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The goal of this study is to explore cognitive burden perceptions among physicians in relation to case report writing. Furthermore, this study evaluates the use of artificial intelligence (AI) assistance as a tool to reduce cognitive burden among providers preparing and submitting case reports. If an AI-tool is helpful in this setting, it may potentially help increase reporting of rare medical events and thereby improve the evidence base for care of these patient populations. This study will occur at a single time point which is expected to last approximately 2 hours. This session will include reviewing two rare tumor cases and then writing a clinical vignette with and without AI assistance.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Case Report with Artificial Intelligence | Experimental | Medical students, resident physicians, or attending physicians report rare cases with using Artificial Intelligence. |
|
| Case Report without Artificial Intelligence | No Intervention | Medical students, resident physicians, or attending physicians report rare cases without using Artificial Intelligence. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Artificial Intelligence | Behavioral | Participants will use the Artificial Intelligence assistance tool for case reports. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Subjective Cognitive workload (CWL) | Subjective Cognitive workload (CWL) will be measured while interviews using The National Aeronautics and Space Administration task load (NASA TLX) index is a tool for measuring and conducting a subjective mental workload (MWL) assessment. The NASA-TLX is a subjective measure of CWL and is used across many disciplines. The NASA-TLX considers six dimensions-Mental, Physical, and Temporal Demands, Frustration, Effort, and Performance. NASA-TLX scores ≥55 have been associated with reduced performance in numerous settings. NASA-TLX is considered to be the most used subjective measure of CWL. The validated two-stage process with participants performing 15 separate pair-wise comparisons between 6 dimensions of NASA-TLX will be used. A workload score will be marked from low and high for each dimension. Score values from 0 -100. The Interpretation Score of NASA TLX for Low 0-9, Medium 10-29, Somewhat high 30-49, High 50-79, and Very high 80-100 | Baseline to 2 hours |
| Perceived cognitive load | The perceived cognitive load will be measured using System Usability Scale (SUS). SUS is a validated post-test questionnaire that measures user satisfaction. Further, studies confirm that SUS is predictive of the impacts of changes to the user interface on usability when multiple changes to a single product were made over a large number of iterations. SUS is composed of 10 questions- five positive and five negative statements, each having a five-point scale that ranges from strongly disagree to strongly agree. SUS provides a score (range, 0-100) based on the participant's rating of 10 statements regarding usability with higher scores indicating greater satisfaction with usability. | Baseline to 2 hours |
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Inclusion Criteria:
1. The subject is a physician, medical student, or postdoctoral student.
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Shivani Sud | Contact | 984-987-1072 | shivani.sud@unchealth.unc.edu | |
| Victoria Xu | Contact | 984-974-8744 | victoria_xu@med.unc.edu |
| Name | Affiliation | Role |
|---|---|---|
| Shivani Sud | UNC Lineberger Comprehensive Cancer Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Lineberger Comprehensive Cancer Center | Chapel Hill | North Carolina | 27514 | United States |
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| Label | URL |
|---|---|
| University of North Carolina Lineberger Comprehensive Cancer Center Clinical Trials | View source |
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| ID | Term |
|---|---|
| D019954 | Neurobehavioral Manifestations |
| ID | Term |
|---|---|
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D001185 | Artificial Intelligence |
| ID | Term |
|---|---|
| D000465 | Algorithms |
| D055641 | Mathematical Concepts |
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