Perceptions of Risk and Optimistic Bias for Acute Gastrointestinal Illness: A Population Survey
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».