RESUMO
BACKGROUND: One of the most complicated medical needs of older adults is managing their complex medication regimens. However, the use of technology to aid older adults in this endeavor is impeded by the fact that their technological capabilities are lower than those of much of the rest of the population. What is needed to help manage medications is a technology that seamlessly integrates within their comfort levels, such as artificial intelligence agents. OBJECTIVE: This study aimed to assess the benefits, barriers, and information needs that can be provided by an artificial intelligence-powered medication information voice chatbot for older adults. METHODS: A total of 8 semistructured interviews were conducted with geriatrics experts. All interviews were audio-recorded and transcribed. Each interview was coded by 2 investigators (2 among ML, PR, METR, and KR) using a semiopen coding method for qualitative analysis, and reconciliation was performed by a third investigator. All codes were organized into the benefit/nonbenefit, barrier/nonbarrier, and need categories. Iterative recoding and member checking were performed until convergence was reached for all interviews. RESULTS: The greatest benefits of a medication information voice-based chatbot would be helping to overcome the vision and dexterity hurdles experienced by most older adults, as it uses voice-based technology. It also helps to increase older adults' medication knowledge and adherence and supports their overall health. The main barriers were technology familiarity and cost, especially in lower socioeconomic older adults, as well as security and privacy concerns. It was noted however that technology familiarity was not an insurmountable barrier for older adults aged 65 to 75 years, who mostly owned smartphones, whereas older adults aged >75 years may have never been major users of technology in the first place. The most important needs were to be usable, to help patients with reminders, and to provide information on medication side effects and use instructions. CONCLUSIONS: Our needs analysis results derived from expert interviews clarify that a voice-based chatbot could be beneficial in improving adherence and overall health if it is built to serve the many medication information needs of older adults, such as reminders and instructions. However, the chatbot must be usable and affordable for its widespread use.
RESUMO
BACKGROUND: With more than 1 million older adults being abused each year, it is imperative for nurses to be knowledgeable about signs and symptoms of elder abuse, assessment, and interventions. This article describes a three-part learning strategy consisting of lecture, simulation using standardized patients (SPs), and debriefing to educate prelicensure nursing students about how to identify, assess, and report elder abuse. Furthermore, the effects of the teaching strategies were assessed. METHOD: Students received a lecture on elder abuse, followed by a simulation with an SP and debriefing. Pre- and posttests were used to assess knowledge, skills, and attitudes about elder abuse. RESULTS: Significant differences were found in pre- and posttest results for knowledge and skills. There were no significant differences in attitude. Teaching strategies affected learning, and students reported increased knowledge and skills in identifying abuse and advocating for vulnerable older adults. CONCLUSION: Lecture and SP simulation followed by debriefing was an effective approach to educate prelicensure nursing students about elder abuse. [J Nurs Educ. 2020;59(6):331-335.].