Two PhD in Psychology students' research work were selected and given an “Honorable Mention” for the 2021 RISE Research Award by the Association for Psychological Society (APS), one of the largest and most prestigious conferences in Psychology in the U.S. The selected researches were “Inhibitory Control Mediates the Relation between Intrusive Parenting and Externalising Behaviors in Socioeconomically Disadvantaged Children: A Structural Equation Analysis" by first-year student, Germaine Tng and "Mental Disengagement Mediates the Effect of Rumination on Smartphone Use: A Latent Growth Curve Analysis" by third-year student, Shuna Khoo.
About Inhibitory Control Mediates the Relation between Intrusive Parenting and Externalising Behaviors in Socioeconomically Disadvantaged Children: A Structural Equation Analysis
This research sheds light on the cognitive mechanism underlying the relation between intrusive caregiving practices (i.e., excessive control, autonomy restriction) and externalizing behaviors (e.g., aggression, hyperactivity, conduct problems) in toddlers from low-income families (N=1,292, Mage =35 months). Using structural equation modeling, we found that the latent factor of inhibitory control (i.e., ability to suppress a prepotent, dominant response), based on three performance-based measures, significantly mediated the effect of intrusive parenting on externalizing behaviors during early childhood when key covariates of gender, ethnicity, household income, and expressive verbal abilities were controlled for. Given the heightened vulnerabilities of socioeconomically disadvantaged children and long-term repercussions of childhood behavioral difficulties, our mediation model establishes the pivotal role of inhibitory control as a key cognitive resource which curtails impulsive behaviors in early childhood. The identification of intermediary cognitive mechanisms and caregiving antecedents contributing to conduct problems can inform targeted interventions, which may be especially crucial for children who are vulnerable to intrusive caregiving due to sociodemographic risk and scarcer parenting resources.
About Mental Disengagement Mediates the Effect of Rumination on Smartphone Use: A Latent Growth Curve Analysis
We examined if ruminators’ heavier smartphone use was due to its use for coping purposes. Using latent growth curve and structural equation modeling, we found that only ruminators’ smartphone use for mental disengagement, but not problem-focused or socioemotional coping, explained their heavier smartphone use—objectively quantified using monitoring applications.
Although studies have demonstrated a significant relation between rumination and excessive smartphone use, little research has been conducted on psychological factors that mediate the link. The compensatory internet use model holds that individuals go online to alleviate negative feelings caused by stressors (Kardefelt-Winther, 2014), suggesting that smartphone coping could be a mediator for the link. Thus, our study examined if smartphone coping mediated the relation between rumination and smartphone use. In doing so, we assessed longitudinal and objective smartphone use by using screen time monitoring applications and employing rigorous analysis methods such as latent growth curve and structural equation modeling. 251 undergraduates were recruited, which is sufficient to attain more than 80% power to detect moderate differences between piecewise slopes. Thirty-four individuals dropped out, resulting in a sample size of 217 (mean age = 21.8 years; female = 74.1%). Participants self-reported their ruminative tendencies, smartphone coping, and smartphone use weekly over 5 weeks. Their smartphone use was also objectively captured through screen time monitoring applications (iOS default application or a free Android application). Participants indicated their age, gender, monthly household income, and depressive symptomology, which served as covariates.
We fitted latent growth curve models (i.e., linear, quadratic, and piecewise) to variables that we expect to change over time (i.e., objective and subjective smartphone use, smartphone coping). For the piecewise growth curve, we specified time point 3 (T3) as the turning point, because during the study period, midterm examinations were cancelled at T3 due to the outbreak of COVID-19 in the country. Such an extraordinary change should inevitably affect our participants’ academic stress, which influences their smartphone use. The piecewise growth model demonstrated best fit for objective smartphone use. We performed structural equation analysis to examine if smartphone coping was a mediator between rumination and objective smartphone use, while controlling for covariates. Mental disengagement was the only significant mediator between rumination and initial levels of smartphone use (βint = 0.160, SEint = 0.064, pint = .013). Rumination positively predicted mental disengagement (β = 0.540; SE = 0.060, p < .001), which, in turn, positively predicted only initial levels of smartphone use (βint = 0.296; SEint = 0.112, pint = .008). Since the direct effect of rumination on initial levels of smartphone use was not significant (βint = -0.070, SEint = 0.103, pint = .498), this implies that mental disengagement fully mediated the relation between rumination and initial levels of smartphone use. Mental disengagement did not mediate the relation between rumination and changes in smartphone use. Furthermore, all indirect effects pertaining to problem-focused and socioemotional coping were not significant.
Our findings provide novel insights into the critical role of one’s motivation for smartphone use in triggering smartphone overuse. Therefore, on a practical note, counselors and policymakers should consider the motivations underlying excessive smartphone use in designing interventions for ruminators to overcome possible maladaptive smartphone-use habits.
References: Kardefelt-Winther, D. (2014). A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior, 31, 351–354. https://doi.org/10.1016/j.chb.2013.10.059
