본 논문은 우선 문헌고찰을 통해 그간 심혈관 질환(CHD: coronary heart disease)의 성격적 위험인자로 지목되어 오던 A형 성격 및 D형 성격에 대하여 비일관된 연구 결과들이 도출된 원인 중의 하나를 생리적 지표에 대한 측정방법들 간의 이질성이나 타당성의 문제에 기인할 수 있다고 가정하였다. 이에 심혈관 질환과 밀접한 관련이 있는 생리적 지표인 혈압측정 방법의 차이에 의해 각 집단(A형, D형, 정상집단)이 구별될 수 있는지 알아보고자 하였다. 이를 위해 148명의 남녀 대학생(남자 45%)을 대상으로 사전에 A형 성격(MMPI-2의 TPA척도)과 D형 성격(DS14) 경향을 측정하는 자기보고형 설문지를 실시하여 A형 D형, 그리고 정상집단으로 구분한 후 혈압이 측정되었다. 먼저 전통적인 혈압측정방법에 의한 혈압수치(수축기/이완기 혈압)를 통해 각 집단이 구분될 수 있는지 살펴본 결과 집단별로 유의한 차이가 나타나지 않았다. 다음 단계로, 측정된 혈압 자료에 대한 패턴분석 방법을 적용했을 때, A형과 D형 성격이 정상인들과 얼마나 잘 구별될 수 있는지 알아보았다. 측정된 혈압 자료는 컴퓨터에 입력되어 커프 압력을 통해 측정된 혈압의 진동패턴은 먼저 정규화 시키고, 이 정규화 된 개인의 혈압 패턴은 국소 퓨리에 변환(STFT)을 사용하여 세 성격 유형간의 시간영역대별 주파수 변이에 대한 특징을 추출한 후 선형판별 분석(LDA)을 통해 분석해 보았다. 그 결과 세 집단을 구별할 수 있는 인식률은 88.8%로 상당히 높은 수준을 보였다. 이러한 결과는 A형 혹은 D형 성격과 심혈관 질환과의 관계에 대한 연구 결과는 심장활동을 충실히 반영하는 다양한 측정 지표나 그 분석방법의 차이에 의해 달라질 수 있으며, 특히 수축기와 이완기 이외의 혈압 진동패턴을 고려하는 것이 더 타당한 방법일 수 있다는 점을 시사하며, 향후 이러한 방법에 의해 심혈관 질환 위험 성격의 구성개념에 대한 새로운 측면에서의 탐색가능성을 제시했다는 의의를 지닌다.
The objective of this study was to test the validity of two different measuring methods of discriminating between type A and type D, which were known as the psychological risk factors for coronary heart disease(CHD), from that of normal people. Before measuring blood pressure, 148 college students(male 45%) participated and were classified as type A , B, and the normal group using the TPA scale of MMPI-2 and DS14. The first analysis was conducted with the data of systolic and diastoloic blood pressure, and we found no significant differences between these three groups. Next, a newly developed analyzing method was applied to the qualitative data of the blood pressure wave to examine the possibility of discriminating between a CHD-prone personality group and those of persons in the normal group. For this analysis, the blood pressure wave was measured with a computer program through cuff pressure. Then, the pressure wave patterns were normalized and transformed by STFT(short-time Fourier transformation). Finally, the wave features of the three groups were extracted from the STFT data, and then was analyzed by using LDA(linear discriminant analysis). The recognition rate was 88.8%, which represents a fairy robust result. The results of our analysis showed the utility of qualitative data of heart functions. Our study also suggests that the relationship between a CHD-prone personality and CHD could be varied by the different aspects of biological features or analyzing method for measuring heart functions.
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