Exp Brain Res DOI 10.1007/s00221-016-4857-4

RESEARCH ARTICLE

Verbal and visual divergent thinking in aging Massimiliano Palmiero1,2 · Raffaella Nori3 · Laura Piccardi1,2 

Received: 20 August 2016 / Accepted: 15 December 2016 © Springer-Verlag Berlin Heidelberg 2016

Abstract  According to the peak and decline model divergent thinking declines at a specific age (in or after middle age). However, if divergent thinking declines steadily in aging still has to be clarified. In order to explore the agerelated changes in verbal and visual divergent thinking, in the present study a sample of 159 participants was divided in five age groups: young adults (18–35 years), middleaged adults (36–55), young old (56–74), old (75–85) and the oldest-old (86–98). Two divergent thinking tasks were administered: the alternative uses for cardboard boxes, aimed at assessing verbal ideational fluency, flexibility and originality; the completion drawing task, aimed at assessing visual ideational fluency, flexibility and originality. Results showed that after peaking in the young adult group (20–35 years) all components of verbal and visual divergent thinking stabilized in the middle-aged adult group (36–55 years) and then started declining in the young old group (56–75). Interestingly, all components were found to be preserved after declining. Yet, verbal and visual divergent thinking were found at the same extent across age groups, with the exception of visual ideational fluency, that was higher in the young old group, the old group and the oldest-old group than verbal ideational fluency. These results support the idea that divergent thinking does not

* Massimiliano Palmiero [email protected] 1

Neuropsychology Unit, I.R.C.C.S. Fondazione Santa Lucia, Rome, Italy

2

Department of Life, Health, and Environmental Sciences, University of L’Aquila, P.le S. Tommasi 1, 67100 Coppito, AQ, Italy

3

Department of Psychology, University of Bologna, Bologna, Italy





decline steadily in the elderly. Given that older people can preserve to some extent verbal and visual divergent thinking, these findings have important implications for active aging, that is, divergent thinking might be fostered in aging in order to prevent the cognitive decline. Keywords  Creativity · Novel idea-generation · Elderly

Introduction The aging population presents significant challenges for the provision of social and health services. The decline of several cognitive skills is reported also in healthy aging, although the debate about the specific types of age-related changes in cognitive functioning is still ongoing. As the number of older people (over the age of 65) has increased and is expected to double in the next five decades, the understanding of the mechanisms underlying cognitive decline and the implementation of strategies to help older people cope with the decline have become crucial. Among others, the issue of creativity and age-related changes has been explored in the last decades since it is widely recognized that creativity leads to various benefits for older people (e.g., Cohen 2006; McFadden and Basting 2010). Traditionally, changes in creativity in aging have been explored using two different models (Levy and Langer 1999). First, the peak and decline model (Lindauer 1998) looks at creativity as the same construct across the lifespan. Creativity peaks in early adulthood, and its decline starts when people are in their 30s or 40s. It has operationalized creativity through psychometric tests, which assess both divergent thinking, that involves quantity indices, (e.g., ideational fluency and flexibility) and qualitative indices (e.g., originality of responses), and productivity measures,

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which assess the number of creative products. Second, the lifespan developmental model (Sasser-Coen 1993) assumes that creativity and productivity are not equivalent. This model focuses only on the quality of creativity and assumes that creativity changes across the years as a result of the changes occurring in the underlying cognitive processes. Indeed, fluid intelligence or the abstract ability for problem solving normally declines, whereas crystallized intelligence or the acquisition of knowledge, such as vocabulary, may increase in aging. This model has operationalized creativity through the social judgement of products in terms of novelty and significance. In particular, divergent thinking is a key factor of creativity, involving an open-ended mental process oriented to find many new, appropriate and different answers to open problems (Guilford 1950, 1967). Divergent thinking typically occurs in a spontaneous, free-flowing manner and involves associative and executive processes, such as broad retrieval ability and fluid intelligence (Beaty et al. 2014). It is an indicator of creative potential (Runco and Acar 2012), which does not necessarily result in creativity outcomes. Divergent thinking is scored in different components, such as: fluency (generation of different responses to fulfill specified requirements), flexibility (generation of responses belonging to different categories), originality (generation of infrequent responses) and elaboration (generation of details along with basic ideas). Visual divergent thinking can also include abstractness of title (e.g., going beyond labeling) and resistance to premature closure (e.g., keeping an open mind). Each component of divergent thinking is affected in different ways in aging and at different times. In general, verbal divergent thinking begins to decline mostly in middle age in terms of fluency, flexibility and originality (Alpaugh and Birren 1977; Guilford 1967), redefinition of a familiar interpretation in order to apply it in a unique situation (Alpaugh and Birren 1977), and in associational, expressional, ideational and word fluency, and remote consequences (McCrae et al. 1987). Moreover, using three age groups, that is youthful (25–35 years), middle-aged (45– 55 years) and old sample (65–75 years), Ruth and Birren (1985) found that both verbal and visual ideational fluency, flexibility and originality peaked in the younger group and decreased starting from the middle-aged group. Palmiero (2015) also revealed that verbal ideational fluency, flexibility, originality and elaboration peaked before 40 years and declined thereafter. However, other studies found that divergent thinking begins to decline after middle age. Jaquish and Ripple (1981), grouping their participants into young adults (18–25 years), adults (26–39 years), middle adults (40– 60 years) and older adults (61–84 years), found that the first three groups were significantly more fluent than the

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Exp Brain Res

oldest one. Young adults and middle adults were also more flexible than older adults and middle adults were significantly more original than older adults. In this direction, dividing the sample into young (17–22 years), middle-aged (40–50 years), old (60–70 years) and old-old (75+ years), Lee (1994) revealed that the middle-aged group scored higher than the old-old group in terms of verbal ideational fluency, flexibility and originality. Reese et al. (2001) also divided the sample into young (17–22 years), middle-aged (40–51 years), young old (60–71 years) and old-old (75– 99 years), confirming that the middle-aged group scored higher, whereas the old-old group scored lower on verbal ideational fluency, flexibility and originality. Yet, different studies revealed no decline of divergent thinking in aging. Foos and Boone (2008) showed that when timed test conditions were removed, old participants (mean age = 72.10) were as divergent as young adults (mean age = 20.53) in terms of fluency (associational, expressional, ideational and word) and remote consequences, although at a slower rate. Interestingly, Roskos-Ewoldsen et al. (2008) revealed that young (mean age  = 19.37) and old participants (mean age = 73.05) showed no difference in terms of figural fluency, resistance to premature closure, originality, elaboration and abstractness of titles. After correcting for visual working memory differences, younger adults scored as older adults at the bonus measure, which involves the use of constructs like humor, imagery and fantasy, and older adults even showed higher abstractness of title scores than younger adults. Interestingly, Leon et al. (2014) revealed that older participants (age = 65–80; M  = 72.93) scored higher than younger participants (age = 18–30; M  = 20.21) in terms of uniqueness at two different non-time-constrained verbal divergent thinking tasks (Alternative Uses and Associative Fluency), even after correcting for the lexical-semantic abilities. However, the two groups did not differ in terms of total fluency for both tasks. Comparing younger (19–25 years) and older adults (57–82 years), Palmiero et al. (2014) similarly found no difference between the two groups in terms of verbal ideational fluency, visual and verbal originality, flexibility, and elaboration; older adults only produced fewer visual ideas than younger adults. In this direction, Madore et al. (2016) revealed that although a brief training in recollecting the details of a past experience boosted old and new ideas of verbal divergent thinking on the alternate uses task (fluency, appropriate use, categories of uses, elaboration and creativity) in both younger (age = 18–30; mean age = 21.61) and older adults (age  = 64–87; mean age = 71.83), no age-related differences were observed. Yet, Addis et al. (2016) found that even though age was significantly associated with imagined episodic details, the effect was strongly related to agerelated changes in episodic retrieval rather than divergent

Exp Brain Res

thinking. Finally, Privodnova and Volf (2016) showed no difference between young (mean age = 22.6) and elderly adults (mean age = 63.4) in terms of originality of verbal divergent thinking, although age-related changes in brain oscillatory activity were found, probably indicating that the two groups used different strategies to carry out the alternative uses task. Thus, although most of the studies are in line with the peak and decline model, showing that divergent thinking declines in or after middle age, different studies found no age-related differences between young and older age groups. However, it must be noted that the lack of differences between young and older people has been found when only two different groups were compared; with more groups differences emerged. Thus, in the present study, the issue of age-related changes in divergent thinking was faced dividing the sample in different age ranges, that is, firstly in young adults group (18–35 years), middle-aged adults group (36–55 years) (e.g., as in Coll et al. 2015; Petry 2002) and young old group (56–74 years) (e.g., as in Ivnik et al. 1992); secondly, moving from the consideration that late adulthood shows higher inter-individual variability than young adults (e.g., Borella et al. 2009; Nelson and Dannefer, 1992), two more age groups were formed: the old group (75–85 years) and the oldest-old group (86– 98 years) (as in De Beni 2009). The hypothesis was formulated according to the peak and decline model: both verbal and visual divergent thinking peak in middle age and thereafter decline. Although verbal and visual divergent thinking are largely independent from each other (Torrance 1990), the unique hypothesis also considers that both forms of divergent thinking share common processes, such as visuospatial mental processing (Duff et al. 2013), that normally decline in aging (e.g., Band and Kok 2000; Palermo et al. 2016; Piccardi et al. 2015). In particular, Duff et al. (2013) revealed that hippocampal amnesic patients, characterized by deficits in the construction of salient visualization of an experience within a spatial setting, showed a lower performance than controls on both verbal and visual divergent thinking.

• Young adult group (20–35), 37 participants (M = 26.7, ±3.7; 18 women and 19 men); • Middle-aged adult group (36–55), 30 participants (M = 48.3, ±4.9; 15 women and 15 men); • Young old group (56–74), 38 participants (M  = 65.4, ±5; 19 women and 19 men); • Old group (75–85), 29 participants (M = 80, ±3.66; 11 women and 18 men); • The oldest-old group (86–99), 25 participants (M = 89.46, ±3.35; 13 women and 12 men). For each age group, the respective number of participants was determined on the basis of the representation of the age range in the population, assuming a minimum age group size of 23 subjects, as reported in Hinkle and Oliver’ (1983) study considering power = .75, p = .05 S.D. = 1. Then, following Faul et al. (2007), the post hoc power calculation (1—Beta error probability) was carried out in light of the number of participants for each unique comparison among groups, using the following parameters: t test two tails, conventional effect size 0.5, α = 0.05. Thus: • The young adult group (37) compared to the middleaged adult group (30) = power 0.518; • The young adult group (37) compared to the young old group (38) = power 0.57; • The young adult group (37) compared to the old group (29) = power 0.51; • The young adult group (37) compared to the oldest-old group (25) = power 0.48; • The middle-aged adult group (30) compared to the young old group (38) = power 0.523; • The middle-aged adult group (30) compared to the old group (29) = power 0.47; • The middle-aged adult group (30) compared to the oldest-old group (25) = power 0.442; • The young old group (38) compared to the old group (29) = power 0.515; • The young old group (38) compared to the oldest-old group (25) = power 0.48; • The old group (29) compared to the oldest-old group (25) = power 0.436.

Method Participants For this study 159 people were enrolled (age range = 20–98; M = 30.7 ± 18.6; 76 women and 83 men). Participants were recruited without any background in visual arts or creative activities as controlled by a checkout interview in order to avoid effects on divergent thinking due to the expertise. Participants were grouped into five age cohorts defined by age at last birthday.

Participants were recruited from the elderly relatives of college students at L’Aquila University, and from City Clubs and Worker’s Clubs of the Abruzzo region, Italy. In enrolling participants we considered the ‘exclusion criteria’ proposed by Crook et al. (1986)—i.e., a history of head trauma, any neurological or psychiatric illness, a history of brain fever, dementia or any other state of altered consciousness, use of benzodiazepines in the previous 3 months, use of illicit drugs, any visual, auditory or motor impairments, any symptomatic cardiovascular conditions,

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breathing problems, or diseases capable of causing cognitive impairments. All participants had normal or corrected (soft contact lenses or glasses) vision. Furthermore, in order to screen for cognitive impairment, all participants were administered the Italian version of the Mini-Mental State Examination—MMSE—(Folstein et al. 1975; Italian version: Frisoni et al. 1993); they all obtained a score higher than 27 (cutoff = 23; Magni et al. 1996). All participants signed the written informed consent after the explanation of the general procedure of the study. The study was designed in accordance with the ethical principles of human experimentation stated in the Declaration of Helsinki and was approved by the Institutional Review Board of the Department of Life, Health and Environmental Science, University of L’Aquila. Materials and procedure Two different divergent thinking tests were administered from the Torrance Test of Creative Thinking—TTCT— Form A—(Torrance 1987; Italian version, Sprini and Tomasello 1989). For verbal divergent thinking the wordbased exercise of listing unusual uses for a cardboard box was used. In this task participants were instructed to come up with as many different alternative uses as possible for cardboard boxes in 10 min. For visual divergent thinking the picture-based exercise of completion of drawings was used. In this task participants were asked to complete max 10 drawings starting from 10 given shapes in 10 min. For each drawing a short title was required. Participants were encouraged to work on both tasks for 10 min, that is, they were not instructed to stop working on the tasks before the time expired. The decision to use only two tasks of the TTCT battery to evaluate divergent thinking in verbal and visual form was made assuming that using simple and short tasks would not disadvantage older people, who are generally less familiar with the experimental procedure and may tire more easily, with a detrimental effect on their performance. Participants were tested individually for half an hour. After signing the written informed consent, they filled in the anamnesis questionnaire, aimed at collecting demographic and health information, and the MMSE. The two divergent thinking tests were administered in random order to avoid any effects due to the order of presentation.

Exp Brain Res

for both verbal and visual divergent thinking: fluency (the number of relevant verbal or figural responses), flexibility (the number of categories encompassing the relevant responses) and originality (the sum of weights of statistically frequent or infrequent responses). In particular, the flexibility row score was computed using the list of the categories included in the technical manual, covering about 99% of the responses provided by the sample of 500 people. When the category was not available, a new category was opportunely created. The originality row score was computed using originality weights as defined in the manual in light of the frequencies of responses provided by the reference sample of 500 people (from preschool to university ages). Therefore, 0 point was given to responses provided by 5% or more of 500 people; 1 point was given to responses provided by 2–4.99% of 500 people; 2 points were given to responses provided by <2% of 500 people. For responses not listed in the manual, that is for those responses that were extremely original, always 2 points were given. The sum of these points across responses was used as the individual originality raw score. Results Firstly, two multivariate analyses of covariance (MANCOVA) were carried out in order to explore age-related changes in ideational fluency, flexibility and originality of verbal and visual divergent thinking separately. This analysis moved from two considerations: firstly, for both verbal and visual divergent thinking, ideational fluency, flexibility and originality scores express different aspects. Torrance (1979) himself discouraged the use of total score of divergent thinking given that a composite score may be misleading because each sub-score has independent meaning, as stated above. Secondly, verbal and visual divergent thinking are almost orthogonal measures (Baer 2011; Torrance 1990). Indeed, they are expressed in two different modalities (the verbal form requires that ideas are put into words, whereas the visual form requires the production of pictures) and generally measure different cognitive abilities (Torrance 1990). In this direction, Palmiero et al. (2010) also found that verbal and visual divergent thinking are largely domain-specific, being supported by specific verbal and visual proficiencies, respectively.

Data scoring

Verbal divergent thinking

Verbal and visual divergent thinking were scored by two scorers (one male and one female) blind to age groups and to the aim of the study using the standard TTCT assessment procedure as described in the technical manual (Sprini and Tomasello 1989). Three basic row scores were considered

In the first MANCOVA, fluency, flexibility and originality scores of verbal divergent thinking were treated as dependent measures; the ‘age group’ was treated as the independent between factor, whereas the education level was treated as covariate (mean = 8.79, S.D. = 4.13).

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Exp Brain Res Table 1  Age group means (and standard error of the mean) on verbal divergent thinking components

Table 2  Age group means (and standard error of the mean) on visual divergent thinking components

Group

Group

Fluency (SE)

Flexibility (SE) Originality (SE)

Young (20– 35 years)

8,861570 (0.47)a

7,914781 (0.40)a

11,19326 (0.93)a

Middle-aged (36–55)

8,493307 (0.46)

7,856169 (0.39)b

10,67484 (0.91)b

Young old (56–74)

7,310816 (0.41)

6,151643 (0.34)b

7,43022 (0.81)

Old (75–85)

7,340635 (0.48)

5,505356 (0.40)a,b

8,07582 (0.95)

Oldest-old (86–98)

6,505332 (0.53)a

5,282012 (0.44)a,b

5,92228 (1.04)a,b

Fluency (SE)

Flexibility (SE)

Originality (SE)

Young (20– 35 years)

a

7,213556 (0.53)

5,133340 (0.31)a

6,902969 (0.65)a

Middle-aged (36–55)

6,487826 (0.52)b

4,307131 (0.30)b

5,333932 (0.63)b

Young old (56–74)

4,147301 (0.46)a,b

3,215825 (0.27)a

3,235738 (0.56)a

Old (75–85)

2,811920 (0.54)a,b

2,420517 (0.32)a,b

3,540890 (0.66)a

Oldest-old (86–98)

2,852821 (0.59)a,b

2,298245 (0.35)a,b

3,437134 (0.73)a

Means with the same superscript letter within a column were significantly different from each other (Bonferroni’s post hoc comparisons, p < 0.05)

The analysis revealed a significant effect of the variable ‘age group’ [Lambda Wilks = .67, F(12, 399,8) = 5.446, p < .000001; partial η2  = .125; observed power = 1]. The covariate ‘education’ was not significant [Lambda Wilks = .989, F(3, 151,0) = .536, p = .66] (see Table 1). Verbal ideational fluency The univariate analysis showed that the variable ‘age group’ significantly affected verbal ideational fluency [F(4, 2 153)  = 12.489, p < .000001; partial η   = .246; observed power  = 1]. Post hoc comparisons with Bonferroni correction revealed no difference between the young adults group and the middle-aged adults group. Both the young adults group and the middle-aged adults group scored better than the young old group, the old group and the oldestold group; no difference was found between the young old, the old and the oldest-old groups. The covariate ‘education’ was not significant for verbal ideational fluency [F(1, 153)  = .9, p = .34]. Verbal flexibility The variable ‘age group’ also affected verbal flexibility [F(4, 153) = 12.668, p < .000001; partial η2 = .249; observed power = 1]. Post hoc comparison with Bonferroni correction revealed no difference between the young adults group and the middle-aged adults group; the young adults group scored better than the young old group, the old group and the oldest-old group; the middle-aged adults group scored better than the old group and the oldest-old group; no difference was found between the young old group, the old group and the oldest-old group. The covariate ‘education’ was not significant for verbal flexibility [F(1, 153)  = .3, p = .58].

Means with the same superscript letter within a column were significantly different from each other (Bonferroni’s post hoc comparisons, p < 0.05)

Verbal originality The variable ‘age group’ also affected verbal originality [F(4, 153)  = 5.498, p < .0005; partial η2  = .126; observed power = .974]. Post hoc comparison with Bonferroni correction revealed that only the young adults group scored better than the young old, the old group and the oldest-old group; no difference was found between the young adults group and the middle-aged adults group; yet no difference was found between the middle-aged adults group, the young old group, the old group and the oldest-old group. The covariate ‘education’ was not significant for verbal originality [F(1, 153) = 1.543, p = .22]. Visual divergent thinking In the second MANCOVA, fluency, flexibility and originality scores of visual divergent thinking were treated as dependent measures; the ‘age group’ was treated as the independent between factor, whereas the education level was treated as covariate. The analysis revealed a significant effect of ‘age group’ (Lambda Wilks = .701, F(12,399, 8) = 4.78, p < .000001; partial η2 = .162; observed power = 1). The covariate ‘education’ was also significant [Lambda Wilks = .84, F(3, 151,00) = 9.59, p < .00001; partial η2 = .166] (see Table 2). Visual ideational fluency The univariate analysis showed that the variable ‘age group’ significantly affected visual ideational fluency [F(4, 153)  = 3.424, p < .05; partial η2  = .082; observed power = .846]. Post hoc comparisons with Bonferroni correction revealed that the young adults group scored better only than the oldest-old group; no difference was found

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among the other groups. The covariate ‘education’ was not significant for visual ideational fluency [F(1, 153)  = .114, p = .74]. Visual flexibility The univariate analysis showed that the variable ‘age group’ significantly affected visual flexibility [F(4, 153)  = 8.707, p < .000005; partial η2  = .185; observed power = .999]. Post hoc comparisons with Bonferroni correction revealed that the young adult scored as the middle-aged adults and the young old group; the young adults group scored better than the old group and the oldest-old group; the middleaged adult group scored better than the young old group, the old group and the oldest-old group; no difference was found between the young old, the old and the oldest-old group. The covariate ‘education’ was significant for visual flexibility [F(1, 153) = 6.934, p < .01; partial η2 = .043; observed power = .744].

Exp Brain Res

showed a main effect of ‘domain’ [F(1, 154)  = 114,510, p < .000005; partial η2 = .426; observed power = 1]: ideational visual fluency score (mean = 7.71; SE = .2) was higher than ideational verbal fluency score (mean = 4.69; SE  = .23). Finally, the analysis revealed an interaction effect of ‘age group × domain’: F(4, 154)  = 4,734, p < .005; partial η2 = .109; observed power = .948]. Post hoc comparisons with Bonferroni correction showed that the ideational fluency was higher in the visual than verbal domain in the young old group (mean = 7.32; SE = .41; mean  = 4.13; SE = .46), the old group (mean = 7.38; SE  = .77; mean = 2.69; SE = .52) and the oldest-old group (mean = 6.56; SE = .5; mean = 2.68; SE = .57). No difference was found between visual and verbal ideational fluency in the young adults group (mean = 8.78; SE = .41; mean = 7.46; SE = .46) and the middle-aged adults group (mean = 8.5; SE = .46; mean = 6.46; SE = .52). Flexibility

The univariate analysis showed that the variable ‘age group’ significantly affected visual originality [F(4, 153)  = 4.936, p < .001; partial η2 = .114; observed power = .956]. Post hoc comparisons with Bonferroni correction revealed that both the young adult and the middle-aged adult groups scored better than the oldest-old group; no difference was found between the other groups. The covariate ‘education’ was not significant for visual originality [F(1, 153) = 2.238, p = .14]. Secondly, moving from the consideration that verbal and visual divergent thinking might share common processes, such as imagery capacity (e.g., Palmiero et al. 2010) and visuospatial mental processing (e.g., Duff et al. 2013), three different ANOVAS were carried out, using the domain (verbal and visual divergent thinking) as a withinsubject variable.

The univariate analysis showed that the variable ‘age group’ significantly affected flexibility [F(4, 154)  = 19,831, p < .000005; partial η2 = .34; observed power = 1]. Post hoc comparisons with Bonferroni correction revealed no difference between the young adults group (mean = 6.31; SE = .41) and the middle-aged adults group (mean = 6.1; SE  = .26). Both the young adults group and the middleaged adults group scored better than the young old group (mean  = 4.7; SE = .23), the old group (mean = 4.1; SE  = .26) and the oldest-old group (mean = 3.94; SE = .26); no difference was found between the young old, the old and the oldest-old groups. The analysis also showed a main effect of ‘domain’ [F(1, 154) = 217,215, p < .000005; partial η2  = .585; observed power = 1]: visual flexibility (mean  = 6.58; SE = .17) score was higher than verbal flexibility score (mean = 3.47; SE = .13). The interaction ‘age group × domain’ [F(4, 154) = 1.555, p > .05] was not significant.

Ideational fluency

Originality

The univariate analysis showed that the variable ‘age group’ significantly affected ideational fluency [F(4, 154) = 18,151, p < .000005; partial η2 = .426; observed power = 1]. Post hoc comparisons with Bonferroni correction revealed no difference between the young adults group (mean = 8.12; SE = .33) and the middle-aged adults group (mean = 7.48; SE  = .37). Both the young adults group and the middleaged adults group scored better than the young old group (mean  = 5.72; SE = .33), the old group (mean = 4.62; SE  = .4) and the oldest-old group (mean = 5.03; SE  = .37); no difference was found between the young old, the old and the oldest-old groups. The analysis also

The univariate analysis showed that the variable ‘age group’ significantly affected originality [F(4, 154) = 10,020, p < .000005; partial η2 = .207; observed power = 1]. Post hoc comparisons with Bonferroni correction revealed no difference between the young adults group (mean = 8.91; SE = .53) and the middle-aged adults group (mean = 8.02; SE  = .59). The young adults group scored better than the young old group (mean = 5.34; SE = .52), the old group (mean = 5.88; SE = .6) and the oldest-old group (mean  = 4.78; SE = .64); the middle-aged adults group scored better than the young old group and the oldest-old group. No difference was found between the middle-aged

Visual originality

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Exp Brain Res

group and the old group, and between the young old, the old and the oldest-old groups. The analysis also showed a main effect of ‘domain’ [F(1, 154)  = 85,909, p < .000005; partial η2  = .358; observed power = 1]: visual originality score (mean = 8.71; SE = .4) was higher than verbal originality score (mean = 4.46; SE = .28). The interaction ‘age group x domain’ [F(4, 154)  = .9716, p > .05] was not significant.

Discussion The present study was aimed at investigating the extent to which verbal and visual divergent thinking change in aging. Participants aged from 20 to 98 years were recruited. Three main findings were found. Firstly, no difference was revealed between the young adults group (20–35 years) and the middle-aged adults group (36–55 years) in terms of quantity (fluency and flexibility) and quality (originality) of verbal and visual divergent thinking. Secondly, the young adult group scored better than the young old (56– 74), the old (75–85) and the oldest-old (86–98) group in all components of verbal divergent thinking; the young adult group also scored better than the oldest-old group in terms of visual ideational fluency, flexibility (better also than the old group) and originality. Yet, the middle-aged adult group scored better than the young old group, the old group and the oldest-old group in terms of verbal ideational fluency and visual flexibility; better than the old group and the oldest-old group in verbal flexibility, and better than the oldest-old group in visual originality. Thirdly, no difference was found between the young old, the old and the oldestold group in any component of verbal and visual divergent thinking. Fourthly, although there is a general main effect of domain, that is visual divergent thinking was generally higher than verbal divergent thinking, age groups performed at the same level across domains, with the exception of ideational fluency: the young old group, the old group and the oldest-old group showed higher ideational fluency in visual than verbal domain. Taken together these results confirm and extend previous studies based on the peak and decline model. They show that after peaking verbal and visual divergent thinking do not change until the age of 55. The decline would occur after the middle age, confirming different studies (e.g., Jaquish and Ripple 1981; Lee 1994; Reese et al. 2001). Surprisingly the oldest-old group (86–98) did not show a dramatic decline in performance with respect to the other groups of old people. In this direction Lee (1994) also found that the old-old group (75+) did not differ from the old group (60–70) in verbal fluency (using coat as test stimulus), flexibility and originality (using both brick and coat as test stimuli). Regarding originality no difference was

found among all groups considering only brick as test stimulus. Also Reese et al. (2001) found no difference between young old (60–71) and old-old groups (75–99) in associational fluency (generation of words in response to different stimulus words). In particular, these results confirm that verbal divergent thinking stabilizes after declining. This finding is not surprising, since verbal divergent thinking is mostly supported by verbal abilities (Ottó 1998; Palmiero et al. 2010), which remain relatively intact across the lifespan (e.g., Kemper and Kemtes 1999; Park et al. 2002). Yet, these results also show that visual divergent thinking is preserved more than verbal divergent thinking and does not steadily decline even in the oldest groups of people but rather stabilizes. This finding is rather surprising, since some mechanisms involved in visual divergent thinking were found to decline in aging, such as visuospatial manipulation (e.g., Band and Kok 2000) and visual mental imagery (De Beni et al. 2007a; Palmiero et al. 2015; Piccardi et al. 2015). One explanation for such a finding might be related to the complexity of the visual divergent thinking task and to the workload produced by the task. In the present study participants only had to produce max 10 drawings in 10 min starting from basic stimuli. Indeed, Palmiero et al. (2016b) found no difference between younger and older participants (18–82 years) at the Clark’s Drawing Ability Test, confirming that visual creativity can be preserved to some extent with age when the task’s requirements can also be managed by the elderly. On the contrary, Palmiero (2015) found that creative objects production, which strongly involves visuospatial mental transformations (Palmiero et al. 2015), declines after the 40s, and, especially when people are in their 70s. In general, although by the age 74–75 a cognitive decline should be expected in different spatial and verbal abilities (Baltes and Mayer 1999; Borella et al. 2007; De Beni et al. 2007b; Schaie 2000; Schaie et al. 2004), the present findings support the idea that divergent thinking can be preserved in older people. This creative potential if opportunely stimulated might be successfully used to better cope with cognitive decline and daily difficulties. According to Madore et al. (2016) a brief training in recollecting the details of a past experience boosts old and new ideas of verbal divergent thinking in young and old adults. In this vein, Privodnova and Volf (2016) suggested that young and elderly adults can use different strategies to solve divergent thinking tasks: in particular, due to the limited resources, elderly adults would use strategies established during the life based on a more economical approach and a lower number of information processing steps than young adults. In addition, verbal divergent thinking has been recently considered as a possible proxy indicator of cognitive reserve (Palmiero et al. 2016a). On this matter,

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neuroimaging studies showed that divergent thinking and creativity do not critically rely on a single brain area and are not specifically associated with the right or left brain hemispheres (Dietrich and Kanso 2010), but rather involve a multi-componential neural system, including the bilateral occipital, parietal, frontal and temporal lobes (Boccia et al. 2015), as also shown in studies performed on patients suffering from dementia (for a review, see Palmiero et al. 2012). Thus, it could be that boosting divergent thinking, brain-related areas would be better stimulated, enhancing also cognitive reserve. Indeed, Colangeli et al. (2016) showed that different brain areas are associated with cognitive reserve proxies in healthy aging. Although in Colangeli et al. (2016) meta-analysis creativity was not considered as a proxy of cognitive reserve, it is worth considering that among the significant activated brain areas there are also areas that play an important role on divergent thinking. In conclusion, different considerations emerge from the present study: verbal and visual divergent thinking can be preserved in terms of both quantity and quality of responses; divergent thinking should be fostered using different tasks and approaches, without making the workload too heavy for older people. Of course more study is necessary to confirm these results in different cohorts, using longitudinal designs. Indeed, in the present cross-sectional study a cohort effect, involving historical influences on a particular birth group that are unique to this group (Keyes et al. 2010), might have occurred. For example, among others the education level might generate the cohort effect. Indeed, older people have generally lower formal education than younger people, and more education could inflate the test scores (Levy and Langer 1999). In the present study the covariate of education was found significant only for visual flexibility. Probably, this effect reflects the fact that visual divergent thinking relies on formal education more than verbal divergent thinking, which might be supported by general knowledge acquired across years even in less educated people. Finally, different cognitive processes that might interact with divergent thinking should also be considered in future studies. Acknowledgements Funding was provided by Fondazione Santa Lucia, Neuropsychology Unit, I.R.C.C.S.

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