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Enregistrement W4411395469 · doi:10.1016/j.ard.2025.05.581

POS0194-PARE USE OF E-LEARNING IMPROVES KNOWLEDGE AND CONFIDENCE TO MANAGE PAIN AND FLARES IN RA

2025· article· en· W4411395469 sur OpenAlexaff
Alysia Bosworth, IA Scott

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineDentistry
ThématiqueDental Research and COVID-19
Établissements canadiensArthritis Society
Organismes subventionnairesnon disponible
Mots-clésMedicineConfidence intervalMedical physicsFamily medicineInternal medicine

Résumé

récupéré en direct d'OpenAlex

Background: An often insufficient aspect of care in people with inflammatory arthritis (IA) is empowering patients to acquire a good understanding of their disease and building their ability to deal with the practical, physical and psychological impacts of it. The ability to self-manage in IA represents an essential component of care that goes beyond drug therapy and in July 2021, a EULAR Taskforce published evidence-based Recommendations for Self-Management strategies in patients with IA. At the end of 2021 NRAS launched an e-learning programme, SMILE-RA, to address the needs of people with RA to learn to self-manage well. The module on Managing Pain & Flares was developed in partnership with the rheumatology team at MPFT. Objectives: The aims of this service evaluation were to assess: •patients' knowledge and confidence at self-managing their arthritis pain and flares before and after module completion •the burden of pain on patients' lives •the extent to which patients used module suggestions Methods: To address the above issues, NRAS and Dr. Ian Scott with members of the MDT at MPFT, who co-produced this module with NRAS, collaborated to develop a survey which was sent to 500 people with RA who had completed the module on Managing Pain and Flares within SMILE-RA on 25 th March 2024. Reminders to complete the survey were sent and it closed on 12 th May. NRAS received 134 completed surveys representing a 26.8% response rate which is high. People completing the survey may have completed the module at any time since 2021. Some people may have completed the module more than once. NRAS set learning objectives at the start of each module and measure learning outcomes at the end in each module within SMILE-RA. Learning objectives are generally met with scores between 92-100% for all modules. Results: Most participants were aged between 41-60 years (31%), and 61-80 years (63%). As expected, the majority were female (83%) and of white British ethnicity (91%). 96% had a diagnosis of RA with the remainder reporting they had other another type of inflammatory rheumatic disease. Most had 1-5 years (37%) or over 10 years (40%) since their arthritis diagnosis; the remainder had less than one year (14%) and 6-10 years (10%). Knowledge and Confidence Before and After the Module: There was a substantial increase in levels of knowledge about pain and flares following undertaking the module. 35.8% rated themselves as being "very" or "fairly" knowledgeable about pain before completing the module, increasing to 75.4% after completing the module. For flares these results were 29.9%, rising to 68.7%. Similar findings were seen for confidence at managing pain and flares. 28.4% rated themselves as "very" or "fairly" confident at managing their pain before completing the module, rising to 59.7% after module completion. For flares, these results were 23.1% and 50.0%. In addition to the above results, we also asked participants how likely they were to try some of the non-pharmacological suggestions to manage pain and flares in the survey and 43.3% and 41.8% said they were "very likely" or "likely" for pain and flares, respectively. Of those people experiencing pain in the past 3 months, many took pain medicines in the past month, with 62% reporting using paracetamol, 24% Co-codamol/Co-dydramol, 32% oral Non-Steroidal Anti-Inflammatories (NSAIDs), 18% topical NSAIDs, 5% Tramadol, 2% pain patches, 2% Gabapentin or Pregabalin, and 18% other over the counter pain medicines. Only 13% reported not taking any pain medicines in the last month. Many participants had also found non-medication methods to manage pain helpful, including heat therapy (64%), cold therapy (23%), pacing (41%), stress management (25%), distraction (23%), and relaxation (31%). Conclusion: This evaluation of the NRAS SMILE Managing Pain and Flares module has three key findings. First, it highlights the ongoing impact of chronic pain in people with rheumatoid arthritis, with two thirds of people giving module feedback having chronic pain, which was "high impact" in one third of people. Second, it demonstrates that people with RA use a broad range of methods to self-manage their pain, spanning analgesics (particularly paracetamol), and non-drug approaches (with two thirds finding exercise and heat therapy helpful, and one half finding staying positive helpful). Third, it shows that many people felt that their knowledge about their pain and flares, and confidence in managing these were substantially enhanced through undertaking the module. Overall, these findings indicate that the module has an important role to play in enabling people with RA to better self-manage their arthritis related pain and flares which has cost-saving implications for the NHS. REFERENCES: NIL . Acknowledgements: Acknowledgement to the multidisciplinary team at the MPFT and the Haywood Hospital, Stoke-on-Trent. Disclosure of Interests: Ailsa Bosworth NRAS has received educational grants from a number of pharmaceutical companies but not in relation to this abstract, Ian Scott: None declared. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,037
Score d'incertitude au seuil0,123

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0370,006

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.

Tête enseignante Opus0,041
Tête enseignante GPT0,360
Écart entre enseignants0,319 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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Même revueAnnals of the Rheumatic DiseasesMême sujetDental Research and COVID-19Travaux en français237 207