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Abstract

Background:

Currently available patient-reported outcome measures (PROM) have limited ability to assess unique issues related to lateral canthal lines (LCL). This study aimed to develop a PROM to assess the severity and psychosocial impact of LCL in afflicted patients.

Methods:

We conducted a cross-sectional survey at a tertiary hospital and two local clinics in Korea. Exploratory factor analysis was conducted to identify the underlying factor structure of the Facial Line Distress Scale for LCL (FINE-LCL), and the internal consistency and test–retest reliability were also examined.

Results:

We developed a questionnaire comprising 20 items in four domains. Coefficient alphas ranged from 0.94 to 0.97 for subdomains and 0.97 for the total questionnaire. The test–retest intraclass correlation coefficient ranged from 0.77 to 0.90. The FINE-LCL was moderately correlated with the appearance appraisal score and body image. Analysis of the accuracy of the FINE-LCL score in predicting severe LCL was characterized by an area under the curve of 0.79.

Conclusions:

FINE-LCL is a reliable, valid, and comprehensive PROM for the assessment of the severity of LCL and their associated distress.

KEY POINTS

Question: Are there currently sufficient methods to assess the severity and psychological impact of lateral canthal lines?

Findings: We developed and validated a new questionnaire that measures both the severity and psychosocial distress linked to lateral canthal lines.

Meaning: Researchers and clinicians can use the Facial Line Distress Scale for lateral canthal lines not only for screening but also for evaluating the efficacy of treatments for lateral canthal lines.

Introduction

Facial wrinkles are a key factor in determining age.¹ Lateral canthal lines (LCL) represent one of the initial signs of aging, with their severity increasing directly with age.² In particular, the eyes express emotion and influence perceptions of age and beauty,¹ making LCL highly relevant targets in the treatment of aging. Indeed, prior studies have identified LCL as the most concerning sign of aging on the face and the one that individuals would prefer to address as a priority.^3–5

With the rising popularity of LCL treatment, such as the injection of fillers or botulinum toxin⁶ and radiofrequency energy, several measures to evaluate the efficacy of these treatments accurately have been introduced. However, some of these methods, such as those utilizing skin mimics⁷ and 3D imaging,⁸ require specialized equipment and expertise. Furthermore, clinician-reported outcome measures, such as the Facial Wrinkle Scale (FWS) and the Merz Aesthetic Scale (MAS),⁹ do not fully capture the patient experience. As treatment for LCL improves not only aesthetics but also psychosocial aspects, patient-reported outcome measures (PROMs) have gained recognition as an effective solution to assess multidimensional treatment satisfaction and success. A variety of different PROMs have subsequently been utilized to evaluate the efficacy of LCL intervention. However, existing PROMs generally evaluate the upper face as a facial subunit and do not separately identify the contribution of LCL.^10,11 In addition, while LCL can cause appearance-related distress, decreased self-confidence, and other mental health issues,⁶ no PROM has yet been developed to assess psychosocial issues specifically related to LCL.

To address this knowledge gap, we developed and validated a new PROM to assess the severity and psychosocial impact of LCL.

Methods

Study participants

This cross-sectional study was conducted at a tertiary hospital and two local clinics in Korea between April 18 and June 17, 2022. The eligibility criteria for study participation included: (1) adults aged ≥18 years, (2) individuals concerned or distressed about LCL, and (3) those capable of reading and writing in Korean. We excluded participants with severe dermal scarring on the upper face, severe cognitive impairment, or mental disorders. The study was advertised via online community groups and offline information boards. The participants were awarded $10 for their participation. This study was approved by the Institutional Review Board (IRB) of Samsung Medical Center, Seoul, Republic of Korea. Informed consent was obtained from all participants (IRB number SMC-2021-07-166).

Measurement

We developed a novel questionnaire, termed the Facial Line Distress Scale for LCL (FINE-LCL), following the Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) checklist¹² and Food and Drug Administration (FDA) guidelines for PROM.¹³ The development of the FINE-LCL involved an extensive literature review and semi-structured in-depth interviews with 25 adults aged >18 years with concerns about LCL. As a result, 37 items in two domains and six subscales (general facial expression, certain situation, distress due to LCL, public self-consciousness, psychological distress, and social distress) were prepared for the initial version of the FINE-LCL. A pilot test was subsequently conducted with five participants who met the eligibility criteria for the in-depth interview. Participants completed the questionnaire and were subsequently interviewed to obtain feedback on the content, ease of response, and acceptability of the terminology, phrasing, and response options.

Psychometric validation of the FINE-LCL was subsequently conducted to evaluate its reliability, validity, and responsiveness. In addition, the convergent and discriminant validities of the FINE-LCL were tested. PROMs for health-related quality of life (HRQoL), body image, and appearance appraisal were compared. For HRQoL, the World Health Organization Quality of Life Assessment Instrument (WHOQOL)-BREF¹⁴ was used. The Body Image Scale (BIS) was used to measure body image,¹⁵ while the MAS¹⁶ was used to assess the severity of facial wrinkles.

Additional sociodemographic and clinical data, including age, sex, marital status, education, monthly family income, employment, and LCL treatment experience, were obtained.

Statistical analysis

The mean and standard deviation (SD) were reported for each item in the FINE-LCL. To reduce the number of items, exploratory factor analysis (EFA) was performed using varimax rotation. To confirm the adequacy of the number of factors, we used the maximum likelihood methods and checked whether the Tucker–Lewis Index of factoring reliability exceeded 0.9. The item response theory (IRT) graded response model (GRM) was used for the distress domain. Differential item functioning (DIF) analyses were further performed to evaluate whether participants from different groups, experiencing similar levels of distress due to LCL, had different probabilities of providing a response after conditioning at the measured state level.

After EFA, we performed confirmatory factor analysis (CFA),¹⁷ which involved evaluation of the model fit using the comparative fit index (CFI) and the standardized root mean square residual (SRMR). A CFI >0.9 and SRMR <0.08 indicated a good fit to the data.^18,19

We subsequently calculated the internal consistency of each domain using Cronbach's alpha and the item–total correlation of each domain. A Cronbach's alpha of ≥0.8 indicated very good reliability.²⁰

Next, the test–retest reliability was measured using the intraclass correlation coefficient (ICC) with a two-way mixed model with absolute agreement specified during repeated measurements. Based on prior reports, the questionnaire was considered reliable if its ICC value was >0.70.²¹ Using the repeated-measure data set, the standard error of measurement (SEm)²² and the smallest detectable change (SDC) were also calculated.²³

Finally, we calculated convergent and discriminant validity using Pearson's correlations between the FINE-LCL and WHOQOL-BREF, BIS, and MAS. To adjust for multiple comparisons, we obtained adjusted p-values using the Holm–Bonferroni method. In addition, we calculated the area under the curve (AUC) of the FINE-LCL for physician-rated severe LCL using the MAS to test criterion validity. For the analysis, “severe LCL” and “very severe LCL” were recorded as the severe LCL group. We also used the Youden index to determine the cutoff values.²⁴

The significance level was set at p < 0.05 (two-sided), and all statistical analyses were performed using STATA v16 (StataCorp LP, College Station, TX) and R v4.1.2 (R Foundation for Statistical Computing, Vienna, Austria).

Results

Among the 216 enrolled patients, one who did not complete the questionnaires was excluded. The mean age (SD) of the participants was 48.43 (13.40) years, the majority of the participants had at least mild LCL, and 27.8% had previously undergone facial aesthetic treatments (see Supplementary Table S1).

All 36 items satisfied Bartlett's test of sphericity (p < 0.01) and the Kaiser–Meyer–Olkin test for sampling adequacy (p = 0.96). The EFA indicated a five-factor solution, with an eigenvalue of >1.0. Four items (#19, #34, #35, and #36) that were loaded on two or more factor solutions with lower loading values (r < 0.5) were also excluded (Table 1). Despite a relatively lower factor loading observed for item #15, participants emphasized its importance during qualitative interview. Consequently, the item was retained in the analysis. Initially, five items designed for the “psychological distress” domain loaded onto the “social distress” domain. Consequently, we combined these two domains into a single domain, termed “psychosocial distress.” Upon further review by experts, questions #13, #22, #24, #26, and #33 were identified as having similar meanings or loading on two or more factors. As a result, these questions were removed.

Table 1.

Factor loadings from the exploratory factor analysis and reliability of the FINE-LCL dimensions (N = 215)

No.	Items (theme)	Factor					Decision
	Items (theme)	1	2	3	4	5
Appraisal of lateral canthal lines
	General
#1	I have a lot of LCL	0.19	0.77	0.20	0.13	0.11	General
#2	My LCL stand out	0.21	0.81	0.26	0.11	0.09	General
#3	My LCL are deep	0.21	0.81	0.12	0.26	0.08	General
#4	My LCL are long	0.28	0.77	0.10	0.24	0.07	General
	Facial expression
#5	I have a lot of LCL	0.18	0.74	0.36	0.03	0.18	Facial expression
#6	My LCL stand out	0.16	0.75	0.42	–0.01	0.19	Facial expression
#7	My LCL are deep	0.23	0.83	0.17	0.17	0.08	Facial expression
#8	My LCL are long	0.24	0.81	0.22	0.14	0.07	Facial expression
	Certain situation
#9	I am concerned about my LCL when talking	0.41	0.38	0.62	0.29	0.08	Certain situation
#10	I am concerned about my LCL when under bright lights	0.38	0.34	0.69	0.22	0.06	Certain situation
#11	I am concerned about my LCL when looking the mirror	0.24	0.41	0.71	0.15	0.16	Certain situation
#12	I am concerned about my LCL when concentrating	0.35	0.27	0.66	0.32	0.06	Certain situation
#13	I am concerned about my LCL when frowning	0.24	0.27	0.72	0.22	0.11	Deleted^a
#14	I am concerned about my LCL when smiling	0.27	0.32	0.74	0.08	0.08	Certain situation
Distress due to lateral canthal lines
	Self-consciousness
#15	I look older than my peers because of my LCL	0.36	0.45	0.38	0.36	0.14	Self-consciousness
#16	I look depressed because of my LCL	0.43	0.36	0.26	0.72	0.13	Deleted^b (IRT fit = 0.050)
#17	I look worried because of my LCL	0.40	0.34	0.26	0.73	0.19	Self-consciousness
#18	My LCL give me the appearance of having a strong personality or a distinctive character	0.47	0.33	0.20	0.64	0.14	Self-consciousness
#19	I look like I went through difficulties in the past due to my LCL	0.18	0.40	0.10	0.22	–0.10	Deleted
	Psychological distress
#20	I have low self-confidence because of my LCL	0.48	0.26	0.44	0.35	0.40	Psychosocial
#21	I think negatively about myself because of my LCL	0.57	0.31	0.25	0.37	0.45	Deleted
#22	I feel unattractive because of my LCL	0.56	0.26	0.29	0.34	0.51	Deleted^a
#23	I am unsatisfied with myself because of my LCL	0.51	0.27	0.36	0.26	0.55	Deleted
#24	I feel bad about myself because of my LCL	0.60	0.28	0.31	0.37	0.44	Deleted^a
	Social distress
#25	I am concerned about meeting new people because of my LCL	0.71	0.30	0.23	0.28	0.27	Psychosocial
#26	I am concerned about people around me talking about my LCL	0.67	0.29	0.33	0.25	0.18	Deleted^a
#27	I am concerned that my LCL will affect my social life	0.79	0.28	0.18	0.27	0.17	Psychosocial
#28	I am concerned about going to important events because of my LCL	0.76	0.30	0.23	0.23	0.16	Deleted^b (sex DIF = 0.026)
#29	I avoid going out without makeup because of my LCL	0.75	0.24	0.29	0.11	0.19	Deleted^a
#31	I avoid sitting close to others because of my LCL	0.82	0.24	0.12	0.26	0.10	Psychosocial
#32	I avoid being photographed by others because of my LCL	0.77	0.26	0.19	0.25	0.10	Deleted^b (sex DIF = 0.020)
#33	I spend a lot of time preparing to go out because of my LCL	0.78	0.24	0.22	0.19	0.12	Deleted^a
#34	I use cosmetics to improve my LCL	0.29	0.04	0.32	–0.10	0.12	Deleted
#35	I had a procedure to improve my LCL	0.24	0.10	0.11	0.00	–0.05	Deleted
#36	I don't make facial expressions that could make my LCL worse	0.41	–0.01	0.26	0.08	–0.03	Deleted

Values >0.4 are presented, and the highest loading values are shown in bold.

Deleted based on the expert review.

Deleted based on the item response theory.

LCL, lateral canthal lines; IRT, item response theory.

In the IRT-GRM, the probability values for the S-χ² statistics ranged from 0.00 to 0.50. Consequently, one item (#16) with a poor fit (pS-χ² < 0.05) was excluded (Table 1). Two more items, #28 (McFadden's pseudo-R² for sex = 0.026) and #32 (McFadden's pseudo-R² for sex = 0.03), were further excluded based on the DIF by sex. There was no DIF according to age group.

The CFA with the 20 items FINE-LCL revealed high loadings (0.63–0.92) in general. The fit indices for this model were good, with the final version of the FINE-LCL (comprising 20 items in two domains and five subscales) achieving a CFI of 0.916 and SRMR of 0.056 (Fig. 1). The FINE-LCL score was calculated after transforming it to a range from 0 to 4, achieved by summing the responses of items in each domain. The possible score range was 0–100, and higher scores indicated higher levels of distress due to LCL.

Fig. 1.

Overview of the confirmatory factor analysis.

The mean total score for the FINE-LCL was 46.91. In this study, the floor and ceiling effects were 1.4% and 0.9%, respectively. The Cronbach's alpha coefficients of the five subscales ranged from 0.94 to 0.97, indicating satisfactory internal consistency. The Cronbach's alpha coefficient of the total score was 0.97 (see Supplementary Table S2).

In analysis to test reliability in 94 patients, the ICC of the total score was 0.74, indicating a satisfactory level of reliability. The SEm of the total score was 9.51, and the SDC was 18.64 (Table 2). The self-evaluation of LCL at rest and in dynamic expressions in the FINE-LCL was moderately correlated with the MAS at rest and the MAS in dynamic expressions. In addition, the impact of LCL on the patient distress domain was moderately correlated with the overall QoL (r = 0.40) and body image (r = 0.51) scores. Although the WHOQOL moderately correlated with the social domain in the FINE-LCL, there was a weak correlation with other domains (Table 3).

Table 2.

Reliability of the FINE-LCL (N = 94)

Subscales	ICC (95% CI)	SEm	SDC
Appraisal of LCL	0.69 (0.59–0.77)	5.93	11.62
General	0.64 (0.53–0.73)	2.46	4.82
Facial expression	0.62 (0.50–0.71)	2.19	4.30
Certain situation	0.61 (0.50–0.71)	2.71	5.32
Impact of LCL on patient distress	0.74 (0.65–0.80)	4.61	9.03
Public self-consciousness	0.72 (0.62–0.79)	2.38	4.66
Psychosocial	0.69 (0.59–0.72)	2.70	5.30
Total FINE-LCL	0.74 (0.65–0.81)	9.51	18.64

FINE-LCL, Facial Line Distress Scale for Lateral Canthal Lines; ICC, intra-class coefficient; CI, confidence interval; SDC, smallest detectable change; SEm, standard error of measurement; LCL, lateral canthal lines.

Table 3.

Correlation of the FINE-LCL with the WHOQOL (N = 215)

	Legacy measures
Subscales	WHOQOL-BREF	BIS	MAS at rest	MAS at dynamic
Appraisal of LCL	–0.27^**	0.39^**	0.61^**	0.65^**
General	–0.28^**	0.34^**	0.66^**	0.66^**
Facial expression	–0.21^**	0.33^**	0.55^**	0.55^**
Certain situation	–0.25^**	0.38^**	0.44^**	0.44^**
Impact of LCL on patient distress	–0.40^**	0.51^**	0.46^**	0.46^**
Public self-consciousness	–0.39^**	0.48^**	0.46^**	0.46^**
Psychosocial	–0.37^**	0.49^**	0.42^**	0.41^**
Total FINE-LCL	–0.35^**	0.47^**	0.58^**	0.60^**

p < 0.01; ^*p < 0.05.

FINE-LCL, Facial Line Distress Scale for Lateral Canthal Lines; WHOQOL, World Health Organization Quality of Life Assessment Instrument; BIS, Body Image Scale; MAS, Merz Aesthetics Scale; LCL, lateral canthal lines.

When the physician evaluated the patients using the MAS, 29% of the participants were found to have severe LCL. A difference of 16.6 points on the FINE-LCL was noted between participants with severe LCL and those without (40.5 vs. 61.4, p < 0.01; data not shown). The accuracy of the FINE-LCL score in predicting severe LCL was characterized by an AUC of 0.79 (Fig. 2). The cutoff score for severe LCL was 51.2 out of 100.

Fig. 2.

Criterion validity: receiver operating characteristic curves of the Facial Line Distress Scale for Lateral Canthal Lines scale for severe lateral canthal lines, evaluated by physicians.

Discussion

In this study, we developed the FINE-LCL, a novel and reliable tool, validated for evaluating the severity and distress associated with LCL, in accordance with the COSMIN and U.S. FDA guidelines for PROM development.

The FINE-LCL appears to have several advantages over the existing tools. First, the FINE-LCL can be easily implemented to measure LCL conditions, even in smaller clinics. Conversely, existing methods, including skin mucus⁷ and 3D imaging,⁸ require specialized equipment and trained personnel. The FINE-LCL also provides an accurate and quantitative assessment by integrating both objective and subjective assessments of distress across two domains. This questionnaire can help clinicians to understand issues related to LCL more comprehensively. Furthermore, it underscores patient-centered care in aesthetic medicine. Unlike existing instruments such as the FWS and MAS,⁹ which rely on clinician-reported assessments, the FINE-LCL strives to fully capture the patient experience.

Another important aspect of the FINE-LCL tool is its focus on the assessment of distress associated with LCL rather than the assessment of treatment efficacy alone. This allows the tool to be used for screening purposes to determine whether patients are experiencing high levels distress due to LCL and whether they would benefit from LCL treatment. By addressing the emotional impact of LCL, the FINE-LCL provides valuable insights that can guide patient management and help to optimize treatment outcomes.

Most importantly, the measure showed good internal consistency. While some items were loaded in a different domain from that initially hypothesized, all such occurrences were explainable. One item in the self-consciousness domain, which inquired about perceived aging, had a similar loading value in the psychosocial distress domain. This may be because perceived aging is associated with social interactions. In the test–retest validation, we confirmed that the FINE-LCL was acceptable overall.

In addition, concurrent validity was demonstrated by the degree of correlation with the MAS. As expected, the FINE-LCL was highly correlated with the MAS. Because we asked the patients about the LCL-specific MAS, there may have been a high correlation between the two measures. In contrast, as expected, body image and WHOQOL showed only weak and moderate correlations with the appraisal and distress domains of the FINE-LCL, respectively. These results suggest that it is appropriate to inquire about the severity of specific wrinkles and the discomfort they cause through separate questions.

This study has several limitations. First, we did not include an existing questionnaire that evaluates distress due to LCL to confirm convergent validity. Second, we recruited only Korean participants, which limits the generalizability of these findings to other ethnicities. However, in this study, we recruited individuals who expressed concerned about LCL from various groups to capture a wider range of potential opinions and facilitate the development of the FINE-LCL.

Conclusions

In conclusion, the FINE-LCL is a reliable and valid PROM for measuring the severity and burden of LCL. This questionnaire has potential utility not only for screening but also for evaluating the efficacy of treatments for LCL. Considering the rising importance of capturing patients' perspective and reflecting the psychosocial impact of aesthetic treatments, additional validation studies with different population at different settings would be necessary.

Footnotes

Authors' Contributions

All authors have reviewed the results and approved the final version of the article before submission. Acquisition of the data by K.C.,E.K.,and S.K.;drafting of the article by K.C.,D.K.,and E.K.;conception and design of the study by D.K.,W.S.L.,and J.C.;data analysis and interpretation by D.K.;and revision of the article by J.C.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This study was supported by Medytox,Inc.

Supplementary Material

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Supplementary Material

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Development and Validation of the Facial Line Distress Scale for Lateral Canthal Lines: FINE-LCL

Abstract

Background:

Methods:

Results:

Conclusions:

KEY POINTS

Introduction

Methods

Study participants

Measurement

Statistical analysis

Results

Discussion

Conclusions

Footnotes

Authors' Contributions

Author Disclosure Statement

Funding Information

Supplementary Material

References

Supplementary Material