Correlation Study of Subjective Clinical Evaluation and Skin Biophysical Properties in Facial Skin among Young Korean Women; Pilot Study

ABSTRACT

Background

Although standardized, evidence‐based diagnostic tools are essential for the assessment of the efficacy of facial skin rejuvenation, aesthetic medicine has largely relied on subjective evaluations, especially in primary clinics. Recent studies have demonstrated the potential of skin biophysical properties for objective assessment; however, they are not widely applied in clinical practice.

Aims

To investigate the correlation of physicians' clinical evaluations of skin hydration, skin firmness, melanin, and erythema with skin biophysical properties.

Patients/Methods

Twenty Korean women with healthy skin were clinically and quantitatively evaluated. The former comprised questionnaires with 7‐point scales regarding the grade of skin hydration, firmness, melanin, and erythema, completed by a dermatologist; the latter comprised measurements of conductance, trans‐epidermal water loss (TEWL), gross elasticity (R2), dermal thickness, and melanin and erythema by another physician independently to subjective assessment.

Results

Conductance and TEWL were significantly correlated with subjective hydration scores (Spearman's 𝜌 = 0.456 and 𝜌 = −0.604, respectively). Moreover, the objectively measured melanin index demonstrated a significant positive correlation with the clinically assessed melanin severity score (𝜌 = 0.612, p < 0.01). Clinical evaluation of erythema was significantly correlated with Young's modulus (𝜌 = −0.614) and inversely correlated with dermal thickness (𝜌 = 0.781, both p < 0.01).

Conclusions

Unlike skin hydration, melanin, and erythema, skin firmness did not significantly correlate with biophysical properties. Thus, clinical evaluation is insufficient to establish treatment strategies for skin tightening in young women. Quantitative data may be an effective adjunctive diagnostic tool for patients who require subclinical interventions. This study was pilot study to explore the potential of objective measurements as adjunctive diagnostic tool in clinical setting, while some limitations include a small sample size, narrow range of age, and sex bias.

1. Introduction

In modern aesthetic medicine, maintaining skin quality in young adults involves managing early, dynamic physiological fluctuations rather than treating advanced chronological degradation or structural sagging. In young Korean women (typically aged 20–35 years), primary dermatological concerns frequently center around transient skin barrier disruption, cutaneous dehydration (sub‐surface xerosis), and subtle shifts in early structural tissue compliance. Consequently, rather than aggressive surgical or high‐energy destructive lifting, preventative non‐invasive interventions—such as polynucleotides, hyaluronic acid skin boosters, and mild energy‐based conditioning—have gained substantial clinical popularity [1, 2, 3, 4, 5]. Capturing these early, sub‐clinical micro‐modifications requires high‐precision biophysical tracking to identify barrier leaks and early structural changes before gross anatomical laxity becomes clinically apparent [5, 6].

To compare the efficacy of various treatment modalities for the implementation of customized medicine, evidence‐based diagnosis via standardized methods must be established [5, 6]. However, assessments in aesthetic medicine have primarily been subjective in nature, leading to limitations in clinical practice, research, and the progression toward AI‐based medicine [7, 8]. Recently, researchers studying on the efficacy of aesthetic dermatological treatments such as polynucleotides (PNs) and micro‐focused ultrasound with visualization (MFU‐V) have made use of skin biophysical properties—specifically stratum corneum hydration (conductance), transepidermal water loss (TEWL), viscoelasticity, dermal thickness, and colorimetric color indices (melanin and erythema)‐ demonstrating quantitative changes [3, 9]. Although such properties hold strong potential as a standardized diagnostic method in aesthetic medicine, they have rarely been applied in diagnosis and consultation within clinical settings to date [7]. Further investigation is required to determine whether the subjective clinical evaluations conducted by primary care physicians in real‐world settings accurately reflect the results obtained through quantitative measurements. Therefore, in this study we aimed to investigate the correlation of physicians' clinical evaluations of skin dryness, firmness, and color with measurable biophysical properties of the skin.

2. Materials and Methods

This study was approved by the V&CO Institutional Review Board (Seoul, South Korea; IRB Registration No. 1‐70094470‐B‐N‐01; Approval No. VNCO_2023_06_01; Approved on December 16, 2024) and conducted according to the guidelines of the 1975 Declaration of Helsinki, as amended in 2013 by the 64th WMA General Assembly. Written informed consent was obtained from all individual participants prior to enrollment.

2.1. Study Population

From January to March 2025, patients who desired noninvasive or minimally invasive skin rejuvenation therapy at single center (V‐Plastic Surgery, 18 Gongpyeong‐ro 10‐gil, Jung‐gu, Daegu, South Korea) were screened for eligibility. The inclusion criterion was an age of 20–40 years. The exclusion criteria were any inflammatory skin diseases of the face (such as eczema, inflammatory acne vulgaris, psoriasis, and bacterial infections), application of topical agents (i.e., steroids and retinoids, except for cosmetics) to the face within 4 weeks, and administration of any facial skin rejuvenation therapy (including monopolar RF treatment, MFU‐V, and injectable skin boosters) within 2 months. Individuals who were pregnant, breastfeeding, or planning a pregnancy during the study period were strictly excluded.

2.2. Study Protocol

2.2.1. Subjective Assessment

Comprehensive scoring systems of extrinsic skin aging have been evaluating various conditions including Hydration, firmness, melanin, and erythema [10, 11, 12]. Subjective clinical evaluations of facial skin conditions were independently performed by an experienced dermatologist using a standardized 7‐point Likert scale (ranging from 1 = very mild/absent to 7 = severe). To maintain an intuitive and clinically straightforward interpretation throughout the study, the scoring system was structured as a severity index for each feature: higher scores for skin hydration indicated optimal cutaneous moisture, and higher scores for skin firmness severity reflected a more severe loss of tissue elastic recoil. Concurrently, for pigmentary and vascular parameters, the ratings were defined as a severity score, where a higher score directly represented a greater degree of melanin hyperpigmentation and a higher intensity of visual facial erythema, respectively. A score of 1 indicated a completely clear, flawless skin state, while a score of 7 represented maximum clinical severity requiring aggressive cosmetic intervention.

2.2.2. Measurements of Skin Biophysical Properties

After clinical assessment, another physician measured biophysical properties independently and was blinded to the result of clinical evaluation. Biophysical measurements were performed at standard room temperature (20°C‐21°C) and humidity (40%‐50% relative humidity). Prior to the evaluations, all participants underwent a strict acclimatization period of 20–30 min in the resting room to stabilize skin blood flow, baseline perspiration, and neutralize macroclimatic barrier variations. A conductance pin probe (Moisture Probe), TEWL X Probe, suction‐cup chamber (Elasticity Probe), high‐resolution ultrasound imaging (20 MHz DermaScan), and Colori Probe (Dermalab Combo 4; Cortex Technology, Hadsund, Denmark, running DermaLab software version 1.2) were used to measure hydration, trans‐epidermal water loss (TEWL), gross elasticity (R2), dermal thickness, and skin color (melanin and erythema), respectively.

Although skin biophysical properties are easy to measure in localized skin conditions, they have limitations for global skin assessment because of variability among measurement sites [9, 10]. Therefore, we chose an area commonly considered for subjective measurements, the anteromedial cheek area, to ensure consistency. All measurements were conducted at the intersection of the vertical line from the lateral canthus with the horizontal line that connects the nasal ala and the tragus. All instrumental assessments were strictly confined to the right anteromedial cheek (a designated 3 × 3 cm test site) of each participant. To ensure data reliability, three consecutive measurements were taken per test site, and the mean value was utilized for subsequent statistical analysis.

2.3. Calculating Young's Modulus

In this study, the Dermalab suction‐cup chamber was used to measure elasticity, and Dermalab high‐resolution ultrasound imaging was used to measure facial skin thickness. By using the suction method to measure skin elasticity, the elastic plate model can be used to calculate Young's modulus, as follows [13]:

$$E=0.3125\frac{\mathrm{\Delta }p}{\mathrm{\Delta }w{h}^3}\left(\mathrm{MPa}\right),$$ (1)

where E is Young's modulus, w is the deflection of the skin surface, p is the suction pressure, and h is the skin thickness. These values were calculated manually by the authors utilizing the mathematical equation (Equation 1) based on the DermaLab software version 1.2.

2.4. Statistical Analysis

Statistical analysis was performed using SPSS version 23.0 (IBM Corp., Armonk, NY). Statistical significance was set at p < 0.05. The normality of the collected data was assessed using the Shapiro–Wilk test. Given the ordinal nature of the 7‐point clinical Likert scale and to robustly handle potentially non‐normally distributed physical parameters without outlier distortion, the correlations between subjective clinical evaluations and objective biophysical properties were determined using Spearman's rank correlation coefficient ($\rho$).

3. Results

3.1. Patients’ Information

Twenty patients were prospectively enrolled in this study. The mean ± standard deviation age of participants was 27.80 ± 5.14 years. Among the participants, 12 responded that their skin type was dry, and 8 responded that their skin type was oily. The Fitzpatrick skin type was distributed from type II to IV (6 with type II, 10 with type III, and 4 with type IV). The mean conductance (measuring the level of moisture) of the stratum corneum was 255.22 ± 85.93 µS, and the TEWL was 10.94 ± 3.23 g/hour/m². The mean R2 (gross elasticity) was 0.80 ± 0.05. The mean dermal thickness was 1580.0 ± 154.8 µm, and Young's modulus calculated with dermal thickness was 1.31 ± 0.46 MPa. The melanin and erythema levels were 32.99 ± 2.28 and 13.93 ± 2.27 arbitrary units, respectively (Table 1).

TABLE 1.

Participants’ information and means±standard deviations of quantitative measurements.

Demographic characteristics of study subjects
Age (years)	27.80±5.14
Skin type
Dry	12
Oily	8
Fitzpatrick skin type
Type II	6
Type III	10
Type IV	4
Skin biophysical Properties (Objective)
Conductance (µS)	255.22±85.93
TEWL (g/hour/m2)	10.94±3.23
R2 (gross elasticity)	0.80±0.05
Dermal thickness (µm)	1580.0±154.84
Young's modulus (MPa)	1.31±0.46
Melanin (arbitrary units)	32.99±2.28
Erythema (arbitrary units)	13.93±2.27
Clinical evaluation (Subjective)
Hydration score	3.39 ± 1.46
Firmness score	4.33 ± 1.37
Melanin score	4.83 ± 1.82
Erythema score	2.89 ± 1.32

Abbreviation: TEWL, Transepidermal Water Loss.

3.2. Correlation Coefficients Between Subjective Evaluation and Quantitative Biophysical Properties

Conductance and TEWL were correlated with the subjective clinical evaluation of skin hydration (Spearman's $\rho$ = 0.456; p = 0.057 and $\rho$ = −0.604; p = 0.008, respectively) (Table 2). TEWL exhibited a stronger correlation with clinical skin hydration than conductance (Figures 1A, 1B). Subjective skin firmness score demonstrated a weak positive trend with Cutometer‐derived gross elasticity (R2) ($\rho$ = 0.135, p = 0.593), but did not show significant correlations with Young's modulus ($\rho$ = −0.022) or dermal thickness ($\rho$ = 0.127). (Table 2). Regarding skin color, the extent of melanin demonstrated a statistically significant and strong positive correlation with the quantitative melanin index (Spearman's $\rho$ = 0.612, p = 0.007). Regarding vascular and mechanical interactions, the clinically assessed erythema severity score demonstrated a robust positive correlation with the objective colorimetric erythema index (Spearman's $\rho$ = 0.638, p = 0.004). Furthermore, a higher clinical erythema severity score (intense redness) was significantly associated with a higher ultrasonic dermal thickness ($\rho$ = 0.781, p = 0.0002) and a significantly lower Young's modulus ($\rho$ = −0.614, p = 0.007)

TABLE 2.

Correlation coefficients between subjective evaluation and quantitative biophysical properties.

	Skin biophysical porperties (Objective)
Clinical Evaluation (Subjective)	Conductance	TEWL	R2	Young's modulus	Dermal thickness	Melanin	Erythema
Hydration	0.456	−0.604 *	0.107	−0.333	0.291	0.287	−0.195
Firmness	0.122	−0.343	0.135	−0.022	0.127	0.317	0.160
Melanin	−0.064	−0.112	0.112	0.270	−0.237	0.612 **	−0.183
Erythema	0.480	0.118	−0.121	−0.614 **	0.781 **	0.281	0.638 **

Abbreviation: TEWL, Transepidermal Water Loss

^* p < 0.05.

^** p < 0.01.

FIGURE 1.

Scatter plots demonstrating Spearman's rank correlations (ρ) between subjective clinical severity scores and objective skin biophysical properties. (A) Clinically assessed hydration score versus objective conductance (B) Clinically assessed hydration score versus objective transepidermal water loss (TEWL) (C) Clinically assessed melanin severity score versus objectively assessed melanin index (D) Clinically assessed erythema severity score versus objective Young's modulus

4. Discussion

In the development of personalized treatment strategies for cosmetic procedures, skin properties such as dryness, firmness, and color (melanin and erythema) are frequently considered and clinically evaluated by physicians. In clinical practice, skin dryness is assessed using tools such as the ODS, which evaluates roughness, inflammation, large scales, and cracks [14]. Skin firmness requires a comprehensive evaluation based on multiple criteria, including wrinkle severity (Fitzpatrick wrinkle type), firmness ratings of specific facial regions (e.g., eyelid folds and nasojugal folds), and pore size and morphology [15, 16, 17]. Among skin color parameters, melanin levels are typically classified using the Fitzpatrick skin type, whereas erythema is assessed using subjective grading systems such as the Clinician Erythema Assessment [13, 18]. However, little research has been conducted on the correlation between these clinical assessment tools and skin biophysical parameters. In this study, we aimed to elucidate the relationships of comprehensive subjective assessments of dryness, firmness, and skin color with objective skin biophysical properties.

In our study, a higher clinically assessed hydration score was associated with superior skin barrier profiles, as demonstrated by a significant positive correlation with objective conductance and a significant inverse correlation with TEWL (Table 2). By establishing a unified scaling system where higher subjective ratings indicate an optimal hydration status (i.e., absent scaling and roughness), the statistical alignment with greater surface conductance and diminished water vapor evaporation remains physically and physiologically coherent. These results are consistent with those of previous studies in which correlations were examined for Japanese Overall Dry Skin Score with stratum corneum hydration and TEWL in the leg and forearm [14]. Notably, clinical skin hydration exhibited a stronger correlation with conductance than with TEWL, suggesting that subjective assessments primarily reflect stratum corneum hydration levels, such as the presence of scales and cracks [19]. Therefore, clinical evaluation including scales, roughness, inflammation, and cracks can sufficiently evaluate skin hydration. However, the relatively low correlation coefficient—consistent with previous reports—still indicates that assessment of skin barrier integrity is best supported by complementary quantitative measurements rather than subjective evaluation alone [14, 19].

Among subjective skin conditions, skin color is the most clinically intuitive. In our study, the clinical evaluation of skin color demonstrated statistically significant correlations with the objective measurements (Table 2). The strong correlations may stem from widespread physician training in commonly used classifications such as the Fitzpatrick skin type. Nevertheless, objective colorimeter‐based measurements remain necessary because the Fitzpatrick skin‐type classification has notable limitations. Certain investigators have criticized the Fitzpatrick skin type because it reportedly correlates poorly with constitutive skin color and minimal erythema dose values. Therefore, a colorimeter should be used as an adjunctive tool to subjective assessment in measuring the skin color [20].

The minor variance observed between visual clinical redness assessments and objective colorimetric erythema indexes ($\rho$ = 0.638, p = 0.004) is highly attributable to epidermal optical filtering effects, rather than investigator bias. In narrow‐band reflectance spectrophotometry utilized by commercial skin colorimeters, epidermal melanin functions as a powerful competitive optical absorber that screens both green and red light. In Asian skin types (predominantly Fitzpatrick types III and IV in our cohort) characterized by higher baseline epidermal melanin concentrations, this optical attenuation can physically mask or distort the remitted light fraction from the underlying dermal hemoglobin flux. This optical crossover effect confounds the human eye's ability to isolate pure vascular erythema from overlapping hyperpigmentation, accounting for the minor divergence between instrumental colorimetry and visual clinical ratings [21].

The enhancement of skin firmness through tightening procedures is fundamental in skin rejuvenation. Interestingly, our study revealed minimal correlations between clinical elasticity evaluations and parameters such as R2 values, dermal thickness, and Young's modulus (Table 2). In existing cosmetic procedures, clinicians often use subjective assessment tools such as the Global Aesthetic Improvement Scale and numerical values derived from cutometer measurements to evaluate treatment outcomes, but their correlations with objective parameters remain poorly studied [3, 6]. Although photograph‐based evaluation methods such as Moiré topography have exhibited strong correlations with cutometer readings, their clinical applicability is limited. In young women, reduction of skin elasticity is often assessed through changes in wrinkles, pore size, and quantity; however, these features may not exhibit pronounced clinical changes, complicating evaluation [22]. Given the rising demand for early preventative treatments among younger individuals, depending solely on clinical assessments may hinder the identification or mislead treatment to patients. This highlights the necessity to incorporate objective quantitative measurements into assessments of elasticity and baseline firmness.

To address this issue, we included Young's modulus, a parameter not widely used in previous studies, to evaluate skin tightening. The lack of a statistically significant correlation between Young's modulus and R2 values suggests its potential as a novel metric to assess elasticity and treatment‐induced improvements [23]. Furthermore, emerging studies have indicated that factors such as age and hydration influence Young's modulus of the skin, which may aid in the development of predictive models for age‐related changes [24]. Given the inverse relationship between dermal hydration and Young's modulus in this study, we propose the development of a water distribution model to quantitatively describe and compare the effects of skin boosters. Future research should be conducted to develop such a model and explore its applicability in the evaluation of treatment efficacy.

A highly notable and pathophysiologically significant finding in our study was the powerful correlation between the clinical erythema severity score and structural dermal mechanics, demonstrating a robust positive correlation with ultrasonic dermal thickness ($\rho$ = 0.781, p = 0.0002) and a strong inverse correlation with Young's modulus ($\rho$ = −0.614, p = 0.007). Rather than a statistical anomaly, this specific coupling provides compelling evidence of subclinical inflammatory dermal edema occurring even within a young demographic. Persistent capillary expansion and microvascular pooling—which clinically manifest as facial redness—induce chronic, low‐grade inflammatory signaling. This inflammatory burden increases endothelial permeability, promoting the shifting of intravascular fluid into the interstitial spaces of the papillary and upper reticular dermis. This localized fluid entrapment physically expands the dermal volume, directly resulting in an increased dermal thickness captured via high‐resolution cutaneous ultrasound [25]. Mechanically, however, this interstitial fluid accumulation induces a swelling‐induced detachment or “loosening” of the tightly packed collagen‐elastin solid matrix. When subjected to suction‐induced negative pressure via the Cutometer, this fluid‐laden tissue exhibits decreased structural resistance to deformation, causing the mathematical plate‐deflection model to register a significant drop in material rigidity (reflected as a lower Young's modulus). This highlights that active vascular inflammatory states can profoundly mask or distort baseline structural mechanics, implying that calming vascular reactivity may be a prerequisite for accurate structural matrix tracking in clinical practice.

This study was a pilot investigation designed to explore the potential of an objective evaluation tool to complement subjective assessment of facial skin quality in clinical settings. However, its limitations include a small sample (only 20 participants), which might have introduced selection bias. Furthermore, the narrow age range, predominance of younger individuals, and exclusive participation of females might have restricted the generalizability of the results. Since all clinical and objective measurements were done by two independent physicians respectively, it is impossible to confirm inter‐rater reliability. Future study including larger and comprehensive cohort would be necessary.

With the accumulation of objective data, it becomes feasible to compare the efficacy of different skin boosters and energy‐based devices, as well as to develop predictive models of treatment outcomes [7, 26]. In future research, we plan to construct a water‐retention model to elucidate how skin boosters such as polynucleotides and hyaluronic acid indirectly reduce trans‐epidermal water loss. We also aim to create algorithms that predict skin age and treatment efficacy by integrating multiple biophysical parameters through artificial intelligence. These prospective studies are expected to enhance diagnostic accuracy and facilitate the design of personalized treatment strategies in primary care settings.

In conclusion, in this study, we evaluated the correlation between clinical manifestations and objectively measured biophysical properties of the skin. Clinical hydration was positively correlated with conductance and negatively correlated with TEWL. The clinically assessed melanin severity score was significantly and positively correlated with the quantitative melanin index ($\rho$ = 0.612, p < 0.01). Furthermore, unlike the preliminary linear evaluation, the subjective erythema severity score demonstrated a robust positive correlation with the objective colorimetric erythema index ($\rho$ = 0.638, p < 0.01), while revealing significant interactions with dermal thickness ($\rho$ = 0.781) and Young's modulus ($\rho$ = −0.614). Clinically determined skin elasticity was not significantly correlated with R2 (gross elasticity), Young's modulus, or dermal thickness. This suggests that clinical evaluation alone may be insufficient to establish treatment strategies for skin tightening. Quantitative data may serve as valuable adjunctive diagnostic tools for skin rejuvenation. Future studies should be focused on the development of predictive tools based on skin biophysical properties to assess improvements in hydration, firmness, and pigmentation, ultimately constructing a model to determine treatment suitability.

Ethics Statements

This study was conducted in accordance with the ethical standards of the 1975 Declaration of Helsinki (as amended in 2013). The study protocol was formally approved by the V&CO Institutional Review Board (Seoul, South Korea; IRB Registration No. 1‐70094470‐B‐N‐01; Approval No. VNCO_2023_06_01; Approved on December 16, 2024). Written informed consent was obtained from all individual participants prior to study enrollment.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.