Background The purpose of the present study was to identify smartphone use patterns associated with problematic smartphone use (PSU) among preschool children. Little is known about PSU patterns in younger children, although the age for first smartphone use is decreasing. Methods We applied a cross-sectional study design to analyze data obtained from a nationwide survey on smartphone overdependence conducted in 2017 by the South Korean Ministry of Science and ICT and the National Information Society Agency. Data from 1,378 preschool children were analyzed using binomial logistic regression analysis. This study was conducted in compliance with STROBE (Strengthening the Reporting of Observational Studies in Epidemiology). Results Seventeen percent of the sample met the criteria for PSU. The odds of PSU significantly increased with frequent smartphone use and in children who used a smartphone for more than two hours per day. Using smartphones to watch TV shows or videos for entertainment or fun significantly increased the odds of PSU, whereas using smartphones for education, games, and social networking did not. Conclusions The findings indicate that one of five preschool children using smartphones could experience PSU. Compared to other age groups, PSU in young children may be more associated with their caregivers. To prevent PSU in preschool children, caregivers need information about the total screen time recommended for children, smartphone use patterns associated with PSU, suggestions for other activities as possible alternatives to smartphone use, and strategies to strengthen children’s self-regulation with regards to smartphone use.
Cryptotanshinone (CT), a major tanshinone of medicinal plant Salvia miltiorrhiza Bunge, demonstrated strong antibacterial activity against clinic isolated methicillin and vancomycin-resistant Staphylococcus aureus (MRSA and VRSA) in this experiment. The CT was determined against clinic isolated MRSA 1–16 with MIC and MBC values ranging from 4 to 32 and 8 to 128 μg/mL; for MSSA 1-2 from 16 to 32 μg/mL and 64 to 128 μg/mL; for VRSA 1-2 from 2 to 4 μg/mL and 4 to 16 μg/mL, respectively. The range of MIC50 and MIC90 of CT was 0.5–8 μg/mL and 4–64 μg/mL, respectively. The combination effects of CT with antibiotics were synergistic (FIC index <0.5) against most of tested clinic isolated MRSA, MSSA, and VRSA except additive, MRSA 4 and 16 in oxacillin, MRSA 6, 12, and 15 in ampicillin, and MRSA 6, 11, and 15 in vancomycin (FIC index < 0.75–1.0). Furthermore, a time-kill study showed that the growth of the tested bacteria was completely attenuated after 2–6 h of treatment with the 1/2 MIC of CT, regardless of whether it was administered alone or with ampicillin, oxacillin, or vancomycin. The results suggest that CT could be employed as a natural antibacterial agent against multidrug-resistant pathogens infection.
Background: Diagnosis of benign paroxysmal positional vertigo (BPPV) depends on the accurate interpretation of nystagmus induced by positional tests. However, difficulties in interpreting eye-movement often can arise in primary care practice or emergency room. We hypothesized that the use of machine learning would be helpful for the interpretation. Methods: From our clinical data warehouse, 91,778 nystagmus videos from 3467 patients with dizziness were obtained, in which the three-dimensional movement of nystagmus was annotated by four otologic experts. From each labeled video, 30 features changed into 255 grid images fed into the input layer of the neural network for the training dataset. For the model validation, video dataset of 3566 horizontal, 2068 vertical, and 720 torsional movements from 1005 patients with BPPV were collected. Results: The model had a sensitivity and specificity of 0.910 ± 0.036 and 0.919 ± 0.032 for horizontal nystagmus; of 0.879 ± 0.029 and 0.894 ± 0.025 for vertical nystagmus; and of 0.783 ± 0.040 and 0.799 ± 0.038 for torsional nystagmus, respectively. The affected canal was predicted with a sensitivity of 0.806 ± 0.010 and a specificity of 0.971 ± 0.003. Conclusions: As our deep-learning model had high sensitivity and specificity for the classification of nystagmus and localization of affected canal in patients with BPPV, it may have wide clinical applicability.
Aims and objectives To explore the factors associated with the intention to leave among nurses in small‐ and medium‐sized hospitals and to determine the predictors about work environment and rewards. Background Compared with large hospitals, insight into the working conditions, rewards and turnover of nurses working for these hospitals is lacking internationally. Design Cross‐sectional study design. Methods Data were obtained from the Korean Nurses Association's 2016 Welfare Policy and System Improvement Survey. Of the participants, data from 951 staff nurses working three shifts were analysed using hierarchical multiple regression to explore the predictors of nurses’ turnover intention. This study complied with the Strengthening the Reporting of Observational studies in Epidemiology. Results The perceived pay level satisfaction was the most obvious and persistent predictor of the intention to leave. Living benefits were shown to be scarcely satisfied, rendering considerable influence on turnover intention. Concerning aspects related to the working environment, the implementation of contract‐abiding working hours and nurse‐friendly night shift schedules reduced the turnover intention of nurses. Conclusions Nurses in small‐ and medium‐sized hospitals are likely to have particular challenges in terms of professional growth. When fundamental rewards and basic working conditions are acceptable to nurses, their turnover can be reduced, and the professional growth can also be expected. Hospitals with a high nurse turnover rate need to preferentially verify these factors perceived by their nurses and to improve to increase nurses’ retention. Relevance to clinical practice Understanding the determinants of intention to leave can lead to the development of strategies that persuade nurses to remain employed. These findings inform policymakers, nurse managers and hospital managers of the causes of nurses’ intentions to leave in small‐ and medium‐sized hospitals. Our findings also provide empirical data on the working conditions and rewards of these nurses and suggest strategies for their retention.
ObjectivesEven though vestibular rehabilitation therapy (VRT) using head-mounted display (HMD) has been highlighted recently as a popular virtual reality platform, we should consider that HMD itself do not provide interactive environment for VRT. This study aimed to test the feasibility of interactive components using eye tracking assisted strategy through neurophysiologic evidence.MethodsHMD implemented with an infrared-based eye tracker was used to generate a virtual environment for VRT. Eighteen healthy subjects participated in our experiment, wherein they performed a saccadic eye exercise (SEE) under two conditions of feedback-on (F-on, visualization of eye position) and feedback-off (F-off, non-visualization of eye position). Eye position was continuously monitored in real time on those two conditions, but this information was not provided to the participants. Electroencephalogram recordings were used to estimate neural dynamics and attention during SEE, in which only valid trials (correct responses) were included in electroencephalogram analysis.ResultsSEE accuracy was higher in the F-on than F-off condition (P=0.039). The power spectral density of beta band was higher in the F-on condition on the frontal (P=0.047), central (P=0.042), and occipital areas (P=0.045). Beta–event-related desynchronization was significantly more pronounced in the F-on (–0.19 on frontal and –0.22 on central clusters) than in the F-off condition (0.23 on frontal and 0.05 on central) on preparatory phase (P=0.005 for frontal and P=0.024 for central). In addition, more abundant functional connectivity was revealed under the F-on condition.ConclusionConsidering substantial gain may come from goal directed attention and activation of brain-network while performing VRT, our preclinical study from SEE suggests that eye tracking algorithms may work efficiently in vestibular rehabilitation using HMD.
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