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

Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
Experimental Designs01:16

Experimental Designs

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...
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to subjects...
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...

You might also read

Related Articles

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

Sort by
Same author

Non-pharmacological interventions for reducing anxiety and depression symptoms among adolescents and young adults: Protocol for a scoping review.

PloS one·2026
Same author

Adverse childhood experiences and risk of living with HIV among lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ+) people: a cross-sectional study.

The Lancet regional health. Western Pacific·2026
Same author

PROTOCOL: Life Skills Education and Psychosocial Interventions for Anxiety and Depression in Forcibly Displaced Persons in LMICs: A Systematic Review.

Campbell systematic reviews·2026
Same author

Precision Imaging to Evaluate Kaposi Sarcoma (PRIME-KS): protocol for a multicountry novel artificial intelligence-based imaging device.

medRxiv : the preprint server for health sciences·2026
Same author

Brief Report: Closing the Implementation Gap: Prioritizing Rapid Science for Global HIV Impact.

Journal of acquired immune deficiency syndromes (1999)·2026
Same author

Cost-Effectiveness Analyses for Sequential Multiple Assignment Randomized Trials.

Statistics in medicine·2026
Same journal

A call for supplemental implementation strategy reporting guidelines to advance minority health: applying expanded specification and reporting recommendations to the Literacy Promotion for Latinos study.

Implementation science communications·2026
Same journal

Growing implementation scientists: NHLBI's K12 programs in heart, lung, blood, and sleep research.

Implementation science communications·2026
Same journal

Implementing a multimodal lifestyle intervention for depression and overweight in primary and secondary care: protocol for an implementation study exploring what works, how, and under what conditions.

Implementation science communications·2026
Same journal

Implementation determinants and outcomes in the Philadelphia TelePrEP Program: a mixed methods study of client and staff perspectives.

Implementation science communications·2026
Same journal

Implementing pharmacogenetic-guided prescribing in general practice: a qualitative process evaluation.

Implementation science communications·2026
Same journal

Implementing systems- and organisational-level change to advance gender equality in healthcare leadership: a mixed-methods implementation protocol.

Implementation science communications·2026
See all related articles

Related Experiment Video

Updated: Jun 21, 2026

Errors as a Means of Reducing Impulsive Food Choice
07:07

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Preferences for rapid implementation science: a real-time discrete choice experiment.

Elvin H Geng1, Rohit Ramaswamy2,3, Alex T Ramsey4

  • 1Division of Infectious Diseases, School of Medicine, Washington University in St. Louis, Saint Louis, MO, USA.

Implementation Science Communications
|June 19, 2026
PubMed
Summary
This summary is machine-generated.

Rapid implementation science methods, like real-time discrete choice experiments (DCEs), can generate timely evidence for decision-makers. Participants prioritized faster results and community engagement over traditional research priorities.

Keywords:
Discrete-choice experimentPreferencesRapid implementation scienceRapid research

More Related Videos

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats
09:12

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

Published on: March 17, 2019

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

Related Experiment Videos

Last Updated: Jun 21, 2026

Errors as a Means of Reducing Impulsive Food Choice
07:07

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats
09:12

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

Published on: March 17, 2019

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

Area of Science:

  • Implementation Science
  • Health Services Research
  • Decision Science

Background:

  • A persistent gap exists between academic research timelines and decision-maker needs for timely evidence.
  • Traditional research often prioritizes methodological rigor over policy relevance and stakeholder engagement.

Purpose of the Study:

  • To assess the feasibility of using real-time discrete choice experiments (DCEs) to gather decision-maker preferences in implementation science.
  • To understand priorities for rapid evidence generation to bridge the research-policy gap.

Main Methods:

  • A 10-minute discrete choice experiment (DCE) was administered in real-time to 94 participants at an implementation science conference.
  • Participants evaluated hypothetical vaccine implementation studies based on attributes like rapidity, design, outcome, engagement, leadership, and cost.
  • A mixed logit model analyzed preferences, with results presented back to the audience.

Main Results:

  • Respondents strongly preferred results within 6 months over 12 or 18 months (p<0.001).
  • Vaccine uptake was a preferred primary outcome over acceptability (p<0.001), and community engagement was preferred over expert leadership (p<0.001).
  • Participants were willing to wait significantly longer for community-engaged programs and uptake-focused results.

Conclusions:

  • Real-time DCEs can generate actionable implementation science evidence rapidly.
  • Findings suggest decision-makers prioritize timely outcomes and community engagement, challenging the primacy of randomization in research design.
  • Rapid science approaches can better align research with policy needs, potentially closing the research-policy gap.