Factors Influencing Home Care Nurses’ Behavioral Intention to Use Digital Healthcare

IF 2.9 3区医学 Q2 NURSING

Asian Nursing Research Pub Date : 2026-02-01 Epub Date: 2025-11-03 DOI:10.1016/j.anr.2025.10.003

So-Hi Kwon , Young-Joo Kim , Seo-Hye Park

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引用次数: 0

Abstract

Purpose

Home care and digital healthcare are essential strategies for addressing health challenges in an aging society. This study aims to understand the behavioral intention (BI) to use digital healthcare and its influencing factors based on the Unified Theory of Acceptance and Use of Technology.

Methods

This cross-sectional study surveyed 180 home care nurses in South Korea using online questionnaires. Participants were from hospital-based home care (HHC), home hospice (HH), and community health center-based home care (CHC). The survey assessed their experience with and intention to use 19 digital health technologies and measured key factors based on the Unified Theory of Acceptance and Use of Technology: performance expectancy, effort expectancy, social influence (SI), attitude toward digital healthcare, and concerns.

Results

Among the 19 digital health technologies, big data/artificial intelligence solutions (87.2%) and artificial intelligence-assisted care sensors (85.6%) had the highest BI to use. Usage experience and intention were negatively correlated across all technologies (κ = −0.10 to −0.70, p < .001). Behavioral intentions differed significantly between groups (χ² = 6.35, p = .042), with HH nurses reporting the highest intention (93.8%), followed by HHC (87.0%) and community health center-based home care (75.0%) nurses. Effort expectancy increased adoption likelihood (odds ratio = 2.26, 95% confidence interval: 1.10–4.62, p = .026), while SI was the strongest predictor (odds ratio = 2.93, 95% confidence interval: 1.15–7.46, p = .024).

Conclusions

Home care nurses generally showed strong BI to adopt digital healthcare. However, the negative association between experience and intention suggests the need to enhance user satisfaction when implementing digital health technologies. Since effort expectancy and SI significantly affect adoption, reducing perceived effort and strengthening social support are essential for successful integration.

查看原文本刊更多论文

影响家庭护理护士使用数字医疗行为意向的因素。

目的：家庭护理和数字医疗保健是应对老龄化社会健康挑战的基本战略。本研究旨在基于技术接受与使用统一理论（UTAUT），了解数字医疗的使用行为意愿及其影响因素。方法：本横断面研究采用在线问卷调查了180名韩国家庭护理护士。参与者来自以医院为基础的家庭护理（HHC）、家庭临终关怀（HH）和社区卫生中心为基础的家庭护理（CHC）。该调查评估了他们使用19种数字医疗技术的经验和意图，并根据技术接受和使用统一理论（UTAUT）测量了关键因素：绩效预期、努力预期、社会影响、对数字医疗的态度和担忧。结果：在19项数字健康技术中，大数据/人工智能（AI）解决方案（87.2%）和人工智能辅助护理传感器（85.6%）的行为使用意愿最高。所有技术的使用体验和意图呈负相关（κ = -0.103 ~ -0.703, p < 0.001）。行为意向组间差异有统计学意义（χ2 = 6.354, p = 0.042）， HH护士行为意向最高（93.8%），其次是HHC护士（87.0%）和CHC护士（75.0%）。努力期望增加了被采纳的可能性（优势比[OR] = 2.256, 95%可信区间[CI]: 1.102-4.617, p = 0.026），而社会影响是最强的预测因子（OR = 2.931, 95% CI: 1.152-7.462, p = 0.024）。结论：家庭护理护士普遍表现出采用数字化医疗的强烈行为意向。然而，体验和意向之间的负相关表明，在实施数字卫生技术时需要提高用户满意度。由于期望付出的努力和社会影响对收养有重大影响，因此减少感知付出和加强社会支持对成功融入至关重要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Asian Nursing Research NURSING-

CiteScore

4.20

自引率

4.50%

发文量

审稿时长

45 days

期刊介绍： Asian Nursing Research is the official peer-reviewed research journal of the Korean Society of Nursing Science, and is devoted to publication of a wide range of research that will contribute to the body of nursing science and inform the practice of nursing, nursing education, administration, and history, on health issues relevant to nursing, and on the testing of research findings in practice.