Do you struggle with ways to feel more relaxed or calm when you are stressed? Do you identify as African American, Black, Hispanic, and/or Latino (a/e/x)? If so, you may be able to take part in a study to see whether a home-based training program can improve emotional well-being and heart health. Compensation provided.

Is your child being hospitalized at UNC Youth Behavioral Health for suicidal thoughts or behaviors? If so, you may be eligible to participate in a research study to identify the risk factors associated with recurrence of suicidal thoughts after psychiatric hospitalization. Both you and your child must participate to be eligible for the research study. Compensation provided.

The purpose of this research study is to gain insight into how people interact with some of Spotify's features including Discover Weeklyl, DJ, and Daylist. We want to learn more about the factors that influence how users discover new music when using these features.

The purpose of this research study is to investigate how human interpret some predictive learned by AI systems when detecting deceptive hotel reviews and how AI explanations can shape human understanding. For instance, the AI system learns that words like "floor" and "bathroom" are highly predictive of genuine reviews and words like "husband" and "luxury" are highly predictive of deceptive reviews. While the AI system highlights these words by learning from the data, the association between these words and the outcome are not easy to comprehend for humans. Thus, our goal of this research is to investigate how participants interact with machine-generated explanations that are unintuitive, and how participants make use of our developed visualizations and tools to make sense of these unintuitive features.

In this study, we want to see how giving birth affects stress chemicals in the body. We will focus on a stress hormone called cortisol and check its levels in people who gave birth, from 3 to 12 months after giving birth.

This study seeks to understand how different things about your life, like your upbringing, might affect how you feel about having kids in the future. By looking at how your background and experiences shape your thoughts on having children, we hope to learn more about what factors influence people's decisions about starting a family.

Do you have problems with your thinking or memory? Or a parent or sibling with dementia? If so, we'd like you to join this registry about the brain and Alzheimer's disease. In return for providing us with a little bit of your health history and background, we will connect you with researchers doing studies you can join, without obligation. Many studies pay a stipend and some offer a possible treatment.

Have you ever noticed yourself repeatedly thinking or doing specific things? Have you experienced symptoms of OCD now or in the past (even if you did not seek treatment)? Do you identify as Black? If you have (or think you might have) OCD, you may be able to participate in a study to learn more about OCD and new methods for prevention and treatment. Participants will receive $50.

Have you ever been concerned about your eating? We're inviting adults in the U.S. who have ever had anorexia nervosa, atypical anorexia nervosa, bulimia nervosa, binge-eating disorder, or avoidant/restrictive food intake disorder (ARFID) at any point in their life to take our survey. No official medical diagnosis is required. Common signs of different eating disorders may include: restricting the amount or type of food you eat or eating excessive amounts of food in one sitting. Some other possible signs are making yourself throw up, using diet pills or laxatives, excessively exercising, or fasting to alter your weight. Only with your help can we the causes and potential cures for these disorders. Eligible participants who complete Core Questionnaires and return their saliva sample will receive a $30 gift card.

The purpose of this research study is to investigate how human interpret some predictive learned by AI systems when detecting deceptive hotel reviews and how AI explanations can shape human understanding. For instance, the AI system learns that words like "floor" and "bathroom" are highly predictive of genuine reviews and words like "husband" and "luxury" are highly predictive of deceptive reviews. While the AI system highlights these words by learning from the data, the association between these words and the outcome are not easy to comprehend for humans. Thus, our goal of this research is to investigate how participants interact with machine-generated explanations that are unintuitive, and how participants make use of our developed visualizations and tools to make sense of these unintuitive features.