Latest Findings in Key Research Areas of Precision Nursing for Chronic Diseases in Older Adults

WU Junhui; ZHOU Weijiao; WANG Weixuan; SHANG Shaomei

doi:10.12182/20230760507

Volume 54 Issue 4

Jul. 2023

Turn off MathJax

Article Contents

Abstract

References

JOURNAL OF SICHUAN UNIVERSITY (MEDICAL SCIENCES) > 2023 > 54(4): 731-735. > DOI: 10.12182/20230760507

WU Junhui, ZHOU Weijiao, WANG Weixuan, et al. Latest Findings in Key Research Areas of Precision Nursing for Chronic Diseases in Older Adults[J]. Journal of Sichuan University (Medical Sciences), 2023, 54(4): 731-735. DOI: 10.12182/20230760507

Citation:

PDF (538 KB)

Latest Findings in Key Research Areas of Precision Nursing for Chronic Diseases in Older Adults

School of Nursing, Peking University, Beijing 100191, China

More Information

Corresponding author:
SHANG Shaomei, E-mail: mei916@263.net
Received Date: June 04, 2023
Revised Date: July 16, 2023
Available Online: July 30, 2023
Published Date: July 19, 2023

Abstract

Abstract

The advent of the era of biomedical big data has helped promote the development of precision nursing. Precision nursing for chronic diseases in older adults is an interdisciplinary research field in which accurate individualized data are utilized to carry out early screening and health management of older adult populations at high risk for chronic diseases and early intervention of diseases, which plays an important role in improving the prognosis of diseases and the health level of the older adult population. Herein, we introduced the concept of precision nursing, and discussed the latest research findings in the key areas of precision nursing for chronic diseases in older adults, including precision symptom management in cancer patients and precision nursing in older patients with multimorbidity. At present, research concerning precise symptom management of cancer patients is mainly focused on prediction modelling for risks of symptoms, longitudinal change trajectories, core symptom identification, etc. Investigations in the precise nursing of cancer patients are conducted in the following areas, risk prediction, the timing of interventions, and intervention targets. Research on precision nursing for multimorbidity is mainly focused on assessment of chronic disease multimorbidity, multimorbidity pattern recognition, and health management of multimorbidity. We also discussed potential opportunities and challenges of precision nursing in the future, in order to provide a scientific basis for the improving the practice and theories of precision nursing. In the future, precision nursing will play an ever more important role in uncovering pathogenic information, the diagnosis and treatment of diseases, the health of the research population, and the promotion of medical research.
- Precision nursing,
- Precision medicine,
- Chronic diseases,
- Symptom management,
- Multimorbidity in older adults,
- Research progress

FullText(HTML)

References (35)

References

[1]	EMMONS-BELL S, JOHNSON C, ROTH G. Prevalence, incidence and survival of heart failure: a systematic review. Heart,2022,108(17): 1351–1360. DOI: 10.1136/heartjnl-2021-320131
[2]	KHAN M A B, HASHIM M J, KING J K, et al. Epidemiology of type 2 diabetes-global burden of disease and forecasted trends. J Epidemiol Glob Health,2020,10(1): 107–111. DOI: 10.2991/jegh.k.191028.001
[3]	Global Burden of Disease Cancer Collaboration; FITZMAURICE C, AKINYEMIJU T F, Al LAMI F H, et al. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 1990 to 2016: a systematic analysis for the global burden of disease study. JAMA Oncol,2018,4(11): 1553–1568. DOI: 10.1001/jamaoncol.2018.2706
[4]	GBD 2017 Colorectal Cancer Collaborators. The global, regional, and national burden of colorectal cancer and its attributable risk factors in 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Gastroenterol Hepatol,2019,4(12): 913–933. DOI: 10.1016/S2468-1253(19)30345-0
[5]	COLLINS F S, VARMUS H. A new initiative on precision medicine. N Engl J Med,2015,372(9): 793–795. DOI: 10.1056/NEJMp1500523
[6]	ROSS J S, WANG K, GAY L, et al. Comprehensive genomic profiling of carcinoma of unknown primary site: new routes to targeted therapies. JAMA Oncol,2015,1(1): 40–49. DOI: 10.1001/jamaoncol.2014.216
[7]	GINSBURG G S, PHILLIPS K A. Precision medicine: from science to value. Health Aff (Millwood),2018,37(5): 694–701. DOI: 10.1377/hlthaff.2017.1624
[8]	许丽, 李伟, 孙学会, 等. 2022年精准医学发展态势. 生命科学,2023,35(1): 42–47. DOI: 10.13376/j.cbls/2023007
[9]	FAWAZ M. Role of nurses in precision health. Nurs Outlook,2021,69(6): 937–940. DOI: 10.1016/j.outlook.2021.01.016
[10]	FU M R, KURNAT-THOMA E, STARKWEATHER A, et al. Precision health: a nursing perspective. Int J Nurs Sci,2020,7(1): 5–12. DOI: 10.1016/j.ijnss.2019.12.008
[11]	DEWELL S, BENZIES K, GINN C. Precision health and nursing: seeing the familiar in the foreign. Can J Nurs Res,2020,52(3): 199–208. DOI: 10.1177/0844562120945159
[12]	常承婷, 刘雨薇, 田亚丽, 等. 精准护理的研究进展. 中国科学:生命科学,2022,52(11): 1731–1737. DOI: 10.1360/SSV-2022-0202
[13]	李源, 周宗蓉, 罗碧如. 精准医学视域下护理专业实践的革新与展望. 护理学杂志,2020,35(18): 107–110. DOI: 10.3870/j.issn.1001-4152.2020.18.107
[14]	秦岚, 叶艳欣, 方庆虹, 等. 住院癌症患者衰弱风险预测模型的构建与验证. 护理学杂志,2022,37(9): 28–33. DOI: 10.3870/j.issn.1001-4152.2022.09.028
[15]	胡保玲. 乳腺癌患者癌因性疲乏风险预测模型的构建与验证. 福州: 福建中医药大学, 2022.
[16]	Di MEGLIO A, HAVAS J, SOLDATO D, et al. Development and validation of a predictive model of severe fatigue after breast cancer diagnosis: toward a personalized framework in survivorship care. J Clin Oncol,2022,40(10): 1111–1123. DOI: 10.1200/JCO.21.01252
[17]	邓本敏, 陈月梅, 边志衡, 等. 化疗相关性恶心和呕吐风险预测模型的构建. 中国护理管理,2022,22(9): 1384–1390. DOI: 10.3969/j.issn.1672-1756.2022.09.022
[18]	MOLASSIOTIS A, STAMATAKI Z, KONTOPANTELIS E. Development and preliminary validation of a risk prediction model for chemotherapy-related nausea and vomiting. Support Care Cancer,2013,21(10): 2759–2767. DOI: 10.1007/s00520-013-1843-2
[19]	刘亚婷, 谢玲女, 蒋丽丽, 等. 基于潜变量增长模型的直肠癌低位前切除患者术后症状发展轨迹研究. 护理与康复,2023,22(2): 1–6. DOI: 10.3969/j.issn.1671-9875.2023.02.001
[20]	TSOU Y L, LEE J M, TANG C C. The trajectory of cancer-related fatigue and its associating factors in patients with esophageal cancer receiving treatments: a prospective longitudinal study. Ann Surg Oncol,2022,29(5): 2784–2790. DOI: 10.1245/s10434-021-11294-2
[21]	蔡婷婷, 黄青梅, 袁长蓉. 乳腺癌患者癌因性疲乏轨迹及其影响因素的研究进展. 解放军护理杂志,2021,38(4): 74–76. DOI: 10.3969/j.issn.1008-9993.2021.04.019
[22]	李蕾蕾, 杨长永, 胡玉冰, 等. 恶性黑色素瘤术后患者免疫检查点抑制剂辅助治疗早期疲劳发展轨迹研究. 中华护理杂志,2022,57(20): 2487–2492. DOI: 10.3761/j.issn.0254-1769.2022.20.008
[23]	VAZ-LUIS I, Di MEGLIO A, HAVAS J, et al. Long-term longitudinal patterns of patient-reported fatigue after breast cancer: a group-based trajectory analysis. J Clin Oncol,2022,40(19): 2148–2162. DOI: 10.1200/JCO.21.01958
[24]	BOWER J E, GANZ P A, IRWIN M R, et al. Do all patients with cancer experience fatigue? A longitudinal study of fatigue trajectories in women with breast cancer. Cancer,2021,127(8): 1334–1344. DOI: 10.1002/cncr.33327
[25]	BAUSSARD L, PROUST-LIMA C, PHILIPPS V, et al. Determinants of distinct trajectories of fatigue in patients undergoing chemotherapy for a metastatic colorectal cancer: 6-month follow-up using growth mixture modeling. J Pain Symptom Manage,2022,63(1): 140–150. DOI: 10.1016/j.jpainsymman.2021.06.019
[26]	BORSBOOM D. A network theory of mental disorders. World Psychiatry,2017,16(1): 5–13. DOI: 10.1002/wps.20375
[27]	杨晨, 刘风侠. 网络分析在癌症病人症状管理中的应用研究进展. 护理研究,2022,36(19): 3494–3498. DOI: 10.12102/j.issn.1009-6493.2022.19.022
[28]	叶艳欣, 秦岚, 曾凯, 等. 癌症患者治疗间歇期核心症状及症状群的识别. 护理学杂志,2022,27(1): 20–22. DOI: 10.3870/j.issn.1001-4152.2022.01.020
[29]	LIN Y, BRUNER D W, PAUL S, et al. A network analysis of self-reported psychoneurological symptoms in patients with head and neck cancer undergoing intensity-modulated radiotherapy. Cancer,2022,128(20): 3734–3743. DOI: 10.1002/cncr.34424
[30]	闫伟, 路云, 张冉, 等. 基于CHARLS数据分析的我国老年人共病现状研究. 中华疾病控制杂志,2019,23(4): 426–430. DOI: 10.16462/j.cnki.zhjbkz.2019.04.012
[31]	MERANIUS M S, HAMMAR L M. How does the healthcare system affect medication self-management among older adults with multimorbidity? Scand J Caring Sci,2016,30(1): 91–98. DOI: 10.1111/scs.12225
[32]	LEROY L, BAYLISS E, DOMINO M, et al. The agency for healthcare research and quality multiple chronic conditions research network: overview of research contributions and future priorities. Med Care,2014,52(Suppl 3): S15–S22. DOI: 10.1097/MLR.0000000000000095
[33]	NOLTE E,DURAND-ZALESKI I. Developing and validating disease management evaluation methods for European healthcare system. Eur J Pub Health,2012,20: 12.
[34]	FARMER C, FENU E, O'FLYNN N, et al. Clinical assessment and management of multimorbidity: summary of NICE guidance. BMJ,2016,354: i4843. DOI: 10.1136/bmj.i4843
[35]	MC NAMARA K P, BREKEN B D, ALZUBAIDI H T, et al. Health professional perspectives on the management of multimorbidity and polypharmacy for older patients in Australia. Age Ageing,2017,46(2): 291–299. DOI: 10.1093/ageing/afw200

OPEN ACCESS This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license (CC BY-NC 4.0). In other words, the full-text content of the journal is made freely available for third-party users to copy and redistribute in any medium or format, and to remix, transform, and build upon the content of the journal. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may not use the content of the journal for commercial purposes. For more information about the license, visit https://creativecommons.org/licenses/by-nc/4.0

Relative Articles

Supplements (0)

Cited By

Get Citation

PDF

XML

Article views (2062) PDF downloads (120)

Latest Findings in Key Research Areas of Precision Nursing for Chronic Diseases in Older Adults

Abstract

References

Catalog

Export File

Citation

Format

Content