To present the knowledge produced on challenges of health services for maintaining surgical care practices in times of the COVID-19 pandemic.Coleta SUS, BIGG, BINACIS, SciELO, PubMed, Science Direct, and Cochrane Library databases.This is an integrative literature review, performed with descriptors ‘Operating rooms’ and ‘Coronavirus Infections’ in the MEDLINE/PubMed Central, IBECS, LILACS, BDENF, Of the 405 studies analyzed, 27 met the inclusion criteria. The main challenges for surgical services during the pandemic were: (i) rearrangement of general practice in surgical units; (ii) administration and management of resources and elective surgeries; (iii) follow-up and control of preoperative patients to medium term; (iv) maintenance of patients’ and health professionals’ autonomy and mental health in this context; and (v) teaching health residents in the operating room.For surgical care services, the challenges caused by managing the high demand of patients in need of care resulted in the transfer of own resources to other units and the consequent hiring of professionals to meet the demand for these services due to the damming of postponed elective surgeries. This knowledge will allow us to propose strategies in decision making in this scenario, considering the new waves that may arise from this disease. This research aims to investigate the challenges that surgical health services have faced in the face of the COVID-19 pandemic in order to preserve safe and effective multidisciplinary healthcare. Infection with SARS-CoV-2, the etiological agent that causes the disease COVID-19, affects an exponentially growing number of individuals daily.,4The COVID-19 pandemic has impacted all health sectors, with the need to issue some recommendations and guidelines for surgical practice and patient management during this new phase. WHO released the guideline for triage of surgical patients, prioritizing emergency surgeries and postponing elective procedures until the pandemic stabilizes. As a resStudies show that the volume of surgical emergencies has dropped dramatically. However, in response to the pandemic, several hospitals around the world needed to prepare to meet a high demand from COVID-19 patients, many of whom required specialized care in ICUs. The most widespread recommendation by scholars was that surgical departments prepare for changes in the acute surgical needs of the population they assist, which could allow for a better allocation of limited resources.,11 GivenThe innovative character of this research is supported by the fact that the proposed theme has gained international repercussion. Therefore, considering the relevance of the explained content, presenting the knowledge that was produced in those times is important for surgical teams to have this knowledge to understand and transform their care and management practice in the current pandemic context. Thus, this study aimed to present the knowledge produced about the challenges of health services for maintenance of surgical care practices in times of the COVID-19 pandemic.This is an integrative literature review, characterized as a research method that makes it possible to gather, analyze and synthesize available research on certain topics in a systematic way. To prepare this integrative review, the following steps were followed: 1) theme identification and research guiding question construction; 2) problem and study objective identification; 3) literature search; 4) data collection; 5) critical analysis of results; and 6) presentation of synthesis. The topiColeciona SUS, BIGG, and BINACIS. For the databases accessed from the VHL, the Brazilian Health Science Descriptors (DeCS) were adopted, which were crossed as follows: “Centros Cirúrgicos” AND “Infecções por Coronavírus”. For other consultations, controlled descriptors from the Medical Subject Headings (MeSH) of U.S. National Library of Medicine and the following crosses were performed: “Surgicenters” AND “Coronavirus Infections”. In order to identify only articles that presented both terms in the same study, it was necessary to use the crossing between the descriptors with the Boolean operator “AND”.The data collection stage was carried out from consultations in the PubMed portal, the regional portal of the Virtual Health Library (VHL), in the academic search engine Science Direct, in the Cochrane database and in the Scientific Electronic Library Online (SciELO). The databases accessed from VHL were BDENF, LILACS, MEDLINE, IBECS, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior). Articles that were repeated in the databases were excluded. The bibliographic search stage took place between February and April 2021 and the databases were accessed through a computer from a university linked to the world wide web, which were exhausted in a single day with recording of the search page. Study search and selection was paired.Scientific articles published and available electronically in full and that answered the guiding question of this research were included. The access to studies that were not available in full in the databases took place from the Coordination for the Improvement of Higher Education Personnel platform  were excluded because they were duplicate manuscripts, were not articles or did not respond to the guiding question of this review. A total of 87 (21.48%) articles related to the subject were exhaustively analyzed; of these, 27 (6.66%) answered the guiding question. The identification, screening and inclusion processes are outlined in Flowchart 1.A validated data collection form was used to collect data from each article in the final sample and this instrument allowed the acquisition of information about article identification, type of publication, methodological characteristics of the study and level of evidence. The sameIn It can be noted that most of the selected studies come from databases accessed through the VHL , mainly MEDLINE . Most were published in 2020  and the others were published in 2021 . The journals that published the most on the researched topic and that answered the study question were those in the medical field . The studies are available in English, Spanish or Portuguese, most of them in English . As for the level of evidence of the selected articles, it was observed that 12 (44.44%) studies bring evidence of level 6, that is, derived from descriptive or qualitative studies. Below, All selected articles brought at least one piece of information that was categorized as one of the challenges for health services that provide surgical care, regardless of whether it is public or private, to the detriment of the COVID-19 pandemic. The most cited challenges were management of the high demand of patients in need of perioperative care (11.1%), accumulation of elective surgeries postponed due to the COVID-19 pandemic (22.2%), transfer of resources from surgical centers to other units (25.9%) and hiring of professionals to meet the demands of these health services that provide surgical care (18.5%). Follow-up and controlling the clinical conditions of patients who had their surgeries postponed was also an important challenge emphasized (14.8%).As a result of the pandemic caused by the new SARS-CoV-2, health services that provide surgical care needed to reorganize their care practices. This required technical, scientific and management skills and knowledge on the part of those who run hospital and/or outpatient surgical units. A study pointed It is known that surgical consultations are unpredictable, therefore, identifying patients’ problems and solving them immediately will not always be possible, and, in these cases, there is a special interdependence between the client and the surgical team. Due to this fact, patients often end up traveling between many health services to have their complaint resolved as quickly as possible. Thus, ifMore than ever before, this new era requires healthcare and management professionals to become increasingly skilled in their decision-making to ensure the safety of clients who seek help and professionals who risk their health to stay working. CertainlThe current working conditions of health professionals, especially nurses, in many countries around the world, are marked by overload of activities, low remuneration and insufficient availability of personal protective equipment. These faIt is important to emphasize that, since graduation, there has always been a discussion about the number of insufficient professionals in health services to provide safe and resolute care. With the pandemic, it could be inferred that a worsening of this framework of insufficient professionals is primarily responsible for culminating in work overload for those who remain working, given the high demand of patients for urgent care.The difficulty faced by health units to manage the high demand of patients who require urgent perioperative care was one of the challenges highlighted, and this required important resignifications in this sector, even if temporary. Scholars,33,35 reOne of the greatest concerns of managers of these health services was regarding the control and availability of beds for intensive care for victims of COVID-19. This ledIn the waves of contagion of the disease, elective surgeries had to be postponed. As a result, the number of elective surgeries generated an increasing volume of backlogs. Managing this accumulation and the impacts of this waiting on the lives of patients worried health services.,36,37,44Due to the cases of patients who presented a bad evolution of their clinical condition because their surgeries were postponed, the need to follow up and control the clinical conditions of all patients who had their surgeries postponed because they were classified as elective.,39,44,45The researchers revealedDeciding to resume elective surgical activities in the pandemic scenario, especially amidst the waves of contagion, requires constant observation about the readjustment of institutional routine surgical practices. This is necessary in order to ensure the safety of assisted patients and healthcare professionals. This challenge requires an important dedication from all those involved in the assistance and from those who are in charge of developing protocols and guidelines for institutional care. GuidanceThe maintenance of patients’ autonomy in the context of healthcare in these times of pandemic was widely discussed, including that of women in choosing their type of childbirth. ThereforAnother important challenge to be discussed is mental health and overcoming the shaken emotional aspects of patients and professionals who make up the surgical team.,34 ThoseSurgical patients are not exempt from being mentally affected, especially in the era of fake news, a challenging period for health professionals to be able to demystify the waves of false information that spread about the COVID-19 disease.,34 UnconIn professional practice, patients are commonly seen emotionally hesitant, insecure and fluctuating about their thoughts and attitudes as a result of their surgical condition. In addition to these factors that affect the mental health of these patients, it is important to point out that professionals from the surgical team and their residents should pay attention to this situation of overlapping risk factors for mental illness. This is important so that these clients do not give up on their treatment and/or do not fail to adhere to the healthcare prescribed by the multidisciplinary team throughout or at some specific time during the perioperative period. Studies show that psychology residents have contributed significantly to this situation.Health residents’ professional performance in surgical units is essential for holistic healthcare and for controlling the demand of patients who need clinical-surgical care. However, the education and arrangement of these professionals in these times of pandemic was seriously compromised at the peak of the disease.,58 TheseIn this scenario, the presence of tutors responsible for these subjects is essential so that they can supervise the professional practice of these health residents with excellence. Surgical patients need quality care that prevents and minimizes the risks involved during surgery. Patients with COVID-19 or with COVID-19 sequels during infection or post-infection, with or without sequels, need multidisciplinary residents and qualified institutional staff.Finally, it should be noted that the impacts of this pandemic have not only affected the community and public health institutions, but also private outpatient services that offer elective procedures. The main challenges focused on overcoming the loss of revenue and personnel for some of these units, especially for public services. These heAlthough the present study consisted of a significant sample of articles, it was not possible to exhaust all existing databases, academic search engines, portals and libraries, nor to carry out more than one crossing of descriptors. Furthermore, during the course of the study, some issues related to the challenges of current care practices in the context of surgical service units were identified. These issues pointed out and discussed may be objects of further research, such as strategies that have been proposed and discussed by scholars to overcome these challenges listed.The main challenges that surgical services have faced or continue to face in this period of the COVID-19 pandemic are the transfer of resources from operating rooms to other units and the hiring of professionals to meet the demands of health services that provide surgical care. Finally, discussing and reflecting on the challenges that have affected and continue to affect outpatient and hospital health services is important. Such reflections encourage professionals, who work on the front line and in the management of these services, to know the motivations that led surgical health services to adopt radical changes in a timely manner to offer safe care to patients affected by COVID-19.The study started from the need to know the evident impacts of the COVID-19 pandemic on health sectors, especially in operating rooms. The results found and the discussions raised allow greater clarity about the challenges in surgical processes during the COVID-19 pandemic. In this regard, they can help health professionals, whether assistance or managers, in decision-making regarding the strategies that could and that can be traced in the face of the current scenario and the likely new waves of contagion of this disease.


Ou and colleagues (We read with great interest the article by lleagues  reportinlleagues  by consilleagues  and (iv)lleagues . Their rlleagues .From our own experience, we found the following points critical in applying ML models in outcome prediction.While the discriminatory ability of the AutoML approach is highest among the statistical approaches in the study presented, the authors did not assess the calibration of the various algorithms. Calibration gives an estimate of how well the observed outcomes and predictions agree and are crucial in the clinical decision-making –8, thus From a clinical perspective, recanalization and recurrences following endovascular therapy of intracranial aneurysms is not infrequently encountered. The authors indeed list the number of patients analyzed and the short-term follow-up as a study limitation. However, the short follow-up time limits its validity. Although it has been shown that coiled aneurysms that showed complete occlusion at 6 months remained stable in most cases, up to 6.5% of those aneurysm occluded completely at 6-month later showed a recanalization . To evalWe commend the authors on presenting an interesting and important application of a novel ML approach applicable for non-AI-experts that outperforms the commonly used statistical methods in predicting treatment outcome, as the latter is of utmost importance in any clinical practice evaluating its treatment outcomes.MH, MML, and LA designed and wrote the initial draft. All authors contributed to the study design and critically revised the commentary. All authors contributed to the article and approved the submitted version.Open access funding was provided by the University of Bern.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Introduction: Rare diseases (RDs) are a severe, chronic, degenerative and often life-threatening group of conditions affecting more than 30 million people in Europe. Their impact is often underreported and ranges from psychological and physical symptoms seriously compromising quality of life. There is then a need to consolidate knowledge on the economic, social, and quality of life impacts of rare diseases.Methods: This scoping review is the result of 9 qualitative interviews with experts and a literature search on Cost-of-Illness (COI) studies and quality of life (QoL) studies following the PRISMA methodology. Grey literature was also included to complement findings. Results. 63 COI studies were retrieved, covering 42 diseases and a vast majority of them using a prevalence-based approach (94%). All studies included medical costs, while 60% included non-medical costs, 68% productivity losses and 43% informal care costs. 56 studies on QoL were retrieved, mostly from Europe, with 30 different measurement tools. Grey literature included surveys from the pharmaceutical industry and patient organisations.Discussion: The majority of studies evaluating the impact of RDs on the individual and society use the COI approach, mostly from a societal perspective. Studies often vary in scope, making them difficult to consolidate or compare results. While medical costs and productivity losses are consistently included, QoL aspects are rarely considered in COI and are usually measured through generic tools.Conclusion: A comprehensive study on impact of rare disease across countries in Europe is lacking. Existing studies are heterogeneous in their scope and methodology and often lack a holistic picture of the impact of rare. Consensus on standards and methodology across countries and diseases is then needed. Studies that consider a holistic approach are often conducted by pharmaceutical companies and patient organisations exploring a specific disease area but are not necessarily visible in the literature and could benefit from the sharing of standards and best practices. Rare diseases are a group of an estimated 6,000 to 9,000 known severe, chronic, degenerative, and often life-threatening conditions defined as diseases affecting no more than 1 in 2,000 people in Europe . AlthougThe burden of disease is used to evaluate the impact of diseases and, depending on the researcher’s field, typically considers clinical, economic, and/or political indicators and is usually expressed in terms of the costs a disease and/or disability exert upon the individual, healthcare system or society. As defined by the World Health Organisation (WHO)  and the The goal of this paper is therefore to review how the burden of disease has been measured to date, including differences in methodologies used to do so, to identify current knowledge gaps, and to propose recommendations on how the impact of rare disease should be measured in future research to be better adapted to their nature. A scoping review of the peer reviewed, policy and grey literature was thus conducted and offers research and policy directions to capture the true impact of rare diseases, encompassing all costs and features impacting people living with a rare disease, healthcare systems and society. Despite the use of the word “burden” in the literature, the authors of this paper will use the term “impact” to refer to the burden of disease, as burden tends to be disliked and negatively perceived by the rare disease community.Rare diseases included in the scope of this paper were selected regardless of their severity or amount of data available on these diseases. Sources were excluded from the selection when a language other than English or French was used. The scope of the literature search was however not geographically limited and included sources published between 2000 and 2021. Authors selected studies and articles that focused on rare diseases and addressed the topic of the impact of rare diseases, including both COI studies on the basis of a previous review  and othevia Google’s search engine.As mentioned earlier, the impact of disease can be defined in different ways depending on the discipline and perspective it is studied from. For this reason, this scoping review was therefore based on a two-tied approach, which allowed for the inclusion of the different relevant perspectives: a qualitative phase and a literature search. Qualitative structured interviews were first conducted with experts in the field of rare diseases who are currently or have been conducting research on the impact of disease to guide the authors in 1. defining the appropriate scope and methods for conducting the scoping review, 2. refining their search and selection of appropriate keywords and 3. contributing to the identification and collection of relevant literature. Especially regarding intangible costs of rare diseases, these experts were consulted to identify the most common and appropriate measurement tools, which were later compared with findings in the literature. The literature search was conducted between April 2021 and October 2021. Peer-reviewed articles were identified and retrieved from Google Scholar and PubMed using keywords . Authors also included grey literature in the scope of this review. Grey literature was identified and retrieved thanks to the experts and network consulted during the qualitative phase of this review and One author (Julien Delaye) conducted the initial literature search by screening sources’ titles and, when titles were in line with the scope of this review, abstracts. A second author (Anna Kole) reviewed the selection of articles and studies, added further sources (both peer-reviewed and grey literature), commented on sources’ relevance until consensus was reached on the final selection for the production of the article. The third co-author  reviewed the article at a later stage and suggested amendments. Characteristics of the retrieved sources on peer-reviewed COI are geographic area, disease, prevalence or incidence-based estimation, perspective, and costs included as per García-Pérez et al. . CharactPeer-reviewed sources on the topic of COI were extracted from the scoping review conducted by García-Pérez et al. , comprisThe 65 studies see  includedThe 58 retrieved peer-reviewed articles  see Tab addressiThe literature reviewed in the scope of this paper shows that, when used to assess the impact of rare diseases, COI studies are generally based on a societal perspective, which health economists identify as the most complete approach . A minorOn the other hand, intangible costs are typically measured in loss of quality of life . Rare diAs Armeni et al.  state, CHand in hand and based on the findings of this scoping review, authors of this paper therefore conclude that a comprehensive study on impact of rare disease across countries in Europe is lacking and is needed to better plan and attract private and public investments in the research and development of rare disease therapies—for which there is a significant unmet need and a great potential for impact. They also state that existing studies are heterogeneous in their scope and methodology and often lack a holistic picture of the impact of rare disease, as they focus on the economic impact and ignore the social and psychological. A consensus on standards and methodology across countries and diseases will thus be helpful in better applying such an evidence base. Lastly, studies that do consider a holistic approach are often conducted by pharmaceutical companies and patient organisations exploring a specific disease area but not necessarily visible in the literature and could benefit from the sharing of standards and best practices to better achieve their impact assessments and apply them in each stage of the therapeutic life cycle.


The sudden outbreak of COVID-19 in early 2020 pushed the online health-care communities (OHCs) into the public eye in China. However, OHCs is an emerging service model, which still has many problems such as low patient trust and low patient utilization rate. Patients are the users and recipients of web-based medical services, as well as the core of medical services. Thus, based on cue utilization theory, this paper studies combination effect of influencing factors in patients’ purchase of web-based medical services through the qualitative comparative analysis method of fuzzy sets (fsQCA).This paper discards statistical methods based on variance theory-based relationships between explanatory and explained variables and uses a construct theory-based fuzzy set qualitative comparative analysis (fsQCA) approach to elucidate such complex relationships of patients' online purchasing behavior. We use a crawler to automatically download information from Haodf.com. This study crawled data in August 2020, involving 1210 physicians.Service price, reputation and service quality are the key factors for patients’ purchasing behavior. Physician’s online reputation, online medical service price, number of published articles, mutual-help group, and appointment registration affect patients' purchasing behavior by means of weighted variation. Only when a high scope of internal attribute-related cue elements and a low scope of external attribute-related cue elements are combined with each other in a specific form, patients will generate purchase behavior.This paper clarifies the complex causes that promote to patients' purchasing behavior of web-based medical services, enriches and develops the relevant theories in the field of consumer purchasing behavior and online health-care communities market research, and has implications for governments, platforms, physicians and patients in the event of web-based medical service purchases. During the new coronavirus epidemic, online health-care communities (OHCs) have been favored and chased by the capital market, and the demand for web-based medical services has seen a blowout-like growth, and with the support of a series of policies, the development of web-based medical services has accelerated. Number of online consultations on several OHCs showed a surge during the epidemic, with the period of Spring Festival 2020, the daily activity of independent APPs in the online consultation sector peaked at 6.712 million people, with a maximum increase of nearly 1.6 million people, or 31.28% [OHCs are becoming a valuable platform for patients to communicate and seek support , 3, and The influence of physicians’ reputation and word-of-mouth information is mainly considered when exploring patients’ decision to choose online medical services –7. From At present, the academia a lot of research on patients’ purchasing behavior of web-based medical services, but these studies mostly through regression method or experimental method to get results, the existing research is symmetric causal relationship among variables (the independent variable is the necessary and sufficient conditions of the dependent variable) and “net effect” . However, according to the theory of consumer behavior, there are many factors affecting consumer purchasing behavior. Patients’ purchasing behavior in OHCs belongs to consumer purchasing behavior, which is influenced by a series of complex factors such as low-scope cues and high-scope cues, namely combination effect. Based on the above information, this paper takes an aggregated and holistic perspective, and uses the qualitative comparative analysis (QCA) method founded by Larkin to investigate the drivers and antecedent constructs of patients' purchasing behavior , using pThe innovation of this paper lies in that it studies the combined effect of patients’ online purchasing behavior based on fsQCA, which expands and deepens the research methods and conclusions in the field of patients’ online purchasing behavior and OHCs. On this basis, this paper focuses on and contrasts and explains the role of these outcome constructs in patients' purchasing behavior, provides an in-depth analysis of the reasons that drive patients' decision to purchase online medical service behavior, and makes targeted recommendations to improve patients' willingness to purchase to help platforms and physicians for using more effective ways to increase sales. It helps medical administration to introduce relevant policies to give full play to the role of web-based medical services. Also, it proposes recommendations to help platforms and physicians, use more effective ways to increase sales, help medical administration to introduce relevant policies, give full play to the substitution and complementary role of online medical services to offline medical care, allocate medical resources rationally and improve the efficiency of consultation. The conclusions of the direct and indirect elemental configurations of medical services drawn in this paper are of great value to correctly guide patients to seek web-based medical treatment and to reasonably match the needs between physicians and patients in the short term.The complexity theory lays a theoretical foundation for exploring the sufficient and necessary conditions and the combined effects of influencing factors of patients’ purchasing behavior in OHCs. According to complexity theory, the relationship among variables in the real word is not necessarily linear or non-linear, and the same factors will have different influences in different situations. In the data analysis of multiple linear regression, although the data can support the positive influence of independent variable X on the result variable Y, there are also case of high X and low Y or low X and high Y in the samples, regression analysis cannot explain these reverse cases. Complexity theory and QCA method point out that the generation of the same result can be caused by multiple paths, that is to say, the combination of different variables can explain the same result variable, so as to help researchers explain these reverse cases. By explaining the complex relationship among variables, complexity theory provides a more powerful tool to explain the mechanism of patients’ purchasing behavior in the context of online medical treatment. Therefore, based on complex theory and with the help of fsQCA method, this paper explores the different paths of patients’ purchasing behavior in OHCs, so as to find out the sufficient and necessary conditions for its occurrence.Based on the complexity, this paper focuses on the factors that influence the occurrence of patients’ purchasing behavior from both high scope of internal cues and low scope of external cues. According to theory of consumer behavior, there are many factors affecting consumer purchasing behavior. Web-based medical advisory services have the trust property, it is difficult to judge before, during and after consumption. The technical quality of service between physicians and patients has serious information asymmetry. According to the signal theory, patients use cues from physicians’ homepage released to decide whether to buy their services .The attributes of product quality are divided into experience quality and search quality . ExperieA single product or service can have empirical quality attribute, search quality attribute and trust quality attribute at the same time, for example, the taste and texture of food products belong to empirical quality attribute, the production date belongs to search quality attribute, and whether it contains a series of additives such as coloring agents and preservatives belongs to trust quality attribute. The accuracy of information is a trust quality attribute, which is difficult to determine before and after the service, but some quality signals can be used to convey quality cues, such as the price of the service, the online reputation, the grade of the offline hospital where the physician works, and the physician's status .Health care is a high trust-demanding service and patients may face difficulties in not being able to determine the quality of the service and make choices about their available treatment options , 16. TruBased on the analysis of previous research , 21, 27,The research model of this study is shown in Fig. Qualitative comparative analysis (QCA) is an analysis method for small and medium sample case studies, which emerged in social science research in the 1980s and is mainly applied in sociology, politics and economics . The QCAIn the initial development of QCA method, the assignment of condition variable and result variable followed the most basic 1/0 division of Boolean algebra, namely QCA method based on clear set (csQCA). However, in the process of coding, some concepts often can neither be completely reduced to 1 nor completely reduced to 0, but are in an intermediate state. Based on this reality, the QCA method has evolved into a comparison method of fuzzy sets (fsQCA) , and intSome variables including longevity, appointment registration, welcome message, article and mutual-help group , 31. TheConsumers judge product quality through a series of cues. Due to the information asymmetry between providers and buyers of online medical consultation service , patientSince welcome message, service prices, articles and mutual-help groups are not service components of online consultation, and are subject to modification by physicians at any time. (1)Physicians will set up a welcome message on their personal pages. The welcome message will introduce the physician’s basic information, professional expertise, and express the hope that patients come to consult. Welcome message can make patients perceive physicians’ professional commitment  , so as tThese variables, which include status, reputation, longevity, appointment registration and service quality, are reliable, credible cues that are established over time, and they may influence external cues. (1)Physicians’ status affects patients’ purchasing behavior. Physicians providing online medical services have different ranks, such as chief physician or associate chief physician et al., and the differences in these ranks will result in different status of online physicians. (2)Reputation is the most important cue of product quality , 40, thuHigh scope of internal cues and the low scope of external cues in Fig. Thus, we hypothesize: When the high scope of intrinsic attributes and the low scope of extrinsic attributes appear simultaneously, the purchasing behavior will appear.There is a causal asymmetry in consumer purchasing behavior, i.e. for a case of purchasing behavior that has occurred, whether a single element plays a facilitating or inhibiting role in it does not depend on the main effect of the variable itself on the outcome, but it depends on its configuration with other variables . PatientEleven factors under the dimensions of content, design, security, and privacy of the web page  were studied for their impact on online sales volume , and merThus, we hypothesize: A single driver element in the set of cause conditions may influence on patient purchase behavior, depending on the way that element and other elements are conformed.There are several different constructs that can generate user purchase behavior, and the elements contained in each construct may be different.This study crawled data from haodf.com for analysis. Haodf.com is a typical online health consulting service platform in China that has a long history of development, mature operation, high user coverage and high physician activity . For theThis study crawled data in August 2020, involving 1210 physicians. After excluding records with missing values, there were 13,240 data from 1205 physicians in the end.In this study, observed variables were used to measure the perceived service quality of patients before the onset of purchase behavior, and the patient-perceived quality of health-care services included nine indicators such as physician’s status, reputation, longevity, appointment registration, service quality, welcome message, service price, articles, and mutual-help group. Table The correlation coefficients between the variables are given in Table Since this study uses qualitative comparative analysis of fuzzy sets, the first step requires initial assignment of variables with the assignment rules shown in Table After the variables in the model are assigned values, the data are imported into the QCA software and the fuzzy set module is used to perform operations on the 10,242 data. The software will first perform truth table construction, listing all possible combinations of constructs that may produce the purchase of health-care services, and automatically filter out the antecedent condition constructs that have some sufficiency for the purchase of health-care services based on the input consistency threshold and case frequency threshold (default criteria: consistency threshold of 80% and case frequency threshold of 1), and the filtered truth table is shown in Table The complex solutions derived from the preliminary analysis of this paper are shown in Table Afterwards, based on the theoretical hypotheses proposed by the researcher, the fuzzy set module continues with the simple and difficult counterfactual analyses, simplifying the complex configurations screened in the previous step to produce simplified and optimized solutions that form the outcome variables. In contrast to the optimized solution, the simplified solution is based on two classes of counterfactual analysis in which the antecedent conditions are more stable and are not affected by the researcher's setting of the antecedent conditions for the simple class of counterfactuals. Meanwhile, this study involves more variables, and considering the research rigor and analytical ease , the simThe data results are shown in Table In the latter four constructs of Table Observing Table Also, the low level of mutual-help group in construct 1 but high level in construct 6 suggests that mutual-help group can increase patient purchasing behavior, but it is also possible that low mutual-help group may promote purchasing behavior along with specific factors. While the articles in Table By analyzing the resultant constructs in Table Physicians with higher reputation, configurations 1 and 3, are the paths for that configuration. Physicians with higher reputation will have more online sales when they set up fewer patient groups or have high prices for their services, which corresponds to previous scholarly research. For online marketplaces, reputation is mainly achieved by evaluation feedback systems. Various types of user feedback systems, such as ratings, comments, likes, and gifts of flowers, reflect a feedback from patients about the quality of the service after using the health consultation service. The more satisfied patients are with the quality of the service, the more they tend to give positive feedback such as higher ratings, more positive comments, more likes and more floral gifts. It has been shown that sellers with a better reputation in the review feedback system have a higher price . The morPhysicians opened the online service for not a long time, Construct 2 is the path for this construct. Long time spent in online medical services together with more published articles constitute sufficient conditions for user purchase behavior. The coverage rate for construct 2 was 7.44% and the net coverage rate was 1.97%, indicating that although the number of cases for construct 2 was small, the intrinsic reasons for the formation of user purchase behavior differed significantly from the other constructs. Following the research in cue utilization theory, the number of years of online service is an important factor affecting service uncertainty , which iPhysicians provide appointment registration service, i.e., patients can make appointments online for physicians' offline "face-to-face" outpatient services, and configuration 4 is this configuration path. With the development of Internet medicine, more and more people are aware of this channel to see a physician, and the epidemic has made Internet medicine even hotter. As a new thing, whether online consultation is reliable and how good the physician is, these are also issues that the patients are more concerned about. Most quality physicians have a high volume of offline visits, and it is difficult to get an appointment with that physician at an offline brick-and-mortar hospital. So even if the price of a quality physician's service online is high, patients are willing to buy it because patients can quickly establish a connection with the physician and then reserve an offline visit with the physician online, which can save patients' waiting time in line. Therefore, the higher price of the service is based on the appointment registration.The types of physicians with higher service prices, configurations 5 and 6, are the paths for that configuration. For the online market, consumers were more concerned about the price of the service than whether the physician's personal homepage had a welcome message. This is consistent with previous research where price is considered to be the monetary consideration for obtaining the use value of a product, or an indication of product quality . The higIn summary, hypothesis 3 is supported by the fact that there are six constructs that increase patients' purchase of online medical services, with each purchase behavior path containing some of the same elemental constructs, with construct 3 and construct 4 belonging to the same behavior path and construct 5 and construct 6 belonging to the same path.This study strictly follows the steps in the QCA guidebook for arithmetic analysis, and at the same time, to ensure the stability of the research results, this paper conducts robustness tests in the following two aspects: (1) after moving the necessary conditions in the configurations out of the research model, the conditional configurations of the results remain basically unchanged; (2) after raising the consistency threshold to 0.85 for arithmetic, configuration 2 disappears and the remaining five configurations are the same as the original results. Therefore, the main conformational results obtained by fsQCA analysis in this paper are credibly robust.(1) Patient-perceivable high-scope service quality cues will combine with low-scope cues to form sufficient conditions for generating purchase behavior (H1). This suggests that different types of online service cues will generate different purchase behaviors, so in the actual online medical service management activities, it is not enough to unilaterally improve the internal cues of online medical service quality or to focus on external cues only; medical platforms should establish a system that meets the needs of different physicians' success according to their actual situation. For physicians, they should use the functions provided by websites so as to provide patients with more cues expressing their medical competence, i.e., online health-care providers need to examine this issue in an integrated manner by combining elements such as high-scope internal cues with low-scope external cues.(2) High-scope intrinsic cues and low-scope extrinsic cues influence patient purchase behavior online through a weighted approach (H2). Consumer purchasing behavior is a complex process and it is difficult to directly explain online patients’ purchasing behavior by a single element; the same level of physician or low scope cue-related factors may increase or decrease the occurrence of purchasing behavior under different cue conditions, depending on the way of conformation with other elements. Thus, studies of user purchase behavior need to examine constructs and such weighting elements in an integrated manner, and it is not meaningful to focus only on the extent to which individual elements explain the results.(3) Patients' purchasing behavior for online medical services is formed by six main constructs(H3): constructs 1 and 3, "physicians with a high reputation", which together with less mutual-help group or a high price of services constitute a sufficient condition for purchasing behavior. Construct 2 "physicians with a short time for online medical services", which together with the number of articles published online is a sufficient condition for purchasing behavior. Physicians who offer appointment registration and have a higher price for their services have better online sales, and construct 4 is this type of construct. Physicians with higher service prices and online service quality have higher online sales when they do not have a website welcome message. Construct 5 is a construct of this type. Construct 6 "higher service price", when the physician sets a higher service price, the online service quality and supporting services  must also be good to have higher online sales.This paper dissects the complex causes of patients' online purchasing behavior from a more systematic and comprehensive perspective, and uses fuzzy sets to qualitatively and comparatively analyze the complex dynamic processes of factors such as physician status, reputation, longevity, appointment registration, online service quality, welcome message, service price, articles, and mutual-help group on consumer purchasing behavior in the medical service domain. Based on real data from the Haodf.com, the fuzzy set module was used to identify six equivalent constructs that influence patients' purchasing behavior, and these constructs were generalized and explained. The specific findings are as follows.This paper enriches and deepens the existing theories and research methods in the field of patients’ purchasing online medical services in the following aspects:First, fsQCA method is widely used in the research of sociology, politics and economics. This paper applies it in the field of medical marketing to explore the effect of various cues on patients’ purchasing behavior in the context of OHCs by taking its advantages in studying asymmetric causality. This not only enriched the research methods in the field of marketing. Second, compared with the previous linear analysis of online medical service sales, this study highlights the effect of both high-scope and low-scope cues on purchase behavior, and summarizes the pathways to purchase behavior based on the interpretation of six types of constructs. This paper clarifies the complex causes of enhancing patients' online purchasing behavior, provides a new perspective for domestic online medical service research, and enriches and develops theoretical studies related to consumer purchasing behavior and the online health consultation market.Third, the net effect study in existing literature is not enough to fully reveal the role of each cue in patients’ purchasing behavior, and further study of its combined effect is needed to clarify its role in a more comprehensive and complete way. In order to achieve this goal, this paper adopts fsQCA method to study the combination effect of factors affecting patients’ purchasing behavior, and obtains six combinations of conditions that can affect patients’ purchasing behavior, which also proposes a new research perspective for researchers.In the process of medical activities, online health consultation platforms will strive to provide consumers with satisfactory services, but due to the special nature of medical services, the platforms cannot prosper without the contribution of physicians, especially high-quality physician resources . Since mFirst, both the administration and the online health consultation platform should note that the formation of online medical service purchasing behavior comes from the synergistic influence of the high scope and low scope cue elements of physicians. OHCs should not only continuously improve the ease of use, but also focus on whether the platform features can effectively deliver positive leads and adopt different incentive systems for physicians with different online service profiles. Moreover, in the operation process, high or low scope of individual elements may increase or decrease patients’ purchasing behavior, and the platform needs to pay special attention to the key elements and weighting elements that shape purchasing behavior and take different measures to target them according to the actual medical scenario of each case.Second, online physicians need to be fully aware that the way to increase sales of online medical services is to fully utilize the business functions offered by the online platform, as high sales are influenced by the synergy of high-scope and low-scope cues. This study is for physicians to reasonably distribute their limited energy and time in different online tools that can increase online sales. Physicians of the same rank, who are new to Internet health care and have not yet built up their own online reputation, should invest more energy and time in publishing articles that will allow patients to learn more about the physician's expertise and skill level, which in turn will increase sales. If the physician has developed a good online reputation, he or she can set a higher price for the service and can get good sales without using many other tools. If the physician's online reputation has not yet been developed, but high service prices and other high scope leads can work together to increase sales.Third, the level of physicians in the online health consulting market varies, and patients have to use high-scope and low-scope cues to eliminate information asymmetry so that they can restore their health. Patients should use the evaluation mechanism of the platform to find a physician with a good online reputation and who has opened an online reservation function for online consultation. Patients can first understand their condition and match the physician who matches their condition through the articles posted by the physician, then purchase the physician's online medical services, consult the relevant solutions and quickly establish a connection with the physician. When it is necessary to shift from online to offline consultation, offline consultation can be conducted through the appointment registration function, which can reduce the time spent in the offline queue for registration and effectively balance the allocation of medical resources in China.This paper has generated some advantageous results; however, there are still certain limitations that must be improved future studies. First, data were taken from one online health-care community, the haodf.com, which is the most acceptable web-based medical consultation platforms , 52; so Most of the population has basically been used to go directly to physical hospitals for consultation and medical treatment due to the influence of traditional thinking, and has not accepted the emerging Internet health care. However, with the outbreak of the new crown pneumonia epidemic in 2020, more and more people became aware of this channel of accessing medical care, and the epidemic made Internet health care even hotter. Many patients began to realize the role of Internet health care during the epidemic, but still held doubts about whether online visits were reliable and how good the physicians were, which were also of greater concern to patients. But after the patient has purchased online medical service experience, this worry will be eliminated, because the patient can contact the original physician who saw him in the offline hospital. The network platform built by Haodf.com allows the best physicians in the country to go out online and provide services to patients by the physicians themselves. The information asymmetry between physicians and patients can be alleviated by applying the theory of cue utilization. The cues to eliminate information asymmetry can be divided into high-scope internal cues and low-scope internal cues. The government, platforms, physicians and patients should note that the formation of online medical service purchasing behavior originates from the synergistic influence of low-scope and high-scope cue elements.


The inclusion of remote automatic systems that use continuous learning technology are of great interest in precision livestock cattle farming, since the average size of farms is increasing while time for individual observation is decreasing. Bovine respiratory disease is a main concern in both fattening and heifer rearing farms due to its impact on antibiotic use, loss of performance, mortality, and animal welfare. Much scientific literature has been published regarding technologies for continuous learning and monitoring of cattle’s behavior and accurate correlation with health status, including early detection of bovine respiratory disease. This review summarizes the up-to-date technologies for early diagnosis of bovine respiratory disease and discusses their advantages and disadvantages under practical conditions.Classically, the diagnosis of respiratory disease in cattle has been based on observation of clinical signs and the behavior of the animals, but this technique can be subjective, time-consuming and labor intensive. It also requires proper training of staff and lacks sensitivity (Se) and specificity (Sp). Furthermore, respiratory disease is diagnosed too late, when the animal already has severe lesions. A total of 104 papers were included in this review. The use of new advanced technologies that allow early diagnosis of diseases using real-time data analysis may be the future of cattle farms. These technologies allow continuous, remote, and objective assessment of animal behavior and diagnosis of bovine respiratory disease with improved Se and Sp. The most commonly used behavioral variables are eating behavior and physical activity. Diagnosis of bovine respiratory disease may experience a significant change with the help of big data combined with machine learning, and may even integrate metabolomics as disease markers. Advanced technologies should not be a substitute for practitioners, farmers or technicians, but could help achieve a much more accurate and earlier diagnosis of respiratory disease and, therefore, reduce the use of antibiotics, increase animal welfare and sustainability of livestock farms. This review aims to familiarize practitioners and farmers with the advantages and disadvantages of the advanced technological diagnostic tools for bovine respiratory disease and introduce recent clinical applications. The global demand and production of livestock products is increasing rapidly due to population growth, rising incomes and changes in lifestyles and diets . The gloMannheimia haemolytica, Pasteurella multocida, Histophilus somni and Mycoplasma bovis) [Bovine respiratory disease (BRD) is one of the most studied cattle diseases since the end of the 19th century  and its a bovis) ,7,13. Moa bovis) . VirusesSick animals suffer a significant decrease in meat quality, welfare, health, productive efficiency and an increase in production costs per produced animal ,15. BRD The setup of this list of “animals suspected to be sick” is possible due to the data received by the technological devices used on the animals when carrying out continuous monitoring of their behavior. Data are transmitted to software that stores and analyzes the information. When the system detects an alert , it provides the information to the farmers‘/practitioners’ device. The system is a dynamic and continuous learning process based on algorithms that are continuously updated by the contributions of the farmer/practitioner . The morThe early diagnosis of pathologies is one of the primary objectives in current livestock production , which cThe main aim of this work is to review new technological tools for early diagnosis of BRD for young stock rearing and cattle feedlots. To tackle the main objective, three specific sub-objectives have been developed: (1) To demonstrate the need for an early diagnosis method for BRD. For this, the disease and the main current diagnostic methods are described, indicating their shortcomings. (2) Review the existing technology for the early detection of BRD. (3) Describe the strengths, weaknesses, opportunities and threats of these technological tools.This study is a bibliographic review. Four main databases were used in the literature review: Google Scholar, PubMed, Scopus and Web of Science (accessed from November 2021 to July 2022), and a total of 24 keywords were used . To idenA total of 105 papers were included in this review, with 73 studies on beef cattle and 25 on dairy. In total, 13 papers were studies about activity behavior, 15 were about feeding behavior and 11 papers were about spatial behavior. The rest of the references included have been used to introduce key topics and discuss some of the relevant technological issues.Diagnostic methods for BRD that require sampling can be on in vivo or post mortem biological samples. In vivo biological samples are based on blood samples, nasal or nasopharyngeal swabs and bronchial and/or transtracheal lavage, using techniques such as PCR, ELISA and microbiological culture. Post mortem sampling is based on tissue samples subjected to laboratory techniques such as histopathology, microbiological culture and PCR . On the It is important to highlight that clinical diagnosis is currently the most widely used method to identify cattle sick with BRD. In addition to clinical signs, this diagnosis is also based on behavior changes. Behavioral changes and clinical signs in BRD-sick cattle include ocular and nasal discharge, cough, extended head, dry snout, floppy ears, poor coat, dull eyes, lethargy, social isolation, hypo-/anorexia, pyrexia, dehydration, tachypnea and dyspnea ,27. ClinThe evaluation of behavior by practitioners, technicians and farmers to diagnose cases of BRD under field conditions is a challenge because other bovine diseases or environmental conditions, such as metabolic acidosis, lameness or heat stress, can cause behavioral patterns similar to BRD . FurtherClinical scoring systems have been developed in recent years to improve early and accurate detection of calves affected by BRD. These mechanisms use a simple and objective clinical scoring system, standardizing the identification of sick calves and increasing the Se of clinical diagnosis without increasing costs ,38. ThesTo increase the Se and Sp in the diagnosis of BRD, visual evaluation can be combined with diagnostic imaging, which is a non-invasive method that allows the diagnosis of pneumonia in vivo. The main drawback of radiography is that it cannot be used in a farm, due to limitations in equipment, expense, anesthesia requirements and potential radiation exposure . HoweverAutomated registration systems monitor cattle continuously with no need for human presence. Therefore, this approach may increase the likelihood of identifying subtle changes in early or mild stages of the disease that could be masked by the calf or not detectable by visual assessment ,49. EarlBAS is based on individual identification of the animals. Thus, animal electronic identification (EID) has become essential in the development of PLF. This EID establishes a unique number, and the information is transferred from the transponder to the transceiver  using a radiofrequency identification system (RFID) ,53. The Most of the technological tools that are detailed in this review use this RFID system. An RFID system is mainly composed of three elements : an RFIDRFID can work with three different levels of radio frequency: low frequency LF, 125–134 kHz), high frequency  and ultra-high frequency  . If UHF 5–134 kHzRecognized behavioral patterns in animals at the onset of febrile infectious diseases are lethargy, depression, hypo- or anorexia and reduced water intake. These patterns are expected in sick animals compared to healthy ones ,27.Currently, there are three main technological options to assess the behavior of cattle for early BRD detection: (1) Monitoring of physical behavior using three-axis accelerometers. These quantify the number of steps animals walk, the time they are standing/lying down and the number of times they lie down ,27,55,56Continuous and non-invasive monitoring of cattle behavior using various technologies has the potential to be a powerful health management tool in fattening  and dairAccelerometers have been widely used in dairy production systems for estrus detection and locomotion problems; however, their use in beef cattle is less explored . These dAccelerometers continuously measure the gravitational force in multiple axes, and the values are processed to determine the activity and postural behaviors of the animals . AccelerY axis is perpendicular to the ground when the animal is lying down, while the X axis is perpendicular to the ground when the calf is standing [Most of the accelerometers that are currently used in livestock farms consist of detection on three axes. In addition, they have the ability to continuously record the data and summarize at intervals set by the user  and may have remote sensing capabilities using UHF radio waves that allow real-time analysis. All three axes are recorded simultaneously and, depending on the placement of device on the animal, the XYZ plane differs between the position of the upright calf and the position of the calf lying down, allowing both positions to be distinguished . The Y astanding .On-farm implementation of this system is simple. It requires an accelerometer containing both sensors that detect movement and the standing/lying down position, as well as a transponder, made up of a microchip that continuously collects data from the animal and an antenna that occasionally sends the information to the transceiver (reader). Information regarding physical behavior will arrive in the computer software along with the transponder number and the animal’s identification number .Mycoplasma bovis. These authors found that the number of steps was negatively associated with a clinical disease score and the size of lung consolidation, suggesting that step monitoring reliably detected disease and differentiated severity. The same results were observed after Mannheimia haemolytica inoculation—the number of steps decreased compared to the control group [The decrease in behavioral variables begins between four and six days before the clinical diagnosis of BRD, and is more accentuated the day before the clinical identification of the disease . Pillen ol group . On the ol group  evaluateol group ,71. In col group . In the ol group  observedMannheimia haemolytica increased resting time compared to the control group on the day the inoculation was performed. The same findings were observed in another study, where calves spent more time lying down after exposure to an experimental challenge [A decrease in activity due to BRD could be confused with lameness or locomotion problems , althoughallenge . In 2016hallenge  determinhallenge ,74.These findings suggest that other variables evaluated  may be more effective than the time spent standing and lying down to diagnose early BRD, since it follows an irregular pattern . It shouIn summary, it could be stated that all the variables of physical behavior monitored with accelerometers are significant and useful for an early BRD diagnosis, except for the number of times calves lie down. Activity provided by the accelerometers can be used as an objective method to help in the management and early identification of sick calves with BRD. If the cost–benefit and the sensors’ attachment to calves are improved, this technology could be effective and feasible for the early detection of BRD in calves.Several systems have been developed to detect BRD-sick animals by monitoring eating behavior and individual feed intake in group-housed cattle ,56. The Such systems require compartmentalization of the feeding area. At arrival to the facility, animals can be frightened and generally require time to habituate. This can be a problem mainly when new grazing calves arrive in the feedlot, during which time they have a high risk of BRD. If access to the feeder/drinker is not easy, this stress may exacerbate this risk, triggering BRD cases. In addition, system errors or confounders may occur until the calves become accustomed to it, since in the first days their consumption would decrease in a way uncorrelated with health status. To address this issue, other systems use antennas enabled above an open feed line, allowing the determination of the frequency and duration of eating. However, data on the average individual feed and water intake are not available .Monitoring eating behavior has been shown to be a promising tool for the detection of BRD and predicting morbidity and mortality in cattle ,22,57. AStudies quantifying changes in feeding behavior relative to the time of the visual detection of BRD are scarce but could provide enough information for the commercial development of automated disease detection systems. By monitoring feeding behavior with RFID, it is possible to diagnose BRD-sick calves 4.1 days earlier compared to conventional methods , with a Se of 90% and a positive predictive value (PPV) of 91% . Other sSeveral studies have been carried out using AMF behavior monitoring during the pre-weaning period to predict morbidity and mortality caused by BRD. All of these results were recently reviewed, and it was found that daily milk consumption, drinking speed, and rewarded and unrewarded visits may provide insight into early disease detection in pre-weaned dairy calves .On the other hand, the results regarding drinking behavior do not provide conclusive information, so this would not be a good variable for the early detection of BRD . In 1997Spatial behavior monitoring can provide additional information on the specific behaviors of cattle. This monitoring in the pen is carried out using RTLS or GPS . GPS canAlthough the RTLS system is similar to RFID feeding behavior systems, the RTLS has the advantage of being able to monitor an animal’s location anywhere within the pen, so it does not restrict assessment to only feeding and drinking behaviors . The RTLMannheimia haemolytica reduced grooming and social interactions for two days after inoculation, suggesting that these behavioral changes may be good indicators of early stages of respiratory disease [These systems have been shown to be an effective method for identifying BRD with higher Se and Sp compared to visual observations ,86,87. I disease . Interes disease .Remote early disease identification (REDI), as a specific system for early diagnosis of BRD , includeThe REDI systems not only maintained productive performance, but also increased performance in calves that were treated twice, since the ADG was better in the animals that were under therapeutic treatment and not submitted to ATB prophylaxis. It would be interesting to evaluate the real differences in a study in which neither of the two groups was preventively treated with an ATB . It is iOther technological tools based on physiology, especially body temperature, are under study, but they need further development and some of them fail to diagnose BRD at early stages ,92. AccoThe weaknesses, threats, strengths, and opportunities (SWOT) of the BAS technological tools for early diagnosis of BRD are detailed in Although the Se and Sp of all early diagnosis tools are not known, the REDI systems specifics for BRD do not differ much from those for thoracic ultrasound techniques  . HoweverThe main opportunity presented by the BAS technological tools for early diagnosis of BRD, which still need to be developed, is the combination with other conventional BRD diagnostic techniques. An example could be laboratory diagnosis. If the causal agents responsible for BRD clinical signs were periodically detected on a farm and integrated into the software, correlations of microorganisms and behavior patterns unnoticed by humans could be triggered by mathematical algorithms. In the case of bacteria, if antimicrobial susceptibility testing were performed by qualitative (Kirby–Bauer method) or quantitative methods ), it could guide the practitioner in each “suspected” case of the disease to use the ATB that have frequently been more sensitive to the specific pattern of disease. This could work if all the laboratory diagnostic results were linked to the software. Thus, the software could look for repeated patterns of BRD and ATB, which have been more sensitive to each pattern (in the case of bacteria) . This doThis system would require periodic analysis; therefore, the laboratory would be a key player. The practitioner veterinarian would also indicate to the program whether or not the treatment has been effective in each case, so that the system was constantly learning and improving. As a final result, it could improve the cure rate even further and decrease the AMR.Another promising combination would be the use of BAS with pathogens or biomarker detection. Metabolomics has been used as a DIVA approach to discriminate between BRD-infected and vaccinated animals , for claHowever, these technological tools also have their weaknesses. Perhaps the most important drawback to their implementation is the cost, as they require a significant investment, and the benefits must come in savings from ATB treatment costs, improved performance and reduced mortality rates . FurtherThe absence of pathognomonic behavior associated with BRD makes it difficult to assess both conventional and modern evaluation of cattle behavior, since the clinical signs of BRD can be confused with acidosis, dehydration or heat stress ,44. In aOther remarkable threats could be the replacement of staff by robots, although that is currently unthinkable since these technologies demand highly skilled labor for maintenance and repair. These systems may result in a technological dependency, which can lead to impacts related to a lack of supply of system components or a need for electricity or internet connection on the farm .Finally, we also sought to answer whether technological tools represent the future of BRD diagnosis for cattle farms. No conclusive information was found on this topic. Note that while these technologies can make an early diagnosis of BRD, the on-farm implementation of the systems needs to be improved and needs to be more accessible to farmers. In this sense, the setup of these technologies would be easier and more viable for big herds. In any case, it seems clear that the most promising aspect of this type of technology is the use of a single device capable of facilitating two main tasks: (1) monitoring different behavioral variables and integrating them into algorithms ,65 and  in diagnosis, and require time for training and labor.Livestock behavior is an important component in the early diagnosis of BRD, and new technological tools can greatly improve the work of farmers and practitioners.The most commonly used behavioral variables for early detection of BRD are feeding/drinking and activity (number of steps). Other interesting variables such as level of activity, rumination, the location within the pen and social patterns can also be integrated.Implementing BAS on farms must have a positive cost–benefit ratio, improve efficiency and health parameters of the herd, be reliable and be integrated into existing management practices. Different farm designs and sizes may limit the use of such systems.The use of single sensors capable of integrating BAS for multiple variables and on-site biological sampling and analysis for biomarkers and/or pathogens seems to be the most promising path for the future of these technologies.Further research is needed to adapt such systems to farms and to use them as a powerful tool for early detection of BRD.


Rising rates of suicide over the past two decades have increased the need for wide-ranging suicide prevention efforts. One approach is to target high-risk groups, which requires the identification of the characteristics of these population sub-groups. This suicidology study was conducted using large-scale, secondary data to answer the question: using the research on suicide, are there variables studied at the community level that are linked to suicide and are measurable using quantitative, demographic data that are already collected and updated? Data on deaths from suicide in U.S. counties for the years 2000, 2005, 2010 and 2015 were analyzed using multiple regression, longitudinal regression, and cluster analysis. Results indicated that the suicide rate in a county can be predicted by measuring the financial stability of the residents, the quality of mental health in the county, and the economic opportunity in the county. The results are further analyzed using two sociological theories, Social Strain Theory and the Theory of Anomie, and two psychological theories, the Shame Model and the Interpersonal Theory of Suicide. In the United States, the rate of death by suicide rose from 10.4 deaths per 100,000 people in 2000 to 14.21 deaths per 100,000 people in 2018, the most recent year for which accurate data are available. Nationwide, during these 18 years, there was a 35.6% increase in the rate of completed suicides. The rate of death by suicide in children and adolescents aged 5 to 24 increased by 45%. Among children and adolescents aged 10 to 24, suicides rose from being the third most common cause of death to the second most common cause of death [While mental health resources are crucial to preventing suicide in individuals, in many cases there is not enough time to connect someone to mental health resources. Research has found that the time between making a plan and completing suicide often lasts ten minutes or less . The timThe intent of this study is to develop a tool for predicting the risk of suicide using factors that contribute to suicidality. Counties serve as an agent of the state and unit of local government and provide vital services and resources to their citizens including schools, healthcare, infrastructure, parks, transportation, and public safety. Understanding the factors that play a role at the county level is valuable because it is the level of government that has the most direct impact on a citizen . The NatUnderstanding suicide risk at the community level can provide valuable knowledge to proactively address rising suicide rates and create a framework for how to allocate resources to where they are most needed. While mental health resources are sporadic and increased risk will not inherently lead to more prevention efforts, it is nevertheless worth studying suicide at the county level because patterns in suicide differ across population subcultures and these differences are underexplored in research ,14.Suicidology, the study of suicide, is embedded within the larger constructs of psychology, sociology, anthropology, and most recently biology. Presented below is a review of the research on these four constructs and the variables that previous research has linked to suicide. Emphasis is given to those variables which link to the present study.Psychology primarily focuses on suicidality in individuals, and factors that influence suicidality at the individual level. Psychological theories of suicide consider varying personal traits and emotions that contribute to suicide, but social isolation is a common thread between these theories. The vulnerability model states that there are certain psychological characteristics that may make an individual more vulnerable to suicide . While cThe Shame model, developed by Marvin Lansky, asserts that shame is the primary contributor to suicidality and describes shame as both the effect of failed social attachments and a hinderance to creating meaningful social bonds . AccordiThe Interpersonal Theory of Suicide, developed by Thomas Joiner, is one of the most widely studied and cited theories of suicide in the field of psychology. A meta-analysis published in 2019 identified 114 empirical studies including the theory, and Joiner’s book in which he outlines the theory boasts over five-thousand citations . This thWhile predicting such personal characteristics as social isolation or loneliness accurately at the county level is likely infeasible, it is possible to measure outside influences that, in combination with cultural values, are contributing factors to social isolation. In the United States and cultures with comparable values of self-reliance, financial instability is a source of shame among individuals, a result of the emphasis that America’s individualist culture places on achieving both financial stability and independence ,20.Numerous studies have supported the notion that suicide is associated with an individual’s financial status, but rather that association is positive or negative depends on both the population of interest and other factors at play ,22,23. TFinancial instability can contribute to an increase in suicide rates by increasing feelings of shame, humiliation, and inadequacy among people. Additionally, the self-reliant nature of American culture and the socially imposed goal of financial success can also increase feelings of shame and additional mental health problems among individuals who face financial dependence or instability . For thiWithin sociology, suicidology studies consider how the norms and values within a society influence the occurrence of suicide. Sociological theories explaining suicide include the Theory of Anomie and Social Strain Theory, both of which consider social isolation as a significant factor . Not onlSociological studies of suicide were made famous by Emile Durkheim’s Theory of Suicide, in which Durkheim defines the social and structural aspects of suicide . The TheSocial Strain Theory was developed by Robert K. Merton from Emile Durkheim’s Theory of Anomie. The argument of Social Strain Theory is that every society has a defined system of norms and values, which includes goals that people within that society should strive to reach. In addition, included within the system of norms and values are the socially acceptable ways of reaching those goals . Social Social isolation is the underlying common thread between sociological theories of suicide, as it is in psychological theories of suicide ,39. In tOne study found lack of employment to be one of the primary sources of anomie among males in the United States and cited the association between one’s work and their contribution to society to be a possible explanation . A recenEconomic stability at the societal level has also been associated with suicide. Unemployment rates have been found to be positively correlated with suicide rates, while lack of health insurance, limited access to healthcare, high levels of social inequality, and inability to access education, housing, or other essential services have all been found to be risk factors for suicide in studies conducted in forty-four countries in total ,44,45,46Within anthropology, the study of suicide considers the cultural implications of suicide, including how suicide is defined within a culture and what members of that culture believe happens after suicide completion . BecauseShame, like economic conditions, is associated with social isolation. Some psychologists have concluded that social connections protect against feelings of shame while social isolation puts one at higher risk for feelings of shame . AnotherThe anthropological perspective of suicidality emphasizes the importance of considering and studying the beliefs about suicide that vary between cultures and subcultures. Characteristics of a culture impact suicide rates by determining what situations are likely to lead suicide, such as social isolation has been shown to do in the United States. The United States scores highest of all ranked countries on the Individualism Index, developed to measure the importance that a nation places on individualism compared to collectivism ,53. HighSuicide, while a study in Italy identified economic fluctuations as an important factor in 1881 [Psychologists, sociologists, and anthropologists began to identify some of the factors of suicide before the end of the 19th century. Durkheim proposed the importance of social integration within members of a society, and the detrimental effects of social isolation in his 1897 book  in 1881 ,36,56,57 in 1881 . However in 1881 . While tThis study seeks to determine the quantitative variables that can be used to predict suicide at the county level. The guiding research question is: using the research on suicide, are there variables studied at the community level that are linked to suicide and are measurable using quantitative, demographic data that are already collected and updated? This study is advantageous because it is one of the few to comprehensively predict suicide at the county level and it is efficient since the necessary data are already available.All variables included data at the county level. Analyzing suicide at the county level, rather than the state or national level, retains more of the variation in suicide rates, which can expose important trends in deaths from suicide. At the state level, the rate of suicide ranges from 5.1 to 27.2 deaths from suicide per 100,000 people. At the county level, however, the rates range from less than 4.7 deaths by suicide per 100,000 people to 49.1 deaths per 100,000 people [This study is unique in that it presents a comprehensive model for classifying counties based on suicide risk and incorporates a multi-disciplinary theoretical explanation for the variation in suicide risk between counties. To the best of the researchers’ knowledge, this study is the first to use cluster analysis as a tool for identifying high risk counties where suicide prevention efforts should be focused.The predictor variables were grouped into four categories. Financial variables were poverty, rate of home ownership, and median household income. Variables for inequality and resource accessibility were unemployment rate, income inequality (the difference between the first and third income quartiles), urbanicity (population density), and high school and college graduation rates. Variables measuring the risk for mental health problems were the rates of drug and alcohol related deaths, the prevalence of mental health practitioners in the county compared to the national average, the percent of the population that are veterans, the average daily amount of sunlight, net population change, and the prevalence of household internet connections. Data for the county population, the average daily amount of solar radiation (sunlight) received, number of deaths from suicide, and the prevalence of drug and alcohol related deaths (two separate variables) were collected by the CDC and provided by the CDC Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) . The couData on the percent of people living in poverty and the median household income at the county level were collected by the United States Census Bureau American Community Survey (ACS) and Decennial Census data archives for the years 2000, 2005, 2010, and 2015 ,61. DataUsing SAS 9.4, these datasets were merged to form one dataset with the following variables: number of deaths from suicide, year, population, sunlight, rate of household internet connections, unemployment, number of drug related deaths, number of alcohol related deaths, percent of people living in poverty, median household income, prevalence of mental health practitioners, number of veterans, population density, population change, the rate of home ownership, and income inequality. Each observation was a county in the United States, identified by the county’s Federal Information Processing Standard (FIPS) code. Each county had up to four observations, one for each time point of the study: 2000, 2005, 2010, 2015. Counties for which the number of suicide deaths was missing were removed from the dataset. 3252 observations remained in the final dataset. For observations that had a missing value for one of the variables, the missing value was replaced with the median value. The distribution of all variables except the rate of home ownership was skewed right, and so a log transformation was done on each skewed variable. The final step in the data management stage was to convert counts into rates so that differences in county population were accounted for when calculating the prevalence of a particular variable. The number of deaths from suicide, drug related deaths, and alcohol related deaths were each divided by the total county population for the respective year, and then the decimal value multiplied by 1000 to result in a number representing the number of deaths per 1000 county residents.Linear regression analysis using SAS was conducted first to check for multicollinearity and to identify significant predictor variables. Multiple linear regression, also using SAS, was then completed to model the importance of each contributing factor. Following multiple linear regression, SAS was used to create a longitudinal model to determine where changes in the predictor variables were significantly correlated with change in the rate of death by suicide.The final stage of analysis consisted of creating multiple clustering algorithms in order to classify counties by predicted suicide risk based on the independent variables considered. Four clustering methods were used to create models: multi-level perceptron classifier, K-means, K-medoid, and hierarchical clustering methods. The multi-level perceptron classifier is an artificial neural network method that uses an input layer, an output layer, and multiple hidden layers to learn and classify data that may be non-linear. The K-means and the K-medoids clustering methods are similar in that both minimize the distance between the points in a cluster, but in the K-means method the center of each cluster is a mean value, whereas in the K-medoids method the clusters are centered around an actual data point and not a mean . The metBuilding a model to predict suicide rates based on quantitative factors allows for a more proactive approach to suicide prevention by sooner identifying characteristics of communities that are at risk for increases in suicide. Suicide prevention initiatives can be aimed at the factors contributing to the increases in suicide rate in communities and can be tailored to individual communities. Classifying counties based on suicide risk can provide a framework to allocate resources to communities in need. A classification model can also allow similar counties to be investigated further to identify additional sociological or cultural factors contributing to or protecting against suicidality.It is necessary to emphasize here that the data evaluated were not nested. Aggregate information was provided for each of the 1000 counties. Information about individuals or neighborhoods within each county was not tested.2 value of 0.63. While population density, prevalence of drug related deaths, and veteran population had small parameter estimates in comparison to others predictor variables, partial F-tests indicated that the model was significantly compromised when these variables were removed from the model. Therefore, all ten significant variables were retained in the final model , economic prospect , and mental health quality  can be used to predict suicide risk in counties. The availability of data on these demographic variables makes the multiple regression model and the clustering algorithm for predicting suicide more powerful, since they can predict an estimate of suicide risk for counties where suicide data are unavailable.Addressing the problems of financial insecurity and poor economic conditions in a community is one important step toward lowering suicide risk. However, the importance of the variables measuring the quality of mental health in the models, including drug and alcohol related deaths, sunlight, and the veteran population, indicates that increasing economic prospect and financial independence alone would be neglecting a key aspect of suicide prevention. In addition, highlighted is the link between financial stability, social class, and mental health in the United States. American culture places high importance on achieving self-reliance and avoiding downward social mobility, which is supported by the interwoven relationships between financial and economic conditions, shame, and suicide behaviors. Efforts to improve mental health and prevent suicide in communities with limited economic growth and widespread poverty are critical in preventing suicide, but must also address ways to improve mental health among people experiencing these conditions.Eliminating poverty, unemployment, and periods of poor economic conditions has thus far been infeasible, and so focus must shift to treating the mental health problems that are exacerbated by these conditions, especially in the aftermath of the COVID-19 pandemic. This study provides a framework for identifying where research and resources should be focused in order to have the largest impact on the rate of death by suicide in communities across the United States, as well as a model for identifying where people are at the highest risk for suicide.


In cognitive behavioral treatment of anxiety disorders, registration of emotions and behavior is an important part of the intervention. Normally, paper and pencil is used but registrations on a mobile application such as MONARCA may be a useful alternative.This study investigates the usability of MONARCA during the first 18 months of commissioning in practice.To explore the usability, semi-structured interviews were conducted with seven patients and three therapists, combined with data from a survey questionnaire where 10 patients and 12 therapists rated the usability of the app on the System Usability Scale. Participants were recruited from an outpatient clinic for affective disorders in The Mental Health Services in the Region of Southern Denmark.Technical performance, time allocation, therapist effort, commitment, enthusiasm, and increased knowledge are imperative factors. Therapists and patients found that the benefits of registering emotions and behaviors on a mobile application were that it was easy for patients to remember to register daily, it was easy to gain an overview over symptom progress, and access to the registrations improved therapist’s ability to prepare sessions.Overall, the results from the interviews and survey indicated that both patients and therapists found MONARCA useful, but several improvement opportunities regarding application features and use in the treatment course were found.No significant relationships.