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Concept: Decision making software


Socioeconomically vulnerable people are likely to have more health risks because of inadequate behaviour choices related to chronic social stresses. Brain science suggests that stress causes cognitively biased automatic decision making, preferring instant stress relief and pleasure (eg, smoking, alcohol use and drug abuse) as opposed to reflectively seeking health-maintenance services (eg, health check-ups). As such, hedonic stimuli that nudge people towards preventive actions could reduce health behaviour disparities. The purpose of this intervention study was to test this hypothesis.

Concepts: Psychology, Decision making, Risk, Cognition, Decision theory, Decision making software, Addiction, Choice architecture


Rock, Paper, Scissors (RPS) represents a unique gaming space in which the predictions of human rational decision-making can be compared with actual performance. Playing a computerized opponent adopting a mixed-strategy equilibrium, participants revealed a non-significant tendency to over-select Rock. Further violations of rational decision-making were observed using an inter-trial analysis where participants were more likely to switch their item selection at trial n + 1 following a loss or draw at trial n, revealing the strategic vulnerability of individuals following the experience of negative rather than positive outcome. Unique switch strategies related to each of these trial n outcomes were also identified: after losing participants were more likely to ‘downgrade’ their item (e.g., Rock followed by Scissors) but after drawing participants were more likely to ‘upgrade’ their item (e.g., Rock followed by Paper). Further repetition analysis revealed that participants were more likely to continue their specific cyclic item change strategy into trial n + 2. The data reveal the strategic vulnerability of individuals following the experience of negative rather than positive outcome, the tensions between behavioural and cognitive influences on decision making, and underline the dangers of increased behavioural predictability in other recursive, non-cooperative environments such as economics and politics.

Concepts: Game theory, Decision making, Risk, Cognition, Decision theory, Decision making software, Strategy, Flipism


BACKGROUND: The evidence on public health interventions has traditionally focussed on a limited number of costs and benefits, adopted inconsistent methods and is not always relevant to the UK context. This paper develops a multi-criteria decision analysis (MCDA) approach to overcome these challenges. METHODS: A document review and stakeholder consultation was used to identify interventions and the criteria against which they should be assessed. The interventions were measured against these criteria using literature reviews and decision models. Criteria weights were generated using a discrete choice experiment. RESULTS: Fourteen interventions were included in the final ranking. Taxation was ranked as the highest priority. Mass-media campaigns and brief interventions ranked in the top half of interventions. School-based educational interventions, statins and interventions to address mental health problems ranked in the bottom half of interventions. CONCLUSIONS: This paper demonstrates that it is possible to incorporate criteria other than cost-effectiveness in the prioritization of public health investment using an MCDA approach. There are numerous approaches available that adopt the MCDA framework. Further research is required to determine the most appropriate approach in different settings.

Concepts: Health economics, Public health, Decision theory, Decision making software, Cost-utility analysis, Public relations, Multi-criteria decision analysis, New Approach to Appraisal


This article aims to define a value-based approach to pricing and reimbursement for off-patent originators using a multiple criteria decision analysis (MCDA) approach centered on a systematic analysis of current pricing and reimbursement policies in China. A drug price policy review was combined with a quantitative analysis of China’s drug purchasing database. Policy preferences were identified through a MCDA performed by interviewing well-known academic experts and industry stakeholders. The study findings indicate that the current Chinese price policy includes cost-based pricing and the establishment of maximum retail prices and premiums for off-patent originators, whereas reference pricing may be adopted in the future. The literature review revealed significant differences in the dissolution profiles between originators and generics; therefore, dissolution profiles need to be improved. Market data analysis showed that the overall price ratio of generics and off-patent originators was around 0.54-0.59 in 2002-2011, with a 40 % price difference, on average. Ten differentiating value attributes were identified and MCDA was applied to test the impact of three pricing policy scenarios. With the condition of implementing quality consistency regulations and controls, a reduction in the price gap between high-quality off-patent products (including originator and generics) seemed to be the preferred policy. Patents of many drugs will expire within the next 10 years; thus, pricing will be an issue of importance for off-patent originators and generic alternatives.

Concepts: Scientific method, Drug, Decision theory, Decision making software, Qualitative research, Price, Pricing, Suggested retail price


In recent times, the use of health technologies in the diagnosis and treatment of diseases experienced considerable and accelerated growth. The goal of the present study was to describe the designated pilot MCDM (Multiple Criteria Decision Making) model for priority setting of health technology assessment in Iran.

Concepts: Time, Decision theory, Decision making software, Philosophy of science, Technology, Neolithic, Technology assessment, Multi-criteria decision analysis


The patient’s role in medical decision making is often not matched to the clinical circumstances: rather than making strong recommendations when there’s greater certainty and allowing patients to decide when there’s greater uncertainty, we should do the opposite.

Concepts: Decision making, Patient, Risk, Physician, Cognition, Decision theory, Decision making software, Decision engineering


Objectives To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement.Design Multistage consultation process.Setting Key informant group, communities of interest, and survey of clinical specialties.Participants 19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties.Results After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on “team talk,” “option talk,” and “decision talk,” to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals.Conclusions The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences.

Concepts: Decision making, Risk, Decision theory, Decision making software, Choice, Task, Revise, Informant


An enduring and richly elaborated dichotomy in cognitive neuroscience is that of reflective versus reflexive decision making and choice. Other literatures refer to the two ends of what is likely to be a spectrum with terms such as goal-directed versus habitual, model-based versus model-free or prospective versus retrospective. One of the most rigorous traditions of experimental work in the field started with studies in rodents and graduated via human versions and enrichments of those experiments to a current state in which new paradigms are probing and challenging the very heart of the distinction. We review four generations of work in this tradition and provide pointers to the forefront of the field’s fifth generation.

Concepts: Psychology, Brain, Decision making, Cognition, Memory, Decision theory, Decision making software, Computational neuroscience


It is important to understand the magnitude and distribution of the economic burden of prescription opioid overdose, abuse, and dependence to inform clinical practice, research, and other decision makers. Decision makers choosing approaches to address this epidemic need cost information to evaluate the cost effectiveness of their choices.

Concepts: Clinical trial, United States, Economics, Poverty in the United States, Decision theory, Decision making software, Choice, Choice architecture


Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Concepts: Epidemiology, Decision making, Risk, Cognition, Decision theory, Decision making software, Decision engineering, Business Decision Mapping