The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.

Force fields are a key component of physics-based molecular modeling, describing the energies and forces in a molecular system as a function of the positions of the atoms and molecules involved. Here, we provide a review and scientific status report on the work of the Open Force Field (OpenFF) Initiative, which focuses on the science, infrastructure and data required to build the next generation of biomolecular force fields. We introduce the OpenFF Initiative and the related OpenFF Consortium, describe its approach to force field development and software, and discuss accomplishments to date as well as future plans. OpenFF releases both software and data under open and permissive licensing agreements to enable rapid application, validation, extension, and modification of its force fields and software tools. We discuss lessons learned to date in this new approach to force field development. We also highlight ways that other force field researchers can get involved, as well as some recent successes of outside researchers taking advantage of OpenFF tools and data.

Understanding 'error' in the forensic sciences: A primer.

This paper distils seven key lessons about 'error' from a collaborative webinar series between practitioners at Victoria Police Forensic Services Department and academics. It aims to provide the common understanding of error necessary to foster interdisciplinary dialogue, collaboration and research. The lessons underscore the inevitability, complexity and subjectivity of error, as well as opportunities for learning and growth. Ultimately, we argue that error can be a potent tool for continuous improvement and accountability, enhancing the reliability of forensic sciences and public trust. It is hoped the shared understanding provided by this paper will support future initiatives and funding for collaborative developments in this vital domain.

Algorithms to identify radiotherapy intent in unresected non-metastatic non-small-cell lung cancer: an I-O Optimise analysis.

This study aimed to develop and evaluate the performance of algorithms for identifying radiotherapy (RT) treatment intent in real-world data from patients with non-metastatic non-small-cell lung cancer (NSCLC). Using data from IPO-Porto hospital (Portugal) and the REAL-Oncology database (England), three algorithms were developed based on available RT information (#1: RT duration, #2: RT duration and type, #3: RT dose) and tested versus reference datasets. Study results showed that all three algorithms had good overall accuracy (91-100%) for patients receiving RT plus systemic anticancer therapy (SACT) and algorithms #2 and #3 also had good accuracy (>99%) for patients receiving RT alone. These algorithms could help classify treatment intent in patients with NSCLC receiving RT with or without SACT in real-world settings where intent information is missing/incomplete.

One objective of many real-world studies is to evaluate which cancer treatments are given during routine visits to hospitals or cancer centers and assess how well the treatments work. This objective is easier to achieve when we know the reason for the cancer treatment (known as treatment intent), but doctors often do not record whether the treatment was given to actively treat the cancer (curative intent) or to slow down a cancer's growth or control symptoms in people with incurable cancer (palliative intent). In this article, we describe the development and testing of algorithms to determine treatment intent in people with lung cancer given radiotherapy (the controlled application of radiation to cancer cells). These algorithms involve following a step-by-step process based on three key questions: for how long was the radiotherapy given? what type of radiotherapy was given? and what dose of radiotherapy was given? Answers were then tested true or false against reference answers provided by doctors who know a lot about radiotherapy. We found that all three algorithms were able to determine the correct treatment intent in more than nine out of ten people given radiotherapy with systemic anticancer therapy (e.g., chemotherapy) and two algorithms were able to determine the correct treatment intent in more than nine out of ten people given radiotherapy alone. These algorithms may be helpful in determining treatment intent in people given radiotherapy to treat lung cancer in real-world settings, and may help us learn more about real-world lung cancer treatment.

"Notification! You May Have Cancer." Could Smartphones and Wearables Help Detect Cancer Early?

This viewpoint paper considers the authors' perspectives on the potential role of smartphones, wearables, and other technologies in the diagnosis of cancer. We believe that these technologies could be valuable additions in the pursuit of early cancer diagnosis, as they offer solutions to the timely detection of signals or symptoms and monitoring of subtle changes in behavior that may otherwise be missed. In addition to signal detection, technologies could assist symptom interpretation and guide and facilitate access to health care. This paper aims to provide an overview of the scientific rationale as to why these technologies could be valuable for early cancer detection, as well as outline the next steps for research and development to drive investigation into the potential for smartphones and wearables in this context and optimize implementation. We draw attention to potential barriers to successful implementation, including the difficulty of the development of signals and sensors with sufficient utility and accuracy through robust research with the target group. There are regulatory challenges; the potential for innovations to exacerbate inequalities; and questions surrounding acceptability, uptake, and correct use by the intended target group and health care practitioners. Finally, there is potential for unintended consequences on individuals and health care services including unnecessary anxiety, increased symptom burden, overinvestigation, and inappropriate use of health care resources.

Emergency department involvement in the diagnosis of cancer among older adults: a SEER-Medicare study.

BACKGROUND: Internationally, 20% to 50% of cancer is diagnosed through emergency presentation, which is associated with lower survival, poor patient experience, and socioeconomic disparities, but population-based evidence about emergency diagnosis in the United States is limited. We estimated emergency department (ED) involvement in the diagnosis of cancer in a nationally representative population of older US adults, and its association with sociodemographic, clinical, and tumor characteristics. METHODS: We analyzed Surveillance, Epidemiology, and End Results Program-Medicare data for Medicare beneficiaries (≥66 years old) with a diagnosis of female breast, colorectal, lung, and prostate cancers (2008-2017), defining their earliest cancer-related claim as their index date, and patients who visited the ED 0 to 30 days before their index date to have "ED involvement" in their diagnosis, with stratification as 0 to 7 or 8 to 30 days. We estimated covariate-adjusted associations of patient age, sex, race and ethnicity, marital status, comorbidity score, tumor stage, year of diagnosis, rurality, and census-tract poverty with ED involvement using modified Poisson regression. RESULTS: Among 614 748 patients, 23% had ED involvement, with 18% visiting the ED in the 0 to 7 days before their index date. This rate varied greatly by tumor site, with breast cancer at 8%, colorectal cancer at 39%, lung cancer at 40%, and prostate cancer at 7%. In adjusted models, older age, female sex, non-Hispanic Black and Native Hawaiian or Other Pacific Islander race, being unmarried, recent year of diagnosis, later-stage disease, comorbidities, and poverty were associated with ED involvement. CONCLUSIONS: The ED may be involved in the initial identification of cancer for 1 in 5 patients. Earlier, system-level identification of cancer in non-ED settings should be prioritized, especially among underserved populations.

Self-scheduling Medical Visits in a Multispecialty, Multisite Medical Practice: Complexity, Challenges, and Successes.

Background: Self-scheduling of medical visits is becoming more common but the complexity of applying multiple requirements for self-scheduling has hampered implementation. Mayo Clinic implemented self-scheduling in 2019 and has been increasing its portfolio of self-schedulable visits since then. Our aim was to show measures quantifying the complexity associated with medical visit scheduling and to describe how opportunities and challenges of scheduling complexity apply in self-scheduling. Methods: We examined scheduled visits from January 1, 2022, through August 24, 2023. For seven visit categories, we counted all unique visit types that were scheduled, for both staff-scheduled and self-scheduled. We examined counts of self-scheduled visit types to identify those with highest uptake during the study period. Results: There were 9555 unique visit types associated with 20.8 M (million) completed visits. Self-scheduled visit types accounted for 4.0% (838,592/20,769,699) of the completed total visits. Of seven visit categories, self-scheduled established patient visits, testing visits, and procedure visits accounted for 93.5% (784,375/838,592) of all self-scheduled visits. Established patient visits in primary care (10 visit types) accounted for 273,007 (32.6%) of all self-scheduled visits. Testing visits (blood and urine testing, 2 visit types) accounted for 183,870 (21.9%) of all self-scheduled visits. Procedure visits for screening mammograms, bone mineral density, and immunizations (8 visit types) accounted for 147,358 (17.6%) of all self-scheduled visits. Conclusion: Large numbers of unique visit types comprise a major challenge for self-scheduling. Some visit types are more suitable for self-scheduling. Guideline-based procedure visits such as screening mammograms, bone mineral density exams, and immunizations are examples of visits that have high volumes and can be standardized for self-scheduling. Established patient visits and laboratory testing visits also can be standardized for self-scheduling. Despite the successes, there remain thousands of specific visit types that may need some staff-scheduler intervention to properly schedule.

Self-scheduling in a Large Multispecialty and Multisite Clinic: A Retrospective, Longitudinal Examination of Multiple Self-Scheduled Visit Types.

Background: Self-scheduling of medical visits is becoming available at many medical institutions. We aimed to examine the self-scheduled visit counts and rate of growth of self-scheduled visits in a multispecialty practice. Methods: For 85 weeks extending from January 1, 2022 through August 24, 2023, we examined self-scheduled visit counts for over 1500 self-scheduled visit types. We compared completed self-scheduled visit counts to all scheduled completed visit counts for the same visit types. We collected counts of the most frequently self-scheduled visit types for each week and examined the change over time. We also determined the proportion that each visit type was self-scheduled. Results: There were 20,769 699 completed visits during the course of the study that met the criteria for inclusion. Self-scheduled visits accounted for 4.0% of all completed visits (838 592/20,769 699). Over the 85-week span, self-scheduled visits rose from 3.0% to 5.3% of the total. There were 1887 unique visit types that were associated with completed visits. There were just 6 appointment visit types of the total 1887 self-scheduled visit types that accounted for 50.7% of the total 838 592 self-scheduled visits. Those 6 visit types were a lab blood test visit (19.5%, 163 K visits), two Family Medicine office visit types (13.0%, 109 K visits), a screening mammogram visit type (6.6%, 55 K visits), a scheduled express care visit type (6%, 50 K visits) and a COVID immunization visit type (5.7%, 48 K visits). Twenty-one visit types that were self-scheduled accounted for 75% of the total self-scheduled visits. Four seasonal visits, accounting for 10.6% of the total self-scheduled visits, were responsible for almost all the non-linear change in self-scheduling. Conclusion: Self-scheduling accounted for a small but growing percent of all outpatient scheduled visits in a multispecialty, multisite practice. A wide range of visit types can be successfully self-scheduled.

Long-Circulating Vasoactive 1,18-Octadecanedioic Acid-Terlipressin Conjugate.

Hepatorenal syndrome (HRS) is a life-threatening complication of end-stage liver disease first reported over a century ago, but its management still poses an unmet challenge. A therapeutic agent found to stabilize the condition is a short cyclic peptide, vasopressin analogue, terlipressin (TP). While TP is commonly prescribed for HRS patients in most parts of the world, it was only recently approved for use in the United States. TP exhibits short circulation half-lives and adverse side effects associated with the dose required. Herein, we present a 1,18-octadecanedioic acid (ODDA) conjugate of the cyclic peptide (ODDA-TP), which enables noncovalent binding to serum albumin via native fatty acid binding modes. ODDA-TP is demonstrated to outperform TP alone in studies including in vitro cellular receptor activation, stability in plasma, pharmacokinetics, and performance in vivo in rats. Specifically, ODDA-TP had an elimination half-life 20 times that of TP alone while exhibiting a superior safety profile.

FDA Approval Summary: Fruquintinib for the Treatment of Refractory Metastatic Colorectal Cancer.

On November 8, 2023, the FDA approved fruquintinib, an inhibitor of vascular endothelial growth factor receptors (VEGFR)-1, -2, and -3, for the treatment of patients with metastatic colorectal cancer (mCRC) who have been previously treated with fluoropyrimidine­, oxaliplatin­, and irinotecan­based chemotherapy, an anti­VEGF therapy, and, if RAS wild­type and medically appropriate, an anti EGFR therapy. Approval was based on Study FRESCO-2, a globally-conducted, double-blind, placebo-controlled randomized trial. The primary endpoint was overall survival (OS). The key secondary endpoint was progression-free survival (PFS). A total of 691 patients were randomized (461 and 230 into the fruquintinib and placebo arms, respectively). Fruquintinib provided a statistically significant improvement in OS with a hazard ratio (HR) of 0.66 (95% CI: 0.55, 0.80; p<0.001). The median OS was 7.4 months (95% CI: 6.7, 8.2) in the fruquintinib arm and 4.8 months (95% CI: 4.0, 5.8) for the placebo arm. Adverse events observed were generally consistent with the known safety profile associated with inhibition of the VEGFR. The results of FRESCO-2 were supported by the FRESCO study, a double-blind, single country, placebo-controlled, randomized trial in patients with refractory mCRC who have been previously treated with fluoropyrimidine­, oxaliplatin­, and irinotecan­based chemotherapy. In FRESCO, the OS HR was 0.65 (95% CI: 0.51, 0.83; p<0.001). FDA concluded that the totality of the evidence from FRESCO-2 and FRESCO supported an indication for patients with mCRC with prior treatment with fluoropyrimidine, oxaliplatin-, and irinotecan-based chemotherapy, an anti-VEGF biological therapy, and if RAS wild­type and medically appropriate, an anti-EGFR therapy.

Helping parents know when to seek help for an acutely ill child: Evidence based co-development of a mobile phone app using complex intervention methodology.

BACKGROUND: Acute illness accounts for the majority of episodes of illness in children under five years of age and is the age group with the highest consultation rate in general practice in the UK. The number of children presenting to emergency care is also steadily increasing, having risen beyond pre-pandemic numbers. Such high, and increasing, rates of consultation have prompted concerns about parents' level of knowledge and confidence in caring for their children when they are ill, and particularly when and how to seek help appropriately. AIM: The ASK SNIFF collaboration research programme identified parents' need for accurate and accessible information to help them know when to seek help for a sick child in 2010. This paper presents the resulting programme of research which aimed to co-develop an evidence-based safety netting intervention (mobile app) to help parents know when to seek help for an acutely ill child under the age of five years in the UK. METHODS: Our programme used a collaborative six step process with 147 parent and 324 health professional participants over a period of six years including: scoping existing interventions, systematic review, qualitative research, video capture, content identification and development, consensus methodology, parent and expert clinical review. RESULTS: Our programme has produced evidence-based content for an app supported by video clips. Our collaborative approach has supported every stage of our work, ensuring that the end result reflects the experiences, perspectives and expressed needs of parents and the clinicians they consult. CONCLUSION: We have not found any other resource which has used this type of approach, which may explain why there is no published evaluation data demonstrating the impact of existing UK resources. Future mobile apps should be designed and developed with the service users for whom they are intended.

Evaluating the Acceptability and Feasibility of Collecting Passive Smartphone Data to Estimate Psychological Functioning in U.S. Service Members and Veterans: A Pilot Study.

INTRODUCTION: This study investigated the acceptability and feasibility of digital phenotyping in a military sample with a history of traumatic brain injury and co-occurring psychological and cognitive symptoms. The first aim was to evaluate the acceptability of digital phenotyping by (1a) quantifying the proportion of participants willing to download the app and rates of dropout and app discontinuation and (1b) reviewing the stated reasons for both refusing and discontinuing use of the app. The second aim was to investigate technical feasibility by (2a) characterizing the amount and frequency of transferred data and (2b) documenting technical challenges. Exploratory aim 3 sought to leverage data on phone and keyboard interactions to predict if a participant (a) is depressed and (b) has depression that improves over the course of the study. MATERIALS AND METHODS: A passive digital phenotyping app (Mindstrong Discovery) functioned in the background of the participants' smartphones and passively collected phone usage and typing kinematics data. RESULTS: Fifteen out of 16 participants (93.8%) consented to install the app on their personal smartphone devices. Four participants (26.7%) discontinued the use of the app partway through the study, primarily because of keyboard usability and technical issues. Fourteen out of 15 participants (93.3%) had at least one data transfer, and the median number of days with data was 40 out of a possible 57 days. The exploratory machine learning models predicting depression status and improvement in depression performed better than chance. CONCLUSIONS: The findings of this pilot study suggest that digital phenotyping is acceptable and feasible in a military sample and provides support for future larger investigations of this technology.

Recommendation endpoints and safety of an online self-triage for depression symptoms.

INTRODUCTION: Online symptom checkers are a way to address patient concerns and potentially offload a burdened healthcare system. However, safety outcomes of self-triage are unknown, so we reviewed triage recommendations and outcomes of our institution's depression symptom checker. METHODS: We examined endpoint recommendations and follow-up encounters seven days afterward during 2 December 2021 to 13 December 2022. Patients with an emergency department visit or hospitalization within seven days of self-triaging had a manual review of the electronic health record to determine if the visit was related to depression, suicidal ideation, or suicide attempt. Charts were reviewed for deaths within seven days of self-triage. RESULTS: There were 287 unique encounters from 263 unique patients. In 86.1% (247/287), the endpoint was an instruction to call nurse triage; in 3.1% of encounters (9/287), instruction was to seek emergency care. Only 20.2% (58/287) followed the recommendations given. Of the 229 patients that did not follow the endpoint recommendations, 121 (52.8%) had some type of follow-up within seven days. Nearly 11% (31/287) were triaged to endpoints not requiring urgent contact and 9.1% (26/287) to an endpoint that would not need any healthcare team input. No patients died in the study period. CONCLUSIONS: Most patients did not follow the recommendations for follow-up care although ultimately most patients did receive care within seven days. Self-triage appears to appropriately sort patients with depressed mood to emergency care. On-line self-triaging tools for depression have the potential to safely offload some work from clinic personnel.

Cognitive and neuroscientific perspectives of healthy ageing.

With dementia incidence projected to escalate significantly within the next 25 years, the United Nations declared 2021-2030 the Decade of Healthy Ageing, emphasising cognition as a crucial element. As a leading discipline in cognition and ageing research, psychology is well-equipped to offer insights for translational research, clinical practice, and policy-making. In this comprehensive review, we discuss the current state of knowledge on age-related changes in cognition and psychological health. We discuss cognitive changes during ageing, including (a) heterogeneity in the rate, trajectory, and characteristics of decline experienced by older adults, (b) the role of cognitive reserve in age-related cognitive decline, and (c) the potential for cognitive training to slow this decline. We also examine ageing and cognition through multiple theoretical perspectives. We highlight critical unresolved issues, such as the disparate implications of subjective versus objective measures of cognitive decline and the insufficient evaluation of cognitive training programs. We suggest future research directions, and emphasise interdisciplinary collaboration to create a more comprehensive understanding of the factors that modulate cognitive ageing.

Early, precise, and safe clinical evaluation of the pharmacodynamic effects of novel agents in the intact human tumor microenvironment.

Introduction: Drug development is systemically inefficient. Research and development costs for novel therapeutics average hundreds of millions to billions of dollars, with the overall likelihood of approval estimated to be as low as 6.7% for oncology drugs. Over half of these failures are due to a lack of drug efficacy. This pervasive and repeated low rate of success exemplifies how preclinical models fail to adequately replicate the complexity and heterogeneity of human cancer. Therefore, new methods of evaluation, early in the development trajectory, are essential both to rule-in and rule-out novel agents with more rigor and speed, but also to spare clinical trial patients from the potentially toxic sequelae (high risk) of testing investigational agents that have a low likelihood of producing a response (low benefit). Methods: The clinical in vivo oncology (CIVO®) platform was designed to change this drug development paradigm. CIVO precisely delivers microdose quantities of up to 8 drugs or combinations directly into patient tumors 4-96 h prior to planned surgical resection. Resected tissue is then analyzed for responses at each site of intratumoral drug exposure. Results: To date, CIVO has been used safely in 6 clinical trials, including 68 subjects, with 5 investigational and 17 approved agents. Resected tissues were analyzed initially using immunohistochemistry and in situ hybridization assays (115 biomarkers). As technology advanced, the platform was paired with spatial biology analysis platforms, to successfully track anti-neoplastic and immune-modulating activity of the injected agents in the intact tumor microenvironment. Discussion: Herein we provide a report of the use of CIVO technology in patients, a depiction of the robust analysis methods enabled by this platform, and a description of the operational and regulatory mechanisms used to deploy this approach in synergistic partnership with pharmaceutical partners. We further detail how use of the CIVO platform is a clinically safe and scientifically precise alternative or complement to preclinical efficacy modeling, with outputs that inform, streamline, and de-risk drug development.

Pharmacokinetic models for first-in-human dose selection of immune-activating products in oncology.

Pharmacokinetic (PK) models are increasingly submitted to the FDA to support first-in-human (FIH) dose selection of immune-oncology products. To examine whether a simple PK modeling (SPM) using clearance for scaling was acceptable for dose estimation, FIH(SPM) doses were computed and compared to doses that were safely administered to patients. We concluded that the SPM approach is acceptable in FIH dose estimation, but the variables should be carefully selected for CD3 constructs. For CD3 constructs, use of 60 kg BWh, a clearance exponent of 0.75, and a targeted plasma concentration based on relevant and/or sensitive activity assays was an acceptable approach for FIH dose selection; use of 0.85 as the scaling factor is questionable at this time as it resulted in a FIH dose that was too close to the AHD for one product (7%). Immune activating mAbs were not sensitive to changes in the clearance exponent (0.75-0.85) or body weight (60-70 kg). For PD-1/PD-L1 mAbs, using products' in vitro EC50 in the model resulted in suboptimal FIH doses and clinical data of closely related products informed FIH dose selection. PK models submitted by sponsors were diverse in methods, assumptions, and variables, and the resulting FIH doses were not always optimal.

Rare SNP in the HELB gene interferes with RPA interaction and cellular function of HELB.

HELB is a human helicase involved in initiation of DNA replication, the replication stress response, and regulation of double-strand DNA break repair. rs75770066 is a rare SNP in the HELB gene that affects age at natural menopause. rs75770066 results in a D506G substitution in an acidic patch within the 1A domain of the helicase that is known to interact with RPA. We found that this amino acid change dramatically impairs the cellular function of HELB. D506G-HELB exhibits impaired interaction with RPA, which likely results in the effects of rs75770066 as this reduces recruitment of HELB to sites of DNA damage. Reduced recruitment of D506G-HELB to double-strand DNA breaks and the concomitant increase in homologous recombination likely alters the levels of meiotic recombination, which affects the viability of gametes. Because menopause occurs when oocyte levels drop below a minimum threshold, altered repair of meiotic double-stranded DNA breaks has the potential to directly affect the age at natural menopause.

The effect of fingerprint expertise on visual short-term memory.

Expert fingerprint examiners demonstrate impressive feats of memory that may support their accuracy when making high-stakes identification decisions. Understanding the interplay between expertise and memory is therefore critical. Across two experiments, we tested fingerprint examiners and novices on their visual short-term memory for fingerprints. In Experiment 1, experts showed substantially higher memory performance compared to novices for fingerprints from their domain of expertise. In Experiment 2, we manipulated print distinctiveness and found that while both groups benefited from distinctive prints, experts still outperformed novices. This indicates that beyond stimulus qualities, expertise itself enhances short-term memory, likely through more effective organisational processing and sensitivity to meaningful patterns. Taken together, these findings shed light on the cognitive mechanisms that may explain fingerprint examiners' superior memory performance within their domain of expertise. They further suggest that training to improve memory for diverse fingerprints could practically boost examiner performance. Given the high-stakes nature of forensic identification, characterising psychological processes like memory that potentially contribute to examiner accuracy has important theoretical and practical implications.

Challenges to mapping and defining m6A function in viral RNA.

Viral RNA molecules contain multiple layers of regulatory information. This includes features beyond the primary sequence, such as RNA structures and RNA modifications, including N6-methyladenosine (m6A). Many recent studies have identified the presence and location of m6A in viral RNA and have found diverse regulatory roles for this modification during viral infection. However, to date, viral m6A mapping strategies have limitations that prevent a complete understanding of the function of m6A on individual viral RNA molecules. While m6A sites have been profiled on bulk RNA from many viruses, the resulting m6A maps of viral RNAs described to date present a composite picture of m6A across viral RNA molecules in the infected cell. Thus, for most viruses, it is unknown if unique viral m6A profiles exist throughout infection, nor if they regulate specific viral life cycle stages. Here, we describe several challenges to defining the function of m6A in viral RNA molecules and provide a framework for future studies to help in the understanding of how m6A regulates viral infection.

A guide to measuring expert performance in forensic pattern matching.

Decisions in forensic science are often binary. A firearms expert must decide whether a bullet was fired from a particular gun or not. A face comparison expert must decide whether a photograph matches a suspect or not. A fingerprint examiner must decide whether a crime scene fingerprint belongs to a suspect or not. Researchers who study these decisions have therefore quantified expert performance using measurement models derived largely from signal detection theory. Here we demonstrate that the design and measurement choices researchers make can have a dramatic effect on the conclusions drawn about the performance of forensic examiners. We introduce several performance models - proportion correct, diagnosticity ratio, and parametric and non-parametric signal detection measures - and apply them to forensic decisions. We use data from expert and novice fingerprint comparison decisions along with a resampling method to demonstrate how experimental results can change as a function of the task, case materials, and measurement model chosen. We also graphically show how response bias, prevalence, inconclusive responses, floor and ceiling effects, case sampling, and number of trials might affect one's interpretation of expert performance in forensics. Finally, we discuss several considerations for experimental and diagnostic accuracy studies: (1) include an equal number of same-source and different-source trials; (2) record inconclusive responses separately from forced choices; (3) include a control comparison group; (4) counterbalance or randomly sample trials for each participant; and (5) present as many trials to participants as is practical.

Critical lessons from a pragmatic randomized trial of home-based COVID-19 testing in rural Native American and Latino communities.

PURPOSE: Native Americans and Latinos have higher COVID-19 infection and mortality rates and may have limited access to diagnostic testing. Home-based testing may improve access to care in rural and underserved populations. This study tests the effect of community health worker (CHW) support on accessibility, feasibility, and completion of COVID-19 home testing among Native American and Latino adults living on the Flathead Reservation in Montana and in Yakima Valley, Washington. METHODS: A two-arm, multisite, pragmatic randomized controlled trial was conducted using block randomization stratified by site and participant age. Active arm participants received CHW assistance with online COVID-19 test kit registration and virtual swabbing support. The passive arm participants received standard-of-care support from the kit vendor. Logistic regression modeled the association between study arm and test completion (primary outcome) and between study arm and test completion with return of valid test results (secondary outcome). Responses to posttest surveys and interviews were summarized using deductive thematic analysis. FINDINGS: Overall, 63% of participants (n = 268) completed COVID-19 tests, and 50% completed tests yielding a valid result. Active arm participants had higher odds of test completion (odds ratio: 1.66, 95% confidence interval [1.01, 2.75]). Differences were most pronounced among adults ≥60 years. Participants cited ease of use and not having to leave home as positive aspects, and transportation and mailing issues as negative aspects of home-based testing. CONCLUSIONS: CHW support led to higher COVID-19 test completion rates, particularly among older adults. Significant testing barriers included language, educational level, rurality, and test kit issues.