Exploring Motives Behind Ideal Melanoma Survivorship Care Plans With Multiple Stakeholders: A Cocreation Study
Notice bibliographique
Résumé
BACKGROUND: Survivorship care plans (SCPs), ie, personalized health care plans for cancer survivors, can be used to support the growing group of melanoma survivors throughout their disease trajectory. However, implementation and effectiveness of SCPs are suboptimal and could benefit from the involvement of stakeholders in developing a user-centered design. OBJECTIVE: The aim of this study was to identify the ideal SCP for patients with melanoma in terms of functions and features to be included according to different stakeholders and to explore their underlying motives. METHODS: In total, 3 cocreation sessions were organized with mixed samples of stakeholders, ie, patients with (a history of) melanoma (n=4), health care providers (HCPs) active in melanoma care (n=3), and IT specialists active in hospital IT departments (n=6). They were invited to compose their ideal melanoma SCP based on potential functions and features identified from prior qualitative research. These functions and features belonged to one of the four main categories of survivorship care (SSC): (1) information and education, (2) identification and treatment, (3) oncological follow-up, and (4) coordination. Participants were invited to explain their motives for including functions and features. Ideas were shared between stakeholders, and interaction was promoted. Descriptive statistics were used to determine the ideal SCP per stakeholder group. To analyze underlying motives, all cocreation sessions were audio-taped, transcribed verbatim, and analyzed in a thematic content analysis. RESULTS: With regard to their ideal SCPs, all stakeholders added functions from all 4 SSC categories. Patients assembled a rather compact SCP with category 2 on identification and treatment being most important. Both HCPs and IT professionals constructed a somewhat larger SCP, with category 3 on oncological follow-up being the most important aspect and HCPs also focusing on category 4 on coordination. As for the motives behind their ideal SCP compositions, patients predominantly added functions based on their personal experiences or experiences from fellow patients, whereas both HCPS and IT professionals based their compositions primarily on their respective areas of expertise: HCPs related their additions to their roles as medical practitioners; for example, in providing a complete treatment plan and obtaining informed consent, while IT professionals' contributions were mainly influenced by feasibility and privacy concerns. CONCLUSIONS: This cocreation study provides insights into stakeholders' ideal melanoma SCP and the motivations behind them. Considering the diversity in both the preferences and underlying motives regarding SCP composition between patients, HCPs, and IT specialists, it is crucial to develop a broad SCP that extends beyond traditional SCP content, emphasizing personalization. In addition to continued stakeholder involvement, efforts should be focused on addressing potential feasibility and privacy issues to ensure the SCP meets both patients' and HCPs' needs.
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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 | 0,029 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,006 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,002 | 0,009 |
| Intégrité de la recherche | 0,002 | 0,004 |
| 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 ».