Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cluster Sampling Method01:20

Cluster Sampling Method

15.8K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
15.8K
Distance Problem01:29

Distance Problem

197
When an object's velocity changes over time, the total distance traveled can be determined by summing small displacement intervals over short increments. This approach approximates the true distance through numerical summation and the use of integral calculus. An estimate of the total displacement can be obtained by measuring velocity at regular intervals and multiplying each value by the corresponding time step.If a runner accelerates over the first three seconds of a race, speed measurements...
197
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

5.7K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
5.7K
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.2K
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
1.2K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

320
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
320
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

5.6K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
5.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Effect of use of ambient listening technology on patient-reported communication and satisfaction ratings.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

Material economic hardships are associated with second-year hospitalizations after pediatric liver transplantation: Results from the SOCIAL-Tx study.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society·2026
Same author

Identifying trajectories across care modalities before and after COVID-19 using sequence analysis.

NPJ digital medicine·2026
Same author

Preventing Severe Hypoglycemia in Type 2 Diabetes: Randomized Controlled Trial of Proactive Care With Versus Without Psychoeducation.

Journal of general internal medicine·2026
Same author

The Long Tail of Long COVID-19: Broad and Extensive Increase in Utilization Within an Integrated Healthcare System.

Cureus·2026
Same author

"We Talk About Everything": Experiences with Digital Health Communication in Palliative Care.

Journal of palliative medicine·2026

Related Experiment Video

Updated: Apr 18, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.1K

The DISTANCE model for collaborative research: distributing analytic effort using scrambled data sets.

Howard H Moffet1, E Margaret Warton2, Melissa M Parker

  • 1Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612.

Information Security and Computer Fraud
|January 14, 2015
PubMed
Summary

This study introduces a novel data-sharing method that protects patient privacy while enabling external researchers to collaborate. This approach distributes analytic tasks, leading to increased scientific output efficiently.

Keywords:
cohort studiescollaborationdata sharingde-identificationepidemiologyinformation disseminationprivacy rule

More Related Videos

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

2.1K
Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
04:44

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Published on: July 21, 2021

5.2K

Related Experiment Videos

Last Updated: Apr 18, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.1K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

2.1K
Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
04:44

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Published on: July 21, 2021

5.2K

Area of Science:

  • Health Informatics
  • Collaborative Research
  • Data Privacy

Background:

  • Ethical imperatives drive data sharing for public health advancement.
  • Data sharing poses risks of privacy breaches and individual harm.
  • Balancing data utility with privacy protection is crucial in research.

Purpose of the Study:

  • To develop and implement an innovative method for scientific collaboration and data sharing.
  • To distribute the analytic burden among researchers while safeguarding patient privacy.
  • To create a secure environment for external investigators to conduct data analysis.

Main Methods:

  • A protocol was established for external investigators collaborating with an analytic coordinating center (ACC).
  • External researchers use de-identified, shuffled 'scrambled data sets' in a secure sandbox environment.
  • Analytic code developed by external investigators is executed on original data at the ACC to generate results.

Main Results:

  • The developed method has been successfully implemented with collaborators.
  • Numerous published papers and conference reports have resulted from this collaborative approach.
  • The system effectively facilitates external research contributions.

Conclusions:

  • Distributing the analytic workload enhances scientific collaboration and expands analytic capabilities.
  • This method promotes efficient research, generating more scientific findings at a lower cost.
  • The approach successfully balances data sharing with robust patient privacy protection.