Research progress of wearable devices in occupational health surveillance among nurses

doi:10.3761/j.issn.0254-1769.2025.10.020

Abstract

Abstract:

Occupational health issues among nurses significantly impact their quality of life and the quality of nursing services. Wearable devices，equipped with functions such as real-time monitoring，intelligent assessment，and early warning feedback，can provide technical support for occupational health surveillance among nurses. This paper reviews the concept of nurses’ occupational health，the advantages of wearable devices in monitoring nurses’ occupational health，and the current applications of wearable devices in monitoring both physiological and psychological health among nurses. It also analyzes the challenges and proposes countermeasures，aiming to provide insights for optimizing occupational health management for nurses.

Key words: Wearable Devices, Nurse, Occupational Health, Surveillance, Review

摘要：

护士的职业健康问题会影响其生活质量与护理服务质量。可穿戴设备具备实时监测、智能评估、预警反馈等功能，可为护士职业健康监护提供技术支持。该文对护士职业健康的概念、可穿戴设备在护士职业健康监护中应用的优势、可穿戴设备在护士生理和心理健康监护中的应用现状进行综述，分析其面临的挑战并提出对策，旨在为优化护士的职业健康管理提供借鉴。

关键词: 可穿戴设备, 护士, 职业健康, 监护, 综述

CHEN Xiuwan, HUANG Hualing, HONG Xuepei, CHEN Yadan, CHEN Fuhong. Research progress of wearable devices in occupational health surveillance among nurses[J]. Chinese Journal of Nursing, 2025, 60(10): 1277-1281.

陈秀婉, 黄华玲, 洪雪珮, 陈亚丹, 陈付红. 可穿戴设备在护士职业健康监护中的应用进展[J]. 中华护理杂志, 2025, 60(10): 1277-1281.

References 31

[1]	国家统计局. 2023年国民经济和社会发展统计公报[EB/OL]. (2024-02-29) [2025-02-12]. https://www.stats.gov.cn/sj/zxfb/2024-02/t20240228_1947915.html.
	National Bureau of Statistics. Statistical bulletin of national economic and social development for 2023[EB/OL].(2024-02-29) [2025-02-12]. https://www.stats.gov.cn/sj/zxfb/2024-02/t20240228_1947915.html.
[2]	梁涛, 刘鑫, 王佳弘, 等. 国外护士健康队列研究现状及对我国的启示[J]. 中国护理管理, 2020, 20(6):816-820.
	Liang T, Liu X, Wang JH, et al. Current state of nurse cohorts in foreign countries and its enlightenment to China[J]. Chin Nurs Manag, 2020, 20(6):816-820.
[3]	Williams GJ, Al-Baraikan A, Rademakers FE, et al. Wearable technology and the cardiovascular system:the future of patient assessment[J]. Lancet Digit Health, 2023, 5(7):e467-e476.
[4]	李亚敏, 李栩亭, 余强, 等. 护士健康队列研究的大样本文献计量学分析[J]. 中华护理杂志, 2024, 59(3):330-337. DOI
	Li YM, Li XT, Yu Q, et al. Bibliometric analysis of large-scale nurse health cohort studies[J]. Chin J Nurs, 2024, 59(3):330-337. DOI
[5]	Buchholz SW, Mowbray FI, Allman G, et al. Wearable devices and nurses’ health:protocol for an integrative review[J]. JMIR Res Protoc, 2023, 12:e48178.
[6]	World Health Organization. Occupational health:health workers[EB/OL].(2024-11-07) [2025-02-01]. https://www.who.int/zh/news-room/fact-sheets/detail/occupational-health--health-workers.
[7]	健康中国行动推进委员会. 健康中国行动(2019-2030年):总体要求、重大行动及主要指标[J]. 中国循环杂志, 2019, 34(9):846-858.
	National Health Promotion Committee. Healthy China Action(2019-2030):overall requirements for major actions and key indicators[J]. Chin Circ J, 2019, 34(9):846-858.
[8]	Sung S, Kwon JW, Kim JE, et al. Real-time stress analysis affe-cting nurse during elective spinal surgery using a wearable device[J]. Brain Sci, 2022, 12(7):909.
[9]	Agarwal AK, Gonzales R, Scott K, et al. Investigating the feasi-bility of using a wearable device to measure physiologic health data in emergency nurses and residents:observational cohort study[J]. JMIR Form Res, 2024, 8:e51569.
[10]	García Patiño A, Khoshnam M, Menon C. Wearable device to monitor back movements using an inductive textile sensor[J]. Sensors (Basel), 2020, 20(3):905.
[11]	Gilchrist A, Pokorná A. Prevalence of musculoskeletal low back pain among registered nurses:results of an online survey[J]. J Clin Nurs, 2021, 30(11/12):1675-1683.
[12]	Ferrone A, Napier C, Menon C. Wearable technology to increase self-awareness of low back pain:a survey of technology needs among health care workers[J]. Sensors (Basel), 2021, 21(24):8412.
[13]	Ji XX, Hettiarachchige RO, Littman ALE, et al. Using digital human modelling to evaluate the risk of musculoskeletal in-jury for workers in the healthcare industry[J]. Sensors (Basel), 2023, 23(5):2781.
[14]	Yin P, Yang L, Du SF, et al. The effect of mobile wearable waist assist robot on lower back pain during lifting and handling tasks[J]. Mob Netw Appl, 2021, 26(3):988-996.
[15]	王泠, 刘晓黎, 王雯. 抗击新型冠状病毒肺炎一线支援护理团队的组建和管理[J]. 中华护理杂志, 2020, 55(增刊):7-9.
	Wang L, Liu XL, Wang W. Set up and management of the first-line support nurses fighting against the coronavirus disease 2019[J]. Chin J Nurs, 2020, 55(S1):7-9.
[16]	Li JC, Yin J, Ramakrishna S, et al. Smart mask as wearable for post-pandemic personal healthcare[J]. Biosensors(Basel), 2023, 13(2):205.
[17]	Kalavakonda RR, Masna NVR, Mandal S, et al. A smart mask for active defense against airborne pathogens[J]. Sci Rep, 2021, 11(1):19910. DOI PMID
[18]	Ye ZL, Ling Y, Yang MY, et al. A breathable,reusable,and zero-power smart face mask for wireless cough and mask-wearing monitoring[J]. ACS Nano, 2022, 16(4):5874-5884.
[19]	Taheri S. Sleep and cardiometabolic health-not so strange bedfellows[J]. Lancet Diabetes Endocrinol, 2023, 11(8):532-534.
[20]	Feng TT, Booth BM, Baldwin-Rodríguez B, et al. A multimodal analysis of physical activity,sleep,and work shift in nurses with wearable sensor data[J]. Sci Rep, 2021, 11(1):8693.
[21]	Konya I, Watanabe K, Shishido I, et al. Post-work recovery from fatigue and sleep episodes among nurses who are engaged in 16-hour night shifts:a prospective observational study[J]. Heal-thcare(Basel), 2022, 10(6):1089.
[22]	王励飞, 米元元, 金晶, 等. ICU护士工作压力体验与应对质性研究的系统评价[J]. 中华护理杂志, 2019, 54(10):1566-1571. DOI
	Wang LF, Mi YY, Jin J, et al. The experience and coping behaviors of work stress among ICU nurses:a meta-synthesis of qualitative studies[J]. Chin J Nurs, 2019, 54(10):1566-1571.
[23]	Ahmadi N, Sasangohar F, Nisar T, et al. Quantifying occupa-tional stress in intensive care unit nurses:an applied natura-listic study of correlations among stress,heart rate,electro-dermal activity,and skin temperature[J]. Hum Factors, 2022, 64(1):159-172.
[24]	Li XX, Zhu WW, Sui XF, et al. Assessing workplace stress among nurses using heart rate variability analysis with wearable ECG device-a pilot study[J]. Front Public Health, 2022, 9:810577.
[25]	Gaballah A, Tiwari A, Narayanan S, et al. Context-aware speech stress detection in hospital workers using Bi-LSTM classifiers[C]// ICASSP 2021IEEE International Conference on Acous-tics,Speech and Signal Processing(ICASSP). June 6-11, 2021. Toronto,ON,Canada. IEEE, 2021:8348-8352.
[26]	Papazian L, Hraiech S, Loundou A, et al. High-level burnout in physicians and nurses working in adult ICUs:a systematic review and meta-analysis[J]. Intensive Care Med, 2023, 49(4):387-400.
[27]	Wilton AR, Sheffield K, Wilkes Q, et al. The burnout predi-ction using wearable and artIficial intelligence(BROWNIE) study:a decentralized digital health protocol to predict bur-nout in registered nurses[J]. BMC Nurs, 2024, 23(1):114.
[28]	de Looff P, Nijman H, Didden R, et al. Burnout symptoms in forensic psychiatric nurses and their associations with personality,emotional intelligence and client aggression:a cross-sectional study[J]. J Psychiatr Ment Health Nurs, 2018, 25(8):506-516.
[29]	Rosen MA, Dietz AS, Lee N, et al. Sensor-based measurement of critical care nursing workload:unobtrusive measures of nursing activity complement traditional task and patient level indicators of workload to predict perceived exertion[J]. PLoS One, 2018, 13(10):e0204819.
[30]	Cosoli G, Spinsante S, Scalise L. Wrist-worn and chest-strap wearable devices:systematic review on accuracy and metrolo-gical characteristics[J]. Measurement, 2020, 159:107789.
[31]	Mahoney C, Hoyle L, Van Splunter C, et al. Wearable activity trackers for nurses’ health:a qualitative acceptability study[J]. Nurs Open, 2023, 10(9):6357-6368.