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Record W4252244591 · doi:10.12688/hrbopenres.13090.1

Identifying and addressing psychosocial determinants of adherence to physical distancing guidance during the COVID-19 pandemic – project protocol

2020· preprint· en· W4252244591 on OpenAlexaff
Hannah Durand, Simon Bacon, Molly Byrne, Eanna Kenny, Kim Lavoie, Brian E. McGuire, Jenny McSharry, Oonagh Meade, Robert Mooney, Chris Noone, Laura O’Connor, Kate O'Flaherty, Gerard J. Molloy

Bibliographic record

VenueHRB Open Research · 2020
Typepreprint
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversité du Québec à MontréalConcordia UniversityHôpital du Sacré-Cœur de Montréal
FundersIrish Research CouncilHealth Research Board
KeywordsDistancingPsychosocialSocial distancePandemicPublic healthPsychologyCoronavirus disease 2019 (COVID-19)MedicineNursingPsychiatryDisease

Abstract

fetched live from OpenAlex

Optimising public health physical distancing measures has been a critical part of the global response to the spread of COVID-19. Evidence collected during the current pandemic shows that the transmission rate of the virus is significantly reduced following implementation of intensive physical distancing measures. Adherence to these recommendations has been poorer than adherence to other key transmission reduction behaviours such as handwashing. There are a complex range of reasons that are likely to predict why people do not or only partially adhere to physical distancing recommendations. In the current project we aim to address the following research questions: (1) What are the psychosocial determinants of physical distancing for the general public and for key socio-demographic sub-groups (e.g., young adults, older adults, etc.)?; (2) Do current Government of Ireland COVID-19 physical distancing communications address the determinants of physical distancing?; and (3) How can communications be optimised and tailored to sub-groups to ensure maximum adherence to guidelines? These will be addressed by conducting three work packages (WPs). In WP1, we will work closely with the iCARE international study, which includes a large online survey of public responses to measures established to reduce and slow the spread of COVID-19, including physical distancing. We will analyse Irish data, comparing it to data from other countries, to identify the key psychosocial determinants of physical distancing behaviour. This will be followed by a qualitative study to explore in depth the barriers and facilitators of physical distancing behaviour among the Irish public (WP2). In WP3, we will conduct a content analysis and evidence mapping of current government messaging around physical distancing, to ensure the findings from this research feed into the development of ongoing communication and future messaging about physical distancing.

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)0.042
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.169
Threshold uncertainty score0.564

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.040
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0020.002
Science and technology studies0.0060.003
Scholarly communication0.0040.004
Open science0.0060.007
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.1690.043

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 head0.686
GPT teacher head0.671
Teacher spread0.015 · 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
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

Citations9
Published2020
Admission routes1
Has abstractyes

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