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1,708
datasets available to search
ShareScore release 0.7.1
Dataset results
1,708 results for “young adults”
Connecting Youth and Young Adults to Optimize ART Adherence: YouTHrive Efficacy Trial
ClinicalTrials.gov study NCT03149757. IPD Sharing: YES. Countries: 1. Publications: 1.
The PRISM Intervention: a Multi-site Randomized Controlled Trial for Adolescents and Young Adults With Advanced Cancer
ClinicalTrials.gov study NCT03668223. IPD Sharing: YES. Countries: 1. Publications: 3.
Videos for Advance Care Planning in Young Adults
ClinicalTrials.gov study NCT04149704. IPD Sharing: YES. Countries: 1. Publications: 1.
Sleep Treatment Education Program for Young Adult Cancer Survivors (STEP-YA)
ClinicalTrials.gov study NCT05358951. IPD Sharing: YES. Countries: 1. Publications: 1.
Mobile Self-Management Program for Stress Reduction in Young Adults
ClinicalTrials.gov study NCT07174544. IPD Sharing: NO. Countries: 1. Publications: 0.
Just-in-time Adaptive Intervention Messaging in a Digital Weight Loss Intervention for Young Adults
ClinicalTrials.gov study NCT05625061. IPD Sharing: YES. Countries: 1. Publications: 0.
DiaBetter Together for Young Adults With Type 1 Diabetes
ClinicalTrials.gov study NCT04247620. IPD Sharing: YES. Countries: 1. Publications: 1.
Addressing Vaccine Hesitancy and Increasing COVID-19 Vaccine Uptake Among African American Young Adults in the South
ClinicalTrials.gov study NCT05490329. IPD Sharing: YES. Countries: 1. Publications: 3.
Curcumin Therapy to Treat Vascular Dysfunction in Children and Young Adults With ADPKD
ClinicalTrials.gov study NCT02494141. IPD Sharing: YES. Countries: 1. Publications: 1.
Monitoring Pre-exposure Prophylaxis for Young Adult Women
ClinicalTrials.gov study NCT02915367. IPD Sharing: YES. Countries: 1. Publications: 2.
Improving Adherence in Adolescents and Young Adults With Bipolar Disorder
ClinicalTrials.gov study NCT04348604. IPD Sharing: YES. Countries: 1. Publications: 1.
Study of Efficacy, Safety and Tolerability of ACZ885 (Canakinumab) in Pediatric and Young Adult Patients With Sickle Cell Anemia
ClinicalTrials.gov study NCT02961218. IPD Sharing: YES. Countries: 7. Publications: 1.
App-based Mental Health Promotion in Young European Adults
ClinicalTrials.gov study NCT04148508. IPD Sharing: YES. Countries: 4. Publications: 22.
Mobile Brain-Body Imaging (MoBI) dual-tasking datasets (response inhibition while walking): Young adults
Open the record for dataset details and reuse information.
Single-unit auditory nerve fibre responses of young-adult and aging gerbils
Open the record for dataset details and reuse information.
Math anxiety mediates the link between number sense and math achievements in high math anxiety young adults
<p>The data are organized into three subfolders. One subfolder for each task:</p> <p><strong>MOT:</strong></p> <p>Each file contains a 3x4 matrix called “MatriceRisultati”.</p> <p>Each row of the matrix “MatriceRisultati” is a condition.</p> <p>The columns contain the following information:</p> <p>1<sup>st</sup>: Condition</p> <p>2<sup>nd</sup>: Number of response correct</p> <p>3<sup>rd</sup>: Total number of trials </p> <p>4<sup>th</sup>: proportion between column 2 and 3</p> <p> </p> <p><strong>Numerosity discrimination: </strong></p> <p>Each file contains a matrix called “a”. </p> <p>Each row of the matrix “a” is a trial.</p> <p>The columns contain the following information:</p> <p>1<sup>st</sup>: Test Numerosity</p> <p>2<sup>nd</sup>: Subject response </p> <p>3<sup>rd</sup>: Reference position: 1= left; 2=right</p> <p> </p> <p> <strong>Size discrimination:</strong> </p> <p>Each file contains a matrix called “MATR”. </p> <p>Each row of the matrix “MATR” is a trial.</p> <p>The columns contain the following information:</p> <p>1<sup>st</sup>: Delta (%) </p> <p>2<sup>nd</sup>: Subject response </p> <p>3<sup>rd</sup>: Test stimulus size (deg)</p> <p>4<sup>th</sup>: Probe stimulus size (deg)</p> <p>5<sup>th</sup>: Delta (%)</p> <p>6<sup>th</sup>: delta (deg)</p>
Dataset for article: Luque-Casado, A., Perakakis, P., Ciria, L.F., Sanabria, D. (2016). Transient autonomic responses during sustained attention in high and low fit young adults. Sci. Rep. 6, 27556
<p>Dataset for article:</p> <p>Luque-Casado, A., Perakakis, P., Ciria, L.F., Sanabria, D. (2016). Transient autonomic responses during sustained attention in high and low fit young adults. Sci. Rep. 6, 27556</p>
Physical Activity is Associated with Reduced Implicit Learning but Enhanced Relational Memory and Executive Functioning in Young Adults
<p>This file contains all data reported in the main analyses of our paper, including age, gender, BMI, Stroop effect, implicit learning sessions 1 and 2, relational memory, and all physical activity variables</p>
Young and older adult vowel categorization responses
<p>Age-related changes in auditory processing may reduce physiological coding of acoustic cues, contributing to older adults' difficulty perceiving speech in background noise. This study investigated whether older adults differed from young adults in patterns of acoustic cue weighting for categorizing vowels in quiet and in noise. All participants relied primarily on spectral quality to categorize /Ꜫ/ and /æ/ sounds in both listening conditions. However, relative to young adults, older adults exhibited greater reliance on duration and less reliance on spectral quality. These results suggest that aging alters patterns of perceptual cue weights that may influence speech recognition abilities.</p>
Data and code from: Healthy young adults use distinct gait strategies to enhance stability when walking on mild slopes and when altering arm swing
<p>This repository contains the Julia code, Jupyter notebook, and data used in the study “Healthy young adults use distinct gait strategies to enhance stability when walking on mild slopes and when altering arm swing” by MacDonald et al.</p> <p><strong>Instructions</strong></p> <p>To run this analysis on your computer, both Julia and Jupyter Notebook must be installed. A version of Julia appropriate for your OS can be downloaded from the <a href="https://julialang.org/downloads/">Julia website</a>, and Jupyter can be installed from within Julia (in the REPL) with</p> <pre><code>] add IJulia</code></pre> <p>Alternate instructions for installing Jupyter can be found on the <a href="https://github.com/JuliaLang/IJulia.jl">IJulia github</a> or the <a href="https://jupyter.org/install">Jupyter homepage</a> (not recommended).</p> <p>From within the main repository directory, start Julia and then start Jupyter in the Julia REPL</p> <pre><code>using IJulia notebook(;dir=pwd())</code></pre> <p>or if using a system Jupyter installation, start Jupyter from your favorite available shell (e.g. Powershell on Windows, bash on any *nix variant, etc.). In Jupyter, open the <code>notebooks/analysis.ipynb</code> notebook. Running all cells will reproduce the results for this paper.</p> <p><strong>Description of data</strong></p> <p>The <code>data</code> directory contains all the data used in the production of the results which were statistically tested.</p> <p>Each <code>.mat</code> file contains events and data generated in Visual3D:</p> <ul> <li>Events <ul> <li><code>LTO</code>/<code>RTO</code> (Left/right toe-off)</li> <li><code>LHS</code>/<code>RHS</code> (Left/right heel-strike)</li> <li><code>HIST</code>/<code>HIEN</code> (Hilly start/end)</li> <li><code>ROST</code>/<code>ROEN</code> (Rocky start/end)</li> <li><code>MLST</code>/<code>MLEN</code> (ML translation start/end)</li> </ul> </li> <li>Data <ul> <li><code>LFootPos</code>/<code>RFootPos</code> (Left/right foot COM position)</li> <li><code>TrunkPos/TrunkVel</code>/<code>TrunkAcc</code> (Trunk COM position, velocity, and acceleration)</li> <li><code>HeadPos/HeadVel</code>/<code>HeadAcc</code> (Head COM position, velocity, and acceleration)</li> <li><code>COG</code> (Whole-body COM/COG)</li> </ul> </li> </ul> <p>The <code>.csv</code> files contain system state of the CAREN system produced by D-Flow software, which includes various system and software settings, most pertinent of which is the treadmill speed.</p> <p>The <code>.c3d</code> files contain the raw motion capture data from Vicon Nexus.</p> <ul> </ul> <p>The results of the <code>notebooks/analysis.ipynb</code> notebook are found in the <code>results</code> folder. Please see the paper for a list of the dependent variables and statistical analyses.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.