Mariel Richter
CONTRIBUTOR
In a new design method used by UNO’s Nebraska Center for Justice Research (NCJR), researchers used a new method of “time diaries” to understand how young adults in college transition from living at home with parents to greater independence, as well as college drinking. Dr. Amy Anderson and Dr. Samantha Clinkinbeard, with UNO students Timothy Barnum and Rita Augustyn used traditional methods along with a burst of text messages.
Ecological momentary assessments (EMAs) are the text messaging features researchers used to track whether changes in mood are positive or negative and could open the door for understanding more complicated psychological changes, said Anderson.
This real-time data offers more information than the traditional reflection data, where participants volunteer their “burst” design with cell phones in additional to traditional panel design to collect information about students’ relationships.
NCJR said that studying these transitions could help researchers understand the mood fluctuations of domestic batterers and released offenders from prison. This could help with “successful re-entry into the community, the after-school activities of at-risk adolescents, the cravings and/or relapses of drug and alcohol abuses.”
Asking a patient with fluctuating moods “How have you been feeling,” may not give accurate information, as this is a reflective question and may not accurately reflect the patients’ past mood, according to Debbie S. Moskowitz and Simon N. Young, researchers of EMA.
“Transitions are important because new opportunities can alter beliefs, attitudes, and behaviors, potentially leading to turning points in the life course trajectory in a short period of time,” according to R.J. Sampson and J.H. Laub. Transitions in life that occur very quickly are difficult to track for researchers. Tracking developmental changes or periods of emotional exploration or establishing personalities mark changes in students’ lives, according to NCJR’s research paper.
The design is good for capturing data that has intra-day variation like mood and stress, or if you want to eliminate differences between people and look at how people change over time, said Anderson.
The research can be found at: http://link.springer.com/article/10.1007/s40865-016-0027-4
