Development of a 24-Hour Movement Behavior Questionnaire: Reliability and Validity Testing in College Students From Low-Income Regions

In this study, we aimed to develop and test the psychometric properties of an online 24-hr movement behavior questionnaire (24 hr-MBQ). We recruited a sample of 195 undergraduate students. We developed a questionnaire based on 19 items extracted from previously validated questionnaires. We conducted reliability and construct validity assessment by classical test theory and structural validity assessment using unsupervised machine learning. In the classic test, we identified seven factors where the explained variance was 66.80% in the exploratory factor analysis, with no item excluded. We identified three clusters using unsupervised machine learning and this structure was able to distinguish differences in physical activity (physically active vs. long sleeper), sedentary behavior (all cluster comparison), and sleep time duration (all cluster comparison). Our findings suggest that the online 24 hr-MBQ is a reliable and structured construct for assessing 24-hr movement behaviors in college students.

Authors

Institutions

Publication Details

Journal
SAGE Open
Published
2025-04-01
DOI
https://doi.org/10.1177/21582440251338337
Primary Topic
Children's Physical and Motor Development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a 24-Hour Movement Behavior Questionnaire: Reliability and Validity Testing in College Students From Low-Income Regions

Lorrane Cristine Conceição da Silva, Heráclito Barbosa Carvalho, Kliver Antonio Marin, Alaiana Marinho Franco et al.
1 links
SAGE Open
Children's Physical and Motor Development
article

Development of a 24-Hour Movement Behavior Questionnaire: Reliability and Validity Testing in College Students From Low-Income Regions

Lorrane Cristine Conceição da Silva, Heráclito Barbosa Carvalho, Kliver Antonio Marin, Alaiana Marinho Franco, Augusto César Ferreira de Moraes, Marcus Vinícius Nascimento‐Ferreira, Francisco Leonardo Torres‐Leal
article en

Abstract

In this study, we aimed to develop and test the psychometric properties of an online 24-hr movement behavior questionnaire (24 hr-MBQ). We recruited a sample of 195 undergraduate students. We developed a questionnaire based on 19 items extracted from previously validated questionnaires. We conducted reliability and construct validity assessment by classical test theory and structural validity assessment using unsupervised machine learning. In the classic test, we identified seven factors where the explained variance was 66.80% in the exploratory factor analysis, with no item excluded. We identified three clusters using unsupervised machine learning and this structure was able to distinguish differences in physical activity (physically active vs. long sleeper), sedentary behavior (all cluster comparison), and sleep time duration (all cluster comparison). Our findings suggest that the online 24 hr-MBQ is a reliable and structured construct for assessing 24-hr movement behaviors in college students.

SAGE OpenVol. 15(2)
Universidade de São Paulo (BR), Universidade Federal do Piauí (BR), Universidade Federal do Tocantins (BR), The University of Texas Health Science Center at Houston (US)
Openalex Percentile: Top 84%
Children's Physical and Motor Development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development of a 24-Hour Movement Behavior Questionnaire: Reliability and Validity Testing in College Students From Low-Income Regions — Lorrane Cristine Conceição da Silva, Heráclito Barbosa Carvalho, et al. · SAGE Open (2025) | TGRS Research Map | TGRS