Min Se Hee, Woo Kyungmi, Song Jiyoun, Alexander Gregory L, O'Malley Terrence, Moen Maria D, Topaz Maxim
University of Pennsylvania School of Nursing, Philadelphia, PA, USA.
Seoul National University College of Nursing, Seoul, South Korea.
West J Nurs Res. 2025 Feb;47(2):71-81. doi: 10.1177/01939459241306946. Epub 2024 Dec 21.
Older adults are a heterogeneous group, and their care experience preferences are likely to be diverse and individualized. Thus, the aim of this study was to identify categories of older adults' care experience preferences and to examine similarities and differences across different age groups.
The initial categories of older adults' care experience preferences were identified through a qualitative review of narrative text (n = 3134) in the ADVault data set. A natural language processing (NLP) algorithm was used to automatically and accurately define older adults' care experience preference categories. Descriptive statistics were used to examine similarities and differences in care experience preference categories across different age groups.
The overall average performance of NLP algorithms was relatively high (average -score = 0.88; range: 0.77-0.96). Through a qualitative review of 350 randomly selected texts, a total of 11 categories were identified. The most frequent category was music, followed by photographs, entertainment, family/friends, religion-related, atmosphere, flower/plants, pet, bed/bedding, hobby, and other. After applying the best performing NLP algorithm to each category, older adults' care experience preference categories were music (41.32%), followed by photographs (28.47%), entertainment (13.46%), religion-related (n = 12.69%), pet (12.22%), flower/plants (11.51%), family/friends (8.45%), atmosphere (7.75%), bed/bedding (6.12%), and hobby (5.45%). Young-old and old-old adults had similar care experience preferences with music being the most frequent category while old-old adults had photographs as the most frequent category for their care experience preference.
Clinicians must understand the distinct categories of care experience preferences and incorporate them into personalized care planning.
老年人是一个异质性群体，他们对护理体验的偏好可能多种多样且因人而异。因此，本研究的目的是确定老年人护理体验偏好的类别，并检查不同年龄组之间的异同。
通过对ADVault数据集中的叙述性文本（n = 3134）进行定性回顾，确定了老年人护理体验偏好的初始类别。使用自然语言处理（NLP）算法自动准确地定义老年人的护理体验偏好类别。描述性统计用于检查不同年龄组在护理体验偏好类别上的异同。
NLP算法的总体平均性能相对较高（平均得分 = 0.88；范围：0.77 - 0.96）。通过对350篇随机选择的文本进行定性回顾，共确定了11个类别。最常见的类别是音乐，其次是照片、娱乐、家人/朋友、宗教相关、氛围、花卉/植物、宠物、床/床上用品、爱好和其他。将性能最佳的NLP算法应用于每个类别后，老年人的护理体验偏好类别为音乐（41.32%），其次是照片（28.47%）、娱乐（13.46%）、宗教相关（n = 12.69%）、宠物（12.22%）、花卉/植物（11.51%）、家人/朋友（8.45%）、氛围（7.75%）、床/床上用品（6.12%）和爱好（5.45%）。年轻老年人和高龄老年人的护理体验偏好相似，音乐是最常见的类别，而高龄老年人护理体验偏好中最常见的类别是照片。
临床医生必须了解护理体验偏好的不同类别，并将其纳入个性化护理计划中。
