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. 2022 Oct 11:1-22.
doi: 10.1007/s12144-022-03745-0. Online ahead of print.

Tolerance for ambiguity, reappraisal, and suppression mediate the relationship between problematic internet use and procrastination

Seyed Javad Emadi Chashmi  1 , Jafar Hasani  2 , Daria J Kuss  3 , Mark D Griffiths  3 , Fatemeh Shahrajabian  2
Affiliations

Tolerance for ambiguity, reappraisal, and suppression mediate the relationship between problematic internet use and procrastination

Seyed Javad Emadi Chashmi et al. Curr Psychol. .

Abstract

The current scientific literature lacks studies on the relationship between problematic internet use (PIU) and procrastination, especially regarding the mediating mechanisms underlying this relationship. The present study examined the association between procrastination and PIU, as well as determining the mediating roles of tolerance for ambiguity, reappraisal, and suppression. The conceptual model was tested using data collected from 434 Iranian college students. The participants completed a number of psychometric scales assessing procrastination, PIU, tolerance for ambiguity, reappraisal, and suppression. Structural equation modeling was used to test the hypothesized model. Results showed that PIU, tolerance for ambiguity, and suppression were positively associated with procrastination, and that there was a negative association between reappraisal and procrastination. Moreover, the mediation analysis indicated that tolerance for ambiguity, reappraisal, and suppression fully mediated the association between PIU and procrastination. However, it is also possible to interpret the results as suggesting that PIU is unimportant as a predictor for procrastination once mediators are controlled for.

Keywords: Problematic internet use; Procrastination; Reappraisal; Suppression; Tolerance for ambiguity.

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Conflict of interest statement

Conflict of interestNone.

Figures

Fig. 1
Fig. 1
Final results of the research model
Fig. 2
Fig. 2
CFA for internet addiction scale (standard solution). Chi-square = 268.6, df = 170, p-value < 0.0001, RMSEA = 0.044
Fig. 3
Fig. 3
CFA for internet addiction scale (t-values). Chi-square = 268.6, df = 170, p-value < 0.0001, RMSEA = 0.044
Fig. 4
Fig. 4
CFA for academic procrastination (standard solution). Chi-square = 660.96, df = 324, p-value < 0.0001, RMSEA = 0.053
Fig. 5
Fig. 5
CFA for academic procrastination (t-values). Chi-square = 660.96, df = 324, p-value < 0.0001, RMSEA = 0.053
Fig. 6
Fig. 6
CFA for tolerance for ambiguity (standard solution). Chi-square = 267.52, df = 209, p-value < 0.0001, RMSEA = 0.041
Fig. 7
Fig. 7
CFA for tolerance for ambiguity (t-values). Chi-square = 267.52, df = 209, p-value < 0.0001, RMSEA = 0.041
Fig. 8
Fig. 8
CFA for emotion regulation (standard solution). Chi-square = 50.66, df = 34, p-value-0.00028, RMSEA = 0.042
Fig. 9
Fig. 9
CFA for emotion regulation (t-values). Chi-square = 50.66, df = 34, p-value-0.00028, RMSEA = 0.042
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