Descriptive statistics, cutoff scores for each test, and histograms with examples of score distributions are reported in Table 3 and Fig. 1. See Additional file 1: Table S1 for the correction grids. Data of TMT-B and TMT-B-A were excluded for 4 participants who interrupted the task (part B); the number of correct items in phonemic fluency was not available for one participant due to technical problems in saving the responses.

Histograms showing the distributions of the examples of test scores in the battery

Age influenced negatively the immediate verbatim score (β = − 0.065, SE = 0.021). Education influenced positively the immediate verbatim score (β = 0.500, SE = 0.059). Immediate paraphrase was predicted by the quadratic function of education (education: β = 0.836, SE = 0.168; education2: β = − 0.018, SE = 0.007). Age negatively predicted the performance in recall verbatim (β = − 0.104, SE = 0.021) and recall paraphrase (β = − 0.042, SE = 0.0149). Education positively predicted the performance in recall verbatim (β = 0.391, SE = 0.058) and recall paraphrase (β = 0.378, SE = 0.043).

Age negatively predicted the immediate free recall (β = − 0.0127, SE = 0.003). The immediate cued recall was positively predicted by age (β = 0.013, SE = 0.003). Notably, in cued recall, the highest scores reflect the worst performance, thus suggesting a difficulty in spontaneously recalling the items resulting in the need for the cue, i.e., the semantic category to which the item belongs, for the correct retrieval. No demographic variables influenced immediate total recall, while immediate total-weighted recall was negatively predicted by age (β = − 0.013, SE = 0.004).

Delayed free recall was negatively predicted by age (β = − 0.025, SE = 0.004) and by the cubic function of education (education: β = 0.427, SE = 0.128; education2: β = − 0.026, SE = 0.010; education3: β = 0.0001, SE = 0.0002). Age positively predicted delayed cued recall (β = 0.015, SE = 0.003). Education negatively predicted delayed cued recall (β = − 0.0311, SE = 0.009). Delayed total recall and delayed total-weighted recall were negatively predicted by age (β = − 0.011, SE = 0.002; β = − 0.036, SE = 0.006, respectively) and by the cubic function of education (education: β = 0.239, SE = 0.079, education2: β = − 0.015, SE = 0.006, education3: β = 0.0003, SE = 0.0001; education: β = 0.666, SE = 0.185, education2: β = − 0.041, SE = 0.014, education3: β = 0.001, SE = 0.0003, respectively).

Total free recall was negatively predicted by age (β = − 0.037, SE = 0.006) and by the cubic function of education (education: β = 0.528, SE = 0.181, education2: β = − 0.031, SE = 0.0134, education3: β = 0.0006, SE = 0.0003). Total cued recalled was positively predicted by age (β = 0.027, SE = 0.004) and negatively predicted by education (β = − 0.045, SE = 0.0123). Total recall was negatively predicted by age (β = − 0.012, SE = 0.003) and by the quadratic function of education (education: β = 0.084, SE = 0.036, education2: β = − 0.003, SE = 0.001). Age negatively predicted delayed total-weighted recall (β = − 0.048, SE = 0.008).

The quadratic function of age (age: β = 0.200, SE = 0.068, age2: β = − 0.002, SE = 0.0005) and the cubic function of education (education: β = 1.141, SE = 0.248, education2: β = − 0.061, SE = 0.019, education3: β = 0.001, SE = 0.0004) predicted the correct without cue score. The correct with cue score was predicted positively by age (β = 0.006, SE = 0.002) and negatively by education (β = − 0.015, SE = 0.004). An increase in the latter score indicated a worse performance, since it considers the number of cues given during the task when participants were unable to spontaneously name the pictures. The correct total score was predicted by the quadratic function of age (age: β = 0.182, SE = 0.063, age2: β = − 0.002, SE = 0.0005) and the cubic function of education (education: β = 1.095, SE = 0.231, education2: β = − 0.059, SE = 0.017, education3: β = 0.001, SE = 0.0004).

The correct score for the animal category (< 30 s) was predicted negatively by age (β = − 0.084, SE = 0.015) and was predicted positively by education (β = 0.254, SE = 0.044). Animals’ correct score (> 30 s) and animals’ total correct score (60 s) were negatively predicted by age (β = − 0.030, SE = 0.014; β = − 0.112, SE = 0.024, respectively) and by the quadratic function of education (education: β = 0.591, SE = 0.169, education2: β = − 0.014, SE = 0.007; education: β = 1.167, SE = 0.281, education2: β = − 0.027, SE = 0.011, respectively). Violations were negatively predicted by age (β = − 0.035, SE = 0.009). No demographic variables predicted the number of perseverations.

Sex (β = 1.931, SE = 0.290), age (β = − 0.050, SE = 0.012), and education (β = 0.236, SE = 0.033) impacted the vegetables’ category correct score (< 30 s): females performed better than males; performance was negatively predicted by age and positively predicted by education. Vegetables’ correct score (> 30 s) was positively predicted by education (β = 0.058, SE = 0.025) and by sex (β = 0.577, SE = 0.227), with females performing better than males. Vegetables’ total correct score (60 s) was predicted by sex (β = 2.514, SE = 0.381), age (β = − 0.055, SE = 0.015), and education (β = 0.189, SE = 0.044), similarly to vegetables’ correct score (< 30 s). Females produced more perseverations than males (β = 0.238, SE = 0.091), while no variables influenced the number of violations.

Semantic fluency total correct score (60 s) was negatively predicted by age (β = − 0.167, SE = 0.033), quadratic function of education (education: β = 1.476, SE = 0.387, education2: β = − 0.032, SE = 0.015), and sex, with females performing better than males (β = 3.071, SE = 0.808). The total number of violations was negatively predicted by age (β = − 0.034, SE = 0.012), while no demographic variables influenced the total number of perseverations.

Letter F correct score (< 30 s) was negatively predicted by age (β = − 0.064, SE = 0.011), the quadratic function of education (education: β = 0.574, SE = 0.135, education2: β = − 0.011, SE = 0.005), and sex, with females performing better than males (β = 1.034, SE = 0.282). Letter F correct score (> 30 s) and letter F total correct score (60 s) were negatively predicted by age (β = − 0.027, SE = 0.010; β = − 0.091, SE = 0.017, respectively) and positively predicted by education (β = 0.224, SE = 0.028; β = 0.517, SE = 0.048, respectively). No demographic variables influenced the number of perseverations and violations in letter F fluency.

Letter L correct score (< 30 s) was predicted negatively by age (β = − 0.043, SE = 0.011) and positively by education (β = 0.285, SE = 0.031) and sex, with females performing better than males (β = 1.058, SE = 0.266). Letter L correct score (> 30 s) was predicted negatively by age (β = − 0.025, SE = 0.009) and positively by education (β = 0.197, SE = 0.025). Age (β = − 0.068, SE = 0.016), education (β = 0.484, SE = 0.045), and sex (β = 1.427, SE = 0.394) predicted letter L total correct score (60s), similarly to letter L correct score (< 30 s). No demographic variables influenced the number of perseverations and violations in letter L fluency.

Phonemic fluency total correct score (60 s) was influenced negatively by age (β = − 0.151, SE = 0.030) and positively by the square root of education (β = 6.686, SE = 0.559). Education positively influenced the total number of perseverations in phonemic fluency (β = 0.041, SE = 0.016), while no variable influenced the total number of violations.

Performance in the copy of Benson figure was predicted by the cubic function of education (education: β = 1.124, SE = 0.230, education2: β = − 0.066, SE = 0.017, education3: β = 0.001, SE = 0.0004), while performance in the recall was negatively predicted by age (β = − 0.084, SE = 0.012) and by the quadratic function of education (education: β = 0.591, SE = 0.138, education2: β = − 0.017, SE = 0.005).

Considering the number of correct trials, females performed worse than males (β = − 0.346, SE = 0.172), and performance was negatively predicted by age (β = − 0.027, SE = 0.007) and by the quadratic function of education (education: β = 0.324, SE = 0.082, education2: β = − 0.007, SE = 0.003). Span length was predicted by the cubic function of age (age: β = − 0.605, SE = 0.251, age2: β = 0.009, SE = 0.004, age3: β = 0.00005, SE = 0.00002) and by the quadratic function of education (education: β = 0.165, SE = 0.047, education2: β = − 0.004, SE = 0.002).

The number of correct trials was predicted by the quadratic function of age (age: β = − 0.172, SE = 0.058, age2: β = 0.001, SE = 0.0004) and education (education: β = 0.331, SE = 0.077; education2: β = − 0.008, SE = 0.003), while span length was predicted by the quadratic function of age (age: β = − 0.087, SE = 0.034, age2: β = 0.0005, SE = 0.0003) and by the square root function of education (β = 0.494, SE = 0.072).

TMT-A was predicted by the cubic function of age (age: β = 13.089, SE = 5.446, age2: β = − 0.220, SE = 0.088, age3: β = 0.001, SE = 0.0005) and education (education: β = − 14.095, SE = 2.848, education2: β = 0.745, SE = 0.213, education3: β = − 0.012, SE = 0.005). TMT-B was predicted by the quadratic function of age (age: β = − 4.758, SE = 1.795, age2: β = 0.055, SE = 0.0143) and the cubic function of education (education: β = − 33.907, SE = 6.816, education2: β = 1.737, SE = 0.507, education3: β = − 0.029, SE = 0.012). TMT-B-A was negatively predicted by the logarithmic function of age (β = − 46.805, SE = 5.412) and by the quadratic function of education (education: β = − 10.921, SE = 1.980, education2: β = 0.293, SE = 0.077).