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.

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.

PAlliative Care in chronic Kidney diSease: the PACKS study—quality of life, decision making, costs and impact on carers in people managed without dialysis

BACKGROUND: The number of patients with advanced chronic kidney disease opting for conservative management rather than dialysis is unknown but likely to be growing as increasingly frail patients with advanced renal disease present to renal services. Conservative kidney management includes ongoing medical input and support from a multidisciplinary team. There is limited evidence concerning patient and carer experience of this choice. This study will explore quality of life, symptoms, cognition, frailty, performance decision making, costs and impact on carers in people with advanced chronic kidney disease managed without dialysis and is funded by the National Institute of Health Research in the UK.

METHODS: In this prospective, multicentre, longitudinal study, patients will be recruited in the UK, by renal research nurses, once they have made the decision not to embark on dialysis. Carers will be asked to 'opt-in' with consent from patients. The approach includes longitudinal quantitative surveys of quality of life, symptoms, decision making and costs for patients and quality of life and costs for carers, with questionnaires administered quarterly over 12 months. Additionally, the decision making process will be explored via qualitative interviews with renal physicians/clinical nurse specialists.

DISCUSSION: The study is designed to capture patient and carer profiles when conservative kidney management is implemented, and understand trajectories of care-receiving and care-giving with the aim of optimising palliative care for this population. It will explore the interactions that lead to clinical care decisions and the impact of these decisions on informal carers with the intention of improving clinical outcomes for patients and the experiences of care givers.

Decision making in child protection: An international comparative study on maltreatment substantiation, risk assessment and interventions recommendations, and the role of professionals’ child welfare attitudes

Child welfare professionals regularly make crucial decisions that have a significant impact on children and their families. The present study presents the Judgments and Decision Processes in Context model (JUDPIC) and uses it to examine the relationships between three indepndent domains: case characteristic (mother’s wish with regard to removal), practitioner characteristic (child welfare attitudes), and protective system context (four countries: Israel, the Netherlands, Northern Ireland and Spain); and three dependent factors: substantiation of maltreatment, risk assessment, and intervention recommendation.
The sample consisted of 828 practitioners from four countries. Participants were presented with a vignette of a case of alleged child maltreatment and were asked to determine whether maltreatment was substantiated, assess risk and recommend an intervention using structured instruments. Participants’ child welfare attitudes were assessed.
The case characteristic of mother’s wish with regard to removal had no impact on judgments and decisions. In contrast, practitioners’ child welfare attitudes were associated with substantiation, risk assessments and recommendations. There were significant country differences on most measures.
The findings support most of the predictions derived from the JUDPIC model. The significant differences between practitioners from different countries underscore the importance of context in child protection decision making. Training should enhance practitioners’ awareness of the impact that their attitudes and the context in which they are embedded have on their judgments and decisions.