Reclaiming the clinical social work role: A call for reform in sickle cell disease psychosocial care
Notice bibliographique
Résumé
Abstract Background:Psychosocial services remain under-integrated and inconsistently supported in comprehensive sickle cell disease (SCD) care. While the complex biopsychosocial needs of people with SCD are recognized, there is a lack of formalized practice guidelines, role definitions and appropriate staffing ratios. Social work is widely recognized as essential in SCD care, but most recommendations do not specify dedicated clinical and non-clinical psychosocial roles. As a result, Clinical Social Workers (CSWs) are often redirected to non-clinical tasks, such as case management and resource navigation (e.g., transportation, public benefits, housing applications, etc.), typically suited for Bachelor's level Social Workers (BSWs) or Community Health Workers (CHWs). This misalignment constrains CSWs' ability to deliver evidence-based behavioral health interventions and practice at the top of their license. To address these issues, the National Alliance of Sickle Cell Centers (NASCC) convened the NASCC Social Work Committee (NSWC), a national network of SCD CSWs and psychosocial care leaders, to identify practice patterns, assess structural inefficiencies, and advocate for high quality psychosocial care as a foundational element in SCD management. Methods:A national mixed-methods survey was distributed to psychosocial providers at NASCC sites in 2023: assessing role scope, supervision, caseload composition, and system barriers. Quantitative data (N=83) were analyzed using univariate statistics and thematic analysis. NSWC members guided survey development and interpretation to ensure practice relevance. In 2025, an additional survey was completed of 24 NASCC sites —10 pediatric, 10 adult, and 4 lifespan programs—assessing psychosocial team composition, including BSWs, CHWs, and FTE staff-to-patient ratios. Results: Findings revealed substantial gaps in psychosocial infrastructure, role expectations, and staffing. Notably, in the 2025 survey, 83% of CSWs reported working below their licensure scope, with 70% citing insufficient staffing for concrete needs. Caseloads were inconsistently defined and often combined clinical and non-clinical tasks. Responses emphasized the need for institutional support, recognition of psychosocial providers' clinical scope, and peer collaboration through educational and professional networks. Patient caseloads per CSW varied widely, ranging from 116 to 700 patients per FTE. Notably, 75% of sites had zero non-clinical psychosocial staff (e.g., BSWs, CHWs), resulting in CSWs being solely responsible for both clinical and concrete needs. These data reflect persistent infrastructure gaps and underinvestment in scalable, role-aligned psychosocial care models. Conclusions:These surveys underscore that psychosocial care in SCD is hindered by vague role definitions and absent formal practice standards. CSWs report that non-clinical assignments undermine effective, outcomes-driven care. This inefficient use increases costs and forfeits revenue, as licensed CSWs are billable providers when delivering clinical services. Delegating concrete tasks to paraprofessionals—CHWs or BSWs— improves cost-effectiveness, access, and allows clinicians to focus on evidence-based behavioral health interventions. When CSWs are able to prioritize clinical care, their capacity can extend to research, quality improvement, program development (e.g., support groups, mentorship programs), and community liaison activities. Optimizing role allocation aligns with best practices to enhance quality of care, patient outcomes, resource use, and workforce retention. Meaningful improvements require institutional investment in non-clinical staff, specialized training, supervision structures and triage models which differentiate clinical and concrete needs. The NSWC is leveraging these findings to develop standardized psychosocial care models within SCD programs and advocate for national consensus guidelines. These efforts aim to embed high-quality psychosocial care as a core element of comprehensive SCD management.
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 | 0,149 | 0,140 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,015 | 0,033 |
| Communication savante | 0,026 | 0,032 |
| Science ouverte | 0,008 | 0,026 |
| Intégrité de la recherche | 0,030 | 0,048 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 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 ».