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Updated: Aug 14, 2025

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Exploring the predictors of physical inactivity in a university setting
Lawrence Bismarck Ndupu1, Mark Faghy2, Vicki Staples2
1School of Life Sciences, Faculty of Health and Life Sciences, Coventry University, 20 Whitefrairs Street, Coventry, CV1 2DS, UK. ae0031@coventry.ac.uk.
Background:
Changes in lifestyle patterns and the dependence on technology have contributed to an increase in prevalence of inactivity. To address this there is a need to identify the predictors of physical inactivity using the Theoretical Domains Framework (TDF).
Methods:
One hundred and twenty-one university administrative staff and 114 PhD students completed a survey. Physical activity (PA) levels were assessed using the Global Physical Activity Questionnaire (GPAQ), with participants scoring below 600 MET-minutes/week of total PA regarded as inactive. The predictors of physical inactivity were assessed using the Determinants of Physical Activity Questionnaire (DPAQ). Multiple regression analyses were used to identify which domains of the TDF predicted physical inactivity in the study samples.
Results:
The results indicated that 64% of administrative staff (Mean = 411.3 ± 118.3 MET-minutes/week of total PA) and 62% of PhD students (Mean = 405.8 ± 111.0 MET-minutes/week of total PA) did not achieve the recommended PA levels. The physical skills domain (t 106 = 2.198, p = 0.030) was the significant predictor of physical inactivity amongst the administrative staff. Knowledge (t 99 = 2.018, p = .046) and intentions (t 99 = 4.240), p = 0.001) domains were the significant predictors of physical inactivity amongst PhD students.
Conclusions:
The results of this study should be used as a theoretical starting point in carrying out behavioural diagnosis, which could inform the design of effective interventions to increase PA levels in universities and other settings.
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