The results of this study illustrated that interventions based on the HAPA model can effectively improve psychological cognitive factors of the excessive Internet use behaviors of Chinese rural adolescents. After the interventions, the rate of excessive Internet users reduced by 30%. Among participants, the rate of average daily Internet time on weekends ≥ 4 h dropped from 57.2–39.1%, and the rate of usually daily game time ≥ 2 h reduced from 51.1–35.2%. Although no improvement was observed in average daily Internet time on weekdays ≥ 2 h and online overnight in the past thirty days, the rates after intervention did not increase. Meanwhile, the interventions improved outcome expectancy, intention, and maintenance self-efficacy of rural adolescents.
Previous school-based studies were designed to improved Internet use behaviors of urban adolescents. The studies focused on health education courses have positive effects on game time, while no impact on daily online time (17, 35). Different from urban adolescents, Internet use behaviors of rural adolescents have not received enough attention and lacked targeted intervention measures. This may be the reason when facing the rapidly developing Internet rural adolescents lack sufficient correct knowledge and lack of self-efficacy, which may lead to excessive Internet use. As far as we know, this is the first intervention study aimed to improve rural adolescents’ excessive Internet use. And the results illustrate that the HAPA model can be used to develop effective interventions for rural adolescents.
In this study, the changes in outcome expectancy, intention, and maintenance self-efficacy were key indicators to the reduction of Internet use. Previous studies have claimed that outcome expectancy is the strongest predictor of intention (36–38). Adolescents are inclined to generate the intention of reducing online time based on the awareness that reduction of online time could bring benefits for themselves such as improving the eyesight and academic performance.
Meanwhile, intention is the most predictable factor for future behaviors (20). The generation of intentions is a prerequisite for planning and transforming planning to behaviors. Besides, maintenance self-efficacy is fundamental in the production of behaviors. Individuals with high maintenance self-efficacy are more likely to convert planning into behaviors and believe that they can overcome the potential obstacles when adopting aim behavior (39). Interventions based on the HAPA model lead to changes in behaviors by enhancing the cognition of these three key variables of the participants, so as to investigate the applicability and effectiveness of HAPA model in intervening excessive Internet use. Interestingly, there were certain differences in the HAPA variable scores of adolescents with different genders and different grades after the intervention, which denotes differences in their perception corresponding to targeted intervention. It meant that boys should strengthen the interventions of action self-efficacy, and younger adolescents are supposed to focus on planning and maintaining self-efficacy.
The results of SEM identified that the HAPA model has good applicability in rural adolescents’ Internet use behaviors. In model 1, most paths had been effectively verified, apart from risk perception to intention, and maintenance self-efficacy to Internet use behaviors. We found that there was only an indirect impact between maintenance self-efficacy and Internet use behaviors, while the direct effect was not observed. It demonstrated that for Internet use behaviors of adolescents, the role of maintaining self-efficacy was to promote planning convert into behaviors and to maintain the implementation of planning. Further, the strong correlation between action self-efficacy and maintenance self-efficacy had been verified (20).
Different from the HAPA hypothesis, this study did not find the association between risk perception and intention similarly to other studies (36, 40, 41). It might be related to the description of the items. In this study, the items of risk perception were described as “If you compare your current Internet use behaviors to that of individuals with the same gender and age, how likely do you think…”.They might not deem that their Internet use behaviors were worse than that of same-gender peers, nor they would encounter the risks mentioned in the items (42). Risk perception having little effect on intention and behaviors have been reported by previous studies applying the HAPA model in different behaviors (20, 36, 41, 43). Behaviors such as taking medicines and vaccination could reduce the risk of diseases, closely associated with risk perception. On the contrary, the risks brought by daily lifestyles (including Internet use behaviors, physical activity, and diet) were not easy to be perceived, which may attenuate the impact of risk perception on behaviors in the general population. It was difficult for adolescents to perceive the risk of excessive Internet use, for whom the comprehension and perception abilities were slightly lower than those of adults.
It is worth mentioning that the ideal results of interventions should be obtained from the comparison between the intervention school and the control school. However, because of the heavy academic pressure, the control school had added a strict system of the residence in the research process, and forbidden students to bring mobile phones and any other electronic products into campus. And students can go home for only 2-day holidays each month. While the experimental school didn’t have such rules. Therefore, it is impossible to directly compare the change degree of excessive Internet use in the experimental school with the control school. Nevertheless, it could be seen that the psychological cognitive factors from HAPA in the experimental school were improved more than those in the control school (Appendix Table 1).
There were some limitations to this study. First, the data came from the self-reports of the participants, and there might be reporting bias. Second, previous studies confirmed that planning could be divided into action planning and coping planning. Action planning is important for the beginning of behaviors, and coping planning is crucial to the maintenance of behaviors(44). However, this study did not refine them. Third, in the research process, the subjects of the control school were affected by the external environment such as the strict management system, which made it difficult to directly compared the status of excessive Internet use in the experimental school with the control school. It is hoped that future researches can improve this deficiency in this study and obtain more realistic results to illustrate the effectiveness of interventions based on the HAPA model.
Despite these limitations, the strengths of this study could not be ignored. It was the first study applying the HAPA model to intervene in adolescents’ excessive Internet use behaviors, which could provide new ideas for understanding the cognitive process of Internet use behaviors in adolescents. Further, longitudinal data in this study were used for analysis to better illustrate the continuous process of cognitive, intention, and behavioral change. Since the transformation of intention, planning and behaviors takes time, the longitudinal design was able to describe the transformation process. Besides, targeted intervention measures were formulated based on the HAPA model, and a positive effect had been obtained in the Internet use behaviors of adolescents. This study not only verified the effectiveness of the HAPA model in guiding behavioral interventions but also proposed several effective measures to improve rural adolescents’ excessive Internet use behaviors.