Exploring the Dynamics: A Comprehensive Scoping Review of Factors Influencing Organ Donation Decisions: A Scoping Review
Bibliographic record
Abstract
Background: This scoping review explores the key demographic and psychosocial factors impacting organ donation, with a focus on studies utilizing online or digital platforms. We aimed to understand the existing facts that influence to effects of the organ donation decision. Methods: This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A comprehensive search of PubMed, CINAHL, and Medline was conducted using MeSH terms and logical operators to identify relevant studies published in English 2018 to 2023. Studies focusing on the demographics and influencing factors for organ donors of any age were included. Abstract concepts, conference proceedings, and non-English studies were excluded. Data extraction and quality assessment were independently conducted by two reviewers using standardized tools, including the Newcastle-Ottawa Scale, Cochrane Risk of Bias tool, and Joanna Briggs Institute checklist. Results: Out of 270 records identified, 9 studies met the inclusion criteria. The synthesis of results revealed three major themes: 1) demographic characteristics of organ donors, 2) psychosocial and digital factors influencing organ donation, and 3) interventions promoting awareness and engagement in organ donation. Online and digital platforms play a significant role in shaping attitudes, intentions, and awareness of organ donation. Quality assessment indicated a moderate-to-high level of methodological rigor across the included studies. Conclusion: This review highlights the key factors influencing organ donation, particularly the role of digital platforms in enhancing awareness and engagement. Future research should focus on leveraging these insights to develop targeted interventions aimed at increasing organ donation rates globally.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".