{"title":"Informing the Development of Reminiscence Technology for Older Adults: A Prospective Study of Acceptance Determinants","authors":"Gillian Zitrin, Emmanuel Monfort","doi":"10.1049/htl2.70066","DOIUrl":null,"url":null,"abstract":"<p>Digital health technologies offer promising avenues for supporting the psychological health of the ageing population. Reminiscence therapy, a non-pharmacological intervention, holds significant potential when delivered via digital platforms. This study investigates the factors influencing the acceptance and intention to use a digital reminiscence platform among older adults. We employed an online questionnaire administered to 56 participants aged 60 to 86 years. The study integrated constructs from the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), alongside an assessment of functional reminiscence types. Our findings indicate that perceived usefulness and hedonic motivation are the primary predictors of older adults' intention to use the digital reminiscence platform. Furthermore, functional reminiscence types, specifically integrative and instrumental reminiscence, showed strong associations with higher platform acceptability. These findings highlight the importance of designing digital reminiscence tools that align with older adults’ psychosocial goals and provide meaningful, enjoyable experiences. In particular, perceived usefulness, hedonic motivation, and the relevance of instrumental and integrative reminiscence functions emerged as key acceptance factors. These insights will inform an ongoing co-design process to develop a user-centred platform that supports memory sharing, personal meaning-making, and intergenerational connection.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12927988/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare Technology Letters","FirstCategoryId":"1085","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/htl2.70066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Digital health technologies offer promising avenues for supporting the psychological health of the ageing population. Reminiscence therapy, a non-pharmacological intervention, holds significant potential when delivered via digital platforms. This study investigates the factors influencing the acceptance and intention to use a digital reminiscence platform among older adults. We employed an online questionnaire administered to 56 participants aged 60 to 86 years. The study integrated constructs from the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), alongside an assessment of functional reminiscence types. Our findings indicate that perceived usefulness and hedonic motivation are the primary predictors of older adults' intention to use the digital reminiscence platform. Furthermore, functional reminiscence types, specifically integrative and instrumental reminiscence, showed strong associations with higher platform acceptability. These findings highlight the importance of designing digital reminiscence tools that align with older adults’ psychosocial goals and provide meaningful, enjoyable experiences. In particular, perceived usefulness, hedonic motivation, and the relevance of instrumental and integrative reminiscence functions emerged as key acceptance factors. These insights will inform an ongoing co-design process to develop a user-centred platform that supports memory sharing, personal meaning-making, and intergenerational connection.
期刊介绍:
Healthcare Technology Letters aims to bring together an audience of biomedical and electrical engineers, physical and computer scientists, and mathematicians to enable the exchange of the latest ideas and advances through rapid online publication of original healthcare technology research. Major themes of the journal include (but are not limited to): Major technological/methodological areas: Biomedical signal processing Biomedical imaging and image processing Bioinstrumentation (sensors, wearable technologies, etc) Biomedical informatics Major application areas: Cardiovascular and respiratory systems engineering Neural engineering, neuromuscular systems Rehabilitation engineering Bio-robotics, surgical planning and biomechanics Therapeutic and diagnostic systems, devices and technologies Clinical engineering Healthcare information systems, telemedicine, mHealth.