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Abstract Background Students are among the groups that use smartphones for long periods throughout the day and night. Therefore, this study aimed to examine the relationship between smartphone characteristics and the prevalence of hand discomfort among university students. Methods This study included 204 university students, selected based on their willingness to participate and inclusion criteria. Participants reported hand pain and discomfort by completing the Cornell Hand Discomfort Questionnaire (CHDQ). Personal information was collected through a demographic questionnaire. Smartphone characteristics were obtained from the Internet based on the smartphone model self-reported by students. Results According to the Cornell questionnaire, 59.3% of students reported experiencing discomfort in their right hand, while 38.2% reported discomfort in their left hand due to smartphone use. Furthermore, 36.3% of students reported experiencing pain in two or more regions on their right hand, while 20.1% reported pain in two or more areas on their left hand. More than half of the students in the right hand (53.5%) and more than one-third (33.3%) in the left hand obtained pain scores of more than 1.5. The chi-square test indicated a statistically significant relationship between the weight of the smartphone and the prevalence of discomfort in the right hand (χ2 = 4.80, p = 0.03). Furthermore, a statistically significant relationship was found between the discomfort or pain scores experienced in both hands and the number of painful areas in those hands (right hand: χ2 = 219.04, p = 0.00; left hand: χ2 = 213.13, p = 0.00). Conclusions Smartphone use can cause discomfort and pain in the hands of university students. The physical characteristics of the smartphone, such as its weight, play a significant role in contributing to right-hand-related pain among students. It is important to consider ergonomic factors in smartphone design and usage to reduce musculoskeletal problems among users, especially students.

Background: Students are among the groups that use smartphones for long periods throughout the day and night. Therefore, this study aimed to examine the relationship between smartphone characteristics and the prevalence of hand discomfort among university students. Methods: This study included 204 university students, selected based on their willingness to participate and inclusion criteria. Participants reported hand pain and discomfort by completing the Cornell Hand Discomfort Questionnaire (CHDQ). Personal information was collected through a demographic questionnaire. Smartphone characteristics were obtained from the Internet based on the smartphone model self-reported by students. Results: According to the Cornell questionnaire, 59.3% of students reported experiencing discomfort in their right hand, while 38.2% reported discomfort in their left hand due to smartphone use. Furthermore, 36.3% of students reported experiencing pain in two or more regions on their right hand, while 20.1% reported pain in two or more areas on their left hand. More than half of the students in the right hand (53.5%) and more than one-third (33.3%) in the left hand obtained pain scores of more than 1.5. The chi-square test indicated a statistically significant relationship between the weight of the smartphone and the prevalence of discomfort in the right hand (χ2 = 4.80, p = 0.03). Furthermore, a statistically significant relationship was found between the discomfort or pain scores experienced in both hands and the number of painful areas in those hands (right hand: χ2 = 219.04, p = 0.00; left hand: χ2 = 213.13, p = 0.00). Conclusions: Smartphone use can cause discomfort and pain in the hands of university students. The physical characteristics of the smartphone, such as its weight, play a significant role in contributing to right-hand-related pain among students. It is important to consider ergonomic factors in smartphone design and usage to reduce musculoskeletal problems among users, especially students. [ABSTRACT FROM AUTHOR]

Abstract Objective Through the study of death characteristics and trend prediction, it is hoped that key populations, regions and seasons can be identified, thereby providing evidence support for the efficient prevention and control management of unintentional injury deaths. Method We collected information on 8630 unintentional deaths of children under age 5 from local surveillance systems, analyzed by chi-square test and predicted by the seasonal ARIMA model. Results About 33.1% of child deaths were under the age of 1, 60.5% were boys, 37.6% were in urban areas, 2.6% were among ethnic Tibetans, 6.8% were among ethnic Yi, and 46.6% died inside houses. The top three of total deaths were accidental drowning (35.0%), accidental suffocation (32.7%) and traffic accident (15.5%). The ratio of males to females in traffic accidents (1.28:1) and poisoning (1.30:1) deaths was relatively lower than accidental falls (1.62:1) and drowning (1.85:1). The causes of death ratio in rural and urban areas were: drowning (1.83:1), poisoning (1.75:1), suffocation (1.62:1), traffic (1.41:1), and falling (1.24:1). Children's deaths of ethnic minority groups of Tibetan and Yi increased year by year (χ 2=75.261, P

Objective: Through the study of death characteristics and trend prediction, it is hoped that key populations, regions and seasons can be identified, thereby providing evidence support for the efficient prevention and control management of unintentional injury deaths.Method: We collected information on 8630 unintentional deaths of children under age 5 from local surveillance systems, analyzed by chi-square test and predicted by the seasonal ARIMA model.Results: About 33.1% of child deaths were under the age of 1, 60.5% were boys, 37.6% were in urban areas, 2.6% were among ethnic Tibetans, 6.8% were among ethnic Yi, and 46.6% died inside houses. The top three of total deaths were accidental drowning (35.0%), accidental suffocation (32.7%) and traffic accident (15.5%). The ratio of males to females in traffic accidents (1.28:1) and poisoning (1.30:1) deaths was relatively lower than accidental falls (1.62:1) and drowning (1.85:1). The causes of death ratio in rural and urban areas were: drowning (1.83:1), poisoning (1.75:1), suffocation (1.62:1), traffic (1.41:1), and falling (1.24:1). Children's deaths of ethnic minority groups of Tibetan and Yi increased year by year (χ2=75.261, P< 0.001). Tibetan and Yi groups had the most deaths in summer, and Han in winter (χ2=29.093, P< 0.001). Accidental suffocation accounted for 78.2 percent of the total unintentional deaths of children under age 1. And drowning accounted for only 2.4 percent. The model SERIMA (1, 1, 2) (2, 0, 0) [12] is suitable for describing and predicting unintentional injury deaths of children under age 5.Conclusion: We should combine death surveillance with qualitative investigation or in-depth quantitative investigation to further analyze unintentional injury deaths in children. [ABSTRACT FROM AUTHOR]