Authors:Jin-Song Wei, Zhe-Bin Jin, Zhi-Qiang Yin, Qiang-Min Xie, Ji-Qiang Chen, Zi-Gang Li and Hui-Fang Tang
In order to determine whether local anesthetics directly affect the propagation and strength of myometrial contractions, we compared the effects of bupivacaine, ropivacaine, lidocaine and tetracaine on the contractions of myometrium isolated from pregnant and non-pregnant rats. Full-thickness myometrial strips were obtained from 18- to 21-day pregnant and non-pregnant Sprague-Dawley rats and incubated in an organ bath. When spontaneous contractions became regular, strips were exposed to cumulative concentrations of the four local anesthetics ranging from 0.01 to 300 μmol/L and the amplitude and frequency of contraction were recorded. All four compounds caused a concentration-dependent inhibition of the contractility of pregnant and non-pregnant uterine muscle. In pregnant myometrium, the concentration that caused 50% inhibition (IC50) was 100 μmol/L for bupivacaine, 157 μmol/L for ropivacaine, > 1000 μmol/L for lidocaine, and 26.3 μmol/L for tetracaine. In non-pregnant myometrium, the IC50 was 26.9 μmol/L for bupivacaine, 40 μmol/L for ropivacaine, 384 μmol/L for lidocaine, and 7.4 μmol/L for tetracaine. These results suggested that local anesthetics do inhibit myometrial contractions in pregnant and non-pregnant rats in a concentration-dependent manner.
Authors:Ji-Bin Li, Joseph T. F. Lau, Phoenix K. H. Mo, Xue-Fen Su, Jie Tang, Zu-Guo Qin and Danielle L. Gross
Background and aims
This study aims to examine the mediating effects of insomnia on the associations between problematic Internet use, including Internet addiction (IA) and online social networking addiction (OSNA), and depression among adolescents.
A total of 1,015 secondary school students from Guangzhou in China participated in a cross-sectional survey. Levels of depression, insomnia, IA, and OSNA were assessed using the Center for Epidemiological Studies-Depression Scale, Pittsburgh Sleep Quality Index, Young’s Diagnostic Questionnaire, and Online Social Networking Addiction Scale, respectively. Logistic regression models were fit to test the associations between IA, OSNA, insomnia, and depression. The mediation effects of insomnia were tested using Baron and Kenny’s strategy.
The prevalence of depression at moderate level or above (CES-D ≥ 21), insomnia, IA, and OSNA were 23.5%, 37.2%, 8.1%, and 25.5%, respectively. IA and OSNA were significantly associated with depression (IA: AOR = 2.79, 95% CI: 1.71, 4.55; OSNA: AOR = 3.27, 95% CI: 2.33, 4.59) and insomnia (IA: AOR = 2.83, 95% CI: 1.72, 4.65; OSNA: AOR = 2.19, 95% CI: 1.61, 2.96), after adjusting for significant background factors. Furthermore, insomnia partially mediated 60.6% of the effect of IA on depression (Sobel Z = 3.562, p < .002) and 44.8% of the effect of OSNA on depression (Sobel Z = 3.919, p < .001), respectively.
The high prevalence of IA and OSNA may be associated with increased risk of developing depression among adolescents, both through direct and indirect effects (via insomnia). Findings from this study indicated that it may be effective to develop and implement interventions that jointly consider the problematic Internet use, insomnia, and depression.
Authors:Ji-Bin Li, Phoenix K. H. Mo, Joseph T. F. Lau, Xue-Fen Su, Xi Zhang, Anise M. S. Wu, Jin-Cheng Mai and Yu-Xia Chen
Background and aims
The aim of this study is to estimate the longitudinal associations between online social networking addiction (OSNA) and depression, whether OSNA predicts development of depression, and reversely, whether depression predicts development of OSNA.
A total of 5,365 students from nine secondary schools in Guangzhou, Southern China were surveyed at baseline in March 2014, and followed up 9 months later. Level of OSNA and depression were measured using the validated OSNA scale and CES-D, respectively. Multilevel logistic regression models were applied to estimate the longitudinal associations between OSNA and depression.
Adolescents who were depressed but free of OSNA at baseline had 1.48 times more likely to develop OSNA at follow-up compared with those non-depressed at baseline [adjusted OR (AOR): 1.48, 95% confidence interval (CI): 1.14–1.93]. In addition, compared with those who were not depressed during the follow-up period, adolescents who were persistently depressed or emerging depressed during the follow-up period had increased risk of developing OSNA at follow-up (AOR: 3.45, 95% CI: 2.51–4.75 for persistent depression; AOR: 4.47, 95% CI: 3.33–5.99 for emerging depression). Reversely, among those without depression at baseline, adolescents who were classified as persistent OSNA or emerging OSNA had higher risk of developing depression compared with those who were no OSNA (AOR: 1.65, 95% CI: 1.01–2.69 for persistent OSNA; AOR: 4.29; 95% CI: 3.17–5.81 for emerging OSNA).
The findings indicate a bidirectional association between OSNA and depression, meaning that addictive online social networking use is accompanied by increased level of depressive symptoms.
Authors:Ji-Bin Li, Anise M.S. Wu, Li-Fen Feng, Yang Deng, Jing-Hua Li, Yu-Xia Chen, Jin-Chen Mai, Phoenix K.H. Mo and Joseph T.F. Lau
Background and aims
Problematic online social networking use is prevalent among adolescents, but consensus about the instruments and their optimal cut-off points is lacking. This study derived an optimal cut-off point for the validated Online Social Networking Addiction (OSNA) scale to identify probable OSNA cases among Chinese adolescents.
A survey recruited 4,951 adolescent online social networking users. Latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses were applied to the validated 8-item OSNA scale to determine its optimal cut-off point.
The 3-class model was selected by multiple criteria, and validated in a randomly split-half subsample. Accordingly, participants were categorized into the low risk (36.4%), average risk (50.4%), and high risk (13.2%) groups. The highest risk group was regarded as “cases” and the rest as “non-cases”, serving as the reference standard in ROC analysis, which identified an optimal cut-off point of 23 (sensitivity: 97.2%, specificity: 95.2%). The cut-off point was used to classify participants into positive (probable case: 17:0%) and negative groups according to their OSNA scores. The positive group (probable cases) reported significantly longer duration and higher intensity of online social networking use, and higher prevalence of Internet addiction than the negative group.
The classification strategy and results are potentially useful for future research that measure problematic online social networking use and its impact on health among adolescents. The approach can facilitate research that requires cut-off points of screening tools but gold standards are unavailable.