Young children's understanding and experience of insight.

An insight is a moment of sudden understanding followed by characteristic feelings of suddenness, positive affect, certainty, and ease, commonly known as an aha experience. Despite evidence from studies with adults that aha experiences benefit learning, little systematic research on children's aha experiences exists. The present study asks how children understand and experience insight. We presented a community sample of 160 children (age: 4-8 years, 47% girls, 51% boys, 2% nonbinary) with an illustrated clues task inspired by the Remote Associate Test, a task commonly used to study insight in adults. In this task, children saw three clues and were asked to find a solution word that was associated with the three clues. Self-reported and observed aha experiences were recorded, along with children's solution accuracy and confidence. Children also answered a set of questions to assess their understanding of aha experiences. We found that although the number of aha experiences remained stable across age, there was a clear developmental increase in the understanding of aha experiences. Children's ability to recognize their own aha experiences as well as their general understanding of the aha concept increased with age. This suggests a lag between the occurrence of children's aha experiences and their understanding of such experiences; children first have aha experiences and later develop an understanding of those experiences. Aha experiences were associated with higher accuracy, but not with higher confidence ratings. Observed aha experiences, but not self-reported aha experiences, predicted increased motivation. Our findings are in line with the literature on metacognitive development and the distinction between the experience and the understanding of emotion. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Updated joint ESPGHAN/NASPGHAN guidelines for management of Helicobacter pylori infection in children and adolescents (2023).

BACKGROUND: Evolving epidemiological data and increasing antibiotic resistance mandate an update of the European and North American Societies of Pediatric Gastroenterology, Hepatology and Nutrition guidelines. METHODS: Certainty of evidence and strength of recommendations were rated by experts according to the Grading of Recommendation Assessment, Development, and Evaluation approach. PICO (patient population, intervention, comparator, and outcome) questions were developed and voted on by the group. Recommendations were formulated using the Evidence to Decision framework. RESULTS: The current literature supports many of the previous recommendations and several new recommendations. Invasive testing with strain antimicrobial susceptibility analysis is recommended for the diagnosis and selection of eradication therapy for H. pylori infection. Molecular methods are acceptable for detection of infection and of antibiotic resistance in gastric biopsy specimens. Reliable, noninvasive tests can be used as a screening method for children with history of gastric cancer in a first-degree relative. When investigating causes of chronic immune thrombocytopenic purpura, testing for H. pylori is no longer recommended. When investigating other diseases such as inflammatory bowel disease, celiac disease, or eosinophilic esophagitis, specific diagnostic biopsies for H. pylori infection are not indicated. However, if H. pylori is an incidental finding, treatment may be considered after discussing the risks and benefits. Treatment should be based on antibiotic antimicrobial susceptibility testing and, if unavailable, regimens containing clarithromycin should be avoided. CONCLUSIONS: Due to decreasing prevalence of infection, increasing challenges with antibiotic resistance, and emerging evidence regarding complications of infection, clinicians must be aware of these recommended changes to appropriately manage H. pylori infection and its clinical sequelae in children.

Empowering the biomedical research community: Innovative SAS deployment on the All of Us Researcher Workbench.

OBJECTIVES: The All of Us Research Program is a precision medicine initiative aimed at establishing a vast, diverse biomedical database accessible through a cloud-based data analysis platform, the Researcher Workbench (RW). Our goal was to empower the research community by co-designing the implementation of SAS in the RW alongside researchers to enable broader use of All of Us data. MATERIALS AND METHODS: Researchers from various fields and with different SAS experience levels participated in co-designing the SAS implementation through user experience interviews. RESULTS: Feedback and lessons learned from user testing informed the final design of the SAS application. DISCUSSION: The co-design approach is critical for reducing technical barriers, broadening All of Us data use, and enhancing the user experience for data analysis on the RW. CONCLUSION: Our co-design approach successfully tailored the implementation of the SAS application to researchers' needs. This approach may inform future software implementations on the RW.

Leveraging the Mukaiyama oxidation-reduction condensation reaction for on-resin aryl thio-esterification for bio-conjugation.

A room-temperature Mukaiyama oxidation-reduction condensation inspired thioesterification methodology has been developed to afford aryl Cα-terminal peptide thioesters on-resin. The conditions herein feature mild reactions compatible with all Fmoc-SPPS protocols offering direct access to this critical arylthioester scaffold. This one-pot synthesis to aryl-thioester functionalised peptides facilitates peptide/protein synthesis by native chemical ligation.

Phytoplankton cell-states: multiparameter fluorescence lifetime flow-based monitoring reveals cellular heterogeneity.

Phytoplankton are a major source of primary productivity. Their photosynthetic fluorescence are unique measures of their type, physiological state, and response to environmental conditions. Changes in phytoplankton photophysiology are commonly monitored by bulk fluorescence spectroscopy, where gradual changes are reported in response to different perturbations, such as light intensity changes. What is the meaning of such trends in bulk parameters if their values report ensemble averages of multiple unsynchronized cells? To answer this, we developed an experimental scheme that enables tracking fluorescence intensities, brightnesses, and their ratios, as well as mean photon nanotimes equivalent to mean fluorescence lifetimes, one cell at a time. We monitored three different phytoplankton species during diurnal cycles and in response to an abrupt increase in light intensity. Our results show that we can define specific subpopulations of cells by their fluorescence parameters for each of the phytoplankton species, and in response to varying light conditions. Importantly, we identify the cells undergo well-defined transitions between these subpopulations. The approach shown in this work will be useful in the exact characterization of phytoplankton cell states and parameter signatures in response to different changes these cells experience in marine environments, which will be applicable for monitoring marine-related environmental effects.

Checking out the unexplained: With age, children become increasingly skeptical of surprising claims.

When presented with surprising claims, older children investigate such claims more often than younger children. The present study tests whether older children (6-7-year-olds) are more skeptical than younger children (4-5-year-olds) about surprising claims that lack supporting evidence because they expect informants to provide evidence for them. To test this hypothesis, we presented 140 4-7-year-old children (47-96 months, 46.4% girls, 53.6% boys, 86.4% with at least one parent who completed a BA degree, 50% parents with income above median) with a series of vignettes. In each vignette, the protagonist wanted to accomplish a task and needed to select the most appropriate object for that task. Before deciding which object to use, the protagonist heard a surprising claim about one of the object's properties, presented with or without supporting evidence. For example, in the supporting explanation condition, the informant stated that the smallest object was the heaviest and that they knew because they had lifted the objects. Children were then asked whether the protagonist knew which object to use and why. Contrary to expectation, children across all ages typically indicated that the protagonist had sufficient knowledge, regardless of whether an informant provided supporting evidence or not. However, with increasing age, children became more skeptical of both supported and unsupported surprising claims and increasingly stated that the protagonist should not select the object suggested by the informant. Finally, when asked to justify this judgment, older children were more likely than younger to express skepticism toward the claims, especially when presented without supporting evidence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Leveraging artificial intelligence to summarize abstracts in lay language for increasing research accessibility and transparency.

OBJECTIVE: Returning aggregate study results is an important ethical responsibility to promote trust and inform decision making, but the practice of providing results to a lay audience is not widely adopted. Barriers include significant cost and time required to develop lay summaries and scarce infrastructure necessary for returning them to the public. Our study aims to generate, evaluate, and implement ChatGPT 4 lay summaries of scientific abstracts on a national clinical study recruitment platform, ResearchMatch, to facilitate timely and cost-effective return of study results at scale. MATERIALS AND METHODS: We engineered prompts to summarize abstracts at a literacy level accessible to the public, prioritizing succinctness, clarity, and practical relevance. Researchers and volunteers assessed ChatGPT-generated lay summaries across five dimensions: accuracy, relevance, accessibility, transparency, and harmfulness. We used precision analysis and adaptive random sampling to determine the optimal number of summaries for evaluation, ensuring high statistical precision. RESULTS: ChatGPT achieved 95.9% (95% CI, 92.1-97.9) accuracy and 96.2% (92.4-98.1) relevance across 192 summary sentences from 33 abstracts based on researcher review. 85.3% (69.9-93.6) of 34 volunteers perceived ChatGPT-generated summaries as more accessible and 73.5% (56.9-85.4) more transparent than the original abstract. None of the summaries were deemed harmful. We expanded ResearchMatch's technical infrastructure to automatically generate and display lay summaries for over 750 published studies that resulted from the platform's recruitment mechanism. DISCUSSION AND CONCLUSION: Implementing AI-generated lay summaries on ResearchMatch demonstrates the potential of a scalable framework generalizable to broader platforms for enhancing research accessibility and transparency.

The Antimicrobial Peptide Capitellacin: Chemical Synthesis of Analogues to Probe the Role of Disulphide Bridges and Their Replacement with Vinyl Sulphides.

Capitellacin (1) is a 20-residue antimicrobial ß-hairpin, produced by the marine polychaeta (segmented worms) Capitella teletai. Since its discovery in 2020, only very limited studies have been undertaken to understand capitellacin's structure-activity relationship (SAR). Using fast-flow Fmoc-SPPS, a focused library of capitellacin analogues was prepared to systematically study the influence of the two disulphide bridges on its structure and activity, and their replacement with a vinyl sulphide as a potential bioisostere. Upon studying the resulting peptides' antimicrobial activity and secondary structure, the most terminal disulphide emerged as the most critical element for maintaining both bioactivity and the secondary structure, properties which were demonstrated to be closely interlinked. The removal of the innermost disulphide bridge or disulphide replacement with a vinyl sulphide emerged as strategies with which to tune the activity spectrum, producing selectivity towards E. coli. Additionally, an enantiomeric d-capitellacin analogue revealed mechanistic insights, suggesting that chirality may be an inherent property of capitellacin's bacterial membrane target, or that a hitherto unknown secondary mechanism of action may exist. Additionally, we propose the Alloc protecting group as a more appropriate alternative to the common Dde group during fast-flow Fmoc-SPPS, in particular for short-chain diamino acids.

Chemical Modifications on the αvß6 Integrin Targeting A20FMDV2 Peptide: A Review.

Integrin proteins have received a significant increase in attention in recent scientific endeavors. The current trend uses the pre-established knowledge that the arginyl-glycyl-aspartic acid (RGD) structural motif present in the A20FMDV2 peptide is highly selective for the integrin class αvß6 which is overexpressed in many cancer types. This review will provide an extensive overview of the existing literature research to date to the best of our knowledge, highlighting significant improvements and drawbacks of structure-activity relationships (SAR) work undertaken, aiding future research to identify established SAR for an informed design of future A20FMDV2 mimetic inhibitors. Herein, the review aims to collate the existing structural chemical modifications present on A20FMDV2 in the literature to highlight key structural analogues that display more potent biological activity.

Scientific and religious beliefs are primarily shaped by testimony.

Understanding why individuals are more confident of the existence of invisible scientific phenomena (e.g., oxygen) than invisible religious phenomena (e.g., God) remains a puzzle. Departing from conventional explanations linking ontological beliefs to direct experience, we introduce a model positing that testimony predominantly shapes beliefs in both scientific and religious domains. Distinguishing direct experience (personal observation) from cultural input (testimony-based evidence), we argue that even apparently direct experiences often stem from others' testimony. Our analysis indicates that variability in direct experience cannot explain belief disparities between science and religion, within each domain, or across cultures. Instead, variability in testimony is the primary driver of ontological beliefs. We present developmental evidence for testimony-based beliefs and elucidate the mechanisms underlying their impact.

[Severe acute pancreatitis secondary to hypertriglyceridemia as the onset of Type 1 Diabetes Mellitus in the pediatric age]. / Pancreatitis aguda grave secundaria a hipertrigliceridemia como debut de Diabetes Mellitus Tipo 1 en edad pediátrica.

Hypertriglyceridemia (HTG)-induced acute pancreatitis (AP) secondary to insulin deficiency following the onset of type 1 diabetes mellitus (T1DM) is a rare but serious complication in children. OBJECTIVE: To describe the diagnosis and treatment of severe HTG and to emphasize the need for timely diagnosis of T1DM. CLINICAL CASE: A 15-year-old female adolescent with a history of overweight presented with a two-weeks history of fever, anorexia, and diffuse abdominal pain. Laboratory tests revealed triglycerides of 17,580 mg/dL, lipase of 723 U/L, and blood glucose of 200 mg/dL. An abdominal CT scan showed an enlarged and edematous pancreas. She was hospitalized with a diagnosis of AP and severe HTG, which progressed to acute necro-hemorrhagic pancreatitis. Treatment included continuous intravenous insulin infusion until triglyceride levels decreased. Upon discontinuation of insulin, fasting hyperglycemia (206 mg/dL) and metabolic acidosis recurred, therefore DM was suspected. Upon targeted questioning, a history of polydipsia, polyuria, and weight loss during the last 3 months stood out. Glycated hemoglobin was markedly elevated (14.7%). Insulin therapy was optimized, achieving stabilization of laboratory parameters after 15 days of treatment and complete anatomical resolution of pancreatic involvement at one year of follow-up. CONCLUSIONS: The presence of severe HTG in pediatrics compels us to consider its secondary causes, such as the onset of T1DM. It is crucial to improve the ability to diagnose T1DM early, as it may present with infrequent and high-risk presentations for the patient.

Identifying erroneous height and weight values from adult electronic health records in the All of Us research program.

INTRODUCTION: Electronic Health Records (EHR) are a useful data source for research, but their usability is hindered by measurement errors. This study investigated an automatic error detection algorithm for adult height and weight measurements in EHR for the All of Us Research Program (All of Us). METHODS: We developed reference charts for adult heights and weights that were stratified on participant sex. Our analysis included 4,076,534 height and 5,207,328 wt measurements from âˆ¼ 150,000 participants. Errors were identified using modified standard deviation scores, differences from their expected values, and significant changes between consecutive measurements. We evaluated our method with chart-reviewed heights (8,092) and weights (9,039) from 250 randomly selected participants and compared it with the current cleaning algorithm in All of Us. RESULTS: The proposed algorithm classified 1.4 % of height and 1.5 % of weight errors in the full cohort. Sensitivity was 90.4 % (95 % CI: 79.0-96.8 %) for heights and 65.9 % (95 % CI: 56.9-74.1 %) for weights. Precision was 73.4 % (95 % CI: 60.9-83.7 %) for heights and 62.9 (95 % CI: 54.0-71.1 %) for weights. In comparison, the current cleaning algorithm has inferior performance in sensitivity (55.8 %) and precision (16.5 %) for height errors while having higher precision (94.0 %) and lower sensitivity (61.9 %) for weight errors. DISCUSSION: Our proposed algorithm outperformed in detecting height errors compared to weights. It can serve as a valuable addition to the current All of Us cleaning algorithm for identifying erroneous height values.

Selecting trial centers using a standardized, automated site assessment survey instrument (SASI).

BACKGROUND: To improve the site selection process for clinical trials, we expanded a site survey to include standardized assessments of site commitment time, team experience, feasibility of tight timelines, and local medical community equipoise as factors that might better predict performance. We also collected contact information about institutional research services ahead of site onboarding. AIM: As a first step, we wanted to confirm that an expanded survey could be feasible and generalizable-that asking site teams for more details upfront was acceptable and that the survey could be completed in a reasonable amount of time, despite the assessment length. METHODS: A standardized, two-part Site Assessment Survey Instrument (SASI), examining qualitative components and with multiple contact list sections, was developed using a publicly accessible dashboard and later transferred to a REDCap platform. After multiple rounds of internal testing, the SASI was deployed 11 times for multicenter trials. Follow-up questionnaires were sent to site teams to confirm that an expanded survey instrument is acceptable to the research community and could be completed during a brief work shift. RESULTS: Respondents thought the SASI collected useful and relevant information about their sites (100%). Sites were "comfortable" (90%) supplying detailed information early in the site selection process and 57% completed the SASI in one to two hours. CONCLUSIONS: Coordinating centers and sites found the SASI tool to be acceptable and helpful when collecting data in consideration of multicenter trial site selection.

Religious polarization and justification of belief in invisible scientific versus religious entities.

Children and adults express greater confidence in the existence of invisible scientific as compared to invisible religious entities. To further examine this differential confidence, 5- to 11-year-old Turkish children and their parents (N = 174, 122 females) from various regions in Türkiye, a country with an ongoing tension between secularism and religion, were tested in 2021 for their belief in invisible entities. Participants expressed more confidence in the existence of scientific than religious entities. For scientific entities, children justified their belief primarily by elaborating on the properties of the entity, rather than referring to the testimonial source of their judgment. This pattern was reversed for religious entities, arguably, highlighting the role of polarization in shaping the testimony children typically hear.

Impact of financial compensation on enrollment and participation in a remote, mobile-app based research study.

Background: There is no consensus on how to determine appropriate financial compensation for research recruitment. Selecting incentive amounts that are reasonable and respectful, without undue inducement, remains challenging. Previously, we demonstrated that incentive amount significantly impacts participants' willingness to complete various hypothetical research activities. Here we further explore this relationship in a mock decentralized study. Methods: Adult ResearchMatch volunteers were invited to join a prospective study where interested individuals were given an opportunity to view details for a study along with participation requirements, then offered a randomly generated compensation amount between $0 and $50 to enroll and participate. Individuals agreeing to participate were then asked to complete tasks using a remote mobile application (MyCap), for two weeks. Tasks included a weekly survey, a daily gratitude journal and daily phone tapping task. Results: Willingness to participate was 85% across all incentive levels but not significantly impacted by amount. Task completion appeared to increase as a function of compensation until a plateau at $25. While participants described the study as low burden and reported that compensation was moderately important to their decision to join, only 31% completed all study tasks. Conclusion: While offering compensation in this study did not have a strong effect on enrollment rate, this work provides insight into participant motivation when joining and participating in studies employing mobile applications.

Illuminating the landscape of high-level clinical trial opportunities in the All of Us Research Program.

OBJECTIVE: With its size and diversity, the All of Us Research Program has the potential to power and improve representation in clinical trials through ancillary studies like Nutrition for Precision Health. We sought to characterize high-level trial opportunities for the diverse participants and sponsors of future trial investment. MATERIALS AND METHODS: We matched All of Us participants with available trials on ClinicalTrials.gov based on medical conditions, age, sex, and geographic location. Based on the number of matched trials, we (1) developed the Trial Opportunities Compass (TOC) to help sponsors assess trial investment portfolios, (2) characterized the landscape of trial opportunities in a phenome-wide association study (PheWAS), and (3) assessed the relationship between trial opportunities and social determinants of health (SDoH) to identify potential barriers to trial participation. RESULTS: Our study included 181 529 All of Us participants and 18 634 trials. The TOC identified opportunities for portfolio investment and gaps in currently available trials across federal, industrial, and academic sponsors. PheWAS results revealed an emphasis on mental disorder-related trials, with anxiety disorder having the highest adjusted increase in the number of matched trials (59% [95% CI, 57-62]; P < 1e-300). Participants from certain communities underrepresented in biomedical research, including self-reported racial and ethnic minorities, had more matched trials after adjusting for other factors. Living in a nonmetropolitan area was associated with up to 13.1 times fewer matched trials. DISCUSSION AND CONCLUSION: All of Us data are a valuable resource for identifying trial opportunities to inform trial portfolio planning. Characterizing these opportunities with consideration for SDoH can provide guidance on prioritizing the most pressing barriers to trial participation.

Identifying and Extracting Rare Diseases and Their Phenotypes with Large Language Models.

Purpose: Phenotyping is critical for informing rare disease diagnosis and treatment, but disease phenotypes are often embedded in unstructured text. While natural language processing (NLP) can automate extraction, a major bottleneck is developing annotated corpora. Recently, prompt learning with large language models (LLMs) has been shown to lead to generalizable results without any (zero-shot) or few annotated samples (few-shot), but none have explored this for rare diseases. Our work is the first to study prompt learning for identifying and extracting rare disease phenotypes in the zero- and few-shot settings. Methods: We compared the performance of prompt learning with ChatGPT and fine-tuning with BioClinicalBERT. We engineered novel prompts for ChatGPT to identify and extract rare diseases and their phenotypes (e.g., diseases, symptoms, and signs), established a benchmark for evaluating its performance, and conducted an in-depth error analysis. Results: Overall, fine-tuning BioClinicalBERT resulted in higher performance (F1 of 0.689) than ChatGPT (F1 of 0.472 and 0.610 in the zero- and few-shot settings, respectively). However, ChatGPT achieved higher accuracy for rare diseases and signs in the one-shot setting (F1 of 0.778 and 0.725). Conversational, sentence-based prompts generally achieved higher accuracy than structured lists. Conclusion: Prompt learning using ChatGPT has the potential to match or outperform fine-tuning BioClinicalBERT at extracting rare diseases and signs with just one annotated sample. Given its accessibility, ChatGPT could be leveraged to extract these entities without relying on a large, annotated corpus. While LLMs can support rare disease phenotyping, researchers should critically evaluate model outputs to ensure phenotyping accuracy.

Classification of Breast Implant Malposition.

BACKGROUND: Implant malposition is a well-recognized complication of prosthetic breast implants. However, to date, no objective classification system has been described. OBJECTIVES: The aim of this study was to perform a prospective trial of an objective and reproducible classification system for implant malposition formulated by analyzing retrospective data from a large cohort of patients with implant malposition. METHODS: The authors retrospectively analyzed the degree of medial/lateral and inferior/superior implant malposition relative to their optimal position within the breast footprint in a series of 189 breasts (n = 100 patients). An objective classification system for implant malposition was devised and then applied to a prospective cohort of 53 breasts in 28 patients with implant malposition. RESULTS: The degree of malposition in a single or combination of axes was categorized according to the distance (measured in centimeters) from the ideal breast footprint. The classification system incorporated the axis of malposition and distance to generate a treatment decision-making guide. Cases of Grade 1 malposition did not warrant surgical intervention, whereas surgical correction was warranted in all Grade 3 cases. In the combined patient cohort (n = 242 breasts, 128 patients), lateral, inferior, medial, and superior displacement ranged between Grades 1 and 3. There was no interobserver variability in the grades assigned to 9 out of 10 patients in the prospective group. CONCLUSIONS: A simple and reproducible classification system for implant malposition has been created that allows surgeons to objectively record the extent of malposition, guides surgical decision-making, and can be used to document the results of any intervention.

Patient-perceived factors influencing physical activity sensor use in stroke prevention and rehabilitation: A thematic synthesis protocol.

INTRODUCTION: While the putative benefits of "fitness trackers" continue to fuel a booming consumer market, results of device-based clinical interventions remain remarkably mixed. This study will explore factors influencing wearable physical activity (PA) sensor use in the context of stroke prevention and rehabilitation for older adults. The findings of this thematic synthesis will provide insights into factors influencing the use of PA sensors in stroke which may inform more effective device-based interventions. METHODS AND ANALYSIS: Thematic synthesis as a formal method described by Thomas and Arden can be used within a systematic review to synthesize primary qualitative research. Accordingly, the proposed study will systematically search bibliographic databases for relevant peer-reviewed papers and synthesize coded thematic data within included papers. The quality of papers will be assessed using the JBI Critical Appraisal Checklist for Qualitative Research. Patterns in the text will be coded, preliminary data visualised, and higher-level analytical themes discerned to explain factors influencing the use of PA sensors in older stroke patients. DISCUSSION: This study does not require ethics approval. Results are expected to be available by June 2024. Data from the thematic synthesis will provide insights into barriers and facilitators influencing the use of wearable PA sensors in stroke and older adults at risk, and implications these factors have for the design of effective device-based interventions. TRIAL REGISTRATION: Systematic review registration: PROSPERO registration number: CRD42020211472. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020211472.

Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity.

Importance: Despite consistent public health recommendations, obesity rates in the US continue to increase. Physical activity recommendations do not account for individual genetic variability, increasing risk of obesity. Objective: To use activity, clinical, and genetic data from the All of Us Research Program (AoURP) to explore the association of genetic risk of higher body mass index (BMI) with the level of physical activity needed to reduce incident obesity. Design, Setting, and Participants: In this US population-based retrospective cohort study, participants were enrolled in the AoURP between May 1, 2018, and July 1, 2022. Enrollees in the AoURP who were of European ancestry, owned a personal activity tracking device, and did not have obesity up to 6 months into activity tracking were included in the analysis. Exposure: Physical activity expressed as daily step counts and a polygenic risk score (PRS) for BMI, calculated as weight in kilograms divided by height in meters squared. Main Outcome and Measures: Incident obesity (BMI ≥30). Results: A total of 3124 participants met inclusion criteria. Among 3051 participants with available data, 2216 (73%) were women, and the median age was 52.7 (IQR, 36.4-62.8) years. The total cohort of 3124 participants walked a median of 8326 (IQR, 6499-10 389) steps/d over a median of 5.4 (IQR, 3.4-7.0) years of personal activity tracking. The incidence of obesity over the study period increased from 13% (101 of 781) to 43% (335 of 781) in the lowest and highest PRS quartiles, respectively (P = 1.0 × 10-20). The BMI PRS demonstrated an 81% increase in obesity risk (P = 3.57 × 10-20) while mean step count demonstrated a 43% reduction (P = 5.30 × 10-12) when comparing the 75th and 25th percentiles, respectively. Individuals with a PRS in the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to have a comparable risk of obesity. To have a comparable risk of obesity to individuals at the 25th percentile of PRS, those at the 75th percentile with a baseline BMI of 22 would need to walk an additional 3460 steps/d; with a baseline BMI of 24, an additional 4430 steps/d; with a baseline BMI of 26, an additional 5380 steps/d; and with a baseline BMI of 28, an additional 6350 steps/d. Conclusions and Relevance: In this cohort study, the association between daily step count and obesity risk across genetic background and baseline BMI were quantified. Population-based recommendations may underestimate physical activity needed to prevent obesity among those at high genetic risk.