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AIMS: This study aimed to explore how incorporating shared decision-making (SDM) can address recruitment challenges in clinical trials. Specifically, it examines how SDM can align the trial process with patient preferences, enhance patient autonomy and increase active patient participation. Additionally, it identifies potential conflicts between SDM and certain clinical trial aspects, such as randomization or blinding, and proposes solutions to mitigate these issues. MATERIALS AND METHODS: We conducted a comprehensive review of existing literature on patient recruitment challenges in clinical trials and the role of SDM in addressing these challenges. We analysed case studies and trial reports to identify common obstacles and assess the effectiveness of SDM in improving patient accrual. Additionally, we evaluated three proposed solutions: adequate trial design, communication skill training and patient decision aids. RESULTS: Our review indicates that incorporating SDM can significantly enhance patient recruitment by promoting patient autonomy and engagement. SDM encourages physicians to adopt a more open and informative approach, which aligns the trial process with patient preferences and reduces psychological barriers such as fear and mental stress. However, implementing SDM can conflict with elements such as randomization and blinding, potentially complicating trial design and execution. DISCUSSION: The desire for patient autonomy and active engagement through SDM may clash with traditional clinical trial methodologies. To address these conflicts, we propose three solutions: redesigning trials to better accommodate SDM principles, providing communication skill training for physicians and developing patient decision aids. By focussing on patient wishes and emotions, these solutions can integrate SDM into clinical trials effectively. CONCLUSION: Shared decision-making provides a framework that can promote patient recruitment and trial participation by enhancing patient autonomy and engagement. With proper implementation of trial design modifications, communication skill training and patient decision aids, SDM can support rather than hinder clinical trial execution, ultimately contributing to the advancement of evidence-based medicine.

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Emotions influence human decisions under risk and uncertainty, even when they are unrelated to the decisions, i.e. incidental to them. Empirical findings are mixed regarding the directions and sizes of the effects of discrete emotions such as fear, anger, or happiness. According to the Appraisal-Tendency Framework (ATF), appraisals of certainty and control determine why same-valence emotions can differentially alter preferences for risky and uncertain options. Building upon this framework of emotion-specific appraisals, we conducted a systematic review and meta-analysis of 28 experimental studies on the effects of discrete incidental emotions on decision-making under risk and uncertainty. We evaluated potential moderators at the task and study levels. We find emotion-specific, moderately heterogeneous effects partially in line with the expectations of the ATF. The framing and financial consequences of choices, the type of choices, and the presence of other participants during the task do not moderate the effect. Our meta-analytic results support the differential influence of discrete, incidental emotions on decision-making under risk and uncertainty depending on appraisals other than valence. We discuss limited sample sizes and heterogeneity as reasons for the absence of significant moderators and encourage experimental investigations of individual differences in the susceptibility to incidental affective influences.

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In oncology, decision-making in individual situations is often very complex. To deal with such complexity, people tend to reduce it by relying on their initial intuition. The downside of this intuitive, subjective way of decision-making is that it is prone to cognitive and emotional biases such as overestimating the quality of its judgements or being influenced by one's current mood. Hence, clinical predictions based on intuition often turn out to be wrong and to be outperformed by statistical predictions. Structuring and objectivizing oncological decision-making may thus overcome some of these issues and have advantages such as avoidance of unwarranted clinical practice variance or error-prevention. Even for uncertain situations with limited medical evidence available or controversies about the best treatment option, structured decision-making approaches like clinical algorithms could outperform intuitive decision-making. However, the idea of such algorithms is not to prescribe the clinician which decision to make nor to abolish medical judgement, but to support physicians in making decisions in a systematic and structured manner. An example for a use-case scenario where such an approach may be feasible is the selection of treatment dose in radiation oncology. In this paper, we will describe how a clinical algorithm for selection of a fractionation scheme for palliative irradiation of bone metastases can be created. We explain which steps in the creation process of a clinical algorithm for supporting decision-making need to be  performed and which challenges and limitations have to be considered.

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Emotions play an important role in decision-making and they can impact individual as well as shared decisions. With increasing complexity of the decision, the potential for emotions to influence the outcome increases. Emotions are thus an influential factor in oncological decision-making which is a complex and high-stakes situation. As the shared decision-making process is at the center of patient-centric decisions, we model emotions as social information that inform the shared decision-making process. We present and explain a range of emotional concepts, together with a specific clinical example, that can impact the shared decision-making process. Our process model shows that emotions are experienced in various combinations before, during, and after a shared decision is made and how patients' and physicians' emotions interact and spill over during a shared decision situation. Overall, our process model and specific example show how emotions can impact shared decision-making in oncology in a multitude of ways. With this paper, we want to raise awareness of the role of emotions in the shared decision-making process, as emotions are often not explicitly recognized as decision criteria. Increased awareness of emotions may help their optimal utilization and reduce their influence as a bias in shared decision-making.

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Overconfidence has been identified as a source of suboptimal decision making in many real-life domains, with often far-reaching consequences. This study identifies a mechanism that can cause overconfidence and demonstrates a simple, effective countermeasure in an incentive-compatible experimental study. We observed that joy induced overconfidence if the reason for joy (an unexpected gift) was unrelated to the judgment task and if participants were not made specifically aware of this mood manipulation. In contrast, we observed well-calibrated judgments among participants in a control group who were in their resting mood. Furthermore, we found well-calibrated judgments among participants who received the joyful mood induction together with questions that forced them to reflect on their current mood and the (ir)relevance of its cause to our judgment tasks. Our findings suggest that being aware of one's positive mood and the reason for that mood may effectively reduce overconfidence for a short period.

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