P103 Evaluation of an online learning module from the National Rheumatoid Arthritis Society to support the self-management of pain and flares in people with rheumatoid arthritis
Notice bibliographique
Résumé
Abstract Background/Aims Many people with rheumatoid arthritis (RA) have chronic pain and arthritis flares. Supporting their self-management of these disease impacts is therefore crucial to improving their quality of life. To address this, the National RA Society (NRAS) co-developed an online learning module for people with RA on managing pain and flares (embedded in their “SMILE-RA” e-learning programme) in collaboration with the Midlands Partnership University NHS Foundation Trust multidisciplinary rheumatology team. The aim of this service evaluation was to assess patients’ knowledge and confidence at self-managing arthritis pain and flares pre- and post-module completion. It also examined the burden of pain on patients’ lives/the extent to which patients used module suggestions. Methods The module was launched in September 2021. A survey was sent via email in March 2024 (available until May 2024) to the 500 people completing the module consenting to contact for feedback. Survey questions covered: (1) demographics; (2) pain experience/management; (3) knowledge/confidence on managing pain/flares (Likert-type responses); (4) likelihood of trying module suggestions (Likert-type responses); (5) free-text feedback. Descriptive statistics summarised survey responses as proportions/means (with standard deviations [SD]) as appropriate. Fisher’s exact tests compared Likert-type responses for knowledge and confidence pre-/post-module. Results Demographic/Arthritis Characteristics: 134 patients completed the survey (27% response rate). 95% reported having RA (5% reported other inflammatory arthritis types). Most (63%) were aged 61-80 years and female (83%). Pain Experience/Management: 98% experienced pain in the past 3 months, present “every/most days” in 63%. Approximately one-third (36%) reported “high impact” chronic pain. Of those with pain in the past 3 months, 87% used analgesics in the last month. Many found non-drug pain care helpful, particularly heat therapy (64%) and exercise (61%). Knowledge/Confidence: The proportion rating themselves “very/fairly/somewhat” knowledgeable at managing pain rose from 62% pre-module to 95% post-module (P = 0.01) and for managing flares from 52% pre-module to 93% post-module (P<0.01). For confidence at managing pain, the proportion rating themselves “very/fairly/somewhat” confident rose from 50% pre-module to 90% post-module (P<0.01) and for managing flares from 44% pre-module to 90% post-module (P<0.01). Using Module Suggestions: 79% and 78% reported they were “very likely/likely/fairly likely” to try module suggestions to manage their pain and flares, respectively. Free-Text Feedback: Key themes were increasing knowledge (e.g. “This is really useful because I don’t feel the NHS gave me enough information and I need something I can trust on the internet”) and self-management (e.g. “It made me feel confident that I could manage on-going problems and flares and rely less on medication”). Conclusion This service evaluation highlights the impact of chronic pain on the lives of people with RA and demonstrates the benefits of this multidisciplinary team-developed online educational resource at improving patient’s knowledge and confidence to self-manage pain and flares. Disclosure I.C. Scott: Grants/research support; National Institute for Health and Care Research (NIHR) Advanced Research Fellowship [NIHR300826]. S. Ryan: None. G. Levey: None. M.J. Thomas: Grants/research support; National Institute for Health and Care Research (NIHR)/Versus Arthritis. S. Hider: Honoraria; SH has received payment for lecture fees from UCB. A. Bosworth: None.
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 | 0,008 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,002 |
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 ».