Ethical Big Data for Personalised Mental Health Nursing: A P4 and Systems View

作者
Erman Yıldız
出处
期刊:Journal of Psychiatric and Mental Health Nursing [Wiley]
卷期号:32 (6): 1404-1411 被引量:1
标识
DOI:10.1111/jpm.70038
摘要

ABSTRACT Background Mental health nursing faces transformation through big data and metadata integration. These technologies create new opportunities but introduce ethical and practical complexities. Digital adoption accelerated during COVID‐19, making it essential to understand implications for nursing practice. Aim This perspective paper aims to critically examine the transformative potential and ethical dilemmas of leveraging big data in mental health nursing, guided by systems biology and P4 (Predictive, Preventive, Personalised, and Participatory) medicine principles. It seeks to define the evolving roles of mental health nurses in this new digital landscape. Method This perspective essay utilises a focused literature review of key studies in nursing, psychiatry, informatics, and ethics, alongside theoretical approaches including systems biology, P4 medicine, and a personalist ethical framework. The analysis explores the integration of big data, focusing on potential benefits, risks, and ethical considerations. Results Big data contributes meaningfully to early diagnosis, personalised treatments, and prevention strategies. However, these contributions must supplement, not substitute, traditional nursing approaches. AI diagnostic tools and digital phenotyping for relapse prediction demonstrate practical applications. Excessive algorithmic dependence risks damaging patient–nurse relationships. Data privacy, algorithmic bias, and access inequities present significant ethical challenges requiring careful attention. Conclusion Big data implementation should enhance, not replace, human interaction in mental health nursing. A new synthesis is proposed where data‐driven insights support efficiency, allowing nurses more time for complex emotional needs. Key recommendations include strengthening data literacy in nursing education, developing robust data governance policies, and establishing comprehensive ethical principles to preserve the essential human dimension of care and ensure equitable access.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
烟花的应助被越悦采纳,获得10
1秒前
无花果的应助被pay采纳,获得10
1秒前
爱学习的小李完成签到,获得积分10
1秒前
特拉法尔加完成签到,获得积分10
1秒前
善良草莓完成签到,获得积分10
2秒前
orixero的应助被Welcome采纳,获得10
2秒前
cai发布了新的文献求助10
3秒前
3秒前
HWX关闭了HWX的文献求助
3秒前
加勒比海带丝完成签到,获得积分10
3秒前
杨枝甘露发布了新的文献求助10
3秒前
小二郎的应助被麦乐鸡采纳,获得10
4秒前
科研小分队完成签到,获得积分10
5秒前
5秒前
wangye完成签到,获得积分20
7秒前
7秒前
tian发布了新的文献求助10
8秒前
8秒前
领导范儿的应助被axx采纳,获得10
8秒前
moli发布了新的文献求助20
9秒前
好好活着发布了新的文献求助10
9秒前
LYB完成签到,获得积分10
10秒前
王昊雨完成签到,获得积分10
10秒前
11秒前
wangye发布了新的文献求助10
11秒前
12秒前
陈旭杰完成签到 ,获得积分10
13秒前
酷波er的应助被勇敢牛牛采纳,获得10
14秒前
酷波er的应助被幸福台灯采纳,获得10
15秒前
15秒前
机智的安梦完成签到,获得积分10
16秒前
空条k完成签到 ,获得积分10
16秒前
勿明发布了新的文献求助10
17秒前
19秒前
zhoudada发布了新的文献求助10
19秒前
19秒前
20秒前
天保大盛发布了新的文献求助10
20秒前
初景发布了新的文献求助10
20秒前
充电宝的应助被小宋采纳,获得10
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
From Scaling and Perturbation to Stability 5000
Les Mantodea De Guyane 2000
Energie-Contracting 1500
Stochastic Models in Operations Research,Vol. 2 600
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization 600
Organizational Behavior 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8030345
求助须知:如何正确求助?哪些是违规求助? 9469651
关于积分的说明 21239296
捐赠科研通 7600184
什么是DOI,文献DOI怎么找? 3388478
关于科研通互助平台的介绍 2520788
邀请新用户注册赠送积分活动 2425271