메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
저널정보
한국치위생학회 한국치위생학회지 한국치위생학회지 제15권 제1호
발행연도
2015.1
수록면
31 - 38 (8page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Objectives: The purpose of this study is to investigate the factors of oral health beliefs on scaling performance by national healthinsurance coverage in consumers. Methods: The subjects were 353 people living in Seoul, Incheon, and Gyeonggi-do from September 25 to October 20, 2013. Theyfilled out the self-reported questionnaire after receiving informed consents. The questionnaire included 6 questions of generalcharacteristics, 6 questions of oral health behavior, 6 questions of health insurance coverage, and 1 question of subjective oral healthrecognition. The oral health belief consisted of 6 questions of seriousness, 6 questions of susceptibility, 8 questions of barriers, 5questions of benefit, and 3 questions of self-efficacy measure by Likert 5 scale. Cronbach’s alpha in the study was 0.759. Data wereanalyzed using SPSS version 20.0 for frequency analysis, t-test, ANOVA, post-hoc Scheffe test, Pearson’s correlation coefficient,and binary logistic regression. Results: The influencing factors of oral health belief model were Seriousness(=0.091), Self efficacy(=-0.471) and age(=0.855)(p<0.05). Those who had highly perceived seriousness and younger age tended to have probability of scaling performance. Higherself-efficacy tended to take more chance to have scaling performance probability. Conclusions: In order to cover the scaling by national health insurance, it is very important to notice the benefit of health insurancecoverage of scaling to the consumers. National health insurance coverage enables the scaling practice to be easily accessible to thepeople. Easy access to scaling by low cost strategy can improve the oral health behavior.

목차

등록된 정보가 없습니다.

참고문헌 (22)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0