Recommendations for accelerating open preprint peer review to improve the culture of science.

Peer review is an important part of the scientific process, but traditional peer review at journals is coming under increased scrutiny for its inefficiency and lack of transparency. As preprints become more widely used and accepted, they raise the possibility of rethinking the peer-review process. Preprints are enabling new forms of peer review that have the potential to be more thorough, inclusive, and collegial than traditional journal peer review, and to thus fundamentally shift the culture of peer review toward constructive collaboration. In this Consensus View, we make a call to action to stakeholders in the community to accelerate the growing momentum of preprint sharing and provide recommendations to empower researchers to provide open and constructive peer review for preprints.

Comprehensive profiling of the human viral exposome in households containing an at-risk child with mitochondrial disease during the 2020-2021 COVID-19 pandemic.

BACKGROUND: Viral infection is a major cause of morbidity in children with mitochondrial disease (MtD). As a result, families with children with MtD are highly adherent to risk mitigation behaviours (RMBs) advised by the Centers for Disease Control and Prevention during the COVID-19 pandemic that can modulate infection risk. METHODS: Deep serologic phenotyping of viral infections was performed via home-based sampling by combining SARS-CoV-2 serologic testing and phage display immunoprecipitation and sequencing. Samples were collected approximately 1 year apart (October 2020 to April 2021 and October 2021 to March 2022) on households containing a child with MtD. RESULTS: In contrast to our first collection in 2020-2021, SARS-CoV-2 antibody profiles for all participants in 2021-2022 were marked by greater isotype diversity and the appearance of neutralizing antibodies. Besides SARS-CoV-2, households (N = 15) were exposed to >38 different respiratory and gastrointestinal viruses during the study, averaging five viral infections per child with MtD. Regarding clinical outcomes, children with MtD (N = 17) experienced 34 episodes of illness resulting in 6 hospitalizations, with some children experiencing multiple episodes. Neurologic events following illness were recorded in five patients. Infections were identified via clinical testing in only seven cases. Viral exposome profiles were consistent with clinical testing and even identified infections not captured by clinical testing. CONCLUSIONS: Despite reported adherence to RMBs during the COVID-19 pandemic by families with a child with MtD, viral infection was pervasive. Not all infections resulted in illness in the child with MtD, suggesting that some were subclinical or asymptomatic. However, selected children with MtD did experience neurologic events. Our studies emphasize that viral infections are inexorable, emphasizing the need for further understanding of host-pathogen interactions through broad serologic surveillance.

Short report: Vaccine attitudes in the age of COVID-19 for a population of children with mitochondrial disease.

BACKGROUND: Children with developmental disabilities are vulnerable to morbidity associated with COVID-19. AIMS: To understand attitudes toward routine childhood vaccinations versus the COVID-19 vaccine in a population of families affected by mitochondrial disease (MtD), a form of developmental disability. METHODS AND PROCEDURES: An online survey was administered via several advocacy groups for children with MtD. OUTCOMES AND RESULT: Eighty-six percent of families reported being up to date with the childhood vaccine schedule and seventy percent reported that their affected child receives the annual flu shot. However, only fifty percent reported that the benefits of the COVID-19 vaccine outweighed the risk for their affected child. One quarter of families expressed concern that their child may become sick or deteriorate after the COVID-19 vaccine. In comparison to other routine childhood vaccines, families expressed less confidence in the COVID-19 vaccine. CONCLUSIONS AND IMPLICATIONS: Families affected by this population of developmental disabilities are more comfortable with the vaccines included in the routine childhood immunization schedule than with the newly introduced COVID-19 vaccine, even despite this group's vulnerability.

Undiagnosed COVID-19 in households with a child with mitochondrial disease.

Background: The impact of the COVID-19 pandemic on medically fragile populations, who are at higher risk of severe illness and sequelae, has not been well characterized. Viral infection is a major cause of morbidity in children with mitochondrial disease (MtD), and the COVID-19 pandemic represents an opportunity to study this vulnerable population. Methods: A convenience sampling cross-sectional serology study was conducted (October 2020 to June 2021) in households (N = 20) containing a child with MtD (N = 22). Samples (N = 83) were collected in the home using a microsampling apparatus and shipped to investigators. Antibodies against SARS-CoV-2 nucleocapsid (IgG), spike protein (IgG, IgM, IgA), and receptor binding domain (IgG, IgM, IgA) were determined by enzyme linked immunosorbent assay. Results: While only 4.8% of participants were clinically diagnosed for SARS-CoV-2 infection, 75.9% of study participants were seropositive for SARS-CoV-2 antibodies. Most samples were IgM positive for spike or RBD (70%), indicating that infection was recent. This translated to all 20 families showing evidence of infection in at least one household member. For the children with MtD, 91% had antibodies against SARS-CoV-2 and had not experienced any adverse outcomes at the time of assessment. For children with recent infections (IgM+ only), serologic data suggest household members as a source. Conclusions: COVID-19 was highly prevalent and undiagnosed in households with a child with MtD through the 2020-2021 winter wave of the pandemic. In this first major wave, children with MtD tolerated SARS-CoV-2 infection well, potentially due to household adherence to CDC recommendations for risk mitigation.

Risk mitigation behaviors to prevent infection in the mitochondrial disease community during the COVID-19 pandemic.

BACKGROUND: A challenge during the COVID-19 pandemic has been widespread adherence to risk-reducing behaviors. Individuals with mitochondrial disease (MtD) are special population with an increased risk of morbidity associated with infection. PURPOSE: To measure risk mitigation behaviors (RMBs) in families affected by MtD and identify factors that may influence these behaviors. METHODS: An online questionnaire was distributed in April and June 2020. Individuals with MtD or their caregivers completed the survey. RESULTS: We received 529 eligible responses with n = 312 completing all questions for our multivariate regression model. The most common RMBs were increased hand washing (96%), social distancing (94%), and avoiding public gatherings (93%). Higher numbers of recent healthcare visits (b = 0.62, p < 0.05) and expressed fear of the MtD patient contracting COVID-19 (b = 0.92, p < 0.05) were associated with more RMBs. Living in a rural community (b = -0.99,p < 0.05) and a history of COVID-19 testing (b = -2.14,p < 0.01) were associated with fewer RMBs. CONCLUSIONS: Our results suggest that during the COVID-19 pandemic, families affected by MtD have near universal adherence to basic RMBs. This may be motivated by fear of the severe morbidity associated with infection in MtD. Patients with frequent healthcare visits may be sicker and therefore take more precautions. Living in a rural community may also impact these behaviors. People who practice fewer RMBs may be more likely to seek testing. Our findings may generalize to other chronic diseases.

Interpersonal Correlates of Dementia Caregivers' Emotional Support Networks: Considering Family History.

Caregiving networks of individuals with Alzheimer's disease and related dementias (ADRD) are comprised of family and friends directly involved in caregiving activities and those supporting these activities. The purpose of this study was to investigate whether caregiving-related behaviors and interactions (i.e., uplift, malfeasance, and nonfeasance), kinship tie (i.e., friend, family), and family history of ADRD were associated with caregivers' emotional support networks. Seventy-one caregivers across 30 families provided information about 776 network members. Perceived emotional support and interactions representing uplift, malfeasance, and nonfeasance were assessed. Results indicated that uplift and friendship were associated with increased, whereas nonfeasance was associated with decreased, likelihood of perceived emotional support. Caregivers with a family history of ADRD were particularly more likely to report emotional support from friends and uplifting network members. Findings suggest the need for differential strategies based on families' prior caregiving experience to facilitate positive and minimize negative interactions within caregiving networks.

Healthcare system conversion to a biosimilar: Trials and tribulations.

PURPOSE: While biologic medications have transformed the care and management of millions of patients, they are a large financial strain on the healthcare system. Biosimilar medications present a great opportunity to improve care affordability. However, despite streamlined approval processes and the potential for cost savings, the acceptance and adoption of biosimilars have been slow. This descriptive report illustrates the preparation for, challenges of, and execution of an enterprise-wide biosimilar conversion within a large healthcare system. The 3 phases of biosimilar conversion utilized at our institution included selection of a biosimilar, pharmacy and therapeutics (P&T) committee approval, and implementation. SUMMARY: When selecting a biosimilar, clinical data, medication safety, cost, institutional cost savings, payer coverage, patient assistance programs, and additional patient services should be taken into consideration to ensure patient care is not affected. Understanding and endorsement of biosimilar use by physician leadership, care managers, and pharmacists are crucial before implementation. P&T committee approval with clear delineation of the patient population (naive vs experienced), disease states, and whether the biosimilar would be the preferred medication should be obtained. Transparent communication of clear expectations to patients and coordination with the information technology (IT), contracting, and supply chain departments are necessary before the go-live date. Contracting and IT implementations should ideally take potential changes in biosimilar adoption into consideration and have enough flexibility to account for these changes. Planned evaluations of patients' experiences with the change to the biosimilar should be incorporated as part of the implementation plan. CONCLUSION: The barriers to biosimilar adoption are plentiful. Careful planning, clear communication, and coordination with all affected disciplines can ensure successful biosimilar conversion.

Studying animal innovation at the individual level: A ratings-based assessment in capuchin monkeys (Sapajus [Cebus] sp.).

Large-scale studies of individual differences in innovative behavior among nonhuman animals are rare because of logistical difficulties associated with obtaining observational data on a large number of innovative individuals across multiple locations. Here, we take a different approach, using observer ratings to study individual differences in innovative behavior in 127 brown capuchin monkeys (Sapajus [Cebus] sp.) from 15 social groups and 7 facilities. Capuchins were reliably rated by 1 to 7 raters (mean 3.2 ± 1.6 raters/monkey) on a 7-point Likert scale for levels of innovative behavior, task motivation, sociality, and dominance. In a subsample, we demonstrate these ratings are valid: Rated innovation predicted performance on a learning task, rated motivation predicted participation in the task, rated dominance predicted social rank based on win/loss aggressive outcomes, and rated sociality predicted the time that monkeys spent in proximity to others. Across all 127 capuchins, individuals that were rated as being more innovative were significantly younger, more social, and more motivated to engage in tasks. Age, sociality, and task motivation all had independent effects on innovativeness, whereas sex, dominance, and group size were nonsignificant. Our findings are consistent with long-term behavioral observations of innovation in wild white-faced capuchins. Observer ratings may, therefore, be a valid tool for studies of animal innovation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Social and behavioral science at the forefront of genomics: Discovery, translation, and health equity.

This special issue highlights the unique role that social and behavioral science has to play at the forefront of genomics. Through the introduction of papers comprising this special issue, we outline priority research areas at the nexus of genomics and the social and behavioral sciences. These include: Discovery science; clinical and community translation, and equity, including engagement and inclusion of diverse populations in genomic science. We advocate for genomic discovery that considers social context, neural, cognitive, and behavioral endophenotypes, and that is grounded in social and behavioral science research and theory. Further, the social and behavioral sciences should play a leadership role in identifying best practices for effective clinical and community translation of genomic discoveries. Finally, inclusive research that engages diverse populations is necessary for genomic discovery and translation to benefit all. We also highlight ways that genomics can be a fruitful testbed for the development and refinement of social and behavioral science theory. Indeed, an expanded ecological lens that runs from genomes to society will be required to fully understand human behavior.

Exponential-Family Random Graph Models for Multi-Layer Networks.

Multi-layer networks arise when more than one type of relation is observed on a common set of actors. Modeling such networks within the exponential-family random graph (ERG) framework has been previously limited to special cases and, in particular, to dependence arising from just two layers. Extensions to ERGMs are introduced to address these limitations: Conway-Maxwell-Binomial distribution to model the marginal dependence among multiple layers; a "layer logic" language to translate familiar ERGM effects to substantively meaningful interactions of observed layers; and nondegenerate triadic and degree effects. The developments are demonstrated on two previously published datasets.

Primary Caregivers in a Network Context.

OBJECTIVES: Caregiving to individuals affected by Alzheimer's disease and related dementia (ADRD) is a family-systems process where tasks are distributed between multiple caregivers in a network. We evaluate the extent to which multiple network members nominate one another as filling primary caregiver (PCG) roles and factors associated with nomination. METHOD: Data come from the Caregiving Roles and Expectations Networks project, which aimed to characterize the caregiving networks of families affected by ADRD. All persons affected by ADRD were either full-time residents in residential care facilities or community-dwelling adult day-care participants. Generalized Poisson regression was used to model the count of incoming PCG nominations of each network member. RESULTS: On average, there were multiple network members identified as PCGs across different network contexts. Network members who were perceived to perform essential caregiving tasks, such as making decisions on behalf of and spending time with the care recipient, received more primary caregiving nominations from their network peers, adjusting for personal attributes, and the context of care. DISCUSSION: Having multiple PCGs in a network may result in lack of consensus in who fills those roles, potentially putting families at risk for interpersonal conflicts. Future work aimed at intervention development should fully assess the social contexts surrounding caregiving processes in order to better understand how network composition might impact outcomes.

The structure of emotional support networks in families affected by Lynch syndrome.

Genetic risk is particularly salient for families and testing for genetic conditions is necessarily a family-level process. Thus, risk for genetic disease represents a collective stressor shared by family members. According to communal coping theory, families may adapt to such risk vis-a-vis interpersonal exchange of support resources. We propose that communal coping is operationalized through the pattern of supportive relationships observed between family members. In this study, we take a social network perspective to map communal coping mechanisms to their underlying social interactions and include those who declined testing or were not at risk for Lynch Syndrome. Specifically, we examine the exchange of emotional support resources in families at risk of Lynch Syndrome, a dominantly inherited cancer susceptibility syndrome. Our results show that emotional support resources depend on the testing-status of individual family members and are not limited to the bounds of the family. Network members from within and outside the family system are an important coping resource in this patient population. This work illustrates how social network approaches can be used to test structural hypotheses related to communal coping within a broader system and identifies structural features that characterize coping processes in families affected by Lynch Syndrome.

Intergenerational exchange of healthful eating encouragement: Consideration of family ancestry and disease history.

INTRODUCTION: Improving diet is a prime target for the prevention and management of chronic disease. The communal coping model suggests that families can mitigate shared risk of chronic disease through encouragement of healthful eating, eliciting preventive behaviors. METHOD: Using network data from 69 Australian families across three ancestry groups (Anglo, Italian, and Asian) with varied family health histories, the present study applied social network analysis to identify patterns of intergenerational encouragement of healthful eating behavior within families, and assess whether patterns varied by family ancestry or disease density. RESULTS: Findings indicated variation in patterns of health encouragement by ancestry such that Asian-Australian families were most distinct from the other ancestry groups. While there was no main effect of familial disease history, it moderated the effect of Italian ancestry on intergenerational encouragement patterns. DISCUSSION: These results provide important context for future family based interventions that leverage normative patterns of intergenerational exchange of encouragement or aim to modify such patterns in an effort to improve family health. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A Bayesian hierarchical logistic regression model of multiple informant family health histories.

BACKGROUND: Family health history (FHH) inherently involves collecting proxy reports of health statuses of related family members. Traditionally, such information has been collected from a single informant. More recently, research has suggested that a multiple informant approach to collecting FHH results in improved individual risk assessments. Likewise, recent work has emphasized the importance of incorporating health-related behaviors into FHH-based risk calculations. Integrating both multiple accounts of FHH with behavioral information on family members represents a significant methodological challenge as such FHH data is hierarchical in nature and arises from potentially error-prone processes. METHODS: In this paper, we introduce a statistical model that addresses these challenges using informative priors for background variation in disease prevalence and the effect of other, potentially correlated, variables while accounting for the nested structure of these data. Our empirical example is drawn from previously published data on families with a history of diabetes. RESULTS: The results of the comparative model assessment suggest that simply accounting for the structured nature of multiple informant FHH data improves classification accuracy over the baseline and that incorporating family member health-related behavioral information into the model is preferred over alternative specifications. CONCLUSIONS: The proposed modelling framework is a flexible solution to integrate multiple informant FHH for risk prediction purposes.

Using hospital administrative data to infer patient-patient contact via the consistent co-presence algorithm.

In health care settings, patients who are physically proximate to other patients (co-presence) for a meaningful amount of time may have differential health outcomes depending on who they are in contact with. How to best measure this co-presence, however is an open question and previous approaches have limitations that may make them inappropriate for complex health care settings. Here, we introduce a novel method which we term "consistent co-presence", that implicitly models the many complexities of patient scheduling and movement through a hospital by randomly perturbing the timing of patients' entry time into the health care system. This algorithm generates networks that can be employed in models of patient outcomes, such as 1-year mortality, and are preferred over previously established alternative algorithms from a model comparison perspective. These results indicate that consistent co-presence retains meaningful information about patient-patient interaction, which may affect outcomes relevant to health care practice. Furthermore, the generalizabiity of this approach allows it to be applied to a wide variety of complex systems.

Genetic, Psychological, and Personal Network Factors Associated With Changes in Binge Drinking Over 2 Years Among Mexican Heritage Adolescents in the USA.

Background: Despite prevalent binge drinking and alcohol-dependent symptoms among Hispanics, few studies have examined how multidimensional factors influence Hispanic adolescents' binge drinking. Purpose This study examines the effects of genetic, psychological, and social network factors on binge drinking over time among Mexican heritage adolescents in the USA and whether there are correlations among genetic variants that are associated with binge drinking and psychological and network characteristics. Methods: Mexican heritage adolescents (n = 731) participated in a longitudinal study, which included genetic testing at baseline, alcohol use assessments at first and second follow-ups, and questionnaires on sensation seeking, impulsivity, and peer and family network characteristics at second follow-up. Logistic regression and Spearman correlation analyses were performed. Results: After adjusting for demographic characteristics, underlying genetic clustering, and binge drinking at first follow-up, two genetic variants on tryptophan hydroxylase 2 (TPH2; rs17110451, rs7963717), sensation seeking and impulsivity, and having a greater fraction of peers who drink or encourage drinking alcohol were associated with greater risk whereas another genetic variant on TPH2 (rs11178999) and having a greater fraction of close family relationships were associated with reduced risk for binge drinking at second follow-up. Genetic variants in TPH1 (rs591556) were associated with sensation seeking and impulsivity, while genetic variants in TPH2 (rs17110451) were associated with the fraction of drinkers in family. Conclusions: Results reveal that genetic variants in the serotonin pathway, behavioral disinhibition traits, and social networks exert joint influences on binge drinking in Mexican heritage adolescents in the USA.

Modeling Dynamic Food Choice Processes to Understand Dietary Intervention Effects.

Background: Meal construction is largely governed by nonconscious and habit-based processes that can be represented as a collection of in dividual, micro-level food choices that eventually give rise to a final plate. Despite this, dietary behavior intervention research rarely captures these micro-level food choice processes, instead measuring outcomes at aggregated levels. This is due in part to a dearth of analytic techniques to model these dynamic time-series events. Purpose: The current article addresses this limitation by applying a generalization of the relational event framework to model micro-level food choice behavior following an educational intervention. Method: Relational event modeling was used to model the food choices that 221 mothers made for their child following receipt of an information-based intervention. Participants were randomized to receive either (a) control information; (b) childhood obesity risk information; (c) childhood obesity risk information plus a personalized family history-based risk estimate for their child. Participants then made food choices for their child in a virtual reality-based food buffet simulation. Results: Micro-level aspects of the built environment, such as the ordering of each food in the buffet, were influential. Other dynamic processes such as choice inertia also influenced food selection. Among participants receiving the strongest intervention condition, choice inertia decreased and the overall rate of food selection increased. Conclusions: Modeling food selection processes can elucidate the points at which interventions exert their influence. Researchers can leverage these findings to gain insight into nonconscious and uncontrollable aspects of food selection that influence dietary outcomes, which can ultimately improve the design of dietary interventions.

Developing Shared Appraisals of Diabetes Risk Through Family Health History Feedback: The Case of Mexican-Heritage Families.

Background: Collecting complete and accurate family health history is critical to preventing type 2 diabetes. Purpose: We seek to identify the optimal risk feedback approach that facilitates risk communication between parents and their adult children and helps them develop shared appraisals of family history of type 2 diabetes. Methods: In a sample of parent-adult child dyads from 125 Mexican-heritage families residing in Houston, Texas, we examine change in parent-child dyadic (dis)agreement with respect to their shared family health history from baseline to 10 months after receipt of risk feedback generated by Family Healthware. A 2 × 2 factorial design is applied to test how the recipient (one parent or all family members) and the content (risk assessment with or without behavioral recommendations) of the feedback affect (dis)agreement through interpersonal ties, particularly dyadic risk communication. Results: Providing risk assessment without behavioral recommendations to the parent, but not the adult child, shifts the dyads toward agreement (relative risk ratio [RRR]= 1.78, 95% confidence interval [CI] [1.18-2.67]), by activating reciprocal risk communication between parents and children (RRR =2.70, 95% CI [1.81-4.03]). Dyads with close interpersonal ties are more likely to shift toward agreement (RRR = 3.09, 95% CI [1.89-5.07]). Conclusion: Programs aimed at improving family health history knowledge and accuracy of reports should tailor risk feedback strategically for better intervention effect and leverage a network approach in disease prevention among at-risk minority and/or immigrant populations. Trial Registration Number: NCT00469339.

Racial differences in family health history knowledge of type 2 diabetes: exploring the role of interpersonal mechanisms.

Collecting complete and accurate family health history is critical to preventing type 2 diabetes. Whether there are any racial difference in family health history knowledge of type 2 diabetes and whether such differences are related to interpersonal mechanisms remain unclear. We seek to identify the interpersonal mechanisms that give rise to discrepancies in family health history knowledge of type 2 diabetes in families of different racial backgrounds. We analyze informant-dyad consensus with respect to shared family history of type 2 diabetes in 127 informants of 45 families in the greater Cincinnati area (white: 28 families, 78 informants; black/African-American: 17 families, 49 informants). We first document a difference in informant-dyad consensus by race and then test whether this difference can be explained by interpersonal ties, particularly health communication. Compared with their white counterparts, dyads in families of black/African-American background are more likely to have an uneven distribution of knowledge, with one informant knowing and the other not knowing his/her family health history. The racial difference is explained by dyads in families of black/African-American background having fewer reciprocal health communication ties. While associated with informant-dyad consensus, education, kinship ties, and closeness ties do not account for the observed racial difference. Activating health communication is a key to improving family health history knowledge, especially in families of black/African-American background. Researchers and clinicians should leverage communication ties in the family network for better collection and utilization of family health history in preventive services.

Multi-relational measurement for latent construct networks.

Multiple item scales have long been used to measure latent constructs on individual-level data. This is appropriate when an otherwise unobserved construct is indirectly measured by combining observable correlated characteristics that are thought to measure slightly different dimensions of that construct. Network data, which consist of observations on the relationships between a set of actors, however, are typically drawn from single-relation measurements. While this approach is sufficient for learning about discrete relations (communication, coauthorship, etc.), multi-item measurement of extemporaneous valued relationships, such as cohesion and conflict, may be of common interest in psychology and related sciences. In this article, we evaluate the use of multirelational network measurement in inferring valued latent construct networks. In particular, we present a psychometric framework for developing multirelational measures of latent construct networks, evaluating their reliability and construct validity, and identification of appropriate scaling approaches for these construct-level networks. (PsycINFO Database Record