Evaluation of Laparoscopic Hysterectomy Simulator
Evaluation of Laparoscopic Hysterectomy Simulator to Improve Cognitive Surgical Knowledge of Obstetrics and Gynecology Trainees
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
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British Columbia
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Vancouver, British Columbia, Canada, V5Z 1M9
- University of British Columbia, Division of Obstetrics and Gynecology
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Ontario
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Toronto, Ontario, Canada, M5S 1A8
- University of Toronto Faculty of Medicine
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Heidelberglaan
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Utrecht, Heidelberglaan, Netherlands, 3508 GA
- University Medical Center, Utrecht, The Netherlands
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California
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Los Angeles, California, United States, 90033
- University of Southern California, Department of Obstetrics and Gynecology
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Los Angeles, California, United States, 90095
- University of California Los Angeles, Department of Obstetrics and Gynecology
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Washington
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Seattle, Washington, United States, 98195
- University of Washington, School of Medicine, Department of Obstetrics and Gynecology
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Faculty in the Department of Ob-Gyn
- Experienced OBGYN surgeons
- Residents in the Department of Ob-Gyn
Exclusion Criteria:
- None
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Supportive Care
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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No Intervention: conventional residency training
no intervention
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Experimental: Laparoscopic Hysterectomy trainer
Intervention: An educational video and web-based e-module will be created.
The final product will be reviewed by the expert contributors.
Once approved, these tools will be showcased to a voluntary focus group of Obstetrics and Gynecology residents at the University of Toronto.
A quantitative assessment of effectiveness of this tool will be performed through the use of pre- and post-tests of knowledge.
A qualitative needs assessment will also be performed using post-viewing surveys.
If found to be effective, this educational tool will be incorporated in the University of Toronto Obstetrics and Gynecology residency curriculum.
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In order to increase comfort level amongst Gynecologists, we aim to identify verbal and non-verbal components of teaching TLH through interview and video recordings.
Utilizing qualitative analysis of common themes, we will develop an educational video and web-based e-module to be used by Gynecology residents and surgeons.
We will also use a combination of quantitative pre- and post-tests and qualitative surveys to assess the effectiveness of such a training tool.
Ultimately, the project aims to create a robust tool that can be implemented in Gynecology residencies.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Number of residents using validation tool
Time Frame: 7-10 days
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Phase I will consist of two on line tests that assess surgical and anatomic knowledge.
The tests will be separated by 7-10 days.
Evaluation will determine the validity of the tests as well as creating a "knowledge curve."
Analyzing resident and faculty performance with a one-way analysis of variance, with level of training as the independent variable, will assess construct validity.
Post hoc contrasts are done with Student-Newman-Keuls test.
We will also evaluate the validity of the exam by comparing the performance of novice surgeons with more advanced residents and experts.
Internal consistency of the examination, which is a measure of the reliability of the test, will be calculated using Cronbach's alpha test.
Results will be presented as percentages, means and standard deviations based on the number of questions that are answered correctly.
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7-10 days
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Number of experts using validation tool
Time Frame: 7-10 days
|
Phase I will consist of two on line tests that assess surgical and anatomic knowledge.
The tests will be separated by 7-10 days.
Evaluation will determine the validity of the tests as well as creating a "knowledge curve."
Analyzing resident and faculty performance with a one-way analysis of variance, with level of training as the independent variable, will assess construct validity.
Post hoc contrasts are done with Student-Newman-Keuls test.
We will also evaluate the validity of the exam by comparing the performance of novice surgeons with more advanced residents and experts.
Internal consistency of the examination, which is a measure of the reliability of the test, will be calculated using Cronbach's alpha test.
Results will be presented as percentages, means and standard deviations based on the number of questions that are answered correctly.
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7-10 days
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Dr. Satkunaratnam Abheha, MD, Unity Health Toronto
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Estimate)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 30509
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
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