A Training Program on Pain Coping Skills for African Americans With Hip or Knee Arthritis
Notice bibliographique
Résumé
This research project is in progress. PCORI will post its findings here within 90 days after our final review is complete. In the meantime, results have been published in peer-reviewed journals, as listed below. Background and Significance: Osteoarthritis (OA) is a leading cause of pain and disability. African Americans have a greater burden of OA. In this demographic group, compared with Caucasians, OA is more common and associated with more severe pain and activity limitations. Existing research suggests that a program called pain Coping Skills Training (CST) has strong potential for helping African Americans with OA reduce their symptoms. However, important limitations remain about what is known in this research, which limits putting CST into practice. First, there is a need to incorporate the perspectives of African Americans with OA, as well as other key stakeholders, into this program; this is necessary to ensure that the program is culturally relevant and that it can be successfully used in a variety of clinical and community settings. Second, there is still a need for a study that will test the effectiveness of pain CST, specifically among African Americans with OA, in “real-world” settings. Therefore, the objective of this project is to examine the effectiveness of a culturally enhanced pain CST program among African Americans with OA. Study Aims: This project has three specific aims: (1) to engage African-American patients with OA, their support partners, healthcare providers, clinic administrators, and public health representatives in a process of evaluating and enhancing a pain CST program for culturally appropriate content and dissemination potential; (2) to examine the effectiveness of a 12-session, culturally enhanced, telephone-based pain CST program among African Americans with hip or knee OA; and (3) to examine whether individual patient characteristics are associated with different levels of improvement in the CST program. The long-term objective of this research is to develop and disseminate an evidence-based pain CST intervention among African Americans with OA to reduce disparities in outcomes. Study Description: After the incorporation of stakeholder perspectives into the pain CST program, we will conduct a randomized controlled trial. We will enroll 248 African Americans with hip or knee OA. They will be randomized into two groups. One group will take part in a two-week pain CST intervention. The other group will be a “wait list” that receives the pain CST program after completing all follow-up study measures. All study participants will be able to continue any other usual medical care for their OA during the study period. The pain CST intervention includes 12 individual sessions with a study counselor, delivered via telephone to enhance access and reach. The sessions include the following: general information about why pain CST is important, training in specific pain coping skills (such as progressive muscle relaxation, communication, imagery, and activity pacing), and guided practice with each skill. The CST program will also include information about other behaviors important for OA, such as physical activity and weight management. Outcomes: The main study outcome will be the pain subscale of the Western Ontario and McMasters Universities Osteoarthritis Index (WOMAC). Other outcomes will include the WOMAC function subscale, coping strategies questionnaire, arthritis self-efficacy scale, depressive symptoms, health-related quality of life, and patient global impression of change. These measures were selected based on stakeholder input and prior research that showed these outcomes as important to patients with OA. Statistical models will be used to compare outcomes between the two study groups at each time point: baseline, 12 weeks (after completion of the initial CST intervention), and 36 weeks (about 6 months after intervention completion). We will also assess whether there are different levels of improvement in outcomes of the CST intervention, based on participant characteristics.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,001 |
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 ».