A total of 401 participants completed the study from January to February 2017. Survey takers were excluded from the study if they were younger than 18 years or had psychiatric conditions such as schizophrenia or an autism spectrum disorder owing to differences in how these individuals direct attention toward a face. Only surveys that were completed in their entirety were included in the final analysis. Approval was obtained for this study from the Johns Hopkins University School of Medicine Institutional Review Board.
Surveys were built using Qualtrics Survey Software (Qualtrics). As described previously, a link was disseminated via various public access websites. The first page of the survey described the task and relevant exclusion criteria. Participants were instructed that they would be looking at photographs of faces, some of which had undergone blepharoplasty and some that had not. At this time, respondents were notified that continuing on to the survey would serve as informed consent for their participation. Survey takers were also informed that they would be eligible to enter a drawing for a gift card of nominal value on successful completion of the survey.
Photographs of 21 female patients who underwent upper and/or lower blepharoplasty, for either cosmetic or functional reasons, were selected from photograph databases at a tertiary academic medical center or private practice clinic. Patients in the photographs provided informed consent for the use of their images and had not undergone additional cosmetic surgery. Using the Delphi method, 5 expert graders (I.D.P, T.C.K., P.J.B., K.D.O.B., and L.E.I.) provided ratings of patient candidacy and surgical outcomes, and these were used to narrow the image pool to reflect optimal surgical outcomes. The experts identified 13 patients who had surgical outcomes in the upper quartile. Three sets of photographs were excluded owing to poor standardization between the preoperative and postoperative photographs or nonneutral facial expressions.
Of the 10 individuals selected for inclusion in the final survey (mean age, 59.8 years), 7 had undergone upper blepharoplasty and 3 had combined upper and lower blepharoplasty. For all patients, bilateral upper blepharoplasty was performed, and 1 patient was noted to have ptotic lacrimal glands that were repositioned during surgery. Lower blepharoplasties were performed using the transconjunctival approach, with 1 patient also undergoing a concurrent laser resurfacing peel. None of the patients was noted to have periorbital botox or fillers between the 2 photographs. Observers were randomly shown either the preoperative or the postoperative photograph of each patient to reduce the possibility of bias due to priming. Sample preoperative and postoperative photographs are in .
For each photograph, observers were asked to estimate the age of the face using a slider bar ranging from 30 to 80 years that could be moved up or down at 1-year increments. Participants were then asked to rate perceived attractiveness, health, and energy level of the individual in the image using a 100-point visual analog scale with 1-point increments for attractiveness (range, 0 to 100, where 0 indicates least attractive and 100 indicates most attractive) and for health and energy level (range, –50 to 50, where –50 indicates least energy and 50 indicates most energy).
Statistical analysis was performed using STATA, version 13 SE (StataCorp). A multivariate mixed effects regression model was used to measure the effect size of blepharoplasty on the domains of interest. This type of model was of particular value as it allowed us to parse out the differences in domain ratings due to surgical effect while accounting for participant biases.
Next we aimed to quantify the clinical effect size of changes in each of the domains using the ordinal rank change approach, as previously described. Using the residual variance from the mixed effects regression model, we plotted the probability density function for the gaussian distribution of ratings for each domain that could then be integrated and scaled in Mathematica, version 10.4 (Wolfram). The area under the curve represents a proportion of the population, and the difference in area under the curve between the mean preoperative and postoperative ratings provides the estimated ordinal rank change for a given domain as a measure of effect size. The integration that yields the ordinal rank change is shown pictorially in a work by Bater et al.
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