MILLER-THESIS-2020.pdf (893.34 kB)
Download file

Using EMA to Evaluate Companionship, Mood, & Helping Behavior in a Sample of Racial/Ethnic Minority Youth

Download (893.34 kB)
thesis
posted on 01.05.2020, 00:00 by Alysa N Miller
Using data collected via ecological momentary assessment (EMA), this work considers the questions of with whom low-income, racial/ethnic minority youth spend their time and how this relates to mood and prosocial behavior. Data for this study were collected during the summer of 2016 from a sample 50 of low-income youth living in Chicago. l. The sample is 56% female, 82% Black, 18% Latino, and the average age was 14.98 years (SD = .73). During the one-week assessment period, youth were asked to carry a smartphone and respond to EMAs five times each day (for a total of 35 assessments per youth). At each assessment, youth indicated who they were with (e.g. parent, peer), prosocial behaviors engaged in over the past three hours (e.g. In the past three hours have you helped someone?), and current mood (anxious, depressed, happy, stressed, and sleepy). Descriptive results show youth most often reported being with their mother (43%) or at least one sibling (43%) during the assessments. Multilevel modeling, where companionship indicators were decomposed into between- and within-person components, were used to estimate relationships with mood and helping behavior. Results revealed that youth were happier when with friends compared to times when they were not with friends. Youth were more likely to report helping someone when with mom or extended family, and less likely to report helping someone when with dad. In-the-moment assessment strategies offer nuanced understanding of how and with whom youth spend their time. This is critical for developing targeted intervention and prevention programs to support healthy youth development.

History

Advisor

Roy, Amanda L

Chair

Roy, Amanda L

Department

Psychology

Degree Grantor

University of Illinois at Chicago

Degree Level

Masters

Degree name

MA, Master of Arts

Committee Member

Mermelstein, Robin Zinsser, Kate

Submitted date

May 2020

Thesis type

application/pdf

Language

en

Usage metrics

Categories

Exports