Screen time among Spanish university students with disabilities: a self-organizing maps analysis

Abstract

Background Screen time can play a significant role in the health and quality of life of people with disabilities. However, there is a lack of studies on this issue among people with disabilities, and even fewer in the university setting. Thus, the aim of our study was to explore the relationships between screen time, disability grade, body mass index (BMI), physical activity and sociodemographic variables (gender and socioeconomic status) in university students with different disabilities. Methods A cross-sectional study was conducted on a sample of 1091 students with disabilities from 55 Spanish universities. Instruments used for data gathering were the Adolescent Sedentary Activity Questionnaire (ASAQ) and the International Physical Activity Questionnaire-Short Form (IPAQ-SF). A Self-Organizing Maps (SOM) analysis was carried out to explore the relationships between the variables under study. Results Participants reported high values in overall screen time (5.45 h per day/week), with computers being the media most used (2.45 h per day/week). The SOM analysis showed slightly higher screen time values in women than men. People with a high disability grade spent less screen time than those with lower disability grade. Contradictory results exist when a group of men with the highest BMI had the highest screen time and the lowest physical activity (PA) while women with low BMI show the highest screen time and PA. Conclusions Gender and disability grade played a moderating role in screen time among people with disabilities while BMI and PA do not play such a role.

Criterion validity and reliability of the International Physical Activity Questionnaire – Hungarian short form against the RM42 accelerometer

“…Contradictory results were found for genders. The group of men with the highest BMI had the highest screen time and the lowest PA while women with low BMI had the least ST and the lowest PA [ 19 ].…”

Physical Activity and Accomplishment of Recommendations in University Students with Disabilities: A Longitudinal Study

“…The IPAQ was created by Craig et al [ 25 ] and has been used worldwide to collect PA data. This questionnaire was modified to be more inclusive for assessing adapted physical activity, as in Rosenberg et al [ 26 ] (e.g., vigorous activities including wheelchair racing or handbiking, moderate activities and walking activities including wheeling) and was applied recently in Spanish studies [ 11 , 27 ]. In addition, when walking, moderate and vigorous PA exceeding 180 min was re-coded to 180 min.…”

Clustering energy support beliefs to reveal unique sub-populations using self-organizing maps

“…SOMs provide a technique for pattern identification in multidimensional space and are a handy tool for organizing large amounts of data that extend over multiple variables, such as in survey data. SOMs have been used in the social sciences to organize patterns in individual behaviors or beliefs, from tracking tourist behaviors [ 26 ], to understanding student behaviors related to learning [ [27] , [28] , [29] , [30] ], and to visualize the geography of climate beliefs in the United States [ 31 ]. This unsupervised machine learning method uses an artificial neural network to classify and cluster data in groups, introducing no bias or supervision from an interpreter in the process.…”