Evidence map›Paper›PMID 36875955›Full record

ArticleSAGE open

Public Knowledge, Attitudes, and Practices Toward COVID-19 Pandemic: A Cross-Sectional Study in Delhi and National Capital Region (NCR), India.

Upma Gautam, Deeksha Bajpai Tewari

Abstract read
In one paragraph

Article in SAGE open. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Upma GautamUniversity School of Law and Legal Studies, Guru Gobind Singh Indraprastha University, Delhi, India.
Deeksha Bajpai TewariUniversity of Delhi, India.ORCID https://orcid.org/0000-0001-6517-7032

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To assess knowledge, attitudes, and practices of people toward coronavirus disease 2019 (COVID-19) pandemic in National Capital Territory of Delhi and National Capital Region (NCR), India. Various nations, including India, devised strategies to impose lockdowns and movement restrictions on their citizens in order to mitigate the effects of COVID-19. Cooperation and compliance by the populace are crucial to the effectiveness of such measures. People's knowledge, attitudes, and behavior toward such diseases are crucial in determining the adaptability of a society to such changes. Using Google Forms, a self-designed semi-structured questionnaire was created. This study is cross-sectional. Participants were eligible to participate if they were over the age of 18 and presently resided in the study area. The questionnaire included demographic variables such as gender, age, location, occupation, and income level. A total of 1,002 people completed the survey. A 48.80% of the respondents in the study group were females. The mean knowledge score was 13.14 (Maximum Score = 17), while the mean attitude score was 27.24 (Maximum Score = 30). Most of the respondents (96%) had adequate knowledge about the disease's symptoms. A 91% of the respondents had an average attitude score. A 74.85% of respondents accepted that they had avoided large social events. Gender had a negligible impact on the average knowledge score, while the score differed significantly across education levels and occupation categories. Consistent dissemination of messages regarding the virus, its spread, control measures implemented, and precautions expected from the public aids in reassuring the public and reducing their anxiety regarding the virus.

Indexed as

attitudeCOVID-19knowledgelockdownpracticessocial distance

Identifiers

PMID36875955
PMCPMC9969222

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.