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Enregistrement W4415666456 · doi:10.1186/s42238-025-00346-z

Symptom management, adherence to therapy, and filling the gaps of medical cannabis therapy: a qualitative study on the importance of nursing consultations for fibromyalgia patients

2025· article· en· W4415666456 sur OpenAlexaff
Giulia Bassi, Valeria Giorgi, Michela Lazzarin, Ramona Meanti, Robert J. Omeljaniuk, Piercarlo Sarzi‐Puttini, Antonio Torsello

Notice bibliographique

RevueJournal of Cannabis Research · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueFibromyalgia and Chronic Fatigue Syndrome Research
Établissements canadiensLakehead University
Organismes subventionnairesUniversità degli Studi di Milano-BicoccaAtsumi International Scholarship Foundation
Mots-clésFibromyalgiaIntervention (counseling)Inclusion (mineral)Qualitative researchMedical diagnosisDiseaseRheumatism

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: In agreement with the latest European League Against Rheumatism (EULAR) on patient education for fibromyalgia (FM) treatment, nurses should be involved in the therapeutic plan of FM patients to provide information about the disease and pharmacological and non-pharmacological approaches that can be used to mitigate symptoms, including the use of medical cannabis. This study aims to demonstrate the key role of nursing educational intervention to improve self-care and therapy adherence by FM patients. DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONS: All potential subjects, solicited from the Italian Fibromyalgia Syndrome Association (AISF Onlus) address book (n = 1100), were provided with a description of the study as well as a privacy protection form (as an e-mail) subsequent to authorization from the AISF. In this qualitative study, nurse educational intervention (30 min duration) was offered via videoconference to FM patients who were taking and/or had taken medical cannabis as well as patients not in therapy but interested in taking it, who matched the inclusion criteria. Two weeks before the educational intervention, subjects (n = 30) completed the Revised Fibromyalgia Impact Questionnaire (FIQR) and the A-14 Scale on-line. Two weeks following intervention, subjects repeated the FIQR and A-14 Scale in addition to the Clinical Global Impression - Global Improvement (CGI-I) Scale. RESULTS: Historic diagnoses of subjects included terms such as “insane”, “imaginary ill”, and “whiny”; as well, their physical conditions were underestimated by their immediate families. All subjects have problematic employment histories which consistently identified their varied employments as physically too demanding. Over time, increased physician- and societal-awareness, resulted in all subjects being diagnosed with FM; consequently, all subjects reported a strong desire to become well-informed about FM and its treatment. Although medical cannabis (MC) was an available therapy, twenty subjects reported that cannabis had never been proposed despite years of ineffective therapies. CONCLUSIONS: The subjects were disappointed and discouraged by the widespread ignorance about their condition and the lack of recognition by the National Health System. Our findings suggest that patients with FM require specialist clinical advice from initial diagnosis through to the end of treatment, and that nurses with in-depth knowledge of fibromyalgia and treatment options are the best professionals to perform this task; furthermore, healthcare professionals should receive a better education about MC-based treatment regimens. REGISTRATION: This study protocol conforms to the Declaration of Helsinki and was approved by the Ethics Committee of the University of Milano-Bicocca (Protocol 545 9-7-2020) and registered on Clinicaltrials.gov NCT05247411. Written informed consent for participation in the study and publication of the results was obtained from all respondents.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,390
Score d'incertitude au seuil0,313

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0060,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,120
Tête enseignante GPT0,480
Écart entre enseignants0,360 · 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 tête enseignante, pas un consensus.

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