Perceptions and Attitudes towards Medical Research in the United Arab Emirates: Results from the Abu Dhabi Cohort Study (ADCS) Focus Group Discussions
Bibliographic record
Abstract
BACKGROUND: In developing medical research, particularly in regions where medical research is largely unfamiliar, it is important to understand public perceptions and attitudes towards medical research. In preparation for starting the first cohort study in the United Arab Emirates, the Abu Dhabi Cohort Study (ADCS), we sought to understand how we could improve the quality of the research process for participants and increase public trust and awareness of research. METHODS: We conducted six focus groups (FG), consisting of Emirati men and women aged above 18 years to resemble the target population for the ADCS. Sampling was purposive and convenient. Data collection was an iterative process until saturation was reached with no new themes identified. Text from each FG was analyzed separately by identifying emerging issues and organizing related concepts into categories or themes. A coding tree was developed, consisting of the main concepts, themes, subthemes and corresponding quotes. Both themes and main ideas were identified using inductive analysis. RESULTS: Forty-two participants enrolled at 3 academic centers (New York University Abu Dhabi, UAE University, Zayed University) and the Abu Dhabi blood bank. Focus group participants described lack of awareness of research as a challenge to participation in clinical research studies. Altruism, personal relevance of the research, and the use of role models were commonly identified motivators. Participants were generally satisfied with the informed consent process for the ADCS, but would be disappointed if not provided test results or study outcomes. Fear of a breach in confidentiality was a frequently expressed concern. CONCLUSIONS: Participants join research studies for varied, complex reasons, notably altruism and personal relevance. Based on these insights, we propose specific actions to enhance participant recruitment, retention and satisfaction in the ADCS. We identified opportunities to improve the research experience through improved study materials and communication to participants and the broader community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".