Exploring the biopsychosocial landscape of chronic illness: A case study of systemic lupus erythematosus (SLE) from epigenetics to education
Notice bibliographique
Résumé
Systemic lupus erythematosus (SLE), or lupus, is a chronic autoimmune condition and global public health issue. SLE is uniquely characterized as gendered, racialized, episodic, invisible and idiosyncratic. SLE primarily impacts women, and most severely, women of colour. Cardiovascular disease (CVD) is a main driver of morbidity and mortality among SLE populations. Recent literature has begun to characterize both SLE and CVD as “biopsychosocial” and concomitant with place. However, the complex biological-social interplay influencing SLE disease trajectories, and morbidity and mortality from CVD in SLE, is not well understood. \nThis thesis explores the biopsychosocial landscape of SLE with three main objectives: 1) to assess theoretical and methodological support for social epigenetics studies of SLE; 2) to investigate existing literature around social factors influencing the development of CVD in SLE; and 3) to engage knowledge users in the co-production of educational tools about the risks of CVD in SLE. Drawing on health geographical approaches, ecosocial and biopsychosocial theories, and feminist perspectives, a multimethods research design was employed involving narrative review, scoping review, focus groups, and interviews. This transdisciplinary process was supported by an embedded integrated knowledge translation (iKT) approach that included knowledge users as equal partners. \n\t This research positions social epigenetics as a novel and transdisciplinary line of inquiry to understand the development and trajectories of chronic diseases. While some theoretical and methodological support exists - with respect to ecosocial and lifecourse theories, and epigenome-wide association studies and exposomic approaches, respectively - expansion in both of these areas is needed with particular attention to intersectionality. Building on this theoretical foundation, and using SLE as a case study, the scoping review revealed several social factors demonstrated to be central to CVD in SLE populations: socioeconomic status, race, mental health, and gender. These results, and complementary information about CVD specific to SLE, were mobilized through the co-development of a lay language patient education resource. Through a focus group with key informants and interviews with patients, knowledge users advised on tailoring content, format, accessibility and inclusivity for the SLE community, with the ultimate goal of improving patient knowledge about CVD. \n\tThis body of work makes theoretical contributions to the practical application of social epigenetics studies, integrating intersectional perspectives, and bridging basic and social science conceptualizations of health and ill-health. Methodologically, these studies contribute to the study of iKT frameworks and patient engagement in the context of chronic illness. This research collectively adds to our substantive understanding of SLE through a biopsychosocial lens, and the risk landscape of CVD in place. With respect to healthcare policy and practice, the findings herein may provide future targets for CVD risk assessment and prevention in the SLE context, inform educational and social interventions to support SLE treatment, and contribute to the development of a future patient-led research agenda for SLE in Canada.
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 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,022 | 0,009 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
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 ».