Task difficulty rather than reward method modulates the reward boosts in visual working memory

Both monetary and notional rewards are important to motivate individuals to prioritize specific items in visual working memory (VWM). However, whether the reward method and task difficulty are the key factors that modulate the reward boosts in VWM is unclear. In this study, we designed two experiments to explore this question. Experiment 1 examined whether the reward method modulates reward boosts in VWM by manipulating the item type (high reward, low reward, equal reward) and reward method (monetary and notional). Experiment 2 examined whether task difficulty modulates reward boosts in VWM by manipulating the number of high-reward items (1, 2, 3), reward method, and item type. The results indicated reward boosts for high-reward items compared to low- and equal-reward items. Moreover, the VWM performance was higher in the monetary reward condition than in the notional reward condition; however, there was no interaction between the reward method and item type. Additionally, a significant interaction was found between the reward number and item type: Reward boosts on VWM performance occurred only when one or two higher reward items were present. In conclusion, reward boosts in VWM tasks are modulated by task difficulty but not the reward method.     

A triangulation approach to the identification of acute sector nurses' training needs for formal nurse practitioner status

The current confusion surrounding the definition and role function of the nurse practitioner (NP) has created a situation in which advanced clinical practice is delivered in a variety of ways and at many levels. Not surprisingly, this has led to difficulties in regulating educational provision for NPs. This study reports a survey of the perceptions of the role definitions and training needs of all nurses working at advanced clinical levels within an acute sector Trust. Although this concept is not a novel one in advanced nursing practice, the procedure adopted differed from previous studies in two fundamental ways: firstly, a unique training needs assessment instrument was used, which because of its validity and opacity, was capable of yielding a highly reliable data-base, comprising a prioritized profile of real training needs as opposed to the standard wish-list typically elicited. Secondly, it did not rely simply on the self-reported needs of the nurse sample, but also included the perceptions of the sample's immediate medical and managerial colleagues. In this way, a triangulation paradigm was adopted. The results indicated that overall, there was high agreement between the nurses and their managers, regarding both the definition of the NP role and the essential training requirements, with somewhat different opinions being offered by the medical staff. When the raw scores were standardized to correct for response bias, the data provided an operational definition of the role of the NP and a prioritized profile of training needs for nurses who wished to train to this level.     

Determining Criteria and Weights for Prioritizing Health Technologies Based on the Preferences of the General Population: A New Zealand Pilot Study

Objectives

The use of multicriteria decision analysis for health technology prioritization depends on decision-making criteria and weights according to their relative importance. We report on a methodology for determining criteria and weights that was developed and piloted in New Zealand and enables extensive participation by members of the general population.

Methods to place a value on additional evidence are illustrated using a case study of corticosteroids after traumatic brain injury

ObjectivesTo establish whether evidence about the effectiveness of a health care intervention is sufficient to justify the use of the intervention in practice and show how value of information (VOI) analysis can be used to place a value on the need for additional evidence and inform research prioritization decisions.Study Design and SettingMeta-analysis provides an estimate of the effect of an intervention with uncertainty. VOI analysis determines the adverse health consequences of not resolving this uncertainty. A case study examining the evidence before the high profile trial of Corticosteroid Randomisation After Significant Head injury (CRASH) shows the consequences on patient outcomes if this trial had not been successfully funded.ResultsThe consequences of uncertainty before CRASH were high at 40 deaths and 1,067 years of full health per annum. VOI analysis indicates that CRASH was worthwhile and the UK National Health Service would have had to spend an additional £205 million elsewhere to generate health benefits similar to CRASH.ConclusionsVOI analysis can be integrated with the results of meta-analysis to help inform whether a particular research proposal is potentially worthwhile and whether it should be prioritized over other research topics that could be commissioned with the same resources.     

A template of information needs for decision-making about delaying remediation on contaminated lands to protect human health

ABSTRACT

The contamination legacy of industrialization, militarization, and nuclear arms race poses current or future risks to populations and the environment. Responsible parties and regulators make decisions regarding which sites to clean up, how, how much, and when. This study aimed to provide an information needs template to evaluate and reduce risks to human health when considering whether to initiate or delay remediation. This investigation focused on four aspects of timing and prioritization: 1) management, planning and implementation, 2) source terms, pathways, and exposures, 3) risks and receptors, and 4) external drivers. Within each type, issues were identified and described. Management class included personnel, health and safety data, funding, equipment, and structural integrity. Source term included contaminant sources, pathways, initiating events, and barriers to exposure. Risk included types and exposures to workers and general public. External drivers included regulatory framework, stakeholders, Congressional mandates, and economic and social contexts. Risk may increase over time as contamination spreads, enters aquifers, and reaches receptors, and may decline as radionuclides decay, and plumes dissipate. The overall objective was to provide a template of information that is useful to managers and regulators, and might be used by the public to understand the risks and benefits of re-prioritization cleanup.     

Discovery of tryptamine derivatives from Bacillus sp. PKU-TA00001

Tryptamine-derived natural products have been discovered from different sources including animals, plants and bacteria,and they show various biological activities. However, they are not discovered widely compared with the large amounts of tryptaminederivatives generated by chemical synthesis. We here report the discovery of five tryptamine-derived natural products (1–5) and one known polyketide 6 from Bacillus sp. PKU-TA00001. Compounds 1 and 2are new compounds featuring methyl-hexanamide moieties, compound 4is first discovered as a natural product, and 3 and 4’s NMR data are first provided. All compounds showed MIC (minimum inhibitory concentration) values higher than 50 µM against several Gram-positive and negative strains, and showed no cytotoxicity at the concentration of 100 µM against the human cancer cell lines A549, HCT-8 and MCF-7. The discovery of 1–4expands the structural diversity of tryptamine-derived natural products, and sets the stage for revealing their biosynthetic mechanisms and biological activities in the future.     

Expensive Cancer Drugs: A Comparison between the United States and the United Kingdom

Context: This article compares the United Kingdom''s and the United States’ experiences with expensive cancer drugs to illustrate the challenges posed by new, extremely costly, medical technologies.Methods: This article describes British and American coverage, access, and cost-sharing policies with regard to expensive cancer drugs and then compares the costs of eleven such drugs to British patients, American Medicare beneficiaries, and American patients purchasing the drugs in the retail market. Three questions posed by these comparisons are then examined: First, which system is fairer? In which system are cancer patients better off? Assuming that no system can sustainably provide to everyone at least some expensive cancer drugs for some clinical indications, what challenges does each system face in making these difficult determinations?Findings: In both the British and American health care systems, not all patients who might benefit from or desire access to expensive cancer drugs have access to them. The popular characterization of the United States, where all cancer drugs are available for all to access as and when needed, and that of the British NHS, where top-down population rationing poses insurmountable obstacles to British patients’ access, are far from the reality in both countries.Conclusions: Key elements of the British system are fairer than the American system, and the British system is better structured to deal with difficult decisions about expensive end-of-life cancer drugs. Both systems face common ethical, financial, organizational, and priority-setting challenges in making these decisions.     

Minimizing Population Health Loss in Times of Scarce Surgical Capacity During the Coronavirus Disease 2019 Crisis and Beyond: A Modeling Study

ObjectivesCoronavirus disease 2019 has put unprecedented pressure on healthcare systems worldwide, leading to a reduction of the available healthcare capacity. Our objective was to develop a decision model to estimate the impact of postponing semielective surgical procedures on health, to support prioritization of care from a utilitarian perspective.MethodsA cohort state-transition model was developed and applied to 43 semielective nonpediatric surgical procedures commonly performed in academic hospitals. Scenarios of delaying surgery from 2 weeks were compared with delaying up to 1 year and no surgery at all. Model parameters were based on registries, scientific literature, and the World Health Organization Global Burden of Disease study. For each surgical procedure, the model estimated the average expected disability-adjusted life-years (DALYs) per month of delay.ResultsGiven the best available evidence, the 2 surgical procedures associated with most DALYs owing to delay were bypass surgery for Fontaine III/IV peripheral arterial disease (0.23 DALY/month, 95% confidence interval [CI]: 0.13-0.36) and transaortic valve implantation (0.15 DALY/month, 95% CI: 0.09-0.24). The 2 surgical procedures with the least DALYs were placing a shunt for dialysis (0.01, 95% CI: 0.005-0.01) and thyroid carcinoma resection (0.01, 95% CI: 0.01-0.02).ConclusionExpected health loss owing to surgical delay can be objectively calculated with our decision model based on best available evidence, which can guide prioritization of surgical procedures to minimize population health loss in times of scarcity. The model results should be placed in the context of different ethical perspectives and combined with capacity management tools to facilitate large-scale implementation.     

PERCH: A Unified Framework for Disease Gene Prioritization

To interpret genetic variants discovered from next‐generation sequencing, integration of heterogeneous information is vital for success. This article describes a framework named PERCH (P olymorphism E valuation, R anking, and C lassification for a H eritable trait), available at http://BJFengLab.org/ . It can prioritize disease genes by quantitatively unifying a new deleteriousness measure called BayesDel, an improved assessment of the biological relevance of genes to the disease, a modified linkage analysis, a novel rare‐variant association test, and a converted variant call quality score. It supports data that contain various combinations of extended pedigrees, trios, and case–controls, and allows for a reduced penetrance, an elevated phenocopy rate, liability classes, and covariates. BayesDel is more accurate than PolyPhen2, SIFT, FATHMM, LRT, Mutation Taster, Mutation Assessor, PhyloP, GERP++, SiPhy, CADD, MetaLR, and MetaSVM. The overall approach is faster and more powerful than the existing quantitative method pVAAST, as shown by the simulations of challenging situations in finding the missing heritability of a complex disease. This framework can also classify variants of unknown significance (variants of uncertain significance) by quantitatively integrating allele frequencies, deleteriousness, association, and co‐segregation. PERCH is a versatile tool for gene prioritization in gene discovery research and variant classification in clinical genetic testing.