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Modelling on Social Media: Influencing Young Adults’ Food Choices

Hoogstins, Eva LU (2017) PSYP01 20171
Department of Psychology
Abstract
The aim of this study was to investigate whether social media influence young adults’ food choices through social modelling. Before the main study, a pilot was conducted to improve and develop scales for measuring the influence of social modelling, as well as some control variables. In the main study, 354 young adult participants (ages 18-35) were recruited through social media and completed an online questionnaire. They were randomly assigned to a modelling or control condition by choosing one of two colors and were then either exposed to a series of Instagram screenshots depicting modelling of eating behaviour (modelling condition) or Instagram screenshots depicting the same meal on its own (control condition). The participants were then... (More)
The aim of this study was to investigate whether social media influence young adults’ food choices through social modelling. Before the main study, a pilot was conducted to improve and develop scales for measuring the influence of social modelling, as well as some control variables. In the main study, 354 young adult participants (ages 18-35) were recruited through social media and completed an online questionnaire. They were randomly assigned to a modelling or control condition by choosing one of two colors and were then either exposed to a series of Instagram screenshots depicting modelling of eating behaviour (modelling condition) or Instagram screenshots depicting the same meal on its own (control condition). The participants were then asked about their attitudes, perception of healthiness and likelihood of consumption of the meal presented. The degree to which participants use social media to make food-related decisions and their interest in the healthiness of their food were used as control variables. Results showed that there was no significant difference between attitudes, consumption, or health perception in the two conditions. Limitations of the study and their possible influence on the results are discussed, as are suggestions for future research. (Less)
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author
Hoogstins, Eva LU
supervisor
organization
course
PSYP01 20171
year
type
H2 - Master's Degree (Two Years)
subject
keywords
social modelling, eating behaviour, food choice, remote confederate, social media
language
English
id
8925466
date added to LUP
2017-09-13 12:52:02
date last changed
2017-09-13 12:52:02
@misc{8925466,
  abstract     = {The aim of this study was to investigate whether social media influence young adults’ food choices through social modelling. Before the main study, a pilot was conducted to improve and develop scales for measuring the influence of social modelling, as well as some control variables. In the main study, 354 young adult participants (ages 18-35) were recruited through social media and completed an online questionnaire. They were randomly assigned to a modelling or control condition by choosing one of two colors and were then either exposed to a series of Instagram screenshots depicting modelling of eating behaviour (modelling condition) or Instagram screenshots depicting the same meal on its own (control condition). The participants were then asked about their attitudes, perception of healthiness and likelihood of consumption of the meal presented. The degree to which participants use social media to make food-related decisions and their interest in the healthiness of their food were used as control variables. Results showed that there was no significant difference between attitudes, consumption, or health perception in the two conditions. Limitations of the study and their possible influence on the results are discussed, as are suggestions for future research.},
  author       = {Hoogstins, Eva},
  keyword      = {social modelling,eating behaviour,food choice,remote confederate,social media},
  language     = {eng},
  note         = {Student Paper},
  title        = {Modelling on Social Media: Influencing Young Adults’ Food Choices},
  year         = {2017},
}