Diabetes in the context of incarceration: a scoping review
Notice bibliographique
Résumé
Background: The burden of chronic conditions, like diabetes, is disproportionately carried by people facing social disadvantages (e.g., those with experiences of incarceration). A dearth of knowledge remains about this topic. We conducted a scoping review to determine the extent of literature about diabetes management and/or self-management in relation to incarceration. Methods: We used the Arksey and O'Malley five stage process, recommendations by Levac et al., and the PRISMA Extension for Scoping Reviews Checklist. Core search terms for diabetes were combined using the Boolean operator AND with terms relevant to incarceration. We initially searched the following electronic academic databases on January 5, 2021, and then updated these searches on September 7, 2022: APA PsycInfo, CINAHL, Criminal Justice Abstracts, EMBASE, MEDLINE, Scopus, and SocINDEX. There were no restrictions on language, study design, quality, location, time, and sex or gender differences. We searched for research articles, conference proceedings, dissertations and theses, government documents, and organization documents. We then searched for other forms of literature using an electronic database (ProQuest Dissertations and Theses - Global), the internet search engine Google, and various corrections and diabetes websites in August 2021 and then updated these searches in September 2022. We also reviewed the reference lists of the final selected documents to identify additional literature. Findings: The search from the seven databases identified 3076 records. The search from other sources (e.g., websites) identified an additional 1077 records. A total of 40 documents met our final inclusion criteria and were included in this review. The type of research conducted was primarily quantitative in nature. Clinic and education interventions were most commonly investigated. Clinical outcomes were often reported. Most guidelines were targeted at healthcare providers. Much of the literature originated from high-income countries, which may not be fully applicable for different contexts like low-income countries. Many interventions were associated with improved outcomes. Interpretation: Administrators can use our findings to develop appropriate policies for this population. Tailored diabetes education for this population and healthcare providers may improve management practices. Our findings offer key insights for improving diabetes care and outcomes for this underserved population. Addressing the diabetes-specific health needs of these people may improve overall public health. Funding: KD has received the O'Brien Institute for Public Health Postdoctoral Scholarship (University of Calgary), Cumming School of Medicine Postdoctoral Scholarship (University of Calgary), and the Libin Cardiovascular Institute's 2021 Person to Population Seed Grant (University of Calgary).
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 | 0,015 | 0,074 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,005 |
| Bibliométrie | 0,027 | 0,029 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,005 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».