If you don't see your institution, add your dataset to the main dataverse named "RepOD".
Select the dataverse to which you want to add the new dataset:
You need to Sign In/Sign Up to add a dataset.
Share this dataset on your favorite social media networks.
Demeshkant, Nataliia, 2020, "Data from Study_Students' eating behavior", https://doi.org/10.18150/6E2PIW, RepOD, V1
Learn about Data Citation Standards.
This file includes data from the study on students' eating behavior.
This study attempts: 1) to separate school students’ eating behavior patterns (healthy and unhealthy clusters) in scores of the social cognitive theory (SCT) components (self-efficacy, intention, situation, self-regulation, social support, outcome expectations, and expectancies); 2) to identify relationships between school students sociodemographic characteristics and clusters membership. The empirical material was gathered during 2018-2019 using the Australian adolescent healthy eating behaviors’ questionnaire. Eligible participants were students of state schools (n=651). The data obtained from the responses were transcribed and analyzed employing IBM SPSS v 26. Analysis of SCT component’s scores demonstrated that the availability of healthy food and the perception of healthy eating mostly differentiated students’ eating behavior patterns. Cluster compositions were determined by some demographic and socioeconomic variables. Findings showed a negative correlation between respondents’ age and healthy eating behavior. Parental age, home income, and fathers’ educational level were also significant predictors for cluster membership. Distinct eating patterns exist among Polish school students, vary by age, place of residence, level of the school, socioeconomic background, and have a major influence on children’s’ healthy behavior.
school’s students, healthy behavior, social cognitive theory, social-demographic background, cluster analysis
CC BY - Creative Commons Attribution 4.0
Please select a file or files to be deleted.
The file(s) will be deleted after you click on the Delete button.
Files will not be removed from previously published versions of the dataset.
Please select a file or files to be edited.
For selected file(s) set a license to
Please select a file or files to be downloaded.
Please select a file or files for access request.
Please select restricted file(s) to be unrestricted.
You need to Log In/Sign Up to request access to this file.
Please confirm and/or complete the information needed below in order to continue.
Asterisks indicate required fields
Access to file(s) subject to additional consent under following conditions:
The restricted file(s) selected may not be downloaded because you have not been granted access.
Click Continue to download the files you have access to download.
Are you sure you want to delete this dataset and all of its files? You cannot undelete this dataset.
Are you sure you want to lift the embargo?
Once you lift the embargo, you will not be able to set it again.
Are you sure you want to delete this draft version? Files will be reverted to the most recently published version. You cannot undelete this draft.
Use a Private URL to allow those without Dataverse accounts to access your dataset. For more information about the Private URL feature, please refer to the User Guide.
Private URL has not been created.
Are you sure you want to disable the Private URL? If you have shared the Private URL with others they will no longer be able to use it to access your dataset.
You will not be able to make changes to this dataset while it is in review.
This dataset cannot be published until RepOD is published. Would you like to publish both right now?
Once you publish this dataset it must remain published.
Are you sure you want to republish this dataset?
Select if this is a minor or major version update.
This dataset cannot be published until RepOD is published by its administrator.
This dataset cannot be published until RepOD and are published.
Are you sure you want to deaccession? The selected version(s) will no longer be viewable by the public.
Contact person for this dataset, having substantive knowledge of the data
Please fill this out to prove you are not a robot.