OBJECTIVES/GOALS: Metabolic syndrome (MetSyn) is a risk for World Trade Center-Lung Injury (WTC-LI; defined as developing FEV1<lower limit of normal [LLN]). Metabolic health is a modifiable disease risk factor. We propose to characterize how time-dependent covariates of MetSyn are longitudinally associated with WTC-LI. METHODS/STUDY POPULATION: WTC-particulate exposed firefighters, consented, with pre-9/11 FEV1 LLN (N = 5,746). Data assessed from last pre-9/11 till August 1, 2017. Longitudinal MetSyn characteristics were assessed using 3 models: i. A linear mixed effect model to assess the effect size of longitudinal MetSyn and its components on longitudinal FEV1% predicted as an outcome; ii. a time-dependent Cox regression to assess the associations of MetSyn to time of onset of WTC-LI; iii. a novel, partially linear single index regression model with repeatedly measured MetSyn to assess their joint effects and delineate their relative contribution on the longitudinal lung function in the WTC-FDNY cohort. RESULTS/ANTICIPATED RESULTS: In Model I, BMI 30 kg/m2 had the largest effect size compared to ever-smoking, with −2.524 (95%CI: −2.708,−2.340) compared to −1.681(−2.325,−1.038) respectively. Having MetSyn, defined as 3/5 risk factors, had an effect size of −2.319(−2.526,−2.112). In Model II, hazards of triglycerides 150mg/dL were highest at 1.497(1.336, 1.677), followed by BMI 30 kg/m2 at 1.406(1.256, 1.575), and HDL<40mg/dL 1.355(1.176-1.561), compared to ever-smoking (1.201, p = 0.002). Having high exposure to PM by being present in the morning of 9/11 was a significant covariate only in Model II investigating HDL<40mg/dL or triglycerides 150mg/dL. Model III The proposed methods will be applied to our cohort study. DISCUSSION/SIGNIFICANCE OF IMPACT: MetSyn is both a predictor and concurrent marker of WTC-LI. The single index model can not only reduce dimensionality of the covariates, but also provides efficient estimates of the joint MetSyn effects, allowing linear or nonlinear effects. Future studies will investigate dietary intervention as a potential disease-modifying factor. CONFLICT OF INTEREST DESCRIPTION: NA, nothing to disclose.

OBJECTIVES/GOALS: Access to biostatistics expertise is essential for a successful clinical and translational research program. However, demand for statistical support at academic research centers can strain the capacity of biostatistics units. Our objective was to efficiently increase access to statistical expertise. METHODS/STUDY POPULATION: In cooperation with the Cancer Center Biostatistics Shared Resource, we replaced an informal 1-hour drop-in consultation program with structured office hours to provide statistical support to clinical and translational researchers at the University of California, Davis Medical Center. We doubled office hours to 2 hours per week and established six 20-minute appointments. Two Ph.D. level statisticians staff office hours. Researchers schedule appointments through Acuity Scheduling, a free on-line resource. Availability of the service is advertised monthly by sending an informational flyer to various university listservs. RESULTS/ANTICIPATED RESULTS: Prior to implementing the program in 2014, we averaged 91 office hour consults per year. Subsequently, consultations jumped to 171 in 2014 and have averaged 150 per year since then. Office hours attract students, residents, staff and faculty from a wide range of disciplines including the Schools of Medicine, Nursing, Veterinary Medicine and basic science departments. Project types span the clinical and translational spectrum covering lab, animal, clinical and population-level studies. Most consults related to data analysis and interpretation (57%) followed by sample size calculations/study design (29%) and response to reviewers (4%), with general statistical advice as the remainder. DISCUSSION/SIGNIFICANCE OF IMPACT: With 6 micro-consults per week, we can meet with many investigators and triage their statistical support needs. This program has proved very popular and was highly rated in a recent user survey, with several investigators noting that the consults facilitated successful publications and proposals.

OBJECTIVES/GOALS: We modeled risk of reintubation within 48 hours of cardiac surgery using variables available in the electronic health record (EHR). This model will guide recruitment for a prospective, pragmatic clinical trial entirely embedded within the EHR among those at high risk of reintubation. METHODS/STUDY POPULATION: All adult patients admitted to the cardiac intensive care unit following cardiac surgery involving thoracotomy or sternotomy were eligible for inclusion. Data were obtained from operational and analytical databases integrated into the Epic EHR, as well as institutional and departmental-derived data warehouses, using structured query language. Variables were screened for inclusion in the model based on clinical relevance, availability in the EHR as structured data, and likelihood of timely documentation during routine clinical care, in the hopes of obtaining a maximally-pragmatic model. RESULTS/ANTICIPATED RESULTS: A total of 2325 patients met inclusion criteria between November 2, 2017 and November 2, 2019. Of these patients, 68.4% were male. Median age was 63.0. The primary outcome of reintubation occurred in 112/2325 (4.8%) of patients within 48 hours and 177/2325 (7.6%) at any point in the subsequent hospital encounter. Univariate screening and iterative model development revealed numerous strong candidate predictors (ANOVA plot, figure 1), resulting in a model with acceptable calibration (calibration plot, figure 2), c = 0.666. DISCUSSION/SIGNIFICANCE OF IMPACT: Reintubation is common after cardiac surgery. Risk factors are available in the EHR. We are integrating this model into the EHR to support real-time risk estimation and to recruit and randomize high-risk patients into a clinical trial comparing post-extubation high flow nasal cannula with usual care. CONFLICT OF INTEREST DESCRIPTION: REF has received grant funding and consulting fees from Medtronic for research on inpatient monitoring.

OBJECTIVES/GOALS: To describe principles, best practices, and techniques recommended to instill deep understanding of the application and interpretation of statistical techniques and statistical inference among translational scientists and trainees, that best support the concepts of scientific Rigor, Reproducibility and Reporting. METHODS/STUDY POPULATION: Each of the six New York City Area Biostatistics, Epidemiology and Research Design (BERD) resources have strong educational programs, novel curricular components, and creative strategies, implemented by award winning educators. To capitalize on shared knowledge, innovation, and resources, the six teams formed the New York City Area BERD Collaborative (NYC-ABC) comprised of BERD resources from Mt. Sinai, Cornell, Einstein, Columbia, Rockefeller, and NYU. The collaborative suggests principles, concepts, tools and approaches to support the concepts of scientific Rigor, Reproducibility and Reporting in translational science. RESULTS/ANTICIPATED RESULTS: Principles:

• Value of team science approach and including biostatisticians early and often.

• Carefully designing experiments to reduce bias and increase precision.

• Trainees’ focus is often on “statistical significance” and the p-value. Consequences of data dredging/p-hacking, and the impact of sample size and other factors on statistical significance.

• Emphasizing the effect size and answering the scientific hypothesis when reporting results.

• Statistical code used to produce results should be well annotated and raw data posted online to enhance reproducibility.

• Incorporate effective multiple modalities (i.e. didactic, demonstrative, hands on workshops, applications, and tools).

• Approach from “the drivers’ seat” perspective, rather than strictly mathematical.

• Endorse flipped classroom approach

DISCUSSION/SIGNIFICANCE OF IMPACT: Like any complex discipline, biostatistical education can be approached from several dimensions, but it remains essential to focus on fundamental goals of science. We remind our trainees that the goal of science is to create knowledge, not to “find significance”. Deep understanding of inferential methods and proper interpretation of results are key. CONFLICT OF INTEREST DESCRIPTION: None.

OBJECTIVES/GOALS:

• A web interface that allows for easy upload of CSV text data to time-based visualizations

• Implementation of change points analysis to identify and display points where event rates increased or decreased

• customizable plots where the user can change point shapes, color, etc.

• customizable and advanced filtering support

• support for plot comparisons and exports

METHODS/STUDY POPULATION: We used the R/Shiny framework to develop a web application for visualization of time stamped data. The Research and Exploratory Analysis Driven Time-data Visualization (READ-TV) application allows for user-friendly mining for longitudinal patterns in data. READ-TV is built specifically for FD analysis, but is easily adaptable to other clinical use cases, as we allow for the use of general metadata on events and cases.The building of a quantitative framework for event analysis starts with the application of homogeneous Poisson processes, which relate the times of occurrence of events in terms of an underlying rate. To understand the changes in this underlying rate, changepoint analysis is used to model the rate as a function of time using piecewise constant approximations. The changepoint analysis allows us to identify the specific periods of time where the rate of FD is increased relative to a baseline or a desired operating range. RESULTS/ANTICIPATED RESULTS: READ-TV application allows for import of time stamped event data from multiple cases. Event and case metadata are supported to facilitate filtering and mining of interesting subsets of data. Stem plots are used for visualization of selected event timelines in chosen cases. This visualization is accompanied with summary of the number and estimates of rates of occurrence of specific event types (e.g. types of FD). Change-point analysis is implemented using the ‘changepoint‘ R library. These analyses allow the users to quickly understand whether the rates of events (FD) is changing across the case timeline and where exactly these changes are occurring. DISCUSSION/SIGNIFICANCE OF IMPACT: We have demonstrated the READ-TV application to the team of the AHRQ-funded Human Factors and Systems Integration in High Technology Surgery (HF-SIgHTS) study. The ability to visualize and perform quantitative analysis of the study data was received with unanimous positive feedback and enthusiasm. We continue READ-TV development focusing on (1) increased user-friendliness using the HF-SIgHTS as our focus group, (2) increased functionality, and (3) use of more general localization terminology to allow for other applications.

OBJECTIVES/GOALS: Diverse medication-based studies require longitudinal drug dose information. EHRs can provide such data, but multiple mentions of a drug in the same clinical note can yield conflicting dose. We aimed to develop statistical methods which address this challenge by predicting the valid dose in the event that conflicting doses are extracted. METHODS/STUDY POPULATION: We extracted dose information for two test drugs, tacrolimus and lamotrigine, from Vanderbilt EHRs using a natural language processing system, medExtractR, which was developed by our team. A random forest classifier was used to estimate the probability of correctness for each extracted dose on the basis of subject longitudinal dosing patterns and extracted EHR note context. Using this feasibility measure and other features such as a summary of subject dosing history, we developed several statistical models to predict the dose on the basis of the extracted doses. The models developed based on supervised methods included a separate random forest regression, a transition model, and a boosting model. We also considered unsupervised methods and developed a Bayesian hierarchical model. RESULTS/ANTICIPATED RESULTS: We compared model-predicted doses to physician-validated doses to evaluate model performance. A random forest regression model outperformed all proposed models. As this model is a supervised model, its utility would depend on availability of validated dose. Our preliminary result from a Bayesian hierarchical model showed that it can be a promising alternative although performing less optimally. The Bayesian hierarchical model would be especially useful when validated dose data are not available, as it was developed in unsupervised modeling framework and hence does not require validated dose that can be difficult and time consuming to obtain. We evaluated the feasibility of each method for automatic implementation in our drug dosing extraction and processing system we have been developing. DISCUSSION/SIGNIFICANCE OF IMPACT: We will incorporate the developed methods as a part of our complete medication extraction system, which will allow to automatically prepare large longitudinal medication dose datasets for researchers. Availability of such data will enable diverse medication-based studies with drastically reduced barriers to data collection.

OBJECTIVES/GOALS: In a previous genome-wide association study of European Americans, rs12772424, a variant in the gene encoding transcription factor 7-like 2 (TCF7L2), was shown to have a SNP-BMI interaction association with bipolar disorder (BD). The objective of this study was to replicate this finding in an African American (AA) sample. METHODS/STUDY POPULATION: Using a sample of 659 controls and 323 BD cases from the Genetic Association Information (GAIN) Study of BD, we conducted analyses to assess association between BD and the interaction of BMI with genetic variation in TCF7L2. For this study we identified 4572 single nucleotide polymorphisms (SNPs) in a 1Mb region around the candidate SNP rs1272424. Based on variants identified in the prior analysis of the larger European American dataset we selected SNPs for analysis in the AA data. This allowed for a smaller AA sample, and still maintained adequate power for statistical significance. RESULTS/ANTICIPATED RESULTS: We anticipate observing an effect of TCF7L2 variation on the relationship between BD and BMI in the AA data. We also anticipate that combining results from the European and African American patients may help narrow down potentially functional variants in TCF7L2 that influence the association between BD and BMI. DISCUSSION/SIGNIFICANCE OF IMPACT: Psychiatric genetics studies lack ancestral diversity among participants, decreasing their generalizability, and possibly increasing health disparities, especially for diseases like BD, which is often misdiagnosed and untreated in AAs. This work propels us towards understanding the genetics of BD and obesity in this underrepresented population.

OBJECTIVES/GOALS: Multivariate regression is used for surgical outcomes analyses; but does not allow for evaluation of all variables. Machine learning could be the perfect alternative to address this issue. Our aim was to evaluate whether machine learning is a feasible alternative to evaluate surgical outcomes. METHODS/STUDY POPULATION: H-CUP National Inpatient Sample database was queried for adult patients with colorectal cancer who underwent colorectal resection, while the NSQIP database was queried for adult patients with rectal cancer who underwent proctectomy. A multivariate regression analysis was performed to assess risk factors associated with 30-day complications following those procedures. Subsequently, machine learning techniques of under-sampling and oversampling were applied to the same datasets for the evaluation of risk factors for the same outcome. These techniques were used to achieve a larger population sample size and to detect statistical significance. Results between the two methodologies were compared. RESULTS/ANTICIPATED RESULTS: Multivariate regression revealed that open approach, gender, race, geographic location, number of comorbidities, and type of insurance was associated with increased 30-day mortality in colorectal resection patients. Conversely, the use of machine learning revealed that preoperative weight loss, preexistent chest heart failure, renal failure or perivascular disease were strongly associated with 30-day mortality. For proctectomy patients, multivariate regression found no association between surgical approach and 30-day mortality. However, machine learning revealed gender, hypertension, and reoperation to be strongly associated with 30-day mortality. DISCUSSION/SIGNIFICANCE OF IMPACT: Machine learning enabled multiple combinations that were not possible to examine in a conventional multivariate regression analysis. Machine learning compared to traditional multivariate regression produced significantly different outcomes, highlighting the need for in depth of these methodologies.

OBJECTIVES/GOALS: Wheezing has been shown to be associated with use of cigarettes, and more recently, electronic nicotine delivery systems (ENDS). This study assessed the association of poly use of tobacco products with wheezing among a national representative sample of US adult current tobacco users. METHODS/STUDY POPULATION: Data from the Population Assessment of Tobacco and Health (PATH) Study Wave 3 (W3) were used. Weighted prevalences of self-reported wheezing and related respiratory symptoms for non-users compared to users of cigarettes, ENDS, cigars, and any combination of these products (poly use of tobacco products) were presented for 28,082 adults. The cross-sectional association of tobacco use with self-reported wheezing and other related respiratory symptoms was assessed using weighted multivariable and ordinal logistic regression with consideration of complex sampling design. RESULTS/ANTICIPATED RESULTS: Most adults who reported on wheezing symptoms did not currently use cigarettes, ENDS or cigars (79%), 15% used cigarettes, 3% used a combination of cigarettes, ENDS and cigars, 1% used ENDS, and 1% used cigars. Significantly higher odds of ever had wheezing or whistling in chest at any time in the past was observed among current cigarette (adjusted OR: 2.62, 95%CI: 2.35, 2.91), ENDS (1.49, 95%CI: 1.14, 1.95), and poly users (2.67, 95%CI: 2.26, 3.16) compared to non-users. No differences were seen for cigar use. Polytobacco use was associated with a higher odds of ever wheezing when compared to ENDS (1.61, 95%CI: 1.19, 2.17) and cigar use (2.87, 95%CI: 1.93, 4.26), but not cigarettes. DISCUSSION/SIGNIFICANCE OF IMPACT: Wheezing is associated with the use of cigarettes, ENDS, or any combination of cigarette, ENDS and cigars likely due to the inhalation of noxious chemicals and gases found in the smoke of cigarettes and ENDS that are likely to increase the odds of experiencing wheezing. CONFLICT OF INTEREST DESCRIPTION: MLG serves as a paid consultant for Johnson & Johnson and has received research grant from Pfizer, manufacturers of smoking cessation medications. The other authors have no conflicts to declare.

OBJECTIVES/GOALS: To evaluate the FAITH! (Fostering African-American Improvement in Total Health) App mHealth lifestyle intervention by using post-intervention feedback obtained from participants in our intervention pilot study. METHODS/STUDY POPULATION: We used qualitative methods (focus groups) to elicit post-intervention feedback. Participants who completed the pilot study were recruited to one of two focus groups. Semi-structured focus groups were conducted to explore participants’ views on the app functionality, utility and satisfaction as well as its impact on healthy lifestyle change. Sessions were audio-recorded, transcribed verbatim and qualitative data were analyzed by systematic text condensation thematic analysis. RESULTS/ANTICIPATED RESULTS: Nine individuals participated (N = 4 and N = 5) in each of the two focus groups. Their mean age was 47.9 years (SD 12.1), 67% were women, and all had at least an education level of some college. Six overarching themes emerged from the data: (1) overall impression, (2) content usefulness (3) formatting, (4) implementation, (5) impact and (6) suggestions for improvement. Underpinning the themes was a high level of agreement that the intervention facilitated healthy behavioral change through cultural tailoring, multimedia education modules and social networking. Among the suggestions for improvement were streamlining of app self-monitoring features, personalization based on individual’s cardiovascular risk and attentiveness to nuanced cultural perspectives. DISCUSSION/SIGNIFICANCE OF IMPACT: This formative evaluation found the FAITH! App mHealth lifestyle intervention had high reported satisfaction and impact on the health-promoting behaviors of African-Americans, thereby improving their overall cardiovascular health. The findings provide further support for the acceptability of mHealth interventions among African-Americans. CONFLICT OF INTEREST DESCRIPTION: None.

OBJECTIVES/GOALS:

• To improve and expand health and research literacy throughout Indiana by sharing health-focused resources and research outcomes.

• To encourage and increase health research participation throughout Indiana by promoting health research opportunities, including clinical studies.

METHODS/STUDY POPULATION:

• Discover and understand community concerns and barriers to good health and clinical research participation by providing a platform for individuals and communities to share their voices.

• Educate Indiana residents on the importance of participating in health research.

• Engage with the community to meet them where they are (online) and continue to build relationships throughout the state.

• Promote healthy living for Indiana residents by sharing health education and resources from existing state health organizations and initiatives.

• Develop and maintain the largest statewide database of research volunteers.

RESULTS/ANTICIPATED RESULTS:

• The anticipated results from this program include engagement of all populations and all communities throughout the state in conversation and education around good health and health research, as well as participation in health research across the CTSI’s partner organizations. Large-scale growth is expected in both the online community and consented volunteer registry is expected to include and engage racially and ethnically diverse populations, as well as special health populations, such as representatives of rural communities, aged, rare disease survivors, and transgender individuals.

DISCUSSION/SIGNIFICANCE OF IMPACT:

• Thorough this work, the Indiana CTSI has developed a unique program, educating the public about health research and opportunities to participate, while simultaneously supporting research departments with marketing promotion of their efforts, and a ready statewide volunteer community.

OBJECTIVES/GOALS: Mobile health applications are widely used by the public but vary in how they are classified and regulated. This study examines the evidence of the safety and efficacy of mobile medical applications specifically focusing on those that are used to manage diabetes. METHODS/STUDY POPULATION: To understand the current regulatory landscape of mobile health applications (mHealth apps) for diabetes, a literature survey was conducted using the Pubmed database. Top mHealth apps were identified by searching the Apple store website using 10 key terms associated with diabetes management applications. A maximum of ten results, when available for each key term, were studied by exploring the FDA databases to understand how the products were regulated and if any were subject to recalls. These selected mHealth apps were also searched on clinicaltrials.gov to see if there were ongoing or completed clinical trials and if the trials were designed to include efficacy and safety outcome measures. RESULTS/ANTICIPATED RESULTS: Of the 71 mHealth apps for diabetes management that were identified, 16 were regulated. These products spanned a diverse range of functions including device data and decision support systems. Although 11 had clinical trial data demonstrating efficacy, only 4 had data demonstrating both efficacy and safety. Two of the regulated applications were subject to product recalls due to programming errors that resulted in incorrect insulin dose recommendations. These two applications had clinical trials evaluating efficacy but not safety. The companies noted that the incorrect insulin calculation from their respective mHealth app could cause either a low- or high-impact hypoglycemic event. DISCUSSION/SIGNIFICANCE OF IMPACT: With little to no clinical trial data to support their safety and efficacy, mHealth apps in the diabetes marketplace pose risks for patients as evidenced by recent safety-related recalls. The results of this study indicate that these products may need to be more tightly regulated.

OBJECTIVES/GOALS: Aims 1&2: Develop (1) and implement (2) online, guided self-help intervention for ED psychopathology and weight reduction. Aim 3: Follow-up to track remission of ED psychopathology and symptoms and WL maintenance at end of treatment and 6-months. METHODS/STUDY POPULATION: N = 60 college students meeting criteria (clinical/sub-clinical binge-type ED with BMI > 25) will complete a baseline survey and then will be randomized into a condition. Students in the intervention group (n = 30) will be offered 8 weeks of an online, guided self-help intervention for ED and WL. Students in the control group (n = 30) will receive an email message to seek support from Student Health Services. All participants will receive follow-ups 9 weeks and 6 months after baseline. Data analysis will compare Eating Disorder Examination Questionnaire (EDE-Q) scores and WL (change in BMI) at all three time-points. Group comparisons will be assessed via two-way mixed-model ANOVA. RESULTS/ANTICIPATED RESULTS: Recruitment is still ongoing. Data collected by the time of the conference will be presented on the poster. DISCUSSION/SIGNIFICANCE OF IMPACT: Online, guided self-help interventions have been used for WL, as well as for treatment of EDs separately, but no program exists to manage these commonly comorbid conditions concurrently. Thus, this pilot study will examine the effectiveness of combined programs to breach this treatment gap.

OBJECTIVES/GOALS: AA are over-represented on the waitlist for kidney transplant and are often unaware of how waitlist acceptance practices differ across transplant programs and influence access to transplant. We will develop a culturally sensitive transplant program report card to communicate these variations. METHODS/STUDY POPULATION: Scientific Registry of Transplant Recipients (SRTR) data will be used to identity clinical factors strongly associated with AA access to transplant. Interviews and focus groups with AA kidney transplant candidates and their families will collect feedback on the SRTR report card and inform the development of the culturally sensitive report card. Additional focus groups will evaluate its effect on knowledge and medical decision making. We will collaborate with the stakeholders, including AA transplant candidates and their families, transplant programs, SRTR, and providers, to identify strategies to disseminate the report card in the AA community RESULTS/ANTICIPATED RESULTS: To date, no investigation has systematically collected feedback on the SRTR transplant program report card from AA candidates to ensure that the tool is accessible and effective in the AA community. We hypothesize that a culturally sensitive report card will improve AA candidates’ knowledge of program factors that impact access to transplant and enable informed decisions about where they pursue a transplant evaluation. The results of this study have the potential to change how AA patients are counselled while seeking transplantation. DISCUSSION/SIGNIFICANCE OF IMPACT: A culturally sensitive report card can reach more AA patients and enable more informed decision making by providing education about differences in transplant programs that may impact their access to transplant. In the future, we will design a trial to evaluate the prototype.

OBJECTIVES/GOALS: To describe preliminary results of Alzheimer’s and dementia caregivers’ (CGs) mobile app use and intention to adopt mHealth apps for their own chronic condition self-management. To discuss implications for designing and implementing mHealth interventions for CGs. METHODS/STUDY POPULATION: This study aims to recruit 110 racially and ethnically diverse family caregivers (CGs) who have a chronic condition, provide care for persons with Alzheimer’s disease or related dementias, and have access to a mobile device. This is a cross-sectional correlational study collecting data with computer-assisted telephone interviews stored through REDCap. The study survey was created using existing surveys about mobile app use; relevant, well-validated research instruments; and questions from the U.S. Census and other national surveys. CGs are being actively recruited from the Baltimore-Washington metropolitan area using various recruitment strategies that have been effective in prior studies. RESULTS/ANTICIPATED RESULTS: The majority of CGs used websites (86%), mobile devices (68%) or apps (53%) to manage their own health. CGs using health-related apps were tracking their exercise (60%), diet (60%), medical records (50%), and physical health measures (50%). More than 4 out of 5 (82%) predicted they would use mobile apps to self-manage their chronic condition, though only 68% actually planned to use them. 86% of CGs were using mobile apps for non-health related purposes, with the most popular app being weather (90%), followed by social media (74%), music/entertainment (68%), and banking/business apps (63%). CGs used weather and social media apps most often (2 or more times/day) and spent 9 hours/week on apps. DISCUSSION/SIGNIFICANCE OF IMPACT: Websites and mobile apps appear to be feasible modes to deliver health interventions to CGs. Researchers should consider including features of apps most frequently used by CGs, such as the weather, ways to connect with others, and music/entertainment, when delivering mHealth interventions to CGs.

OBJECTIVES/GOALS: 1) In this literature review we want to explore the literature on DMHI (Interventions delivered via digital technologies, such as smartphones, websites, or text messaging), specifically designed to treat Posttraumatic Stress Disorder (PTSD), and/or to promote positive change & resilience after trauma. 2) We also want to evaluate the literature in terms of the theoretical model used in each DMHI, engagement, effectiveness, & potential harms/challenges. METHODS/STUDY POPULATION: We will review the literature that describes DMHI for PTSD, resilience, & positive change in persons exposed to psychological trauma (Exposure to actual or threatened death, serious injury, or sexual violence, as defined by the fifth edition of the Diagnostic & Statistical Manual of Mental Disorders). We will review the following databases: PsychINFO, EBSCOhost, PubMed, & PsychiatryOnline. The following inclusion criteria will be used: 1) Interventions delivered by computer, smartphones, or online, 2) studies published between 1999-2019. Exclusion criteria will include reviews, opinion, or discussion articles, & unpublished works. RESULTS/ANTICIPATED RESULTS: We expect to find that the most popular therapeutic model for DMHI is cognitive behavioral therapy. We also expect to find a higher number of web-based interventions, as opposed to phone-based interventions, or other types of DMHI. We also expect to find variable drop-out rates, low engagement, & small to moderate effect sizes. DISCUSSION/SIGNIFICANCE OF IMPACT: We expect our contribution to center on evaluating available DMHI for psychological trauma. This systematic literature review is expected to provide scientific justification for the development (or validation), & implementation of a DMHI that takes into account the results of previous studies. This contribution is expected to be significant because it will help in choosing, or developing an effective future intervention with DMHI. CONFLICT OF INTEREST DESCRIPTION: There is no conflict of interest in this study.

OBJECTIVES/GOALS: Geographic and linguistic isolation is associated with negative mental health outcomes, including increased risk for suicide, among ethnic/racial minorities. This study explores the feasibility of using smartphone technology with active and passive sensing to assess mental health symptoms and social behavior among at risk Spanish-speakers. METHODS/STUDY POPULATION: Participants were 13 Spanish-speaking adult outpatients who reported hopelessness/suicide ideation in the last month. Participants completed a baseline interview, 2-weeks of remote ecological momentary assessments (EMA; 4xday) using a smartphone with optional passive sensing (GPS, ambient sound recording), and a final interview. All participants identified as Hispanic (84.6% female, M age = 42.24 years). 53.8% identified as White, with 46.2% reporting race as Other (e.g., Indio, Trigueña). On average, participants had lived in the USA for 6.56 years (SD = 12.63 years). A majority (69.2%) met for Major Depressive Episode Current. At baseline, 53.8% reported passive and 23.1% reported active suicide ideation in the last month. 46.2% of participants reported a previous suicide attempt. RESULTS/ANTICIPATED RESULTS: A majority (84.6%) of participants consented to all passive data collection (GPS tracking and ambient sound recording). One participant dropped out after baseline and did not complete the EMA study portion. Participants completed on average 76.93% EMA survey instances (SD = 18.01%). Baseline depression/anxiety severity were significantly positively associated with symptom severity at 2-week follow-up (p < .01); however, baseline suicide ideation was not associated with ideation at follow-up. Participants did not report significant changes in mood or ideation from baseline to 2-week follow-up. Symptom severity at baseline was not associated with EMA instances completed. Percent of EMA instances completed were also not associated with symptom severity at follow-up, controlling for baseline severity. DISCUSSION/SIGNIFICANCE OF IMPACT: Results support the feasibility of smartphones to assess mental health symptoms and behaviors in real time, real world settings with Spanish-speakers. A majority of patients consented to active and passive remote assessments. Adherence to remote EMA was good and study attrition was minimal. Implications and future directions will be discussed.

OBJECTIVES/GOALS: To demonstrate how brief online audiovisual presentations, “learning shots”, informed by evaluation, can be used to quickly and effectively provide essential just-in-time research-related education in the complex and evolving world of clinical and translational science. METHODS/STUDY POPULATION: “Learning shots” are an educational tool, originally developed by the University of Virginia IRB for Health Sciences Research, that cover a broad spectrum of methodological, regulatory, and ethical topics in research. They are designed to be responsive to adult learners, a rapidly changing research environment, and the need for flexible offerings. Learning shots target different groups involved in research including clinical research coordinators, investigators, and trainees. A survey was used to assess the role of learning shots in meeting learning needs. Moving forward, continuous evaluation will occur through the addition of tracking and a short evaluation survey to each learning shot. RESULTS/ANTICIPATED RESULTS: The University of Virginia has an online library of over 30 learning shots. Learning shots are used to cover foundational topics (e.g. GCP) as well as more specialized topics (e.g. comparative effectiveness research). They can also be used to quickly respond to breaking issues (e.g. single IRB review). In an initial survey targeting University of Virginia clinical research coordinators, 54 (68%) of 79 respondents reported having viewed a learning shot. Among those who had, 41 (84%) of 49 respondents reported that learning shots were helpful to their learning needs. Continuous evaluation is expected to further inform how learning shots meet clinical and translational science education needs. DISCUSSION/SIGNIFICANCE OF IMPACT: Learning shots are an innovative and versatile educational tool for clinical and translational science that can be used to quickly and effectively convey important research information in response to an increasingly complex research environment and diverse learner needs.

OBJECTIVES/GOALS: We conducted a review of CTSA websites to understand the current landscape for CRP institutional professional development and training revealed in the CTSA hub websites. METHODS/STUDY POPULATION: We accessed and reviewed 59 currently funded CTSA hub websites for evidence of CRP training opportunities. Parameters reviewed included: 1) opportunities were specified for CRPs versus K and T trainees; 2) mandated training; 3) leveling; 4) delivery methods/resources; 5) public accessibility; 6) unique features. The website reviews informed a REDCap survey sent to the CTSA Administrators (n = 149) and the Coordinator Taskforce (n = 105) listservs to gain additional knowledge of CRP training available at the institution. A subsequent repeat review of the CTSA hub websites will be conducted to determine evolving trends. RESULTS/ANTICIPATED RESULTS: A total of 40 responded to the survey from 59 CTSA hubs. Survey results are being analyzed. Website review data are being tabulated and the subsequent review of websites will be collected in February. Those findings are pending and will include a comparison of prior findings. 42% of CRP hubs list CRP training within the CTSA hub website. Required onboarding training (beyond CITI certificates) is revealed for some hubs (15%). DISCUSSION/SIGNIFICANCE OF IMPACT: On our initial website review less than half of the CTSA hub websites list specific CRP training on their website. Many were hidden behind firewalls and could not be reviewed for content. The REDCap Survey will provide more granular descriptions of programs. Data from a second website review will be collected for comparison. Based on a preliminary re-review of sites, there is a suggestion of increasing CRP workforce development information. CTSAs are well-positioned to be a central hub for promoting educational excellence of the institutional workforce, for medical centers and in other venues where clinical research is performed.

OBJECTIVES/GOALS: Project Extension for Community Health Outcomes (ECHO), a telehealth model, was launched at Penn State University in 2018 to connect specialists with community providers to provide education on best clinical practices. We aim to describe clinical topics covered and relevant provider level outcomes. METHODS/STUDY POPULATION: The heart of the ECHO model is a hub-and-spoke knowledge-sharing system. The ECHO model has four core principles: 1) use technology to leverage scarce resources; 2) share best practices to reduce disparities; 3) employ case-based learning to master complexity; 4) monitor outcomes to ensure benefit. Unlike telemedicine, where outside specialists assume the care of the patient, Project ECHO is a guided learning community aimed at practice improvement: providers receive mentoring and feedback on de-identified patient cases, strengthen their skillset, and retain responsibility for their patients. RESULTS/ANTICIPATED RESULTS: Clinical topics launched include Medication Assisted Treatment for Opioid Use Disorder, Ehlers Danlos Syndrome, Polyneuropathy, and Dementia. In addition, we launched a nutrition-focused ECHO with Boy Scout summer camp leaders in 26 states, reaching 107,347 scouts. Over the past year we have reached 118 clinicians in 62 clinics within 19 counties in Pennsylvania, providing a total of 268 CME hours. These providers have treated 2,294 patients and reported increased knowledge (94%), decreased sense of professional isolation (86%), and improvement in ability to provide patient care (92%) following completion of an ECHO series. DISCUSSION/SIGNIFICANCE OF IMPACT: Project ECHO is a powerful telehealth model providing mentorship and education to clinicians, encouraging them to treat more complex cases in their primary care clinics. As a result, patients receive higher quality care when they need it, and close to home, particularly important in rural areas.