Background: Falls are a major threat to older adults worldwide. Although various effective interventions have been developed, their comparative effectiveness remains unreported. Methods: A systematic review and network meta-analysis was conducted to determine the most effective interventions to prevent falls in community-dwelling adults aged 60 and over. Combined odds ratio (OR) and 95% credible interval (95% CrI) were calculated. Results: A total of 49 trials involving 27,740 participants and 9271 fallers were included. Compared to usual care, multifactorial interventions (MFI) demonstrated the greatest efficacy (OR: 0.64, 95% CrI: 0.53 to 0.77) followed by interventions combining education and exercise (EDU + EXC) (OR: 0.65, 95% CrI: 0.38 to 1.00) and interventions combining exercise and hazard assessment and modification (EXC + HAM) (OR: 0.66, 95% CrI: 0.40 to 1.04). The effect of medical care performed the worst (OR: 1.02, 95% CrI: 0.78 to 1.34). Model fit was good, inconsistency was low, and publication bias was considered absent. The overall quality of included trials was high. The pooled odds ratios and ranking probabilities remained relatively stable across all sensitivity analyses. Conclusions: MFI and exercise appear to be effective to reduce falls among older adults, and should be considered first as service delivery options. Further investigation is necessary to verify effectiveness and suitableness of the strategies to at-risk populations.

Background Two decomposition methods have been widely used to attribute death differences between two populations to population size, age structure of the population, and age-specific mortality rate (ASMR), but their properties remain uninvestigated. Methods We assess how the two established decomposition methods yield varying results with three-factor factorial experimental designs, illustrating that they are sensitive to the choice of the reference group. We then propose a novel decomposition method to obtain robust decomposition results and use three cases to demonstrate its advantage. Results The three decomposition methods differ fundamentally in their allocation of interactions to the contributions of the three factors. In comparison with the existing methods, the new method is robust to the choice of the reference group. Three case studies showed inconsistent attribution results for the two existing methods but robust results for the new method when the choice of the reference population changes. Conclusions The proposed method offers robust and more justifiable attribution results compared to the two existing methods. This method could be generalized to attribution of group differences of other health indicators.

Background With the growing popularity of mobile health technology, app-based interventions delivered by smartphone have become an increasingly important strategy toward injury prevention. Objective This study aimed to develop a framework supporting the design of an app-based intervention to prevent unintentional injury, targeted for caregivers of Chinese children aged 0 to 6 years. Methods A theory-based mixed-method study, including focus groups and Web-based quantitative survey, was performed. Adult caregivers who care for children aged 0 to 6 years and own a smartphone were recruited into 2 sequential stages of research. First, focus groups were conducted among the caregivers at community health care centers and preschools from December 2015 to March 2016. Focus groups (8-10 participants per group) explored awareness, experiences, and opinions of caregivers toward using an app to prevent unintentional injury among children. Second, based on the focus groups findings, a Web-based quantitative survey was designed and distributed to caregivers in November 2016; it collected information on specific needs for the app-based intervention. Thematic analysis and quantitative descriptive analyses were performed. Results In total, 12 focus groups were completed, involving 108 caregivers. Most participants expressed a strong desire to learn knowledge and skills about unintentional child injury prevention and held positive attitudes toward app-based interventions. Participants expressed multiple preferences concerning the app-based intervention, including their contents, functions, interactive styles, installation and registration logistics, and privacy protection and information security. Following the focus groups, 1505 caregivers completed a WeChat-based quantitative survey, which generated roughly similar results to those of focus groups and added numerical metrics concerning participants’ preferences on what to learn, when to learn it, and how to learn it. A detailed framework was established involving 5 components: (1) content design, (2) functional design, (3) interactive style, (4) installation and registration logistics, and (5) privacy protection and information security, and 15 specific requirements. Conclusions We developed a framework that can be used as a guide to design app-based interventions for parents and caregivers, specifically for unintentional injury prevention of children aged 0 to 6 years.

Improper, unprofessional, or misleading media reports about violence against medical care providers (typically doctors and nurses) may provoke copycat incidents. To examine whether media reports about violence against medical care providers in China follow professional journalism recommendations, we identified 10 influential incidents of violence against medical care providers in China through a systematic strategy and used standardized internet-based search techniques to retrieve media reports about these events from 2007–2017. Reports were evaluated independently by trained coders to assess adherence to professional journalism recommendations using a 14-item checklist. In total, 788 eligible media reports were considered. Of those, 50.5% and 47.3%, respectively, failed to mention the real and complete names of the writer and editor. Reports improperly mentioned specific details about the time, place, methods, and perpetrators of violence in 42.1%, 36.4%, 45.4%, and 54.6% of cases, respectively. Over 80% of reports excluded a suggestion to seek help from professional agencies or mediation by a third party and only 3.8% of reports mentioned the perspectives of all three key informants about an event: medical care providers, patients, and hospital administrators. Of those that mentioned medical care providers, patient, and/or hospital administrator perspectives, less than 20% indicated they had obtained the interviewee’s consent to include their perspective. We concluded that most reports about violence against medical care providers in the Chinese media failed to strictly follow reporting recommendations from authoritative media bodies. Efforts are recommended to improve adherence to professional guidelines in media reports about violence against medical care providers in China, as adherence to those guidelines is likely to reduce future violent events against medical care providers like doctors and nurses.

The construction of a correct worldview, outlook on life, and values for students is linked to the development and breakthrough in the management of ideological as well as political education of students. At the same time, college students must be encouraged to follow well-rounded education and struggle to be well-prepared for the challenges of the new era. In order to raise students’ understanding of the critical role that political and ideological education plays in their academic success, it is authoritative that efforts to integrate these two spheres of learning be extended and new encounters made. That’s what prompted this study, which is focused on assessing college students’ level of ideological and political education administration, and it uses a mixture of big data technologies as well as artificial intelligence (AI) to do it. The accuracy of the traditional ideological as well as political education management quality assessment algorithm is not high, feature information extracted by the single-scale neural network (NN) is not rich enough, and the multiscale convolutional network (CN) fusion cannot consider the different values and importance for each scale. In this paper, the convolution kernel of the two-dimensional CN is changed to a one-dimensional convolution kernel, and the multiscale feature fusion CN model MCNN is first designed. The model is optimized and improved, the attention mechanism is integrated, and the MACNN model for the management evaluation of ideological as well as political education is proposed. Besides, this work organizes the network model in a wireless network environment that users can contact and operate at any time.