User‐led Design of a Self‐administered Smartphone‐based Learning and Memory Assessment. (20th December 2022)

• Record Type: Journal Article
• Authors: Edgar, Chris J.; Simic, Veronika; Stephens, David; Murray, Erica; Maruff, Paul
• Is Part Of: Alzheimer's & dementia. Volume 18(2022)Supplement 7
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-20
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.066067
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: The International Shopping List test (ISLT) is a verbal word list learning assessment set within a realistic shopping list context, supporting ease of cultural adaptation, and addressing content validity and patient relevance. Improvements to and the wide adoption of natural language processing (NLP) software has enabled the possibility for self‐administered tests of verbal learning. A beta version of a self‐administered, smartphone‐application (app) was developed, using the virtual assistant and NLP: the "List Learning and Memory Assessment (Lila TM )". Method: To ensure usability of the app, a user led design process was followed. A beta version was created via several rounds of focus group development in older adults. 12 older adults were then recruited for interviews (8 healthy and 4 with Mild Cognitive Impairment). Participants were pseudo‐randomly assigned to participate in interviews during test performance, using either iPhone or Nokia devices. Each participant completed the test and provided concept elicitation feedback. Qualitative analysis of the interview results was performed using thematic coding. Result: Key positive themes included the ease with which the app could be navigated, and the clarity of visual display and instructions, whilst an important negative theme was the length of time between different components of the test. Conclusion: Qualitative analysis of concept elicitation interviews has suggested several areas of improvement to the beta‐app, including improvements to performance that shorten processing and wait times between test components. The clarity of the visual display and test instructions were well supported.