Knowledge, Attitudes and Practices towards SARS-CoV-2 vaccination among morbid obese individuals: a pilot study.
Bibliographic record
Abstract
BACKGROUND AND AIM: Vaccinations have dramatically impacted on the ongoing pandemic of COVID-19, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As morbid obese (MO) individuals are at high risk for severe complications, their acceptance of SARS-CoV-2 vaccines is of certain public health interest. METHODS: We investigated the knowledge, attitudes and eventual acceptance of SARS-CoV-2/COVID-19 vaccination among MO individuals either in waiting list, or recipients of bariatric surgery from a reference center (Parma University Hospital) shortly before the inception of the Italian mass vaccination campaign (March 2021). Data were collected through a web-based questionnaire. Association of individual factors with acceptance of SARS-CoV-2 vaccine was assessed by means of a logistic regression analysis with eventual calculation of adjusted Odds Ratios (aOR) and corresponding 95% Confidence Intervals (95%CI). RESULTS: Adequate, general knowledge of SARS-CoV-2/COVID-19 was found in the majority of MO patients. High perception of SARS-CoV-2 risk was found in around 80% of participants (79.2% regarding its occurrence, 73.6% regarding its potential severity). Acceptance of SARS-CoV-2/COVID-19 vaccination was reported by 65.3% of participants, and was more likely endorsed by MO patients who were likely to accept some sort of payment/copayment (aOR 5.783; 1.426; 23.456), or who were more likely towards a vaccination mandate (aOR 7.920; 1.995; 31.444). CONCLUSIONS: Around one third of the MO individuals among potential recipient of bariatric surgery exhibited some significant hesitancy towards SARS-CoV-2 vaccine, and a rational approach may fail to capture and address specific barriers/motivators in this subset of individuals, stressing the importance for alternative interventions. (www.actabiomedica.it).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".