This data was collected using the custom made application "Tymer", which recorded smartphone use data and requested participants to fill in micro-surveys throughout the day, and surveys that participants filled out at either a briefing or debriefing session. The following describes the data collected and used for a study conducted by Beryl Noë, Liam D. Turner, David E. J. Linden, Stuart M. Allen, Gregory R. Maio and Roger M. Whitaker. This project seeks to determine the feasibility of using everyday human interaction with the smartphone to detect mood states for mental health monitoring. Smartphones are an increasingly useful proxy for human behaviour, accompanying their owners for a significant proportion of each day and mediating access to the web, diverse services and communication. Our hypothesis is that from focusing on daily patterns of human smartphone usage we can develop an accurate approach to mental health monitoring that is effective and unobtrusive.

Seventy-six participants were recruited through posters and online advertisement at Cardiff University, UK. Participants were selected on two aspects: they needed to own a smartphone running Android 4.4 or higher, and they had to have no history of mental illness. The study was approved by the ethics committee of the School of Psychology, Cardiff University and all participants provided written, informed consent. Thirtynine participants were male, 36 female, and 1 participant chose not to disclose their gender. The participants were all between 19 and 46 years old (M = 24.94, SD = 5.69). Data was collected from participants through 3 different ways: (1) surveys administered in a lab setting at a briefing session and at a debriefing session that were at least 8 weeks apart (2) raw usage data obtained from a custom-made app that participants had installed on their phone for 8 weeks, starting after the briefing session (3) micro-surveys consistent of 1 to 3 questions administered through the notifications sent by the app everyday for 8 weeks