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Figure 1.
Conceptual Path Diagram Illustrating Dominant Relationships Among the Variables in the Structural Equation Model for Patients With Facial Lesions
Conceptual Path Diagram Illustrating Dominant Relationships Among the Variables in the Structural Equation Model for Patients With Facial Lesions

QOL indicates quality of life; SG, standard gamble; VAS, visual analog scale.

Figure 2.
Structural Equation Model Marginsplot, Illustrating Observer Comfort in Conversing With Individuals in Each Lesion Category Before and After Surgery
Structural Equation Model Marginsplot, Illustrating Observer Comfort in Conversing With Individuals in Each Lesion Category Before and After Surgery

Error bars represent 95% confidence intervals.

Table 1.  
Structural Equation Model for Social Perception of Normal Faces: Fixed Effects
Structural Equation Model for Social Perception of Normal Faces: Fixed Effects
Table 2.  
Structural Equation Model for Social Perception of Faces With Lesions: Fixed Effectsa
Structural Equation Model for Social Perception of Faces With Lesions: Fixed Effectsa
Table 3.  
Random Effects for Structural Equation Models
Random Effects for Structural Equation Models
Table 4.  
Conversation Hypothesis Testing, Comparing Postoperative to Normal Facesa
Conversation Hypothesis Testing, Comparing Postoperative to Normal Facesa
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Original Investigation
Mar/Apr 2015

The Social Penalty of Facial LesionsNew Evidence Supporting High-Quality Reconstruction

Author Affiliations
  • 1Division of Facial Plastic and Reconstructive Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland
  • 2Department of Otolaryngology–Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland
  • 3Division of Rhinology, Department of Otolaryngology–Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland
JAMA Facial Plast Surg. 2015;17(2):90-96. doi:10.1001/jamafacial.2014.1131
Abstract

Importance  To date, there have been no studies attempting to measure the multidimensional impact of facial lesions, before and after reconstruction, on social conversation.

Objective  To measure the direct social impact of facial lesions before and after surgical reconstruction.

Design, Setting, and Participants  Prospective randomized controlled experiment at an academic tertiary referral center. One hundred twenty casual observers viewed images of faces with lesions of varying sizes and locations before and after reconstruction as well as faces without lesions (normal faces) for comparison.

Main Outcomes and Measures  Observers rated faces using a battery of metrics, including how comfortable they would be having a conversation with the participant in each facial image. The conversation questions were answered on a scale from 0 to 100, where the higher the score, the more comfortable the observer would be conversing with the subject.

Results  The mean (SD) conversation score for participants with normal faces was 85.02 (17.95) of 100 points. Facial lesions had a negative effect (or, a penalty) on conversation (61.63 [29.50]). Structural equation modeling showed this conversation penalty varied with lesion size and location, with large and central lesions generating the greatest penalty. Reconstructive surgery increased observers’ comfort and willingness to converse with individuals with facial lesion by an average of 19.83 (95% CI, 17.49-22.17), an improvement that also varied with preoperative lesion size and location. Planned hypothesis testing showed that reconstructive surgery normalized observer comfort in communicating with people with small peripheral, small central, and large peripheral lesions. However, substantial discomfort communicating with patients with large central lesions remained after surgery. Observer-rated facial attractiveness, affect, and perceived quality of life also influenced this social communication measure.

Conclusions and Relevance  Facial lesions induce a significant social penalty as rated by the casual observer. Specifically, observers are less comfortable communicating with people who have facial lesions. Surgical reconstruction of facial lesions increased observers’ comfort in conversing with people with facial lesions, an impact that varied with lesion size and location.

Level of Evidence  NA.

Introduction

Face-to-face conversation is a vital aspect of human life. The face plays an essential role in communication, both verbal and nonverbal, and is the focus of attention in social encounters.13 Therefore, any deformity of the face can disrupt communication and perturb social interactions. Recent literature describes how facial disfigurement has a negative impact, or penalty, on social interactions, particularly everyday interactions with strangers.46 Disrupting communications and social interactions that are so basic to human nature often leads to devastating psychosocial sequelae for those with facial deformity.510

Anecdotally, most people who have interacted and conversed with a person with a facial disfigurement appreciate that the disfigurement was distracting and somehow negatively altered the interaction. Scientists have worked to better understand the variables influencing these initial social interactions between those with facial disfigurement and those without (hereinafter, normal individuals) in society. Studies show that despite our best intentions, facial deformities (eg, lesions, crooked noses, and facial paralysis) fundamentally alter the way we direct attention to a face.1113 This perturbed facial processing may underlie the negative perception of people with facial disfigurements by members of society, who consistently rate faces with lesions as less attractive and more emotively negative than demographically matched normal faces.14,15 The present study aims to characterize how these extrinsic, appearance-based variables influence a more direct social measure, conversation—specifically, how facial lesions and their surgical reconstruction change these variables of facial perception and have an impact on casual, social conversation as perceived by society.

Human conversation is complex, influenced by a multitude of observable and latent variables. While our model accounts for these sources of variability, the focus of this study is the extrinsic, appearance-based variables of facial perception that influence initial social interactions. These “first impression” variables are important because they significantly influence the course of subsequent interactions.16 The literature has identified perceived attractiveness and affect display as key variables influencing social interactions. Studies1620 show that people are more willing to interact with those whom they perceive as more attractive and more affectively positive. In addition, our pilot studies on observer perception of facial deformity have identified a perceived quality of life (QOL) variable that influences observer perception of faces, quantifying a new dimension of facial perception independent of attractiveness and affect. Perceived QOL is a latent variable that represents observer perception of appearance-related health or QOL. Using these extrinsic variables of attractiveness, affect, and perceived QOL, we generated a social conversation model to test our hypotheses.

Our first main hypothesis was that facial lesions have a negative impact on casual, social conversation as measured by decreased observer comfort in conversing with people with facial lesions compared with those without facial lesions (with normal faces). Based on previous studies,14,15 we subhypothesized that this conversation penalty will be a function of lesion size and location, with larger and more centrally located lesions inducing the greatest penalty. Our second main hypothesis was that surgical reconstruction of facial lesions would decrease the measured conversation penalty. We subhypothesized that surgery would normalize the conversation score for some categories of lesions. Our third main hypothesis was that perception of attractiveness, affect, and QOL would independently affect observer-rated conversation.

Methods
Participants

This study was approved by the institutional review board of the Johns Hopkins University. We enrolled 174 casual observers using university-based and public access website postings to randomly sample the general population. Occupation was recorded for each observer, and approximately 27% were in a medically associated field. Regression analysis found that neither observer occupation nor recruitment website had a significant impact on the observer-rated metrics in this study. After providing electronic informed consent (surveys were online, so observers reviewed the consent and clicked to accept the terms and agree to participate) and verifying that the exclusion criteria did not apply, observers randomly completed 1 of the 4 surveys. Thirty-three observers were removed from the study because they failed to complete the entire survey; 10 were eliminated as outliers because they rated 2 or more normal faces as having a facial lesion, and then 11 were randomly eliminated to evenly balance the 4 surveys with 30 responses each, leaving 120 observers whose data were analyzed. Observers younger than 18 years and those self-reporting to have an affective psychiatric condition (schizophrenia, autism, or related spectrum disorders) were excluded owing to established differences in the way individuals with those disorders perceive faces.21,22 Observers ranged in age from 18 to 72 years (mean [SD], 32.31 [13.79] years) and were naïve to the study objectives. They were incentivized to participate using a raffle of nominal value.

Instrument

Four surveys were created using photographs of faces with lesions before and after surgical reconstruction as well as faces without lesions or other obvious deformity (normal faces). Our reconstructive surgery image archive was keyword searched to identify facial photographs of patients with facial lesions who had consented to have their pictures used in research studies. From this pool of images, patients with facial lesions were randomly selected and classified into 4 categories based on lesion size and location: small peripheral, small central, large peripheral, and large central. Lesion size and location were defined as described by Godoy et al.14 Patients with facial lesions continued to be randomly selected and categorized until each of the 4 lesion groups contained 8 patients with preoperative and postoperative frontal view photographs in repose. All postreconstruction patients were more than 6 months out from surgery. Photographs of 16 normal faces were then selected from our image database to demographically match the lesion faces with respect to age, sex, and race. The photographs were evenly and randomly distributed into 4 mutually exclusive surveys, such that (1) each survey contained 4 photographs per lesion category (2 preoperative, 2 postoperative), (2) each survey contained 4 photographs of normal faces, and (3) no survey contained more than 1 photograph of the same patient, to limit repeated measure effects.

For each image, observers were given the context of a face-to-face interaction in a relaxed social setting with the person displayed in the facial image. Observers were then asked to rate how comfortable they would be having a conversation with that person using a slider bar with 1-point increments from 0 (extremely uncomfortable, would not even make eye contact with this person) to 100 (extremely comfortable having a normal conversation with this person). Observers then characterized the affect of each facial image by selecting all terms that applied from the list of 8 primary affects derived from the Derogatis Affects Balance Scale (joyful, content, vigorous, affectionate, anxious, depressed, guilty, hostile) plus a neutral affect dimension.23 Attractiveness was measured using normalized slider bars with 0.1-point increments to rate attractiveness from 0 to 10 (10 indicating most attractive). Perceived QOL is a latent variable and was thus measured using 2 validated health utility measures: a visual analog scale (VAS) and a standard gamble (SG) question series. For these health utility measures, observers were instructed that if they noticed a lesion on the facial image, they were to imagine that same lesion on their own face. Then, for the VAS question, observers rated their QOL with the facial lesion using a normalized slider bar with 1-point increments from 0 (death) to 100 (perfect health, with no facial lesion). For the SG question series, observers were first asked to choose between 2 options: remain at the given health state (facial lesion) or to undergo reconstructive surgery with some probability of achieving a perfect health state (perfect repair of facial lesion) and some probability of death during surgery. If they chose to undergo surgery and accept some risk of death for a perfect repair, they answered subsequent questions to determine the maximum percentage chance of death they would accept. This was achieved using a series of questions in a bisecting search routine with 6 iterations until an inflection point was reached, as described in the literature.24,25

Data Analysis

Data were collected using Research Electronic Data Capture (REDCap; http://www.project-redcap.org) and analyzed using R software (R Foundation for Statistical Computing) with the poLCA package and Stata SE software (version 13; Stata Corp).26,27 Multiple analytic techniques were used in this study as follows. First, we measured the intraclass correlation coefficient for the conversation metric using a test-retest experiment and found it equal to 0.94, suggesting that it is highly repeatable. For normal faces, this conversation metric was highly correlated with domains of the validated Willingness to Communicate Scale, including the observers’ willingness to speak with an acquaintance (r = 0.82; P < .001) and comfort having interpersonal conversations (r = 0.57; P < .001).28 Second, as previously described by Dey et al,29 latent class analysis fitted the 8 Derogatis affects and neutral affect into 3 latent classes: neutral, positive, and negative. This analysis allowed us to characterize the affect for each face as viewed by each observer based on probability of latent affect class membership. We present a schematic of this model in the upper portion of Figure 1 illustrating the dominant (highest probability) connections between the 9 affect measures and the 3 latent affect classes. Third, structural equation modeling(SEM) was used to determine the effect of each independent variable on the observer-rated conversation score, selected for its superior ability to generate multidimensional models with observable and latent variables while accounting for inherent variance sources. Alternate models were studied; only the most cogent model is presented herein. Fourth, we conducted planned hypothesis testing using the bootstrap method. A total of 500 samples were used to estimate the standard error (SE) of the distribution of mean difference in conversation score for each postoperative lesion category vs normal faces, which were used to estimate the 95% confidence intervals for the expected differences. We determined which comparisons were significant using the Wald test. The experiment-wide α was set at .05. We corrected for multiple comparisons using the Bonferroni method.

Results

Observers were comfortable having face-to-face conversations with patients with normal faces, with a mean (SD) conversation score of 85.02 (17.95) of 100 points. As a group, facial lesions penalized conversation (61.63 [29.50]). However, reconstructive surgery on average improved the conversation metric, with a mean postoperative conversation score of 81.46 (21.68). Subsequent analyses sought to better understand and characterize this social penalty and the effect of surgical reconstruction.

The literature1620 provides evidence that variables such as attractiveness and affect have an impact on conversation and social interaction. Therefore, we first tested these effects in our sample of normal faces. The SEM presented in Table 1 details the impact of attractiveness and affect on observers’ comfort in conversing with people with normal faces. Observers were more comfortable conversing with those considered more attractive and affectively positive. For every 1 additional point (on a 10-point scale) that observers rated the person’s attractiveness, they were 3.97 of 100 points more comfortable conversing with that person. Furthermore, with neutral affect as the base category, observers were more comfortable conversing with people with normal faces who they perceived as positive (3.5) and less comfortable conversing with those they perceived as negative (−7.5). The perceived QOL term is a disease-related QOL measure and therefore was not included in the model for normal faces.

We next used SEM to quantify the impact of facial lesions and reconstructive surgery on social conversation. As noted herein, there are multiple extrinsic variables that influence conversation. SEM allowed us to not only calculate the change in conversation score with facial lesions of varying size and location, before and after reconstructive surgery, but also to account for the impact of other variables known to influence social interaction: attractiveness, affect display, and perceived QOL. The SEM for faces with lesions is presented in Table 2, which contains 4 regressions and details the key findings of this study. All findings are statistically significant with 95% confidence intervals that do not contain zero (P < .001). Figure 1 is a conceptual path diagram that provides a visual representation of the SEM shown in Table 2, illustrating the dominant relationships among the model’s constructs. Nondominant paths and interactions are not shown in Figure 1; however, they are detailed in the SEM shown in Table 2.

Starting with the main conversation regression in Table 2, we confirm our first hypothesis that facial lesions have a negative impact on observer-rated conversation, with large and central lesions generating the greatest penalty. Bootstrap calculation of expected marginal means found that preoperatively large lesions penalized conversation by an average of −17.21 (95% CI, −20.75 to −13.68) and central lesions decreased conversation by −16.35 (95% CI, −19.92 to −12.79). Our second main hypothesis is also supported by the data showing that reconstructive surgery improved the conversation score, with a bootstrap-calculated expected marginal mean improvement of 19.83 (95% CI, 17.49 to 22.17). This improvement with surgery also varied by lesion size and location, as indicated by the statistically significant interactions between surgery and lesion size and location presented in Table 2 and illustrated in Figure 2. The next regression data support our third hypothesis that there are multiple variables influencing the conversation metric. It is important to recall that the effects of the independent variables (covariates) in this regression model are independent of one another. For every 1 additional point (on a 10-point scale) that observers rated the attractiveness of a patient with facial lesions, they were 4.36 of 100 points more comfortable conversing with them. With neutral affect as the base category, we note that observers were more comfortable conversing with people with affects they considered positive (4.50) and less comfortable conversing with those they perceived as negative (−6.69). Finally, observer perceived QOL also influenced the social conversation metric. The QOL term represents the latent, perceived-QOL variable. It shows that, on average, observers preferred conversing with people with higher perceived QOL. To better understand the QOL term, we now review the other regressions in the model.

Perceived QOL is a latent variable, measured in this study using 2 established health utility metrics: the VAS and the SG. The VAS and SG regressions in Table 2 demonstrate that lesions decrease QOL and reconstructive surgery increases QOL as perceived by the casual observer. The QOL term included in the model is a latent variable representing the lesion-related QOL independent of the factors accounted for in the VAS and SG subregressions (size, location, and surgery). Therefore, QOL is an important lesion-related QOL variable, providing insight into another unique domain of facial perception that influences social conversation. The final regression in the Table 2 SEM regresses attractiveness and confirms earlier studies that facial lesions decrease attractiveness and surgery increases attractiveness, effects dependent on lesion size and location.14 The random effects for the SEMs for individuals with and without facial lesions are presented in Table 3.

Finally, to test the subhypothesis that surgical reconstruction of facial lesions can normalize conversation for some lesion categories, we preformed planned hypothesis tests using the bootstrap method. The results are presented in Table 4, which shows that surgery normalized the conversation score for all categories of lesions except large central lesions. Despite significant improvement with surgery, faces with large central lesions had a remaining conversation penalty of −9.749 (95% CI, −13.160 to −6.338) after surgery.

Discussion

One ultimate measure of successful reconstruction is normalization of appearance. The problem is that there is no singular measure of “normalcy.” Normalization is perhaps the ultimate variable; it cannot be directly measured. This is particularly true when studying outcomes as perceived by general society. Because there is no singular metric for normal appearance, we must use a battery of metrics to assess multiple dimensions of facial perception. Assessing multiple dimensions and comparing them across aggregates of faces with lesions before and after surgery and normal faces yields a comprehensive assessment of the changes that occur with lesions and with reconstructive surgery. In the present study, we used multiple scales to measure social facial perception and then created a statistical model to account for each metric, arguably generating the most comprehensive model of observer perception of facial deformity in the literature to date. The variance in Table 3 shows that this model is not perfect and does not account for all of the variables in social facial perception. However, the multidimensional nature of this model is one of the major strengths and contributions of this study.

From the raw data, we determined that facial lesions have a negative impact on conversation, an effect reduced after reconstructive surgery. The statistical support for these initial findings is provided in structural equation models, which also account for other variables that have an impact on social conversation (Table 2). Observer-rated attractiveness, affect, and perceived QOL significantly affected conversation. Regression quantified the independent effect of each covariate on the conversation metric, showing that positive affect and greater perceived attractiveness and QOL increased observers’ comfort in conversing with patients with facial abnormalities. Likewise, negative affect and lesser perceived attractiveness and QOL decreased observers’ comfort in conversing with these patients. Accounting for these variables that influence conversation allowed us to more accurately calculate the impact of facial lesions and reconstructive surgery on observer-rated conversation. We found that (1) facial lesions penalize conversation, with large and central lesions having the most negative impact, and (2) reconstructive surgery significantly increases the conversation score (Table 2 and Figure 2).

Another major finding in this study is the effectiveness of reconstructive surgery to improve and normalize observer-rated conversation. As illustrated in Table 4 and Figure 2, surgical reconstruction improved and even normalized conversation for every lesion group, except patients with large central lesions. For those with large central lesions, while surgery reduced the conversation penalty, it did not eliminate it. These findings provide evidence of the effectiveness of reconstructive surgery. They also identify large central lesions as a focus for future research and surgical innovation efforts.

Multiple variables influence human conversation and are organized according to 3 domains: intrinsic (internal), extrinsic (external), and contextual. Intrinsic variables describe internal factors of individuals that influence conversation. Intrinsic variables include willingness to communicate, a trait-like variable that quantifies how willing one is to converse in various contexts.28,30 Other intrinsic variables are communication apprehension, tendency for verbal activity, and self-perceived communication competence.3133 In our study, the intrinsic variables are accounted for in the residual variance of our statistical models. The context variables include aspects about settings, circumstances, and modes of communication. We controlled for context variables by fixing them; that is, the exact same context (“a face-to-face social encounter with a stranger in a relaxed social setting”) was presented throughout the survey. It has been shown that this is one of the most difficult and strained social encounters for people with facial abnormalities.5,34 Accounting for the intrinsic variables and fixing the context variables were important to allow focus on the extrinsic variables that influence conversation.

The importance of studying these extrinsic variables is at least 3-fold. First, extrinsic variables are arguably the most affected by facial deformities and therefore should be a major focus of research and treatment efforts. Second, while it is difficult to change the intrinsic and context variables that influence conversation (ie, it is difficult to change a personality trait or to avoid interacting in certain social contexts), extrinsic variables can be modified with surgical reconstruction. Third, there is evidence that extrinsic variables significantly influence the course of subsequent interactions.16 Macgregor5 described how facial deformities can evoke visceral reactions in observers, turning otherwise normal social encounters into experiences of aversion and anxiety. Patients with facial abnormalities are acutely aware of the perturbed nature of these encounters, and they often experience negative psychosocial consequences.58 This emphasizes the need to characterize which aspects of facial perception are perceived abnormally or negatively by observers and how those variables have an impact on social interactions. Improved understanding of how society perceives facial abnormalities has the potential to provide reconstructive goals and outcomes tools to help minimize these extrinsic variables that perturb social interaction and reduce QOL.

This study has limitations. We used a subjective metric of conversation to assess observers’ perception of stimulus faces. These initial perception data, collected in a theoretical setting, may not match the actual experience in a real-life setting. However, data indicate that initial perception may be just as important as actual experience because if an initial perception is negative, it can modulate action and prevent otherwise normal social interactions from occurring. Another challenge in the study of conversation is that multiple variables influence it. While we accounted for multiple variables, there are likely others that were not directly tested. However, we can account for them in the residual variance of our regression models, allowing us to more accurately quantify the effects of the independent variables. Another limitation is in the pilot nature of this study, showing only 1 photograph of each person to observers, whereas multiple photographs or videos might have been better stimuli. Furthermore, the included patients were from an academic facial plastic surgery division; therefore, these results may not generalize to all facial plastic surgery practices.

Despite its limitations, this study makes important contributions to the literature and to our ability to care for patients. We measured observer perception of an important dependent variable, conversation; studied a new dimension of facial perception, perceived QOL; and generated a multidimensional model to account for the effects of multiple variables. We used that model to quantify the social penalty associated with facial lesions and the effectiveness of reconstructive surgery. We should use these findings to openly counsel our patients about the impact of their lesions on their social interactions. We can reassure them that though the lesion may cause them great distress, with carefully planned and executed reconstruction we can restore them toward a state of “normalcy,” engendering confidence in social situations. At times, the reconstruction process may seem cumbersome or time consuming, particularly in multistage repairs, but with these data we can confidently support the investment.

Conclusions

Facial lesions have a negative impact on multiple dimensions of perception as rated by the casual observer. A comprehensive data analysis finds that lesions have a negative impact on social conversation, an effect alleviated with reconstructive surgery. This study provides new evidence supporting high-quality surgical reconstruction of facial lesions and suggests future research avenues.

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Article Information

Corresponding Author: Lisa E. Ishii, MD, MHS, The Johns Hopkins School of Medicine, Department of Otolaryngology–Head and Neck Surgery, 601 N Caroline St, Ste 6231, Baltimore, MD 21287 (learnes2@jhmi.edu).

Accepted for Publication: September 9, 2014.

Published Online: December 4, 2014. doi:10.1001/jamafacial.2014.1131.

Author Contributions: Mr Dey had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Dey, L. E. Ishii, Boahene, M. Ishii.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Dey, L. E. Ishii, M. Ishii.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Dey, L. E. Ishii, M. Ishii.

Obtained funding: M. Ishii.

Administrative, technical, or material support: Dey, L. E. Ishii, Boahene, M. Ishii.

Study supervision: L. E. Ishii, Byrne, M. Ishii.

Conflict of Interest Disclosures: None reported.

Previous Presentation: This study was an oral presentation at the American Academy of Facial Plastic and Reconstructive Surgery Annual Meeting; September 18, 2014; Orlando, Florida.

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