Identifying and addressing psychosocial determinants of adherence to physical distancing guidance during the COVID-19 pandemic – project protocol
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".