Unravelling the migration decision-making process: English early retirees moving to rural mid-Wales

There are established migrant reasons to explain rural in-migration. These include quality of life, rural idyll and lifestyle motivations. However, such one-dimensional sound bites portray rural in-migration in overly simplistic and stereotypical terms. In contrast, this paper distinguishes the decision to move from the reason for moving and in doing so sheds new light on the interconnections between different domains (family, work, finance, health) of the migrant's life which contribute to migration behaviour. Focussing on early retirees to mid-Wales and adopting a life course perspective the overall decision to move is disaggregated into a series of decisions. Giving voices to the migrants themselves demonstrates the combination of life events necessary to lead to migration behaviour, the variable factors (and often economic dominance) considered in the choice of destination (including that many are reluctant migrants to Wales), and the perceived 'accidental' choice of location and/or property. It is argued that quality of life, rural idyll and lifestyle sound bites offer an inadequate understanding of rural in-migration and associated decision-making processes. Moreover, they disguise the true nature of migrant decision making.

Shared decision making in patients at risk of cancer: The role of domain and numeracy

Background
Shared decision making has become an integral part of medical consultation. Research has, however, reported wide differences in individuals' desires to be involved in the decision-making process, and these differences in preferences are likely to be the result of a number of factors including age, education and numeracy.

Objective
To investigate whether patients at genetic risk for cancer had preferences for shared decision making that differed depending on medical domain (general health vs. cancer) and whether decision preferences are linked to numeracy abilities.

Methods
Four hundred and seventy-six women who consented to participate in response to an email sent by a local branch of the U.S.-based Cancer Genetics Network (CGN) to its members. Participants completed the Control Preference Scale, as well as an objective and subjective numeracy scales.

Results
Decision domain (cancer vs. general health) was not associated with women's preferences for involvement in decision making. Objective and subjective numeracy predicted a preference for decision involvement in general, and only objective numeracy was predictive with regard to cancer.

Conclusion
Participants were equally likely to state they wanted to play an active, collaborative or passive role in both medical domains (general and cancer). High-numeracy participants were more likely to express a desire for an active role in general and in case they were diagnosed with cancer.

Practice implications
Health authorities' recommendations to clinicians to include patients in their medical decisions are supported by patients' desires, and clinicians should be cognizant of their patients' preferences as well as their numeracy skills.

Can Safe Clinical Thinking be Taught?

OBJECTIVES: To determine if: (a) safe clinical decision making can be taught to undergraduate final year medical students and (b) if such students can be taught to specifically recognise illness severity from nominal clinical data. 
METHODS: 115 final year undergraduate medical students completed a 3 hour interactive Safe Thinking Workshop which focussed entirely on nontechnical skills such as potential perceptive pitfalls, attention to detail, teamwork and safe clinical decision making. The study involved students inspecting and interpreting a set of arterial blood gas results relating to a patient with acute respiratory distress, then answering a short questionnaire addressing biochemical diagnosis, clinical diagnosis and effective management. A separate question was embedded in the questionnaire to determine if astute students could determine the severity of the illness from the CO2 value provided. The study group (n = 58) completed the questionnaire immediately after the Safe Thinking Workshop, whilst the control group (n = 57) completed the questionnaire prior to the Workshop.
RESULTS: The mean total score for study students was 80.51%, with a mean total score of 63.86% for the control group (Student’s t-test; p<0.05). Correct classification of illness severity was observed in 10.35% of study students, compared with 3.51% of control students (p<0.05). 
CONCLUSION: These results suggest that safe clinical decision making and recognition of illness severity can be fostered by specific teaching in the nontechnical skill areas described above.

An international comparison of legal frameworks for supported and substitute decision-making in mental health services

There have been important recent developments in law, research, policy and practice relating to supporting people with decision-making impairments, in particular when a person’s wishes and preferences are unclear or inaccessible. A driver in this respect is the United Nations Convention on the Rights of Persons with Disabilities (CRPD); the implications of the CRPD for policy and professional practices are currently debated. This article reviews and compares four legal frameworks for supported and substitute decision-making for people whose decision-making ability is impaired. In particular, it explores how these frameworks may apply to people with mental health problems. The four jurisdictions are: Ontario, Canada; Victoria, Australia; England and Wales, United Kingdom (UK); and Northern Ireland, UK. Comparisons and contrasts are made in the key areas of: the legal framework for supported and substitute decision-making; the criteria for intervention; the assessment process; the safeguards; and issues in practice. Thus Ontario has developed a relatively comprehensive, progressive and influential legal framework over the past thirty years but there remain concerns about the standardisation of decision-making ability assessments and how the laws work together. In Australia, the Victorian Law Reform Commission (2012) has recommended that the six different types of substitute decision-making under the three laws in that jurisdiction, need to be simplified, and integrated into a spectrum that includes supported decision-making. In England and Wales the Mental Capacity Act 2005 has a complex interface with mental health law. In Northern Ireland it is proposed to introduce a new Mental Capacity (Health, Welfare and Finance) Bill that will provide a unified structure for all substitute decision-making. The discussion will consider the key strengths and limitations of the approaches in each jurisdiction and identify possible ways that further progress can be made in law, policy and practice.

Regret and adaptive decision making in young children

In line with the claim that regret plays a role in decision making, O’Connor, McCormack, and Feeney (2014) found that children who reported feeling sadder on discovering they had made a non-optimal choice were more likely to make a different choice next time round. We examined two issues of interpretation regarding this finding: whether the emotion measured was indeed regret, and whether it was the experience of this emotion rather than the ability to anticipate it that impacted on decision making. To address the first issue, we varied the degree to which children aged 6-7 were responsible for an outcome, assuming that responsibility is a necessary condition for regret. The second was addressed by examining whether children could accurately anticipate that they would feel worse on discovering they had made a non-optimal choice. Children were more likely to feel sad if they were responsible for the outcome; however even if they were not responsible, children were more likely than chance to report feeling sadder. Moreover, across all conditions feeling sadder was associated with making a better subsequent choice. In a separate task, we demonstrated that children of this age cannot accurately anticipate feeling sadder on discovering that they had not made the best choice. These findings suggest that although children may feel regret following a non-optimal choice, even if they were not responsible for an outcome they may experience another negative emotion such as frustration. Experiencing either of these emotions seems to be sufficient to support better decision making.

Approximate credal network updating by linear programming with applications to decision making

Credal nets are probabilistic graphical models which extend Bayesian nets to cope with sets of distributions. An algorithm for approximate credal network updating is presented. The problem in its general formulation is a multilinear optimization task, which can be linearized by an appropriate rule for fixing all the local models apart from those of a single variable. This simple idea can be iterated and quickly leads to accurate inferences. A transformation is also derived to reduce decision making in credal networks based on the maximality criterion to updating. The decision task is proved to have the same complexity of standard inference, being NPPP-complete for general credal nets and NP-complete for polytrees. Similar results are derived for the E-admissibility criterion. Numerical experiments confirm a good performance of the method.

Decision Making by Credal Nets

Credal nets are probabilistic graphical models which extend Bayesian nets to cope with sets of distributions. This feature makes the model particularly suited for the implementation of classifiers and knowledge-based systems. When working with sets of (instead of single) probability distributions, the identification of the optimal option can be based on different criteria, some of them eventually leading to multiple choices. Yet, most of the inference algorithms for credal nets are designed to compute only the bounds of the posterior probabilities. This prevents some of the existing criteria from being used. To overcome this limitation, we present two simple transformations for credal nets which make it possible to compute decisions based on the maximality and E-admissibility criteria without any modification in the inference algorithms. We also prove that these decision problems have the same complexity of standard inference, being NP^PP-hard for general credal nets and NP-hard for polytrees.