Don Roosan|Jay Chok|Mazharul Karim|Anandi V. Law|Andrius Baskys|Angela Hwang|Moom R. Roosan
Artificial Intelligence–Powered Smartphone App to Facilitate Medication Adherence: Protocol for a Human Factors Design Study
Western University of Health Sciences|Keck Graduate Institute|Claremont Colleges|Western University of Health Sciences|Western University of Health Sciences|Western University of Health Sciences|Western University of Health Sciences|Chapman University
medication guides consisting crucial interactions side effects extensive complex due exhaustive information patients retain necessary medication information result hospitalizations medication nonadherence gap exists understanding patients cognition managing complex medication information however advancements technology artificial intelligence ai allow us understand patient cognitive processes design app better provide important medication information patientsour objective improve design innovative ai human factorbased interface supports patients medication information comprehension could potentially improve medication adherencethis study three aims aim 1 three phases 1 observational study understand patient perception fear biases regarding medication information 2 eyetracking study understand attention locus medication information 3 psychological refractory period prp paradigm study understand functionalities observational data collected audio video recordings gaze mapping time prp total 50 patients aged 1865 years started least one new medication developed visualization information cognitive status 34 cognitive screening using ticsm test health literacy level included aim study aim 2 iteratively design evaluate aipowered medication information visualization interface smartphone app knowledge gained component aim 1 interface assessed two usability surveys total 300 patients aged 1865 years diabetes cardiovascular diseases mental health disorders recruited surveys data surveys analyzed exploratory factor analysis aim 3 order test prototype twoarm study design aim include 900 patients aged 1865 years internet access without cognitive impairment least two medications patients sequentially randomized three surveys used assess primary outcome medication information comprehension secondary outcome medication adherence 12 weekspreliminary data collection conducted 2021 results expected published 2022this study lead future aibased innovative digital interface design aid improving medication comprehension may improve medication adherence results study also open future research opportunities understanding patients manage complex medication information inform format design innovative aipowered digital interfaces medication guidesprr110219621659