Smartphone and social media addiction: Exploring the perceptions and experiences of Canadian teenagers

Prospective longitudinal relations among frequent social media use, nicotine vaping and experiencing internalizing mental health problems

AIMS

To compare four a priori rival mediated pathways of frequent social media use, electronic nicotine delivery systems (ENDS) use and internalizing mental health (MH) problems across five waves of nationally representative data.

DESIGN, SETTING AND PARTICIPANTS

This was a longitudinal study using data drawn from waves 2-5 (October 2014-November 2019) of the Population Assessment of Tobacco and Health Study, a nationally representative cohort study spanning approximately 5 years, conducted in the United States. The analytical sample of participants included those who were aged 12-14 years at wave 2 and who provided data in subsequent waves until wave 4.5 (n = 4627, 69.7% were White and 51.4% were male).

MEASUREMENTS

Frequent social media use (several times a day), ENDS use (past 30-day use) and internalizing MH problems (endorsed symptoms on four items in the past year) were dichotomized for analysis.

FINDINGS

The weighted proportions of the three key variables increased over time. From wave 2 to wave 5, frequent social media use grew from 56.9 to 77.2%; internalizing MH problems from 18.9 to 29.0%; and ENDS use from 1.4 to 11.4%. In weighted logistic regressions using generalized linear mixed models with random effects, there was a significant within-person association between frequent social media use at time t and greater ENDS use at t + 1 [adjusted odds ratio (aOR) = 1.87; 95% confidence interval (CI) = 1.47, 2.37] and worsened internalizing MH problems at t + 1 (aOR = 1.19; 95% CI = 1.04, 1.37). A model-based causal mediation analysis and marginal structural models were fitted to estimate the average causal mediation effect. Among all four examined mediation pathways throughout the three constructs, partial mediation was observed, and all the pathways were significant for both boys and girls. Sex differences did not emerge in the examined prospective mediated pathways.

CONCLUSIONS

Among youth in the United States, frequent social media use appears to mediate the prospective association between experiencing internalizing mental health problems and using electronic nicotine delivery systems.

Determining the Effects of Ramadan Fasting on Risky Behaviors of Turkish Nursing Students

The aim of this study was to determine the effect of nursing students' fasting during Ramadan on their risky behaviors. This study was conducted in a university located in 2022 using the prospective cohort study method. The data were collected from the nursing department students through face-to-face questionnaires. The sample of the study consisted of 186 nursing students. The data were obtained using a descriptive information form, which consists of questions regarding the descriptive characteristics of the nursing students, and the risky behaviors form, created by the researchers, to evaluate the effect of fasting during Ramadan on nursing students' risky behaviors. According to the findings of the research, it has been determined that the students who always fast during Ramadan have regular sahur. When the students' level of religious faith and fasting and having sahur status were compared with their risky behaviors, the mean scores of exercise and nutrition increased significantly, and the mean scores of interpersonal relationships decreased significantly. It was determined that the majority of students had a high level of religious faith, fasted and had sahur during Ramadan. Consequently, while Ramadan fasting negatively affected students' physical activity, nutrition and sleep patterns, it positively affected their interpersonal relationship status.

Internet addiction and depressive and anxious symptoms among Chinese rural left-behind adolescents: Mediating roles of resilience and friendship quality

BACKGROUND

Rural left-behind adolescents are more vulnerable to Internet addiction and depressive and anxious symptoms due to the lack of family support and parental supervision. This study was the first to investigate the longitudinal relationships between Internet addiction and depressive and anxious symptoms and to examine the mediating roles of resilience and friendship quality in rural left-behind adolescents.

METHODS

Included in this study, which was from a longitudinal study conducted five times over 2 years, were 1001 rural left-behind adolescents. The internationally used scales for depressive and anxious symptoms, Internet addiction, resilience and friendship quality were administered. A structural equation model was used for analysis.

RESULTS

The prevalence of Internet addiction, depressive and anxious symptoms among rural left-behind adolescents were 17.7%, 35.8% and 27.6%, respectively. Internet addiction predicted the later depressive and anxious symptoms (β = 0.200, 95% confidence interval [CI]: 0.116-0.274 and β = 0.263, 95% CI: 0.188-0.330). Resilience acted as an independent mediator in the relationships between Internet addiction and depressive and anxious symptoms (β = 0.037 and 0.034, P < 0.01). Resilience and friendship quality played a chain-mediating role on the longitudinal relationships between Internet addiction and depressive and anxious symptoms (β = 0.011 and 0.010, P < 0.001). The mediating effects accounted for 24.0% and 16.7% of the total effects, respectively.

CONCLUSION

Resilience and friendship quality play an independent or chain-mediating role in longitudinal relationships between Internet addiction and depressive and anxious symptoms. The findings inform targeted intervention strategies to improve the mental health of left-behind adolescents.

Dissociative experiences reduce online problem gambling treatment effectiveness

AIMS

To determine whether dissociative experiences moderate online problem gambling treatment effectiveness, and to characterize the temporal persistence of the relationship between dissociation and problem gambling.

DESIGN

Repeatedly measured self-report data on a guided online cognitive behavioral therapy for problem gambling collected on four occasions: before treatment, after treatment, and at 6- and 12-month follow-ups.

SETTING AND PARTICIPANTS

The data (N = 1243, 59.2% males) were collected in Finland between 2019 and 2021.

MEASUREMENTS

The primary outcome variable was the self-reported level of problem gambling. The predictors were the treatment phase and dissociative experiences, their interaction, and the demographic covariates of age, education, income, and gender.

FINDINGS

Problem gambling scores and dissociative experiences declined significantly following treatment and remained low through the follow-ups (retention rates: 52.6% [post-treatment], 26.3% [at the 6-month follow-up], and 16.1% [at the 12-month follow-up]). However, the treatment was significantly less effective in reducing problem gambling for individuals who kept experiencing dissociation after the treatment.

CONCLUSIONS

Dissociation is an integral sign of problem gambling severity and sustained dissociative experiences may significantly reduce the long-term effectiveness of online problem gambling treatments. Treatment efforts should be customized to account for individual differences in dissociative tendencies, and future research should broaden the study of dissociative experiences to other behavioral addictions.

A Teenager Physical Fitness Evaluation Model Based on 1D-CNN with LSTM and Wearable Running PPG Recordings

People attach greater importance to the physical health of teenagers because adolescence is a critical period for the healthy development of the human body. With the progress of biosensing technologies and artificial intelligence, it is feasible to apply wearable devices to continuously record teenagers’ physiological signals and make analyses based on modern advanced methods. To solve the challenge that traditional methods of monitoring teenagers’ physical fitness lack accurate computational models and in-depth data analyses, we propose a novel evaluation model for predicting the physical fitness of teenagers. First, we collected 1024 teenagers’ PPGs under the guidance of the proposed three-stage running paradigm. Next, we applied the median filter and wavelet transform to denoise the original signals and obtain HR and SpO₂. Then, we used the Pearson correlation coefficient method to finalize the feature set, based on the extracted nine physical features. Finally, we built a 1D-CNN with LSTM model to classify teenagers’ physical fitness condition into four levels: excellent, good, medium, and poor, with an accuracy of 98.27% for boys’ physical fitness prediction, and 99.26% for girls’ physical fitness prediction. The experimental results provide evidence supporting the feasibility of predicting teenagers’ physical fitness levels by their running PPG recordings.