Normative uncertainty and middle-status innovation in the US daily newspaper industry

2019 ◽  
Vol 18 (3) ◽  
pp. 377-406
Author(s):  
Bo Kyung Kim
Keyword(s):  
Digital Media ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Daily Newspaper ◽  
Newspaper Industry ◽  
Adoption And Implementation ◽  
Binomial Regression ◽  
The Us ◽  
Normative Uncertainty ◽  
Middle Status

This article focuses on normatively uncertain innovations and asks when and how organizational status affects the adoption and implementation of these innovations. I argue that middle-status organizations perceive normative uncertainty more as an opportunity for gain, whereas high- and low-status organizations perceive it more as a threat of loss and competition. Consequently, middle-status organizations are likely to be the first to adopt normatively uncertain innovations and to implement them in a way that emphasizes normative uncertainty. Event history and negative binomial regression analyses of the US newspaper industry from 1993 to 2007, the period after the emergence of digital media that was normatively uncertain, support my theoretical arguments. Middle-status newspapers launched their websites faster than other newspapers did. In addition, they emphasized interactivity on the web, which could potentially change the identity of newspapers from sole news producers to facilitators.

scholarly journals ECONOMIC IMPACT OF HOSPITALIZATIONS IN US ADULTS WITH SARCOPENIA

2019 ◽  
pp. 1-7
Author(s):  
S. Goates ◽  
K. Du ◽  
M.B. Arensberg ◽  
T. Gaillard ◽  
J. Guralnik ◽  
...  
Keyword(s):  
Black Women ◽  
Economic Burden ◽  
Negative Binomial ◽  
Functional Limitations ◽  
Negative Binomial Regression ◽  
Health And Nutrition ◽  
Binomial Regression ◽  
The Us ◽  
The Cost ◽  
Us Census

ackground: Sarcopenia is characterized by progressive loss of muscle mass with corresponding decline in strength and/or physical function. The economic burden of sarcopenia-associated disability is considerable in the US. Objective: To estimate the cost of hospitalizations in US adults with sarcopenia categorized by age, sex, and race/ethnicity. Design, setting and participants: A retrospective, prevalence based, economic burden study, consisting of 4011 adults aged ≥40 years with and without sarcopenia. Methods: Data on prevalence of low lean mass, functional limitations, and hospitalizations were obtained from the National Health and Nutrition Examination Survey (1999-2004); cost of hospitalizations was obtained from the Healthcare Cost and Utilization Project – National Inpatient Sample (2014), and population estimates were obtained from the US Census (2014). Probability and cost of hospitalizations were estimated by multiple logistic regression and negative binomial regression models, respectively. Results: The total estimated cost of hospitalizations in individuals with sarcopenia was USD $40.4 billion with an average per person cost of USD $260. Within this category, average per person cost was highest for Hispanic women (USD $548) and lowest for Non-Hispanic Black women (USD $25); average per person cost was higher for older adults (≥65 years) (USD $375) than younger adults (40-64 years) (USD $204) with sarcopenia. The total cost of hospitalizations in individuals with sarcopenia (≥65 years) was USD $19.12 billion. Individuals with sarcopenia had greater odds of hospitalization (OR, 1.95; p<.001) compared to those without and had an annual marginal increase in cost of USD $2315.7 per person compared to individuals without sarcopenia. Conclusion: Sarcopenia places considerable economic burden on the US healthcare system. The ethnic disparity and economic burden associated with sarcopenia warrant further investigation.

scholarly journals Emergency activations for chest pain and ventricular arrhythmias related to regional COVID-19 across the US

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sidney Aung ◽  
Eric Vittinghoff ◽  
Gregory Nah ◽  
Anthony Lin ◽  
Sean Joyce ◽  
...  
Keyword(s):  
Chest Pain ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
The United States ◽  
Myocardial Infarctions ◽  
Healthcare Facilities ◽  
Binomial Regression ◽  
The Us ◽  
National Emergency ◽  
Us Census

AbstractEvidence that patients may avoid healthcare facilities for fear of COVID-19 infection has heightened the concern that true rates of myocardial infarctions have been under-ascertained and left untreated. We analyzed data from the National Emergency Medical Services Information System (NEMSIS) and incident COVID-19 infections across the United States (US) between January 1, 2020 and April 30, 2020. Grouping events by US Census Division, multivariable adjusted negative binomial regression models were utilized to estimate the relationship between COVID-19 and EMS cardiovascular activations. After multivariable adjustment, increasing COVID-19 rates were associated with less activations for chest pain and non-ST-elevation myocardial infarctions. Simultaneously, increasing COVID-19 rates were associated with more activations for cardiac arrests, ventricular fibrillation, and ventricular tachycardia. Although direct effects of COVID-19 infections may explain these discordant observations, these findings may also arise from patients delaying or avoiding care for myocardial infarction, leading to potentially lethal consequences.

Receipt of and Spending on Cessation Medication Among US Adults With Employer-Sponsored Health Insurance, 2010 and 2017

2021 ◽  
pp. 003335492098415
Author(s):  
Sundar S. Shrestha ◽  
Xin Xu ◽  
Xu Wang ◽  
Stephen D. Babb ◽  
Brian S. Armour ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Health Insurance ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Annual Average ◽  
Smoking Cessation Treatment ◽  
Cessation Treatment ◽  
Binomial Regression ◽  
The Us ◽  
Annual Average Number

Objective Studies examining the use of smoking cessation treatment and related spending among enrollees with employer-sponsored health insurance are dated and limited in scope. We assessed changes in annual receipt of and spending on cessation medications approved by the US Food and Drug Administration (FDA) among tobacco users with employer-sponsored health insurance from 2010 to 2017. Methods We analyzed data on 439 865 adult tobacco users in 2010 and 344 567 adult tobacco users in 2017 from the IBM MarketScan Commercial Database. We used a negative binomial regression to estimate changes in receipt of cessation medication (number of fills and refills and days of supply). We used a generalized linear model to estimate spending (total, employers’, and out of pocket). In both models, covariates included year, age, sex, residence, and type of health insurance plan. Results From 2010 to 2017, the percentage of adult tobacco users with employer-sponsored health insurance who received any cessation medication increased by 2.4%, from 15.7% to 16.1% ( P < .001). Annual average number of fills and refills per user increased by 15.1%, from 2.5 to 2.9 ( P < .001) and days of supply increased by 26.4%, from 81.9 to 103.5 ( P < .001). The total annual average spending per user increased by 53.6%, from $286.40 to $440.00 ( P < .001). Annual average out-of-pocket spending per user decreased by 70.9%, from $70.80 to $20.60 ( P < .001). Conclusions Use of smoking cessation medications is low among smokers covered by employer-sponsored health insurance. Opportunities exist to further increase the use of cessation medications by promoting the use of evidence-based cessation treatments and reducing barriers to coverage, including out-of-pocket costs.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

scholarly journals Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Nabil Shaaban ◽  
Bárbara Peleteiro ◽  
Maria Rosario O. Martins
Keyword(s):  
Length Of Stay ◽  
Regression Model ◽  
Random Effects ◽  
Count Data ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Comprehensive Approach ◽  
Negative Binomial Regression Model ◽  
Hiv Patients ◽  
Binomial Regression

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.

scholarly journals Association between breakfast skipping and metabolic outcomes by sex, age, and work status stratification

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jun Heo ◽  
Won-Jun Choi ◽  
Seunghon Ham ◽  
Seong-Kyu Kang ◽  
Wanhyung Lee
Keyword(s):  
Regression Analysis ◽  
Negative Binomial ◽  
Metabolic Diseases ◽  
Young Male ◽  
Negative Binomial Regression ◽  
Final Analysis ◽  
Work Status ◽  
Breakfast Skipping ◽  
Metabolic Outcomes ◽  
Binomial Regression

Abstract Background The association between breakfast skipping and abnormal metabolic outcomes remains controversial. A comprehensive study with various stratified data is required. Objective The aim of this study was to investigate the relationship between abnormal metabolic outcomes and breakfast skipping by sex, age, and work status stratification. Methods We used data from the Korea National Health and Nutrition Examination Surveys from 2013 to 2018. A total of 21,193 (9022 men and 12,171 women) participants were included in the final analysis. The risk of metabolic outcomes linked to breakfast skipping was estimated using the negative binomial regression analysis by sex, work status, and age stratification. Results A total of 11,952 (56.4%) participants consumed breakfast regularly. The prevalence of abnormal metabolic outcomes was higher among those with irregular breakfast consumption habits. Among young male workers, negative binomial regression analysis showed that irregular breakfast eaters had a higher risk of abnormal metabolic outcomes, after adjusting for covariates (odds ratio, 1.15; 95% confidence interval, 1.03–1.27). Conclusions The risk of abnormal metabolic outcomes was significant in young men in the working population. Further studies are required to understand the association of specific working conditions (working hours or shift work) with breakfast intake status and the risk of metabolic diseases.

scholarly journals Coronary deaths during Midsummer festival in Finland: miseries of long, light nights

2021 ◽  
Author(s):  
Simo Näyhä
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Alcohol Consumption ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Adverse Consequence ◽  
Heavy Alcohol ◽  
Summer Peak ◽  
Binomial Regression ◽  
Heavy Alcohol Consumption

AbstractThis paper examines whether the anomalous summer peak in deaths from coronary heart disease (CHD) in Finland could be attributed to adverse effects of the Midsummer festival and alcohol consumption during the festival. Daily deaths from CHD and alcohol poisoning in Finland, 1961–2014, that occurred during the 7 days centering on Midsummer Day were analysed in relation to deaths during 14 to 4 days before and 4 to 14 after Midsummer Day. Daily counts of deaths from CHD among persons aged 35–64 years were regressed on days around the Midsummer period by negative binomial regression. Mortality from CHD was highest on Midsummer Day (RR 1.25 (95% confidence interval 1.12–1.31), one day after the peak in deaths from alcohol poisonings. RR for CHD on Midsummer Day was particulary high (RR = 1.43; 1.09–1.86) in the 2000s, 30% of deaths being attributable to that day. In conclusion, the anomalous and prominent summer peak in deaths from CHD in Finland is an adverse consequence of the Midsummer festival. The most likely underlying reason is heavy alcohol consumption during the festival period, especially on Midsummer Eve. In the 2000s, one third of deaths from CHD on Midsummer Day are preventable.

Sign in / Sign up

Export Citation Format

Share Document