The unseen pandemic: treatment delays and loss to follow-up due to fear of COVID
Bibliographic record
Abstract
BACKGROUND: Fear of contracting SARS-CoV-2 has transformed public interaction with healthcare professionals and hospitals alike. In turn, this has resulted in a collateral impact on patients' health across medical and surgical paradigms. Understanding the causative factors of this fear, and tackling it head on, is vital to return to pre-pandemic levels of healthcare. MAIN BODY: In this editorial, we explore the evidence base behind the fear of healthcare professionals and facilities that has developed during the course of the SARS-CoV-2pandemic. We also reflect on the ways in which these fears have affected the general public. In so doing, we review a recent article from Montalto et al. that has explored fear of SARS-CoV-2 among patients undergoing surgery in Italy. CONCLUSION: While fear of SARS-CoV-2 is uncommon among surgical patients, there are still those who delay or avoiding seeking medical care due to fear of transmission. Physicians must lead the fight against this fear in a hope to regain the trust of the public.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".