Chracteristic Analysis and Cut-off Values of the Pediatric Weakness Scale for Diagnosing Weak Children

국문 초록 (Abstract)

배경
이학적 검사에서 이상을 발견할 수 없지만 다른 아이보다 자주 잔병치레하고, 잘 피로를 느끼고, 식욕이 없는 아이들이 있다. 한의학에서는 이를 ‘허약아’의 범주로 진단하고 치료하지만, 진단과 평가를 위한 도구가 부족한 실정이다. 소아 허약 검사(Pediatric Weakness Scale, PWS)는 소아의 허약을 평가하기 위한 설문지로 타당도가 검증되어 있으나 절단값이 산정되어 있지 않다. 본 연구는 타당도가 검증된 PWS의 절단값을 산정하는 것을 목표로 하여, 허약아를 더 쉽게 진단할 수 있도록 할 것이다.

방법
6 – 9세의 자녀를 둔 보호자를 대상으로 PWS, 다차원 피로척도(MFS), 한국판 아동 청소년 행동평가척도(K-CBCL), 한국어판 아동식습관 설문지(K-CBEQ), 자녀의 성장 지표, 최근 호흡기 감염의 빈도와 평균 이환일수 등이 포함된 설문조사를 시행했다. PWS 하위척도별로 평균 점수와 백분위수(10th, 25th, 50th, 75th, 90th)를 산출하였으며, PWS와 다른 설문지 간의 관계를 분석하기 위해 Pearson 상관분석을 수행하였다. 장부별로 허약지수의 Received Operating Characteristic (ROC) curve를 산출하여, Area Under the Curve (AUC)가 최대가 되는 점을 절단값으로 산정하였다.

결과
총 326명의 부모가 연구에 참여하였다. PWS 중 간장의 허약지수는 MFS, 심장의 허약지수는 K-CBCL, 비장의 허약지수는 K-CEBQ, 폐장의 허약지수는 호흡기 감염의 빈도와 이환 기간, 신장의 허약지수는 출생 시 체중, 신장 및 체중 백분위수와 유의미한 상관관계를 보였다. 각 PWS 하위척도의 백분위수 분석 결과, 오장별로 차이를 보였으나 대략 3–5점은 50 백분위수, 6–8은 75 백분위수, 9–11은 90 백분위수에 해당하였다. 허약아 진단을 위한 절단값은 간계허약아 4.50점, 심계허약아 7.50점, 비계허약아 4.50점, 폐계허약아 4.50점, 신계허약아 4.50점으로 산출되었다.

결론
본 연구에서 도출된 PWS 절단값은 소아 허약을 진단하고 평가하는 데 있어 유용한 기준을 제공한다.

다국어 초록 (Multilingual Abstract)

Background
Despite showing no abnormalities on medical examinations, few children frequently suffer from minor illnesses, experience fatigue, and have reduced appetite. In traditional Korean medicine (TKM), these children are recognized as having weaknesses and treated accordingly. However, standardized diagnostic tools for assessing pediatric weakness are lacking. The Pediatric Weakness Scale (PWS) is a validated questionnaire for evaluating this condition; however, cutoff values for its subscales have not yet been established. This study aimed to develop validated cutoff values for PWS to aid in the diagnosis of weakness in children.

Methods
Parents of children aged 6–9 years completed surveys measuring the PWS, Multidimensional Fatigue Scale (MFS), Korean Child Behavior Checklist (K-CBCL), Korean version of the Children’s Eating Behavior Questionnaire (K-CEBQ), growth indices, frequency and average duration of respiratory infections. For each PWS subscale, the mean scores and percentiles (10th, 25th, 50th, 75th, and 90th) were calculated. Pearson’s correlation analysis was performed to analyze the relationships between the PWS subscales and other surveys. Receiver operating characteristic curves were generated for each PWS subscale within five visceral categories (liver, heart, spleen, lungs, and kidneys), and the optimal cutoff points were determined based on the highest area under the curve.

Results
A total of 326 parents representing their children participated in the study. The following PWS subscales showed significant correlations: liver weakness index with MFS, heart weakness index with K-CBCL, spleen weakness index with K-CEBQ, lung weakness index with respiratory infection frequency and duration, and kidney weakness index with birth weight, height, weight percentiles. Percentile analysis of each PWS subscale showed that scores of approximately 3–5, 6-8, and 9-11 corresponded to the 50th, 75th, and 90th percentiles, respectively, with slight variations across the five visceral systems. The cut- off values for diagnosing weakness were determined as 4.50 for the liver, 7.50 for the heart, 4.50 for the spleen, 4.50 for the lung, and 4.50 for the kidney.

Conclusions
The cutoff values derived in this study provide a practical tool diagnosing and evaluating pediatric weakness. Keywords Pediatric, Diagnosis, Deficiency, Questionnaire, ROC Curve, Pediatric Weakness Scale

목차 (Table of Contents)

• Abstract ⅲ
• I. Introduction 1
• II. Materials and Methods 3
• 1. Study design and ethical considerations 3
• 2. Study participants 4
• 3. Survey design 5
• 4. Definition of children with weakness 7
• 5. Statistical analysis 8
• III. Results 9
• 1. Demographic characteristics 9
• 2. Reliability and correlation coefficients among PWS subscales 11
• 3. Mean scores and SDs for each subscale and individual items of the PWS 13
• 4. Percentile distribution of PWS total score and subscales 16
• 5. Correlation coefficients in the PWS and survey data 18
• 6. Optimal cutoff value 28
• IV. Discussion 30
• V. Acknowledgment 36
• References 37
• Korean Abstract 40