Satisfaction with Care among Low-Income Women with Breast Cancer
Notice bibliographique
Résumé
BACKGROUND: Patient satisfaction is an important outcome measure in determining quality of care. There are few data evaluating patient satisfaction in nonwhite, low-income populations. The objective of this study was to identify the structure, process, and outcome factors that impact patient satisfaction with care in a low-income population of women with breast cancer. METHODS: In a cross-sectional survey of low-income women newly diagnosed with breast cancer, eligible women enrolled in the California Breast and Cervical Cancer Treatment Program (BCCTP) from February 2003 through September 2005 were interviewed by phone 6 months after their enrollment. This was a population-based sample of women aged >or=18 years (n = 924) with a definitive diagnosis of breast cancer and enrolled in the BCCTP. The main outcome measure was satisfaction with care received. RESULTS: Random effects logistic regression revealed that less acculturated Latinas were more likely (odds ratio, [OR] = 5.36, p < 0.000) to be extremely satisfied with their care compared with non-Hispanic white women. Women who believed they could have been diagnosed sooner were less likely to be extremely satisfied (OR = 0.61, p < 0.000). Women who had received or were receiving radiotherapy or chemotherapy had nearly twice the odds of being extremely satisfied (OR = 2.02, p < 0.000, and OR = 2.13, p < 0.000, respectively). Greater information giving was associated with greater satisfaction (OR = 1.17, p < 0.000). Women reporting greater physician emotional support were more likely to report being extremely satisfied (OR = 1.26, p < 0.000). A higher participatory treatment decision-making score was associated with greater satisfaction (OR = 1.78, p < 0.000). CONCLUSIONS: In a low-income population, satisfaction is also reported at high levels. In addition to age, ethnicity/acculturation, receipt of chemotherapy and radiotherapy, physician emotional support, and collaborative decision making, perception of diagnostic delay is a predictor of dissatisfaction in this population.
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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».