Pandemic influenza in Australia: Using telephone surveys to measure perceptions of threat and willingness to comply
Bibliographic record
Abstract
BACKGROUND: Baseline data is necessary for monitoring how a population perceives the threat of pandemic influenza, and perceives how it would behave in the event of pandemic influenza. Our aim was to develop a module of questions for use in telephone health surveys on perceptions of threat of pandemic influenza, and on preparedness to comply with specific public health behaviours in the event of pandemic influenza. METHODS: A module of questions was developed and field tested on 192 adults using the New South Wales Department of Health's in-house Computer Assisted Telephone Interviewing (CATI) facility. The questions were then modified and re field tested on 202 adults. The module was then incorporated into the New South Wales Population Health Survey in the first quarter of 2007. A representative sample of 2,081 adults completed the module. Their responses were weighted against the state population. RESULTS: The reliability of the questions was acceptable with kappa ranging between 0.25 and 0.51. Overall 14.9% of the state population thought pandemic influenza was very or extremely likely to occur; 45.5% were very or extremely concerned that they or their family would be affected by pandemic influenza if it occurred; and 23.8% had made some level of change to the way they live their life because of the possibility of pandemic influenza. In the event of pandemic influenza, the majority of the population were willing to: be vaccinated (75.4%), be isolated (70.2%), and wear a face mask (59.9%). People with higher levels of threat perception are significantly more likely to be willing to comply with specific public health behaviours. CONCLUSION: While only 14.9% of the state population thought pandemic influenza was very or extremely likely to occur, a significantly higher proportion were concerned for self and family should a pandemic actually occur. The baseline data collected in this survey will be useful for monitoring changes over time in the population's perceptions of threat, and preparedness to comply with specific public health behaviours.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".