Problematic smartphone usage, objective smartphone engagement, and executive functions: A latent variable analysis

The associations among type D personality and nomophobia, metacognitions about smartphone use, smartphone addiction in Chinese university freshmen: a two-wave study

OBJECTIVE

This study aimed to examine longitudinal associations of Type D personality and smartphone addiction, while also exploring the mediating roles of nomophobia and metacognitions about smartphone use.

METHODS

Type D Personality Scale-14 (T1), Nomophobia Questionnaire (T2), Metacognitions about Smartphone Use Questionnaire (T2) and Smartphone Addiction Scale Short Version (T2) were applied at two time points. 653 university freshmen (Mage= 18.56, SD = 0.65) from a university in China were surveyed.

RESULTS

(1) Type D personality was significantly and positively correlated with nomophobia, negative metacognition, and smartphone addiction. In contrast, the correlation between Type D personality and positive metacognition did not reach the significant level. (2) Compared with individuals with non-Type D personality, those with Type D personality scored significantly higher on nomophobia, negative metacognition, and smartphone addiction. However, the difference was not significant for positive metacognition. (3) Nomophobia and metacognitions about smartphone use fully mediated the relationship between Type D personality and smartphone addiction. While the mediating effects of nomophobia and negative metacognition were significant, the mediating effect of positive metacognition was not significant.

CONCLUSIONS

Type D personality can not only affect smartphone addiction directly but also indirectly through nomophobia and negative metacognition. Therefore, to prevent and intervene in smartphone addiction, we can start from both affect (nomophobia) and metacognition (negative metacognitions about smartphone use).

Iconic logic: the visual art of drawing the right conclusion

Most people, evidence suggests, have a hard time thinking straight. Symbolic logic is a tool that can help remedy this problem. Unfortunately, it is highly abstract and uses symbols whose meanings rely on unintuitive arbitrary conventions. Without sacrificing rigor, iconic logic is more concrete and uses icons that resemble what they stand for and whose meanings are thus easier to picture, process, and remember. Here I review and critique iconic existential graphs and concept diagrams-the former link iconic logic to iconic mathematics; the latter expand popular Euler or Venn diagrams and have, to some degree, been empirically investigated for user-friendliness. I lay out how expertise in perception, cognition, and genetics can inform and improve such empirical research to help make iconic logic more ergonomic. After all, logic is a tool, and tools should not only suit their use but also their user.

Individual differences in attention control: A meta-analysis and re-analysis of latent variable studies

A meta-analysis and re-analysis of prior latent variable studies was conducted in order to assess whether there is evidence for individual differences in broad attention control abilities. Data from 90 independent samples and over 23,000 participants suggested that most (84.4%) prior studies find evidence for a coherent attention control factor with average factor loadings of .51. This latent attention control factor was related to other cognitive ability factors including working memory, shifting, fluid intelligence, long-term memory, reading comprehension, and processing speed, as well as to self-reports of task-unrelated thoughts and task specific motivation. Further re-analyses and meta-analyses suggest that the results remained largely unchanged when considering various possible measurement issues. Examining the factor structure of attention control suggested evidence for sub-components of attention control (restraining, constraining and sustaining attention) which could be accounted for a by a higher-order factor. Additional re-analyses suggested that attention control represents a broad ability within models of cognitive abilities. Overall, these results provide evidence for attention control abilities as an important individual differences construct.

The Relationships between Effortful Control, Mind Wandering, and Mobile Phone Addiction Based on Network Analysis

BACKGROUND

The prevailing mobile phone use brought the problem of addiction, which might cause negative consequences. Effortful control and mind wandering were associated with addictive behavior. The present study aimed to investigate the dimension-level relationships between effortful control, mind wandering, and mobile phone addiction.

METHODS

A total of 1684 participants participated this study. The mobile phone addiction, effortful control, and mind wandering were measured through self-report scales, respectively. Dimension-level network of these psychological variables was estimated and bridge expected influence (BEI) values for each node was calculated.

RESULTS

Dimensions of mobile phone addiction, effortful control, and mind wandering exhibited distinct and complex links to each other. The node "activation control" exhibited the highest negative BEI value (BEI = -0.32), whereas "spontaneous thinking" showed the highest positive BEI value (BEI = 0.20).

CONCLUSIONS

Different dimensions of effortful control and mind wandering had varied yet significant connections with distinct dimensions of mobile phone addiction, facilitating understanding of the specific pathways underlying the three constructs. The identified dominant bridge nodes can provide potential targets for the intervention of mobile phone addiction.

The neuropsychological profile of work addiction

The objective of this study was to examine, for the first time, the neuropsychological aspects of work addiction, with a specific emphasis on the cognitive factors identified by theoretical models. While previous research has highlighted self-reported obsessiveness and impulsiveness in work addiction, this study sought to go beyond self-report measures by employing also neuropsychological reaction time tasks to assess executive functions. A total of 101 participants were categorized into two groups based on their Work Addiction Risk Test scores: a high-risk group (HWA; n = 39) and a low-risk group (LWA; n = 62) for work addiction. Executive functions were assessed using Go/No-Go, Digit Span, Counting Span, N-back, and Card Sorting Tasks. The findings revealed that the HWA group had poorer inhibitory control and achieved lower scores on the more complex working memory task involving updating (2-back). However, they exhibited unaltered cognitive flexibility and outperformed the LWA group on the 1-back task associated with maintenance and storage of information and sustained attention. Higher levels of impulsiveness and compulsiveness were observed in the HWA group, consistent with previous studies. These findings highlight the role of inhibition and working memory in work addiction, potentially contributing to challenges such as inefficient working strategies and impaired social functioning. This study offers valuable insights into the neurocognitive aspects of work addiction, deepening our understanding of this phenomenon.

Relationship between Problematic Smartphone Use, Sleep Quality and Bedtime Procrastination: A Mediation Analysis

The purpose of this investigation was to study the relationship between sleep quality, problematic smartphone use (PSU) and bedtime procrastination, as well as to assess gender and age differences. A total of 313 participants, aged 18-60 (M = 30 ± 10.1; 53.2% males), completed an online survey between February and May 2023 in Spain. The Pittsburgh Sleep Quality Index, Smartphone Addiction Scale-Short Version and Bedtime Procrastination Scale were used to measure sleep quality, PSU and bedtime procrastination, respectively. Additionally, smartphone use habits were evaluated through self-report questions. Pearson correlations, independent samples t-tests, one-way ANOVA, Bonferroni's post hoc tests and mediation analysis were conducted. Correlation analysis showed positive associations between the three main variables. Independent sample t-tests indicated females were more prone to PSU along with higher overall smartphone use. Post hoc analysis of one-way ANOVA exposed age differences between young adults (18-25 years old), adults (26-44 years old) and middle-aged adults (45-60 years old) in PSU and bedtime procrastination. Finally, mediation analysis revealed that PSU had indirect effects on sleep quality through bedtime procrastination, but no direct effects on sleep quality. Therefore, PSU, and especially bedtime procrastination, should be considered as targets in future campaigns or intervention programs to improve sleep quality among the young Spanish population.