Knowledge, Attitudes, and Fear of COVID-19 during the Rapid Rise Period in Bangladesh
Bibliographic record
Abstract
ABSTRACT Objectives To determine the level of Knowledge, Attitude, and Practice (KAP) related to COVID-19 preventive health habits and perception of Fear towards COVID-19 in subjects living in Bangladesh. Design Prospective, cross-sectional survey of (n= 2157) male and female subjects, 13-90 years of age, living in Bangladesh. Methods Ethical Approval and Trial registration were obtained prior to the commencement of the study. Subjects who volunteered to participate and signed the informed consent were enrolled in the study and completed the “Fear of COVID-19 Scale” (FCS). Results Twenty-eight percent (28.69%) of subjects reported one or more COVID-19 symptoms and 21.4% of subjects reported one or more comorbidities. Knowledge scores were slightly higher in males (8.75± 1.58) than females (8.66± 1.70). Knowledge was significantly correlated with age (p<.005), an education level (p<.001), Attitude (p<.001), and urban location (p=<.001). Knowledge scores showed an inverse correlation with Fear scores (p=<.001). Eighty-three percent (83.7%) of subjects with COVID-19 symptoms reported wearing a mask in public and 75.4% of subjects reported staying away from crowded places. Subjects with one or more symptoms reported higher Fear compared to subjects without (18.73± 4.6; 18.45± 5.1). Conclusions Overall, Bangladeshis reported a high prevalence of self-isolation, positive preventive health behaviors related to COVID-19, and moderate to high fear levels. Higher Knowledge and Practice were found in males, higher education levels, older age, and urban location. “Fear” of COVID-19 was more prevalent in female and elderly subjects. Positive “Attitude” was reported for the majority of subjects, reflecting the belief that COVID-19 was controllable and containable. Ethical approval Ethical permission obtained from the Institutional review board (BPA-IPRR/IRB/29/03/2020/021) of Institute of Physiotherapy, Rehabilitation, and Research (IPRR), the academic organization of the Bangladesh Physiotherapy Association. WHO Trial registry The trial registration obtained prospectively from a primary trial registry of WHO (CTRI/2020/04/024413). Data Availability The data are available regarding this study and can be viewed upon request
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".