BH03 Do patients with afro-textured hair who are experiencing hair loss feel understood by their dermatologists? A cross-sectional study
Notice bibliographique
Résumé
Abstract Providing good-quality care for skin and hair conditions in patients with skin of colour is an important area of dermatology. This study aims to analyse patient perceptions of their dermatology experience with hair loss and caring for afro-textured hair. We also examined whether they were signposted to the British Association of Dermatologists patient information leaflet (BAD PIL) ‘Caring for Afro-textured hair’ [British Association of Dermatologists. Caring for Afro-textured hair. Available at: https://www.bad.org.uk/pils/caring-for-afro-textured-hair (last accessed 19 April 2024)]. Patients with afro-textured hair attending a consultation for hair loss between 2020 and 2023 were included. Patients consented to participating in an anonymous online survey. A Google form was emailed to participants between December 2023 and January 2024, with responses recorded. A link to the BAD PIL was attached to the survey. Seventeen patients responded. Of these, 59% did not receive a diagnosis prior to seeing a dermatologist. In total, 71% of patients did not fully understand the cause of their hair loss and commonly used social media (53%), online websites (41%, including 18% using the BAD website) and family and friends (35%) to seek information about hair loss. Social media (35%) and family and friends (29%) were the most common forms of seeking information regarding caring for their hair. After seeing a dermatologist, 13 patients (76%) received a diagnosis. Fourteen patients (82%) were offered a biopsy, which 12 underwent. Overall, 29% of patients believed their dermatologist understood their hair loss very well, 24% somewhat well, 35% not very well and 6% not at all. Most patients (63%) had the same understanding about their hair loss after their consultation, and half of patients (47%) did not gain any confidence about managing their hair loss. Patients are more likely to refer to the BAD website after seeing a dermatologist (35%). However, only five patients (29%) were signposted to the BAD PIL during their consultation. Overall, 41% of patients found the leaflet somewhat or very helpful. Patients expressed that their consultation was more beneficial when they were seen by a doctor with afro-textured hair, and were disappointed when signposted to leaflets that featured hair loss in non-afro-textured hair. Others feel saddened because there is ‘no cure’ and current management has not helped. This study highlights the challenges that patients with afro-textured hair face in the management of their alopecia. There appears to be a perception that dermatologists do not fully understand hair loss in afro-textured hair, unless they have such hair themselves. Further education to dermatology colleagues is imperative to improve patient care and satisfaction. The BAD PIL is a useful signpost, which can be more reliable than patients relying on social media for advice.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».