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Record W3214166353 · doi:10.1093/eurpub/ckab164.585

COVID-19: Identifying and addressing determinants of adherence to physical distancing guidance

2021· article· en· W3214166353 on OpenAlexaff
Hannah Durand, SL Bacon, Molly Byrne, Karen Farrell, Eanna Kenny, KL Lavoie, Brian E. McGuire, Jenny McSharry, Oonagh Meade, GJ Molloy

Bibliographic record

VenueEuropean Journal of Public Health · 2021
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversité du Québec à MontréalConcordia UniversityHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsDistancingPsychosocialSocial distancePublic healthGovernment (linguistics)PsychologyPsychological interventionPandemicQualitative researchMedicineEnvironmental healthSocial psychologyCoronavirus disease 2019 (COVID-19)NursingPsychiatrySociologyDisease

Abstract

fetched live from OpenAlex

Abstract Background Optimising physical distancing measures has been a critical part of the global response to the spread of COVID-19. Adherence to these recommendations has been poorer than adherence to other key transmission reduction behaviours. The current project aimed to identify psychosocial determinants of adherence to physical distancing, and to determine whether Government of Ireland COVID-19 communications adequately address the determinants. Methods A nationally representative cross-sectional survey as part of the International COVID-19 Awareness and Responses Evaluation (iCARE) study, a qualitative interview study, and a content analysis of COVID-19 poster communications were conducted to identify psychosocial determinants of adherence and determine the extent to which these were addressed in government communications. Results The iCARE survey showed adherence to physical distancing measures varies by sociodemographic group (e.g., age, sex, COVID-19 risk category) and beliefs. Poorest adherence was reported by younger people, males, those at lower risk of serious illness from COVID-19, and those who were less concerned about the impact of COVID-19 on public health and the economy. The qualitative interview study revealed maintaining and negotiating close relationships, public physical environments, habituation to threat, risk-taking to maintain wellbeing, and confusion and uncertainty around government guidelines as barriers to physical distancing behaviour. Having a sense of personal responsibility and control over one's own behaviour was identified as a potential facilitator of adherence to distancing. Content analysis revealed some important gaps, particularly in terms of rationale for specific public health guidelines. Conclusions Though adherence was high overall, there was variability among sociodemographic groups. Government communications to promote physical distancing could be refined to better address key barriers and facilitators of the behaviour.

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)0.013
metaresearch head score (Gemma)0.040
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 score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.318
GPT teacher head0.503
Teacher spread0.185 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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