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Enregistrement W2327569787 · doi:10.1097/ncc.0b013e31820254db

Does Increased Patient Awareness Improve Accrual Into Cancer-Related Clinical Trials?

2011· article· en· W2327569787 sur OpenAlexaff
Carla Stiles, Laureen Johnson, Darlene Whyte, Tevi Helland Nergaard, Jane Gardner, Jackson Wu

Notice bibliographique

RevueCancer Nursing · 2011
Typearticle
Langueen
DomaineMedicine
ThématiqueEthics in Clinical Research
Établissements canadiensAlberta Health Services
Organismes subventionnairesHealth Research Board
Mots-clésMedicineAccrualClinical trialMEDLINEOncologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

In Brief Background: Oncology literature cites that only 2% to 4% of patients participate in research. Up to 85% of patients are unaware that clinical trials research is being conducted at their treatment facility or that they might be eligible to participate. Objectives: It was hypothesized that patients' satisfaction with information regarding clinical trials would improve after targeted educational interventions, and accruals to clinical trials would increase in the year following those interventions. Methods: All new patients referred to the cancer center over a 4-month period were mailed a baseline survey to assess their knowledge of clinical research. Subsequently, educational interventions were provided, including an orientation session highlighting clinical trials, a pamphlet, and a reference to a clinical trials Web site. A postintervention survey was sent to the responders of the initial survey 3 months after the initial mailing. Results: Patient satisfaction with information significantly increased after the interventions. There was no increase in subsequent enrollment in clinical trials. Patients who indicated an inclination to participate in clinical trials tended to have greater satisfaction with the information they received. Conclusions: A set of educational interventions designed for cancer patients significantly improved their satisfaction with information on clinical research, but did not improve clinical trial enrollment of these participants as of 1 year after the study. Implications for Practice: The development of educational interventions may be justified, but such interventions may require prolonged implementation to establish benefit. Information relating to research may be most effectively delivered by patients' primary cancer care providers. Background: Oncology literature cites that only 2% to 4% of patients participate in research. Up to 85% of patients are unaware that clinical trials research is being conducted at their treatment facility or that they might be eligible to participate. Objectives: It was hypothesized that patients' satisfaction with information regarding clinical trials would improve after targeted educational interventions, and accruals to clinical trials would increase in the year following those interventions. Methods: All new patients referred to the cancer center over a 4-month period were mailed a baseline survey to assess their knowledge of clinical research. Subsequently, educational interventions were provided, including an orientation session highlighting clinical trials, a pamphlet, and a reference to a clinical trials Web site. A postintervention survey was sent to the responders of the initial survey 3 months after the initial mailing. Results: Patient satisfaction with information significantly increased after the interventions. There was no increase in subsequent enrollment in clinical trials. Patients who indicated an inclination to participate in clinical trials tended to have greater satisfaction with the information they received. Conclusions: A set of educational interventions designed for cancer patients significantly improved their satisfaction with information on clinical research, but did not improve clinical trial enrollment of these participants as of 1 year after the study. Implications for Practice: The development of educational interventions may be justified, but such interventions may require prolonged implementation to establish benefit. Information relating to research may be most effectively delivered by patients' primary cancer care providers.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,017
score de la tête « metaresearch » (Gemma)0,066
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,983
Score d'incertitude au seuil0,089

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0170,066
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,002
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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.

Tête enseignante Opus0,638
Tête enseignante GPT0,655
Écart entre enseignants0,017 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
DomaineMéthodes
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations13
Publié2011
Routes d'admission1
Résumé présentoui

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