Health Communication for Hospice Care through Chinese media: Digital Topic Modeling Approach (Preprint)

2021 ◽  
Author(s):  
Qian Liu ◽  
Zequan Zheng ◽  
Jingsen Chen ◽  
Winghei Tsang ◽  
Jin Shan ◽  
...  
Keyword(s):  
Mass Media ◽  
Health Communication ◽  
Topic Modeling ◽  
Health Care Services ◽  
Hospice Care ◽  
Patient Treatment ◽  
News Reports ◽  
Care Services ◽  
Time Period ◽  
Second Period

BACKGROUND Hospice care, a type of end-of-life care provided for dying patients and their families, has been rooted in China since the 1980s. It can improve receivers’ quality of life as well as ease their economic burden. The Chinese mass media have continued to actively dispel misconceptions of hospice care and deliver the latest information to citizens. OBJECTIVE This study aimed to retrieve and analyze news reports on hospice care to gain insight into whether any differences exist in delivered heath information as time went by and the role the mass media played in health communication in recent years. METHODS We searched the Huike (WiseSearch) database for related news from Chinese mass media between 2014 and 2019. We set January 1, 2014 to December 31, 2016 as the first time period and January 1, 2017 to December 31, 2019 as the second time period. Python was used to complete the data cleaning process. We determined appropriate topic numbers for these two periods based on coherence score and applied the latent Dirichlet allocation topic modeling. Keywords of each topic and corresponding topics’ names were then generated. The topics were plotted into different circles and their distances on the two-dimensional plane was represented by multidimensional scaling. RESULTS After removing the duplicated and irrelevant news articles, we obtained a total of 2227 articles. We chose eight as the suitable topic number for both time periods and generated topics’ name and their keywords. The top three most reported topics in the first period were patient treatment, hospice care stories, and development of health care services and health insurance, accounting for 18.68% (n = 178), 16.58% (n = 158), and 14.17% (n = 135) of the collected reports, respectively. The top three most reported topics in the second period were hospice care stories, patient treatment, and development of health care services, accounting for 15.62% (n = 199), 15.38 (n = 15.38), and 14.27% (n = 182), respectively. CONCLUSIONS Topic modeling of news reports gives us a better understanding of patterns of health communication about hospice care by mass media. Chinese mass media frequently reported on hospice care in April due to a traditional Chinese festival. An increase in coverage in the second period was observed. These two periods share six similar topics, among which patient treatment outstrips hospice care stories as the most-reported topic in the second period, showing the humanistic spirit behind the reports. We suggest stakeholders cooperate with the mass media when planning to update policies.

scholarly journals Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach (Preprint)

2020 ◽  
Author(s):  
Qian Liu ◽  
Zequan Zheng ◽  
Jiabin Zheng ◽  
Qiuyi Chen ◽  
Guan Liu ◽  
...  
Keyword(s):  
Mass Media ◽  
Health Communication ◽  
News Media ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Community Education ◽  
Early Stage ◽  
News Reports ◽  
Media Reports ◽  
Novel Coronavirus

BACKGROUND In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. OBJECTIVE The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. METHODS We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. RESULTS After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics’ themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. CONCLUSIONS Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.

scholarly journals Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach

10.2196/19118 ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. e19118 ◽  
Author(s):  
Qian Liu ◽  
Zequan Zheng ◽  
Jiabin Zheng ◽  
Qiuyi Chen ◽  
Guan Liu ◽  
...  
Keyword(s):  
Mass Media ◽  
Health Communication ◽  
News Media ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Community Education ◽  
Early Stage ◽  
News Reports ◽  
Media Reports ◽  
Novel Coronavirus

Background In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. Objective The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. Methods We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. Results After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics’ themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. Conclusions Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.

scholarly journals Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: A Digital Topic Modeling Approach

2020 ◽  
Author(s):  
Qian Liu ◽  
Zequan Zheng ◽  
Jiabin Zheng ◽  
Qiuyi Chen ◽  
Guan Liu ◽  
...  
Keyword(s):  
Mass Media ◽  
Health Communication ◽  
Sentiment Analysis ◽  
Topic Modeling ◽  
Modeling Method ◽  
Search Term ◽  
Public Attention ◽  
News Reports ◽  
The Mass Media ◽  
Novel Coronavirus

AbstractBackgroundIn December 2019, some COVID-19 cases were first reported and soon the disease broke out. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus.MethodsWe adopted the Huike database to extract news articles about coronavirus from major press media, between January 1st, 2020, to February 20th, 2020. The data were sorted and analyzed by Python software and Python package Jieba. We sought a suitable topic number using the coherence number. We operated Latent Dirichlet Allocation (LDA) topic modeling with the suitable topic number and generated corresponding keywords and topic names. We divided these topics into different themes by plotting them into two-dimensional plane via multidimensional scaling.FindingsAfter removing duplicates, 7791 relevant news reports were identified. We listed the number of articles published per day. According to the coherence value, we chose 20 as our number of topics and obtained their names and keywords. These topics were categorized into nine primary themes based on the topic visualization figure. The top three popular themes were prevention and control procedures, medical treatment and research, global/local social/economic influences, accounting for 32·6%, 16·6%, 11·8% of the collected reports respectively.InterpretationThe Chinese mass media news reports lag behind the COVID-19 outbreak development. The major themes accounted for around half the content and tended to focus on the larger society than on individuals. The COVID-19 crisis has become a global issue, and society has also become concerned about donation and support as well as mental health. We recommend that future work should address the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.FundingNational Social Science Foundation of China (18CXW021)Evidence before this studyThe novel coronavirus related news reports have engaged public attention in China during the COVID-19 crisis. Topic modeling of these news articles can produce useful information about the significance of mass media for early health communication. We searched the Huike database, the most professional Chinese media content database, using the search term “coronavirus” for related news articles published from January 1st, 2020, to February 20th, 2020. We found that these articles can be classified into different themes according to their emphasis, however, we found no other studies apply topic modeling method to study them.Added value of this studyTo our knowledge, this study is the first to investigate the patterns of health communications through media and the role the media have played and are still playing in the light of the current COVID-19 crisis in China with topic modeling method. We compared the number of articles each day with the outbreak development and identified there’s a delay in reporting COVID-19 outbreak progression for Chinese mass media. We identify nine main themes for 7791 collected news reports and detail their emphasis respectively.Implications of all the available evidenceOur results show that the mass media news reports play a significant role in health communication during the COVID-19 crisis, government can strengthen the report dynamics and enlarge the news coverage next time another disease strikes. Sentiment analysis of news data are needed to assess the actual effect of the news reports.

scholarly journals Lista de comprobación para mejorar la información sobre fármacos en la prensa: la importancia de informar sobre las fases y la incertidumbre de la investigación = A checklist for improving drug information in the general press: the importance of reporting on the phases and uncertainty of research

2018 ◽  
Vol 9 (2) ◽  
pp. 203
Author(s):  
Fèlix Bosch ◽  
Clàudia Escalas ◽  
Ainoa Forteza ◽  
Elisabet Serés ◽  
Gonzalo Casino
Keyword(s):  
Mass Media ◽  
Health Communication ◽  
Drug Information ◽  
Qualitative Studies ◽  
Current Phase ◽  
Quality Of Reporting ◽  
Interest In Science ◽  
News Reports ◽  
Medios De Comunicacion

Resumen: El interés de la ciudadanía por la ciencia es consecuente con que los medios de comunicación difundan también información sobre fármacos. Sin embargo, se requieren más estudios cuantitativos y cualitativos que analicen este tipo de información en la prensa generalista. En este artículo se revisan los estudios que han analizado las noticias sobre fármacos, así como las herramientas disponibles para evaluar su calidad. Se revisan aspectos cualitativos a considerar al informar sobre fármacos en investigación o ya comercializados: la necesidad de contrastar las fuentes, citar la publicación de origen y emplear un lenguaje comprensible. Asimismo, se recomienda informar tanto de beneficios como de riesgos, y hacerlo con valores relativos y absolutos; evitar la generación de falsas expectativas y contextualizar los aspectos relacionados con la financiación. Además, se sugiere explicitar la fase de investigación en la que se encuentra el fármaco para así orientar sobre las posibilidades y plazos para su comercialización, y sobre las fuentes de información más adecuadas. Con esta revisión y las consideraciones planteadas, este artículo pretende promover una reflexión general para mejorar la calidad de las noticias sobre fármacos, a la vez que proporciona una primera lista de comprobación útil para comunicadores y periodistas científicos.Palabras clave: comunicación en salud; divulgación; fármacos; información; investigación; medicamentos; medios de comunicación; prensa.Abstract: Given the public’s interest in science, it is logical that the mass media disseminate information about drugs. However, few quantitative or qualitative studies have analyzed the way this type of information is presented in the lay press. This article reviews the studies that have analyzed news reports about drugs and discusses the tools that are available to evaluate the quality of such reports. It also examines qualitative aspects when reporting on drugs in research or when have already been marketed: the need to check the sources, to cite the original reports, and to use language that is easy to understand. To avoid creating false expectations, news reports should inform readers about risks as well as benefits in both relative and absolute terms and put financial aspects in context. Moreover, it is important to specify the drug’s current phase of development to inform if and when it is likely to be commercialized. Finally, news reports about drugs should point readers to the most appropriate sources to obtain further information. This article aims to promote general reflection and ultimately to improve the quality of reporting about drugs in the general press and to provide a checklist for science communicators and journalists.Keywords: health communication; popularization; drugs; information; investigation; medicines; media; press.

Linking Cost Control Measures to Health Care Services by Using Activity-Based Information

1995 ◽  
Vol 8 (4) ◽  
pp. 221-233 ◽  
Author(s):  
Ronald E. Hoyt ◽  
Colin M. Lay
Keyword(s):  
Health Care ◽  
Health Care Services ◽  
New Technology ◽  
Control Measures ◽  
Patient Treatment ◽  
Management Information ◽  
Care Services ◽  
Potential Benefits ◽  
Cost Variability ◽  
The Impact

Canada's health care institutions are under pressure to limit expenditures, maintain or increase productivity, and assimilate new technology. Even though more than 75% of hospital operating expenditures are controllable, according to a study by the Economic Council of Canada, cost systems are needed to provide essential management information. The new Canadian Management Information System (MIS) Guidelines for health care are designed to provide accurate cost measurement of patient treatment and to help managers evaluate the impact of planned program changes on areas of operational responsibility. Other potential benefits of implementing the MIS guidelines include correcting dysfunctional funding of health care units with benchmarking and setting high reporting standards for resource use at the patient level (MIS, 1991). This paper focuses on one important aspect of bringing these costs under control by examining the relation between cost deviations (variances) and underlying cost drivers. Our discussion will lead to the conclusion that incompatibility of DRG methodology and traditional cost accounting models may be an important source of cost variability within diagnostically-related disease groupings.

scholarly journals Regional variations of amenable mortality rate in Latvia

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J Skrule ◽  
J Lepiksone
Keyword(s):  
Health Care ◽  
Death Rate ◽  
Health Care Services ◽  
National Level ◽  
Regional Level ◽  
Regional Variations ◽  
Reduce Health Inequality ◽  
Amenable Mortality ◽  
Care Services ◽  
Time Period

Abstract Background Death can be considered as amenable if all or most deaths from that cause (at certain age group if appropriate) could be avoided through optimal quality of health care. Amenable mortality is one of indicators to use for assessing health system performance and outcome. Methods For amenable death causes using list of diseases and conditions from Office for National Statistics of United Kingdom (used by Eurostat). Calculation of amenable death rate (per 100000 population) for ages 0 to 74 years at regional level (six statistical regions) for time period 2015-2017, direct age-standardization to the overall national population. Results accompanied by confidence intervals (95%). Results There is a slight decline in amenable mortality of Latvia at national level over the period 2015-2017. Amenable death rate of Latvia in 2017 was 309 per 100 000 (95% CI, 308.95 - 309.05). Death rates at regional level varies from 274.34 (274.23 - 274.44) in Pieriga region to 375.49 (375.37 - 375.62) per 100 000 in Latgale region. There are no significant changes in ranking of regions for three years period. Conclusions Results shows that there are differences of amenable mortality rates between regions of Latvia. There are health inequalities between regions: Pieriga region show the best health care services performance, while Latgale displays the worst performance. There is field for deeper analysis and find better interventions for improvements at national level and reducing variability between regions. Key messages There are regional variations of amenable mortality in Latvia. Regional variations show places to reduce health inequality.

scholarly journals Patterns of Health Care Services During Pediatric Concurrent Hospice Care: A National Study

2021 ◽  
pp. 104990912110186
Author(s):  
Lisa C. Lindley ◽  
Radion Svynarenko ◽  
Kim Mooney-Doyle ◽  
Annette Mendola ◽  
Wendy C. Naumann ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Services ◽  
Latent Class ◽  
Hospice Care ◽  
Care Service ◽  
Health Care Service ◽  
National Study ◽  
Care Needs ◽  
Demographic Profiles ◽  
Care Services

Background: Children at end of life have unique and complex care needs. Although there is increasing evidence about pediatric concurrent hospice care, the health care services received while in hospice have not received sufficient attention. Objectives: To examine the health care services, unique clusters of health care services, and characteristics of the children in the clusters. Methods: Multiple data sources were used including national Medicaid claims data. Children under 21years in pediatric concurrent hospice care were included. Using Medicaid categories assigned to claims, health care services were distributed across 20 categories. Latent class analysis was used to identify clusters of health care services. Demographic profiles of the clusters were created. Results: The 6,243 children in the study generated approximately 500,0000 non-hospice, health care service claims while enrolled in hospice care. We identified 3 unique classes of health care services use: low (61.1%), moderate (18.1%), and high (20.8%) intensity. The children in the 3 classes exhibited unique demographic profiles. Conclusions: Health care services cluster together in unique fashion with distinct patterns among children in concurrent hospice care. The findings suggest that concurrent hospice care is not a 1-size-fit all solution for children. Concurrent hospice care may be customized and require attention to care coordination to ensure high-quality care.

scholarly journals Health Communication for Hospice Care through Chinese Media: Digital Topic Modeling Approach (Preprint)

10.2196/29375 ◽  
2021 ◽  
Author(s):  
Qian Liu ◽  
Zequan Zheng ◽  
Jingsen Chen ◽  
Winghei Tsang ◽  
Jin Shan ◽  
...  
Keyword(s):  
Health Communication ◽  
Topic Modeling ◽  
Hospice Care ◽  
Chinese Media ◽  
Modeling Approach

Examining the Light and Dark of an Online Young Adult Cancer Support Community

2016 ◽  
Vol 27 (6) ◽  
pp. 938-948 ◽  
Author(s):  
Brittani Crook ◽  
Brad Love
Keyword(s):  
Young Adult ◽  
Health Communication ◽  
Support Groups ◽  
Health Care Services ◽  
Dark Side ◽  
Online Support ◽  
Online Support Groups ◽  
Care Providers ◽  
Care Services ◽  
Cancer Support

The young adult (YA) cancer community represents an understudied population in interpersonal and health communication scholarship. Through qualitative analysis, this study sought to advance a dark side perspective by exploring the content of messages shared in an online support forum for YAs with cancer. Our findings highlight a variety of complexities YAs face in an online cancer support community, including the light and dark of soliciting support, disclosing to a community, advocacy online, negative sentiment evaluating health care services, and asynchronous communication. Understanding the light and dark nuances involved with participating in an online YA support forum advances a dark side perspective on the scholarly research in health communication that can ultimately help care providers recommend resources and coach YAs to optimally and effectively use and navigate online support groups.

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