Health Care Providers’ Perceptions of Unmet Needs Among African American Cancer Caregivers: Qualitative Investigation Among US Medical Professionals
Notice bibliographique
Résumé
BACKGROUND: African American caregivers are more likely to be sole unpaid caregivers, spend more hours on caregiving tasks, and receive less external support compared to White caregivers; yet, limited research focuses on their specific needs. Even less attention has been paid to health care provider perspectives on how to better support this population, despite providers' critical role in connecting caregivers to resources and implementing systems-level changes. OBJECTIVE: This study aimed to understand health care providers' experiences supporting African American cancer caregivers and to identify actionable recommendations for improving care. Specific objectives were to (1) identify unmet needs that providers observe among African American cancer caregivers, (2) explore barriers preventing these needs from being met, and (3) elicit provider recommendations for interventions to enhance caregiver support. METHODS: Between January and May 2023, we conducted semistructured online interviews with 12 health care providers across 7 US states. Providers were purposively sampled from facilities serving patient populations with ≥20% African American representation. Participants included physicians (n=7), social workers (n=2), nurses (n=2), and other providers (n=1), with 58% identifying as Black or African American and 83% having more than 15 years of clinical experience. Interviews lasted ~60 minutes and were conducted via Zoom (Zoom Video Communications, Inc) with audio recording. Data were analyzed using condensed thematic analysis guided by the McKillip needs assessment framework and socioecological model. RESULTS: Thematic analysis revealed 2 overarching categories of findings. First, providers identified three types of unmet needs among African American cancer caregivers (1) practical needs, including transportation, financial constraints, and competing family obligations; (2) social-emotional needs, including stress, burnout, and fear; and (3) cultural barriers, including medical mistrust rooted in historical trauma, "superhero Black woman" expectations, tensions between faith and medical treatment, and stigma around mental health. Second, providers offered four themes of recommendations for transformational change: (1) formal acknowledgment and compensation of caregiving as essential work; (2) integration of caregivers as equal members of multidisciplinary care teams; (3) recognition and leveraging of cultural assets, including strong family networks, community values, and faith-based support; and (4) strengthening providers' roles as hubs for individual-level support and systems-level advocacy. CONCLUSIONS: Health care providers readily identify substantial unmet needs among African American cancer caregivers and offer practice-based recommendations that extend beyond individual-level support to emphasize structural and systems transformation. Findings suggest that meaningful improvement requires multilevel intervention. This includes policy changes to formalize and compensate caregiving work, organizational restructuring to integrate caregivers into care teams, provider training in cultural humility and asset-based approaches, and institutional commitment to addressing historical trauma and rebuilding trust with African American communities. This novel provider-focused approach offers actionable pathways for clinical settings to reduce disparities and improve outcomes for African American cancer caregivers and the patients they support.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».