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Jung and Kim: FACTORS AFFECTING PATIENTS’DECISION-MAKING FOR DENTAL PROSTHETIC TREATMENT
ORIGINAL ARTICLE

J Korean Acad Prosthodont 2008;46(6):610-619.

Published online: 18 December 2008

DOI: https://doi.org/10.4047/jkap.2008.46.6.610

FACTORS AFFECTING PATIENTS’DECISION-MAKING FOR DENTAL PROSTHETIC TREATMENT

Hyo Kyung Jung, PhD1, Han Gon Kim, PhD2, ∗

1Professor, Department of Dental Technology, Daegu Health College

2Professor, Department of Sociology, Yeungnam University

Corresponding Author: Han Gon Kim Deaprtment of Sociology, College of Liberal Arts, Yeungnam University 214 Daedong, Gyongsan, 712-749, Korea +82 53 810 2255: e-mail, hgkim@yu.ac.kr

Received 28 October 20083 December 2008       Accepted 4 December 2008

Copyright © 2008 The Korean Academy of Prosthodontics

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

STATEMENT OF PROBLEM

Factors affecting patients'decision-making for dental prosthetic treatment should be examined in terms of understanding improving patients'oral health.

PURPOSE

The main purpose of this dissertation was to investigate patients'dental prosthetic treatment and factors affecting patients'decision-making for dental prosthesis treatment in Deagu and Gyungbook areas.

MATERIAL AND METHODS

This study was based on the preliminary survey of dental patients conducted from July 1 to August 31 in 2006. A total of 700 questionnaires had been distributed and 640 were collected. 629 questionnaires were used for the statistical analysis. Descriptive and inferential statistics, such as frequencies, cross tabulation analysis, correlation analysis, logistic regression analysis, and multiple regression analysis were introduced. In the multiple regression analysis and logistic regression analysis, twenty-two independent variables were employed to explore the factors which have impacts on decision-making and satisfaction.

RESULTS

The results of this dissertation are as follows: Logistic regression analysis turned out that monthly income, age, degree of expectation, marital status, and employer-insured policy of national insurance statistically increased the odds of decision-making of dental prosthesis treatment. But educational attainment decreased the odds ratio of the decision-making of dental prosthesis treatment. However, the rest independent variables do not have statistically significant impacts on the decision-making of dental prosthesis treatment

CONCLUSION

Among independent variables, marital status had the most significant influence on the decision making of dental prosthesis treatment. Finally, suggestions for the future study and policy implications to improve satisfaction of the patients’ dental prosthetic treatment were discussed.

Keywords: Dental prosthetic treatment, Decision-making, Logistic regression analysis

REFERENCES

1.Kim MA. A study on the Patient Satisfaction of Dental Outpatients of University Hospital. MA thesis, Graduate School of Environmental Studies, Youngnam University,. 2002.
2.Kim JS. Status of Dental Prosthetic Treatment in a Few Areas of Korea and Analysis of Related Factors. PhD thesis, Geimyoung University,. 2004.
3.Kim BO. Periodontology. Daehan Nara publishing;2004.
4.Sin SH. The Degree of Dental Caries and Related Factors in Children of an Elementary School. PhD thesis, Kyoungpook Univerisity,. 1989.
5.Lee HS. Object of Oral Health Education in School and Development of the Curriculum model. PhD thesis, Kyoung Nam University,. 2000.
6.Chang KY., Song GB., Lee CH., Cho GH. An Analysis on Dental Patients' Attitude and Satisfaction of the Treatment in Department of Prosthodontics, Kyoungpook University. Kor Acad Dent Health,. 1997. 21:605–20.
7.Choi WJ. Contemporary Public Oral Health,. Myoungmoon Publishing;2003.
8.Ivancevich JM. Stress and Work AM;. Foresman and Company;1980.

Fig. 1.
Hypothetic research model about factors affecting decision-making of dental prosthetic treatment.
jkap-46-610f1.tif
Table I.
General characteristics of respondents N = 629
Characteristics Category Number (N) Percentage (%)
Gender Male 254 40.6
Female 372 59.4
Age - 29 240 39.1
30 - 39 108 17.6
40 - 49 145 23.6
50 - 59 82 13.3
60 - 69 28 4.6
70 - 11 1.8
Marital status Unmarried 250 41.1
Married 344 56.6
Divorce, lost spouse 14 2.3
Education < Middle school education 87 14.1
High school graduate 211 34.3
Community college graduate 156 25.3
College or more 162 26.3
Occupation Professionals 149 24.4
Office workers 62 10.2
Service, sales person 107 17.5
Students 102 16.7
Housewives 129 21.1
Peasant, technician 28 4.6
Laborer 16 2.6
Other 17 2.8
Monthly incomes (KRW) < \ 990,000 85 14
\ 1,000,000 - 1,990,000 217 35.6
\ 2,000,000 - 2,990,000 174 28.6
\ 3,000,000 - 3,990,000 69 11.3
\ 4,000,000 - 4,990,000 35 5.7
> \ 5,000,000 29 4.8
Table II.
Cross tabulation analysis between sex and decision-making of prosthetic treatment
Decision-making of prosthetic treatment Sex
Male N (%) Female N (%)
Opted to get treatment 176 (71.0) 284(78.2)
Opted not to get treatment 72 (29.0) 79(21.8)
Total 242 (100.0) 363(100.0)
χ2 = 4.184 df = 1 P = .041
Table III.
Cross tabulation analysis between age and prosthetic treatment
Decision-making of prosthetic treatment Age
< 30 N (%) 30 s N (%) 40 s N (%) > 50 N (%)
Opted to get treatment 206 (83.4) 80 (74.8) 93 (67.6) 79 (68.1)
Opted not to get treatment 41 (16.6) 27 (25.2) 46 (32.4) 37 (31.9)
Total 247 (100.0) 107 (100.0) 142 (100.0) 116 (100.0)
χ2 = 16.493 df = 3 P = .001
Table IV.
Cross tabulation analysis between marital status and decsion-making of prosthetic treatment
Decision-making of prosthetic treatment Marital status
Unmarried N (%) Married N (%)
Opted to get treatment 212 (81.5) 237 (71.0)
Opted not to get treatment 48 (18.5) 97 (29.0)
Total 260 (100.0) 334 (100.0)
χ2 = 8.869 df= 1 P = .003
Table V.
Cross tabulation analysis between education and decision making of prosthetic treatment
Decision-making of prosthetic treatment Education
< middle school N (%) < High < school N (%) community school N (%) > college graduate N (%)
Opted to get treatment 48 (56.5) 155(76.0) 113(72.9) 138 (86.8)
Opted not to get treatment 37 (43.5) 49(24.0) 42(27.1) 21 (13.2)
Total 85 (100.0) 204(100.0) 155(100.0) 159 (100.0)
χ2= 28.016 df = 3 P = .000
Table VI.
Cross tabulation analysis between monthly income and decision-making of prosthetic treatment
Decision-making of prosthetic treatment Monthly incomes (KRW)
< 1,990,000 2 N (%) 2,000,0000 - 3,990,000 N (%) > 4,000,000 N (%)
Opted to get treatment 208 (70.5) 124 (73.4) 88 (86.3)
Opted not to get treatment 87 (29.5) 45 (26.6) 14 (13.7)
Total 295 (100.0) 169 (100.0) 102 (100.0)
χ2 = 9.930 df = 2 P = .007
Table VII.
Cross tabulation analysis between expectation and decision-making of prosthetic treatment
Decision-making of prosthetic treatment Degree of expectation
Low N (%) Middle N (%) High N (%)
Opted to get treatment 17 (42.5) 160 (67.8) 265 (76.6)
Opted not to get treatment 23 (57.5) 76 (32.2) 81 (23.4)
Total 40 (100.0) 236 (100.0) 346 (100.0)
χ2 = 22.233 df = 2 P = .000
Table VIII.
Cross tabulation analysis of financial status and decision-making of prosthetic treatment
Decision-making of prosthetic treatment Financial burden
None N (%) A little bit N (%) Much N (%)
Opted to get treatment 25 (67.6) 64 (61.5) 354 (73.4)
Opted not to get treatment 12 (32.4) 40 (38.5) 128 (26.6)
Total 37 (100.0) 104 (100.0) 482 (100.0)
χ2 = 6.142 df = 2 P = .046
Table IX.
Logistic regression analysis of factors affecting decision-making of dental prosthetic treatment
Characteristics b S.E. Wald Sig Exp (B)
Income 0.249 0.08 9.735 0.002∗∗ 1.282
Age 0.05 0.011 19.13 0.000∗∗∗ 1.051
Sex (male = 1, female = 0) 0.061 0.2 0.094 0.759 1.063
Education -0.09 0.043 4.451 0.035∗ 0.914
Marital status 0.801 0.279 8.227 0.004∗∗ 2.228
(Married = 1, Unmarried = 0)
Health status -0.07 0.119 0.339 0.56 0.933
Expectation 0.272 0.129 4.443 0.035∗ 1.312
Dental insurance coverage 0.353 0.2 3.128 0.077 1.424
(employer covered = 1, other = 0)          
Financial status 0.155 0.119 1.687 0.194 1.168
Selection factor 0.003 0.01 0.072 0.789 1.003
Constant -3.939 1.277 9.517 0.002∗∗ 0.019

∗ P < .05

∗∗ P < .01

∗∗∗ P < .001

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