Promoting Adherence to Enhance the Early Detection and Treatment of Cognitive Decline
The Florida State University Center for Research and Education on Aging and Technology Enhancement, under the direction of Drs. Neil Charness and Walter Boot, seeks on campus DIS students for the Fall 2022 and Spring 2023 semesters. Our projects examine how computer technology can be successfully designed to benefit aging adults, with an emphasis on reducing social isolation among older adults.
Currently, we are working on closing our PRISM 2.0 study, and will be beginning our new projects, APPT and ENHANCE. The ultimate goal of these new projects will be to develop a personalized technology-based prospective memory aid for individuals with MCI, TBI, and Post-stroke Cognitive Impairment (PSCI) to help them plan for, and remember to perform, everyday activities that support health, finances, well-being, and social connectedness.
DIS will be responsible for recruitment calls, conducting participant appointments, and general data entry. Students must also be CITI certified in the following certifications:
- Human Subjects Research
- Responsible Conduct of Research
- Good Clinical Practice
If students are not CITI certified we will instruct them on how to begin these courses virtually, and they will be expected to complete the courses within 3 weeks of classes beginning.
For more information, please contact Antonio Rolon at: rolon@psy.fsu.edu
**Face-to-face and remote DIS options available**
Requirements for enrolling:
- Minimum GPA of 3.0
- Sophmore, Junior, or Senior class standing
- Ability to closely follow instructions and work both independently and as part of a team
- Microsoft Excel proficiency is a plus
The aims of the Adherence Promotion with Person-centered Technology (APPT) project are to promote early detection and treatment of age-related cognitive impairment and dementia by 1) enhancing adherence to cognitive intervention and assessment protocols, 2) improving understanding of barriers to long-term adherence, and 3) assisting in the development of algorithms for predicting and preventing adherence failures.