Connelly Jenni, Swingler Kevin, Rodriguez-Sanchez Nidia, Whittaker Anna C
Faculty of Health Sciences and Sport, University of Stirling, Stirling, United Kingdom.
Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom.
JMIR Aging. 2025 Mar 3;8:e64661. doi: 10.2196/64661.
Malnutrition is a challenge among older adults and can result in serious health consequences. However, the dietary intake monitoring needed to identify malnutrition for early intervention is affected by issues such as difficulty remembering or needing a dietitian to interpret the results.
This study aims to co-design a tool using automated food classification to monitor dietary intake and food preferences, as well as food-related symptoms and mood and hunger ratings, for use in care homes.
Participants were 2 separate advisory groups and 2 separate sets of prototype testers. The testers for the first prototype were 10 community-dwelling older adults based in the Stirlingshire area in Scotland who noted their feedback on the tool over 2 weeks in a food diary. The second set of testers consisted of 14 individuals (staff: n=8, 57%; and residents: n=6, 43%) based in 4 care homes in Scotland who provided feedback via interview after testing the tool for a minimum of 3 days. In addition, 130 care home staff across the United Kingdom completed the web-based survey on the tool's needs and potential routes to pay for it; 2 care home managers took part in follow-up interviews. Data were collected through food diaries, a web-based survey, audio recordings and transcriptions of focus groups and interviews, and research notes. Systematic text condensation was used to describe themes across the different types of data.
Key features identified included ratings of hunger, mood, and gastrointestinal symptoms that could be associated with eating specific foods, as well as a traffic light system to indicate risk. Issues included staff time, Wi-Fi connectivity, and the accurate recognition of pureed food and fortified meals. Different models for potential use and commercialization were identified, including peer support among residents to assist those considered less able, staff-only use of the tool, care home-personalized database menus for easy meal photo selection, and targeted monitoring of residents considered to be at the highest risk using the traffic light system.
The tool was deemed useful for monitoring dietary habits and associated symptoms, but necessary design improvements were identified. These should be incorporated before formal evaluation of the tool as an intervention in this setting. Co-design was vital to help make the tool fit for the intended setting and users.
营养不良是老年人面临的一项挑战，可能导致严重的健康后果。然而，为了早期干预而识别营养不良所需的饮食摄入监测受到诸如记忆困难或需要营养师解读结果等问题的影响。
本研究旨在共同设计一种工具，利用自动食物分类来监测饮食摄入、食物偏好以及与食物相关的症状、情绪和饥饿评分，供养老院使用。
参与者包括2个独立的咨询小组和2组独立的原型测试者。第一个原型的测试者是苏格兰斯特灵郡地区的10名居家老年人，他们在2周内通过食物日记记录了对该工具的反馈。第二组测试者由苏格兰4家养老院的14个人组成（工作人员：n = 8，57%；居民：n = 6，43%），他们在对该工具进行至少3天的测试后通过访谈提供反馈。此外，英国各地的130名养老院工作人员完成了关于该工具需求和潜在付费途径的网络调查；2名养老院经理参与了后续访谈。数据通过食物日记、网络调查、焦点小组和访谈的音频记录及文字转录以及研究笔记收集。采用系统文本浓缩法来描述不同类型数据中的主题。
确定的关键特征包括与食用特定食物相关的饥饿、情绪和胃肠道症状评分，以及一个用于指示风险的交通信号灯系统。问题包括工作人员时间、无线网络连接，以及对泥状食物和强化餐的准确识别。确定了潜在使用和商业化的不同模式，包括居民之间的同伴支持以帮助那些能力较弱的人、工作人员单独使用该工具、养老院个性化数据库菜单以便轻松选择餐食照片，以及使用交通信号灯系统对被认为风险最高的居民进行针对性监测。
该工具被认为对监测饮食习惯和相关症状有用，但也确定了必要的设计改进。在将该工具作为此环境中的一项干预措施进行正式评估之前，应纳入这些改进。共同设计对于使该工具适合预期环境和用户至关重要。
