Perceptions of Risk and Optimistic Bias for Acute Gastrointestinal Illness: A Population Survey
Bibliographic record
Abstract
Optimistic bias refers to the tendency of individuals to believe that they are less likely to experience negative events compared with other people. Individuals who perceive their risk of an adverse health event to be low may not be as receptive to informational messages aimed at disease prevention. Our objective was to estimate the magnitude of optimistic bias for acute gastrointestinal illness, and to describe demographic associations with, and reasons for, individuals' perception of personal risk. Data were obtained by a retrospective, cross-sectional telephone survey of 2057 randomly selected English-speaking residents of Ontario, Canada conducted between May 2005 and April 2006. Data were collected on the occurrence of acute gastrointestinal illness during the 28 days prior to the survey, demographics, respondents' perception of their personal risk of acute gastrointestinal illness compared with the average person, and the reasons for this perception. Associations with perception of illness were evaluated using ordinal logistic regression and reasons for perception of risk were explored qualitatively. Optimistic bias was present among all respondents, but was not statistically significant within the group that had experienced acute gastrointestinal illness in the previous 28 days. Rural residency and not having experienced acute gastrointestinal illness in the previous 28 days were associated with a lower perception of risk compared with the average person. Proportionally fewer individuals who had not completed secondary education saw themselves as at less than average risk. The most common reason given for the perception of lower risk was that the respondent was healthier than the average person, although personal lifestyle choices also were provided as reasons. The presence of optimistic bias may negatively impact compliance with public health initiatives to reduce acute gastrointestinal illness. Therefore, recognizing the demographic characteristics associated with a perception of lower risk and understanding the reasons for this perception may help with targeting effective preventive messaging.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".