Large-scale evaluation of a computer-based learning program to increase prison staff knowledge on geriatric and...

Area of Science:

• Geriatric Medicine
• Correctional Healthcare
• Educational Technology

Background:

• Geriatric and end-of-life (EOL) care in correctional facilities is inequitable compared to community settings.
• The incarcerated population is aging, increasing the demand for specialized care.
• Technological solutions like computer-based learning (CBL) can bridge care gaps.

Purpose of the Study:

• To develop and evaluate a scalable computer-based learning (CBL) system for geriatric and EOL care in correctional settings.
• To improve the quality of care for aging and dying incarcerated individuals.
• To reduce disparities in geriatric and EOL care within prisons.

Main Methods:

• A mixed-methods approach was used to develop an interactive CBL for multidisciplinary correctional staff.
• The CBL was iteratively tested and refined before a full-scale evaluation.
• A pre/post-intervention design was employed across 7 correctional sites with 173 participants completing post-tests.

Main Results:

• Post-tests showed significant improvements in staff knowledge (cognitive measure) and attitudes (affective measure) regarding geriatric and EOL care (p < 0.01).
• The CBL was found to be acceptable, feasible, and usable in correctional environments.
• No significant differences in outcomes were observed based on sex or ethnicity.

Conclusions:

• The developed CBL is an effective tool for enhancing correctional staff's capacity to care for aging and dying incarcerated persons.
• This e-learning approach shows promise in addressing the growing healthcare needs of the elderly prison population.
• Implementing such training can contribute to more equitable geriatric and EOL care within correctional systems.