国内网络舆情研究热点与趋势分析

目的了解国内网络舆情热点,提高舆情监测能力,为政府及相关部门决策提供服务。方法通过下载CNKI收录的网络舆情论文（2005-2010年）,借助于统计软件与科学计量方法对近6年来我国网络舆情的研究状况进行分析。结果研究的热点问题为文本挖掘、引导、高校、突发事件、模型、舆情分析、预警、指标体系等;舆情研究已进入了发展阶段,形成了一批高产作者和出名的研究机构,部分阶段性研究成果已在网络舆情监测系统中得到应用。结论舆情研究已进入了发展阶段,舆情监测工作应从实际需求出发,实时研究舆情发展趋势。     

医院网络舆情工作模型的构建与应用研究

目的构建医院网络舆情工作模型,以上海公立医院为调研对象,对该模型进行论证。方法根据建立的模型设计调查问卷,经专家多次咨询修改论证后发放调查上海市107家公立医院的医院管理者或舆情工作者,对课题构建的网络舆情工作模型进行论证和应用研究,并对数据进行统计分析。结果凭借调查,构建网络舆情工作模型,设置舆情监测、应对、反馈、分析4个职责分组。调查对象对本课题构建的舆情工作模型能够认可,舆情工作模型的应用具有一定适用性。结论医院舆情工作是接受群众监督,不断改善医疗流程、服务等的新手段,借助网络舆情分析甄别,推进医院流程再造,不断提升医疗服务水平及患者满意度。     

卫生计生网络舆情分析及应对策略研究

在信息时代,互联网已成为卫生计生舆情监测的主要渠道。本文概述了2015年卫生计生网络舆情监测分析的总体情况,研究了卫生计生网络舆情的特征规律,并对卫生计生重点舆情进行了分析研判。在此基础上就进一步做好卫生计生宣传工作提出了建议策略。     

化被动为主动 积极应对医院网络舆情

近年来,常州市第一人民医院采取一系列措施,如成立舆情应对工作机构、完善舆情应对处置流程、加强与发帖者及媒体的主动沟通、建立新闻发言人制度等,在网络舆情处置方面积累了一些经验,也取得了一定成果。     

基于工作分析的社区卫生服务机构岗位绩效考核构想

简述了绩效考评在卫生服务领域中的应用,分析了我国社区卫生服务机构岗位绩效考评中存在的问题,提出基于工作分析的社区卫生服务机构岗位绩效考核构想,建议采取"业绩+技能+态度+工作强度"的绩效考核模式,在工作分析的基础上,编制社区卫生服务机构中医、护、防等各类卫生服务人员的工作说明书,并制定有针对性的岗位绩效考核体系,从而真正提高社区卫生服务机构岗位绩效,使社区卫生服务能够满足社区居民不断变化的卫生需求.     

2014年我国环境与健康事件网络舆情分析

为了解2014年环境与健康网络舆情热点及其特点,分析舆情发展趋势,为国家环境与健康舆情相关工作提供参考,以拓尔思(TRS)社会媒体分析云服务系统为主要工具,综合分析传统媒体与新媒体中的数据源,按照"媒体关注度高、网民讨论热烈"的筛选原则,结合专家定性评估的方法,全面梳理了2014年我国环境与健康领域发生的网络舆情热点及其特点。结果显示,2014年十大环境与健康舆情事件中3件涉及空气污染,3件涉及重金属污染,水污染、垃圾焚烧厂、电子垃圾回收和新《环保法》相关事件各1件。与2013年相比,环境与健康舆情更加多元化,儿童血铅超标事件仍被高度关注,居民对垃圾焚烧厂兴建的关注成为新热点,并且政府逐步采取措施保障环境健康。     

上海某医院网络舆情监测工作的分析与实践

以上海某公立医院实际开展网络舆情监测工作实践为例,分析了该院近年网络舆情监测工作趋势、正面信息媒体报道和负面信息内容数据,阐述了该院网络舆情的管理体系式、研判机制、舆情呈报制度,对于监督行业人员从业规范、推进医院流程再造、提高民众满意度,具有重要的现实意义。     

职业卫生技术服务模式的探讨

《中华人民共和国职业病防治法》颁布后,职业病防治工作越来越受到全社会的重视,职业卫生技术服务机构逐年增加,但它们在基本满足社会需求的同时,也暴露出了一些问题和不足。通过回顾职业卫生技术服务机构的演变历程,分析当前职业卫生技术服务机构的构成情况以及当前职业卫生技术服务存在的问题,提出了改善职业卫生技术服务模式的构想,同时就如何在新形势下做好职业卫生技术服务工作,最大限度地发挥好职业卫生技术服务机构的作用做了探讨。     

贵阳市社区卫生服务机构人员工作满意度现状分析

[目的]了解贵阳市社区卫生服务机构人员工作满意度的基本现状,为社区卫生服务人力管理提供科学依据。[方法]从贵阳市随机选取10家开展社区卫生服务机构的314名人员进行问卷调查,内容包括人员基本特征和23个工作满意度因子。对满意度结果做统计描述,并进行 Spearman 相关分析、t检验和方差分析。[结果]机构人员工作总体满意度一般,满意度评分为（3.34±0.79）分。较不满意的因子有工资福利、职称晋升、奖惩制度、个人发展机会等。医学技术人员、在编职工是满意度总和评分较低的群体,职工离职意愿与满意度评分相关。[结论]社区卫生服务机构人员工作满意度有待提高;应加强对在个人发展前景提升、工作回报提高、工作期望增加等方面的政策措施。     

“十二五”期间四川省公共卫生网络舆情分析

目的开展"十二五"期间(2011~2015年)四川省公共卫生网络舆情分析。方法对2011~2015年的公共卫生网络舆情数据进行描述性统计分析。结果 "十二五"期间,四川省内共监测到公共卫生舆情原始数量合计10435条,历年舆情信息合计在550条~6214条之间,年均2087条;根据筛选后上报最终数量排序在前3位的是食品安全事件、传染病事件和预防接种事件,累积构成比达到全部上报舆情的77.6%,与全国排位不同(全国范围前3位的公共卫生舆情是传染病事件、环境因素事件、服药事件,累积构成比为67.1%)。2011~2015年,四川省公共卫生舆情较多的月份集中在3~8月(全国范围仅10~11月较少)。2013年,四川省雅安地震当月,省内舆情信息合计数量和上报数量均为"十二五"期间的最高值。结论 "十二五"期间,虽然四川省公共卫生舆情分布在种类数量排名和月份分布的趋势上均与全国不同,省内舆情事件种类热度地域性较强,但是方向和势态比较稳定。疾病预防控制舆情的监测和分析对提高省内疾病预防控制机构的工作质量和效率有重要作用。     

突发公共卫生事件舆情监测与恐荒度分析系统的设计

目的：探讨并设计突发公共卫生事件舆情监测与公众恐慌度分析系统。方法：从分析互联网上公众恐慌机理入手,通过网络舆情监测,采用基于Web的数据挖掘技术实现公众恐慌的度量。结果：提出并构建了突发公共卫生事件网络舆情监测与公众恐慌度实时监测与度量的新思路。结论：突发公共卫生事件不仅对个人的生命财产造成损害,还将导致人们不同程度的心理变化,由此引发公众恐慌,并激发衍生事件。由于互联网技术的发展使信息传播更加快捷,随之带来的负面影响也更加严重,该系统可为政府相关部门的新闻发布、舆情引导、应急管理提供有效的决策支持。     

Stigmatizing smokers: public sentiment toward cigarette smoking and its relationship to smoking behaviors

Public sentiment in the United States has been evolving against cigarette smoking. Providing support for stronger tobacco control legislation, unfavorable public sentiment has contributed to the decrease in the size of the smoking population in this country. The present study hypothesizes that the unfavorable public sentiment may also discourage cigarette smoking by creating an unfavorable "smoking climate" in which smoking is socially rejected as a deviant behavior. Analyses of several secondary data-sets provided evidence that smoking rates are lower in the states where the public holds relatively unfavorable sentiment toward cigarette smoking. The relationship between public sentiment and smoking rates was significant even after controlling for the effects of state-level tobacco control measures, such as cigarette taxes and smoking restrictions in private workplaces and restaurants. We also found that smokers who have experienced unfavorable public sentiment are more willing to quit smoking than those who have not, supporting the hypothesized effects of antismoking public sentiment on smoking behaviors.     

Semantic network analysis of vaccine sentiment in online social media

ObjectiveTo examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines.BackgroundVaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood.MethodsWe constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment.ResultsThe semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits.ConclusionSemantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage in the United States.     

Public attitudes toward COVID-19 vaccines on English-language Twitter: A sentiment analysis

ObjectiveTo identify themes and temporal trends in the sentiment of COVID-19 vaccine-related tweets and to explore variations in sentiment at world national and United States state levels.MethodsWe collected English-language tweets related to COVID-19 vaccines posted between November 1, 2020, and January 31, 2021. We applied the Valence Aware Dictionary and sEntiment Reasoner tool to calculate the compound score to determine whether the sentiment mentioned in each tweet was positive (compound ≥ 0.05), neutral (-0.05 < compound < 0.05), or negative (compound ≤ -0.05). We applied the latent Dirichlet allocation analysis to extract main topics for tweets with positive and negative sentiment. Then we performed a temporal analysis to identify time trends and a geographic analysis to explore sentiment differences in tweets posted in different locations.ResultsOut of a total of 2,678,372 COVID-19 vaccine-related tweets, tweets with positive, neutral, and negative sentiments were 42.8%, 26.9%, and 30.3%, respectively. We identified five themes for positive sentiment tweets (trial results, administration, life, information, and efficacy) and five themes for negative sentiment tweets (trial results, conspiracy, trust, effectiveness, and administration). On November 9, 2020, the sentiment score increased significantly (score = 0.234, p = 0.001), then slowly decreased to a neutral sentiment in late December and was maintained until the end of January. At the country level, tweets posted in Brazil had the lowest sentiment score of −0.002, while tweets posted in the United Arab Emirates had the highest sentiment score of 0.162. The overall average sentiment score for the United States was 0.089, with Washington, DC having the highest sentiment score of 0.144 and Wyoming having the lowest sentiment score of 0.036.ConclusionsPublic sentiment on COVID-19 vaccines varied significantly over time and geography. Sentiment analysis can provide timely insights into public sentiment toward the COVID-19 vaccine and guide public health policymakers in designing locally tailored vaccine education programs.     

工作描述法在社区卫生服务中心公共卫生人员数量配置中的运用

目的 采用工作描述法测算成都市某区社区卫生服务中心公共卫生人力资源数量配置需求,探索工作描述法对社区卫生服务中心公共卫生人力资源配置测算的适用性。方法 利用流程分析法、问卷调查法、访谈法等工作描述法对成都市某区8家政府办社区卫生服务中心全年公共卫生服务量进行描述与统计,进而测算出所需配置的公共卫生人力资源数。结果 调查的社区卫生服务中心辖区内每万人需配备的公共卫生人员为2.05人,应配备的公共卫生人员总数为128人,现有132人。结论 运用工作描述法对调查地区社区卫生服务中心公共卫生人员数量配置测算的结果比较符合实际情况,每万人口公共卫生人员配置数测算结果与国内其他研究结果相一致,且符合相关政策规定,工作描述法对社区卫生服务中心公共卫生人力资源配置测算具有一定的适用性。     

试析单位制度对我国公立医院的影响

单位体制是公立医院重要的制度环境,对公立医院体制机制改革具有重要影响。本文试从单位制度理论对公立医院的组织定位、组织特征解释入手,分析单位制目标和功能多元化、单位级别化以及依附性等特征对我国公立医院的影响,结合深化医改和事业单位分类改革的宏观制度背景,探索公立医院体制机制改革的思路,包括细分公立医院职责、明确专业目标和功能定位,以现代公益事业法人治理改革试点实现公立医院管理体制的突破,建立基于契约的聘用关系,促进人才流动。     

Evaluation of a multinational,multilingual vaccine debate on Twitter

BackgroundPublic confidence in an immunization programme is a pivotal determinant of the programme’s success. The mining of social media is increasingly employed to provide insight into the public’s sentiment. This research further explores the value of monitoring social media to understand public sentiment about an international vaccination programme.ObjectiveTo gain insight into international public discussion on the paediatric pentavalent vaccine (DTP-HepB-Hib) programme by analysing Twitter messages.MethodsUsing a multilingual search, we retrospectively collected all public Twitter messages mentioning the DTP-HepB-Hib vaccine from July 2006 until May 2015. We analysed message characteristics by frequency of referencing other websites, type of websites, and geographic focus of the discussion. In addition, a sample of messages was manually annotated for positive or negative message tone.ResultsWe retrieved 5771 messages. Only 3.1% of the messages were reactions to other messages, and 86.6% referred to websites, mostly news sites (70.7%), other social media (9.8%), and health-information sites (9.5%). Country mentions were identified in 70.4% of the messages, of which India (35.4%), Indonesia (18.3%), and Vietnam (13.9%) were the most prevalent. In the annotated sample, 63% of the messages showed a positive or neutral sentiment about DTP-HepB-Hib. Peaks in negative and positive messages could be related to country-specific programme events.ConclusionsPublic messages about DTP-HepB-Hib were characterized by little interaction between tweeters, and by frequent referencing of websites and other information links. Twitter messages can indirectly reflect the public’s opinion about major events in the debates about the DTP-HepB-Hib vaccine.     

Public perception of COVID-19 vaccines through analysis of Twitter content and users

BackgroundWith the global continuation of the COVID-19 pandemic, the large-scale administration of a SARS-CoV-2 vaccine is crucial to achieve herd immunity and curtail further spread of the virus, but success is contingent on public understanding and vaccine uptake. We aim to understand public perception about vaccines for COVID-19 through the wide-scale, organic discussion on Twitter.MethodsThis cross-sectional observational study included Twitter posts matching the search criteria ((‘covid*’ OR ‘coronavirus’) AND ‘vaccine’) posted during vaccine development from February 1st through December 11th, 2020. These COVID-19 vaccine related posts were analyzed with topic modeling, sentiment and emotion analysis, and demographic inference of users to provide insight into the evolution of public attitudes throughout the study period.FindingsWe evaluated 2,287,344 English tweets from 948,666 user accounts. Individuals represented 87.9 % (n = 834,224) of user accounts. Of individuals, men (n = 560,824) outnumbered women (n = 273,400) by 2:1 and 39.5 % (n = 329,776) of individuals were ≥40 years old. Daily mean sentiment fluctuated congruent with news events, but overall trended positively. Trust, anticipation, and fear were the three most predominant emotions; while fear was the most predominant emotion early in the study period, trust outpaced fear from April 2020 onward. Fear was more prevalent in tweets by individuals (26.3 % vs. organizations 19.4 %; p < 0.001), specifically among women (28.4 % vs. males 25.4 %; p < 0.001). Multiple topics had a monthly trend towards more positive sentiment. Tweets comparing COVID-19 to the influenza vaccine had strongly negative early sentiment but improved over time.InterpretationThis study successfully explores sentiment, emotion, topics, and user demographics to elucidate important trends in public perception about COVID-19 vaccines. While public perception trended positively over the study period, some trends, especially within certain topic and demographic clusters, are concerning for COVID-19 vaccine hesitancy. These insights can provide targets for educational interventions and opportunity for continued real-time monitoring.     

军队医院网络舆情监控实践

本文结合军队基层医院创新开展的网络舆情监控工作的实践,探索涉医网络舆情监控及应对的方法,制定一系列应急预案、摸索和优化处置流程,同时也发现亟待解决的不足之处,为军队医院全面开展网络舆情监控提供借鉴与参考。     

未婚青少年实现安全流产需求的障碍

目的:从公立医院医务人员视角分析未婚青少年安全流产需求的主要障碍。方法:采用目的性抽样和方便抽样,对广东、江苏、陕西、甘肃、北京等省市共9所公立医院12名妇产科医务人员展开半结构式个体深入访谈或集体访谈。在定性分析软件NVivo8中基于社会构建理论采用主题分析法对访谈材料进行分析。结果:未婚青少年生殖健康知识的匮乏,公立医院的制度缺陷与医疗服务价格高的印象,以及私立医疗机构欠缺资质与夸大宣传是妨碍未婚青少年安全流产需求实现的主要障碍。结论:亟需加强青少年性教育,改良公立医院流产服务流程,加强流产医疗机构资质审核与监管,规范流产服务和宣传。