Olivia Drescher
Biographic Data
| ID | 7233288 |
|---|---|
| NAME | Olivia Drescher |
| GIVEN NAMES | Olivia |
| FAMILY NAME | Drescher |
| SIGNATURE | DRESCHER O |
| AFFILIATIONS | Université Laval Faculté de médecine, Quebec, Quebec, Canada |
| ORCID | 0000-0002-4281-6695 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Prediction models of diabetes complications
BACKGROUND: Diabetes often places a large burden on people with diabetes (hereafter 'patients') and the society, that is, in part attributable to its complications. However, evidence from models predicting diabetes complications in patients remains unclear. With the collaboration of patient partners, we aimed to describe existing prediction models of physical and mental health complications of diabetes. METHODS: Building on existing frameworks, w…
Sound Practices
PURPOSE: Written examinations such as multiple-choice question (MCQ) exams are a key assessment strategy in health professions education (HPE), frequently used to provide feedback, to determine competency, or for licensure decisions. However, traditional psychometric approaches for monitoring the quality of written exams, defined as items that are discriminant and contribute to increase the overall reliability and validity of the exam scores, usu…
No prominent works on this page.
Sound Practices
PURPOSE: Written examinations such as multiple-choice question (MCQ) exams are a key assessment strategy in health professions education (HPE), frequently used to provide feedback, to determine competency, or for licensure decisions. However, traditional psychometric approaches for monitoring the quality of written exams, defined as items that are discriminant and contribute to increase the overall reliability and validity of the exam scores, usu…
Prediction models of diabetes complications
BACKGROUND: Diabetes often places a large burden on people with diabetes (hereafter 'patients') and the society, that is, in part attributable to its complications. However, evidence from models predicting diabetes complications in patients remains unclear. With the collaboration of patient partners, we aimed to describe existing prediction models of physical and mental health complications of diabetes. METHODS: Building on existing frameworks, w…
Medicine (2 works) · Amputation (1 work) · Applied Psychology (1 work) · Artificial Intelligence in Healthcare (1 work) · Complication (1 work) · Data collection (1 work) · Dementia (1 work) · Descriptive statistics (1 work) · Diabetes Management and Research (1 work) · Diabetes mellitus (1 work)