A Web- and Mobile-Based Intervention for Women Treated for Breast Cancer to Manage Chronic Pain and Symptoms Related to Lymphedema: Randomized Clinical Trial Rationale and Protocol
Notice bibliographique
Résumé
BACKGROUND: Despite current advances in cancer treatment, many breast cancer survivors still face long-term post-operative challenges as a result of suffering from daily pain and other distressing symptoms related to lymphedema, ie, abnormal accumulation of lymph fluid in the ipsilateral upper limb or body. Grounded in research-driven behavioral strategies, The-Optimal-Lymph-Flow is a unique Web- and mobile-based system focusing on self-care strategies to empower, rather than inhibit, how breast cancer survivors manage daily pain and symptoms. It features a set of safe, feasible, and easily-integrated-into-daily-routine exercises to promote lymph flow and drainage, as well as guidance to maintain an optimal body mass index (BMI). OBJECTIVE: To conduct a randomized clinical trial (RCT) to evaluate the efficacy of the Web- and mobile-based The-Optimal-Lymph-Flow system for managing chronic pain and symptoms related to lymphedema. The primary outcome includes pain reduction, and the secondary outcomes focus on symptom relief, limb volume difference by infra-red perometer, BMI, and quality of life (QOL) related to pain. We hypothesize that participants in the intervention group will have improved pain and symptom experiences, limb volume difference, body mass index, and QOL. METHODS: A parallel RCT with a control-experimental, pre- and post-test, repeated-measures design is used in this study. A total of 120 patients will be randomized according to the occurrence of pain. Participants will be recruited face-to-face at the point of care during clinical visits. Participants in the intervention group will receive the Web- and mobile-based The-Optimal-Lymph-Flow intervention and will have access to and learn about the program during the first in-person research visit. Participants in the control group will receive the Web- and mobile-based Arm Precaution program and will have access to and learn about the program during the first in-person research visit. Participants will be encouraged to enhance their learning by accessing the program and following the daily exercises during the study period. Participants will have monthly online self-report of pain and symptoms at 4 and 8 weeks post-intervention. During the two in-person research visits prior to and 12 weeks post-intervention, participants will be measured for limb volume difference, BMI, and complete self-report of pain, symptoms, self-care behaviors, and QOL. RESULTS: This trial is currently open for recruitment. The anticipated completion date for the study is July 2017. The primary endpoint for the study is absence or reduction of pain reported by the participants at week 12 post-intervention. CONCLUSIONS: The-Optimal-Lymph-Flow is a unique Web- and mobile-based self-care and patient-reported outcome system designed to effectively help women treated for breast cancer manage daily pain and symptoms related to lymphedema. Patients learn self-care strategies from a Web- and mobile-based program and track their symptoms. The RCT will directly benefit all women treated for breast cancer who suffer from or at risk for pain and symptoms related to lymph fluid accumulation. TRIAL REGISTRATION: Clinicaltrials.gov NCT02462226; https://clinicaltrials.gov/ct2/show/NCT02462226 (Archived by WebCite at http://www.webcitation.org/6du4IupG5).
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 | 0,014 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,002 |
| Méta-épidémiologie (sens large) | 0,008 | 0,004 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,006 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,035 | 0,005 |
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 ».