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Related Concept Videos

Archival Research01:40

Archival Research

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Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
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Elaborative Rehearsals01:07

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Elaborative rehearsal is a crucial cognitive strategy that strengthens information encoding in long-term memory by making meaningful connections between new data and pre-existing knowledge. This approach contrasts with maintenance rehearsal, which involves simple repetition without delving into the significance of the information. While maintenance rehearsal might temporarily keep information active in short-term memory, it is less effective for long-term retention.
The effectiveness of...
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Information Processing Approach01:30

Information Processing Approach

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The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
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Chunking and Rehearsal in Sensory Memory01:22

Chunking and Rehearsal in Sensory Memory

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Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of...
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Cognitive Learning01:21

Cognitive Learning

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
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Retrieval01:12

Retrieval

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Retrieval is the process of getting information out of memory storage and back into conscious awareness. This ability is essential for daily tasks like brushing hair and teeth, driving to work, and performing job duties. Retrieval occurs in three ways: recall, recognition, and relearning.
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Updated: Jul 5, 2025

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Building Research Infrastructure to Develop Greater Learning Efficiencies (BRIDGE).

Danne C Elbers1,2, Nathanael R Fillmore1,2, Jennifer La1

  • 1VA Boston Healthcare System, Boston MA, USA.

Studies in Health Technology and Informatics
|January 25, 2024
PubMed
Summary
This summary is machine-generated.

The Department of Veterans Affairs developed a Learning Health System (LHS) in oncology using real-world data. This system integrates data, develops algorithms, and returns results to clinics, improving cancer care.

Keywords:
Learning health systemoncology

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Area of Science:

  • Oncology
  • Health Informatics
  • Health Services Research

Background:

  • The Department of Veterans Affairs (VA) aims to implement a Learning Health System (LHS).
  • Oncology lacks robust evidence from randomized control trials, making it suitable for LHS implementation.
  • Existing healthcare systems need improvement for integrating evidence into clinical practice.

Purpose of the Study:

  • To outline the VA's developed Learning Health System (LHS) in oncology.
  • To describe the technical components and implementation strategy of the LHS.
  • To propose a framework for integrating knowledge generation into clinical workflows.

Main Methods:

  • Development of a large real-world data repository for oncology.
  • Establishment of a data science and algorithm development framework.
  • Creation of a mechanism for disseminating results back to clinical practice and patients.

Main Results:

  • A functional LHS in oncology at the VA, comprising data infrastructure, analytics capabilities, and a feedback loop.
  • Demonstrated feasibility of using real-world data to generate evidence in oncology.
  • Identification of the need for a collaborative bridging framework.

Conclusions:

  • The developed LHS at the VA shows promise for improving oncology care through data-driven insights.
  • A collaborative bridging framework between informatics and medical professionals is crucial for successful LHS integration.
  • This approach can enhance evidence generation and application at the point of care in oncology.