MP44-14 PATIENT-CENTERED RECONSTRUCTION AND EVALUATION OF PROSTATE CANCER INFORMATION MATERIALS
Notice bibliographique
Résumé
You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Practice Patterns, Quality of Life and Shared Decision Making III (MP44)1 Apr 2019MP44-14 PATIENT-CENTERED RECONSTRUCTION AND EVALUATION OF PROSTATE CANCER INFORMATION MATERIALS Alexander E Kiciak*, Andrew Dawson, Thomas Dymond, Michael J Leveridge, D. Robert Siemens, and Jason P Izard Alexander E Kiciak*Alexander E Kiciak* More articles by this author , Andrew DawsonAndrew Dawson More articles by this author , Thomas DymondThomas Dymond More articles by this author , Michael J LeveridgeMichael J Leveridge More articles by this author , D. Robert SiemensD. Robert Siemens More articles by this author , and Jason P IzardJason P Izard More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000556257.33130.ebAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: The Canadian Urological Association (CUA) publishes freely accessible patient information materials (PIM) on a range of urological issues including prostate cancer. Previous work has established that the prostate cancer PIM are written at a grade 11 reading level which may be too complex for low literacy patients. We sought to directly compare the standard CUA PIM to a reconstructed patient-centred PIM. METHODS: PIM covering radical prostatectomy (RP) and radiation therapy (RT) for prostate cancer were rewritten in a simplified format to enhance readability. The final format reflected a 6th grade reading level and was published in a graphical format identical to the original PIM to avoid bias. Patients who had undergone previous treatment for localized prostate cancer or were on active surveillance were recruited from Kingston Health Sciences Centre. Participants evaluated both ″standard″ and ″patient-centred″ formats of both RP and RT topics. PIM formats and topics were randomized in order of presentation. We collected demographic, educational and disease specific details of our participants. Health literacy was assessed using the REALM-SF. Semi-structured interviews were used to obtain qualitative feedback on all PIM. Participants were asked to score the PIM formats on a Likert scale with respect to usefulness, comprehension and preference of one format over the other. RESULTS: There were 61 participants with complete information for analysis. The median age of participants was 70 years (50-86) with a median REALM-SF score of 7 (5-7) and 62% (38/61) had at least some college or university education. Patients had been treated with surgery (35/61), radiation (24/61) and active surveillance (18/61). Usefulness ratings were high for all PIM format but did not vary statistically between formats (p = 0.84). Comprehension ratings were significantly higher in the patient-centred PIM (p<0.01). Preference for PIM format did not reach statistical significance (p=0.32 for RP; p =0.19 for RT). However, within the qualitative feedback 16% of patients commented without prompting that the language within the standard PIM was too complex. Participants also expressed the desire for more information regarding care after treatment. CONCLUSIONS: Within this group of highly educated participants with high health literacy, a simplified written structure improves patient comprehension ratings of informational materials. Future work will focus on revising the informational content of our PIM in an iterative format based on participant feedback. Source of Funding: This project was sponsored by a research grant from the Canadian Urological Association Scholarship Foundation. Kingston, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e634-e634 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Alexander E Kiciak* More articles by this author Andrew Dawson More articles by this author Thomas Dymond More articles by this author Michael J Leveridge More articles by this author D. Robert Siemens More articles by this author Jason P Izard More articles by this author Expand All Advertisement PDF downloadLoading ...
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 | 0,007 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,267 | 0,063 |
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 ».