A generic societal preference-based scoring system is now available for all studies using these 7 PROMIS health domains.

ObjectivesThe PROMIS-Preference (PROPr) score is a recently developed summary score for the Patient-Reported Outcomes Measurement Information System (PROMIS). PROPr is a preference-based scoring system for seven PROMIS domains created using multiplicative multi-attribute utility theory. It serves as a generic, societal, preference-based summary scoring system of health-related quality of life. This manuscript evaluates construct validity of PROPr in two large samples from the US general population.MethodsWe utilized 2 online panel surveys, the PROPr Estimation Survey and the Profiles-Health Utilities Index (HUI) Survey. Both included the PROPr measure, patient demographic information, self-reported chronic conditions, and other preference-based summary scores: the EuroQol-5D (EQ-5D-5L) and HUI in the PROPr Estimation Survey and the HUI in the Profiles-HUI Survey. The HUI was scored as both the Mark 2 and the Mark 3. Known-groups validity was evaluated using age- and gender-stratified mean scores and health condition impact estimates. Condition impact estimates were created using ordinary least squares regression in which a summary score was regressed on age, gender, and a single health condition. The coefficient for the health condition is the estimated effect on the preference score of having a condition vs. not having it. Convergent validity was evaluated using Pearson correlations between PROPr and other summary scores.ResultsThe sample consisted of 983 respondents from the PROPr Estimation Survey and 3,000 from the Profiles-HUI survey. Age- and gender-stratified mean PROPr scores were lower than EQ-5D and HUI scores, with fewer subjects having scores corresponding to perfect health on the PROPr. In the PROPr Estimation survey, all 11 condition impact estimates were statistically significant using PROPr, 8 were statistically significant by the EQ-5D, 7 were statistically significant by HUI Mark 2, and 9 were statistically significant by HUI Mark 3. In the Profiles-HUI survey, all 21 condition impact estimates were statistically significant using summary scores from all three scoring systems. In these samples, the correlations between PROPr and the other summary measures ranged from 0.67 to 0.70.ConclusionsThese results provide evidence of construct validity for PROPr using samples from the US general population.

Objectives: The Patient-Reported Outcomes Measurement Information System ® (PROMIS) Profile instruments measure health status on 8 PROMIS domains. The PROMIS-Preference (PROPr) score provides a preference-based summary score for health states defined by 7 PROMIS domains. The Profile and PROPr share 6 domains; PROPr has 1 unique domain (Cognitive Function-Abilities), and the Profile has 2 unique domains (Anxiety and Pain Intensity). We produce an equation for calculating PROPr utility scores with Profile data.Methods: We used data from 3982 members of US online survey panels who have scores on all 9 PROMIS domains. We used a 70%/30% split for model fit/validation. Using root-mean-square error and mean error on the utility scale, we compared models for predicting the missing Cognitive Function score via (A) the population average; (B) a score representing excellent cognitive function; (C) a score representing poor cognitive function; (D) a score predicted from linear regression of the 8 profile domains; and (E) a score predicted from a Bayesian neural network of the 8 profile domains.Results: The mean errors in the validation sample on the PROPr scale (which ranges from -0.022 to 1.00) for the models were: (A) 0.025, (B) 0.067, (C) -0.23, (D) 0.018, and (E) 0.018. The root-mean-square errors were: (A) 0.097, (B) 0.12, (C) 0.29, (D) 0.095, and (E) 0.094. Conclusion:Although the Bayesian neural network had the best root-mean-square error for producing PROPr utility scores from Profile instruments, linear regression performs almost as well and is easier to use. We recommend the linear model for producing PROPr utility scores for PROMIS Profiles.

In this manuscript we study type A nilpotent Hessenberg varieties equipped with a natural S 1action using techniques introduced by Tymoczko, Harada-Tymoczko, and Bayegan-Harada, with a particular emphasis on a special class of nilpotent Springer varieties corresponding to the partition λ = (n − 2, 2) for n ≥ 4. First we define the adjacent-pair matrix corresponding to any filling of a Young diagram with n boxes with the alphabet {1, 2, . . . , n}. Using the adjacent-pair matrix we make more explicit and also extend some statements concerning highest forms of linear operators in previous work of Tymoczko. Second, for a nilpotent operator N and Hessenberg function h, we construct an explicit bijection between the S 1 -fixed points of the nilpotent Hessenberg variety Hess(N, h) and the set of (h, λ N )-permissible fillings of the Young diagram λ N . Third, we use poset pinball, the combinatorial game introduced by Harada and Tymoczko, to study the S 1equivariant cohomology of type A Springer varieties S (n−2,2) associated to Young diagrams of shape (n − 2, 2) for n ≥ 4. Specifically, we use the dimension pair algorithm for Betti-acceptable pinball described by Bayegan and Harada to specify a subset of the equivariant Schubert classes in the T -equivariant cohomology of the flag variety Fℓags(C n ) ∼ = GL(n, C)/B which maps to a module basis of H * S 1 (S (n−2,2) ) under the projection map H * T (Fℓags(C n )) → H * S 1 (S (n−2,2) ). Our poset pinball module basis is not poset-upper-triangular; this is the first concrete such example in the literature. A straightforward consequence of our proof is that there exists a simple and explicit change of basis which transforms our poset pinball basis to a poset-upper-triangular module basis for H * S 1 (S (n−2,2) ).We close with open questions for future work. CONTENTS 1. Introduction 1 2. Nilpotent Hessenberg varieties and S 1 -actions 3 3. Adjacent-pair matrices and highest forms of nilpotent operators 4 4. S 1 -fixed points in Hessenberg varieties and permissible fillings 12 5. Betti-acceptable pinball and linear independence 14 6. Small-n cases: n = 4 and n = 5 17 7. A poset pinball module basis for (n − 2, 2) Springer varieties 18 8. Open questions 24 References 24 1 We use English notation for Young diagrams. 2 We work with cohomology with coefficients in C throughout, and hence omit it from our notation.POSET PINBALL, HIGHEST FORMS, AND (n − 2, 2) SPRINGER VARIETIES 3 between permissible fillings and S 1 -fixed points of the Springer variety. The module basis is obtained by taking images under the natural projection map H * T (Fℓags(C n )) → H * S 1 (S (n−2,2) ), to be described in detail below, of a subset of the T -equivariant Schubert classes in H * T (Fℓags(C n )). A similar analysis by Bayegan and the second author in a special case of regular nilpotent Hessenberg varieties [2] yields a poset-uppertriangular basis in the sense of [9]. In contrast to the results in [2], in the present manuscript we find that the module basis is not poset-upper-triangular; this is t...

Background Health-related quality of life (HRQL) scores are used extensively to quantify the effectiveness of medical interventions. Societal preference-based HRQL scores aim to produce societal valuations of health by aggregating valuations from individuals in the general population, where each aggregation procedure embodies different ethical principles, as explained in social choice theory. Methods Using the Health Utilities Index as an exemplar, we evaluate societal preference-based HRQL measures in the social choice theory framework. Results We find that current preference aggregation procedures are typically justified in terms of social choice theory. However, by convention, they use only one of many possible aggregation procedures (the mean). Central to the choice of aggregation procedure is how to treat preference heterogeneity, which can affect analyses that rely on HRQL scores, such as cost-effectiveness analyses. We propose an analytical-deliberative framework for choosing one (or a set of) aggregation procedure(s) in a socially credible way, which we believe to be analytically sound and empirically tractable, but leave open the institutional mechanism needed to implement it. Conclusions Socially acceptable decisions about aggregating heterogeneous preferences require eliciting stakeholders’ preferences among the set of analytically sound procedures, representing different ethical principles. We describe a framework for eliciting such preferences for the creation of HRQL scores, informed by social choice theory and behavioral decision research.

IMPORTANCEThe US Food and Drug Administration (FDA) authorized SARS-CoV-2 rapid at-home self-test kits for individuals with and without symptoms. How appropriately users interpret and act on the results of at-home COVID-19 self-tests is unknown.OBJECTIVE To assess how users of at-home COVID-19 self-test kits interpret and act on results when given instructions authorized by the FDA, instructions based on decision science principles, or no instructions. DESIGN, SETTING, AND PARTICIPANTSA randomized clinical trial was conducted of 360 adults in the US who were recruited in April 2021 to complete an online survey on their interpretation of at-home COVID-19 self-test results. Participants were given 1 of 3 instruction types and were presented with 1 of 4 risk scenarios. Participants were paid $5 and had a median survey completion time of 8.7 minutes. Data analyses were performed from June to July 2021.INTERVENTION Participants were randomized to receiving either the FDA-authorized instructions (authorized), the intervention instructions (intervention), or no instructions (control), and to 1 of 4 scenarios: 3 with a high pretest probability of infection (COVID-19 symptoms and/or a close contact with COVID-19) and 1 with low pretest probability (no symptoms and no contact). The intervention instructions were designed using decision science principles.MAIN OUTCOMES AND MEASURES Proportion of participants in the high pretest probability scenarios choosing to quarantine per federal recommendations and perceived probabilities of infection given a negative or positive COVID-19 test result. A Bonferroni correction accounted for multiple comparisons (3 instruction types × 4 scenarios; α = 0.004). RESULTSAfter excluding 22 individuals who completed the survey too quickly, the responses of 338 participants (median [IQR] age, 38 [31 to 48] years; 154 (46%) women; 215 (64%) with a college degree or higher) were included in the study analysis. Given a positive test result, 95% (322 of 338; 95% CI, 0.92 to 0.97) of the total participants appropriately chose to quarantine regardless of which instructions they had received. Given a negative test result, participants in the high pretest probability scenarios were more likely to fail to quarantine appropriately with the authorized instructions (33%) than with the intervention (14%; 95% CI for the 19% difference, 6% to 31%; P = .004) or control (24%; 95% CI for the 9% difference, −4% to 23%; P = .02). In the low pretest probability scenario, the proportion choosing unnecessary quarantine was higher with the authorized instructions (31%) than with the intervention (22%; 95% CI for the 9% difference, −14% to 31%) or control (10%; 95% CI for the 21% difference, 0.5% to 41%)-neither comparison was statistically significant (P = .05 and P = .20 respectively). CONCLUSIONS AND RELEVANCEThe findings of this randomized clinical trial indicate that at-home COVID-19 self-test kit users relying on the authorized instructions may not follow the Centers for Disease Control and Prevention's quarantine...

Danish children find new bacteria One of the worlds' largest citizenscience experiments has led to the rapid discovery of ten new bacterial species in Denmark. About 25,000 schoolchildren aged 10-16 years found these Lactobacillus species after analysing some 11,000 plant samples from urban and rural ecosystems (see go.nature. com/2sq5muw). By comparison, Danish researchers find an average of just one new bacterial species per year. Lactobacillus is a beneficial group of bacteria that has been used for food preservation for thousands of years (M. Bernardeau et al. FEMS Microbiol. Rev. 30, 487-513; 2006). The study was spearheaded by the biotechnology company Novozymes near Copenhagen, and its updated biobank is now open to researchers around the world, offering fresh opportunities for industrial and drug development. Children are a large but untapped source of citizen scientists (see also Nature 562, 480-482; 2018). Moreover, they will form the next generation of scientists.

Background. In a systematic review, Engel et al. found large variation in the exclusion criteria used to remove responses held not to represent genuine preferences in health state valuation studies. We offer an empirical approach to characterizing the similarities and differences among such criteria. Setting. Our analyses use data from an online survey that elicited preferences for health states defined by domains from the Patient-Reported Outcomes Measurement Information System (PROMIS®), with a U.S. nationally representative sample ( N = 1164). Methods. We use multidimensional scaling to investigate how 10 commonly used exclusion criteria classify participants and their responses. Results. We find that the effects of exclusion criteria do not always match the reasons advanced for applying them. For example, excluding very high and very low values has been justified as removing aberrant responses. However, people who give very high and very low values prove to be systematically different in ways suggesting that such responses may reflect different processes. Conclusions. Exclusion criteria intended to remove low-quality responses from health state valuation studies may actually remove deliberate but unusual ones. A companion article examines the effects of the exclusion criteria on societal utility estimates.