Knowledge, Attitude and Practice towards COVID-19 Vaccination among adults of Sullia Taluk in Dakshin Kannada District of Karnataka- A Community based Survey)
Bibliographic record
Abstract
Background: Vaccination programs for corona virus disease (COVID-19) were initiated globally in a record time unparalleled in the history of immunisation. Thus the community's and perceptions towards COVID-19 vaccinations are poorly understood. This study thus aimed to investigate community knowledge, attitudes and practices towards COVID-19 vaccinations in Sullia Taluk of Dakshin Kannada. Methods: An exploratory and anonymous population- based survey was conducted among 600 general individuals (58.17% male; 41.83% female). The survey was conducted using a validated self- administered questionnaire containing a set of questions pertaining to knowledge, attitudes, and practices. Multiple linear regression was performed to determine the variables predicting knowledge, and attitudes towards COVID-19 vaccinations. Results: The mean scores of knowledges and attitudes were 2.73±1.48 and 9.44±2.39 respectively. About a quarter of participants thought that the COVID-19 vaccination available in India is safe, 60% reported that they will continue to have further vaccinations if necessary. About 54% reported recommending it to family and friends. Regression analysis revealed that higher SES, university/ higher levels of education, nuclear families and those with a previous history of essential vaccines uptake were associated with a higher knowledge score; whilst attitudes were significantly associated to gender and previous history of essential vaccines uptake. Just over half of the participants(54%) thought that everyone should be vaccinated. A majority of the population 72.17% population reported vaccine should be administered free of cost in India. Keywords:- Covid Vaccination; Survey; Karnatak.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.000 | 0.000 |
| 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".