94
Views
0
CrossRef citations to date
0
Altmetric
Research Article

The Impact of Effort Attributions on the Quality of Esteem Support Messages Produced

ORCID Icon, , , , , ORCID Icon, , , & show all
Pages 302-321 | Published online: 15 Dec 2023
 

ABSTRACT

Research indicates that receiving esteem support has multiple benefits, however, less is known about the factors that influence the production of esteem support messages of varying quality. We examine how characteristics of potential recipients shape esteem support message production, specifically, how recipients’ effort to help themselves may alter emotions and motivations of potential esteem support providers, affecting the quality of esteem support messages produced. A between-subjects experiment tested predictions derived from the attribution-emotion-action model (AEAM) and the cognitive-emotional theory of esteem support messages (CETESM). Results are consistent with a process of serial mediation where recipient effort causes effort attributions in potential support providers, which increase sympathy, which increases helping motivation, leading to more high-quality content in esteem support messages. Anger, although negatively associated with effort attribution, did not appear to play a mediating role in esteem support message production within the job search context. Theoretic and pragmatic implications are discussed.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Reed M. Reynolds

Reed M. Reynolds (PhD, Michigan State University) is an assistant professor in the Communication Department at University of Massachusetts, Boston. He studies mechanisms of social influence in the context of health behavior, misinformation diffusion, and social networks.

Amanda J. Holmstrom

Amanda J. Holmstrom (PhD, Purdue University) is a professor in the Department of Communication at Michigan State University Her work focuses primarily on the communication of various forms of social support, including informational, tangible, network, emotional, and esteem support.

Samantha J. Shebib

Samantha J. Shebib (PhD, Michigan State University) is a social scientist who studies communication in a variety of contexts with a dark side perspective, shedding light on the paradoxical, dialectical, hidden, and forbidden facets of human relating.

David D. Clare

David D. Clare (PhD, Michigan State University) is a Principal Consultant at Sage Analysis Group.

Ashley A. H. Edwards

Ashley A. H. Edwards (PhD, Michigan State University) is an associate professor in the Department of Communication Studies at University of Wisconsin, La Crosse. She studies interpersonal communication, social support, computer-mediated communication, and teaching in a multi-modal environment.

Allison P. Mazur

Allison P. Mazur (MA, Michigan State University) is a doctoral candidate in the Department of Communication at University of California, Santa Barbara. She studies gender-based violence and how interpersonal relations can play a role in preventing sexual violence and supporting those who have experienced it.

Travis L. Poland

Travis L. Poland (MA, Michigan State University) works for the Michigan Department of Health and Human Services.

Morgan E. Summers

Morgan E. Summers (MA, Ball State University) is a math teacher at American Fork High School.

Haley R. Royer

Haley R. Royer (MA, Michigan State University) works for the Hanover Insurance Group.

Lu Zhang

Lu Zhang is a graduate student in the Department of Communication at Michigan State University.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 144.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.