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Record W4313470775 · doi:10.6000/1929-6029.2022.11.22

Vaccination, Compliance with Preventive Measures and Mental Health during COVID-19 among Adults in Bangladesh: Do Vaccination and Compliance with Preventive Measures Improve Mental Health?

2022· article· en· W4313470775 on OpenAlexvenueno aff
Bipasha Singha, Shamal Chandra Karmaker, M. Mazharul Islam, Kareman Eljamal, Bidyut Baran Saha

Bibliographic record

VenueInternational Journal of Statistics in Medical Research · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnxietyVaccinationMental healthDepression (economics)Logistic regressionPandemicCompliance (psychology)Descriptive statisticsEnvironmental healthPsychiatryCoronavirus disease 2019 (COVID-19)DiseasePsychologyInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

Background and Objective: In addition to the reduction of risk of COVID-19 transmission and mortality, vaccination and compliance with the preventive measures of COVID-19 may have important additional benefits for the improvement of mental health. This study examined the levels and determinants of vaccination, compliance with preventive measures, and anxiety, depression and stress among Bangladeshi adults. It also examined the effects of vaccination and compliance with preventive measures on mental health status among Bangladeshi adults. Methods: Data for the study come from an online survey conducted during November and December 2021 among Bangladeshi adults. A total of 615 adults participated in the survey. A 21-item Depression, Anxiety, and Stress scale (DASS 21) were used for collecting data on mental health. Both descriptive and inferential statistical methods including multiple logistic regression were used for data analysis. Results: About 69% of Bangladeshi adults were vaccinated with at least one dose; 87% of adults believed that vaccines are moderate to highly effective in reducing COVID-19 infection. Among the preventive measures during a pandemic, the level of complete compliance with wearing masks and hand washing was almost universal, while the compliance level with other preventive measures was moderate. Vaccinated people had a 55% (OR=0.45; 95%CI:0.26-0.82), 67% (OR=0.33; 95%CI:0.12-0.91), and 44% (OR=0.56; 95%CI:0.27-0.97) lower chance of suffering from depression, anxiety, and stress, respectively than non-vaccinated people. People with complete compliance had 64% (OR= 0.36; 95%CI:0.18-0.72), 71% (OR=0.29; 95%CI:0.15-0.58), and 74% (OR=0.26; 95%CI:0.13-0.50) lower risk of suffering from depression, anxiety, and stress, respectively, than respondents with irregular preventive behaviors. Conclusion: This study documents the important psychological benefits of vaccination and compliance with preventive measures of COVID-19.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.086
GPT teacher head0.486
Teacher spread0.401 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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