Age-related changes can affect mental health, but aging-focused mental health research is limited. The objective was to identify the top 10 unanswered research questions on aging and mental health according to what matters most to aging Canadians. A steering group of experts-by-experience (e.g., older adults, caregivers, health and social care providers) guided three phases of a modified James Lind Alliance priority-setting partnership: (1) a broad national survey (n = 305) and a rapid literature scan; (2) a follow-up national survey (n = 703); and (3) four online workshops (n = 52) with a nominal group technique. Forty-two unique questions on aging and mental health resulted, of which 18 were determined to be answered by existing evidence. Of the 25 partially and unanswered questions, 10 were ranked as top priority. Findings can be used to prioritize future research, knowledge mobilization, and funding decisions, and to promote and support collaboration between longstanding siloed research and care fields.

Some philosophers and segments of the public think age is relevant to healthcare priority-setting. One argument for this is based in equity: “Old” patients have had either more of a relevant good than “young” patients or enough of that good and so have weaker claims to treatment. This article first notes that some discussions of age-based priority that focus in this way on old and young patients exhibit an ambiguity between two claims: that patients classified as old should have a low priority, and that patients classified as young should have high priority. The author next argues, drawing on a problem raised by Christine Overall, that equity cannot justify giving “old” patients low priority, since there is wide variety in the total lifetime experiences of older people, partly influenced by gender, race, class, and disability injustice. Finally, the author suggests that there might be a limited role for age-based prioritization in the context of infant and childhood death, since those who die in childhood are always and uncontroversially among the worst-off.

When setting priorities for health, there is broad agreement that a range of social values and ethical principles beyond clinical and cost-effectiveness matter, but exactly how health technology assessment (HTA) should account for a broader set of criteria remains an area of ongoing debate. In light of this, we welcome a recent review paper by Baltussen et al. evaluating the potential of different multi-criteria decision analysis (MCDA) approaches to enable HTA agencies to incorporate a broader set of values in their appraisals. The authors describe three approaches to MCDA—qualitative MCDA, quantitative MCDA, and MCDA with decision rules—laying out their relative advantages and disadvantages and providing recommendations for how they can best be implemented. While we endorse many of the authors' assessments and conclusions, including the critical role of deliberation in any MCDA approach and the undertaking of qualitative MCDA at a minimum, we take a stronger position regarding the flaws of quantitative MCDA and strongly caution against it. We find quantitative MCDA antithetical to at least two of the ways MCDA is intended to improve HTA recommendations: (i) enhancing quality and (ii) promoting transparency. Quantitative MCDA may mask the complex tradeoffs that exist within and between decision criteria and remain generally inaccessible to those who are not well-versed in its technical methods of appraisal. We advocate for a predominantly qualitative approach to MCDA appraisal centered around deliberation and supplemented with decision aids to help account for health opportunity costs.

Although substantial amount of nutrition research is conducted in Africa, the research agenda is mainly donor-driven. There is a clear need for a revised research agenda in Africa which is both driven by and responding to local priorities. The present paper summarises proceedings of a symposium on how evidence can guide decision makers towards context-appropriate priorities and decisions in nutrition. The paper focuses on lessons learnt from case studies by the Evidence Informed Decision Making in Nutrition and Health Network implemented between 2015 and 2016 in Benin, Ghana and South Africa. Activities within these countries were organised around problem-oriented evidence-informed decision-making (EIDM), capacity strengthening and leadership and horizontal collaboration. Using a combination of desk-reviews, stakeholder influence-mapping, semi-structured interviews and convening platforms, these country-level studies demonstrated strong interest for partnership between researchers and decision makers, and use of research evidence for prioritisation and decision making in nutrition. Identified capacity gaps were addressed through training workshops on EIDM, systematic reviews, cost–benefit evaluations and evidence contextualisation. Investing in knowledge partnerships and development of capacity and leadership are key to drive appropriate use of evidence in nutrition policy and programming in Africa.

Objectives: The objectives of this study is to review the set of criteria of the Institute of Medicine (IOM) for priority-setting in research with addition of new criteria if necessary, and to develop and evaluate the reliability and validity of the final priority score.

Methods: Based on the evaluation of 199 research topics, forty-five experts identified additional criteria for priority-setting, rated their relevance, and ranked and weighted them in a three-round modified Delphi technique. A final priority score was developed and evaluated. Internal consistency, test–retest and inter-rater reliability were assessed. Correlation with experts’ overall qualitative topic ratings were assessed as an approximation to validity.

Results: All seven original IOM criteria were considered relevant and two new criteria were added (“potential for translation into practice”, and “need for knowledge”). Final ranks and relative weights differed from those of the original IOM criteria: “research impact on health outcomes” was considered the most important criterion (4.23), as opposed to “burden of disease” (3.92). Cronbach's alpha (0.75) and test–retest stability (interclass correlation coefficient = 0.66) for the final set of criteria were acceptable. The area under the receiver operating characteristic curve for overall assessment of priority was 0.66.

Conclusions: A reliable instrument for prioritizing topics in clinical and health services research has been developed. Further evaluation of its validity and impact on selecting research topics is required.

We develop and apply a four-dimensional priority-setting process for the conservation of threatened birds in Venezuela. The axes that we consider are extinction risk, degree of endemicity, taxonomic uniqueness and public appeal. Alhough the first three are relatively objective measures of biological attributes, the last one is a subjective judgement of the likelihood that conservation actions in favour of a species may succeed. By grouping higher priority species according to their geographical distribution within Venezuela, we generate a list of the top priorities to save the country's threatened birds, both species- and bioregion-based. The highest priority species are northern-helmeted curassow Pauxi pauxi, Andean condor Vultur gryphus, red siskin Carduelis cucullata and plain-flanked rail Rallus wetmorei, followed by eight high priority birds, wattled guan Aburria aburri, yellow-shouldered parrot Amazona barbadensis, scissor-tailed hummingbird Hylonympha macrocerca, rusty-faced parrot Hapalopsittaca amazonina, northern screamer Chauna chavaria, torrent duck Merganetta armata, rusty-flanked crake Laterallus levraudi, and military macaw Ara militaris. Northern Venezuela stands out as a significantly higher conservation priority than the south. The Andean Cordillera, Central Coastal Cordillera, Paria Peninsula-Turimiquire Massif Complex, and Sierra de Perijá are the highest priority bioregions, followed by Lara-Falcón Arid Lands and Maracaibo Lake Basin. A final set of combined priorities was determined by integrating all top ranking species and bioregions. Our approach is relatively simple and readily applicable to other taxa and regions.