Health Information Technology Commons^™

Supraventricular Tachycardia Associated With Repeat Cesarean Section Under Spinal Anesthesia, Malik A Althobiani, Rebecca Shuttleworth, John Conway, Jonathan Dainton, Anna Duckworth, Ana Jorge Da Ponte, Jessica Mandizha, Joseph W Lanario, Michael A Gibbons, Sarah Lines, Chris J Scotton, John R Hurst, Joanna C Porter, Anne-Marie Russell

Faculty, Staff and Student Publications

INTRODUCTION: Patients diagnosed with Interstitial Lung Diseases (ILD) use devices to self-monitor their health and well-being. Little is known about the range of devices, selection, frequency and terms of use and overall utility. We sought to quantify patients' usage and experiences with home digital devices, and further evaluate their perceived utility and barriers to adaptation.

METHODS: A team of expert clinicians and patient partners interested in self-management approaches designed a 48-question cross-sectional electronic survey; specifically targeted at individuals diagnosed with ILD. The survey was critically appraised by the interdisciplinary self-management group at Royal Devon University Hospitals NHS Foundation Trust during …

Perceptions Of Acute Care Telemedicine Among Caregivers For Persons Living With Dementia: A Qualitative Study, Anita Chary, Norvin Hernandez, Ana Paulina Rivera, Vivian Ramont, Tracey Obi, Ilianna Santangelo, Christine Ritchie, Hardeep Singh, Emily Hayden, Aanand D Naik, Shan Liu, Maura Kennedy

Faculty, Staff and Student Publications

Persons living with dementia (PLWD) have high emergency department (ED) utilization. Little is known about using telemedicine with PLWD and caregivers as an alternative to ED visits for minor acute health problems. This qualitative interview-based study elicited caregivers' perspectives about the acceptability of telemedicine for acute complaints. We performed telephone interviews with 28 caregivers of PLWD from two academic EDs, one in the Northeast and another in the South. Using a combined deductive-inductive approach, we coded interview transcripts and elucidated common themes by consensus. All caregivers reported they would need to participate in the telemedicine visit to help overcome communication …

Comparing The Use And Effectiveness Of In-Person And Remote Physical Education Delivery During The Covid-19 Pandemic, Kempson Onadeko, Timothy J Walker, Derek W Craig, Jacob Szeszulski, Andjelka Pavlovic, Laura F Defina, Harold W Kohl

Faculty, Staff and Student Publications

BACKGROUND: Physical Education is a key component to improve youth health, but there is limited information on Physical Education delivery in different formats.

PURPOSE: We compared PE formats (in-person versus remote) across evaluation aspects: weekly minutes; perceived effectiveness; and student-to-teacher ratio.

METHODS: We distributed questionnaires (2020-2021 school year) to school contacts who represented NFL Play 60 FitnessGram

RESULTS: Among 165 schools, 10% (n=17) offered in-person instruction, 31% (n=51) offered remote instruction, and 59% offered both (n=97). Results revealed higher in-person PE minutes (77.2±7.3) compared to remote minutes (67.1±14.6), but results were not significantly different (p=0.19). School contacts reported significantly more …

Stroke Survivors’ Telemedicine Experiences During The Covid-19 Pandemic: A Phenomenological Investigation, Barbara Kimmel, Annette Walder, Anette Ovalle, Chethan P Venkatasubba Rao, Sean I Savitz, Mark Goldberg, Steven Warach, Salvador Cruz-Flores, Daiwai M Olson, Jane A Anderson

Faculty, Staff and Student Publications

PURPOSE: This study aimed to describe stroke survivors' experiences receiving telemedicine visits at the Lone Star Stroke Consortium during the COVID-19 pandemic.

MATERIALS AND METHODS: A qualitative descriptive phenomenological design was applied to gather patients' telemedicine experiences through in-depth interviews, using a study guide. Audio-recorded interviews were conducted via ZOOM and transcribed verbatim. Two independent reviewers used the Giorgi descriptive method to analyze the data and search for the essence of stroke survivors' follow-up telemedicine experiences during the COVID-19 pandemic.

RESULTS: Fifteen underserved patients were recruited: mean age, 51.8 (15.7), and 9 (60%) females. Three themes emerged: (1) vivid memory …

Patients With Floaters: Answers From Virtual Assistants And Large Language Models, Gloria Wu, Weichen Zhao, Adrial Wong, David A Lee

Faculty, Staff and Student Publications

OBJECTIVES: "Floaters," a common complaint among patients of all ages, was used as a query term because it affects 30% of all people searching for eye care. The American Academy of Ophthalmology website's "floaters" section was used as a source for questions and answers (www.aao.org). Floaters is a visual obstruction that moves with the movement of the eye. They can be associated with retinal detachment, which can lead to vision loss. With the advent of large language model (LLM) chatbots ChatGPT, Bard versus virtual assistants (VA), Google Assistant, and Alexa, we analyzed their responses to "floaters."

METHODS: Using AAO.org, "Public …

Post-Covid-19 Cognitive Symptoms In Patients Assisted By A Teleassistance Service: A Retrospective Cohort Study, Lívia Paula Freire Bonfim, Thais Rotsen Correa, Bruno Cabaleiro Cortizo Freire, Thais Marques Pedroso, Daniella Nunes Pereira, Thalita Baptisteli Fernandes, Luciane Kopittke, Clara Rodrigues Alves De Oliveira, Antonio Lucio Teixeira, Milena Soriano Marcolino

Faculty, Staff and Student Publications

INTRODUCTION: Four years after the onset of the COVID-19 pandemic, the frequency of long-term post-COVID-19 cognitive symptoms is a matter of concern given the impact it may have on the work and quality of life of affected people.

OBJECTIVE: To evaluate the incidence of post-acute COVID-19 cognitive symptoms, as well as the associated risk factors.

METHODS: Retrospective cohort, including outpatients with laboratory-confirmed COVID-19 and who were assisted by a public telehealth service provided by the Telehealth Network of Minas Gerais (TNMG), during the acute phase of the disease, between December/2020 and March/2022. Data were collected through a structured questionnaire, applied …

Acceptability And Use Of An Online Health Priorities Self-Identification Tool For Older Adults: A Qualitative Investigation, Emily L Mroz, Kizzy Hernandez-Bigos, Jessica Esterson, Eliza Kiwak, Aanand Naik, Mary E Tinetti

Faculty, Staff and Student Publications

OBJECTIVE: To examine the use of a web-based, self-directed health priorities identification tool for older adults with multiple chronic conditions (MCCs).

METHODS: We recruited a gender- and racially-diverse, highly educated sample of older adults with MCCs to engage with our My Health Priorities tool, then complete a semi-structured interview. Thematic analysis was used to examine interview transcripts.

RESULTS: Twenty-one participants shared perspectives on the acceptability and use of the tool. Three themes (with eleven subthemes) were generated to describe: website

CONCLUSION: Participants found this tool acceptable and easy to use, describing a variety of benefits of the priorities self-identification process …

Selecting Patient-Reported Outcome Measures For A Patient-Facing Technology, Priyank Raj, Youmin Cho, Yun Jiang, Yang Gong

Faculty, Staff and Student Publications

OBJECTIVE: This article provides insight into our process and considerations for selecting patient-reported outcome measures (PROMs) designed for self-reporting symptoms and quality-of-life among breast cancer (BCA) patients undergoing oral anticancer agent treatment via a patient-facing technology (PFT) platform.

METHODS: Following established guidelines, we conducted a thorough assessment of a specific set of PROMs, comparing their content to identify the most suitable options for studying BCA patients.

RESULTS: We recommend utilizing the combination of EORTC QLQ-C30 + EORTC QLQ-BR45 as the preferred instrument, especially when developing a dedicated "breast cancer-only" application.

DISCUSSION: When developing and maintaining a dashboard for a PFT …

Will You Go The Distance? A Satisfaction Survey Of Telemedicine In Sexual Medicine, Gal Saffati, Taher Naeem, Jordan Kassab, Daniela Orozco Rendon, Charles Green, Larry I Liphsultz, Mohit Khera

Faculty, Staff and Student Publications

BACKGROUND: The success of telemedicine depends on patient satisfaction with the care that they receive, which is impacted by the ease of use of the technology, quality of the connection, and perceived effectiveness of care.

AIM: The study sought to evaluate patient satisfaction with telemedicine services in a high-volume andrology clinic.

METHODS: We included all patients who had a telemedicine appointment between January 1, 2020, and August 22, 2022. Demographic information was gathered, and a satisfaction survey was conducted using REDCap software. Data were grouped into 2 age categories, with ≥50 years as the cutoff (19-50 years; >50 years). The …

Innovation Process And Industrial System Of Us Food And Drug Administration-Approved Software As A Medical Device: Review And Content Analysis, Jiakan Yu, Jiajie Zhang, Shintaro Sengoku

Faculty, Staff and Student Publications

BACKGROUND: There has been a surge in academic and business interest in software as a medical device (SaMD). SaMD enables medical professionals to streamline existing medical practices and make innovative medical processes such as digital therapeutics a reality. Furthermore, SaMD is a billion-dollar market. However, SaMD is not clearly understood as a technological change and emerging industry.

OBJECTIVE: This study aims to review the landscape of SaMD in response to increasing interest in SaMD within health systems and regulation. The objectives of the study are to (1) clarify the innovation process of SaMD, (2) identify the prevailing typology of such …

Evaluation Of Negative Binomial And Zero-Inflated Negative Binomial Models For The Analysis Of Zero-Inflated Count Data: Application To The Telemedicine For Children With Medical Complexity Trial, Kyung Hyun Lee, Claudia Pedroza, Elenir B C Avritscher, Ricardo A Mosquera, Jon E Tyson

Faculty, Staff and Student Publications

BACKGROUND: Two characteristics of commonly used outcomes in medical research are zero inflation and non-negative integers; examples include the number of hospital admissions or emergency department visits, where the majority of patients will have zero counts. Zero-inflated regression models were devised to analyze this type of data. However, the performance of zero-inflated regression models or the properties of data best suited for these analyses have not been thoroughly investigated.

METHODS: We conducted a simulation study to evaluate the performance of two generalized linear models, negative binomial and zero-inflated negative binomial, for analyzing zero-inflated count data. Simulation scenarios assumed a randomized …

Narrative Review Of The Role Of Technology In Pediatric Diabetes: From Testing Blood Glucose To Subcutaneous Automated Therapy And Hope For Cure, Michael Yafi, Avni Shah, Katherine Velez

Faculty, Staff and Student Publications

BACKGROUND AND OBJECTIVE: Type 1 diabetes, the most common cause of diabetes in pediatrics, is defined by the hyperglycemia that results from the permanent autoimmune damage to the pancreas. The Diabetes Control and Complications Trial (DCCT) demonstrated that strict glycemic control targeting lower HbA1c goals can both delay the onset and progression of its complications that include diabetic neuropathy, nephropathy, retinopathy, and increased cardiovascular events. Our primary objective is to review the literature available regarding the technology applied for the treatment of diabetes, not only aiding patients' quality of life but addressing its effects on hypoglycemia and reduced risk of …

Abnormal Motion Capture In Acute Stroke (Bionics): A Low-Cost Tele-Evaluation Tool For Automated Assessment Of Upper Extremity Function In Stroke Patients, Syed A Zamin, Kaichen Tang, Emily A Stevens, Melissa Howard, Dorothea M Parker, Allyson Seals, Xiaoqian Jiang, Sean Savitz, Shayan Shams

Faculty, Staff and Student Publications

BACKGROUND: The incidence of stroke and stroke-related hemiparesis has been steadily increasing and is projected to become a serious social, financial, and physical burden on the aging population. Limited access to outpatient rehabilitation for these stroke survivors further deepens the healthcare issue and estranges the stroke patient demographic in rural areas. However, new advances in motion detection deep learning enable the use of handheld smartphone cameras for body tracking, offering unparalleled levels of accessibility.

METHODS: In this study we want to develop an automated method for evaluation of a shortened variant of the Fugl-Meyer assessment, the standard stroke rehabilitation scale …

Cancer Patients' Preferences And Perceptions Of Advantages And Disadvantages Of Telehealth Visits During The Covid-19 Pandemic, Deepika Kumar, Nancy Gordon, Constanza Zamani, Tammy Sheehan, Ernesto Martin, Olga Egorova, Jessica Payne, Tatjana Kolevska, Elad Neeman, Raymond Liu

Faculty, Staff and Student Publications

PURPOSE: We aimed to ascertain oncology patients' perceptions of telehealth versus in-person (IP) visits for different types of clinical encounters.

METHODS: We surveyed adults undergoing cancer treatment at Kaiser Permanente Northern California infusion centers between November 2021 and May 2022 using a self-administered questionnaire. Patients were asked about visit modality preferences (video, phone, and IP) for six types of clinical discussions, overall advantages and disadvantages of telehealth (video or phone) versus IP modalities, and barriers to video visit use.

RESULTS: The 839 patients who completed surveys in English were 63% female; median age 63 years; 64% White; and 73% college-educated …

Wearable Biosensor With Molecularly Imprinted Conductive Polymer Structure To Detect Lentivirus In Aerosol, Jaskirat Singh Batra, Ting-Yen Chi, Mo-Fan Huang, Dandan Zhu, Zheyuan Chen, Dung-Fang Lee, Jun Kameoka

Faculty, Staff and Student Publications

The coronavirus disease (COVID-19) pandemic has increased pressure to develop low-cost, compact, user-friendly, and ubiquitous virus sensors for monitoring infection outbreaks in communities and preventing economic damage resulting from city lockdowns. As proof of concept, we developed a wearable paper-based virus sensor based on a molecular imprinting technique, using a conductive polyaniline (PANI) polymer to detect the lentivirus as a test sample. This sensor detected the lentivirus with a 4181 TU/mL detection limit in liquid and 0.33% to 2.90% detection efficiency in aerosols at distances ranging from 30 cm to 60 cm. For fabrication, a mixture of a PANI monomer …

Add-On Soft Electronic Interfaces For Continuous Cuffless Blood Pressure Monitoring, Myeong Namkoong, Balaji Baskar, Lakhvir Singh, Heng Guo, Justin Mcmurray, Kimberly Branan, Md Saifur Rahman, Chin-To Hsiao, Josh Kuriakose, Joanna Hernandez, Arda A Arikan, Luis E Garza-Rivera, Gerard L Coté, Limei Tian

Faculty, Staff and Student Publications

Continuous monitoring of arterial blood pressure is clinically important for the diagnosis and management of cardiovascular diseases. Soft electronic devices with skin-like properties show promise in a wide range of applications, including the human-machine interface, the Internet of things, and health monitoring. Here, we report the use of add-on soft electronic interfaces to address the connection challenges between soft electrodes and rigid data acquisition circuitry for bioimpedance monitoring of cardiac signals, including heart rate and cuffless blood pressure. Nanocomposite films in add-on electrodes provide robust electrical and mechanical contact with the skin and the rigid circuitry. We demonstrate bioimpedance sensors …

Effectiveness Of An Emergency Department-Based Machine Learning Clinical Decision Support Tool To Prevent Outpatient Falls Among Older Adults: Protocol For A Quasi-Experimental Study, Daniel J Hekman, Amy L Cochran, Apoorva P Maru, Hanna J Barton, Manish N Shah, Douglas Wiegmann, Maureen A Smith, Frank Liao, Brian W Patterson

Faculty, Staff and Student Publications

Background

Emergency department (ED) providers are important collaborators in preventing falls for older adults because they are often the first health care providers to see a patient after a fall and because at-home falls are often preceded by previous ED visits. Previous work has shown that ED referrals to falls interventions can reduce the risk of an at-home fall by 38%. Screening patients at risk for a fall can be time-consuming and difficult to implement in the ED setting. Machine learning (ML) and clinical decision support (CDS) offer the potential of automating the screening process. However, it remains unclear whether …

Non-Melanoma Skin Cancer Detection In The Age Of Advanced Technology: A Review, Haleigh Stafford, Jane Buell, Elizabeth Chiang, Uma Ramesh, Michael Migden, Priyadharsini Nagarajan, Moran Amit, Dan Yaniv

Faculty, Staff and Student Publications

Skin cancer is the most common cancer diagnosis in the United States, with approximately one in five Americans expected to be diagnosed within their lifetime. Non-melanoma skin cancer is the most prevalent type of skin cancer, and as cases rise globally, physicians need reliable tools for early detection. Artificial intelligence has gained substantial interest as a decision support tool in medicine, particularly in image analysis, where deep learning has proven to be an effective tool. Because specialties such as dermatology rely primarily on visual diagnoses, deep learning could have many diagnostic applications, including the diagnosis of skin cancer. Furthermore, with …

Deep Single-Cell Rna-Seq Data Clustering With Graph Prototypical Contrastive Learning, Junseok Lee, Sungwon Kim, Dongmin Hyun, Namkyeong Lee, Yejin Kim, Chanyoung Park

Faculty, Staff and Student Publications

MOTIVATION: Single-cell RNA sequencing enables researchers to study cellular heterogeneity at single-cell level. To this end, identifying cell types of cells with clustering techniques becomes an important task for downstream analysis. However, challenges of scRNA-seq data such as pervasive dropout phenomena hinder obtaining robust clustering outputs. Although existing studies try to alleviate these problems, they fall short of fully leveraging the relationship information and mainly rely on reconstruction-based losses that highly depend on the data quality, which is sometimes noisy.

RESULTS: This work proposes a graph-based prototypical contrastive learning method, named scGPCL. Specifically, scGPCL encodes the cell representations using Graph …

Use Of Telemedicine For Postdischarge Assessment Of The Surgical Wound: International Cohort Study, And Systematic Review With Meta-Analysis, Nihr Global Health Research Unit On Global Surgery, Globalsurg Collaborative

Faculty, Staff and Student Publications

OBJECTIVE: This study aimed to determine whether remote wound reviews using telemedicine can be safely upscaled, and if standardized assessment tools are needed.

BACKGROUND: Surgical site infection (SSI) is the most common complication of surgery worldwide, and frequently occurs after hospital discharge. Evidence to support implementation of telemedicine during postoperative recovery will be an essential component of pandemic recovery.

METHODS: The primary outcome of this study was SSI reported up to 30 days after surgery (SSI), comparing rates reported using telemedicine (telephone and/or video assessment) to those with in-person review. The first part of this study analyzed primary data from …

Quehry: A Question Answering System To Query Electronic Health Records, Sarvesh Soni, Surabhi Datta, Kirk Roberts

Faculty, Staff and Student Publications

OBJECTIVE: We propose a system, quEHRy, to retrieve precise, interpretable answers to natural language questions from structured data in electronic health records (EHRs).

MATERIALS AND METHODS: We develop/synthesize the main components of quEHRy: concept normalization (MetaMap), time frame classification (new), semantic parsing (existing), visualization with question understanding (new), and query module for FHIR mapping/processing (new). We evaluate quEHRy on 2 clinical question answering (QA) datasets. We evaluate each component separately as well as holistically to gain deeper insights. We also conduct a thorough error analysis for a crucial subcomponent, medical concept normalization.

RESULTS: Using gold concepts, the precision of quEHRy …

Accuracy Of Administrative Claim Data For Gastric Adenoma After Endoscopic Resection, Ga-Yeong Shin, Hyun Ho Choi, Jae Myung Park, Sang Yoon Kim, Jun Young Park, Donghoon Kang, Yu Kyung Cho, Sung Soo Kim, Myung-Gyu Choi

Faculty, Staff and Student Publications

BACKGROUND/AIMS: Administrative databases provide valuable information for large-cohort studies. This study aimed to evaluate the diagnostic accuracy of an administrative database for resected gastric adenomas.

METHODS: Data of patients who underwent endoscopic resection for benign gastric lesions were collected from three hospitals. Gastric adenoma cases were identified in the hospital database using International Classification of Diseases (ICD) 10-codes. The non-adenoma group included patients without gastric adenoma codes. The diagnostic accuracy for gastric adenoma was analyzed based on the pathological reports of the resected specimen.

RESULTS: Among 5,095 endoscopic resections with codes for benign gastric lesions, 3,909 patients were included in …

Privacy Preservation In Smart Meters: Current Status, Challenges And Future Directions, Jonathan Kua, Mohammad Belayet Hossain, Iynkaran Natgunanathan, Yong Xiang

Faculty, Staff and Student Publications

Recent years have seen the rapid development of technologies in Smart Grids (SGs) to enhance electricity networks with digital and data communication technologies. SGs can proactively detect, react, and respond to dynamic changes in the network. SGs can also enhance the efficiency and reliability of electricity supplies and promote the integration of renewable energy sources. Smart Meters (SMs) are often seen as the first step to a successful implementation of SGs. While SMs enable Utility Providers and consumers to obtain near real-time information of energy consumption, they can also be exploited to infer sensitive consumer data. Therefore, privacy preservation in …

Prediction Of Brain Metastases Development In Patients With Lung Cancer By Explainable Artificial Intelligence From Electronic Health Records, Zhao Li, Rongbin Li, Yujia Zhou, Laila Rasmy, Degui Zhi, Ping Zhu, Antonio Dono, Xiaoqian Jiang, Hua Xu, Yoshua Esquenazi, W Jim Zheng

Faculty, Staff and Student Publications

PURPOSE: Early detection of brain metastases (BMs) is critical for prompt treatment and optimal control of the disease. In this study, we seek to predict the risk of developing BM among patients diagnosed with lung cancer on the basis of electronic health record (EHR) data and to understand what factors are important for the model to predict BM development through explainable artificial intelligence approaches accurately.

MATERIALS AND METHODS: We trained a recurrent neural network model, REverse Time AttentIoN (RETAIN), to predict the risk of developing BM using structured EHR data. To interpret the model's decision process, we analyzed the attention …

Inequities In Telemedicine Use Among Patients With Stroke And Cerebrovascular Diseases: A Tricenter Cross-Sectional Study, Imama A. Naqvi, Audrey S Cohen, Youngran Kim, Jennifer Harris, Mary Carter Denny, Kevin Strobino, Nathan Bicher, Ryan A Leite, Dylan Sadowsky, Comfort Adegboye, Nnedinma Okpala, Munachi Okpala, Sean I Savitz, Randolph S Marshall, Anjail Sharrief

Faculty, Staff and Student Publications

BACKGROUND AND OBJECTIVES: In response to the COVID-19 pandemic, outpatient stroke care delivery was rapidly transformed to outpatient evaluation through video (VTM) and telephone (TPH) telemedicine (TM) visits around the world. We sought to evaluate the sociodemographic differences in outpatient TM use among stroke patients.

METHODS: We conducted a retrospective chart review of outpatients evaluated at 3 tertiary stroke centers in the early period of the pandemic, 3/16/2020 through 7/31/2020. We compared the use of TM by patient characteristics including age, sex, race/ethnicity, insurance status, stroke type, patient type, and site. The association between TM use and patient characteristics was …

A Scoping Review Of Digital Health Interventions For Combating Covid-19 Misinformation And Disinformation, Katarzyna Czerniak, Raji Pillai, Abhi Parmar, Kavita Ramnath, Joseph Krocker, Sahiti Myneni

Faculty, Staff and Student Publications

OBJECTIVE: We provide a scoping review of Digital Health Interventions (DHIs) that mitigate COVID-19 misinformation and disinformation seeding and spread.

MATERIALS AND METHODS: We applied our search protocol to PubMed, PsychINFO, and Web of Science to screen 1666 articles. The 17 articles included in this paper are experimental and interventional studies that developed and tested public consumer-facing DHIs. We examined these DHIs to understand digital features, incorporation of theory, the role of healthcare professionals, end-user experience, and implementation issues.

RESULTS: The majority of studies (n = 11) used social media in DHIs, but there was a lack of platform-agnostic generalizability. …

An Artificial Neural Network For Nasogastric Tube Position Decision Support, Ignat Drozdov, Rachael Dixon, Benjamin Szubert, Jessica Dunn, Darren Green, Nicola Hall, Arman Shirandami, Sofia Rosas, Ryan Grech, Srikanth Puttagunta, Mark Hall, David J Lowe

Faculty, Staff and Student Publications

PURPOSE: To develop and validate a deep learning model for detection of nasogastric tube (NGT) malposition on chest radiographs and assess model impact as a clinical decision support tool for junior physicians to help determine whether feeding can be safely performed in patients (feed/do not feed).

MATERIALS AND METHODS: A neural network ensemble was pretrained on 1 132 142 retrospectively collected (June 2007-August 2019) frontal chest radiographs and further fine-tuned on 7081 chest radiographs labeled by three radiologists. Clinical relevance was assessed on an independent set of 335 images. Five junior emergency medicine physicians assessed chest radiographs and made feed/do …

Assessing The Suitability Of A Virtual 'Pink Warrior' For Older Breast Cancer Survivors During Covid-19: A Pilot Study, Maria C Swartz, Michael C Robertson, Ursela Christopherson, Stephanie J Wells, Zakkoyya H Lewis, Jinbing Bai, Michael D Swartz, H Colleen Silva, Eloisa Martinez, Elizabeth J Lyons

Faculty, Staff and Student Publications

The COVID-19 pandemic impacted the conduct of in-person physical activity (PA) interventions among older survivors of BC, who need such interventions to stay active and prevent functional decline. We tested the feasibility of virtually delivering an exergame-based PA intervention to older BC survivors. We enrolled 20 female BC survivors ≥55 years and randomly assigned them to two groups. The intervention group (Pink Warrior 2) received 12 weekly virtual exergame sessions with behavioral coaching, survivorship navigation support, and a Fitbit for self-monitoring. The control group received 12 weekly phone-based survivorship discussion sessions and wore a Mi Band 3. Feasibility was evaluated …

Conducting Clinical Genomics Research During The Covid-19 Pandemic: Lessons Learned From The Cser Consortium Experience, Stephanie A Kraft, Heidi Russell, Jeannette T Bensen, Katherine E Bonini, Jill O Robinson, Nuriye Sahin-Hodoglugil, Kathleen Renna, Lucia A Hindorff, Dave Kaufman, Carol R Horowitz, Margaret Waltz, Jamilyn M Zepp, Sara J Knight

Faculty, Staff and Student Publications

Clinical research studies have navigated many changes throughout the COVID-19 pandemic. We sought to describe the pandemic's impact on research operations in the context of a clinical genomics research consortium that aimed to enroll a majority of participants from underrepresented populations. We interviewed (July to November 2020) and surveyed (May to August 2021) representatives of six projects in the Clinical Sequencing Evidence-Generating Research (CSER) consortium, which studies the implementation of genome sequencing in the clinical care of patients from populations that are underrepresented in genomics research or are medically underserved. Questions focused on COVID's impact on participant recruitment, enrollment, and …

Digital Health Interventions To Improve Adolescent Hpv Vaccination: A Systematic Review, Jihye Choi, Irene Tamí-Maury, Paula Cuccaro, Sooyoun Kim, Christine Markham

Faculty, Staff and Student Publications

Digital technologies are being increasingly utilized in healthcare to provide pertinent and timely information for primary prevention, such as vaccination. This study aimed to conduct a systematic review to describe and assess current digital health interventions to promote HPV vaccination among adolescents and parents of adolescents, and to recommend directions for future interventions of this kind. Using appropriate medical subject headings and keywords, we searched multiple databases to identify relevant studies published in English between 1 January 2017 and 31 July 2022. We screened and selected eligible studies for inclusion in the final analysis. We reviewed a total of 24 …