Center for Large Data Research and Data Sharing in Rehabilitation

Linda Tickle-Degnen, PhD, OTR/L
Professor,
Department of Occupational Therapy
Tufts University

General Description

The Social Self-Management of Parkinson’s Disease study (SocM-PD) is a mixed-method (quantitative-qualitative) prospective cohort study of how people with Parkinson’s disease (PD) and their primary caregiver (as available) naturalistically manage chronic disease, wellness and social life in their home and community. This project began April 1, 2013 and data collection was completed on March 31, 2019. The long-term objective of this project is to provide evidence to guide person-centered interventions that support social integration and overall health and well-being for those living with PD, and to contribute to the knowledge about facial masking for social life. A useable archived database will contribute to the knowledge about naturalistic home and community living with PD and serve as a model for researching naturalistic living with chronic disabling conditions that have socially incapacitating symptoms.

Jaynie Yang PT, PhD
Professor,
Department of Physical Therapy
University of Alberta

General Description

The Retraining Walking Over Ground in a Powered Exoskeleton After Spinal Cord Injury study was a prospective cohort study using the ReWalk powered exoskeleton to train people with chronic, severe spinal cord injury to walk. Researchers were able to determine training dosage required for walking proficiency in the device, the sensory motor changes in the nervous system induced by the training, the functionality of the device in a home-like environment, and the participants’ perspective on the device and training. There are increasing numbers of small trials published with respect to the use of powered exoskeletons for over ground walking. Since these trials are very time consuming to complete, and each study has a small number of participants, depositing these data in a publically available database will allow meta-analyses across studies in the future.

Stroke Initiative for Gait Data Evaluation (STRIDE)

Natalia Sánchez, PhD
Assistant Professor of Research
Division of Biokinesiology and Physical Therapy
University of Southern California

General Description

The Stroke Initiative for Gait Data Evaluation (STRIDE) is an initiative based at the University of Southern California to create an inter-institutional, public database containing de-identified demographic and kinematic, kinetic, and spatiotemporal measures assessed via gait analysis in individuals post-stroke, to provide a larger and more heterogeneous research dataset than that typically amassed at a single institution. The data in STRIDE can be used to run pilot analyses and power calculations for research studies, design and validate statistical models to test associations between gait variables, provides data for simulation-based biomechanical studies in stroke and provides data to assess the reproducibility of research findings, without the added data collection requirements. By creating the STRIDE database in ADDEP, we will ensure that research data can be used by secondary users long into the future, enhancing data impact and visibility to advance the field of stroke rehabilitation.

Colleen Hanlon, PhD
Associate Professor
Department of Psychiatry & Behavioral Sciences and Neurosciences
Medical University of South Carolina

General Description
Researchers at the Medical University of South Carolina have amassed a database of TMS neurophysiology outcome measures from over 100 healthy adults. The aim of this archiving proposal is to systematically curate these data from MUSC and share them with the community of clinical researchers investigating cortical excitability in neurologically healthy populations.

Archiving Stroke Recovery Data

Steve Kautz, PhD
Chair and Professor, Department of Health Sciences and Research
Professor, Department of Physical Therapy
College of Health Professions
Medical University of South Carolina

General Description
The goal of this project is to archive data resulting from Medical University of South Carolina Stroke Data (NIH 2R01 HD46820-06) conducted at the Medical University of South Carolina over the span of one year to delineate the cause/effect relationship between neural output and the biomechanical functions being executed in walking in post-stroke patients. Kinematic, kinetic, and electromyography (EMG) data were collected from 27 post-stroke subjects and from 17 healthy control subjects. Each subject walked on a treadmill at their self-selected walking speed in addition to a randomized block design of four steady- state mobility capability tasks: walking at maximum speed, and walking at self-selected speed with maximum cadence, maximum step length, and maximum step height.

Archiving Early Intervention Colorado Participant Characteristics, Service Use, and Outcomes

Beth McManus, ScD, PT, MPH
Associate Professor
Department of Health Systems Management and Policy
Colorado School of Public Health

Mary Khetani, ScD, OTR/L
Assistant Professor
Department of Occupational Therapy
University of Illinois at Chicago

General Description
Approximately 5,800 infants and toddlers with developmental disabilities and delays access Early Intervention Colorado (EI-CO) annually, yet the effects of EI-CO are poorly understood. Through collaboration with the Denver Metro Early Intervention program, this study will archive data generated from an urban early intervention program electronic administrative database.

Archiving the SCIRehab Study: Patient Level Dataset

Gale Whiteneck, PhD, FACRM
Director of Research
Craig Hospital

Julie Gassaway, M.S., BSN
Director Health and Wellness Research
Senior Clinical Research Scientist
Shepherd Center

General Description
The Spinal Cord Injury (SCI) Rehabilitation study was a multi-site, prospective observational study utilizing Practice Based Evidence methods to relate details of the rehabilitation process to patient outcomes using data collected from 1,376 people with spinal cord injuries from six collaborating institutions. The SCIRehab study was first in developing a systematic classification of the entire process of SCI rehabilitation and involved the development of 7 different treatment taxonomies to ensure consistent and detailed documentation of interventions. With a dataset as large and comprehensive as the SCIRehab study, additional research questions can still be answered by providing public access to the datasets for secondary data analysis. This award will support the necessary work needed for preparing the Patient Level dataset for archiving.

Archiving the Boston Rehabilitative Impairment Study of the Elderly (Boston RISE)

Jonathan Bean, MD
Director
Center for Lifelong Health & Fitness
Spaulding Rehabilitation Network

Associate Professor
Physical Medicine & Rehabilitation
Harvard Medical School

Director
New England Geriatric Research Education and Clinical Center
VA Boston Healthcare System

Rachel Ward, PhD, MPH
Research Scientist, Instructor
Department of Physical Medicine and Rehabilitation
Harvard School of Medicine

General Description

The Boston Rehabilitative Impairment Study of the Elderly (Boston RISE) study was sponsored by the NIH/NIA (R01 AG032052). The prospective cohort study included older primary care patients, aged 65 years and older, who were at risk for declining mobility and disability at baseline. The study was designed to investigate which combinations of neuromuscular impairments are most responsible for mobility decline and disability over 2 years of follow up. The Boston RISE database will be archived by the Inter-university Consortium for Political and Social Research (ICPSR) for broad use among investigators interested in rehabilitation and aging.

ATLAS: Anatomical Tracings of Lesions after Stroke

Sook-Lei Liew, PhD, OTR/L
Assistant Professor
USC Chan Division of Occupational Science & Occupational Therapy
University of Southern California

General Description
ATLAS (Anatomical Tracings of Lesions after Stroke) is a manually traced lesion dataset comprised of deidentified, raw T1-weighted MRI images of individuals after stroke and manually traced lesion masks. ATLAS provides the largest known, open source collection of manually traced lesion masks for researchers to use for testing and validation of new automated lesion segmentation algorithms and has the potential to be used in the development of powerful new tools for stroke neurorehabilitation and research. The ATLAS database will be archived by the Inter-university Consortium for Political and Social Research (ICPSR) in the Archive of Data on Disability to Enable Policy and research (ADDEP) for broad use among investigators interested in rehabilitation and aging.

Archiving the Stroke Recovery in Underserved Populations Study

Glenn Ostir, PhD
Assistant Professor
Director, Professor
Health Promotion & Behavior, Institute of Gerontology
University of Georgia

General Description
The Stroke Recovery in Underserved Populations (SRUP) study was sponsored by the NIA/NIH (R01-AG024806). The longitudinal dataset contains over 1,200 records of persons aged 55 years and older with stroke who received in-patient medical care from one of eleven medical rehabilitation facilities located across the United States. The SRUP dataset is unique as it combines information from the In-patient Rehabilitation Facilities Patient Assessment Instrument (IRF PAI) with individual-level information including psychological and social factors for the three largest ethnic/racial groups in the United States - non-Hispanic whites, non-Hispanic blacks, and Hispanics. The SRUP database will be archived by the Inter-university Consortium for Political and Social Research (ICPSR) for broad use among investigators interested in stroke and functional recovery after stroke.