies for health research: Opportunities, limitations, and practical and conceptual considerations. Brain, Behavior, and Immunity. 2023;113:444-52.\u003c/li\u003e\n\u003cli\u003eM\u0026uuml;ller C, Krauth KA, Ger\u0026szlig; J, Rosenbaum D. Physical activity and health-related quality of life in pediatric cancer patients following a 4-week inpatient rehabilitation program. Support Care Cancer. 2016;24(9):3793-802.\u003c/li\u003e\n\u003cli\u003eRehorst-Kleinlugtenbelt LB, Bekkering WP, van der Torre P, van der Net J, Takken T. Physical activity level objectively measured by accelerometery in children undergoing cancer treatment at home and in a hospital setting: A pilot study. Pediatric Hematology Oncology Journal. 2019;4(4):82-8.\u003c/li\u003e\n\u003cli\u003eSwartz MC, Teague AK, Wells SJ, Honey T, Fu M, Mahadeo KM, et al. Feasibility and Acceptability Findings of an Energy Balance Data Repository of Children, Adolescents, and Young Adults with Cancer. J Clin Med. 2020;9(9).\u003c/li\u003e\n\u003cli\u003eDalla Santa E, Barton F, Downie P, De Graves S, Nicklen P, Farlie MK. Feasibility of a prospective physiotherapy model of care during the intense treatment phase of childhood cancer (FITChild): A mixed methods design. Pediatr Blood Cancer. 2023:e30488.\u003c/li\u003e\n\u003cli\u003evan Hulst AM, van den Akker ELT, Verwaaijen EJ, Fiocco M, Rensen N, van Litsenburg RRL, et al. Hydrocortisone to reduce dexamethasone-induced neurobehavioral side-effects in children with acute lymphoblastic leukaemia-results of a double-blind, randomised controlled trial with cross-over design. Eur J Cancer. 2023;187:124-33.\u003c/li\u003e\n\u003cli\u003eLong TM, Rath SR, Wallman KE, Howie EK, Straker LM, Bullock A, et al. Exercise training improves vascular function and secondary health measures in survivors of pediatric oncology related cerebral insult. PLoS One. 2018;13(8):e0201449.\u003c/li\u003e\n\u003cli\u003eZupanec S, Jones H, McRae L, Papaconstantinou E, Weston J, Stremler R. A Sleep Hygiene and Relaxation Intervention for Children With Acute Lymphoblastic Leukemia: A Pilot Randomized Controlled Trial. Cancer Nurs. 2017;40(6):488-96.\u003c/li\u003e\n\u003cli\u003eHalman A, Oshlack A. Catchii: Empowering literature review screening in healthcare. Res Synth Methods. 2024;15(1):157-65.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Appendix 1","content":"\u003cp\u003eSupplementary file Appendix 1 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-digital-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjdigitalmed","sideBox":"Learn more about [npj Digital Medicine](http://www.nature.com/npjdigitalmed/)","snPcode":"41746","submissionUrl":"https://submission.springernature.com/new-submission/41746/3","title":"npj Digital Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6517066/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6517066/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis review summarizes the current literature on the use of wearable devices for collecting physiological data in pediatric oncology.\u003c/p\u003e \u003cp\u003eSearches were conducted in MEDLINE, PubMed and Embase, focusing on pediatric patients (0\u0026ndash;25 years) with a cancer diagnosis, and utilizing a wearable device during and/or after treatment.\u003c/p\u003e \u003cp\u003eOf the 77 articles that met the inclusion criteria, 61 studies primarily used wearable devices as a tool to monitor physiological changes in an interventional or observational setting. Only 16 studies integrated wearable devices as an active component of the intervention. The most reported wearable device brands were ActiGraph (19 studies, 24.7%), FitBit (14 studies, 18.2%), Ambulatory Monitoring Inc. (11 studies, 14.3%) and Philips Respironics (10 studies, 13%).\u003c/p\u003e \u003cp\u003eThis scoping review offers valuable insights into the current use of wearable devices in pediatric oncology but also reveals notable gaps in the literature, particularly when compared to the body of research in adult oncology.\u003c/p\u003e","manuscriptTitle":"Utilization of wearable devices in pediatric oncology: A Scoping Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:27:46","doi":"10.21203/rs.3.rs-6517066/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-22T15:00:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-20T12:45:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"62604672965542107668652925013811672932","date":"2025-05-15T08:09:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-14T11:24:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"220408183944165363735305214061406301819","date":"2025-05-05T11:22:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-28T07:59:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-24T23:22:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-24T11:51:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Digital Medicine","date":"2025-04-24T04:51:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-digital-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjdigitalmed","sideBox":"Learn more about [npj Digital Medicine](http://www.nature.com/npjdigitalmed/)","snPcode":"41746","submissionUrl":"https://submission.springernature.com/new-submission/41746/3","title":"npj Digital Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e576f67-9711-406e-a283-54ef4674bae1","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47819271,"name":"Biological sciences/Cancer"},{"id":47819272,"name":"Health sciences/Health care"}],"tags":[],"updatedAt":"2025-08-04T16:39:45+00:00","versionOfRecord":{"articleIdentity":"rs-6517066","link":"https://doi.org/10.1038/s41746-025-01842-5","journal":{"identity":"npj-digital-medicine","isVorOnly":false,"title":"npj Digital Medicine"},"publishedOn":"2025-07-31 16:05:00","publishedOnDateReadable":"July 31st, 2025"},"versionCreatedAt":"2025-05-07 06:27:46","video":"","vorDoi":"10.1038/s41746-025-01842-5","vorDoiUrl":"https://doi.org/10.1038/s41746-025-01842-5","workflowStages":[]},"version":"v1","identity":"rs-6517066","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6517066","identity":"rs-6517066","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}