Equity considerations in clinical practice guidelines for traumatic brain injury and the criminal justice system: A systematic review
Notice bibliographique
Résumé
BACKGROUND: Traumatic brain injury (TBI) is disproportionately prevalent among individuals who intersect or are involved with the criminal justice system (CJS). In the absence of appropriate care, TBI-related impairments, intersecting social determinants of health, and the lack of TBI awareness in CJS settings can lead to lengthened sentences, serious disciplinary charges, and recidivism. However, evidence suggests that most clinical practice guidelines (CPGs) overlook equity and consequently, the needs of disadvantaged groups. As such, this review addressed the research question "To what extent are (1) intersections with the CJS considered in CPGs for TBI, (2) TBI considered in CPGs for CJS, and (3) equity considered in CPGs for CJS?". METHODS AND FINDINGS: CPGs were identified from electronic databases (MEDLINE, Embase, CINAHL, PsycINFO), targeted websites, Google Search, and reference lists of identified CPGs on November 2021 and March 2023 (CPGs for TBI) and May 2022 and March 2023 (CPGs for CJS). Only CPGs for TBI or CPGs for CJS were included. We calculated the proportion of CPGs that included TBI- or CJS-specific content, conducted a qualitative content analysis to understand how evidence regarding TBI and the CJS was integrated in the CPGs, and utilised equity assessment tools to understand if and how equity was considered. Fifty-seven CPGs for TBI and 6 CPGs for CJS were included in this review. Fourteen CPGs for TBI included information relevant to the CJS, but only 1 made a concrete recommendation to consider legal implications during vocational evaluation in the forensic context. Two CPGs for CJS acknowledged the prevalence of TBI among individuals in prison and one specifically recommended considering TBI during health assessments. Both CPGs for TBI and CPGs for CJS provided evidence specific to a single facet of the CJS, predominantly in policing and corrections. The use of equity best practices and the involvement of disadvantaged groups in the development process were lacking among CPGs for CJS. We acknowledge limitations of the review, including that our searches were conducted in English language and thus, we may have missed other non-English language CPGs in this review. We further recognise that we are unable to comment on evidence that is not integrated in the CPGs, as we did not systematically search for research on individuals with TBI who intersect with the CJS, outside of CPGs. CONCLUSIONS: Findings from this review provide the foundation to consider CJS involvement in CPGs for TBI and to advance equity in CPGs for CJS. Conducting research, including investigating the process of screening for TBI with individuals who intersect with all facets of the CJS, and utilizing equity assessment tools in guideline development are critical steps to enhance equity in healthcare for this disadvantaged group.
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 | 0,080 | 0,335 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,006 |
| Bibliométrie | 0,020 | 0,020 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,005 | 0,008 |
| Science ouverte | 0,004 | 0,006 |
| Intégrité de la recherche | 0,004 | 0,004 |
| 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 ».