Suppr超能文献

护理理论、术语与大数据:基于数据驱动在档案随机临床试验数据中发现新模式

Nursing Theory, Terminology, and Big Data: Data-Driven Discovery of Novel Patterns in Archival Randomized Clinical Trial Data.

作者信息

Monsen Karen A, Kelechi Teresa J, McRae Marion E, Mathiason Michelle A, Martin Karen S

机构信息

Karen A. Monsen, PhD, RN, FAAN, is Associate Professor, School of Nursing, University of Minnesota, Minneapolis. Teresa J. Kelechi, PhD, RN, FAAN, is Professor, College of Nursing, Medical University of South Carolina, Charleston. Marion E. McRae, MScN, ACNP-BC, Robert Wood Johnson Foundation Future of Nursing Scholar, is Nurse Practitioner Nurse Practitioner-Coronary Care Unit, Ronald Reagan UCLA Medical Center, Los Angeles, California. Michelle A. Mathiason, MS, is Statistician, School of Nursing, University of Minnesota, Minneapolis. Karen S. Martin, MSN, RN, FAAN, is Consultant, Martin Associates, Omaha, Nebraska.

出版信息

Nurs Res. 2018 Mar/Apr;67(2):122-132. doi: 10.1097/NNR.0000000000000269.

Abstract

BACKGROUND

The growth and diversification of nursing theory, nursing terminology, and nursing data enable a convergence of theory- and data-driven discovery in the era of big data research. Existing datasets can be viewed through theoretical and terminology perspectives using visualization techniques in order to reveal new patterns and generate hypotheses. The Omaha System is a standardized terminology and metamodel that makes explicit the theoretical perspective of the nursing discipline and enables terminology-theory testing research.

OBJECTIVE

The purpose of this paper is to illustrate the approach by exploring a large research dataset consisting of 95 variables (demographics, temperature measures, anthropometrics, and standardized instruments measuring quality of life and self-efficacy) from a theory-based perspective using the Omaha System. Aims were to (a) examine the Omaha System dataset to understand the sample at baseline relative to Omaha System problem terms and outcome measures, (b) examine relationships within the normalized Omaha System dataset at baseline in predicting adherence, and (c) examine relationships within the normalized Omaha System dataset at baseline in predicting incident venous ulcer.

METHODS

Variables from a randomized clinical trial of a cryotherapy intervention for the prevention of venous ulcers were mapped onto Omaha System terms and measures to derive a theoretical framework for the terminology-theory testing study. The original dataset was recoded using the mapping to create an Omaha System dataset, which was then examined using visualization to generate hypotheses. The hypotheses were tested using standard inferential statistics. Logistic regression was used to predict adherence and incident venous ulcer.

RESULTS

Findings revealed novel patterns in the psychosocial characteristics of the sample that were discovered to be drivers of both adherence (Mental health Behavior: OR = 1.28, 95% CI [1.02, 1.60]; AUC = .56) and incident venous ulcer (Mental health Behavior: OR = 0.65, 95% CI [0.45, 0.93]; Neuro-musculo-skeletal function Status: OR = 0.69, 95% CI [0.47, 1.00]; male: OR = 3.08, 95% CI [1.15, 8.24]; not married: OR = 2.70, 95% CI [1.00, 7.26]; AUC = .76).

DISCUSSION

The Omaha System was employed as ontology, nursing theory, and terminology to bridge data and theory and may be considered a data-driven theorizing methodology. Novel findings suggest a relationship between psychosocial factors and incident venous ulcer outcomes. There is potential to employ this method in further research, which is needed to generate and test hypotheses from other datasets to extend scientific investigations from existing data.

摘要

背景

护理理论、护理术语和护理数据的发展与多样化,使得在大数据研究时代,理论驱动与数据驱动的发现能够相互融合。利用可视化技术,可以从理论和术语的角度审视现有数据集,以揭示新的模式并生成假设。奥马哈系统是一种标准化术语和元模型,它明确了护理学科的理论视角,并支持术语 - 理论验证研究。

目的

本文旨在通过使用奥马哈系统,从基于理论的角度探索一个包含95个变量(人口统计学、体温测量、人体测量学以及测量生活质量和自我效能的标准化工具)的大型研究数据集,来说明该方法。目标是:(a)检查奥马哈系统数据集,以了解相对于奥马哈系统问题术语和结局指标的基线样本;(b)检查基线时标准化奥马哈系统数据集中预测依从性的内部关系;(c)检查基线时标准化奥马哈系统数据集中预测静脉溃疡发生率的内部关系。

方法

将一项预防静脉溃疡冷冻疗法干预的随机临床试验中的变量映射到奥马哈系统术语和测量指标上,以得出术语 - 理论验证研究的理论框架。使用该映射对原始数据集进行重新编码,以创建奥马哈系统数据集,然后通过可视化对其进行检查以生成假设。使用标准推断统计对假设进行检验。采用逻辑回归预测依从性和静脉溃疡发生率。

结果

研究结果揭示了样本心理社会特征中的新模式,这些模式被发现是依从性(心理健康行为:比值比 = 1.28,95%置信区间[1.02, 1.60];曲线下面积 = 0.56)和静脉溃疡发生率(心理健康行为:比值比 = 0.65,95%置信区间[0.45, 0.93];神经 - 肌肉骨骼功能状态:比值比 = 0.69,95%置信区间[0.47, 1.00];男性:比值比 = 3.08,95%置信区间[1.15, 8.24];未婚:比值比 = 2.70,95%置信区间[1.00, 7.26];曲线下面积 = 0.76)的驱动因素。

讨论

奥马哈系统被用作本体、护理理论和术语,以弥合数据与理论之间的差距,可被视为一种数据驱动的理论化方法。新发现表明心理社会因素与静脉溃疡发生结局之间存在关联。有潜力在进一步研究中采用此方法,需要从其他数据集生成并检验假设,以扩展基于现有数据的科学调查。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验