Standardized Information Research Articles

책생태계 지속가능성을 위한 북메타데이터 구축에 관한 연구

The domestic and international publishing industry is facing environmental changes in the media industry. Information technology and data integration in the publishing industry are considered fundamental infrastructure for innovation and demand generation in the book business market. This study examines the digitization of publishing, with a focus on book metadata, to support the sustainable book ecosystem in South Korea, which is navigating through the evolving media landscape. The importance of book metadata lies in its efficient data utilization, data accumulation, enhancing discoverability and sales of books, as well as providing useful services to stakeholders in the publishing industry. Additionally, it plays a crucial role in marketing efficiency. In this context, the implications for the sustainability of the book ecosystem are as follows: Firstly, it involves cost savings through standardized book information input and the creation of an environment for marketing using uniform book data. Secondly, it emphasizes the need for interconnected sharing of information among publishers, bookstores, distributors, and other relevant parties. Thirdly, it highlights the requirement for data analysis infrastructure to support comprehensive support systems for stakeholders in the publishing and distribution ecosystem. Finally, it underscores the necessity of utilizing book metadata for the establishment of policies promoting the development of the publishing industry.

A novel naïve Bayes approach to identifying grooming behaviors in the force-plate actometric platform

BackgroundSelf-grooming behavior in rodents serves as a valuable behavioral index for investigating stereotyped and perseverative responses. Most current grooming analyses rely on video observation, which lacks standardization, efficiency, and quantitative information about force. To address these limitations, we developed an automated paradigm to analyze grooming using a force-plate actometer. New methodGrooming behavior is quantified by calculating ratios of relevant movement power spectral bands. These ratios are input into a naïve Bayes classifier, trained with manual video observations. The effectiveness of this method was tested using CIN-d mice, an animal model developed through early-life depletion of striatal cholinergic interneurons (CIN-d) and featuring prolonged grooming responses to acute stressors. Behavioral monitoring was simultaneously conducted on the force-place actometer and by video recording. ResultsThe naïve Bayes approach achieved 93.7% accurate classification and an area under the receiver operating characteristic curve of 0.894. We confirmed that male CIN-d mice displayed significantly longer grooming durations than controls. However, this elevation was not correlated with increases in grooming force. Notably, the dopaminergic antagonist haloperidol reduced grooming force and duration. Comparison with existing methodsIn contrast to observation-based approaches, our method affords rapid, unbiased, and automated assessment of grooming duration, frequency, and force. ConclusionsOur novel approach enables fast and accurate automated detection of grooming behaviors. This method holds promise for high-throughput assessments of grooming stereotypies in animal models of neuropsychiatric disorders.

Has FinTech changed the sensitivity of corporate investment to interest rates?—Evidence from China

Taking into account the differences in the capabilities of FinTech to process standardized and non-standardized information within the credit market, this study introduces a novel perspective: FinTech has dual opposing effects on the interest rate sensitivity of corporate investment. Utilizing data from 2010Q1 to 2020Q4 of China, we empirically test this new viewpoint using the system-GMM and dynamic panel quantile regression methods. The results indicate that, overall, FinTech enhances banks' abilities to process standardized information but does not significantly weaken their capacity to handle non-standardized information. Consequently, banking FinTech amplifies the impact of interest rates on investment. However, further heterogeneity analysis reveals that FinTech does not have a significant impact on the interest rate sensitivity of investment for state-owned enterprises. Contrary to the prevalent belief that FinTech has inclusive benefits, its positive effects on small and medium-sized enterprises (SMEs) are noticeably diminished in regions with lower degrees of marketization, where non-standardized information dominates the credit market. The study's policy implications indicate that the impact of FinTech on alleviating SMEs financing constraints in developing countries may be overstated. Effective FinTech implementation necessitates synergies with market-oriented reforms. Government focus should pivot towards market-driven institutional changes, as relying solely on technological advancements for a 'leapfrog' strategy is likely to prove challenging.

Augmenting mental health literacy of troops in a large military station: A novel approach.

Mental health literacy (MHL) helps in acknowledging the symptoms at an early stage, thus promoting prompt management of negative stress behaviors. Despite the central thrust towards augmentation of MHL of troops, there is a paucity of available literature on the subject matter, especially in the Indian context. Current research explores the efficacy of a standardized Information Education and Communication (IEC) module for the promotion of MHL among troops. 1200 soldiers posted in a large military station underwent a psycho-educational module about stress and related mental health conditions in an open-label experimental study. Data was collected using a simple demographic tool and a specially constructed Armed Forces Medical College (AFMC) mental health awareness questionnaire. The same sample was studied before the IEC activity, immediately after the IEC activity, and again after six months. Community-based psycho-educational module helped in improvement in MHL and the gains were stable at six months. Well-standardized and structured module was found to be an effective strategy for improving MHL. The authors consider this study as seminal for bringing objectivity to mental health promotional programs in the Armed Forces.

PCA‐based fast point feature histogram simplification algorithm for point clouds

AbstractIn order to realize efficient and lightweight digital inspection technology, we propose an improved method to simplification large volumes of scanned point cloud data of aircraft integral panels and facilitate subsequent processing. Fast Point Feature Histogram (FPFH) method is utilized to extract feature information and optimize the Principal Component Analysis (PCA) algorithm to calculate the contribution degree to transform into principal components, yielding PCA‐based FPFH features. Next, based on PCA‐based FPFH features, we classify the point cloud data into non‐feature and feature point clouds and extract the feature point clouds through random downsampling to obtain simplified non‐feature point clouds, extract the feature point clouds to retain their boundary integrity, and downsample the remaining feature point clouds by curvature to obtain the simplified feature point clouds. Finally, we combine the two to obtain the final simplified panel point cloud data within 30 s. To evaluate the simplification effect, we adopt a standardized information entropy‐based point cloud simplification accuracy evaluation method based on the simplification rate. Our method achieves an information entropy of more than 0.95, indicating its effectiveness in simplification point cloud data for efficient and lightweight digital inspection technology.

Sexually and Non-sexually Transmitted Infections and The risk of Prostate Cancer

Abstract Introduction Prostate cancer (PCa) is by far the most common type of cancer among men in western countries. However, relatively little is known about its etiology despite the high morbidity and mortality rates, where only advanced age, ethnicity, and family history of prostate cancer are well-established non-modifiable risk factors. It has been suggested that chronic inflammation may be involved in the development of prostate carcinogenesis. Therefore, our objective was to investigate the role of sexually and non-sexually transmitted infections in the occurrence of prostate cancer with a specific interest in the aggressive types based on data from EPICAP. Methods EPICAP is a population-based case-control study conducted in the département of Hérault, France, between 2012 and 2014. A total of 819 incident cases and 879 controls were interviewed face-to-face using a standardized questionnaire gathering information on known or suspected risk factors of prostate cancer and personal history of specific sexually and non-sexually transmitted infections: Gonorrhea, Syphilis, Trichomonas, Herpes, Mononucleosis, Epstein Barr, Varicella-zoster, and Dengue. Odds Ratios (OR) and their 95% confidence interval were estimated using multivariate unconditional logistic regression. Results No association emerged for the history of sexually transmitted infections (OR 1.04, 95%CI: 0.84-1.25) and non-sexually transmitted infections (OR1.09, 95%CI: 0.89-1.34) and the risk of prostate cancer. Even for all the infections studied separately, there was no association with the risk of low-grade or high-grade prostate cancer. Conclusions Our results showed that sexually or non-sexually transmitted infections do not seem to be risk factors for prostate cancer in the EPICAP study. Therefore, further investigation is needed to help advance our understanding of the role of chronic inflammation in the etiology of prostate cancer, with a particular focus on its most aggressive types.

A repository of occupant-centric control case studies: Survey development and database overview

Occupant-centric controls (OCC) and operations have emerged as a key concept in shifting the focus from conventional building- (or system-) centric operations to a more occupant-centric approach. Despite the potential of OCC to meet occupants’ demands and bridge buildings’ energy performance gap, its implementation in real-world settings has been limited. In addition, there is a lack of standardization in methodologies and terms to facilitate meaningful comparisons among case studies. Therefore, this paper aims to present a repository of OCC case studies, offering a platform for standardization and presenting key information about practical implementations of these strategies in real-world scenarios. To accomplish this, descriptors, terms, and concepts about OCC case studies were discerned through a literature review. These elements were systematically integrated into a structured survey to capture comprehensive information on OCC field study implementations. This paper provides an overview of the survey structure and insights into the current dataset, which comprises a total of 58 OCC case studies. By publishing the case study repository, we intend to establish standard categories for OCC strategies and to offer researchers and practitioners a database through which they can understand trends and possibilities for implementing OCC strategies.

Semantic rule checking of cross-domain building data in information containers for linked document delivery using the shapes constraint language

Information exchange is a crucial process throughout the lifecycle of built assets. Building Information Modeling (BIM) and standardized information delivery enable exchanging, storing, and linking cross-domain information bundled in containers such as the standardized Information Container for Linked Document Delivery (ICDD). While assessing the quality of the interlinking and metadata is essential to allow all parties to interpret an information container correctly, most research efforts have focused on code compliance of domain-specific models. In order to address this gap, this paper proposes an approach for validating ICDD information containers using the Shapes Constraint Language (SHACL), the W3C recommendation for Resource Description Framework (RDF) data validation. For optimized querying and validation, a case study applies SHACL inference rules to the linking structure of ICDD to infer predicates between linked entities in four ICDD containers in varying dataset sizes and different linking methods. Afterward, the validation of these containers is analyzed using three types of validation rules with increasing complexity for another SHACL implementation. Results show the feasibility of cross-domain building information validation in ICDD with SHACL and how performance enhancements can be obtained on an inferred dataset compared to the original dataset.

Minimum Data Set of Mucormycosis in Iran

Introduction: Mucormycosis, the third most prevalent invasive fungal disease ranked, has a very high mortality rate. The timely diagnosis, coupled with the prompt administration of drug and surgical interventions, yields a substantial reduction in mortality rates. To accomplish these objectives, the acquisition of accurate data and information assumes paramount importance. A minimum data set (MDS) serves as a crucial tool for data collection, offering healthcare managers a standardized information resource. Consequently, the aim of this study was to develop a MDS to mucormycosis in Iran.Material and Methods: This research was conducted using a practical approach, employing a two-step Delphi method. An extensive literature review was conducted aimed at extracting relevant information specific to mucormycosis. two individual checklists were developed. Following these checklists underwent rigorous evaluation through the Delphi, involving the 20 experts, consisting of five specialists each in the fields of infectious diseases, dermatology, otolaryngology, and health information management.Results: Experts thoroughly examined a total of 72 out of 86 items on the demographic information checklist throughout both the initial and second phases of the Delphi process. Furthermore, within the clinical information checklist, experts meticulously evaluated 303 out of 323 data elements during the first and second phases of the Delphi process. The demographic checklist was structured into four categories basic information, demographic details, insurance particulars, and referral information. The clinical checklist consisted of seven categories, encompassing risk factors, types of mucormycosis disease, clinical signs and symptoms, diagnosis, species, treatment, and outcomes.Conclusion: In recent years, the prevalence of underlying diseases has witnessed an upward trend, resulting in a subsequent escalation in the number of mucormycosis patients. In light of the burgeoning incidence of mucormycosis cases in Iran, it becomes imperative to establish a standardized MDS for this disease.

Real-world, anti-tobacco environmental impact upon price-induced smoking reduction among urban Chinese men: Evidence from China's 2015 cigarette tax increase.

Raising the price of cigarettes via taxation has been promoted by the World Health Organization as an important tobacco control strategy. Price elasticity of cigarettes is not uniform and is dependent upon individual and environmental determinants. Many studies have examined the determinants of price-induced smoking, taking into account sociodemographic characteristics and consumption patterns. Little research has been conducted on the association between anti-smoking environments and price-induced smoking behavior. This study addresses the deficit within the Chinese context. Participants were 2852 male smokers identified through a multi-stage survey sampling process encompassing 6 cities in China between July and December 2016. A standardized questionnaire tapped price-induced smoking reduction and related information. Both unadjusted and adjusted logistic regression methods were applied in the analyses. In all, 25.5% (95% CI: 22.5-27.9) of smokers in this study decreased their smoking expenditures following the 2015 excise tax increase. The adjusted logistic regression analysis showed that increased exposures to an anti-smoking information environment (AOR=1.39; 95% CI: 1.10-1.79), restricted smoking in their home (AOR=1.67; 95% CI: 1.32-2.08) and workplace (AOR=1.43; 95% CI: 1.09-1.85) were more likely to report diminished cigarette smoking following the tax increases. This study adds to understanding price-induced smoking behavior among urban male Chinese smokers. Strengthening of excise tax policies needs to intensify environmental smoking restrictions and public education campaigns to increase the sensitivity of cigarette price changes among smokers.

Development and validation of a pharmacist-led education model in allergic rhinitis management: a multi-phase study

BackgroundPatient education is identified as one of the core and fundamental management strategies in the management of allergic rhinitis. The Allergic Rhinitis and its Impact on Asthma (ARIA) guidelines developed guidance for the management of allergic respiratory disease, and the guidelines are applicable to the international context. The ARIA guidelines for the pharmacy have specifically encouraged the creation of local pharmacist-led intervention in allergic rhinitis management. This study aims to develop a pharmacist-led educational model using a multi-phase study approach.MethodIn phase one, we conducted a literature review using four databases to extract relevant articles and clinical practice guidelines published between 2017 and 2022. The information was structured into a questionnaire consisting of patient education material (10 domains with 130 items) and pharmacist counseling scopes (15 domains with 43 items), with each item having a rating scale ranging from 1 (lowest) to 9 (highest) level of agreement. Fifty-two panellists, including otorhinolaryngologists and pharmacists, were invited to complete the questionnaire. A consensus agreement was considered when at least 70% of panellists scored 7 to 9 (critically important). A two-round survey was conducted, and descriptive analysis, inter-rater reliability (≥ 0.5–1 indicate moderate to excellent reliability), variation in the relative interquartile (VRIR < 0.3 indicate good stability), and variation in the coefficient of variation (VCV < 40% considered consensus achieved) were performed. In phase two, patient education material was developed into audio-visual format, and in phase three, patients rated its understandability and actionability using a validated Patient Education Materials Assessment Tool.ResultsIn the round one Delphi survey, 43 panellists responded, with 171 out of 173 items achieving “consensus agreement” (75.4–100%). In the second survey, 32 out of 43 panellists responded, with most items (171 out of 173 items) stable across rounds and all items had acceptable internal consistency (VCV: − 12.21–15.81). Two items did not achieve “consensus agreement” (64%) but improved in round two (92.9%), however, instability was observed (VRIR: 0.36). These two items were retained in the model due to achieving the minimum level of agreement and internal consistency (VCV = 15.81). Inter-rater reliability was 0.608 and 0.970 in the respective rounds. Patients rated the educational material as understandable (81.8–100%) and actionable (100%).ConclusionThe validated pharmacist-led education model, with its educational materials tested on end-users, provides structured patient education and pharmaceutical care in assisting patients with allergic rhinitis. The educational material allows the delivery of standardized information by the healthcare providers to the patients. Further research on the effectiveness of this model in improving patients’ symptom control and quality of life is warranted.

Unsupervised Community Detection Algorithm with Stochastic Competitive Learning Incorporating Local Node Similarity

Community detection is an important task in the analysis of complex networks, which is significant for mining and analyzing the organization and function of networks. As an unsupervised learning algorithm based on the particle competition mechanism, stochastic competitive learning has been applied in the field of community detection in complex networks, but still has several limitations. In order to improve the stability and accuracy of stochastic competitive learning and solve the problem of community detection, we propose an unsupervised community detection algorithm LNSSCL (Local Node Similarity-Integrated Stochastic Competitive Learning). The algorithm calculates node degree as well as Salton similarity metrics to determine the starting position of particle walk; local node similarity is incorporated into the particle preferential walk rule; the particle is dynamically adjusted to control capability increments according to the control range; particles select the node with the strongest control capability within the node to be resurrected; and the LNSSCL algorithm introduces a node affiliation selection step to adjust the node community labels. Experimental comparisons with 12 representative community detection algorithms on real network datasets and synthetic networks show that the LNSSCL algorithm is overall better than other compared algorithms in terms of standardized mutual information (NMI) and modularity (Q). The improvement effect for the stochastic competition learning algorithm is evident, and it can effectively accomplish the community detection task in complex networks.

An overview of current evaluation methods of postgraduate dental specialty residents.

A lack of contemporary dental literature exists on evaluating dental residents in postgraduate education, with no standardized criteria or information on technology adoption. This study aims to understand current evaluation methods in dental residency programs and compare them to existing literature. A survey with 22 questions was sent to program directors of 749 ADA/CODA (American Dental Association/Commission on Dental Accreditation)-accredited postgraduate dental residencies. The questions focused on evaluation frequency, faculty involvement, submission methods, and electronic software usage. The survey response rate was 30.2% (226 responses). Results show that 98% of program directors are involved in evaluations, but require more support from auxiliary faculty. Evaluations are typically submitted twice or four times a year, with 12% of programs wanting increased frequency. Face-to-face delivery of feedback is considered crucial. While desktop computers are widely used for evaluation submission, 55% of programs utilize mobile devices, which correlates with higher program director satisfaction. The most popular evaluation software includes New Innovations, MEd Hub, and Qualtrics. Overall, 86.96% of program directors are satisfied with current evaluation practices. Areas needing improvement are non-program director faculty involvement, resident response/feedback, and software navigation. This study found that a majority of program directors of the postgraduate dental education system are using electronic technology for their resident evaluation systems and are satisfied with their current mechanism of evaluation.

Knowledge, attitudes, and practices of caregivers on childhood immunization in Okaikoi sub-metro of Accra, Ghana.

Immunization remains one of the most cost-effective health interventions. However, there are still issues of vaccine hesitancy especially in caregivers who are required to protect their children from vaccine-preventable diseases. This thwarts the overall vaccine coverage in disease-endemic areas such as sub-Saharan Africa. Therefore, to determine the factors that promote vaccine hesitancy in caregivers, this study sought to assess the knowledge, attitude, and practices of caregivers on childhood immunization in Okaikoi, a sub-metro of Accra in Ghana. A cross-sectional study on childhood immunization was conducted to determine the knowledge, attitudes, and practices of caregivers. A total of 120 caregivers with infants aged 12 months to 23 months were interviewed with a structured questionnaire containing open-ended and closed-ended queries. From the community, infants whose caregivers had adhered completely to immunization constituted 53.3% while the rest were partially immunized. The two main deterrents to complete immunization were time constraints (25.8%) and forgetfulness (17.5%). It was observed that vaccination uptake and maternal level of education, as well as vaccination adverse reaction, did not impact the completion of the EPI program by these caregivers. Unfortunately, it was noted that caregivers with higher education levels were unable to complete their vaccination schedules due to their busy work schedules. Nonetheless, the main deterrent to adhering to complete childhood immunization was poor maternal knowledge (58%). The study revealed that, the caregivers in the community had poor knowledge on vaccination and its benefits, and therefore, with no strict adherence to vaccination schedules. This promoted the incomplete immunization of children in the community by their caregivers. Also, since the main source of information with regard to immunization in the sub-metro was through the antenatal and postnatal child welfare clinics and the media, we recommend that the health workers collaborate with media personnel to ensure that standardized information is disseminated.

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization

BackgroundWhole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical databases and a lack of proper benchmarking on real-world patient cohorts.MethodsWe developed ClinPrior, a novel method for the analysis of WES/WGS data that ranks candidate causal variants based on the patient’s standardized phenotypic features (in Human Phenotype Ontology (HPO) terms). The algorithm propagates the data through an interactome network-based prioritization approach. This algorithm was thoroughly benchmarked using a synthetic patient cohort and was subsequently tested on a heterogeneous prospective, real-world series of 135 families affected by hereditary spastic paraplegia (HSP) and/or cerebellar ataxia (CA).ResultsClinPrior successfully identified causative variants achieving a final positive diagnostic yield of 70% in our real-world cohort. This includes 10 novel candidate genes not previously associated with disease, 7 of which were functionally validated within this project. We used the knowledge generated by ClinPrior to create a specific interactome for HSP/CA disorders thus enabling future diagnoses as well as the discovery of novel disease genes.ConclusionsClinPrior is an algorithm that uses standardized phenotype information and interactome data to improve clinical genomic diagnosis. It helps in identifying atypical cases and efficiently predicts novel disease-causing genes. This leads to increasing diagnostic yield, shortening of the diagnostic Odysseys and advancing our understanding of human illnesses.

The digital pregnancy: A qualitative study of Danish women’s use of pregnancy apps

Based on an interview study with Danish women, this article explores how the frequent use of pregnancy mobile applications shapes the lived or experienced pregnancy. More specifically, we look at a reported dilemma between, on one hand, using the information of pregnancy apps on bodily and fetal developments to gain a sense of control over individual pregnancies and, on the other hand, an experience of the apps becoming something of a controlling factor in the lives of pregnant women. Respondents reported that the information of the apps created different kinds of concerns and that they became almost obsessed with comparing their own symptoms with the apps’ standardized information on what they could expect to experience at specific stages of the pregnancy. Our analysis draws on a socio-material perspective that acknowledges the ability of technology to enact certain kinds of experiences and shape concerns. We argue that the power of the apps (so to speak) is related, in part to the abundance of information they provide, which may contribute to a sensation of never knowing enough, but also in part to the use of apps becoming an integrated part of everyday cell phone routines.

Policy-Relevant Lists of Species

Biodiversity-related regulations often include lists of species in annexes of legal texts. Unfortunately, those publications are often published in PDF with lists in tables in annexes, not suitable for machine reading nor for incorporation into databases, decision making tools or any other information technology tools. This situation undermines efficient data reporting and therefore limits the follow-up of the policies. I tried to publish several species lists*1 from some key European Union legislation (e.g., the Habitats and Birds Directives) to ChecklistBank. Based on my experience, I will discuss the adequacy of existing biodiversity informatics standards to publish policy-relevant lists of species and see how they differ from usual taxonomic checklists. I will also suggest possible improvements to cope with the specificities of these policy-relevant lists.

Associations between dementia staging, neuropsychiatric behavioral symptoms, and divorce or separation in late life: A case control study.

Dementia can be difficult for married couples for many reasons, including the introduction of caregiving burden, loss of intimacy, and financial strain. In this study, we investigated the impact of dementia staging and neuropsychiatric behavioral symptoms on the likelihood of divorce or separation for older adult married couples. For this case-control study, we used data from the National Alzheimer's Coordinating Center (NACC) Uniform dataset (UDS) versions 2 and 3. This dataset was from 2007 to 2021 and contains standardized clinical information submitted by NIA/NIH Alzheimer's Disease Research Centers (ADRCs) across the United States (US). This data was from 37 ADRCs. We selected participants who were married or living as married/domestic partners at their initial visit. Cases were defined by a first divorce/separation occurring during the follow-up period, resulting in 291 participants. We selected 5 controls for each married/living as married case and matched on age. Conditional logistic regression estimated the association between overall Neuro Psychiatric Inventory (NPI) score and severity of individual symptoms of the NPI with case/control status, adjusted for education, the CDR® Dementia Staging Instrument score, living situation, symptom informant, sex, and race. Separate analyses were conducted for each symptom. Multiple comparisons were accounted for with the Hochberg method. Later stage of dementia was negatively associated with divorce/separation with an adjusted odds ratio (AOR) = 0.68 (95%CI = 0.50 to 0.93). A higher overall NPI score was positively associated with divorce/separation AOR = 1.08 (95% CI = 1.03 to 1.12,). More severe ratings of agitation/aggression, depression/dysphoria, disinhibition, and elation/euphoria were associated with greater odds of divorce/separation. Among older adults in the US, a later stage of dementia is associated with a lower likelihood of divorce or separation, while having more severe neuropsychiatric behavioral symptoms of agitation/aggression, depression/dysphoria, disinhibition, and elation/euphoria are associated with a higher likelihood of divorce or separation.

Does Social Media Dominate Government Report Cards in Influencing Nursing Home Demand?

Problem definition: Social media has become an indispensable platform for disseminating quality information to consumers across various service sectors. Recently, it has extended its influence to healthcare services, which traditionally relied on government report cards to disclose standardized quality information to the public. This article explores the impact of social media on consumer demand for healthcare services and compares its effectiveness with government report cards. Methodology/results: We analyze quality ratings of U.S. nursing homes collected from two information channels: (1) consumer ratings on Yelp and (2) government ratings on Nursing Home Compare, both of which adopt a five-star quality rating scale and are accessible on the Internet. We employ the method of difference-in-differences with continuous treatment intensity and instrumental variables to analyze the data. Using nursing home resident admissions as a proxy for consumer demand, we find that higher Yelp ratings led to higher consumer demand, particularly among Medicare-covered consumers. Furthermore, the effect of Yelp ratings was primarily driven by extreme ratings (one-star or five-star), as opposed to neutral ratings. We also find that Yelp ratings exerted a stronger effect on consumer demand than government ratings. This dominance of Yelp ratings over government ratings was observed primarily in markets with high Yelp penetration or markets with low and medium consumer education levels. Although higher Yelp ratings were associated with increased net incomes, we find little evidence that nursing homes made quality improvement in response to their Yelp ratings. Managerial implications: We recommend that the Centers for Medicare and Medicaid Services recognize social media platforms as valuable sources of information and collaborate with reputable platforms, such as Yelp, to promote public awareness of government report cards like Nursing Home Compare. Moreover, we advise nursing home operators to proactively manage their reputation on social media by promptly addressing consumer complaints and implementing quality improvement measures. Funding: Y. Li was supported by the National Natural Science Foundation of China [Grant 72301193], the Shanghai Sailing Program [Grant 22YF1451000], and the Fundamental Research Funds for the Central Universities. S. F. Lu was supported by the Gerald Lyles Rising Star fund. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0303 .

Centralization and democratization: Managing crisis communication in health care delivery.

Communication is an essential organizational process for responding to adversity. Managers are often advised to communicate frequently and redundantly during crises. Nonetheless, systematic investigation of how information receivers perceive organizational communication amid crises has remained lacking. The aim of this study was to characterize features of effective internal crisis communication by examining how information-sharing processes unfolded during the initial stage of the COVID-19 pandemic. Between June and August 2020, we conducted 55 semistructured interviews with emergency department workers practicing in a variety of roles. We analyzed interview transcripts following constructivist constant comparative methods. Our findings revealed that at the onset of COVID-19 pandemic response, emergency department workers struggled with immense fear and anxiety amid high uncertainty and equivocality. Frequent and redundant communication, however, resulted in information delivery and uptake problems, worsening anxiety, and interpersonal tension. These problems were ameliorated by the emergence of contextual experts who centralized and democratized communication. Centralization standardized information received across roles, work schedules, and settings while decoupling internal communication from turbulence in the environment. Democratization made information accessible in a way that all could understand. It also ensured information senders' receptiveness to feedback from information receivers. Centralization and democratization together worked to reduce sensed uncertainty and equivocality, which reduced anxiety and interpersonal tension. Establishing frequent and redundant communication strategies does not necessarily address the anxiety and interpersonal tension produced by uncertainty and equivocality in crises. Centralization and democratization of crisis communication can reduce anxiety, improve coordination, and promote a safer workplace and patient care environment.