Notice bibliographique
Résumé
<div> Introduction Hypothetical bias continues to be a primary challenge for stated preference methods. The source of hypothetical bias might be approached from the conceptual framework of “psychological distance.” By comparing the two samples of pregnant and non-pregnant women, this study aimed to investigate the impact of psychological distance from real-life choice on prenatal screening and diagnostic strategies preferences. Method A discrete choice experiment was conducted among a sample of pregnant women and a sample of the general Canadian population. The attributes included: timing of the results, false-negative rate, false-positive rate, risk of miscarriage, and out-of-pocket cost. The dual response design, including forced and unforced choices, was used. Hierarchical Bayes modelling was employed to estimate part-worth utilities at the individual level. The relative importance scores of the attributes and willingness to pay for improvement in attributes were compared between pregnant and non-pregnant women. Using the individual-level preference weights, we also estimated the uptake rates for various scenarios and compared the two samples. We quantified hypothetical bias by comparing the real-world decision and predicted choices for different strategies for the pregnant and non-pregnant women samples. Results A sample of 426 pregnant women was matched to 426 non-pregnant women from the general public sample. For pregnant women, the ability to detect chromosomal abnormalities was the most important attribute. For the matched sample of non-pregnant women, false-negative rate and risk of miscarriage were the most important attributes. In addition, pregnant women were willing to pay more for improvement in test characteristics and less sensitive to changes in strategy cost than non-pregnant women. The findings also showed a more significant difference between the actual and predicted choice among non-pregnant women. Conclusion Our findings showed that although both groups valued safer and more accurate screening strategies, there was a difference in willingness to pay, sensitivity to cost, and predictive power of discrete choice experiment estimates between pregnant and non-pregnant women. This difference can be explained by their psychological distance from the decision. In conclusion, psychological distance impacts decision-making and can be identified as a source of hypothetical bias in measuring prenatal screening and diagnosis preferences. </div>
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 | 0,020 | 0,309 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,482 | 0,011 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».