Fear of COVID-19 among the Indian youth: A cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Coronavirus disease is a highly infectious and fatal disease. It has caused distress in the form of fear, and anxiety among masses including youth. The psychosocial health of youth is important to build resilient nations after the pandemic is over.This study aimed to capture the level of COVID-19 fear among youth studying in a northern Indian university and to compare it with demographic variables. MATERIALS AND METHODS: This was a cross-sectional study (April-May 2020) conducted among university students in North India. Fear of COVID-19 Scale (FCV-19S) was used for online survey using Google Forms. FCV-19S is a reliable tool for assessing the fear of COVID-19 among the general population. Descriptive statistics and principal component analysis (PCA) with varimax rotation were used for statistical analysis. RESULTS: A total of 521 responses were recorded. The majority (78%) of the participants were in the age group of 18-23 years and more than half (57%) were pursuing graduation. The respondents belonged to 16 states and union territories in the country. A total of 17% reported severe fear, while a few reported moderate (17%) or mild (11%) fear on the FCV-19S. No respondent could be categorized with "no fear" based on the overall FCV-19S score. Approximately, 42% of respondents were nervous after watching news/social media posts about COVID-19. Based on PCA, factor 1 labeled as anxiety toward COVID-19, factor 2 media effect on shaping of fear, and factor 3 thanatophobia as contributing factors for fear among youth. CONCLUSIONS: Reflection of fear among youth suggests that adequate knowledge about COVID-19, preventive steps, treatment options, etc., may be planned to allay fears among youth.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".