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Table 13 Simple and multiple regressions with demographic variables as predictors of gains 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 gains: Simple regressions Demographic variables as predictors of AARC gains: Multiple regression
  AARC-50 cognitive functioning gains
Variables Coeff. [95% CI] p-value Standardized Coeff. Coeff. [95% CI] p-value Standardized Coeff.
Age −.06 [−.07, −.05] < .0001 −.10 −.04 [−.06, −.03] < .001 −.07
Sex 1.30 [1.08, 1.52] < .0001 .12 1.06 [.84, 1.29] < .001 .10
Marital status −.51 [−.74, −.28] < .0001 −.05 −.51 [−.75, −.28] < .001 −.05
Employment .78 [.59, .96] < .0001 .09 .41 [.18, .63] < .001 .05
University education −.63 [−.84, −.41] < .0001 −.06 −.63 [−.85, −.42] < .001 −.06
Total R2   .03
Adjusted R2   .03
Model F-test   51.36 (5, 8633); p < .001
  1. Note: In the regression models we included only those participants that have no missing data. AARC-50 cognitive functioning gains = Subscale of the AARC 50-item questionnaire assessing gains in the cognitive functioning domain. 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