As shown in Table 1, female students displayed significantly higher PMPUS scores than male students (t =−3.81, p < 0.001, difference between means = 3.65). Yet, no significant difference was found between majors/grades/urban or rural sources/family structures. Further analysis demonstrated that compared to males, females represented higher problematic mobile phone use in all four dimensions as well as higher scores in interpersonal, entertainment and transaction use patterns (see Table 2). However, there is no significant difference in information seeking use pattern and self-control between genders.
Table 3 shows the correlation coefficients of the problematic mobile phone use, use patterns and self-control. As indicated, self-control was negatively correlated with PMPUS score as well as interpersonal, entertainment and transaction use patterns (r =−0.40 for PMPUS, r =−0.14–−0.18 for use patterns; p < 0.01 for all), while positively correlated with information seeking pattern (r = 0.09, p < 0.05). Additionally, the level of problematic mobile phone use positively correlated with use patterns of interpersonal, entertainment and transaction (r = 0.17–0.27, p < 0.01 for all), whereas not significant correlated with information seeking use pattern (r = 0.03, p > 0.05).
To assess whether mobile phone overuse and use patterns distinguished between students displaying different levels of self-control, participants were categorized into three groups with the first 27% as high self-control group (SCS score > 65, n = 84) and the last 27% as low self-control group (SCS score < 55, n = 78). As illustrated in Table 4, the low self-control group scored significantly higher than the high self-control group on PMPUS (t = 7.71, p < 0.001) as well as use patterns of interpersonal (t = 2.73, p < 0.01), entertainment (t = 2.65, p < 0.01) and transaction (t = 2.56, p < 0.05), whereas marginally significant less on information seeking pattern (t =−1.78,p = 0.07).
Regressing PMPUS score on gender, self-control and mobile phone use patterns are shown in Table 5. Information seeking use pattern is not included for no significant correlation with PMPUS was observed. In step 1, gender could significantly predict problematic mobile phone use (β = 0.17, p < 0.001), accounting for 3% of the variance of PMPUS. In step 2, self-control was the negative predictor of PMPUS (β =−0.40, p < 0.001), accounting for an additional 16%. In step 3, the predictive effects of gender and self-control were still significant, with use patterns accounting for 5% independently. Moreover, use patterns of interpersonal and transaction could positively predict PMPUS (β = 0.15, p < 0.01 for interpersonal; β = 0.14, p <0.01 for transaction), while the predictive effect of entertainment was not significant (β =−0.04, p > 0.05). All these variables jointly explained 24% of the variance of PMPUS.
The hypothesis model of this research assumes use patterns mediate the relationship between self-control and problematic mobile phone use. As shown in Fig. 1, the model fitting values are χ2/df = 2.26, RMSEA = 0.05, GFI = 0.97, CFI = 0.97, NFI = 0.94, TLI = 0.95, IFI = 0.97, indicating the model fit is ideal. Thus, self-control can directly predict college students’ problematic mobile phone use, and indirectly via interpersonal and transaction use patterns. The mediating effect accounted for 12.77% of the total effect.