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Record W3163559629 · doi:10.1136/bmjopen-2021-048720

International survey for assessing COVID-19’s impact on fear and health: study protocol

2021· article· en· W3163559629 on OpenAlexaff
Kris Yuet Wan Lok, Dyt Fong, Janet Yuen Ha Wong, Mandy Ho, Edmond Pui Hang Choi, Vinciya Pandian, Patricia M. Davidson, Wenjie Duan, Marie Tarrant, Jung Jae Lee, Chia‐Chin Lin

Bibliographic record

VenueBMJ Open · 2021
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPandemicMedicineAnxietyHealth literacyPopulationPublic healthGlobal healthEnvironmental healthCoronavirus disease 2019 (COVID-19)GerontologyHealth carePsychiatryDiseaseNursingEconomic growthInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

INTRODUCTION: COVID-19, caused by the SARS-CoV-2, has been one of the most highly contagious and rapidly spreading virus outbreak. The pandemic not only has catastrophic impacts on physical health and economy around the world, but also the psychological well-being of individuals, communities and society. The psychological and social impacts of the COVID-19 pandemic internationally have not been well described. There is a lack of international study assessing health-related impacts of the COVID-19 pandemic, especially on the degree to which individuals are fearful of the pandemic. Therefore, this study aims to (1) assess the health-related impact of the COVID-19 pandemic in community-dwelling individuals around the world; (2) determine the extent various communities are fearful of COVID-19 and (3) identify perceived needs of the population to prepare for potential future pandemics. METHODS AND ANALYSIS: This global study involves 30 countries. For each country, we target at least 500 subjects aged 18 years or above. The questionnaires will be available online and in local languages. The questionnaires include assessment of the health impacts of COVID-19, perceived importance of future preparation for the pandemic, fear, lifestyles, sociodemographics, COVID-19-related knowledge, e-health literacy, out-of-control scale and the Patient Health Questionnaire-4. Descriptive statistics will be used to describe participants' characteristics, perceptions on the health-related impacts of COVID-19, fear, anxiety and depression, lifestyles, COVID-19 knowledge, e-health literacy and other measures. Univariable and multivariable regression models will be used to assess the associations of covariates on the outcomes. ETHICS AND DISSEMINATION: The study has been reviewed and approved by the local ethics committees in participating countries, where local ethics approval is needed. The results will be actively disseminated. This study aims to map an international perspective and comparison for future preparation in a pandemic.

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)0.029
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.052
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.020
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.004
Science and technology studies0.0030.001
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0520.012

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 head0.560
GPT teacher head0.699
Teacher spread0.139 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations21
Published2021
Admission routes1
Has abstractyes

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