Table 6.
Dependent variable | Predictors | Unstand Co | Stand Co | t | Sig | 95% CI for B | ||
---|---|---|---|---|---|---|---|---|
B | Std. error | Beta | Lower bound | Upper bound | ||||
OHIP before R2 = .911 | (Constant) | − 15.102 | 17.106 | – | − .883 | .418 | − 59.074 | 28.870 |
Age | − 1.000 | .453 | − 1.290 | − 2.210 | .078 | − 2.164 | .163 | |
Education level | 7.643 | 4.442 | .887 | 1.721 | .146 | − 3.775 | 19.060 | |
Marital status | 21.453 | 7.673 | 1.449 | 2.796 | .038 | 1.730 | 41.177 | |
Smoking | 7.288 | 3.261 | .534 | 2.235 | .076 | − 1.095 | 15.672 | |
Incisor class | − 4.034 | 3.592 | − .455 | − 1.123 | .312 | − 13.268 | 5.200 | |
Molar class | 4.265 | 9.073 | .457 | .470 | .658 | − 19.059 | 27.588 | |
Skeletal class | − 4.135 | 9.413 | − .452 | − .439 | .679 | − 28.332 | 20.061 | |
Overbite | − 3.781 | 3.173 | − .504 | − 1.192 | .287 | − 11.937 | 4.375 | |
Overjet | 3.947 | 3.554 | .533 | 1.111 | .317 | − 5.190 | 13.085 | |
Cross bite | 4.094 | 11.004 | .227 | .372 | .725 | − 24.193 | 32.380 | |
Scissor bite | − 10.207 | 12.647 | − .502 | − .807 | .456 | − 42.717 | 22.304 | |
Extraction | 4.629 | 3.039 | .324 | 1.523 | .188 | − 3.184 | 12.442 | |
Crowding/Spacing | 6.347 | 2.445 | .716 | 2.595 | .049 | .060 | 12.633 | |
N Before | − 3.667 | 2.107 | − .521 | − 1.740 | .142 | − 9.083 | 1.750 | |
E Before | 4.053 | 2.895 | .468 | 1.400 | .220 | − 3.390 | 11.496 | |
O Before | 5.235 | 2.012 | .632 | 2.601 | .048 | .062 | 10.407 | |
A Before | − 5.772 | 4.198 | − .630 | − 1.375 | .228 | − 16.563 | 5.018 | |
C Before | − .112 | 2.125 | − .014 | − .053 | .960 | − 5.574 | 5.349 | |
OHIP after R2 = .959 | (Constant) | − 84.641 | 17.105 | − 4.948 | .004 | − 128.612 | − 40.671 | |
Age | .119 | .257 | .113 | .461 | .664 | − .543 | .780 | |
Education level | 9.087 | 2.624 | .781 | 3.464 | .018 | 2.343 | 15.832 | |
Marital status | − 27.299 | 6.649 | − 1.367 | − 4.106 | .009 | − 44.391 | − 10.207 | |
Smoking | 7.145 | 2.777 | .388 | 2.573 | .050 | .007 | 14.284 | |
Incisor class | 19.584 | 3.505 | 1.638 | 5.587 | .003 | 10.573 | 28.594 | |
Molar class | 37.958 | 9.481 | 3.017 | 4.003 | .010 | 13.586 | 62.331 | |
Skeletal class | − 49.067 | 8.924 | − 3.971 | − 5.499 | .003 | − 72.007 | − 26.128 | |
Overbite | 14.202 | 3.806 | 1.404 | 3.732 | .014 | 4.419 | 23.984 | |
Overjet | − 12.780 | 3.816 | − 1.280 | − 3.349 | .020 | − 22.589 | − 2.971 | |
Cross bite | − 5.932 | 8.916 | − .243 | − .665 | .535 | − 28.851 | 16.987 | |
Scissor bite | 47.545 | 10.914 | 1.732 | 4.356 | .007 | 19.489 | 75.601 | |
Extraction | − 12.616 | 3.481 | − .655 | − 3.624 | .015 | − 21.565 | − 3.668 | |
Crowding/spacing | − 8.813 | 2.203 | − .737 | − 4.001 | .010 | − 14.476 | − 3.150 | |
N After | − 3.328 | 2.074 | − .298 | − 1.605 | .169 | − 8.658 | 2.003 | |
E After | − 8.224 | 2.482 | − .761 | − 3.313 | .021 | − 14.605 | − 1.843 | |
O After | 21.795 | 4.302 | 1.694 | 5.067 | .004 | 10.737 | 32.853 | |
A After | − 3.771 | 1.807 | − .315 | − 2.087 | .091 | − 8.416 | .874 | |
C After | 10.293 | 2.138 | 1.008 | 4.813 | .005 | 4.796 | 15.790 |
OHIP = Oral Health Impact Profile scores, R2 = Coefficient of determination, Before = Before treatment, After = After treatment, N = Neuroticism, E = Extraversion, O = Openness, A = Agreeableness, C = Conscientiousness, Unstand Co = Unstandardized coefficient, Stand Co = Standardized coefficient, B = Beta statistics, Std. Error = Standard Error, t = t statistics, Sig = Significance of probability (P value), CI = Confidence intervals. During the hierarchical multiple regression analysis, gender, age, education level, marital status, smoking, incisor class, canine class, molar class, skeletal class, overbite, overjet, cross bite, scissor bite, extraction, and crowding/spacing variables were included in the first block of independent variables and the neuroticism, extraversion, openness, agreeableness, and conscientiousness NEO-FFI dimension scores were included in the second block of independent variables to account for the confounding effects of first block variables on the contribution of NEO-FFI scores towards the OHIP scores (i.e. ability of NEO-FFI scores to predict OHIP scores).