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.

For many patients, the time spent meeting with their physician-the clinical encounter-is the most opportune moment for them to become engaged in their own health through the process of shared decision making. In the United States shared decision making is being promoted for its potential to improve the health of populations and individual patients, while also helping control care costs. In this overview we describe the three essential elements of shared decision making: recognizing and acknowledging that a decision is required; knowing and understanding the best available evidence; and incorporating the patient's values and preferences into the decision. To achieve the promise of shared decision making, more physicians need training in the approach, and more practices need to be reorganized around the principles of patient engagement. Additional research is also needed to identify the interventions that are most effective.

Background Across countries and disciplines, studies show male researchers receive more research funding than their female peers. Because most studies have been observational, it is unclear whether imbalances stem from evaluations of female research investigators or of their proposed research. In 2014, the Canadian Institutes of Health Research created a natural experiment by dividing investigator-initiated funding applications into two new grant programmes: one with and one without an explicit review focus on the calibre of the principal investigator. Methods We analysed application success among 23 918 grant applications from 7093 principal investigators in all investigator-initiated Canadian Institutes of Health Research grant programmes between 2011 and 2016. We used generalised estimating equations to account for multiple applications by the same applicant and compared differences in application success between male and female principal investigators under different review criteria. Findings Overall application success across competitions was 15•8%. After adjusting for age and research domain, the predicted probability of success in traditional programmes was 0•9 percentage points lower for female applicants than male applicants (95% CI 2•0 lower-0•2 higher; odds ratio 0•934, 95% CI 0•854-1•022). In the new programme, in which review focused on the proposed science, the gap remained 0•9 percentage points (3•2 lower-1•4 higher; 0•998, 0•794-1•229). In the new programme with an explicit review focus on the calibre of the principal investigator, the gap was 4•0 percentage points (6•7 lower-1•3 lower; 0•705, 0•519-0•960). Interpretation Gender gaps in grant funding are attributable to less favourable assessments of women as principal investigators, not of the quality of their proposed research. We discuss reasons less favourable assessments might occur and strategies to foster fair and rigorous peer review.

BackgroundConsensus guidelines have recommended that decision aids include a process for helping patients clarify their values. We sought to examine the theoretical and empirical evidence related to the use of values clarification methods in patient decision aids.MethodsBuilding on the International Patient Decision Aid Standards (IPDAS) Collaboration’s 2005 review of values clarification methods in decision aids, we convened a multi-disciplinary expert group to examine key definitions, decision-making process theories, and empirical evidence about the effects of values clarification methods in decision aids. To summarize the current state of theory and evidence about the role of values clarification methods in decision aids, we undertook a process of evidence review and summary.ResultsValues clarification methods (VCMs) are best defined as methods to help patients think about the desirability of options or attributes of options within a specific decision context, in order to identify which option he/she prefers. Several decision making process theories were identified that can inform the design of values clarification methods, but no single “best” practice for how such methods should be constructed was determined. Our evidence review found that existing VCMs were used for a variety of different decisions, rarely referenced underlying theory for their design, but generally were well described in regard to their development process. Listing the pros and cons of a decision was the most common method used. The 13 trials that compared decision support with or without VCMs reached mixed results: some found that VCMs improved some decision-making processes, while others found no effect.ConclusionsValues clarification methods may improve decision-making processes and potentially more distal outcomes. However, the small number of evaluations of VCMs and, where evaluations exist, the heterogeneity in outcome measures makes it difficult to determine their overall effectiveness or the specific characteristics that increase effectiveness.