Variation In Decisions Research Articles

Assessment and potential levels of technosphere industrial safety

The article discusses approaches to assessing cause-effect relationships determining the causes of emergencies at the enterprise, including the identification of direct and indirect factors, the direction and intensity of emergencies at the enterprise using the methods (risk sessions) of hazard research. The article poses the classical problem of hazard identification based on methods (risk sessions) in a matrix format with subsequent decision-making based on identification results. The authors of the article provide justifications, conclusions and recommendations regarding the development and launch of measures to improve the efficiency and reliability of industrial safety systems at a hazardous production facility. The principal distinguishing feature of the research results are: the variability of the managerial decision on the corresponding challenge of the industrial safety system of a particular facility and the security of the region in which the subject operates; “Ideal” solution to the potential problem of loss of efficiency and reliability of industrial safety systems at a hazardous production facility.

Sport arbitration as an emergent process in a complex system: Decision-making variability is a marker of expertise in national-level football referees

This study examined the experiential knowledge of eight Australian national-level football referees (3.2 yrs mean national-level experience) about the notion of consistent decision-making during competitive matches. Using a grounded theory approach, the analysis revealed that participants view “consistency” as context-dependent, rather than a rigid process of uniformly responding to isolated foul-play transgressions with putatively correct responses. Our results present two key conceptual abstractions—”referential and game dependent” and “purpose and context”—as a framework for understanding referee decision-making consistency. Results evidence that in higher level referees, consistent decision-making performance is an emergent process defined by the decision-making actions of the referee, and exploitation of specifying contextual game factors. Our discussion outlines how this process can be understood as dynamical transactions within a complex system (i.e. competitive football game), in which varying decision-making responses to superficially similar incidents is a marker of expertise, rather than inconsistency. These findings draw attention to the limitations of isolated foul-play video assessment, suggesting that training orientated toward complete uniform agreement on game incidents may reduce attention (attunement) to key contextual information that is necessary to prospectively control player behaviors and thus, the emergent trajectory of each game. Instead, findings support more representative game opportunities for referees to practice making decisions with key contextual information sources present. Future research could consider the extent context and/or variability define performance at different levels of competition and across sports with distinct cultural structures.

Reducing variability of perceptual decision making with offline theta-burst TMS of dorsal medial frontal cortex

BackgroundRecent evidence suggests that the dorsal medial frontal cortex (dMFC) may make an important contribution to perceptual decision-making, and not only to motor control. Objective/hypothesisBy fitting psychometric functions to behavioural data after TMS we tested whether the dMFC is critical specifically for the precision and/or bias of perceptual judgements. Additionally we aimed to disentangle potential roles of the dMFC in dealing with perceptual versus response switching. MethodsA subjective visual vertical task (SVV) was used in which participants weight visual (and other, e.g., vestibular) information to establish whether a line is oriented vertically. To ensure a high perceptual demand (putatively necessary to demonstrate a dMFC involvement) SVV lines were presented inside pop-out targets within a visual search array. Distinct features of perceptual performance were analysed before as compared to following theta-burst TMS stimulation of the dMFC, a control site, or no stimulation, in three groups, each of 20 healthy participants. ResultsdMFC stimulation improved the precision of verticality judgments. Moreover, dMFC stimulation improved accuracy, selectively when response switches occurred with perceptual repeats. ConclusionThese findings point to a causal role of the dMFC in establishing the precision of perceptual decision making, demonstrably dissociable from an additional role in motor control in attentionally demanding contexts.

Systematic and random sources of variability in perceptual decision-making: Comment on Ratcliff, Voskuilen, and McKoon (2018).

A key assumption of models of human cognition is that there is variability in information processing. Evidence accumulation models (EAMs) commonly assume 2 broad variabilities in information processing: within-trial variability, which is thought to reflect moment-to-moment fluctuations in perceptual processes, and between-trial variability, which is thought to reflect variability in slower-changing processes like attention, or systematic variability between the stimuli on different trials. Recently, Ratcliff, Voskuilen, and McKoon (2018) claimed to "provide direct evidence that external noise is, in fact, required to explain the data from five simple two-choice decision tasks" (p. 33), suggesting that at least some portion of the between-trial variability in information processing is due to "noise." However, we argue that Ratcliff et al. (2018) failed to distinguish between 2 different potential sources of between-trial variability: random (i.e., "external noise") and systematic (e.g., item effects). Contrary to the claims of Ratcliff et al. (2018), we show that "external noise" is not required to explain their findings, as the same trends of data can be produced when only item effects are present. Furthermore, we contend that the concept of "noise" within cognitive models merely serves as a convenience parameter for sources of variability that we know exist but are unable to account for. Therefore, we question the usefulness of experiments aimed at testing the general existence of "random" variability and instead suggest that future research should attempt to replace the random variability terms within cognitive models with actual explanations of the process. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Clinical decision-making for shoulder surgery referral: An art or a science?

Decision-making in musculoskeletal health care is complex, with discrepancy among clinical providers and variation in the per cent of referrals for specialist care. To date, there is an increased focus on specialist referrals, risking overuse of expensive testing and contributing to unnecessary treatment. This report will considerer the difficulties of primary care musculoskeletal decision-making using shoulder injuries as an example, presenting a solution based on multi-criteria decision-making analysis with online software. The associated issues involved in clinical decision-making are complex. Contributing to the components of complexity are; the multifaceted aetiology of shoulders, the experience and knowledge of providers, and the burden of patient demands. Notwithstanding, funding considerations, resource allocation availability and other associated issues around clinical decision-making. Considering the many facets and complexities of clinical decision-making, this is an area where multi-criteria decision-making analysis (MCDM) may be appropriate. The MCDM analysis approach is increasingly being used in health care and can assist in the organizing and weighting of identified key clinical factors. MCDM could be applied to the challenges of musculoskeletal care with the potential to decrease decision-making variability. Furthermore, the significance of each key clinical factor that musculoskeletal decision-making is based on are to date unclear. Therefore, this preliminary report offers a start towards clarifying key factors and an approach for implementing improved shoulder clinical care decision-making which could then be adapted and applied to other body sites.

Suicide and “do not resuscitate”: An ethical dilemma

Advance directives allow people to accept or decline medical interventions and to appoint surrogate decision makers if they become incapacitated. Living wills are written in ambiguous terms and require interpretation by clinical providers. Living wills cannot cover all conceivable end-of-life decisions. There is too much variability in clinical decision making to make an all-encompassing living will possible. While there are many limitations of advance directives, this article reviews some of the most troublesome ethical dilemmas with regard to advance directives.

76. PICU FELLOW ENTRUSTMENT: HOW DO FACULTY MAKE SUPERVISION DECISIONS?

Introduction Academic faculty make supervision decisions which balance the goals of trainee competency with patient safety. Previous work shows significant variability and potential bias in these entrustment decisions. Given the high stakes, understanding how these decisions are made is vital. Qualitative studies established traits that influence entrustment decisions, but the relative contribution of each has not been described. We aim to characterize the influence of these traits on entrustment decisions for Pediatric Critical Care Medicine (PCCM) fellows. Methods We surveyed faculty who supervise PCCM trainees at three PCCM departments. Based on 8 vignettes, faculty chose the level of supervision for a fellow performing an endotracheal intubation- direct or indirect supervision with the attending, direct or indirect supervision of a fellow supervising a junior trainee, or unsupervised. Each vignette varied by 3 traits: 1) patient condition 2) trainee-supervisor relationship and 3) trainee experience. There was a 72% response rate (n=51/70). We created a logistic regression model using the 3 traits and faculty attributes (gender, primary unit, education role) as predictors of direct supervision. We also compared faculty attributes for those selecting direct supervision for e4 cases and Results The majority of vignettes (78%, 311/396) were rated direct supervision. Of vignettes with a 3rd year fellow, 59% (118/199) were rated direct supervision compared with 97% (193/197) for a 1st year. Trainee-supervisor relationship, patient status and primary unit were significant predictors of direct supervision in the regression model. Compared with cardiac ICU faculty, the odds ratio for pediatric ICU faculty to entrust fellows was 2.27 (95% CI 1.07-4.81) and 4.68 (95% CI 1.54-14.19) for mixed cardiac/pediatric ICU faculty. Odds ratios were 2.14 (95% CI 1.47-3.12) for 1 week on service with the fellow (ref: never worked together) and 0.09 (95% CI 0.04-0.17) for a rapidly deteriorating patient (ref: stable patient). Faculty selecting direct supervision for e or Conclusion PCCM entrustment decisions are influenced by the patient's condition, supervisor's relationship with the trainee and supervisor's primary unit.

The practice in applying and ways to improve criteria for establishing the degree of occupational disability in the territory of the Russian Federation

Aim. To assess the practice in applying Temporary criteria of determination of extent of loss of professional working capacity currently in force in various constituent entities of the Russian Federation and to substantiate the main directions for their improvement.
 Methods. The analysis of expert decisions to establish the degree of occupational disability, adopted in the period from 2015 to 2017, was carried out in 77 subjects of the Russian Federation for two nosological forms: (1) consequences of lower limb injuries (T93) and (2) bilateral sensorineural hearing loss (H83.3). A comparative analysis of expert decisions made using current and proposed by the authors criteria in 2 constituent entities of the Russian Federation in 2018 was carried out. For data analysis, we used descriptive statistics methods.
 Results. Taking into account a high variability in expert decisions making in the constituent entities of the Russian Federation for similar cases (coefficient of variation 21.6%), the authors conclude that it is necessary to change approaches to the methodology for assessing the type of professional activity (qualifications, quality and volume of work, ability to perform it). Using the authors propose criteria based on the concept of reasonable accommodation allowed us to significantly reduce the variability of the decisions made in the pilot regions, the coefficient of variation decreased from 21.25 to 7.43%.
 Conclusion. High variability of decisions made during the examination of the degree of occupational disability is associated with the imperfection of the methods and criteria for assessing the victim's professional activities; the use of the criteria proposed by the authors allows for a higher reproducibility of the results of the examinations.

Pengambilan Keputusan Strategis Pemasaran di Perguruan Tinggi dengan menggunakan Analytics Hierarchy Process (AHP)

In marketing strategies, it is very important to consider various variables in decision making. With intense competition in higher education, it is important to determine a more appropriate and effective marketing strategy to get prospective students. For this reason, it is necessary to investigate what factors influence prospective students in determining tertiary institutions. This study reveals that the most influencing factors for prospective students in determining academic institutions are the ease of getting a job after graduation, followed by some other supporting factors, such as: scholarships, campus reputation, spiritual activities, and campus lifestyle.

A note on decomposition of sources of variability in perceptual decision-making

Information processing underlying human perceptual decision-making is inherently noisy and identifying sources of this noise is important to understand processing. Ratcliff, Voskuilen, and McKoon (2018) examined results from five experiments using a double-pass procedure in which stimuli were repeated typically a hundred trials later. Greater than chance agreement between repeated tests provided evidence for trial-to-trial variability from external sources of noise. They applied the diffusion model to estimate the quality of evidence driving the decision process (drift rate) and the variability (standard deviation) in drift rate across trials. This variability can be decomposed into random (internal) and systematic (external) components by comparing the double-pass accuracy and agreement with the model predictions. In this note, we provide an additional analysis of the double-pass experiments using the linear ballistic accumulator (LBA) model. The LBA model does not have within-trial variability and thus it captures all variabilities in processing with its across-trial variability parameters. The LBA analysis of the double-pass data provides model-based evidence of external variability in a decision process, which is consistent with Ratcliff et al.’s result. This demonstrates that across-trial variability is required to model perceptual decision-making. The LBA model provides measures of systematic and random variability as the diffusion model did. But due to the lack of within-trial variability, the LBA model estimated the random component as a larger proportion of across-trial total variability than did the diffusion model.

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.

Analysis of the Relationship Between Psychological Well-Being and Decision Making in Adolescent Students

Adolescents are frequently faced with situations in which they have to make decisions by choosing from a range of possible alternatives. In such circumstances, individual, social, and environmental conditions have an impact on the choice of the final decision in light of the various options presented. The main objective of this study is to analyze the relationship between the psychological well-being of adolescent students and their decision-making style. The research method used corresponds to an ex post facto, quantitative, transversal, correlational, and descriptive design, with an initial sample of 1,262 students from the Autonomous Community of Madrid, Spain, aged 13–19. A subsequent resampling of 385 participants was extracted from the initial sample by proportional allocation to strata (according to the levels of the variables gender, academic year, and educational institution classification) to guarantee the representativeness of the population data. Data collection uses the first Spanish adaptation of Ryff's Psychological well-being Scale and the Flinders Adolescent Decision Making Questionnaire, adapted by Friedman and Mann. The data shows that greater use of adaptive decision-making strategies correlates significantly with greater psychological well-being. In contrast, the correlation is high and negative at the intersection of the maladaptive decision-making variables and psychological well-being.

Statistically enhanced model of oil sands operations: Well-to-wheel comparison of in situ oil sands pathways

Abstract Although the life cycle greenhouse gas (GHG) emissions associated with Canadian oil sands have been investigated in recent years, questions remain regarding the source and impact of variability in emissions in this industry over time. This study combines publicly-available data from the fifteen largest operating in situ extraction projects, i.e., cyclic steam stimulation (CSS) and steam assisted gravity drainage (SAGD) with a statistically-enhanced life cycle model to investigate variability in well-to-wheel (WTW) GHG emissions. We estimate that the WTW GHG emissions from CSS-derived gasoline range from 99 to 114 g CO2eq/MJ (80% confidence interval), 6–22% higher than the RFS2 baseline. The corresponding range for SAGD-derived gasoline is 98–133 g CO2eq/MJ, 5–42% higher than the RFS2 baseline. SAGD-derived gasoline has more variability as some operators “upgrade” their crudes, emitting GHGs, whereas no CSS operator employs upgrading. Without upgrading, the 90th percentile for SAGD emissions would be 114 g CO2eq/MJ. Upstream variability in GHG emissions drives the positively skewed WTW GHG distributions. This demonstrates the importance of understanding the nature and magnitude of variability and uncertainty in decision making.

Cell-to-cell ATP differences can modulate cellular decision-making

Cells generate phenotypic diversity both during development and in response to stressful and changing environments, aiding survival. Functionally vital cell fate decisions from a range of phenotypic choices are made by regulatory networks, the dynamics of which rely on gene expression and hence depend on the cellular energy budget (and particularly ATP levels). However, despite pronounced cell-to-cell ATP differences observed across biological systems, the influence of energy availability on regulatory network dynamics is often overlooked as a cellular decision-making modulator, limiting our knowledge of how energy budgets affect cell behaviour. Here, we consider a mathematical model of a highly generalisable, ATP-dependent, decision-making regulatory network, and show that cell-to-cell ATP variability changes the sets of decisions a cell can make. Our model shows that increasing intracellular energy levels can increase the number of supported stable phenotypes, corresponding to increased decision-making capacity. Model cells with sub-threshold intracellular energy are limited to a singular phenotype, forcing the adoption of a specific cell fate. We suggest that energetic differences between cells may be an important consideration to help explain observed variability in cellular decision-making across a broad range of biological systems, including bacteria and the blood stem cell system.

The limitations of artificial intelligence (legal problems)

The subject. Possible problems that may lead to further use of artificial intelligence, as well
 as ways to overcome them are studied.
 The purpose of the article is to identify the principles of the legal status of artificial intelligence.
 The methodology includes formal-logical method, systematic approach, formal-legal
 method, comparative method, analysis, synthesis.
 The main results of the research. The basic approaches to the definition of the concept of
 artificial intelligence are examined, specific examples are given, the problems that can
 cause the further use of artificial intelligence are analyzed. Artificial intelligence as a complex computing system is characterized by: variability in decision-making, a certain degree
 of autonomy when working, as well as the ability to take into account the experience gained
 from previously made decisions and use it to correct them. The challenges that are facing
 both the legislators and scientists are identified, such as: determining the status of artificial
 intelligence, responsibility for its actions and, accordingly, finding the most acceptable way
 to transform legislation governing the use of artificial intelligence.
 Conclusions. Artificial intelligence, due to both its novelty and certain functioning features,
 causes disagreement in the scientific community regarding the permissible limits of its application, its legal status, responsibility for the results of its activities, as well as on many
 other related issues. Today there is no unity of opinion even in relation to the definition of
 the term “artificial intelligence”, which is largely due to the previously mentioned features. Therefore, in a world of continuous scientific and technological progress, where artificial
 intelligence plays an increasing role, we should continue to study these technologies in order to: firstly, determine their role and place in the future of humanity; secondly, to define
 the permissible limits of the use of artificial intelligence in order not to harm individual people or groups of people; thirdly, based on an understanding of the nature and principles of
 artificial intelligence, transform legislation in such a way that it best meets the challenges,
 which legal scholars will have to face in the future.

Prone positioning in non-intubated patients with COVID-19: raising the bar

Prone positioning in non-intubated patients with COVID-19: raising the bar

Modeling operation problem of active distribution networks with retailers and microgrids: A multi-objective bi-level approach

Implementation of distributed energy resources (DERs) has led to a decrement in the cost of supplying demand in distribution networks. Integration of DERs in the forms of micro-grids (MGs) is a solution to enhance the operation of these resources in the low voltage networks. To meet the demand by MG operator, both technical and economic characteristics as well as the prices offered by retailers are considered to schedule DERs optimally. In these networks, the profit of retailers is maximized by power trading with MGs and optimally purchasing the energy from wholesale markets. Due to the existence of several retailers and MGs in active distribution networks (ADNs), hierarchical decision-making frameworks are needed to model their operation problem. For this purpose, a bi-level optimization technique is proposed in this paper to model the operation problem of retailers and MGs as decision-making variables in distribution networks in the upper and lower levels, respectively. To solve the proposed model, multi-objective particle swarm optimization (MOPSO) algorithm is used. The proposed model and its solution method are applied to a hypothetical distribution network with several retailers and MGs to validate the theories and discussions. Numerical results show that the maximum capacity of DG and the amount of demand have an important effect on this decision and the prices of purchased power from wholesale markets determine the amount of retailers’ offers to MGs.

A value creation perspective on international business in Latin America: directions for differentiation between emerging market multinationals

PurposeThis study aims to draw researchers’ attention to the need to differentiate within the emerging market multinational companies (EMNCs) category. This study focuses on international business in Latin America to argue that the region’s specific institutional characteristics have consequences for within-firm decision-making regarding internationalization strategies. Additionally, the study suggests that to develop a more specific understanding of international business in emerging markets, it is important to consider how decision-makers define value and how they can capture such value.Design/methodology/approachThe approach used in this study draws on the bathtub analogy used in micro-foundations research in international business. It proposes a multilevel analysis in which micro-level variation in within-firm decision-making is considered, while accounting for the conditioning effects of macro-level contextual factors.FindingsThe study identifies characteristics of the Latin American institutional context that are relevant to international business strategies and that potentially differ from other emerging market contexts. These include the pendular shifts to and from pro-market economic reform, fragmented government intervention in business, underdeveloped capital markets, low competition among firms and polarized labor markets. The study explains how these characteristics shape the definition of value and firm strategies to capture value in international markets, and provides examples from firms in different industries.Originality/valueThis study applies a value creation and capture perspective to international business in Latin America, allowing for the simultaneous consideration of macrolevel institutional characteristics and microlevel variation in decision-making regarding internationalization strategies. This perspective not only helps to distinguish Latin American EMNCs from companies from other emerging market contexts, but also explains the considerable variation in the internationalization strategies of firms within the region.

Clarifying managerial biases using a probabilistic framework

A unifying probabilistic framework is developed to analyze and compare the impact of the psychological biases of overconfidence and underconfidence on managerial perceptions about the expected value, overall risk, downside risk, value-at-risk and expected shortfall of decision-making economic variables. The results depict that overconfident managers overestimate their expected values and underestimate downside risk, VaR and ES of decision-making variables. Underconfident managers, on the other hand, underestimate their expected values and overestimate downside risk, value-at-risk, and expected shortfall.

The human dimension of water availability: Influence of management rules on water supply for irrigated agriculture and the environment

A global challenge for water resource management in rivers worldwide is ensuring water supply reliability satisfies consumptive and environmental demands. High variability in water supply, water policy and management decisions, and uncertainty about the effects of climate change compound this challenge. Understanding factors driving water allocations and consequences for water users and the environment is essential. Rainfall and streamflow traditionally drive allocations, yet the influence of water management decisions are often overlooked because they are complex, rarely codified and dependent on the regional context. We compared the relative influences of water management, climate and the river system characteristics including demand and water storage infrastructure on regulated and unregulated water allocations in two regulated rivers with large dams for water supply to towns, irrigated agriculture and wetlands of international significance (Gwydir and Macquarie Rivers of the Murray-Darling Basin, southeastern Australia), using hydrological simulation models and regression-based sensitivity analyses under an historical and drier climate. Water management decisions influenced regulated water allocations (explaining 23% to 52% of the variance) considerably more than unregulated water allocations (explaining 2%). For regulated water allocations, water management decisions and the river system were more important than a plausible change in climate, while for unregulated water allocations, the river system and climate change were dominant drivers. Changing management rules alone could vary long term water allocations by between −6% and +0.1% in the Gwydir River and between −4% and +22% in the Macquarie River. Management rules which allocated future inflows (i.e. credit model) were more likely to fail in a drying environment with projected reductions in runoff, compared to rules where only water in storage is allocated (i.e. debit model). Management rules differed despite both river systems being governed by a single management agency under the same legislative and policy framework. More systematic approaches to justify water management rules and greater transparency in their influence on water allocations are critical for maximizing the benefits to water users and river health, and for managing risks to water supply in a variable and changing climate.