A Culturally Tailored Mobile Health Intervention to Improve Quality of Life in Black Survivors With Prostate Cancer: Protocol for a Stratified Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Prostate cancer (CaP) disproportionately affects Black men in the United States, leading to significant disparities in incidence, survival, and quality of life (QoL). Treatment-related side effects, including urinary dysfunction, pain, fatigue, and psychological distress, contribute to poor long-term outcomes. There is an urgent need for culturally-tailored, technology-based interventions to support symptom self-management and survivorship care. OBJECTIVE: This study aims to develop, refine, and evaluate the Survivorship App for Ethnically Diverse Black Prostate Cancer Survivors (SAFE-CaPS), a tailored mobile health intervention designed to enhance QoL, improve symptom self-management, and provide psychosocial support. METHODS: This 12-month stratified randomized clinical trial will enroll 248 Black survivors with CaP (including native born, African-born, and Caribbean-born men) into the SAFE-CaPS intervention arm and standard care (SC) control group (1:1 allocation). Eligible participants are self-identified Black men (including native born, African-born, and Caribbean-born) aged 40 to 80 years with a confirmed CaP diagnosis within the past 5 years who own or are willing to use a smartphone. SC will consist solely of routine oncology or primary care follow-up, including clinic visits, referrals, and supportive services as needed, with no digital components. The SAFE-CaPS intervention, developed using the Insight platform, includes daily and weekly ecological momentary assessments of pain, urinary and bowel symptoms, sleep, fatigue, sexual function, mood, physical activity, and diet; adaptive educational modules addressing treatment-related side effects and culturally grounded survivorship concerns; automated symptom alerts prompting nurse follow-up and provider notification; and engagement features such as reminders, goal-setting, and literacy-appropriate content. Intervention content incorporates culturally tailored messaging, patient narratives, and feedback from prior qualitative work with ethnically diverse Black CaP. Stratified randomization will ensure balanced representation of ethnic subgroups. Primary outcomes include overall QoL. Secondary outcomes include specific symptom domains, mental health (depression and anxiety), health care engagement, and app acceptability. Assessments will occur at baseline, 3, 6, 9, and 12 months, and linear mixed models with intent-to-treat principles will evaluate intervention effects over time. RESULTS: The study was funded in 2024, institutional review board approval was received in mid-2024, and the study began recruitment on August 24, 2025. Overall, 6 participants have been enrolled, with 2 in the SAFE-CaPS intervention and 4 in SC. Recruitment is expected to conclude in July 2027. Data analysis will occur in late 2027, with article preparation and publication planned for mid-2028 and early 2029. We hypothesize that SAFE CaPS participants will experience greater improvements in QoL, reduced symptom burden, and higher engagement in care compared to SC. CONCLUSIONS: This study will provide critical evidence on the feasibility, acceptability, and preliminary effectiveness of a culturally tailored mobile health intervention designed to enhance survivorship outcomes among Black survivors with CaP, informing future large-scale trials and real-world implementation. TRIAL REGISTRATION: ClinicalTrials.gov NCT06651359; https://clinicaltrials.gov/study/NCT06651359. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/81503.
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 | 0,019 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,009 | 0,006 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,005 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,088 | 0,011 |
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 ».