Web Application to Enable Online Social Interactions in a Parkinson Disease Risk Cohort: Feasibility Study and Social Network Analysis.

BACKGROUND: There is evidence that social interaction has an inverse association with the development of neurodegenerative diseases. PREDICT-Parkinson Disease (PREDICT-PD) is an online UK cohort study that stratifies participants for risk of future Parkinson disease (PD). OBJECTIVE: This study aims to explore the methodological approach and feasibility of assessing the digital social characteristics of people at risk of developing PD and their social capital within the PREDICT-PD platform, making hypotheses about the relationship between web-based social engagement and potential predictive risk indicators of PD. METHODS: A web-based application was built to enable social interaction through the PREDICT-PD portal. Feedback from existing members of the cohort was sought and informed the design of the pilot. Dedicated staff used weekly engagement activities, consisting of PD-related research, facts, and queries, to stimulate discussion. Data were collected by the hosting platform. We examined the pattern of connections generated over time through the cumulative number of posts and replies and ego networks using social network analysis. We used network metrics to describe the bonding, bridging, and linking of social capital among participants on the platform. Relevant demographic data and Parkinson risk scores (expressed as an odd 1:x) were analyzed using descriptive statistics. Regression analysis was conducted to estimate the relationship between risk scores (after log transformation) and network measures. RESULTS: Overall, 219 participants took part in a 4-month pilot forum embedded in the study website. In it, 200 people (n=80, 40% male and n=113, 57% female) connected in a large group, where most pairs of users could reach one another either directly or indirectly through other users. A total of 59% (20/34) of discussions were spontaneously started by participants. Participation was asynchronous, with some individuals acting as "brokers" between groups of discussions. As more participants joined the forum and connected to one another through online posts, distinct groups of connected users started to emerge. This pilot showed that a forum application within the cohort web platform was feasible and acceptable and fostered digital social interaction. Matching participants' web-based social engagement with previously collected data at individual level in the PREDICT-PD study was feasible, showing potential for future analyses correlating online network characteristics with the risk of PD over time, as well as testing digital social engagement as an intervention to modify the risk of developing neurodegenerative diseases. CONCLUSIONS: The results from the pilot suggest that an online forum can serve as an intervention to enhance social connectedness and investigate whether patterns of online engagement can impact the risk of developing PD through long-term follow-up. This highlights the potential of leveraging online platforms to study the role of social capital in moderating PD risk and underscores the feasibility of such approaches in future research or interventions.

Balancing best practice and reality in behavioral intervention development: A survey of principal investigators funded by the National Institutes of Health.

Preliminary studies play a prominent role in the development of large-scale behavioral interventions. Though recommendations exist to guide the execution and interpretation of preliminary studies, these assume optimal scenarios which may clash with realities faced by researchers. The purpose of this study was to explore how principal investigators (PIs) balance expectations when conducting preliminary studies. We surveyed PIs funded by the National Institutes of Health to conduct preliminary behavioral interventions between 2000 and 2020. Four hundred thirty-one PIs (19% response rate) completed the survey (November 2021 to January 2022, 72% female, mean 21 years post-terminal degree). Most PIs were aware of translational models and believed preliminary studies should precede larger trials but also believed a single preliminary study provided sufficient evidence to scale. When asked about the relative importance of preliminary efficacy (i.e. changes in outcomes) and feasibility (i.e. recruitment, acceptance/adherence) responses varied. Preliminary studies were perceived as necessary to successfully compete for research funding, but among PIs who had peer-reviewed federal-level grants applications (n = 343 [80%]), responses varied about what should be presented to secure funding. Confusion surrounding the definition of a successful, informative preliminary study poses a significant challenge when developing behavior interventions. This may be due to a mismatch between expectations surrounding preliminary studies and the realities of the research enterprise in which they are conducted. To improve the quality of preliminary studies and advance the field of behavioral interventions, additional funding opportunities, more transparent criteria in grant reviews, and additional training for grant reviewers are suggested.

Initial testing of behavioral interventions can provide valuable information about the methods of the intervention and whether it is effective. However, recommendations that provide researchers with guidance on how to best conduct pilot studies assume ideal circumstances. The mismatch between what can be realistically accomplished in a preliminary study, and what researchers expect from preliminary studies creates confusion. As a result, it is difficult for researchers to judge the quality, relevance, and potential of preliminary studies. This study suggests more research funding opportunities, clearer rules for reviewing grant applications, and more training for the people who review these applications could help improve preliminary studies and create more effective health behavior programs.

Artificial Intelligence and Technology Collaboratories: Innovating aging research and Alzheimer's care.

This perspective outlines the Artificial Intelligence and Technology Collaboratories (AITC) at Johns Hopkins University, University of Pennsylvania, and University of Massachusetts, highlighting their roles in developing AI-based technologies for older adult care, particularly targeting Alzheimer's disease (AD). These National Institute on Aging (NIA) centers foster collaboration among clinicians, gerontologists, ethicists, business professionals, and engineers to create AI solutions. Key activities include identifying technology needs, stakeholder engagement, training, mentoring, data integration, and navigating ethical challenges. The objective is to apply these innovations effectively in real-world scenarios, including in rural settings. In addition, the AITC focuses on developing best practices for AI application in the care of older adults, facilitating pilot studies, and addressing ethical concerns related to technology development for older adults with cognitive impairment, with the ultimate aim of improving the lives of older adults and their caregivers. HIGHLIGHTS: Addressing the complex needs of older adults with Alzheimer's disease (AD) requires a comprehensive approach, integrating medical and social support. Current gaps in training, techniques, tools, and expertise hinder uniform access across communities and health care settings. Artificial intelligence (AI) and digital technologies hold promise in transforming care for this demographic. Yet, transitioning these innovations from concept to marketable products presents significant challenges, often stalling promising advancements in the developmental phase. The Artificial Intelligence and Technology Collaboratories (AITC) program, funded by the National Institute on Aging (NIA), presents a viable model. These Collaboratories foster the development and implementation of AI methods and technologies through projects aimed at improving care for older Americans, particularly those with AD, and promote the sharing of best practices in AI and technology integration. Why Does This Matter? The National Institute on Aging (NIA) Artificial Intelligence and Technology Collaboratories (AITC) program's mission is to accelerate the adoption of artificial intelligence (AI) and new technologies for the betterment of older adults, especially those with dementia. By bridging scientific and technological expertise, fostering clinical and industry partnerships, and enhancing the sharing of best practices, this program can significantly improve the health and quality of life for older adults with Alzheimer's disease (AD).

Supporting physical activity through co-production in people with severe mental ill health (SPACES): protocol for a randomised controlled feasibility trial.

BACKGROUND: Severe mental ill health (SMI) includes schizophrenia, bipolar disorder and schizoaffective disorder and is associated with premature deaths when compared to people without SMI. Over 70% of those deaths are attributed to preventable health conditions, which have the potential to be positively affected by the adoption of healthy behaviours, such as physical activity. People with SMI are generally less active than those without and face unique barriers to being physically active. Physical activity interventions for those with SMI demonstrate promise, however, there are important questions remaining about the potential feasibility and acceptability of a physical activity intervention embedded within existing NHS pathways. METHOD: This is a two-arm multi-site randomised controlled feasibility trial, assessing the feasibility and acceptability of a co-produced physical activity intervention for a full-scale trial across geographically dispersed NHS mental health trusts in England. Participants will be randomly allocated via block, 1:1 randomisation, into either the intervention arm or the usual care arm. The usual care arm will continue to receive usual care throughout the trial, whilst the intervention arm will receive usual care plus the offer of a weekly, 18-week, physical activity intervention comprising walking and indoor activity sessions and community taster sessions. Another main component of the intervention includes one-to-one support. The primary outcome is to investigate the feasibility and acceptability of the intervention and to scale it up to a full-scale trial, using a short proforma provided to all intervention participants at follow-up, qualitative interviews with approximately 15 intervention participants and 5 interventions delivery staff, and data on intervention uptake, attendance, and attrition. Usual care data will also include recruitment and follow-up retention. Secondary outcome measures include physical activity and sedentary behaviours, body mass index, depression, anxiety, health-related quality of life, healthcare resource use, and adverse events. Outcome measures will be taken at baseline, three, and six-months post randomisation. DISCUSSION: This study will determine if the physical activity intervention is feasible and acceptable to both participants receiving the intervention and NHS staff who deliver it. Results will inform the design of a larger randomised controlled trial assessing the clinical and cost effectiveness of the intervention. TRIAL REGISTRATION: ISRCTN: ISRCTN83877229. Registered on 09.09.2022.

ScreenPlus: A comprehensive, multi-disorder newborn screening program.

The increasing availability of novel therapies highlights the importance of screening newborns for rare genetic disorders so that they may benefit from early therapy, when it is most likely to be effective. Pilot newborn screening (NBS) studies are a way to gather objective evidence about the feasibility and utility of screening, the accuracy of screening assays, and the incidence of disease. They are also an optimal way to evaluate the complex ethical, legal and social implications (ELSI) that accompany NBS expansion for disorders. ScreenPlus is a consented pilot NBS program that aims to enroll over 100,000 infants across New York City. The initial ScreenPlus panel includes 14 disorders and uses an analyte-based, multi-tiered screening platform in an effort to enhance screening accuracy. Infants who receive an abnormal result are referred to a ScreenPlus provider for confirmatory testing, management, and therapy as needed, along with longitudinal capture of outcome data. Participation in ScreenPlus requires parental consent, which is obtained in active and passive manners. Patient-facing documents are translated into the ten most common languages spoken at our nine pilot hospitals, all of which serve diverse communities. At the time of consent, parents are invited to receive a series of online surveys to capture their opinions about specific ELSI-related topics, such as NBS policy, residual dried blood spot retention, and the types of disorders that should be on NBS panels. ScreenPlus has developed a stakeholder-based, collective funding model that includes federal support in addition to funding from 14 advocacy and industry sponsors, all of which have a particular interest in NBS for at least one of the ScreenPlus disorders. Taken together, ScreenPlus is a model, multi-sponsored pilot NBS program that will provide critical data about NBS for a broad panel of disorders, while gathering key stakeholder opinions to help guide ethically sensitive decision-making about NBS expansion.

Recommended practices for virtual nutrition education interventions for adolescents with autism spectrum disorder: A reflection from two pilot interventions during the COVID-19 pandemic.

Youth with autism spectrum disorder (ASD) demonstrate unhealthy eating behaviors and dietary patterns compared to their neurotypical counterparts. Given the increased risk of unhealthy weight gain and the onset of the COVID-19 pandemic, modified nutrition programs in this population are warranted. The authors independently conducted two virtual pilot interventions during COVID-19 that offered feasible and acceptable alternatives to in-person delivery, providing unique opportunities for participant engagement and family involvement. Future virtual nutrition education programs for adolescents with ASD may include visual and verbal aids through Zoom, more parent/family integration, and accommodations for those with varying ASD severity levels.

Mobilizing pilot-based evidence for the spread and sustainability of innovations in healthcare: The role of innovation intermediaries.

An endemic challenge facing healthcare systems around the world is how to spread innovation more widely and sustainably. A common response to this challenge involves conducting pilot implementation studies to generate evidence of the innovation's benefits. However, despite the key role that such studies play in the local adoption of innovation, their contribution to the wider spread and sustainability of innovation is relatively under-researched and under-theorized. In this paper we examine this contribution through an empirical examination of the experiences of an innovation intermediary organization in the English NHS (National Health Service). We find that their work in mobilizing pilot-based evidence involves three main strands; configuring to context; transitioning evidence; and managing the transition. Through this analysis we contribute to theory by showing how the agency afforded by intermediary roles can support the effective transitioning of pilot-based evidence across different phases in the innovation journey, and across different occupational groups, and can thus help to create a positive feedback loop from localized early implementers of an innovation to later more widespread adoption and sustainability. Based on these findings, we develop insights on the reasons for the unnecessary repetition of pilots - so-called 'pilotitis'- and offer policy recommendations on how to enhance the role of pilots in the wider spread and sustainability of innovation.

A flexible test for early-stage studies with multiple endpoints.

This paper builds on the recently proposed prediction test for muliple endpoints. The prediction test combines information across multiple endpoints while accounting for the correlation between them. The test performs well with small samples relative to the number of endpoints of interest and is flexible in the hypotheses across the individual endpoints that can be combined. The prediction test addresses a global hypothesis that is of particular interest in early-stage studies and can be used as justification for continuing on to a larger trial. However, the prediction test has several limitations which we seek to address. First, the prediction test is overly conservative when both the effect sizes across all endpoints and the number of endpoints are small. By using a parametric bootstrap to estimate the null distribution, we show that the test achieves the nominal error rate in this situation and increases the power of the test. Second, we provide a framework to allow for predictions of a difference on one or more endpoints. Finally, we extend the test with a composite null hypothesis that allows for different null hypothesized predictive abilities across the endpoints which can be especially useful if the study contains both familiar and novel endpoints. We use an example from a physical activity trial to illustrate these extensions.

Predictive Potential of Cmax Bioequivalence in Pilot Bioavailability/Bioequivalence Studies, through the Alternative ƒ2 Similarity Factor Method.

Pilot bioavailability/bioequivalence (BA/BE) studies are downsized trials that can be conducted prior to the definitive pivotal trial. In these trials, 12 to 18 subjects are usually enrolled, although, in principle, a sample size is not formally calculated. In a previous work, authors recommended the use of an alternative approach to the average bioequivalence methodology to evaluate pilot studies' data, using the geometric mean (Gmean) ƒ2 factor with a cut off of 35, which has shown to be an appropriate method to assess the potential bioequivalence for the maximum observed concentration (Cmax) metric under the assumptions of a true Test-to-Reference Geometric Mean Ratio (GMR) of 100% and an inter-occasion variability (IOV) in the range of 10% to 45%. In this work, the authors evaluated the proposed ƒ2 factor in comparison with the standard average bioequivalence in more extreme scenarios, using a true GMR of 90% or 111% for truly bioequivalent formulations, and 80% or 125% for truly bioinequivalent formulations, in order to better derive conclusions on the potential of this analysis method. Several scenarios of pilot BA/BE crossover studies were simulated through population pharmacokinetic modelling, accounting for different IOV levels. A redefined decision tree is proposed, suggesting a fixed sample size of 20 subjects for pilot studies in the case of intra-subject coefficient of variation (ISCV%) > 20% or unknown variability, and suggesting the assessment of study results through the average bioequivalence analysis, and additionally through Gmean ƒ2 factor method in the case of the 90% confidence interval (CI) for GMR is outside the regulatory acceptance bioequivalence interval of [80.00-125.00]%. Using this alternative approach, the certainty levels to proceed with pivotal studies, depending on Gmean ƒ2 values and variability scenarios tested (20-60% IOV), were assessed, which is expected to be helpful in terms of the decision to proceed with pivotal bioequivalence studies.

The influence of an esports-adapted coping effectiveness training (E-CET) on resilience, mental health, and subjective performance among elite league of Legends players: A pilot study.

OBJECTIVE: This study aimed to develop, and pilot esports-adapted coping effectiveness training (E-CET) and measure its influence on coping effectiveness (global and specific), subjective performance, mental health (psychological distress and wellbeing), and resilience. DESIGN: Five elite male League of Legends players competing in the League of Legends Circuit Oceania participated in a mixed methods research design. The effects of E-CET were measured using a within-subjects quasi-experimental design (i.e., pre-to-post, no control group). To measure the effects of E-CET on specific stressors, a longitudinal diary design was used. METHOD: Players participated in a 2-h session of E-CET and a 45-min follow-up workshop. The 2-h workshop delivered content on two conceptual areas: (1) developing awareness of the stress and coping process; and (2) how to cope with stress. Players completed pre-intervention, post-intervention, and follow-up measures and twice-weekly stress journals. RESULTS: E-CET led to increases in players' perceived coping effectiveness and subjective performance, but there were no changes in psychological distress, psychological wellbeing, and resilience. However, the results indicate some positive signs for future coping interventions with League of Legends players and iterations of E-CET. CONCLUSION: The E-CET program appears to provide an opportunity to improve performance and mental health for esports players.

Treatment Effect Estimates From Pilot Trials Are Unreliable.

CONTEXT: The CONSORT guideline defines a pilot trial as a small-scale version of a desired future efficacy trial that is intended to answer the key questions of whether and how a larger study should be done. For example, a pilot trial might evaluate different approaches to data collection or outcome measurement. However, pilot trials are unreliable for assessing treatment efficacy due to the statistical phenomenon called sampling variability. OBJECTIVES: In this tutorial we use computer simulation to demonstrate the influence of sampling variability on efficacy estimates from pilot trials, illustrating why pilot trial designs should not be used to evaluate whether a treatment is promising or not. METHODS: We simulate a 2-arm parallel group trial (N=20 per group) with a survival outcome as an example. Simulations are done under two scenarios: 1) the treatment is efficacious at the level of a hypothetical minimum clinically important difference (hazard ratio [HR] = 0.75); and 2) the treatment is not efficacious (HR=1). RESULTS: As expected, in both simulated scenarios the range of observed results is distributed around the true treatment effect, HR=0.75 or HR=1. Importantly, ∼20% of trials simulated under scenario 1 incorrectly suggest the treatment may be harmful (HR > 1). Under scenario 2, half of the simulated studies incorrectly suggest the treatment is beneficial. CONCLUSION: Treatment effect estimates from pilot trials should not be used to make future development decisions regarding a novel therapy because of the high risk of misleading conclusions.

The SOFIA pilot study: assessing feasibility and fidelity of coordinated care to reduce excess mortality and increase quality of life in patients with severe mental illness in a general practice setting; a cluster-randomised pilot trial.

OBJECTIVE: To evaluate the feasibility and fidelity of implementing and assessing the SOFIA coordinated care program aimed at lowering mortality and increasing quality of life in patients with severe mental illness by improving somatic health care in general practice. DESIGN: A cluster-randomised, non-blinded controlled pilot trial. SETTING: General Practice in Denmark. INTERVENTION: The SOFIA coordinated care program comprised extended structured consultations carried out by the GP, group-based training of GPs and staff, and a handbook with information on signposting patients to relevant municipal, health, and social initiatives. PATIENTS: Persons aged 18 years or older with a diagnosis of psychotic, bipolar, or severe depressive disorder. MAIN OUTCOME MEASURES: We collected quantitative data on the delivery, recruitment and retention rates of practices and patients, and response rates of questionnaires MMQ and EQ-5D-5 L. RESULTS: From November 2020 to March 2021, nine practices were enrolled and assigned in a 2:1 ratio to the intervention group (n = 6) or control group (n = 3). Intervention group practices included 64 patients and Control practices included 23. The extended consultations were delivered with a high level of fidelity in the general practices; however, thresholds for collecting outcome measures, and recruitment of practices and patients were not reached. CONCLUSION: Our findings suggest that delivering the coordinated care program in a fully powered trial in primary care is likely feasible. However, the recruitment methodology requires improvement to ensure sufficient recruitment and minimize selective inclusion. TRIAL REGISTRATION: The date of pilot trial protocol registration was 05/11/2020, and the registration number is NCT04618250.

How to follow the new EU Council recommendation and improve prostate cancer early detection: the Prostaforum 2022 declaration.

An updated Council of the EU recommendation on cancer screening was adopted in December 2022 during the Czech EU presidency. The recommendation included prostate cancer as a suitable target disease for organised screening, and invited countries to proceed with piloting and further research. To support further discussions and actions to promote early detection of prostate cancer, an international conference in November 2022 (Prostaforum 2022) resulted in a joint declaration. Here we describe the EU policy background, summarise the preparation of the declaration and the key underlying evidence and expert recommendations, and report the text of the declaration. The declaration summarises the striking inequalities in prostate cancer burden in Europe and calls on all stakeholders to consider and support concrete steps for advancement of organised early detection of prostate cancer. Our aim is to request endorsement of the text and potential initiation of practical actions by all stakeholders to support the aims of the declaration. Patient summary: Prostate cancer is among the most frequent cancers and is one of the most common causes of cancer death among men. The European Union has recommended new pilot programmes for prostate cancer screening. The Prostaforum 2022 declaration invites all stakeholders to support this new recommendation with specific steps.

Alternative Analysis Approaches for the Assessment of Pilot Bioavailability/Bioequivalence Studies.

Pilot bioavailability/bioequivalence (BA/BE) studies are usually conducted and analysed similarly to pivotal studies. Their analysis and interpretation of results usually rely on the application of the average bioequivalence approach. However, due to the small study size, pilot studies are inarguably more sensitive to variability. The aim of this work is to propose alternative approaches to the average bioequivalence methodology, in a way to overcome and reduce the uncertainty on the conclusions of these studies and on the potential of test formulations. Several scenarios of pilot BA/BE crossover studies were simulated through population pharmacokinetic modelling. Each simulated BA/BE trial was analysed using the average bioequivalence approach. As alternative analyses, the centrality of the test-to-reference geometric least square means ratio (GMR), bootstrap bioequivalence analysis, and arithmetic (Amean) and geometric (Gmean) mean ƒ2 factor approaches were investigated. Methods performance was measured with a confusion matrix. The Gmean ƒ2 factor using a cut-off of 35 was the most appropriate method in the simulation conditions frame, enabling to more accurately conclude the potential of test formulations, with a reduced sample size. For simplification, a decision tree is also proposed for appropriate planning of the sample size and subsequent analysis approach to be followed in pilot BA/BE trials.

Development and pilot testing of the 2019 Canadian Abortion Provider Survey.

BACKGROUND: Substantial changes in abortion care regulations, available medications and national clinical practice guidelines have occurred since a 2012 national Canadian Abortion Provider Survey (CAPS). We developed and piloted the CAPS 2019 survey instrument to explore changes of the abortion provider workforce, their clinical care as well as experiences with stigma and harassment. METHODS: We undertook development and piloting in three phases: (1) development of the preliminary survey sections and questions based on the 2012 survey instrument, (2) content validation and feasibility of including certain content aspects via a modified Delphi Method with panels of clinical and research experts, and (3) pilot testing of the draft survey for face validity and clarity of language; assessing usability of the web-based Research Electronic Data Capture platform including the feasibility of complex skip pattern functionality. We performed content analysis of phase 2 results and used a general inductive approach to identify necessary survey modifications. RESULTS: In phase 1, we generated a survey draft that reflected the changes in Canadian abortion care regulations and guidelines and included questions for clinicians and administrators providing first and second trimester surgical and medical abortion. In phase 2, we held 6 expert panel meetings of 5-8 participants each representing clinicians, administrators and researchers to provide feedback on the initial survey draft. Due to the complexity of certain identified aspects, such as interdisciplinary collaboration and interprovincial care delivery differences, we revised the survey sections through an iterative process of meetings and revisions until we reached consensus on constructs and questions to include versus exclude for not being feasible. In phase 3, we made minor revisions based on pilot testing of the bilingual, web-based survey among additional experts chosen to be widely representative of the study population. Demonstrating its feasibility, we included complex branching and skip pattern logic so each respondent only viewed applicable questions based on their prior responses. CONCLUSIONS: We developed and piloted the CAPS 2019 survey instrument suitable to explore characteristics of a complex multidisciplinary workforce, their care and experience with stigma on a national level, and that can be adapted to other countries.

Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics.

BACKGROUND: Implementation of new technologies into national health care systems requires careful capacity planning. This is sometimes informed by data from pilot studies that implement the technology on a small scale in selected areas. A critical consideration when using implementation pilot studies for capacity planning in the wider system is generalisability. We studied the feasibility of using publicly available national statistics to determine the degree to which results from a pilot might generalise for non-pilot areas, using the English human papillomavirus (HPV) cervical screening pilot as an exemplar. METHODS: From a publicly available source on population indicators in England ("Public Health Profiles"), we selected seven area-level indicators associated with cervical cancer incidence, to produce a framework for post-hoc pilot generalisability analysis. We supplemented these data by those from publicly available English Office for National Statistics modules. We compared pilot to non-pilot areas, and pilot regimens (pilot areas using the previous standard of care (cytology) vs. the new screening test (HPV)). For typical process indicators that inform real-world capacity planning in cancer screening, we used standardisation to re-weight the values directly observed in the pilot, to better reflect the wider population. A non-parametric quantile bootstrap was used to calculate 95% confidence intervals (CI) for differences in area-weighted means for indicators. RESULTS: The range of area-level statistics in pilot areas covered most of the spectrum observed in the wider population. Pilot areas were on average more deprived than non-pilot areas (average index of multiple deprivation 24.8 vs. 21.3; difference: 3.4, 95% CI: 0.2-6.6). Participants in HPV pilot areas were less deprived than those in cytology pilot areas, matching area-level statistics. Differences in average values of the other six indicators were less pronounced. The observed screening process indicators showed minimal change after standardisation for deprivation. CONCLUSIONS: National statistical sources can be helpful in establishing the degree to which the types of areas outside pilot studies are represented, and the extent to which they match selected characteristics of the rest of the health care system ex-post. Our analysis lends support to extrapolation of process indicators from the HPV screening pilot across England.

The reporting of pilot and feasibility studies in the top dental specialty journals is suboptimal.

BACKGROUND: Pilot and feasibility studies (PAFS) are smaller investigations seeking to assess the feasibility of conducting a larger more definitive study. In late 2016, the CONSORT statement was extended to disseminate good practices for reporting of randomized pilot and feasibility trials. In this quality assurance review, we assessed whether PAFS in the top dental speciality journals adhere to good practices of conduct and reporting, by prioritizing assessment of feasibility and stating pre-defined progression criteria to inform the decision to pursue funding for a larger trial. METHODS: With the help of a librarian, we searched MEDLINE and EMBASE from 2017 to 2020, inclusive, for PAFS in the top 3 journals from each of the 10 dental specialties. We collected data on methodological and general characteristics of the studies, their objectives, and reporting of items recommended in the CONSORT extension. RESULTS: Of the 111 trials included, 51.4% (95% CI 41.7-61.0%) stated some indication of intent to assess feasibility while zero reported progression criteria; 74.8% (95% CI 65.6-82.5%) of trials used the terms "pilot" or "feasibility" in their titles and 82.9% (95% CI 74.6-89.4%) of studies stated there is a need for a future trial, but only 9.0% (95% CI 4.4-15.9%) stated intent to proceed to one. Most of the studies, 53.2% (95% CI 43.4-62.7%), reported hypothesis testing without cautioning readers on the generalizability of the results. Studies that used the terms "pilot" or "feasibility" in their title were less likely to have feasibility objectives, compared to trials that did not, with an odds ratio (OR) of 0.310 (95% CI 0.103-0.930; p = 0.037). Compared to trials that did not conduct hypothesis testing, trials that conducted hypothesis testing were significantly less likely to assess feasibility, among them, trials that cautioned readers on the generalizability of their results had an OR of 0.038 (95% CI 0.005-0.264; p < 0.001) and trials that did not caution readers on the generalizability of their results had an OR of 0.043 (95% CI 0.008-0.238; p = 0.001). CONCLUSION: Many PAFS in dentistry are not conducted with the intent of assessing feasibility, nor do they state progression criteria, and few report intent to proceed to a future trial. Misconceptions about PAFS can lead to them being poorly conducted and reported, which has economic and ethical implications. Research ethics boards, funding agencies, and journals need to raise their standards for the conduct and reporting of PAFS, and resources should be developed to address misconceptions and help guide researchers on the best practices for their conduct and reporting.

Population-based screening of newborns: Findings from the newborn screening expansion study (part two).

Rapid advances in genomic technologies to screen, diagnose, and treat newborns will significantly increase the number of conditions in newborn screening (NBS). We previously identified four factors that delay and/or complicate NBS expansion: 1) variability in screening panels persists; 2) the short duration of pilots limits information about interventions and health outcomes; 3) recent recommended uniform screening panel (RUSP) additions are expanding the definition of NBS; and 4) the RUSP nomination and evidence review process has capacity constraints. In this paper, we developed a use case for each factor and suggested how model(s) could be used to evaluate changes and improvements. The literature on models was reviewed from a range of disciplines including system sciences, management, artificial intelligence, and machine learning. The results from our analysis highlighted that there is at least one model which could be applied to each of the four factors that has delayed and/or complicate NBS expansion. In conclusion, our paper supports the use of modeling to address the four challenges in the expansion of NBS.

Newborn screening research sponsored by the NIH: From diagnostic paradigms to precision therapeutics.

Newborn screening (NBS) is a successful public health initiative that effectively identifies pre-symptomatic neonates so that treatment can be initiated before the onset of irreversible morbidity and mortality. Legislation passed in 2008 has supported a system of state screening programs, educational resources, and an evidence-based review process to add conditions to a recommended universal newborn screening panel (RUSP). The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, has promoted NBS research to advance legislative goals by supporting research that will uncover fundamental mechanisms of disease, develop treatments for NBS disorders, and promote pilot studies to test implementation of new conditions. NICHD's partnerships with other federal agencies have contributed to activities that support nominations of new conditions to the RUSP. The NIH's Newborn Sequencing In Genomic Medicine and Public Health (NSIGHT) initiative funded research projects that considered how genomic sequencing could be integrated into NBS and its ethical ramifications. Recently, the workshop, "Gene Targeted Therapies: Early Diagnosis and Equitable Delivery," has explored the possibility of expanding NBS to include genetic diagnosis and precision, gene-based therapies. Although hurdles remain to realize such a vision, broad engagement of multiple stakeholders is essential to advance genomic medicine within NBS.

Applying mixed methods to pilot feasibility studies to inform intervention trials.

BACKGROUND: Pilot feasibility studies serve a uniquely important role in preparing for larger scale intervention trials by examining the feasibility and acceptability of interventions and the methods used to test them. Mixed methods (collecting, analyzing, and integrating quantitative and qualitative data and results) can optimize what can be learned from pilot feasibility studies to prepare rigorous intervention trials. Despite increasing use of mixed method designs in intervention trials, there is limited guidance on how to apply these approaches to address pilot feasibility study goals. The purpose of this article is to offer methodological guidance for how investigators can plan to integrate quantitative and qualitative methods within pilot feasibility studies to comprehensively address key research questions. METHODS: We used an informal consensus-based process informed by key methodological resources and our team's complementary expertise as intervention researchers and mixed methodologists to develop guidance for applying mixed methods to optimize what can be learned from pilot feasibility studies. We developed this methodological guidance as faculty in the Mixed Methods Research Training Program (MMRTP) for the Health Sciences (R25MH104660) funded by the National Institutes of Health through the Office of Behavioral and Social Science Research. RESULTS: We provide the following guidance for applying mixed methods to optimize pilot feasibility studies: (1) identify feasibility domain(s) that will be examined using mixed methods, (2) align quantitative and qualitative data sources for the domain(s) selected for mixing methods, (3) determine the timing of the quantitative and qualitative data collection within the flow of the pilot study, (4) plan integrative analyses using joint displays to understand feasibility, and (5) prepare to draw meta-inferences about feasibility and implications for the future trial from the integrated data. CONCLUSIONS: By effectively integrating quantitative and qualitative data within pilot feasibility studies, investigators can harness the potential of mixed methods for developing comprehensive and nuanced understandings about feasibility. Our guidance can help researchers to consider the range of key decisions needed during intervention pilot feasibility testing to achieve a rigorous mixed methods approach generating enhanced insights to inform future intervention trials.