Variation In Decisions Research Articles

Good Interrater Reliability for Standardized MRI Assessment of Tendon Discontinuity and Tendon Retraction in Acute Proximal Full-Thickness Hamstring Tendon Injury

Background: Proximal full-thickness free hamstring tendon injury (ie, tendon avulsion or rupture) is a severe injury. Treatment decision making relies on clinical factors and magnetic resonance imaging (MRI) variables; it specifically relies on which tendons are injured as well as the extent of tendon retraction. According to a worldwide evaluation of current practice, discontinuity of both proximal tendons and retraction of >2 cm are used as surgical indications. However, both the diagnosis and the use of MRI variables in decision making may be fraught with uncertainty in clinical practice. A reliable standardized MRI assessment is required. Purpose: To propose an MRI assessment for acute proximal full-thickness free hamstring tendon injury and to evaluate its interater reliability. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: We included 40 MRI scans of patients with acute (≤4 weeks of injury) proximal full-thickness free hamstring tendon injury. Three musculoskeletal radiologists assessed proximal full-thickness free hamstring tendon discontinuity using the novel “dropped ice cream sign” and tendon retraction (in mm). Quantification of tendon retraction (in mm) was performed using 2 different methods: (1) a direct (ie, shortest distance between the center of the hamstring origin and the tendon stump) method and (2) a combined craniocaudal/mediolateral measurement method. Absolute and relative interrater reliability were calculated. Results: We found an almost perfect interrater agreement (kappa = 0.87) for assessment of full-thickness tendon discontinuity using the dropped ice cream sign. Interrater agreement for the direct and craniocaudal retraction measurements was good for both the conjoint (intraclass correlation coefficient [ICC], 0.88 and 0.83) and the semimembranosus tendons (ICC, 0.81 and 0.79). The mediolateral retraction measurement yielded only moderate to poor reliability for the conjoint (ICC, 0.53) and semimembranosus tendons (ICC, 0.41). Conclusion: The standardized MRI assessment to identify proximal hamstring tendon discontinuity and quantify tendon retraction is reliable. We recommend using the novel dropped ice cream sign and the direct retraction measurement in clinical practice and research.

Management aspects of blended learning implementation in an educational organization: the main problems and ways to solve them

This paper examines the management tasks that the administration of an educational organization has to solve when introducing blended learning technology. Particular attention is paid to the creation of material and technical conditions, taking into account the specifics of blended learning models implementation, the organizational and regulatory components of this process in conditions of a lack of financial resources (in particular, centralized access to the resources of the school media center). The approaches to content creation for information and educational environment are analyzed, taking into account their variability and educational organization capabilities, the analysis of management decisions is carried out. Particular attention is paid to the preparation of subjects of the educational process for the implementation of blended learning. Considering the issues of improving the qualifications of teaching staff, a comprehensive analysis of the problem and the associated need for a systematic approach to its solution are noted; variability of managerial decision making; advantages of in-house training and the creation of temporary creative teams are noted. The paper reveals the problems of preparing students for blended learning, gives recommendations for extracurricular activities organization aimed at students digital competence development in accordance with the requirements of the Federal State Educational Standard. In conclusion, it is noted that there is a need for a systematic and planned nature of measures to introduce blended learning and monitor the achievement of the set goals, which will require the development of a system of criteria and indicators of the attainability of the tasks.

Decision-Making in U.S. Foreign Policy Crises: Presidential Leadership and Outcomes

Scholars of foreign policy decision-making have argued that international interactions ultimately are grounded in people acting singly or in groups. Unfortunately, data limitations prevent many of these crucial foreign policy decision-making theories from being rigorously tested and systematically compared with theories from alternative perspectives. A promising approach to remedying this deficiency is the addition of decision-making variables to existing, large- N data sets. In this study, we coded a series of foreign policy decision-making variables for all U.S. cases in the International Crisis Behavior (ICB) data set, and examined how these decision-making variables compared with structural factors in shaping crisis outcomes. The results reveal that when controlling for structural factors such as conflict setting and power discrepancy, foreign policy decision-making variables related to leaders’ traits, advisory structure, and the political context shaped the severity and centrality of violence employed by the United States. We conclude that including decision-making variables alongside structural variables will enhance the quality of data analysis in the areas of conflict studies and foreign policy analysis.

Complex dynamical behavior and numerical simulation of a Cournot-Bertrand duopoly game with heterogeneous players

In this paper, we consider the Cournot-Bertrand duopoly mixed competition model, which is characterized by different decision-making variables and different objective functions of the two enterprises. This form of competition is more consistent with the complex actual economic market. The general stability conditions of the four equilibria are given and analyzed with eigenvalues and Jury criterion, so that enterprise decision makers could choose appropriate parameters to determine the development of the enterprise. Under the specific parameter conditions, the stability conditions are analyzed and demonstrated in detail by using two-dimensional bifurcation diagrams, stable region diagrams and bifurcation curves. Many fractal Arnold's tongues are found in two-dimensional bifurcation diagrams. These tongues are associated with the Neimark-Sacker bifurcation of the fixed point and are arranged in accordance with the organization law of the periodic tree of the Stern-Brocot tree, which is helpful for us to analyze the transitions of system between period and chaos. With the help of the basin of attraction, the coexistence of attractors is analyzed, on which the decision maker can choose the initial conditions that are beneficial to the development of the enterprise. We also analyze the topology structure of basin of attraction and the formation mechanism of holes in the basin of attraction by using the theory of critical curve and noninvertible map.

Consumer Behaviour Dimensions in Selection of Undergraduate Management Specialization Courses in Nepal

Tribhuvan University has designed their undergraduate BBA program by offering students the possibility to customize their educational program through the specialization in four different areas: banking & finance, industry and services management, micro enterprise management, and sales and marketing management. However, students have been specializing only in two courses namely: banking & finance, and sales and marketing. In this regard, the study aims at understanding the specialization choice of such students, as marketers need to be more aware of the underlying factors considered by students when choosing specialization and design the product offerings in this competitive market.
 The study has the objective of examining the effect of various decision-making variables on the specialization choice of undergraduate students from a consumer behavior perspective.

Variability in Management Practices and Surgical Decision Making in Spinal Tuberculosis: An Expert Survey-Based Study.

Study DesignElectronic survey–based study.PurposeThe aim of the study was to objectively review the variability in the prevailing treatment protocols and surgical decision making in the management of patients with spinal tuberculosis (TB) among spine surgeons with expertise in spinal TB across the country.Overview of LiteratureA lack of good-quality evidence, ambiguities in the national spinal TB guidelines, and the demand for early rehabilitation and a better quality of life in patients with spinal TB has led to the emergence of various gray zones in the management of spinal TB.MethodsSeventeen fellowship-trained spinal TB experts representing different geographical regions of India completed an online survey consisting of questions pertaining to the conservative management of spinal TB (antitubercular therapy) and 30 clinical case vignettes including a wide spectrum of presentations of spinal TB with no or minimal neurological deficit. The variability in the responses for questions and case wise variability with respect to surgical decision making was assessed using the index of qualitative variation (IQV). The average tendency to operate (TTO) was calculated for various groups of respondents.ResultsHigh variability was observed in all questions regarding conservative spinal TB management (IQV > 0.8). Among the 30 case vignettes, 14 were found to have high variability with respect to surgical decision making (IQV > 0.8). With respect to levels of fixation, all but two cases had poor or slight agreement. Younger age and practice in a government or tertiary care teaching hospital were factors associated with a higher TTO.ConclusionsSignificant variability was detected in treatment practices for the management of spinal TB among experts. Most of the case vignettes were found to have significant heterogeneity with respect to surgical decision making, which reflects a significant lack of consensus and lacunae in literature.

Methodology for the Selection of Trenchless Sewer Rehabilitation Technologies in Bogotá, Colombia

Context: Operational and/or structural failures in sewer networks lead network operators to carry out rehabilitation tasks to maintain water transport conditions, which is why it is necessary to decide on the type of intervention to be performed, that is, i) a traditional open-ditch procedure, or ii) the use of trenchless rehabilitation technologies. Objective: This article focuses on the methodology developed and implemented in the SELECTOR program, whose purpose is to provide public service companies responsible for sewer service, as well as related professionals, with a decision tool that answers, from a technical perspective, which of the analyzed trenchless rehabilitation technologies (pipe bursting, cured-in-place pipe, slip lining, and spiral wound) is the most suitable for the rehabilitation of sewer networks. Method: To this effect, it is necessary ​​to consider all the influence parameters at the time of sewer rehabilitation, define the application ranges of these trenchless technologies, extract the differential variables, use fuzzy logic verbalization, determine the priority and relationship between the variables using the data mining technique known as decision trees, and develop the SELECTOR program by means of the Visual Studio 2017® platform. Results: The differential variables for decisions regarding the application of trenchless rehabilitation technologies in underground sewerage infrastructure projects were identified. A graphic summary of the decision model was made using the verbalization diagrams and the SELECTOR program, which allows processing the information of the sewerage networks individually and for a whole sewer rehabilitation project, detailing the intervention collector to collector. Conclusions: There are eight differential variables when deciding on sewer rehabilitation. Verbalization diagrams allow to compress the decision model and facilitate its programming, and automated decision models increase effectiveness and transparency in construction processes.

Factors Affecting Investment Decision Among Indians

Sector-specific study of investment decision-making variables aids several stakeholders in comprehending investors' behavior. After considering important factors such primary safety, availability of funds, reliability of returns, flexibility of ownership, etc., investors are prepared to put their money to work. But, the tastes and actions of each investor will determine which of these elements they prioritize. This research contributes significantly to the functioning of investing behavior.

Theory-driven Determinants of School Students’ STEM Career Goals: A Preliminary Investigation

This study investigated Turkish school students’ attitudes towards STEM disciplines and careers and explored determinants of students’ STEM career goals. In total, 117 lower secondary school students (aged 11 to 14) completed the STEM Semantic Survey including an open-ended question about their career intention after high school and the reasons for their goals. Using the conceptualisation of the influences of behavioural, personal, and contextual variables in career choice decisions, the students’ descriptions of career goal reasons were presented to elaborate on the variables that influence their STEM career goals. Attitudes towards individual STEM disciplines were from moderate to high and towards STEM careers were high. The gender difference was negligible. One of the key determinants of students’ career intentions was interests, involving interest in a particular career (e.g., architect) and career-relevant activities (e.g., planning, drawing, and designing) or subjects (e.g., mathematics). Larger, societal influences (altruism and patriotism) were among the motives of students’ career goals. Implications for research, practice, and policy-making were presented.

Management and Complications in Nonoperative Fractures of the Tibial Spine: A Systematic Review.

Effective options exist for acute nonoperative management of anterior tibial spine fractures, yet there exists a paucity of literature describing long-term outcomes for these patients. This systematic review thus aims to consolidate management strategies and complications for patients with nonoperative anterior tibial spine fractures. In accordance with PRISMA guidelines, 5 databases (CINAHL, MEDLINE, EMBASE, Cochrane, and Pubmed) were searched and screened in duplicate. Quality assessment was performed using the Methodological Index for Non-Randomized Studies (MINORS) criteria. Of 485 studies identified in the initial search, a total of 18 studies involving 369 patients were eligible for this review. These were stratified into 173 type I, 124 type II, and 72 type III injuries as described by Meyers and McKeever. All patients were treated with knee immobilization in either full extension or slight flexion, with possible closed reduction and/or aspiration of hemarthrosis. Complications at final follow-up comprised 33.9% of patients with persistent stiffness, 19.4% persistent instability, 11.1% mechanical symptoms, 6.37 delayed anterior cruciate ligament reconstruction, 4.9% delayed operative intervention for other complications, and 1.9% extension impingement. Given the lack of comparative studies in this review, definitive conclusions for nonoperative management are difficult to establish on the basis of the current body of literature alone. A modestly higher rate of arthrofibrosis and persistent laxity are seen in higher-grade injuries, however, only a minority of studies stratified complications by Meyers and McKeever classification in this review. A better understanding of variables in treatment decision making require further prospective study focused on the collection of functional and patient-reported outcome measures, whereas also further delineating complications by injury severity.

Bayesian interval-based oncology dose-finding design with repeated quasi-continuous toxicity model

In oncology dose-finding clinical trials, the key to accurately estimating the maximum tolerated dose (MTD) is to use all data efficiently given small sample sizes. Currently, popular designs dichotomize adverse events of various types and grades that occur within the first treatment cycle into binary toxicity outcomes of dose-limiting toxicity (DLT) events. Such compression of toxicity data from multiple treatment cycles causes huge loss of information, often resulting in MTD estimation with large bias and variance. To improve this, a continuous endpoint (the total toxicity profile, TTP) was proposed to incorporate adverse event types and grades. The Bayesian Repeated Measures Design (RMD) was further developed by Yin et al. (2017) to account for the cumulative toxicity information from multiple treatment cycles. However, the existing RMD method selects the dose that minimizes the loss function based on point estimates, which may generate inconsistent results due to small sample sizes in phase I trials. To reduce the variability in dose escalation decision-making, we propose an improved repeated measures design with an interval-based decision rule that selects the dose with the highest posterior probability of falling in a pre-specified target toxicity interval. Through comprehensive simulations, we compared this proposed design with the existing RMD design, along with well-established DLT-based designs such as Continual Reassessment Method (CRM) and Bayesian Logistic Regression Model (BLRM). The results demonstrated that our proposed design outperforms all other designs in terms of accurately identifying the MTD and assigning fewer patients to sub-therapeutic or overly toxic doses.

Why we need to account for human behavior and decision-making to effectively model the non-linear dynamics of livestock disease

Animal disease costs the livestock industries billions of dollars annually. These costs can be reduced using effective biosecurity. However, costs of biosecurity are steep and benefits must be weighed against the uncertain infection risks. Much effort has gone into determining efficacy of different biosecurity tactics and strategies. Unfortunately, the variability in human behavior and decision-making when confronted with risk information has largely been overlooked. Here we show that use of the human behavioral component is necessary to understand the patterns of infection incidence in livestock industries. Using an agent-based model developed with a foundation of supply chain and industry structural data, we integrate human behavioral data generated using experimental games that parameterizes communication strategies, learning, psychological discounting and categorization of human behavior along a risk aversion spectrum. The influence of risk communication strategies on human behavior can be tested with experimental gaming simulations and their impact on the system can be projected using agent-based models, delivering feedback to increase disease resiliency of production systems.

PRIORITIZATION OF URBAN MOBILITY INFRASTRUCTURE PROJECTS BASED ON URBAN CONFIGURATION AND ON MULTIDIMENSIONAL SCALING

ABSTRACT Purpose: This article aims to propose an alternative methodology of analysis, assessment, and prioritization of urban mobility master projects capable of supporting investment decision-making, considering financial, economic, and space variables. Originality/value: There are no clear criteria on project proposal selection, what corroborates the critics about the selection process and prioritization of urban mobility projects in the Ministry of Cities. Intrinsically economic issues that are leveled in recent methodologies of investment and project analyses are variables considered hard to be converted into financial benefits to make up the financial evaluation. Design/methodology/approach: The methodology proposed will draw on the multidimensional scaling as a multivariate assessment tool in order to evaluate and prioritize the projects using their economic variables, the spatial variables of the urban planning, and the financial models of each project. The economic variables arise from the economic analysis available in the projects, as well as the projects’ financing models. The spatial variables acquired from the social logic of space theory or spatial syntax allow the assessment of cities’ integration capacity before project implementation and after their development, making it possible to identify improvements in urban mobility conditions. Findings: The use of multidimensional scaling by applying economic, financial, and spatial variables has proved to be effective in promoting decision-making, whether by indicating the best project or identifying how close and/or distant they are from the objectives of a given public policy.

Network Self-Exciting Point Processes To Measure Health Impacts of COVID-19

The assessment of the health impacts of the COVID-19 pandemic requires the consideration of mobility networks. To this aim, we propose to augment spatio-temporal point process models with mobility network covariates. We show how the resulting model can be employed to predict contagion patterns and to help important decisions such as the distribution of vaccines. The application of the proposed methodology to 27 European countries shows that human mobility, along with vaccine doses and government policies, are significant predictors of the number of new COVID-19 reported infections and are therefore key variables for decision making.

Adapting sweet cherry orchards to extreme weather events – Decision Analysis in support of farmers' investments in Central Chile

Available options for mitigating the impacts of extreme weather events on temperate fruit trees involve a number of risks and uncertainties, leaving growers hesitant about the benefits of implementing new technologies to protect their orchards. We used Decision Analysis approaches, which account for these risks and uncertainties, to assess investment decisions in sweet cherry production systems in central Chile. We evaluated the adoption of polyethylene covers for orchards in northern- and southern-central Chile. Gathering expert and key stakeholder knowledge, we identified relevant variables for the adoption decision and developed a causal impact pathway model. We parameterized this model by collecting estimates from experts in the form of probability distributions. We implemented the model as a Monte Carlo simulation and projected probability distributions for the Net Present Value and the annual cash flow. Results highlight that farmers in southern-central Chile could expect major benefits from covering their orchards, with a 90% confidence interval for the Net Present Value from −33,605 USD to 595,447 USD. In northern-central areas, implementing covers did not significantly improve the Net Present Value (90% confidence interval from −149,597 USD to 433,361 USD). Across zones, our model results were sensitive to market price, crop yield, and fruit quality problems (i.e. low firmness). Cover effectiveness against rain events was relevant only in the southern-central zone, whereas effectiveness against frost events was relevant in both sites. Expected Value of Perfect Information calculations revealed that additional information on yield and market price could substantially help to make a confident decision. Our simulations suggest that orchard protection in southern-central Chile may be necessary for secure and profitable cherry production in the future. In this case study, we demonstrated the applicability of Decision Analysis to support farmers in identifying appropriate and effective strategies in time to overcome future challenges resulting from climate change.

Research on water resources dispatch model based on improved genetic algorithm – water resources dispatch model

Abstract According to the research on reservoir water resources scheduling and distribution, the aim is to balance the water supply and demand in each period, and consider the total water supply and the annual external water withdrawal of the reservoir in each period as water rights. The decision-making variables are provided for the water supply of the reservoir in this paper, so that water demand of the water-receiving area can be better met to alleviate the water shortage at various stages and realize the effective use of water resources. Moreover, through the constraints of reservoir operation rules and other constraints, a mathematical model is established for optimal operation of water resources in the reservoir system. Meanwhile, optimized genetic algorithms are applied to solve the model according to the characteristics of the model. After simulation tests, compared with the traditional linear binary algorithm used in the reservoir, the improved genetic algorithm studied in the paper improves the accuracy of data calculation and data convergence, which proves that the research results of the paper provide theoretical and practical significance for improving the level of reservoir water resources management and solving the problem of optimal water resources scheduling.

True colors: Consumers’ packaging choices depend on the color of retail environment

Color is one of the most elementary techniques used in marketing and produces behavioral effects reflecting purchase attitudes. However, packaging color has seldom been investigated in-context. Additionally, color research mainly focuses on individual colors, instead of color combinations. Here, we aim to study the putative effect that dominant retail environment colors might produce on attractiveness and product purchase intention, when products use similar store colors, and when products use complementary colors to those of the store. Moreover, we investigate if these choices are product dependent (e.g., do food and non-food products evoke the same packaging color choices in a given retail color context). A total of 653 participants were recruited to participate in two experimental studies disseminated through online platforms. Study 1 showed an interaction between store and product color significantly affecting both product attractiveness and purchase intention. Importantly, we found that the product category might modulate the complementary color-effect, in terms of attractiveness and purchase intention. Study 2 revealed that product-type subtends sensorial experience or semantic derivation mechanisms for preferred color choices. Together these studies unveil a complex relation between product type, context and color that possibly subtend different cognitive decision-making mechanisms. As such, colors cannot be considered as standalone variables in consumer decision making strategies. Here, we shed light into color perception and product strategy, thus helping marketers, retailers and designers to communicate more efficiently and to define a successful brand strategy.

A game-theoretic approach for decision analysis in end-of-life vehicle reverse supply chain regarding government subsidy

The presence of end-of-life vehicles (ELV) in the cities creates irreparable damage in environmental and economic terms. Thus, governments have been searching for ways to collect ELVs. An effective way to address ELVs is subsidies' policy. In this study, a supply chain including an ELV take-back center, an inspection center, and a repair center are considered. The decision variables are the purchase price of the ELVs, the sale price of the repaired vehicle, and the level of vehicle repair. In this supply chain, the government pays a subsidy to take-back centers that deliver their used vehicles. A Stackelberg game structure is considered with the government as the leader, the inspection center as the primary follower, and the collection and repair centers as the second followers. Using the game theory approach, the effects of government subsidies on equilibrium values of the decision-making variables of the centers in the ELV supply chain have been investigated in three scenarios. The scenarios comprise profit sharing, revenue sharing, and a centralized (cooperative) scenario. The results indicate that the centralized scenario has the most significant advantage compared to the two contracts of profit sharing and cost sharing. For example, the repair level of the ELVs, the amount of repaired vehicles demand, consumer surplus, and the whole supply chain's profit are at their maximum. The most significant impact of subsidy payment is related to the take-back center's profit and the ELV supply. On the other hand, the subsidy does not affect the profit of the repair center.

How do parole board members in England and Wales construct decisions about whether to release perpetrators of intimate partner violence from prison?

Existing research explores Parole Board decision-making, but not specifically for perpetrators of intimate partner violence (IPV), a special case due to the gendered and secretive nature of IPV and the role of control in predicting reoffending. To identify associations between case variables in England and Wales Parole Board decisions regarding perpetrators of IPV and explore how these variables help construct the decision. Logistic regressions regarding decisions in a sample of all 137 male prisoners who had abused women and applied for release or progression to open conditions in England and Wales from April 2018 to September 2019, developed into latent class analyses. Thematic analyses of six interviews with Parole Board members about decision-making in IPV cases. Release decisions were strongly predicted by the recommendations of offender managers, offender supervisors and psychologists, mediated by the Parole Board's confidence in their ability. Decisions were also significantly associated with custodial behaviour and attendance on courses, mediated by the Board's confidence in the prisoner's insight and honesty. Thematic analysis was both consistent with these findings and provided a context in which the associations could be understood. The findings have implications for understanding the dynamics between professional decisions and the Parole Board's decision; for the importance of offender managers demonstrating their expertise and ability to manage risk; for Parole Board members' reflection and development; for academic research into IPV; and for those who have experienced IPV and are looking to understand parole decisions about their abuser.

Evaluation of Pattern Recognition Techniques in Response to Cardiac Resynchronization Therapy (CRT)

Cardiac resynchronization therapy (CRT) improves cardiac function in patients with heart failure (HF), and the result of this treatment is decrease in death rate and improving quality of life for patients. This research is aimed at predicting CRT response for the prognosis of patients with heart failure under CRT. According to international instructions, in the case of approval of QRS prolongation and decrease in ejection fraction (EF), the patient is recognized as a candidate of implanting recognition device. However, regarding many intervening and effective factors, decision making can be done based on more variables. Computer-based decision-making systems especially machine learning (ML) are considered as a promising method regarding their significant background in medical prediction. Collective intelligence approaches such as particles swarm optimization (PSO) algorithm are used for determining the priorities of medical decision-making variables. This investigation was done on 209 patients and the data was collected over 12 months. In HESHMAT CRT center, 17.7% of patients did not respond to treatment. Recognizing the dominant parameters through combining machine recognition and physician’s viewpoint, and introducing back-propagation of error neural network algorithm in order to decrease classification error are the most important achievements of this research. In this research, an analytical set of individual, clinical, and laboratory variables, echocardiography, and electrocardiography (ECG) are proposed with patients’ response to CRT. Prediction of the response after CRT becomes possible by the support of a set of tools, algorithms, and variables.