Mood and cognition in healthy older European adults: the Zenith study

BMC Psychology

Table 6 Summary of hierarchical regression analyses for each of four cognitive measures as dependent variables, and socio-demographics, state and trait negative mood as predictor variables

Measure	Step	Predictor variables	R ²	∆R ²	F	p
Pattern recognition memory (ms)
	1	Socio-demographics	.094	.094	F (4, 367) = 9.53	< .001
	2	State negative mood	.095	.001	F(1, 366) = 0.52	.471
	3	Trait negative Mood mean and variability	.102	.006	F(2, 364) = 1.31	.270
Spatial working memory – total errors
	1	Socio-demographics	.039	.039	F (4, 367) = 3.72	.006
	2	State negative mood	.059	.021	F (1, 366) = 7.98	.005
	3	Trait negative Mood mean and variability	.060	.001	F(2, 364) = 0.04	.832
5-Choice reaction time (ms)
	1	Socio-demographics	.154	.154	F (4, 367) = 16.67	< .001
	2	State negative mood	.160	.006	F(1, 366) = 2.61	.107
	3	Trait negative Mood mean and variability	.163	.003	F(2, 364) = 0.82	.443
Match to sample visual search (ms)
	1	Socio-demographics	.153	.153	F (4, 367) = 16.55	< .001
	2	State negative mood	.153	.000	F(1, 366) = 0.08	.789
	3	Trait negative Mood mean and variability	.155	.002	F(2, 364) = 0.35	.708

Note. Significant increases in R ² indicated in bold. The first step in the regression analysis involved entering socio-demographic information of age in years, sex and social class, followed by state negative affect in step two, and lastly, in step three trait measures of negative mood and its variability were entered. It should be noted that each step, after step one, included the variable(s) from the previous step(s).

ISSN: 2050-7283