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Table 14 Simple and multiple regressions with demographic variables as predictors of losses scores on the AARC-50 cognitive functioning subscale

From: International relevance of two measures of awareness of age-related change (AARC)

(N = 8639)

Demographic variables as predictors of AARC losses: Simple regressions

Demographic variables as predictors of AARC losses: Multiple regressions

 

AARC-50 cognitive functioning losses

Variables

Coeff.

[95% CI]

p-value

Standardized Coeff.

Coeff.

[95% CI]

p-value

Standardized Coeff.

Age

.08

[.07, .09]

< .001

.17

.07

[.05, .08]

< .001

.13

Sex

−.88

[−1.06, −.70]

< .001

−.11

−.76

[−.95, −.58]

< .001

−.09

Marital status

−.33

[−.51, −.14]

< .001

−.04

−.17

[−.36, .03]

.09

−.02

Employment

−.84

[−.99, −.69]

< .001

−.12

−.24

[−.43, −.06]

.01

−.03

University education

−.47

[−.64, −.30]

< .001

−.06

−.41

[−.59, −.24]

< .001

−.05

Total R2

 

.04

Adjusted R2

 

.04

Model F-test

 

70.07 (5, 8633); p < .001

  1. Note: In the regression models we included only those participants that have no missing data. AARC-50 cognitive functioning losses = Subscale of the AARC 50-item questionnaire assessing losses in the cognitive functioning domains. Marital status was operationalized as a dichotomous variable capturing whether the participant is married/ civil partnership/ co-habiting or widowed/ separated/ divorced/ single. Employment was operationalized as a dichotomous variable capturing whether the participant is working or not. University education was operationalized as a dichotomous variable.. Standardized beta coefficients are calculated by subtracting the mean from the variable and dividing it by its standard deviation