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

Study Designs in Epidemiology01:20

Study Designs in Epidemiology

264
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
264
What is an Experiment?01:12

What is an Experiment?

11.7K
An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
11.7K
Data Collection by Experiments01:13

Data Collection by Experiments

24.3K
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...
24.3K
Experimental Designs01:16

Experimental Designs

11.5K
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
11.5K
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.7K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.7K
Group Design02:01

Group Design

9.0K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
9.0K

You might also read

Related Articles

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

Sort by
Same author

Attrition of older adults in web-based health interventions: Survival analysis within an observational cohort study.

Journal of health psychology·2024
Same author

International eHealth ecosystems and the quest for the winning value proposition: findings from a survey study.

Open research Europe·2023
Same author

Optimizing appreciation and persuasion of embodied conversational agents for health behavior change: A design experiment and focus group study.

Health informatics journal·2023
Same author

Developing an eMental health monitoring module for older mourners using fuzzy cognitive maps.

Digital health·2023
Same author

Development of an online service for coping with spousal loss by means of human-centered and stakeholder-inclusive design: the case of LEAVES.

Death studies·2023
Same author

How to Prevent the Drop-Out: Understanding Why Adults Participate in Summative eHealth Evaluations.

Journal of healthcare informatics research·2023

Related Experiment Video

Updated: Jul 18, 2025

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
06:28

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy

Published on: August 1, 2019

8.4K

An experiment on data sharing options designs for eHealth interventions.

Valentina Bartali1, Lex van Velsen1

  • 1Roessingh Research and Development and University of Twente, Roessinghsbleekweg 33b, 7522 AH Enschede, the Netherlands.

Internet Interventions
|August 28, 2023
PubMed
Summary

The design of data sharing options in eHealth technology significantly impacts user trust and ease of use. Visualizing data sharing from a data perspective enhances information control for users.

Keywords:
Design for privacyEase of useTrustUser-centred designeHealth intervention

More Related Videos

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.1K
Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
15:00

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Published on: February 3, 2023

2.5K

Related Experiment Videos

Last Updated: Jul 18, 2025

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
06:28

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy

Published on: August 1, 2019

8.4K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.1K
Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
15:00

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Published on: February 3, 2023

2.5K

Area of Science:

  • Human-Computer Interaction
  • Digital Health
  • Health Informatics

Background:

  • eHealth technology facilitates personal health data sharing among stakeholders.
  • Users require control over who accesses their health information.
  • Current eHealth interventions offer data sharing functionalities, but visual design research is limited.

Purpose of the Study:

  • To compare two visual designs for eHealth data sharing options: data perspective vs. party perspective.
  • To evaluate designs based on user trust, privacy concerns, ease of use, and information control.
  • To understand inter-factor influences and provide design recommendations for privacy.

Main Methods:

  • A between-subjects online experiment involving 123 participants.
  • Participants interacted with one of two visualized data sharing designs.
  • Data analysis included t-tests, correlation, and regression analyses.

Main Results:

  • The data perspective design resulted in higher information control (t(97) = 2.25, p = .03).
  • Regression analyses indicated that trust and ease of use influence all sharing-related factors.
  • User experience is demonstrably affected by the visual design of data-sharing options.

Conclusions:

  • eHealth data sharing design choices critically impact user trust and ease of use.
  • The data perspective design offers enhanced information control.
  • Actionable design advice for enhancing privacy in eHealth interfaces is provided.