MyPainPal, a Novel mHealth App to Improve Pain in Patients With Advanced Cancer: Single-Arm Pilot Study
Notice bibliographique
Résumé
BACKGROUND: Pain is common among patients with advanced cancer and is often inadequately controlled. Opioids are central to treatment; yet, self-management is challenging, and clinicians lack scalable tools to monitor and support patients between visits. OBJECTIVE: This study aimed to evaluate the feasibility and acceptability of MyPainPal (Dana-Faber Cancer Institute), a novel mobile health app designed to optimize cancer pain management. MyPainPal combines daily surveys assessing symptoms and analgesic use, algorithmic self-management support, tailored psychoeducation, and clinician monitoring. Secondary objectives were to explore preliminary clinical impact and identify priorities for refinement. METHODS: This single-arm pilot study enrolled adults with advanced malignancies using opioids for moderate-to-severe pain from an outpatient palliative care clinic at a comprehensive cancer center. Participants used MyPainPal for 28 days while nurses monitored symptom responses via a secure portal, and also completed structured surveys at end-of-study. Primary assessment of usability and acceptability included the System Usability Scale (SUS; range 0-100), the Acceptability E-Scale (range 6-30), and ratings of satisfaction using a 5-point Likert scale. Semistructured debriefing interviews explored user experience, perceived impact, and suggestions for optimization. RESULTS: Twenty participants with advanced cancer enrolled, with a mean age of 57 (SD 12.3) years, 55% (11/20) female, 80% (16/20) non-Hispanic White, with mixed cancer types. Over the 28-day study, patients logged into MyPainPal a median of 14 (IQR 8-17) times, and completed a median of 8 (IQR 5-14) symptom surveys, reflecting mean of 36% (SD 20%) of eligible (out-of-hospital) days on study. Usability and acceptability ratings of MyPainPal were high (mean SUS 78.3, SD 16.2; mean Acceptability E-Scale 24.0, SD 4.4); 79% rated overall satisfaction of greater than or equal to 4/5. Twenty percent of surveys generated an alert, prompting nurse outreach. In response, 5 participants had symptom medications changed and 2 had medication errors corrected. In debriefing interviews, many participants described that the intervention reduced barriers to pain reporting and facilitated timely and constructive interactions with care teams for symptom management. Several noted that the intervention validated their pain experience, reduced stigma around opioid use, enabled constructive conversations with providers, and promoted self-management. Patients recommended several survey modifications, including reducing their frequency and enabling more nuanced pain assessments. Participants underused the educational resources and suggested that they be featured more prominently. Some patients suggested that the MyPainPal app should be introduced earlier in patients' cancer pain trajectory when pain needs are higher and opioid management is novel. CONCLUSIONS: In this pilot study, MyPainPal demonstrated feasibility, acceptability, and preliminary evidence of potential clinical impact among patients with advanced cancer receiving palliative care. The app has been rebuilt and optimized with attention to patient feedback and in preparation for a future efficacy study. TRIAL REGISTRATION: ClinicalTrials.gov NCT03717402; https://clinicaltrials.gov/study/NCT03717402.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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.
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