{"title":"Accessibility and Feasibility of Bluetooth Communication System and Smart Devices to Measure Nursing Activity.","authors":"Younhee Kang, Yujin Hur","doi":"10.1097/NNR.0000000000000906","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>One of the main reasons nurses leave the clinical field is the increasing workload. Researchers have estimated nursing workload by relying on self-reported nursing hours, tasks, and nurse-to-patient ratios. However, directly measuring nursing hours is essential for obtaining an accurate estimate.</p><p><strong>Objectives: </strong>The aims of this study were to measure nursing activities using real-time location information from beacons, smartwatches, and smartphones in the medical unit, and concurrently to collect physiological indicators through wearable devices.</p><p><strong>Methods: </strong>We used a descriptive, cross-sectional design to explore nursing workload in a medical ward based on partial data from the SMART-NURSE project involving the collection of biometric and location data using smartwatches and Bluetooth beacons, with subsequent integration based on synchronized timestamps. Descriptive statistics, the Kruskal-Wallis test, and Spearman's rank correlation were used to analyze physical activity indicators such as heart rate, step count, and energy expenditure.</p><p><strong>Results: </strong>A total of 49 work shifts were studied, with 15, 16, and 18 shifts for day, evening, and night, respectively. Nursing hours had significant differences depending on duties, with night>day>evening. The average total energy expenditure during the duties was 906.21 kcal ( SD =205.99). The average heart rate was 92.55 ( SD =9.79), and it was significantly correlated with the number of patients' procedures and the number of discharged patients. The average number of steps was 7343.65 ( SD =1376.62), which was positively correlated with direct nursing and negatively correlated with indirect nursing and nursing stress.</p><p><strong>Discussion: </strong>The nursing hours measured in this study were almost identical to the actual nursing hours, leading us to conclude that this method was successful in measuring nursing hours without any loss. As a result, physical activity data could be used as a fundamental basis for devising a measurement method to measure nurses' workload and burden.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":"E231-E237"},"PeriodicalIF":2.5000,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nursing Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/NNR.0000000000000906","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
Abstract
Background: One of the main reasons nurses leave the clinical field is the increasing workload. Researchers have estimated nursing workload by relying on self-reported nursing hours, tasks, and nurse-to-patient ratios. However, directly measuring nursing hours is essential for obtaining an accurate estimate.
Objectives: The aims of this study were to measure nursing activities using real-time location information from beacons, smartwatches, and smartphones in the medical unit, and concurrently to collect physiological indicators through wearable devices.
Methods: We used a descriptive, cross-sectional design to explore nursing workload in a medical ward based on partial data from the SMART-NURSE project involving the collection of biometric and location data using smartwatches and Bluetooth beacons, with subsequent integration based on synchronized timestamps. Descriptive statistics, the Kruskal-Wallis test, and Spearman's rank correlation were used to analyze physical activity indicators such as heart rate, step count, and energy expenditure.
Results: A total of 49 work shifts were studied, with 15, 16, and 18 shifts for day, evening, and night, respectively. Nursing hours had significant differences depending on duties, with night>day>evening. The average total energy expenditure during the duties was 906.21 kcal ( SD =205.99). The average heart rate was 92.55 ( SD =9.79), and it was significantly correlated with the number of patients' procedures and the number of discharged patients. The average number of steps was 7343.65 ( SD =1376.62), which was positively correlated with direct nursing and negatively correlated with indirect nursing and nursing stress.
Discussion: The nursing hours measured in this study were almost identical to the actual nursing hours, leading us to conclude that this method was successful in measuring nursing hours without any loss. As a result, physical activity data could be used as a fundamental basis for devising a measurement method to measure nurses' workload and burden.
期刊介绍：
Nursing Research is a peer-reviewed journal celebrating over 60 years as the most sought-after nursing resource; it offers more depth, more detail, and more of what today''s nurses demand. Nursing Research covers key issues, including health promotion, human responses to illness, acute care nursing research, symptom management, cost-effectiveness, vulnerable populations, health services, and community-based nursing studies. Each issue highlights the latest research techniques, quantitative and qualitative studies, and new state-of-the-art methodological strategies, including information not yet found in textbooks. Expert commentaries and briefs are also included. In addition to 6 issues per year, Nursing Research from time to time publishes supplemental content not found anywhere else.
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