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. 2023 Oct 11:11:e16270.
doi: 10.7717/peerj.16270. eCollection 2023.

Physical activity, problematic smartphone use, and burnout among Chinese college students

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Physical activity, problematic smartphone use, and burnout among Chinese college students

Lianghao Zhu et al. PeerJ. .

Abstract

The aim of this study was to investigate the association between physical activity (PA), problematic smartphone use (PSU), and burnout, as well as to identify whether there is a mediating role for PSU. We recruited 823 college students (Mage = 18.55, SD = 0.83) from Wuhan, China, in December 2022, including 499 males and 324 females. Demographic information, the International Physical Activity Questionnaire-Short Form (IPAQ-SF), the Smartphone Addiction Scale-Short Version (SAS-SV), and the Maslach Burnout Inventory-Student Survey (MBI-SS) were used for assessments. Pearson correlation analysis showed that PA was significantly associated with PSU (r = -0.151, p < 0.001), PSU was significantly associated with burnout (r = 0.421, p < 0.001), and the association between PA and burnout was not statistically significant (r = -0.046, p > 0.05). The results of the mediation model test showed that PA could not predict burnout directly; it instead predicted burnout entirely indirectly through PSU. Furthermore, PSU mediated the predictive effect of PA on exhaustion and cynicism. In conclusion, there is no direct connection between PA levels and burnout. PA indirectly affects burnout through PSU, but does not fully apply to the three different dimensions of exhaustion, cynicism, and professional efficacy.

Keywords: Burnout; Cynicism; Exhaustion; Physical activity; Problematic smartphone use; Professional efficacy.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1. Results of multiple linear regression analysis.
Notes: *p < 0.05, **p < 0.01, ***p < 0.001. Regression coefficients were standardized. The parameters of the control variable (i.e., gender) were not shown in the model. Level of confidence for all confidence intervals in output: 95%.

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