Enhancing Home Health Mobile Phone App Usability Through General Smartphone Training: Usability and Learnability Case...

Area of Science:

• Gerontology
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Millions of older adults experience falls annually, leading to significant social and economic burdens.
• Fall prediction is crucial for preventative strategies, as falling once increases the risk of future falls.
• A smartphone-based system using smart insoles and apps was developed for continuous fall risk assessment and fall detection.

Purpose of the Study:

• To evaluate the impact of basic smartphone training on the user experience of older adults with a connected health fall prediction system.
• To determine if rudimentary training improves technology acceptance and engagement among less tech-savvy users.

Main Methods:

• 22 older adults (65-85 years) were trained on a smartphone-based fall prediction system.
• Participants were divided into two groups: one received basic smartphone training, the other did not.
• User experience was assessed via satisfaction ratings, task completion time, cues needed, and errors made.

Main Results:

• The group receiving basic smartphone training showed significantly fewer errors and required fewer cues in the initial days of system use.
• Performance differences between the groups diminished by the fourth and fifth days of use.
• Initial training positively influenced early user experience and system interaction.

Conclusions:

• Supplementary basic smartphone training is vital when introducing app-based health interventions to older, less tech-proficient populations.
• Such training can mitigate early technology rejection and boost engagement and overall user experience.
• Improved user experience can lead to greater adoption and effectiveness of digital health tools for fall prevention.