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Effects of intellectual variables, age, and gender on divergent thinking in adulthood

International Journal of Behavioral Development Effects of intellectual variables, age, and gender on Texas A & M University–Kingsville, USA West Virginia University, Morgantown, USA Divergent thinking was assessed in 400 adult women and men with tests of word association(associational uency) and alternate uses (production uency, participants were from four age cohorts: young (17–22 years old), middle-aged (40–50), young-old(60–70), and old-old (75‡). The test battery also included two intellectual ‘‘process’’ variables (inductive reasoning, memory span), one ‘‘dynamic resource variable’’ (intellectual speediness), one‘‘structural resource variable’’ (vocabulary), and two moderator variables (depression, education).
Hierarchical multiple regression analyses showed that divergent thinking was signi cantly, linearly,positively, and moderately related to all of these variables except depression, which was notsigni cantly related to divergent thinking. Effects of age group and gender were assessed in analysesof variance (alpha ˆ .01). The age groups did not differ signi cantly in associational uency, but the middle-aged group was the best on production uency, exibility, and originality. Gender had asigni cant effect on only one variable: Women had higher depression scores than men.
The study reported in this paper dealt with divergent thinking.
the evidence they cited, this conclusion seems to have been In Guilford’s (1967) theory of intelligence, ‘‘divergent’’ much too cautious. Although they stated that many studies thinking is contrasted with ‘‘convergent’’ thinking in the failed to demonstrate construct validity, they did not specify following way: Divergent thinking is related to creativity, as the number and they cited no speci c studies. In contrast, they usually conceptualised (e.g., Simonton, 2000), in that both referred to more than 75 studies that demonstrated construct involve the production of a variety of new, original solutions to validity, including more than 50 reviewed in an unpublished a problem. Divergent thinking is therefore useful for solving article they cited and 25 they speci cally reviewed.
problems that do not have a single, objectively correct solution Four issues were addressed in the present study. The rst but rather have several potentially workable solutions whose issue was about the nature of divergent thinking. Research with originality or other kind of value can be assessed. Greater children and young adults has shown that training in uency or originality is expected if the production of ideas is uent (many exibility yields an increase not only in the trained process but ideas are produced) and exible (several categories of ideas are also in originality—originality of physical constructions in produced) (Guilford, 1967). In contrast, convergent thinking preschool children (Holman, Goetz, & Baer, 1977) and verbal is intended to produce a single solution to a problem—not productions in college students (Meadow, Parnes, & Reese, merely the subjectively best solution but the only objectively 1959). These results imply that originality is intrinsically correct solution. Given this difference, tests of divergent related to uency and exibility. However, Goff (1992) found thinking ask for the production of many alternative answers that creativity training increased older adults’ and tests of convergent thinking require arriving at a single true exibility but not their originality, implying that originality is a separate dimension of divergent thinking.
Several tests have been developed to assess divergent Other ndings indicate that divergent thinking is different thinking, and although their usefulness has been challenged, from general intelligence but is correlated with general the challenges can themselves be challenged. For example, intelligence (McCrae, Arenberg, & Costa, 1987). The second Sternberg (1985) questioned the usefulness of divergent issue addressed in the present study was whether divergent thinking tests, but he may have been reacting to only their thinking is related to a different set of intellectual variables.
face validity, which is usually a trivial aspect of a test. Barron The third issue was how divergent thinking is related to age.
and Harrington (1981) also questioned their usefulness and More research has been done on age differences in creativity concluded that ‘‘some divergent thinking tests, administered than divergent thinking, but the presumed relation of creativity under some conditions and scored by some sets of criteria’’, are to divergent thinking implies that the age differences should be valid ‘‘in some domains’’ (p. 447). However, on the basis of similar. The creativity research seems to have begun with Correspondence should be addressed to Hayne W. Reese, 4516 the National Chengchi University, Taipei, Taiwan. We are indebted to French Lake Drive, Fort Worth, TX 76133, USA. Tel: (817) 346 Mike Gregory for aid in developing the scoring procedures for the alternate uses test. Preliminary reports were given at the Conference on This research was supported by a grant (R01 AG06069) from the Human Development, Pittsburgh, PA, April 1994, and the meeting of National Institute on Aging, United States Department of Health and the International Society for the Study of Behavioral Development, Human Services, to the rst author. Co-author Liang-Jei Lee is now at REESE ET AL. / DIVERGENT THINKING IN ADULTHOOD historical surveys in which biographies of persons identi ed as independent of divergent thinking. This expectation was highly creative were studied to determine the ages at which veri ed in our study by exploratory factor analyses and they made their creative contributions. Creative contributions multiple regression analyses. The taxonomy also turned out were found to decline with age (e.g., Dennis, 1966; Lehman, to be consistent with the data in some other respects indicated 1953; for reviews of these and similar studies, see Botwinick, 1984, chap. 19; Gilhooly, 1988, chap. 9). The approach inother research has been to look at the creative process ratherthan the products of this process (e.g., Alpaugh & Birren,1977; Bromley, 1956; for a relevant review, see Kausler, 1991, pp. 619–625). Like the biographical research, this research hasshown a decline in creativity with increasing age. Therefore, divergent thinking should also decline with increasing age(Kausler, 1991, p. 620). In agreement with this hypothesis, The research participants were from a large-scale cross- some research has shown that divergent thinking begins to sectional study of cognition conducted by Reese, Puckett, decline in middle age (Alpaugh & Birren, 1977; Guilford, and Cohen in 1986–90. In this study, 400 adults were given a 1967; McCrea et al., 1987; Ruth & Birren, 1985). However, battery of 24 questionnaires, tests, and tasks divided equally some other research has shown that the decline begins after between two sessions and given in a xed order designed to middle age (Baltes & Lindenberger, 1997; Jaquish & Ripple, minimise carry-over effects. The battery yielded scores on well 1981; Schaie & Hertzog, 1983). In short, prior research had over a hundred different variables. The participants were from not settled the issue of how early in adulthood the decline four age cohorts de ned by age at last birthday: 17–22, 40–50, 60–70, and 75 or more years old, here designated young, The fourth issue investigated here was how divergent middle-aged, young-old, and old-old. The selection criteria thinking is related to gender. Gender differences were not were age and gender. Additional selection criteria would have assessed in any study we located, and although gender been hearing, vision, reading, and health adequate for differences in creativity were assessed in several studies, the participation, but all except one of the volunteers met these results have been inconsistent (Osborn, 1963, p. 22). Some criteria. The exception was a 99-year-old man who was researchers found no statistically signi cant gender differences included in the study despite visual problems; he was the (Agarwal & Kumari, 1982; Alpaugh & Birren, 1977; Bromley, oldest participant in the study and he took all the tests in the 1956; Jaquish & Ripple, 1981) and others found gender battery reported in this paper except Letter Sets (inductive differences, sometimes favouring women (Bharadwaj, 1985) reasoning) and Finding A’s (intellectual speediness), which and sometimes favouring men (Ruth & Birren, 1985, but using a test evidently biased in favour of male-typical knowledge).
No attempt was made to match the age/gender groups on The foregoing overviews indicate that prior research had not education, health, or other variables that might in uence de nitively established the dimensionality of divergent thinking performance. The reason is that matching, or ‘‘control by nor its relations to other intellectual variables, age, and gender equation’’ (Baltes, Reese, & Nesselroade, 1988, pp. 216–218; during adulthood. The present study was designed to provide Bitterman, 1960), must yield samples that are not representa- evidence about these relations by assessing four divergent tive of one or more of the age/gender populations (Krauss, thinking variables, four other intellectual variables, and two possible moderator variables in women and men from fouradulthood age periods. The four intellectual variables were selected to represent two intellectual ‘‘processes’’, one ‘‘dy-namic resource’’, and one ‘‘structural resource’’ (Salthouse, Thirteen demographic variables were assessed via self-report 1985, 1988). The process variables were inductive reasoning, (except where indicated otherwise in the following list) in a which is an index of uid intelligence (or uid mechanics— structured, face-to-face interview given as the rst task in the Baltes, 1993), and memory span, which is an index of ‘‘short- rst session. They are de ned in the following list and the age term acquisition and retrieval’’ (Horn, 1978a, b). The dynamic group statistics for the 400 participants who took one or both resource variable was speed of mental processing (Horn, of the divergent thinking tests are presented in Table 1.
1978a, b); and the structural resource variable was vocabulary,which indexes verbal knowledge or crystallised intelligence (or (a) Age in years (to two decimal places) at the rst testing crystallised pragmatics—Baltes, 1993). The possible modera- session was used for correlations of age with other variables.
tor variables were depression and amount of education, which Age in years at last birthday was used for assignment to age have been shown to be related to cognitive performance (depression: e.g., La Rue, Dessonville, & Jarvik, 1985; Luszcz, Bryan, & Kent, 1997; education: e.g., Chi & Ceci, 1987) and t the taxonomy of variables. Depression, or (d) Predominant marital status during adulthood.
rather its absence, might be a kind of dynamic resource (e) Location of current residence (rural vs. urban).
variable and education might index general knowledge, which (f) Location of usual residence during the preceding 10 is a kind of structural resource variable; because of these possible classi cations—and for stylistic simplicity—we refer (g) and (h) Population (to nearest thousand according to a herein to depression and education as ‘‘intellectual’’ variables.
Rand–McNally atlas) of the Greater Metropolitan Area in Except for depression and perhaps education, these vari- which the participant (g) was currently residing and (h) had ables re ect various kinds of convergent thinking and therefore usually resided during the preceding 10 years (less than 500 we expected them to be positively related to but factorially was coded as 0, more than 998,499 was coded as 999).
Demographic characteristics of the age groups
Note: See text for de nitions of nonobvious variables.
aAge at rst session. bPercentage of participants who were from urban areas with population greater than 250,000. cPercentage of participants per category. See Item (k) in the Method section forde nitions. One young-adult record was eliminated because of examiner error. dOnly for the 23participants who reported possibly being currently affected by drugs. Possible range: 1 (‘‘A little’’) to 3(‘‘A lot’’).
(i) Current and (j) career occupation. The categories used otherwise unemployed part-time students (all were in the were: (1) Manager/Professional: Managerial & Professional Young group) and otherwise unemployed housepersons (1 in Specialties (codes 3–199 in the Standard Occupational Classi- the Young group for Current, none for Career). (5) Un- cation Manual, 1980). (2) Technical/Sales/Service: Technical, employed: Not working but seeking employment. (6) Retired: Sales, & Administrative Support (codes 203–389) and Service Not working and not seeking employment. (The last three (codes 403–469). (3) Worker: Farming, Forestry, & Fishing categories are not coded in the Standard Occupational (codes 473–499), Precision Production, Craft, & Repair (codes 503–699), and Operators, Fabricators, and Laborers (codes (k) Drugs taken and possibly affecting performance at the 703–889). (4) Student/Houseperson: Full-time students and time of testing. The questionnaire included None and the REESE ET AL. / DIVERGENT THINKING IN ADULTHOOD following categories and examples: (1) Sedatives: ‘‘Librium, (f) Education was self-reported in the demographic inter- Valium, etc.’’; (2) Alcohol: ‘‘beer, liquor, wine, etc.’’; (3) view (Session 1, Task 1) and was coded in years: 1–12 years Tranquillisers: ‘‘Chlorpromazine, Haldol, etc.’’; (4) Sleeping through high school (12 years assigned for high school diploma pills: ‘‘Phenobarbital, Seconal, etc.’’; (5) Other: ‘‘Quaaludes, or equivalent) plus 1–4 years of undergraduate college Marijuana, etc’’. Categories (2) through (5) are combined as education (4 years assigned for bachelor’s degree) plus 1–4 years of postgraduate education (4 years assigned for Ph.D., (l) Drug dose (1 ˆ a little, 2 ˆ a moderate amount, 3 ˆ a Ed.D., and M.D.; no participant had any other doctoral lot). Table 1 gives data only for the 23 participants who reported being possibly affected by drugs at the time of testing.
(m) Health index (0 ˆ poor, 1 ˆ fair, 2 ˆ good, 3 ˆ excellent). The health index was the mean of three items:‘‘How would you rate your health?’’ (Excellent, Good, Fair, The divergent thinking variables were obtained from two tests: Poor); ‘‘How much concern do you have about your health?’’ word association and alternate uses. Eleven of the 400 (Not concerned, Mildly concerned, Concerned, Very much participants did not take the word-association test and 8 did concerned); and ‘‘How impaired are you in your everyday not take the alternate uses test, but all 400 took at least one of activities because of your health?’’ (None, Little, Some, A lot).
these tests. The variables assessed with these tests are identi edin the following paragraphs and the mean scores of the age The data in Table 1 indicate that except for the gender groups are presented in the bottom panel in Table 4.
distributions, the age groups were reasonably typical of the (a) Associational uency, or ‘‘verbal productive thinking’’ respective age-range populations. Details about residence and (Horn, 1978a, b), was assessed with a 12-item word-associa- recruitment procedures are reported elsewhere (Reese, Lee, tion test constructed for this study (Session 1, Task 2). The stimulus items, in order of presentation, were husband, answer,garden, hand, doctor, trouble, order, sweet, of ce, thief, problem, and table, each with a 30-second time limit. The criteria forselecting the items were high frequency, at least one paradig- Four intellectual variables other than divergent thinking and matic and one syntagmatic association within the two moderator variables were assessed. They are identi ed in associates in the Postman (1970) or Palermo and Jenkins the following paragraphs and the mean scores of the age groups (1964) association norms, and at least ve associates within the are presented in the Results section in the top panel in Table 4.
rst 90% of the associates (i.e., the relative frequency (a) Inductive reasoning was assessed with the Letter Sets test accumulated over the ve most frequent associates was 90% (Session 1, Task 3), using the standard scoring procedure or less). Each stimulus item was read to the participant and was (Eckstrom, French, Harman, & Derman, 1976). This test printed on a card that remained visible throughout the 30- consists of 15 items, each with ve four-letter sets; in four sets second response period. Responses were given orally and were the letters are combined consistently with a rule (different for tape recorded for later transcription. The score was the mean each item) and in the other set the combination is inconsistent number of associations per item (total number of associations, with this rule. The participant is asked to nd the rule and to divided by 12). For each item, only the rst instance of a (b) Memory span was assessed with the forward and (b) Production uency, (c) exibility, and (d) originality were backward Digit Span tests from the Wechsler Adult Intelli- assessed with a two-item ‘‘alternate uses’’ test (Session 2, Task gence Scale–Revised (Session 1, Tasks 4 and 5), using the 5). In this test, the participants were asked to respond rst to standard scoring procedure: 1 point for each correct trial, ‘‘coat hanger’’ and then to ‘‘brick’’, giving ‘‘unusual uses’’ summed across the forward and backward tests (Wechsler, without an effective time limit for either item. Speci cally, the 1981). In our study the Pearson correlation between scores on participant was told, ‘‘I’m going to name an everyday object, the forward and backward tests was moderately strong, r ˆ .57, and I’d like you to tell me as many unusual uses of the object p < .0001, and although it increased across age groups, the you can think of’’. Three minutes were to be allowed for each increase was nonsigni cant, r ˆ .46, .52, .59, .64, ps for item, with up to two prompts to continue if the participant adjacent age groups > .50, p for young versus old-old > .07.
stopped responding, but all participants received the two (c) Intellectual speediness was assessed with the Finding A’s prompts and stopped responding a third time before three test (Session 2, Task 1), using the standard scoring procedure minutes had elapsed. The responses were tape recorded and (Eckstrom et al., 1976). This is a speed test in which the participant crosses out words that contain the letter ‘‘a’’; the Details of the scoring procedures are given elsewhere (Reese test has two parts, each with a 2-minute time limit for assessing et al., 2000). Brie y, the gists of the transcribed responses and 820 words arranged on four pages with ve 41-word columns the superordinate categories of the gists were identi ed and per page. The participant is informed that each column were counted to obtain, respectively, the uency and exibility contains ve words to be crossed out.
scores. The total number of different gists identi ed was 1127 (d) Vocabulary was assessed with the vocabulary test from for coat hanger and 947 for brick; the total number of different the WAIS-R (Session 1, Task 9), using the standard scoring superordinate categories identi ed was 14 for coat hanger and 16 for brick. Examples for coat hanger are the transcribed (e) Depression was assessed with the Center for Epidemio- responses ‘‘Make an antenna for a car radio’’ and ‘‘Hook it up logical Studies Depression Scale (Session 2, Task 10), using to the radio and use it as an antenna’’. The gists were identi ed the standard scoring procedure (U.S. Department of Health, as ‘‘Car antenna’’ and ‘‘Radio antenna’’ and the superordinate Education and Welfare, 1980). This scale is believed to be category was identi ed as ‘‘Equipment’’, which for a coat valid in the normal (nonclinical depression) range.
hanger was de ned as an object that functions passively or that INTERNATIONAL JOURNAL OF BEHAVIORAL DEVELOPMENT, 2001, 25 (6), 491–500 is acted on in the course of some use. Examples for brick are identi cation of the subordinate-level categories of the gists— the transcribed responses ‘‘Use it to chock a car wheel’’ and but this aspect occurred in the development of a dictionary of ‘‘Put it behind a wheel or something, you know, to keep things subordinate-level categories. The dictionary (in Reese et al., from rolling’’. The gists were identi ed as ‘‘Car chock’’ and 2000) was developed by a joint effort of the four investigators ‘‘Keep things from rolling’’ and the category was identi ed as and a graduate research assistant. After the dictionary had been ‘‘Instrument’’, which for a brick was de ned as an object used developed, the scoring of originality was completely objective to aid some action or used with some other object.
because the dictionary gave the subordinate-level category for Originality was scored on the basis of the statistical each of the 2074 gists that were identi ed.
unusualness of subordinate-level categories (Mervis & Rosch, Internal consistency reliabilities of the four divergent 1981) of the gists rather than on the basis of the statistical thinking measures were also assessed. The index used for unusualness of the gists themselves, which we believed might uency was Cronbach’s alpha based on the be too closely associated with vocabulary size. The data uency scores counted separately for each of the 12 items; the con rmed this belief and the effectiveness of our solution; as index used for production uency, exibility, and originality indicated later (in Table 3), vocabulary was signi cantly was the Pearson correlation between the scores for the coat related to production uency, which is based on gists, and hanger and brick items, corrected with the Spearman–Brown was not signi cantly related to originality based on subordi- formula. All of the obtained internal consistencies were nate-level categories of gists. We used subordinate-level statistically signi cant (ps < .001). The internal consistencies categories because superordinate categories are too general for associational uency (.93), production uency (.83), and for assessing originality. Examples of subordinate-level cate- exibility (.71) were high and fully adequate. The internal gories are ‘‘Antenna’’ for ‘‘Car antenna’’ and ‘‘Radio antenna’’ consistency for originality was low (.40), but still at a level and ‘‘Chock’’ for ‘‘Car chock’’ and ‘‘Keep things from judged to be adequate when sample sizes and group differences rolling’’. The number of participants in the overall sample are large, as in the present study (Thorndike & Hagen, 1955, who used each subordinate-level category was counted and this pp. 139–140). Thus, the tests provided internally consistent number was assigned to each subordinate-level category that a information, though less so for originality than for the other participant used. The participant’s originality score was based on the sum of these numbers, divided by the number ofsubordinate-level categories the participant used. The score Dimensionality of divergent thinking. We used two steps to test that was recorded and analysed was the complement of this quotient, so that higher scores indicated more originality.
uency, exibility, and originality are aspects of a single kind of thinking that is different from other intellectual abilities. In the rst step, we ran an exploratory factor analysis (principalcomponents with varimax rotation and Kaiser normalisation), The participants were tested individually in two sessions about which showed that the four putative divergent thinking two or three days apart (range ˆ 0 to 9 days); the means were variables constituted one factor and that the other six 1.97, 2.42, 2.52, and 2.77 days for the respective age groups.
intellectual variables constituted other factors (for details, see On average, each session lasted about an hour or two (range ˆ Reese et al., 2000). Consistent with these results, hierarchical 0.8 to 4.6 hours); the Session 1 means were 1.47, 1.57, 1.61, multiple regression analyses, summarised in the next subsec- and 1.64 hours for the respective age groups and the Session 2 tion, showed that three of the four divergent thinking variables means were 1.54, 1.73, 1.80, and 1.79 hours (session were signi cantly but only moderately related to ve of the durations were recorded for only about two-thirds of the participants). The only statistically signi cant correlations of In the second step, we tested the linearity and strength of these procedural variables with the divergent thinking variables relations among the divergent thinking variables, using were negligible—Session 2 duration correlated ¡.184 (p < hierarchical multiple regression analyses in which the age .004) with associational uency and .148 (p < .020) with groups were combined and the linear, quadratic, and cubic originality (largest other j r j ˆ .075, p > .24).
components of each ‘‘independent’’ variable were entered inthat sequence. The results are summarised in Table 2. All ofthe obtained correlations were positive, as expected, but not all were linear. (a) Associational uency and (b) originality werelinearly related to each of the other three divergent thinking Because of the large sample size, the probability of a Type I variables, (c) production uency was curvilinearly related to error was set at .01 except for tests of simple effects, for which associational uency and originality and curvilinearly related toproduction uency. The presence of curvilinear relations indicates that these variables constitute separate dimensionsof divergent thinking.
Reliabilities of the divergent thinking measures. The scoring ofproduction Relations of divergent thinking to other intellectual coding decisions; therefore, the inter-scorer reliabilities (Pear- son correlations) were assessed with a 22% sample of theprotocols scored by independent scorers. For the coat hanger The linearity of relations among variables is often not tested in and brick items, respectively, they were .95 and .89 for correlational research. However, testing it is important because production uency and .88 and .90 for exibility.
although the usual index of relation—the Pearson correlation The scoring of originality had a subjective aspect— coef cient—is a valid estimate of the accuracy of prediction REESE ET AL. / DIVERGENT THINKING IN ADULTHOOD Table 2
Hierarchical regression tests of linearity of relations among the divergent thinking variables
Relations with associational uency Note: Data are included only for components that signi cantly increased R2 (alpha ˆ .01).
aF for increment in R2. bFor the quadratic component, R ˆ .295; increment in R2 ˆ .009; p for increment in R2 ˆ whenever a linear prediction equation is used, it is a valid The main effect of gender was signi cant only for estimate of the strength of relation only if the true relation is depression (p < .0001); women had a higher mean (13.58) linear (e.g., Blommers & Lindquist, 1960). In the present than men (9.28). However, the main effect of gender study, the linearity and strength of relations among the ‘‘approached’’ signi cance for memory span, F(1, 392) ˆ variables were tested with hierarchical multiple regression 5.44, p < .021, favouring men (14.72 vs. 13.84), and for analyses in which the age groups were combined and the linear, intellectual speediness, F(1, 391) ˆ 6.16, p < .014, favouring quadratic, and cubic components of each independent variable women (52.81 vs. 49.48) (smallest other p > .06). The age were entered in that sequence. These analyses are summarised group by gender interaction was not signi cant for any of the rst six panels in Table 3. Depression was not variables (smallest p > .10).
signi cantly related to any of the divergent thinking variables,but the other intellectual variables were signi cantly related to Divergent thinking variables. The bottom panel in Table 3 all except originality. All of the signi cant relations were shows hierarchical multiple regressions of the divergent moderate, linear, and positive. The strongest relations were for thinking variables on age. As can be seen, associational uency vocabulary (the mean of the signi cant correlations was was signi cantly related to the linear component of age and 0.309), followed closely by education (mean 0.275) and had virtually no relation to the quadratic component of age. In inductive reasoning (mean 0.273) and less closely by intellec- contrast, production uency, exibility, and originality had no tual speediness (mean 0.210) and memory span (mean 0.186).
signi cant relation to the liner component of age but weresigni cantly related to the quadratic component of age. The Relations of variables to age and gender least-squares regression equations—linear for associational uency and curvilinear for the other variables—are shown Variables other than divergent thinking. The top panel in Table graphically in Figure 1, with divergent thinking scores 4 shows the age group means on the six intellectual variables transformed into standard scores (M ˆ 50, SD ˆ 10). As other than divergent thinking. The pairwise differences in this can be seen, the regression line for production originality was panel (and the bottom panel) were assessed with Fisher’s LSD somewhat different from the lines for production uency and test; the Newman–Keuls, SheffeÂ, and Tukey tests are more exibility, which were virtually identical, and all three of these popular, but they are too conservative with respect to Type II lines re ect stronger age differences than the straight line for errors (Reese, 1970). As can be seen, the main effect of age group was signi cant for all six variables. Vocabulary and To assess the joint effects of age and gender on divergent education peaked in middle-age and the means for the other thinking, we began with a multivariate analysis of variance four variables were highest in the young group and generally including all four divergent thinking variables. This analysis revealed signi cant main effects of age group and gender and INTERNATIONAL JOURNAL OF BEHAVIORAL DEVELOPMENT, 2001, 25 (6), 491–500 Table 3
Hierarchical regression tests of linearity of relations of the six intellectual variables and age with the four divergent
thinking variables

Relations with inductive reasoning Relations with intellectua l speediness Note: Data for linear component are included regardless of statistical signi cance. Data for quadratic and cubic components are included only if increment in R2 was signi cant (alpha ˆ .01), except for quadratic component of age no signi cant age group by gender interaction: respectively, the latter variables, however, the main effect of age group met a Pillai’s trace ˆ 0.139, 0.041, 0.033; multivariate F(12, 1125; 4, lenient criterion of signi cance (alpha ˆ .05) and the 373; 12, 1125) ˆ 4.54, 3.99, 1.03; p < .001, <.004, >.41. In regression analysis (Table 3) indicated strictly signi cant follow-up analyses, each divergent thinking variable was relations to age. We therefore analysed the simple effects for analysed in a separate univariate analysis of variance with age these variables as well as for production uency and exibility.
group and gender as independent variables.
The age group means are shown in the bottom panel in The univariate analyses of variance revealed signi cant main Table 4. As can be seen, the young group exhibited more effects of age group for production uency and exibility, but difference was signi cant only for the young versus old-old uency: F(3, 384) ˆ 7.63, p < .001; exibility: F(3, 384) ˆ contrast. The table also shows that production 7.73, p < .001; originality: F(3, 384) ˆ 3.38, p < .019; exibility, and originality were greatest in the middle-aged associational uency; F(3, 381) ˆ 2.79, p ˆ .041). For both of group and least in the old-old group, but that not all of the REESE ET AL. / DIVERGENT THINKING IN ADULTHOOD Table 4
Age group means (and standard deviations) on the intellectual and divergent thinking variables
Note: (1) Means with the same superscript letter within a row were signi cantly different from each other (alpha < .05). (2) The last column contains the probability of the main effect of age group in agegroup £ gender analyses of variance. (3) Each age group mean is the mean of the male and female subgroup means, unweighted by subgroup size. (4) Standard deviations are in parentheses.
aHigh score indicates strong depression (maximum ˆ 60). bThe tests of simple effects were statistically unjusti ed because the main effect was nonsigni cant.
pairwise differences were signi cant. For production uency of the separate age groups. Also, like production uency and exibility, (a) the middle-aged group had signi cantly exibility it was curvilinearly related to age (Table 3). On the higher means than each of the other age groups and (b) the other hand, it was different from the other dimensions of young-old group had signi cantly higher means than the old- divergent thinking: Unlike the other dimensions, it was not old group, but (c) the young group was signi cantly different signi cantly correlated with any of the six other intellectual from only the middle-aged group. For originality, the old-old variables (Table 3) and unlike production group had a signi cantly lower mean than each of the other age exibility, it exhibited only a ‘‘marginally’’ signi cant main groups, which did not differ signi cantly from one another.
effect of age group in the age group by gender analyses of The univariate analyses of variance also revealed that the main effect of gender was not signi cant for any variable,although it met a lenient criterion of signi cance for associa-tional uency, on which women outscored men (6.32 vs. 5.79), Relations to other intellectual variables F(1, 381) ˆ 6.16, p < .014; smallest other p > .38. The age group by gender interaction was nonsigni cant in all four As expected, divergent thinking was found to be different from analyses, smallest p > .15.
the other intellectual variables but related to them. Thestrongest relations of divergent thinking were with the‘‘structural resource’’ variables—vocabulary and perhaps education—for which the mean of the signi cant correlations(Table 3) was .292, and the two ‘‘process’’ variables: inductive This study dealt with the nature of divergent thinking in reasoning and memory span (mean 0.229). The relations with adulthood and its relation to other intellectual variables, age, the ‘‘dynamic resource’’ variables were weaker. Intellectual and gender. These issues are discussed in that order.
speediness had some relation (mean 0.210); but depression,the absence of which we tentatively classi ed in this category, was not signi cantly related to divergent thinking. The lastresult was unexpected, but its generality is as yet unknown.
Our results are consistent with the implication of Goff’s (1992) Lewinsohn, Seeley, Roberts, and Allen (1997) found no study that divergent thinking consists of separate dimensions.
relation of depression to a composite of cognitive tests in older On the one hand, our exploratory factor analyses (Reese et al., adults (50–96 years), but Luszcz et al. (1997) obtained 2000) showed that originality was a dimension of divergent signi cant relations to memory abilities in very old adults thinking, not only in the combined age groups but also in each INTERNATIONAL JOURNAL OF BEHAVIORAL DEVELOPMENT, 2001, 25 (6), 491–500 Figure 1. Plots of regressions of divergent thinking on age. The divergent thinking scores were standardised with means of 50 and standard
deviations of 10; the curves were derived from statistically significant components of age (Table 3) as predictors in least-squares regression
equations—linear for associational fluency and curvilinear for production fluency, flexibility, and originality.
and Ripple (1981), and the decline after middle age is in additionconsistent with the ndings of Lehman (1953), Guilford (1967), We found marked age group differences in divergent thinking Alpaugh and Birren (1977), and McCrae et al. (1987).
as re ected by production uency and exibility, but not as Given that uid intelligence increases until early middle age re ected by originality and associational uency, for which the and then declines (e.g., Schaie & Labouvie-Vief, 1974), the age main effect of age group did not meet our conservative trends might suggest that divergent thinking is a kind of uid criterion of signi cance (Table 4). However, both of the latter intelligence. We included only one marker of variables were positively and signi cantly correlated with age gence—inductive reasoning—and inconsistent with this sug- (Table 3). Production uency, exibility, and originality were gestion, it was somewhat less strongly correlated with divergent curvilinearly related to age, but associational thinking than was crystallised intelligence (indexed by voca- linearly related to age (Tables 3 and 4). Baltes and Lindenberger (1997) also obtained a curvilinear relation ofassociational uency to age in a sample comparable to ours insize (N ˆ 315) and age range (25–101 years) but different in nationality (German) and—presumably more importantly—with different measures of associational uency (Baltes and Some previous research indicated gender differences in verbal Lindenberger did not assess divergent production).
creativity, especially for young participants. In the present For production uency, exibility, and originality, two major study, however, gender had no signi cant effect on any kinds of age group differences emerged: First, the middle-aged divergent thinking variable, although it ‘‘approached’’ signi - group had the largest mean on these variables, although not cance on associational uency (p < .014). The interaction signi cantly larger in some comparisons; and second, the old- between gender and age group did not even approach old group had the lowest mean on these variables, although not signi cance for any variable. Thus, in the heterogeneous signi cantly lower in some comparisons. The curves for population that was sampled in the present study, gender is production uency, exibility, and originality (Figure 1) show evidently not an important determinant of divergent thinking these age differences very clearly. The peaking of divergent and not an important moderator of the effect of age on thinking in middle age is consistent with the ndings of Jaquish REESE ET AL. / DIVERGENT THINKING IN ADULTHOOD Gilhooly, K.J. (1988). Thinking: Directed, undirected and creative (2nd ed.).
Measures of divergent thinking consist of at least three Goff, K. (1992). Enhancing creativity in older adults. Journal of Creative dimensions, or outcome variables— uency, Behavior, 26, 40–49.
Guilford, J.P. (1967). The nature of human intelligence. New York: McGraw-Hill.
originality. Fluency and exibility are highly correlated with Holman, J., Goetz, E.M., & Baer, D.M. (1977). The training of creativity as an each other and only moderately correlated with originality; operant and an examination of its generalization characteristics. In B.C. Etzel, J.M. LeBlanc, & D.M. Baer (Eds.), New developments in behavioral research:Theory, method, and application (pp. 441–471). Hillsdale, NJ: Erlbaum.
operations that are at least highly similar and different from the Horn, J.L. (1978a). Human ability systems. In P.B. Baltes (Ed.), Life-span mental operations underlying originality. Whatever these development and behavior (Vol. 1, pp. 211–256). New York: Academic operations are, they evidently correlate moderately with structural resource variables and process variables, and less Horn, J.L. (1978b). The nature and development of intellectua l abilities. In R.T.
Osborne, C.E. Noble, & N. Weyl (Eds.), Human variation: The biopsychology of so with dynamic resource variables. This generalisation seems age, race, and sex (pp. 107–136). New York: Academic Press.
to be valid, at least with respect to the variables assessed in this Jaquish, G.A., & Ripple, R.E. (1981). Cognitive creative abilities and self-esteem study, because the sample size was relatively large and the across the adult life-span. Human Development, 24, 110–119.
Kausler, D.H. (1991). Experimental psychology, cognition, and human aging (2nd demographics of the age-group samples were representative of the respective age-group populations.
Krauss, I.K. (1980). Between- and within-group comparisons in aging research.
Gender differences in divergent thinking are evidently In L.W. Poon (Ed.), Aging in the 1980s: Psychological issues (pp. 542–551).
negligible, but age-group differences are large. The age-group Washington, DC: American Psychological Association.
La Rue, A., Dessonville, C., & Jarvik, L.F. (1985). Aging and mental disorders.
similarities and differences obtained in this study suggest that In J.E. Birren & K.W. Schaie (Eds.), Handbook of the psychology of aging (pp.
the operations underlying divergent thinking are the same at all 664–702). New York: Van Nostrand Reinhold.
adult ages but vary with age in how effectively or ef ciently Lehman, H.C. (1953). Age and achievement. Princeton, NJ: Princeton University they are used. Speci cally, effectiveness or ef ciency peaks in Lewinsohn, P.M., Seeley, J.R., Roberts, R.E., & Allen, N.B. (1997). Center for middle age and declines markedly especially in the later portion Epidemiologic Studies Depression Scale (CES-D) as a screening instrument of old age. The decline in old age is expectable, given its for depression among community-residing older adults. Psychology and Aging, ubiquity in other research; but the peak in middle age is an Luszcz, M.A., Bryan, J., & Kent, P. (1997). Predicting episodic performance of important nding because except for vocabulary, which is a very old men and women: Contributions from age, depression, activity, structural resource variable, most other cognitive variables cognitive ability, and speed. Psychology and Aging, 12, 340–351.
exhibit statistically signi cant peaks in early adulthood, as in McCrae, R.R., Arenberg, D., & Costa, P.T., Jr. (1987). Declines in divergent thinking with age: Cross-sectional, longitudinal , and cross-sequential analysis.
Psychology and Aging, 2, 130–137.
Meadow, A., Parnes, S.J., & Reese, H. [W.] (1959). In uence of brainstorming instructions and problem sequence on a creative problem solving test. Journalof Applied Psychology, 43, 413–416.
Mervis, C.B., & Rosch, E. (1981). Categorizatio n of natural objects. Annual Review of Psychology, 32, 89–115.
Osborn, A.F. (1963). Applied imagination: Principles and procedures of creative problem-solving (3rd rev. ed.). New York: Scribner’s.
Palermo, D.S., & Jenkins, J.J. (1964). Word association norms: Grade school Agarwal, S., & Kumari, S. (1982). A correlational study of risk-taking and through college. Minneapolis, MN: University of Minnesota Press.
creativity with special reference to sex differences. Indian Educational Review, Postman, L. (1970). The California norms: Association as a function of word frequency. In L. Postman & G. Keppel (Eds.), Norms of word association (pp.
Alpaugh, P.K., & Birren, J.E. (1977). Variables affecting creative contributions 241–320). New York: Academic Press.
across the adult life span. Human Development, 20, 240–248.
Reese, H.W. (1970). Multiple comparison methods. American Psychologist, 25, Baltes, P.B. (1993). The aging mind: Potential and limits. The Gerontologist, 33, Reese, H.W., Lee, L.-J., Cohen, S.H., & Puckett, J.M., Jr. (2000). Effects of Baltes, P.B., & Lindenberger , U. (1997). Emergence of a powerful connection intelligence, age, and sex on divergent thinking in adulthood. Unpublished paper, between sensory and cognitive functions across the adult life span: A new West Virginia University, Morgantown, WV.
window to the study of cognitive aging? Psychology and Aging, 12, 12–21.
Ruth, J.E., & Birren, J.E. (1985). Creativity in adulthood and old age: Relations Baltes, P.B., Reese, H.W., & Nesselroade, J.R. (1988). Life-span developmental to intelligence , sex, and mode of testing. International Journal of Behavioral psychology: Introduction to research methods. Hillsdale, NJ: Erlbaum.
Development, 8, 99–109.
Barron, F., & Harrington, D.M. (1981). Creativity, intelligence , and personality.
Salthouse, T. [A.] (1985). A theory of cognitive aging. Amsterdam: North- Annual Review of Psychology, 32, 439–476.
Bharadwaj, R. (1985). Intelligence , sex, and age as correlates of the components Salthouse, T.A. (1988). Resource-reductio n interpretations of cognitive aging.
of creativity. Asian Journal of Psychology and Education, 16, 41–44.
Developmental Review, 8, 238–272.
Bitterman, M.E. (1960). Toward a comparative psychology of learning.
Schaie, K.W., & Hertzog, C. (1983). Fourteen-yea r cohort-sequentia l analyses American Psychologist, 15, 704–712.
of adult intellectua l development. Developmental Psychology, 19, 531–543.
Blommers, P., & Lindquist, E.F. (1960). Elementary statistical methods in Schaie, K.W., & Labouvie-Vief, G. (1974). Generational versus ontogeneti c psychology and education. Boston, MA: Houghton Mif in.
components of change in adult cognitive behavior: A fourteen-yea r cross- Botwinick, J. (1984). Aging and behavior: A comprehensive integration of research sequential study. Developmental Psychology, 10, 305–320.
ndings (3rd ed.). New York: Springer.
Simonton, D.K. (2000). Creativity: Cognitive, personal, developmental, and Bromley, D.B. (1956). Some experimental tests of the effect of age on creative social aspects. American Psychologist, 55, 151–158.
intellectua l output. Journal of Gerontology, 11, 74–82.
Standard occupational classi cation manual (1980). Washington, DC: U.S.
Chi, M.T.H., & Ceci, S.J. (1987). Content knowledge: Its role, representation, Department of Commerce, Of ce of Federal Statistical Policy and and restructuring in memory development. In H.W. Reese (Ed.), Advances in child development and behavior (Vol. 20, pp. 91–142). Orlando, FL: Academic Sternberg, R.J. (1985). Implicit theories of intelligence , creativity, and wisdom.
Journal of Personality and Social Psychology, 49, 607–627.
Denney, N.W. (1990). Adult age difference s in traditional and practical problem Thorndike, R.L., & Hagen, E. (1955). Measurement and evaluation in psychology solving. In E.A. Lovelace (Ed.), Aging and cognition: Mental processes, self- and education. New York: Wiley.
awareness and interventions (pp. 329–349). Amsterdam: North-Holland.
U.S. Department of Health, Education and Welfare. (1980). Basic data on Dennis, W. (1966). Creative productivity between the ages of 20 and 80 years.
depressive symptomatology, United States, 1974–75. Vital and Health Journal of Gerontology, 21, 1–8.
Statistics-Series 11, No. 216. Hyattsville, MD: Department of Health, Eckstrom, R.B., French, J.W., Harman, H., & Derman, D. (1976). Kit of factor- referenced cognitive tests, 1976 revision. Princeton, NJ: Educational Testing Wechsler, D. (1981). WAIS-R manual: Wechsler Adult Intelligence Scale—Revised. New York: Psychological Corporation.


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Eyup Akgün Education/Training University of Marburg, Marburg, Germany, B.S. (Chemistry) University of Marburg, Marburg, Germany, M.S. (Organic Chemistry) University of Marburg, Marburg, Germany, Ph.D. (Medicinal Chemistry) Assoc. Prof. (registered Technical University of Istanbul) Faculty of no tenure tract of University of Pittsburgh; Pittsburgh, PA Faculty of no tenure tract

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