Notice bibliographique
Résumé
Objective. The course of autoimmune arthritis varies by individual and can cause significant and progressive decline in physical function, mental health, social independence, and financial stability. This disease process has also been linked to early mortality, often due to complications from infections or cardiovascular disease. While intervention from health professionals is paramount for this population, education is also imperative to enable patients to collaborate successfully with the healthcare team. Persons with autoimmune disease require education about the disease process and self-management techniques to develop self-efficacy in managing their disease within their daily lives. The first aim of this mixed methods study was to develop and evaluate a disease self-management program based on Self-Determination Theory (SDT) for participants with autoimmune arthritis. The second aim was to evaluate the participants' outcomes, with emphasis on any behavioral changes noted after attending the program. Methods. Four adult participants with physician-diagnosed arthritis attended a 6-session disease self-management program. Eight content topics were developed and delivered over the 6-week period by an interprofessional team consisting of the primary instructor and five student instructors (three physical therapy students and two pharmacy students). The content was evaluated using weekly session evaluation forms, as well as semi-structured post-program interviews conducted individually with the participants, and collectively with the student instructors. Participants' outcomes were measured using five outcome measures validated for this population; namely, the Health Assessment Questionnaire Disability Index (HAQ-DI); Arthritis Self-efficacy Scale, 8-item version (ASES); Patient Knowledge Questionnaire (PKQ); Short Form 36 Health survey (SF-36); and McMaster Toronto Arthritis Patient Preference Disability Questionnaire (MACTAR), which were completed by the participants both before and after the program. Results were analyzed using the Wilcoxon signed ranks test with a significance set at 0.10. One month after the program ended, participants completed a semi-structured interview to explore their thoughts about the program and any health behavior changes noted. Qualitative data were analyzed using generic qualitative inquiry and the three tenets of SDT: autonomy, competence, and relatedness. Results. Participants found the content helpful, the delivery effective, and the program acceptable, even though they had been living with their arthritic conditions for several years. Both participants and students felt the ongoing program was feasible, however, they suggested a larger group, attempting to recruit some younger people for the group, and adding guest speakers. Participants' suggestions for additional topics included involving a recently graduated rheumatologist (suggestive of being more up to date on recent findings), information about Cannabidiol (CBD) supplements, and the relationship between diabetes and rheumatic disease. Only one of the five standardized measures, the PKQ, demonstrated a difference (p = 0.07) from the beginning to end of the program with an effect size of r = .65. The MACTAR scores did not reach significance, but the effect size was r = .57. The 1-month, post-program qualitative interviews revealed positive health behavior changes, including self-selected physical activities, advocacy for self, knowledge seeking, and acquisition of new adaptive or exercise equipment, all related to the tenets of SDT. Conclusion. Because of the small, homogenous sample size, participant outcomes cannot be extrapolated to the population at large, but the qualitative results demonstrate that this type of program, based on SDT, is both feasible to offer again with modifications, and acceptable to the participants. This program shows promise in facilitating positive behavior changes in individuals with autoimmune arthritis. Keywords: arthritis, self-determination theory, disease self-management, rheumatic disease
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».