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Related Concept Videos

Naturalistic Observations02:30

Naturalistic Observations

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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...
Observational Learning01:12

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning because...
Observational Studies01:11

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...
Steps in the Modeling Process01:14

Steps in the Modeling Process

Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...

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Related Experiment Video

Updated: Jul 17, 2026

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time
06:05

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

Applying direct observation to model workflow and assess adoption.

Kim M Unertl1, Matthew B Weinger, Kevin B Johnson

  • 1Dept. of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|January 24, 2007
PubMed
Summary

Understanding clinical workflow is key for health IT adoption. Direct observation revealed gaps between expected and actual use of informatics tools, leading to inefficiencies.

Related Experiment Videos

Last Updated: Jul 17, 2026

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time
06:05

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

Area of Science:

  • Health Informatics
  • Clinical Workflow Analysis
  • Information Behavior

Background:

  • Health IT system adoption is often hindered by a lack of understanding regarding clinical workflow.
  • Observational techniques offer valuable insights into the complexities of clinical environments.

Purpose of the Study:

  • To assess workflow and information flow within an outpatient chronic disease clinic.
  • To develop a general model of workflow and information behavior in a clinical setting.
  • To identify discrepancies between intended and actual use of health informatics tools.

Main Methods:

  • Conducted a pilot study employing direct observation over 55 hours.
  • Focused on an outpatient chronic disease clinic setting.
  • Analyzed the utilization of informatics systems, non-electronic artifacts, and workarounds.

Main Results:

  • Observed significant use of both electronic informatics systems and non-electronic artifacts/workarounds.
  • Identified gaps between clinic workflow and informatics tool design/implementation.
  • Found discrepancies between institutional expectations and actual user behavior with informatics tools.
  • Concurrent use of paper and electronic systems led to duplicated effort and inefficiencies.

Conclusions:

  • Direct observation effectively reveals critical information about workflow and health IT adoption.
  • Addressing the gap between designed and actual workflow is essential for successful health IT implementation.
  • Workflow analysis using observational methods can improve the efficiency and effectiveness of clinical information systems.