The study is designed to investigate how people find and learn information using digital search systems. With the World Wide Web and other digital tools, tons of information is placed at the tips of our fingers. For many years, search engines were the predominant tool for information retrieval on the web. However, recent developments in artificial intelligence (AI) have resulted in increasing use of AI chatbots to find and learn information. This study compares how users interact with search engines and chatbots to find and learn information to better understand the cognitive processes involved in digital search and how these systems support learning.

Our study focuses on finding potential cases of Perinatal Depression amongst women in Za'atari Refugee Camp for Syrian refugees in Jordan. We created a paper survey that took questions from the Edinburgh Perinatal Depression Scale, the official questionnaire for assessing individuals for symptoms of this mental condition, and plan to give copies of the survey to patients at the Women and Girls Comprehensive Centre run by the Jordan Health Aid Society (JHASi). We are conducting this study because, while JHASi has information on some mental health conditions in Za'atari, they have no data on Perinatal Depression. According to this research, it seems many women are exposed to situations that could result in them developing Perinatal Depression. By assessing the women in the clinic for symptoms of this condition, our study will help fill this gap in JHASi's data and allow the organization to create new mental health support systems.

The purpose of this research study is to learn how people's experiences at work relate to their health.

This study seeks to build novel understanding of the household-level impacts of extreme weather events (like flash floods) on motor vehicle ownership and travel patterns.

We are studying how to make medical test results easier for patients to understand. Pathology reports, which explain what doctors find in tissue samples, are often written for medical professionals and can be hard for patients to read. In this study, we are testing whether artificial intelligence (AI) can help explain these reports in plain language. Patients having a routine screening procedure will read a sample report with or without an AI-generated explanation. Then they will answer questions about how well they understood the report and how they felt about it. We want to learn if using AI helps people better understand their health information and feel more confident making decisions. This will help improve the way test results are shared in the future.

This study seeks to understand how best to increase knowledge about clinical trials, best way of communicating information about clinical trials, and suggestions for improving clinical trial participation particularly among African Americans (AA).

Understand the extent research on CABs, supplementing that knowledge with insights from participatory action research with approximately 125 local government practitioners.

The purpose of this study is to examine people's intentions to perform different health behaviors, and what individual factors predict these intentions.

The purpose of this study would be to establish an LCC training simulation for civilian first responders (i.e., paramedics, search and rescue, etc.).

Identify acceptable and feasible school-based interventions for adolescent obesity prevention among adolescent girls in an informal settlement in Kenya