Mind Window

The University of Arizona

O aplikaciji

Do you ever wonder if there is some rhyme or reason to how you think? How often are your thoughts focused on troubling topics, the past, the future, or memories and imaginative thinking? Mind Window helps you to track the way that you uniquely think and discover how these patterns of thought may affect your well-being.

Mind Window is part of a scientific research project, developed at the University of Arizona, to develop a large international database of thoughts in daily life. The purpose of this app is to identify patterns of thought by asking questions about user’s thoughts at random moments throughout their day-to-day life.

FEATURES:

- Allows you to help develop an international research database of patterns of thought

- Check-ins provide a convenient reminder so that you can track your thoughts throughout the day

- Statistics:
- Let you discover what kinds of thoughts are commonly on your mind
- Learn about the patterns of thought you have
- Receive feedback that helps you identify how your thinking may impact your well-being
- Explore changes in thought patterns over time

- Customization:
- Choose an assistant to serve as your guide while using the app
- Explore results by day, week, month, or all times

- Using Mind Window will allow you the opportunity to participate in upcoming and collaborative research in psychology, genetics, and neuroscience.


*** Please note that Mind Window is a tool for use in scientific research. Users must be at least 18 years of age and fluent in English. An Institutional Review Board responsible for human subjects research at The University of Arizona reviewed this research project and found it to be acceptable, according to applicable state and federal regulations and University policies designed to protect the rights and welfare of participants in research.

Što je novo

A fix for a crash when using the help option in the "On-Task" statistics has been made. Additionally, Mind Window now limits font scaling so that text is no longer cutoff when using high-value scaling.