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A Brief Training Program to Support the Use of a Digital Pill System for Medication Adherence: Pilot Descriptive
Peter R Chai1,2,3,4, Maria J Bustamante3, Georgia Goodman3,5
1Department of Emergency Medicine, Brigham and Women's Hospital, Boston, MA, United States.
JMIR Formative Research
|April 23, 2021
Summary
A digital pill system (DPS) training program effectively taught users how to operate the technology, ensuring accurate adherence data collection. The program addressed technical challenges and was well-received by participants.
Area of Science:
- Digital Health
- Medication Adherence Technology
- Health Informatics
Background:
- Digital Pill Systems (DPSs) integrate ingestible sensors to directly measure medication ingestion.
- Effective user training is crucial for obtaining actionable adherence data from DPS.
Purpose of the Study:
- To develop and pilot a training program for Digital Pill System (DPS) operation.
- The program was grounded in the Technology Acceptance Model to enhance user understanding and adoption.
- To assess the efficacy and user experience of a novel DPS training intervention.
Main Methods:
- A two-part training program combining in-person instruction and text message support was implemented.
- The study involved HIV-negative men who have sex with men using DPS for pre-exposure prophylaxis adherence monitoring.
- Data collected included technical support requests, issue resolution, and qualitative user feedback.
Main Results:
- 15 participants completed the training program with high acceptability.
- Seven technical challenges were reported, primarily related to device connectivity, charging, and app operation.
- Most technical issues were resolved remotely, with positive user feedback on both training components.
Conclusions:
- A brief, two-part DPS training program is effective in preparing users to operate the system.
- The training addresses potential technical challenges, facilitating successful DPS implementation.
- User-centered training enhances the collection of reliable digital health data.
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