Aesthetic medicine during COVID‐19: Patient perspectives and motivations amidst a pandemic
Notice bibliographique
Résumé
To the editor, There have been immense worldwide changes to life and the practice of medicine and dermatology in the last few months due to the COVID-19 pandemic.1, 2 In March 2020, there was mandated closure of all nonessential services in British Columbia, Canada in the midst of the COVID-19 pandemic.3 As per the local regulatory public health authorities, Humphrey Cosmetic Dermatology closed to patients for 8 weeks. Aligned with reopening of other ambulatory medical clinics in British Columbia, we welcomed patients back into our clinic with increased environmental and personal safety measures.4 In an effort to improve patient care, we have endeavored to characterize patient attitudes, perceptions, and motivations for receiving aesthetic treatments amidst the COVID-19 pandemic. We designed a short quantitative survey to understand factors affecting patient perceptions of comfort at their most recent clinic visit and their motivations for aesthetic treatment during the COVID-19 pandemic. We identified 221 patients who attended clinic in the first 4 weeks upon our reopening. We invited them to participate in our survey through a personalized email with an anonymized link hosted through Qualtrics XM. The survey was viewed by 55 patients and completed by 49 (89% overall response rate) in the 72 hours after distribution. At our clinic, we have implemented rigorous environmental controls and safety measures following local regulatory public health guidance for a low-risk ambulatory dermatology clinic. We focused on patient perceived comfort and how these individual measures influence comfort levels. On a 5-point Likert scale (from extremely comfortable to extremely uncomfortable), 42 (85.7%) responded as "extremely comfortable" when asked "compared with prior visits to our clinic, how comfortable did you feel at your most recent visit?". Zero patients reported feeling somewhat or extremely uncomfortable. When rating factors influencing patient comfort, trust in the clinics team was cardinal, rated as extremely important (n = 40, 81.6%) or very important (n = 9, 18.4%) by all respondents. This was followed in importance by rigorous prescreening protocols, masks, and face shields worn by treatment providers, and then other environmental controls (Table 1). The overwhelming influence of trust in ensuring patient comfort reiterates to us the fundamental importance of the doctor-patient relationship in aesthetic medicine. When comparing level of comfort to other activities, respondents were more comfortable at their most recent clinic visit than at the grocery store (87.5%), pharmacy (75.0%), gym (90.9%), place of work (57.9%), or hairdresser (54.6%) (Table 1). To understand whether patient motivations changed during COVID, we asked "What are your reasons for coming in now for your treatment?". Major motivators of aesthetic treatments during the pandemic were to continue with previously scheduled treatments, do something positive, refresh their look, gain confidence, or address something of concern (Table 1). There were 11 (22.45%) patients who acknowledged that COVID has changed their aesthetic treatment priorities. When posed with the question "when reflecting on the pandemic, how did you feel when you were unable to have aesthetic treatment?" respondents replied with themes of frustration, anxiety, stress, and disappointment. However, sentiments surrounding understanding and the value of safety as a priority were also relayed. The results of this single-center survey are being shared to inform others of our patients experience upon resuming aesthetic treatments. Patient trust is paramount to the perception of comfort upon return to clinic, above all the other environmental controls implemented upon resumption of clinical care. Our patients overwhelmingly endorse self-care and doing something positive as reasons for resuming aesthetic treatments. The data that supports the findings of this study are available primarily in Table 1; any further data can be requested from the corresponding author.
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 | 0,003 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».