Boumans Roel, van de Sande Yana, Thill Serge, Bosse Tibor
Behavioural Science Institute, Radboud University, Nijmegen, Netherlands.
Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands.
JMIR Aging. 2022 Apr 25;5(2):e32473. doi: 10.2196/32473.
Older adults often have increasing memory problems (amnesia), and approximately 50 million people worldwide have dementia. This syndrome gradually affects a patient over a period of 10-20 years. Intelligent virtual agents may support people with amnesia.
This study aims to identify state-of-the-art experimental studies with virtual agents on a screen capable of verbal dialogues with a target group of older adults with amnesia.
We conducted a systematic search of PubMed, SCOPUS, Microsoft Academic, Google Scholar, Web of Science, and CrossRef on virtual agent and amnesia on papers that describe such experiments. Search criteria were (Virtual Agent OR Virtual Assistant OR Virtual Human OR Conversational Agent OR Virtual Coach OR Chatbot) AND (Amnesia OR Dementia OR Alzheimer OR Mild Cognitive Impairment). Risk of bias was evaluated using the QualSyst tool (University of Alberta), which scores 14 study quality items. Eligible studies are reported in a table including country, study design type, target sample size, controls, study aims, experiment population, intervention details, results, and an image of the agent.
A total of 8 studies was included in this meta-analysis. The average number of participants in the studies was 20 (SD 12). The verbal interactions were generally short. The usability was generally reported to be positive. The human utterance was seen in 7 (88%) out of 8 studies based on short words or phrases that were predefined in the agent's speech recognition algorithm. The average study quality score was 0.69 (SD 0.08) on a scale of 0 to 1.
The number of experimental studies on talking about virtual agents that support people with memory problems is still small. The details on the verbal interaction are limited, which makes it difficult to assess the quality of the interaction and the possible effects of confounding parameters. In addition, the derivation of the aggregated data was difficult. Further research with extended and prolonged dialogues is required.
老年人经常出现记忆力问题(失忆症),全球约有5000万人患有痴呆症。这种综合征会在10至20年的时间里逐渐影响患者。智能虚拟代理可能会为失忆症患者提供帮助。
本研究旨在识别关于虚拟代理的前沿实验研究,这些虚拟代理可在屏幕上与患有失忆症的老年目标群体进行言语对话。
我们在PubMed、SCOPUS、Microsoft Academic、Google Scholar、Web of Science和CrossRef上系统搜索了描述此类实验的关于虚拟代理和失忆症的论文。搜索标准为(虚拟代理或虚拟助手或虚拟人或对话代理或虚拟教练或聊天机器人)且(失忆症或痴呆症或阿尔茨海默病或轻度认知障碍)。使用QualSyst工具(阿尔伯塔大学)评估偏倚风险,该工具对14项研究质量项目进行评分。符合条件的研究在一个表格中报告,包括国家、研究设计类型、目标样本量、对照组、研究目的、实验人群、干预细节、结果以及代理的图像。
本荟萃分析共纳入8项研究。这些研究的参与者平均数量为20名(标准差为12)。言语互动通常较短。总体报告显示可用性为积极。在8项研究中的7项(88%)中,基于代理语音识别算法中预定义的简短单词或短语出现了人类话语。平均研究质量得分在0至1的量表上为0.69(标准差为0.08)。
关于支持有记忆问题人群的虚拟代理的实验研究数量仍然较少。言语互动的细节有限,这使得难以评估互动质量和混杂参数的可能影响。此外,汇总数据的推导也很困难。需要进行更长时间和更深入对话的进一步研究。