A Comparison of Two Data Analysis Training Methods for Paraprofessionals in an Educational Setting

Analyzing and using student educational data to guide instructional programming is a critical staff skill to ensure quality programming based on applied behavior analysis. We compared two training methods to teach staff to use rules to analyze graphed educational data to enact program changes: didactic instruction and behavioral skills training using direct practice. Participants showed improvements in verbally identifying data patterns using simulated data; however, participants in the latter group were also effective using actual student data. The lack of correspondence between rule identification and rule following challenges the assumption that an individual’s ability to identify rules predicts actual performance.     

An Evaluation of Stimulus Preference Assessment Methodology in Organizational Behavior Management

The organizational behavior management literature has yielded few stimulus preference assessment methodologies for use with employees. The current investigation compared three preference assessments (ranking, survey, and multiple stimulus without replacement procedures) found in the organizational behavior management literature for their ability to predict reinforcers for direct care staff members’ behavior. In the first experiment all assessments were effective for predicting reinforcers, but the results were limited by a lack of control items in the assessment. In the second experiment the survey and ranking assessments both proved to be effective for identifying reinforcers and neutral or ineffective stimuli. Implications of these results and directions for future research are discussed.     

The Discussion of Behavioral Principles in JOBM

Abstract

We addressed the inclusion of behavioral analyses in the research and case study articles published in the Journal of Organizational Behavior Management (JOBM) over the past 5 years (1992–1997). The amount of behavior analysis included in JOBM articles appears to be greater than that found in JABA in the early 1980s. However, the presence of such analyses in JOBM can still be increased. Further, a significant number of articles do not mention how the particular intervention was chosen to address a specific organizational problem. This lack of a functional assessment makes it difficult for readers to decide if a proposed intervention is applicable to a situation with which they might be dealing. Additionally, we reviewed articles and examined the range of those behavioral principles discussed and found little diversity among the principles used. This paper serves to address some of the problems and ramifications associated with this separation and to offer suggestions as to how this situation could be improved.     

The Architecture of Chemical Alternatives Assessment

Chemical alternatives assessment is a method rapidly developing for use by businesses, governments, and nongovernment organizations seeking to substitute chemicals of concern in production processes and products. Chemical alternatives assessment is defined as a process for identifying, comparing, and selecting safer alternatives to chemicals of concern (including those in materials, processes, or technologies) on the basis of their hazards, performance, and economic viability. The process is intended to provide guidance for assuring that chemicals of concern are replaced with safer alternatives that are not likely to be later regretted. Conceptually, the assessment methods are developed from a set of three foundational pillars and five common principles. Based on a number of emerging alternatives assessment initiatives, in this commentary, we outline a chemical alternatives assessment blueprint structured around three broad steps: Scope, Assessment, and Selection and Implementation. Specific tasks and tools are identified for each of these three steps. While it is recognized that on‐going practice will further refine and develop the method and tools, it is important that the structure of the assessment process remain flexible, adaptive, and focused on the substitution of chemicals of concern with safer alternatives.     

Reducing Risk on Machinery: A Field Evaluation Pilot Study of Risk Assessment

A pilot evaluation of the ANSI B11-TR3 Machinery Risk Assessment/Risk Reduction (RA/RR) Guideline was conducted. The TR3 guideline was introduced into five companies on one machinery system in each company with a second machine system serving as a control. A pre-post investigation was performed with safety conditions measured pre and post in both treatment and control and with risk reduction score measured only in the treatment machine system. NIOSH provided a commercially available risk assessment software to facilitate the process. Evaluation measures included avoided injuries, reduced exposure to machinery hazards, pretest and posttest knowledge demonstration, assessment of group processes following training, correct implementation of the guidelines, and degree to which risk reduction recommendations were implemented. The qualitative results of this pilot effort appear to be the best indicators for the way ahead in industrial machine risk assessment. All companies indicated that they derived value in participating in this study and in conducting risk assessments. Quantitative study results suggest that: (1) as measured by the knowledge of the participants before and after the TR3 training, the guidelines can be effective at enhancing employee knowledge of safe machine operations and (2) although the injury reduction trends appear successful, the small sample size in the study size should be considered in interpreting these early results.     

An overview of the Salmonella enteritidis risk assessment for shell eggs and egg products.

This article summarizes a quantitative microbial risk assessment designed to characterize the public health impact of consumption of shell eggs and egg products contaminated with Salmonella Enteritidis (SE). This risk assessment's objectives were to: (1) establish the baseline risk of foodborne illness from SE, (2) identify and evaluate potential risk mitigation strategies, and (3) identify data gaps related to future research efforts. The risk assessment model has five modules. The Egg Production module estimates the number of eggs produced that are SE-contaminated. Shell Egg Processing, Egg Products Processing, and Preparation & Consumption modules estimate the increase or decrease in the numbers of SE organisms in eggs or egg products as they pass through storage, transportation, processing, and preparation. A Public Health Outcomes module then calculates the incidence of illnesses and four clinical outcomes, as well as the cases of reactive arthritis associated with SE infection following consumption. The baseline model estimates an average production of 2.3 million SE-contaminated shell eggs/year of the estimated 69 billion produced annually and predicts an average of 661,633, human illnesses per year from consumption of these eggs. The model estimates approximately 94% of these cases recover without medical care, 5% visit a physician, an additional 0.5% are hospitalized, and 0.05% result in death. The contribution of SE from commercially pasteurized egg products was estimated to be negligible. Five mitigation scenarios were selected for comparison of their individual and combined effects on the number of human illnesses. Results suggest that mitigation in only one segment of the farm-to-table continuum will be less effective than several applied in different segments. Key data gaps and areas for future research include the epidemiology of SE on farms, the bacteriology of SE in eggs, human behavior in food handling and preparation, and human responses to SE exposure.     

Historical Relationship Between Performance Assessment for Radioactive Waste Disposal and Other Types of Risk Assessment

This article describes the evolution of the process for assessing the hazards of a geologic disposal system for radioactive waste and, similarly, nuclear power reactors, and the relationship of this process with other assessments of risk, particularly assessments of hazards from manufactured carcinogenic chemicals during use and disposal. This perspective reviews the common history of scientific concepts for risk assessment developed until the 1950s. Computational tools and techniques developed in the late 1950s and early 1960s to analyze the reliability of nuclear weapon delivery systems were adopted in the early 1970s for probabilistic risk assessment of nuclear power reactors, a technology for which behavior was unknown. In turn, these analyses became an important foundation for performance assessment of nuclear waste disposal in the late 1970s. The evaluation of risk to human health and the environment from chemical hazards is built on methods for assessing the dose response of radionuclides in the 1950s. Despite a shared background, however, societal events, often in the form of legislation, have affected the development path for risk assessment for human health, producing dissimilarities between these risk assessments and those for nuclear facilities. An important difference is the regulator's interest in accounting for uncertainty.     

A Risk Assessment Framework for Assessing Metallic Nanomaterials of Environmental Concern: Aquatic Exposure and Behavior

Nanomaterials are finding application in many different environmentally relevant products and processes due to enhanced catalytic, antimicrobial, and oxidative properties of materials at this scale. As the market share of nano‐functionalized products increases, so too does the potential for environmental exposure and contamination. This study presents some exposure ranking methods that consider potential metallic nanomaterial surface water exposure and fate, due to nano‐functionalized products, through a number of exposure pathways. These methods take into account the limited and disparate data currently available for metallic nanomaterials and apply variability and uncertainty principles, together with qualitative risk assessment principles, to develop a scientific ranking. Three exposure scenarios with three different nanomaterials were considered to demonstrate these assessment methods: photo‐catalytic exterior paint (nano‐scale TiO₂), antimicrobial food packaging (nano‐scale Ag), and particulate‐reducing diesel fuel additives (nano‐scale CeO₂). Data and hypotheses from literature relating to metallic nanomaterial aquatic behavior (including the behavior of materials that may relate to nanomaterials in aquatic environments, e.g., metals, pesticides, surfactants) were used together with commercial nanomaterial characteristics and Irish natural aquatic environment characteristics to rank the potential concentrations, transport, and persistence behaviors within subjective categories. These methods, and the applied scenarios, reveal where data critical to estimating exposure and risk are lacking. As research into the behavior of metallic nanomaterials in different environments emerges, the influence of material and environmental characteristics on nanomaterial behavior within these exposure‐ and risk‐ranking methods may be redefined on a quantitative basis.     

企业社会业绩内部评价体系研究

在企业社会责任受到广泛关注的现在,企业社会业绩内部评价正越来越成为事关企业生存与发展的新课题.由此,构建了一个服务于企业生存与发展要求的企业社会业绩内部评价体系,该体系由理念层面评价(指企业关于社会责任的看法评价),行为层面评价(指企业社会责任管理及企业行为评价),结果层面评价(指企业对社会的影响评价),战略性评价(指从企业战略角度对企业社会业绩的总体评价)等4部分组成.     

Quantitative risk assessment of rabies being introduced into mainland France through worldwide noncommercial dog and cat movements

France has been rabies-free among nonflying mammals since 2001. Despite this status, the rabies virus has been introduced several times through noncommercial pet movements, posing a threat of infection by this 100%-lethal zoonosis among local animal and human populations. To quantify the risk of rabies being introduced through worldwide noncommercial dog and cat movements, we performed a quantitative risk assessment using stochastic scenario tree modeling. The mean annual probability of at least one rabies introduction incident was 0.35 (median: 0.24, 90% prediction interval (PI) [0.04; 0.98]) and the mean annual number of rabies-infected pets introduced through pet movements was 0.96 (median: 0.27, 90% PI [0.04; 3.88]). These results highlight a nonnegligible, even high risk due to the associated consequences of such events. In alternative scenario testing, preventive anti-rabies vaccination proved to be an effective measure since removing the vaccination requirement led to a > 15-fold increase in risk. The serological testing requirement had less of an effect (approximately two-fold increase when removed) and the posttest waiting period to ensure that antibodies were not linked to an infection had a negligible effect. Any change in pet owner compliance, especially regarding vaccination, could have a major impact on the risk. This study also shows that reinforced border control staff training could be more effective in reducing risk than more frequent checks. These results provide quantitative data for assessing the probability of the rabies virus entering France, and could help policymakers decrease this risk in rabies-free areas.     

Incorporation of Pharmacokinetics in Noncancer Risk Assessment: Example with Chloropentafluorobenzene

Noncancer risk assessment traditionally relies on applied dose measures, such as concentration in inhaled air or in drinking water, to characterize no-effect levels or low-effect levels in animal experiments. Safety factors are then incorporated to address the uncertainties associated with extrapolating across species, dose levels, and routes of exposure, as well as to account for the potential impact of variability of human response. A risk assessment for chloropentafluorobenzene (CPFB) was performed in which a physiologically based pharmacokinetic model was employed to calculate an internal measure of effective tissue dose appropriate to each toxic endpoint. The model accurately describes the kinetics of CPFB in both rodents and primates. The model calculations of internal dose at the no-effect and low-effect levels in animals were compared with those calculated for potential human exposure scenarios. These calculations were then used in place of default interspecies and route-to-route safety factors to determine safe human exposure conditions. Estimates of the impact of model parameter uncertainty, as estimated by a Monte Carlo technique, also were incorporated into the assessment. The approach used for CPFB is recommended as a general methodology for noncancer risk assessment whenever the necessary pharmacokinetic data can be obtained.     

Comparative Human Health Impact Assessment of Engineered Nanomaterials in the Framework of Life Cycle Assessment

For safe innovation, knowledge on potential human health impacts is essential. Ideally, these impacts are considered within a larger life‐cycle‐based context to support sustainable development of new applications and products. A methodological framework that accounts for human health impacts caused by inhalation of engineered nanomaterials (ENMs) in an indoor air environment has been previously developed. The objectives of this study are as follows: (i) evaluate the feasibility of applying the CF framework for NP exposure in the workplace based on currently available data; and (ii) supplement any resulting knowledge gaps with methods and data from the li fe c ycle a pproach and human r isk a ssessment (LICARA) project to develop a modified case‐specific version of the framework that will enable near‐term inclusion of NP human health impacts in life cycle assessment (LCA) using a case study involving nanoscale titanium dioxide (nanoTiO₂). The intent is to enhance typical LCA with elements of regulatory risk assessment, including its more detailed measure of uncertainty. The proof‐of‐principle demonstration of the framework highlighted the lack of available data for both the workplace emissions and human health effects of ENMs that is needed to calculate generalizable characterization factors using common human health impact assessment practices in LCA. The alternative approach of using intake fractions derived from workplace air concentration measurements and effect factors based on best‐available toxicity data supported the current case‐by‐case approach for assessing the human health life cycle impacts of ENMs. Ultimately, the proposed framework and calculations demonstrate the potential utility of integrating elements of risk assessment with LCA for ENMs once the data are available.     

A Fuzzy‐Based Risk Assessment Framework for Autonomous Underwater Vehicle Under‐Ice Missions

The use of autonomous underwater vehicles (AUVs) for various scientific, commercial, and military applications has become more common with maturing technology and improved accessibility. One relatively new development lies in the use of AUVs for under‐ice marine science research in the Antarctic. The extreme environment, ice cover, and inaccessibility as compared to open‐water missions can result in a higher risk of loss. Therefore, having an effective assessment of risks before undertaking any Antarctic under‐ice missions is crucial to ensure an AUV's survival. Existing risk assessment approaches predominantly focused on the use of historical fault log data of an AUV and elicitation of experts’ opinions for probabilistic quantification. However, an AUV program in its early phases lacks historical data and any assessment of risk may be vague and ambiguous. In this article, a fuzzy‐based risk assessment framework is proposed for quantifying the risk of AUV loss under ice. The framework uses the knowledge, prior experience of available subject matter experts, and the widely used semiquantitative risk assessment matrix, albeit in a new form. A well‐developed example based on an upcoming mission by an ISE‐explorer class AUV is presented to demonstrate the application and effectiveness of the proposed framework. The example demonstrates that the proposed fuzzy‐based risk assessment framework is pragmatically useful for future under‐ice AUV deployments. Sensitivity analysis demonstrates the validity of the proposed method.     

Risk Assessment and Alternatives Assessment: Comparing Two Methodologies

The selection and use of chemicals and materials with less hazardous profiles reflects a paradigm shift from reliance on risk minimization through exposure controls to hazard avoidance. This article introduces risk assessment and alternatives assessment frameworks in order to clarify a misconception that alternatives assessment is a less effective tool to guide decision making, discusses factors promoting the use of each framework, and also identifies how and when application of each framework is most effective. As part of an assessor's decision process to select one framework over the other, it is critical to recognize that each framework is intended to perform different functions. Although the two frameworks share a number of similarities (such as identifying hazards and assessing exposure), an alternatives assessment provides a more realistic framework with which to select environmentally preferable chemicals because of its primary reliance on assessing hazards and secondary reliance on exposure assessment. Relevant to other life cycle impacts, the hazard of a chemical is inherent, and although it may be possible to minimize exposure (and subsequently reduce risk), it is challenging to assess such exposures through a chemical's life cycle. Through increased use of alternatives assessments at the initial stage of material or product design, there will be less reliance on post facto risk‐based assessment techniques because the potential for harm is significantly reduced, if not avoided, negating the need for assessing risk in the first place.     

基于改进教学式方法的可解释信用风险评价模型构建

信用风险评价是金融机构风险防控的重要环节之一。近年来，基于机器学习的信用风险评价模型以其准确的预测效果受到越来越多的关注，但机器学习模型具有可解释性不强的弊端，导致投资者无法完全信任其预测结果。针对上述问题，本文提出了一种改进的教学式方法，利用机器学习模型指导生成一个兼顾准确性与可解释性的信用风险评价决策树模型，以辅助投资者决策。为提高决策树对机器学习模型中正确功能的学习能力，提出了基于Weight Synthetic Minority Over-sampling Technique（Weight-SMOTE）的伪数据集生成方法，以提高伪数据集中可信度高的功能所标记的伪样本比例；为实现所生成的决策树在准确性、可解释性以及其与机器学习模型一致性间的有效权衡，在决策树生成过程中提出了一种新的决策树剪枝方法；同时针对保真度评价指标的局限性，提出了真保真度评价指标，来有效的衡量决策树与机器学习模型正确功能的近似程度。最后使用3个真实信用风险评价数据集对改进的教学式方法进行验证，实验结果表明所提出方法能够生成准确且可解释的信用风险评价模型，以满足投资者的决策偏好与实际需求。     

Defining Susceptibility for Microbial Risk Assessment: Results of a Workshop

An interdisciplinary workshop was convened by the George Washington University in June 2001 to discuss how to incorporate new knowledge about susceptibility to microbial pathogens into risk assessment and management strategies. Experts from government, academic, and private sector organizations discussed definitions, methods, data needs, and issues related to susceptibility in microbial risk assessment. The participants agreed that modeling approaches need to account for the highly specific nature of host-pathogen relationships, and the wide variability of infectivity, immunity, disease transmission, and outcome rates within microbial species and strains. Concerns were raised about distinguishing between exposure and dose more clearly, interpreting experimental and outbreak data correctly, and using thresholds and possibly linearity at low doses. Recommendations were made to advance microbial risk assessment by defining specific terms and concepts more precisely, designing explicit conceptual frameworks to guide development of more complex models and data collection, addressing susceptibility in all steps of the model, measuring components of immunity to characterize susceptibility, reexamining underlying assumptions, applying default methods appropriately, obtaining more mechanistic data to improve default methods, and developing more biologically relevant and continuous risk estimators. The interrelated impacts of selecting specific subpopulations and health outcomes, and of increasing model complexity and data demands, were considered in the contexts of public policy goals and resources required. The participants stated that zero risk is unattainable, so targeted and effective risk reduction and communication strategies are essential not only to raise pubic awareness about water quality but also to protect the most susceptible members of the population.     

A Behavioral Analysis of Goal Setting

Goal setting is a promising strategy for improving performance in organizational settings. This paper reviews goal setting from a behavior analytic perspective, discussing the function of goals and a number of key variables related to goal setting: goal difficulty, feedback on goal attainment and participation in goal setting. The advantages of utilizing behavior analytic methodology, such as objective measurement, clear specification of independent variables, intensive experimental designs and a behavioral theoretical framework are presented, along with suggestions for future research in the area.     

Partitioning of Dietary Metal Intake—A Metal Dietary Exposure Screening Tool

Detection of heavy metals at trace or higher levels in foods and food ingredients is not unexpected given the widespread unavoidable presence of several metals in nature, coupled with advancement in analytical methods and lowering limits of detection. To assist risk managers with a rapid risk assessment when facing these situations, a metal dietary exposure screening tool (MDEST) was developed. The tool uses food intake rates based on the National Health and Nutrition Examination Survey 2005–2010 consumption data for the U.S. population two+ years and up and for infants age six months to <two years based on the Nestlé Feeding Infants and Toddlers Study, and existing exposure limits for several frequently detected metals (e.g., inorganic arsenic, cadmium, chromium, lead, and mercury). The tool has data entry fields for detected concentrations and includes algorithms that combine metal levels with consumption data to generate screening‐level exposure estimates, which it then compares to MDEST assigned default portions of the exposure limits in the risk characterization module. As a screening‐level tool, the risk assessment output is intentionally conservative, public health protective, and useful for a rapid assessment to set aside issues that are not of concern. Issues that cannot be readily resolved using this screening tool will need to be further evaluated with more refined input data that are tailored to the specific question or situation under consideration.     

Integrating Software into PRA: A Test-Based Approach

Probabilistic risk assessment (PRA) is a methodology to assess the probability of failure or success of a system's operation. PRA has been proved to be a systematic, logical, and comprehensive technique for risk assessment. Software plays an increasing role in modern safety critical systems. A significant number of failures can be attributed to software failures. Unfortunately, current probabilistic risk assessment concentrates on representing the behavior of hardware systems, humans, and their contributions (to a limited extent) to risk but neglects the contributions of software due to a lack of understanding of software failure phenomena. It is thus imperative to consider and model the impact of software to reflect the risk in current and future systems. The objective of our research is to develop a methodology to account for the impact of software on system failure that can be used in the classical PRA analysis process. A test-based approach for integrating software into PRA is discussed in this article. This approach includes identification of software functions to be modeled in the PRA, modeling of the software contributions in the ESD, and fault tree. The approach also introduces the concepts of input tree and output tree and proposes a quantification strategy that uses a software safety testing technique. The method is applied to an example system, PACS.     

An Initial Assessment of Effective Preference Assessment Intervals Among Employees

Previous research has shown that employee preferences for tangible items may change significantly from one month to the next. Although a 1-month interval may be too long to wait between preference assessment administrations, no guidelines exist with regard to how often to assess employee preference. This study examined changes in preference as measured by two different preference assessments across four different time intervals. We measured preference stability by assessing changes in designations of high- and low-preference items from one assessment to the next. Only the 1-week interval indicated no changes in item designation from high preference to low preference or low preference to high preference. These data suggest that if tangibles are used, preferences may need to be assessed over time.