Acceptability of Technologies to Support Early Dementia Detection: Qualitative Study With the Boston University Alzheimer’s Disease Center Cohort - Report - MDSpire
Advertisement
Acceptability of Technologies to Support Early Dementia Detection: Qualitative Study With the Boston University Alzheimer’s Disease Center Cohort
Clinical Report: Evaluation of Technology Acceptance for Early Detection of Dementia
Overview
This qualitative study explores the acceptability of digital technologies for early dementia detection among older adults and individuals with mild cognitive impairment (MCI). Findings indicate that user acceptance is crucial for the successful implementation of these technologies in clinical practice.
Background
With over 57 million individuals living with dementia globally, early detection is critical for effective intervention. Current diagnostic methods are often invasive and resource-intensive, highlighting the need for less invasive, cost-effective alternatives. Digital technologies present a promising avenue for monitoring cognitive function, but their acceptance by end users is essential for successful integration into healthcare.
Data Highlights
No numerical data or trial data was presented in the article.
Key Findings
Participants expressed varying levels of acceptance towards different digital technologies for dementia detection.
Older adults and those with MCI are potential end users of these technologies.
Successful implementation of digital tools relies on user involvement in their design and development.
Technologies must be perceived as appropriate and easy to use to gain acceptance.
Digital technologies could facilitate remote monitoring of cognitive abilities.
Clinical Implications
Healthcare professionals should consider user perspectives when integrating digital technologies for dementia detection. Ensuring that these tools are user-friendly and accessible can enhance their acceptance and effectiveness in clinical settings.
Conclusion
The study underscores the importance of user acceptance in the development of digital technologies for early dementia detection, which could significantly impact clinical practice and patient outcomes.
by Sarah Wilson, Emily Beswick, Zachary Popp, Salman Rahman, Sharandeep Bhogal, Tim Whitfield, Spencer Low, Raiyan Khan, Clare Tolley, Zuzana Walker, Rhoda Au, Sarah P Slight
