Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.


50th Annual Convention; Philadelphia, PA; 2024

Event Details

Previous Page


Symposium #137
CE Offered: BACB
Stop Doom Scrolling and Get Into Your Life: Exploratory Assessments of Social Media Use
Saturday, May 25, 2024
4:00 PM–4:50 PM
Marriott Downtown, Level 3, Liberty Ballroom Salon A
Area: CSS/EAB; Domain: Applied Research
Chair: Nicholas Hammond (Hammond Associates Inc)
Discussant: Liz Kyonka (California State University - East Bay)
CE Instructor: Nicholas Hammond, Ph.D.

Over 80% of Canadians aged 15 to 34 regularly use social media; and over 70% of adults in the United States use at least one social media site. Social media use has many upsides (e.g., social relationships, long distance communication, dissemination of knowledge, etc.) and downsides (e.g., distracted driving, impact on interpersonal relationships, the spread of misinformation, etc.). Social media use is still a relatively new technology, and a gap exists in the state of assessment and treatment of problematic social media use within a behavioral framework. This symposium will present the results from a series of studies that investigate how a behavior analysts can shed light on factors that contribute to potentially excessive and or problematic social media use via pilot studies using novel assessments. Study 1 will describe an examination of the validity of a newly developed functional assessment questionnaire - the Social Media Use Functional Assessment (SMUFA; Malkin et al., 2021). Study 2 will describe the results obtained using the hypothetical social media purchase task (SMPT). Both studies present implications for the assessment and treatment of problematic social media use.

Instruction Level: Intermediate
Keyword(s): Behavioral Economics, Demand Analysis, Functional Assessment, Social Media
Target Audience:

Some basic knowledge of psychometrics and behavioral economics

Learning Objectives: 1. Participants will be able to discuss how behavior analysis can be applied to study and analyze social media use. 2. Participants will be able to describe the Social Media Use Functional Assessment (SMUFA) and its validity in assessing problematic social media use. 3. Participants will be able to discuss the hypothetical Social Media Purchase Task (SMPT) and the role of behavioral economics in studying excessive social media use.
Toward a Functional Assessment of Social Media Use
ALBERT MALKIN (Western University), Mark Justin Rzeszutek (University of Kentucky), Karl Fannar Gunnarsson (University of Iceland /The National University Hospital of Iceland), Aman-Preet Randhawa (Brock University), Erin Walker (Western University/Momentum ABA Services), Kristina Axenova (Western University / York University), Aly Aly Moscovitz (Western University)
Abstract: To address the need to provide a behavioral framework for social media use, this study sought to assess the validity of a newly developed functional assessment questionnaire - the Social Media Use Functional Assessment (SMUFA; Malkin et al., 2021). Participants included 380 students undergraduate and graduate students. An initial exploratory factor analysis indicated that a four-factor solution loaded attention and escape functions of social media use into different factors but loaded tangible and sensory functions into similar factors. After reducing the number of questions and factors, a three factor model (i.e., Attention, Escape, Tangible/Sensory) identified a good fit (RMSEA = .068). We also examined whether results obtained in the SMUFA were associated to other commonly used social media use scales. The SMUFA sub-scale scores generally correlated with the Social Media Engagement Questionnaire (SMEQ; Przybylski et al., 2016), Social Media Disorder Scale (SMDS; van den Eijnden et al., 2016), and Bergen Social Media Scale (BSMS; Andreassen, et al., 2016), r = .24¬–.73, with the escape subscore having the strongest relationship to the SMDS and BSMS relative to the other subscales. The SMEQ measures use within the past week, which might not be sensitive to molar patterns of problematic social media usage. Generally, the SMUFA appears to correlate with other established measures for longer term use of social media. Practical and conceptual issues related to assessing and treating problematic social media use will be discussed.
Fifteen Million Merits: A Function-Based Behavioral Economic Demand Assessment of Social Media Use
KARL FANNAR GUNNARSSON (University of Iceland /The National University Hospital of Iceland), Albert Malkin (Western University), Mark Justin Rzeszutek (University of Kentucky), Promise Tewogbola (Southern Illinois University, Carbondale), Amy Nicole Siebold (Nationwide Children's Hospital ), Eric A. Jacobs (Southern Illinois University Carbondale)
Abstract: Using a hypothetical social media purchase task (SMPT), this study sought to understand the contingencies governing the reinforcing value of social media based on its putative function. A mixed-effects modeling approach was used to evaluate group and individual behavioral patterns. Participants were 334 undergraduate and graduate students. A mixed-effects model yielded an overall R2 of .92. Accessing social media as an escape from aversive stimuli, an information source, or for positive reinforcement resulted in differing patterns of consumption, especially when compared to seeking likes/engagements. The difference was evident in both Q0 (consumption at minimal cost) and α (sensitivity to price). Individual Q0 and α values were significantly correlated across conditions. Individual model estimates were compared with social media usage questionnaires such as SMEQ, SMDS, and BSMS. Correlations were generally weak (ranging r=−.18 to .2), with the demand for likes showing the strongest correlation with the SMDS and BSMS. In conclusion, this study provides insights into the behavioral economic and operant variables influencing social media consumption patterns.



Back to Top
Modifed by Eddie Soh