Preventive Health Behaviors in Unaffected High-Risk Women: The Impact of Perceived vs Actual Risk and Preferred Involvement in Decision-Making.
Notice bibliographique
Résumé
Abstract Background: While major advances have been made in the diagnosis and treatment of breast cancer, more limited progress has been made in the prevention of the disease. Although several clinical trials have demonstrated the advantages of lifestyle alteration, weight loss and use of anti-estrogens, uptake of such strategies is generally sporadic in women at high risk. It has been particularly challenging to engage even women at very high risk in clinical trials aimed at primary prevention. These decisions may be influenced by several factors, among which perceived risk, actual risk and preferences for participation in preventive decision making may be particularly important. In this project, we seek to describe how perceived risk, actual risk and the preferred level of involvement in the decision jointly impact the risk management intentions and subsequent decisions.Methods: As a regular component of risk assessment process at the High Risk Breast Assessment Clinic (HRBAC) of the Ottawa Regional Women's Breast Health Centre, a detailed questionnaire is administered to women referred to the clinic before their first risk assessment consultation. The questionnaire includes several items required for calculating actual risk (using Gail score) as well as questions concerning health practices (breast screening, clinical breast examination, breast self-examination) and lifestyle practices (weight, height, smoking, alcohol and physical activity). Women's perceived risk is assessed by the following question: “What do you think the likelihood is of you developing breast cancer in your lifetime?”, and women are required to provide a percentage to express their risk. Women are also asked to indicate their intentions about breast cancer prevention and to identify which prevention strategy is the most important to them. Preferred role involvement in decision making is also assessed by the following question: “What role would you like to take in making your decision?”and women are classified as active or passive. Patient's charts are used to obtain information about the prevention decisions that women made 1 year after receiving risk counselling.We hypothesize that risk reduction counselling will weaken the association between perceived risk and prevention decisions and conversely will strengthen the correlation between actual risk and risk reduction option considered by women.Results: Correlational and chi-square analyses of the demographic data, actual(calculated0 and perceived risk, as well as prevention behaviour uptake obtained from 300 patients will be presented. A low correlation between perceived and actual risks is expected before patients receive risk counselling at the clinic. Statistically reliable association between perceived risk and precounselling prevention intentions and a low level association between actual risk and precounselling prevention intentions are also expected. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 1040.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,011 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».