DS28 Left-handedness in dermatological surgery
Notice bibliographique
Résumé
Abstract Overall, 90% of the world’s population are right-hand dominant (RHD) and as such most environments are designed with right-handed individuals in mind. This extends to operating theatres, where left-hand dominant (LHD) surgeons face documented challenges when training in right-handed environments. These challenges include limited access to left-handed instruments and a lack of LHD mentors. When using right-handed instruments, LHD surgeons must reverse their natural motion or learn to operate with their right hand – both of which are unnatural and fatiguing. This study aims to explore the experiences, challenges and adaptations of left-handed dermatologists, trainees, and general practitioners with extended roles (GPwERs) in Ireland and the UK when performing dermatological surgery. An online questionnaire was distributed to dermatologists, trainees, GPwERs and specialist nurses through Irish and UK dermatology professional organizations. In total 105 respondents participated (50 consultants, 35 trainees, four GPwERs and 16 nurses). Of these, 47 (44.8%) were LHD and 58 (55.2%) were RHD. Five of 15 (33%) Mohs surgeons were LHD. Among 47 LHD respondents, 13 reported operating equally with both hands, 31 with primarily the left hand, and three with primarily the right hand. Only 6% (n = 3) of LHD respondents have access to left-handed instruments, although only 10 respondents had requested them: two successfully and eight unsuccessfully. Eighteen LHD respondents had tried to change handedness during their training. When comparing handedness across surgical tasks, LHD trainees were more likely than RHD trainees to report using their nondominant hand or demonstrating ambidexterity when using scissors (47% vs. 7%), suturing (38% vs. 5%) and undermining (34% vs. 14%). No difference was found in electrocautery (9% vs. 10%) or scalpel use (9% vs. 5%). When asked whether hand dominance significantly affected the learning curve in dermatological surgery, 53% (25 of 47) of LHD respondents felt it did not, compared with 22% (13 of 58) of RHD respondents, although previous research has shown increased efficiency using handed-matched vs. handed-unmatched needle drivers. Themes from open-ended questions highlighted initial difficulties with scissors and needle holders, but all reported adaptation. Some respondents noted logistical challenges in acquiring and maintaining left-handed equipment within departments, and many indicated they were self-taught, struggling to find adequate resources for left-handed surgical training techniques. This study highlights challenges faced by LHD dermatologists, trainees and GPwERs, particularly due to limited access to left-handed instruments and training resources. While most respondents did not feel their handedness significantly affected their learning curve, the lack of appropriate tools and mentorship remains a barrier. Improving access to left-handed instruments and tailored training could enhance the learning experience and reduce the physical strain on LHD practitioners in dermatological surgery.
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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 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 ».