We conducted a qualitative study using a phenomenological approach in India’s Spiti Valley between August and October 2023. Sixteen individuals, age 18 years and older, participated in one-on-one interviews. The interviews were transcribed from Hindi into English, reviewed for accuracy by a native speaker, and imported into Dedoose software. Data were analyzed using inductive coding. These are the raw data sheets associated with this study. Ethics approval was provided by the University of Utah’s Institutional Review Board (IRB:00167060).
Evaluator responses to compliance, understandability, actionability, and readability criteria, by base and type, for Hearing Conservation educational materials from active-duty, continental United States Air Force bases.
Datasets include interviews and observations of healthcare staff in 25 long-term care facilities across 7 states and two data collection visits to understand frequency, type, and reason (i.e., types of care activities provided during an interaction) for staff-resident interactions in 2019 and 2020. Staff-resident interactions were studied to examine potential for multidrug-resistant organism (MDRO) transmission within long-term care settings.
This collection includes radial component displacement seismograms in the time window including the SKS, SKKS and SPdKS seismic arrivals. These data all interact with ultra-low velocity zone (ULVZ) structures at the core-mantle boundary beneath East Asia. Data used in the study of Festin et al., 2024 (TSR) is included in this collection.
The data from the Digital Library Outreach and Instruction survey is intended to discover how digital library practitioners at various types of cultural institutions promote their unique resources, beyond simply placing content in an online repository for users to discover. Types of outreach investigated include social media promotion, integration of digital collections into teaching and instruction activities, and partnerships with external campus units or community organizations.
The purpose of this dataset is to use a full powered pilot sample (n=166) and a randomized waitlist control experimental design where participants are exposed to either the full intervention for 16 weeks or partial intervention for the first 8 weeks and then full intervention for weeks 9-16. All participants were given a follow-up survey 4 weeks after completing the intervention.
The measures included in this dataset are related to respite, respite time-use, and well-being.
These pilot data were used to assess feasibility and to explore hypotheses regarding the potential efficacy of the intervention, as well as the mechanism (i.e., time-use satisfaction) underlying the interventions effect on wellbeing.
This dataset is a retrospective study of de-identified electronic-medical record data of transgender and gender-diverse (TGD; i.e. those whose gender identity does not align with their sex assigned at birth) adults 18 years and older who receive gender-affirming care within the University of Utah healthcare system. Gender-affirming care includes gender-affirming hormone therapy (i.e. estrogen- or testosterone-based medications) and gender-affirming surgeries. The goal of creating this dataset is to contribute to the growing literature needed about the TGD population in order to facilitate public health efforts to address health disparities as well as answer clinically impactful questions.
The microbiology data represents the microorganisms recovered during the study period at the University of Utah hospital from samples collected from patients, environmental surfaces, and healthcare personnel (HCP) hands using premoistened sponges. Patient samples were collected daily from the axilla, groin, and perianal areas or stool. Environmental samples were collected daily from room surfaces and unit common areas (such as bed rails, overbed tables, door handles, computer keyboards, and other high-touch areas). HCP hands were periodically sampled upon HCP exit from a patient room after engaging in health care activities. Samples were collected from the 20-bed University of Utah Hospital Cardiovascular ICU (CVICU) over a 54 day period. The information from these datasets can be used to understand how different organisms appear and move throughout a hospital ward over a period of time.
This dataset contains room occupancy during the study period at University of Utah hospital. Admission, Discharge, and Transfer (ADT) data is captured in participating hospitals to characterize room occupancy and non-occupancy in wards. These data are pulled from multiple sources collected during the study by study staff as well as harvested EHR data. Data were adjudicated and compiled into one comprehensive file. Data manipulation included redaction of dates, replaced with study days 1-n, as well as transformation from long format to wide for ease of use.