| Literature DB >> 33114420 |
Azhar T Rahma1, Mahanna Elsheik1,2, Iffat Elbarazi1, Bassam R Ali2,3, George P Patrinos2,3,4, Maitha A Kazim1, Salma S Alfalasi1, Luai A Ahmed1,2, Fatma Al Maskari1,2.
Abstract
Medical and health science students represent future health professionals, and their perceptions are essential to increasing awareness on genomic medicine and pharmacogenomics. Lack of education is one of the significant barriers that may affect health professional's ability to interpret and communicate pharmacogenomics information and results to their clients. Our aim was to assess medical and health science students' knowledge, attitudes and perception for a better genomic medicine and pharmacogenomics practice in the United Arab Emirates (UAE). A cross-sectional study was conducted using a validated questionnaire distributed electronically to students recruited using random and snowball sampling methods. A total of 510 students consented and completed the questionnaire between December 2018 and October 2019. The mean knowledge score (SD) for students was 5.4 (±2.7). There were significant differences in the levels of knowledge by the year of study of bachelor's degree students, the completion status of training or education in pharmacogenomics (PGX) or pharmacogenetics and the completion of an internship or study abroad program (p-values < 0.05. The top two barriers that students identified in the implementation of genomic medicine and pharmacogenomics were lack of training or education (59.7%) and lack of clinical guidelines (58.7%). Concerns regarding confidentiality and discrimination were stated. The majority of medical and health science students had positive attitudes but only had a fair level of knowledge. Stakeholders in the UAE must strive to acquaint their students with up-to-date knowledge of genomic medicine and pharmacogenomics.Entities:
Keywords: UAE students; attitudes; barriers; genomic medicine; knowledge; pharmacogenomics
Year: 2020 PMID: 33114420 PMCID: PMC7711592 DOI: 10.3390/jpm10040191
Source DB: PubMed Journal: J Pers Med ISSN: 2075-4426
Students’ demographic and academic characteristics (n = 510).
| Count (%) | |
|---|---|
| Gender | |
|
| 421 (82.7%) |
|
| 88 (17.3%) |
| Age Group | |
|
| 69 (13.5%) |
|
| 388 (76.1%) |
|
| 38 (7.5%) |
|
| 6 (1.2%) |
| University Location | |
|
| 245 (68.6%) |
|
| 83 (16.5%) |
|
| 55 (10.9%) |
|
| 17 (3.4%) |
|
| 1 (0.2%) |
|
| 1 (0.2%) |
|
| 1 (0.2%) |
| Program | |
|
| 265 (52.2%) |
|
| 149 (29.3%) |
|
| 35 (6.9%) |
|
| 59 (11.6%) |
medical imaging, radiology, radiography, biochemistry, biomedical sciences, dentistry, pharmacology, physiology, psychology, public health, occupational health.
Questions assessing genomic medicine and pharmacogenomics’ knowledge among students (n = 506).
| Knowledge Questions | Correct Answer | Answered “True” | Answered “False” | Answered “Do not Know” |
|---|---|---|---|---|
| 1. Humans have 48 chromosomes. | False | 149 | 350 | 7 |
| (29.4%) | (69.2%) | (1.4%) | ||
| 2. Adenine (A) only pairs with cytosine (C) and Thymine (T) only pairs with Guanine (G). | False | 79 | 385 | 42 |
| (15.6%) | (76.1%) | (8.3%) | ||
| 3. Pharmacogenomics seeks to individualize therapy based on patient’s genetic profile. | True | 418 | 12 | 76 |
| (82.6%) | (2.4%) | (15%) | ||
| 4. Genetic changes can cause adverse reactions. | True | 426 | 20 | 60 |
| (84.2%) | (4.0%) | (11.9%) | ||
| 5. Pharmacogenomics testing is recommended by FDA for certain drugs. | True | 261 | 25 | 220 |
| (51.6%) | (4.9%) | (43.5%) | ||
| 6. Genetic changes can affect the patient’s response to certain drug. | True | 455 | 11 | 40 |
| (89.9%) | (2.2%) | (7.9%) | ||
| 7. Genes can be activated or deactivated by other genes. | True | 412 | 16 | 78 |
| (81.4%) | (3.2%) | (15.4%) | ||
| 8. Every cell of the body contains the whole genome. | False | 314 | 112 | 80 |
| (62.1%) | (22.1%) | (15.8%) | ||
| 9. Environmental factors, such as cigarette smoke, can affect gene activity. | True | 423 | 43 | 40 |
| (83.6%) | (8.5%) | (7.9%) |
Comparison of the level of knowledge by demographic and academic characteristics.
| Level of Knowledge | |||||
|---|---|---|---|---|---|
| Mean Score (± SD) | Good | Fair | Poor | ||
| Overall | 5.4 (± 2.7) | 219 (42.9%) | 191 (37.5%) | 100 (19.6%) | |
| Gender | 0.47 | ||||
|
| 5.3 (± 2.7) | 176 (41.8%) | 161 (38.2%) | 84 (20.0%) | |
|
| 5.6 (± 2.6) | 43 (48.9%) | 30 (34.1%) | 15 (17.0%) | |
| Age group | 0.56 | ||||
|
| 5.0 (± 2.5) | 23 (33.3%) | 31 (44.9%) | 15 (21.7%) | |
|
| 5.5 (± 2.8) | 177 (45.6%) | 137 (35.3%) | 74 (19.1%) | |
|
| 5.3 (± 2.8) | 14 (36.8%) | 16 (42.1%) | 8 (21.1%) | |
|
| 5.0 (± 2.6) | 2 (33.3%) | 3 (50.0%) | 1 (16.7%) | |
| Program | 0.12 | ||||
|
| 5.5 (± 2.7) | 123 (46.4%) | 95 (35.8%) | 47 (17.7%) | |
|
| 5.6 (± 2.7) | 69 (46.3%) | 52 (34.9%) | 28 (18.8%) | |
|
| 4.7 (± 2.9) | 11 (31.4%) | 15 (42.9%) | 9 (25.7%) | |
|
| 4.8 (± 2.4) | 16 (27.1%) | 29 (49.2%) | 14 (23.7%) | |
| Degree | 0.44 | ||||
|
| 6.4 (± 1.7) | 185 (44.5%) | 148 (35.6%) | 83 (20.0%) | |
|
| 5.9 (± 1.5) | 14 (33.3%) | 20 (47.6%) | 8 (19.0%) | |
|
| 6.6 (± 1.2) | 19 (40.4%) | 20 (42.6%) | 8 (17.0%) | |
|
| 5.8 (± 1.0) | 1 (25.0%) | 3 (75.0%) | 0 (0.0%) | |
| Year of study (Bachelor) | 0.00 * | ||||
|
| 5.1 (± 2.0) | 11 (5.9%) | 29 (19.6%) | 13 (15.7%) | |
|
| 6.4 (± 1.7) | 37 (20.0%) | 22 (14.9%) | 15 (18.1%) | |
|
| 7.0 (± 1.4) | 52 (28.1%) | 26 (17.6%) | 22 (26.5%) | |
|
| 6.6 (± 1.6) | 55 (29.7%) | 35 (26.3%) | 20 (24.1%) | |
|
| 6.5 (± 1.5) | 23 (12.4%) | 12 (8.1%) | 7 (8.4%) | |
|
| 6.1 (± 1.3) | 5 (2.7%) | 12 (8.1%) | 3 (3.6%) | |
|
| 5.8 (± 1.2) | 2 (1.1%) | 12 (8.1%) | 3 (3.6%) | |
| Year of study (Master) | 0.35 | ||||
|
| 5.8 (± 1.4) | 5 (35.7%) | 9 (45.0%) | 3 (37.5%) | |
|
| 5.8 (± 1.6) | 5 (35.7%) | 10 (50.0%) | 3 (37.5%) | |
|
| 6.3 (± 1.2) | 2 (14.3%) | 1 (5.0%) | 2 (25.0%) | |
|
| 7.5 (± 0.7) | 2 (14.3%) | 0 (0.0%) | 0 (0.0%) | |
| Year of study (PhD) | 0.08 | ||||
|
| 6.2 (± 1.1) | 7 (36.8%) | 12 (60.0%) | 1 (12.5%) | |
|
| 6.9 (± 1.2) | 5 (26.3%) | 4 (20.0%) | 1 (12.5%) | |
|
| 7.0 (± 1.3) | 3 (15.8%) | 3 (15.0%) | 2 (25.0%) | |
|
| 7.5 (± 0.6) | 4 (21.1%) | 0 (0.0%) | 4 (50.0%) | |
|
| 5.0 (± 0.0) | 0 (0.0%) | 1 (5.0%) | 0 (0.0%) | |
| Previous exposure to genetic issues | 0.56 | ||||
|
| 5.9 (± 2.1) | 94 (45.2%) | 92 (44.2%) | 22 (10.6%) | |
|
| 6.0 (± 2.2) | 125 (49.6%) | 99 (39.3%) | 28 (11.1%) | |
| Completed PGX/pharmacogenetics training or education | 0.00 * | ||||
|
| 6.5 (± 2.2) | 110 (62.5%) | 51 (29.0%) | 15 (8.5%) | |
|
| 5.6 (± 2.1) | 109 (38.4%) | 140 (49.3%) | 35 (12.3%) | |
| Completed internship or study abroad program | 0.00 * | ||||
|
| 5.9 (± 2.2) | 191 (47.0%) | 169 (41.6%) | 46 (11.3%) | |
|
| 3.2 (± 3.4) | 29 (27.4%) | 22 (20.8%) | 55 (51.9%) | |
* significant p-value < 0.05.
Figure 1Views and considerations on genomic medicine and PGX (n = 388).
Figure 2Desire to participate in genetic and PGX research (n = 388).
Figure 3Accessibility and availability of genetic testing (n = 388).
Figure 4Concerns and ethics regarding genomic medicine and PGX (n = 388).