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Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
Data Collection II01:29

Data Collection II

The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and family,...
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
Data Collection by Observations01:08

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Data Collection by Experiments01:13

Data Collection by Experiments

Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public clinical trial...

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Childhood Disadvantage Moderates Late Midlife Default Mode Network Cortical Microstructure and Visual Memory Association.

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Related Experiment Video

Updated: Jun 12, 2026

Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation
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Published on: July 14, 2023

Strategies for collection, management, and release of data for multi-site longitudinal studies: Lessons from the ABCD

Janosch Linkersdörfer1, Sammy Berman1, Calen Smith1

  • 1Center for Multimodal Imaging and Genetics, J. Craig Venter Institute, La Jolla, CA, USA.

Developmental Cognitive Neuroscience
|June 10, 2026
PubMed
Summary

The Adolescent Brain Cognitive Development (ABCD) Study

Keywords:
Data collectionData curationData managementData releaseData scienceReproducibilityResults-based accountabilityTransparency

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Area of Science:

  • Neuroscience
  • Data Science
  • Longitudinal Studies

Background:

  • The Adolescent Brain Cognitive Development (ABCD) Study collects extensive data from a large, multi-site, multi-modal cohort.
  • Managing and sharing data from such a large study presents significant logistical and technical challenges.

Purpose of the Study:

  • To synthesize ten years of experience from the ABCD Study's Data Analysis, Informatics, & Resource Center (DAIRC).
  • To highlight strategies for efficient data collection, management, and release in large-scale longitudinal research.
  • To provide a framework for future multi-site data center operations.

Main Methods:

  • Refinement of internal processes, including electronic data capture instruments and quality control procedures.
  • Development of metrics and tools for recruitment, retention, and protocol completeness.
  • Establishment of data curation standards and a sharing infrastructure to promote open science.

Main Results:

  • Enhanced DAIRC efficiency and resilience through structured and adaptable processes, overcoming challenges like the COVID-19 pandemic.
  • Improved data quality and accessibility through refined data ingestion and quality control.
  • Development of a robust data sharing infrastructure supporting transparency and reproducibility.

Conclusions:

  • The strategies developed by the DAIRC offer a scalable and sustainable model for data center operations in multi-site longitudinal studies.
  • Lessons learned can inform the design and management of future large-scale research data initiatives.
  • Promoting open science and data accessibility lowers barriers for scientific use and collaboration.