Cognitive Reserve and Creative Thinking in Aging: A Cross-Sectional Study on the Role of Education, Occupation, and Leisure Activities

Abstract

Cognitive reserve (CR) is widely recognized as a protective factor that supports cognitive functioning across the lifespan. Recent research suggests a reciprocal relationship between CR and creative thinking—particularly divergent thinking (DT)—with DT potentially contributing to and benefiting from CR and remaining relatively preserved in older adulthood. This cross-sectional study, conducted in Italy between April and July 2025 using convenience sampling, examined whether CR predicts verbal and conceptual creativity in healthy older adults. One hundred participants (aged 65–92 years; M = 68.45, SD = 8.12) completed the Cognitive Reserve Index questionnaire (CRIq), the Test di Intelligenza Breve (TIB; Short Intelligence Test), and two creativity tasks. Data were analyzed using IBM SPSS Statistics (version 25.0; IBM Corp., Armonk, NY, USA). Multiple regression analyses showed that overall CR significantly predicted all creativity outcomes, including verbal fluency (β = 0.316, p = 0.011) and flexibility (β = 0.336, p = 0.007), as well as conceptual fluency (β = 0.371, p = 0.003), flexibility (β = 0.381, p = 0.002), and originality (β = 0.338, p = 0.006). Education and leisure activities more strongly predicted verbal creativity, whereas occupational experience and leisure activities predominantly predicted conceptual creativity. These findings indicate that CR supports creative thinking in later life and highlight the importance of cognitively and socially enriched experiences across the lifespan.

1. Introduction

The considerable interindividual variability observed in cognitive aging highlights the need to understand the factors that underlie it [1,2,3]. Among these factors, a central role has been attributed to cognitive reserve (CR), a multidimensional construct reflecting the brain’s capacity to maintain cognitive performance despite age- or pathology-related neural changes [4,5,6]. According to Stern’s [5] model, CR encompasses the set of cognitive and experiential resources that enable individuals to optimize information processing and recruit alternative strategies or compensatory neural networks in response to structural or functional brain alterations [5,6]. Initially conceptualized through educational attainment, the notion of CR has progressively expanded to include occupational complexity, leisure engagement, and other cognitively stimulating activities accumulated across the lifespan, and is now regarded as a latent construct inferred from behavioral, experiential, and lifestyle indicators [6,7,8,9]. Numerous studies have demonstrated that CR acts as a protective factor against cognitive decline and the onset of dementia-related symptoms, even in the presence of significant neuropathology [10,11,12]. Creative thinking, particularly divergent thinking (DT), has been proposed as both a contributor to and a manifestation of CR, as it can remain preserved during aging and support the maintenance of cognitive functioning, with beneficial effects in both healthy and clinical populations [13,14,15,16,17,18]. Creative thinking refers to the ability to generate ideas that are novel, original, and contextually appropriate, breaking automatic response patterns and fostering alternative behaviors, particularly in unfamiliar or complex situations [13,16,19,20]. Within this framework, DT, the ability to identify multiple possible solutions to open-ended tasks or problems, represents a complex cognitive construct that involves both crystallized intelligence and executive processes such as the inhibition of habitual responses, attentional flexibility, and the capacity to form novel semantic associations [15,21]. DT therefore constitutes a valuable cognitive measure for assessing an individual’s creative potential [20,22]. A central component of DT is verbal divergent production, defined as the ability to generate multiple ideas, solutions, or associations in response to a linguistic stimulus [23,24]. Recent neuropsychological evidence suggests that this ability may serve as a form of cognitive stimulation capable of mitigating or delaying cognitive decline [16]. These findings support the hypothesis that training in generating multiple and flexible ideas may exert a protective effect comparable to that of other activities contributing to CR [2].

Empirical evidence indicates a positive relationship between CR and DT in older adults [2,15,16,17]. Both CR and creative thinking depend on the efficient and flexible use of cognitive resources, adaptive problem-solving, and the recruitment of alternative or compensatory neural networks [25,26,27]. From this perspective, CR may provide a cognitive foundation for creative thinking by supporting the metacognitive control and cognitive flexibility required for divergent thought and the original recombination of information [15,28]. Conversely, engagement in creative thinking may contribute to the development or preservation of CR through sustained cognitive stimulation [29,30]. Recent findings further indicate that CR and psychological well-being are significant predictors of DT performance across different sociocultural contexts [17]. This bidirectional relationship aligns with multidimensional models of positive aging, which emphasize how cognitively stimulating occupations, enriching leisure activities, and domain-specific skills interact to enhance both cognitive flexibility and personal generativity [2,31]. Together, these findings suggest that DT and CR mutually reinforce each other, promoting adaptive cognitive and psychological functioning in later life. In line with this evidence, the theoretical model of the present study conceptualizes CR as a multidimensional predictor of creative thinking in older adults. Specifically, the model assumes that higher levels of CR enhance the cognitive and metacognitive processes that support both verbal and conceptual DT. Educational experiences are expected to strengthen verbal and linguistic resources underlying verbal fluency and flexibility, whereas occupational complexity and diverse leisure activities are hypothesized to foster broader cognitive flexibility, semantic expansion, and problem-solving strategies relevant to conceptual creativity. Moreover, the model presumes domain-specific pathways, whereby different components of CR contribute uniquely to distinct creativity outcomes, reflecting the differentiated cognitive demands of verbal versus conceptual DT. Thus, CR is theorized to serve both as a general facilitator of creative performance and as a domain-specific predictor shaped by the qualitative nature of lifelong cognitive experiences.

The Present Study

Building on this theoretical framework, the present study aims to investigate whether, and to what extent, CR predicts performance across multiple domains of creativity—both verbal and conceptual—in a sample of healthy older adults. Creativity was assessed using two tasks: one targeting verbal creativity (Acronyms Task: Fluency and Flexibility) and one targeting conceptual creativity (Alternative Uses Task: Fluency, Flexibility, and Originality). It was hypothesized that

H1. 

General CR Effects on Creativity. Higher overall CR would positively predict both verbal and conceptual creativity, reflecting the general role of accumulated cognitive resources and adaptive mechanisms in supporting creative thinking.

H2. 

Role of Occupational and Leisure Experiences. Engagement in creative occupations and greater frequency and diversity of cognitively or socially stimulating leisure activities would significantly predict higher creativity scores, even after controlling for education.

H3. 

Domain-Specific Effects of CR. Components of CR related to verbal and experiential engagement would differentially predict creativity measures: (a) verbal creativity (Acronyms Task: Fluency and Flexibility) would be more strongly associated with education and verbally demanding experiences (e.g., professional training, leisure activities involving cognitive/verbal engagement); (b) conceptual creativity (Alternative Uses Task: Fluency, Flexibility, and Originality) would be more strongly associated with diverse occupational and leisure experiences that foster problem-solving and cognitive flexibility.

2. Materials and Methods

2.1. Participants

This cross-sectional study involved one hundred healthy older adults (54 females, 46 males), aged between 65 and 92 years (M = 68.45, SD = 8.12), who took part in the study. Participants were recruited via convenience sampling, through university-affiliated outreach programs, community associations, and local senior centers in the metropolitan areas of Messina and Catania. Participation was voluntary. Inclusion criteria were (a) age 65 years or older, (b) Italian citizenship, and (c) absence of neurological, psychiatric, or medical conditions. Exclusion criteria included the presence of cognitive, sensory, or motor impairments and the current use of psychotropic or illicit substances. Medical history and current use of psychotropic medication were collected via a structured self-report questionnaire administered before the study, together with sociodemographic information. Participants were considered healthy older adults if they did not report any neurological, psychiatric, or medical conditions, cognitive, sensory, or motor impairments, or use of psychotropic or illicit substances. No participant was excluded from the study. All participants provided written informed consent prior to participation, in accordance with the ethical standards of the Declaration of Helsinki. Descriptive characteristics of the sample are presented in

Table 1. Demographic statistics of participants (n = 100).

Measures	Frequency (n)	Percentage (%)
Gender
Female	54	54.0
Male	46	46.0
Age	68.45 (M)	8.12 (SD)
Cohabitation
Alone	41	41.0
With family	59	59.0
Marital status
Married	68	68.0
Single	18	18.0
Widowed	14	14.0
Employment status
Worker	35	35.0
Pensioner	65	65.0
Educational attainment
Elementary school	2	2.0
Middle school graduates	16	16.0
High school graduates	30	30.0
Three-year degree	30	30.0
Master’s degree	22	22.0

Note. n = number of participants; % = percentage; M = mean; SD = standard deviation.

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2.2. Instruments

Medical History and Sociodemographic Questionnaire. A brief self-report questionnaire, specifically designed for this study, was used to collect information on participants’ medical history, current use of psychotropic medication, and sociodemographic characteristics. The medical history section assessed the presence or absence of neurological, psychiatric, and medical conditions, as well as cognitive, sensory, or motor impairments. Participants also reported any current use of psychotropic or other relevant medications. The sociodemographic section collected information on gender, age, cohabitation, marital status, employment status and educational attainment. The questionnaire was administered via Google Forms.

Cognitive Reserve Index questionnaire (CRIq). CR was assessed using the Cognitive Reserve Index questionnaire (CRIq) [7], a semi-structured 20-item interview. The CRIq provides a total score and three subdomain scores—education, occupational activity, and leisure time—based on the duration and frequency of activities from age 18 to the time of assessment. The education domain includes years of formal schooling and vocational training; the occupational activity domain classifies occupations by cognitive complexity and responsibility; and the leisure time domain covers unpaid activities performed with varying frequency. Raw scores were adjusted for age using linear regression and standardized (M = 100, SD = 15). In the present sample, the CRIq showed good overall internal consistency (α = 0.82), while subscales had lower consistency (α = 0.59), as expected for heterogeneous domains [32].

Test di Intelligenza Breve (TIB; Short Intelligence Test). The TIB [33] is a brief intelligence test based on the correlation between general cognitive ability and reading skills. It is primarily used to assess premorbid intellectual functioning and provides an estimate of Full-Scale IQ (FSIQ), age-adjusted. The TIB includes subtests such as Vocabulary, Similarities, and Digit Span, allowing researchers to control for general cognitive abilities in studies examining creativity or other cognitive functions.

Creativity tasks. Creativity was assessed using two tasks: the Acronyms Task [34] and the Alternative Uses Task [34,35]. In the Acronyms Task, participants were asked to generate, within 5 min, as many meaningful expressions as possible for three acronyms (SOS, OMG, TGIF), producing coherent phrases. Fluency (total number of valid responses) and flexibility (variety of categories represented) were scored. In the Alternative Uses Task, participants were asked to list, within 5 min, as many different, unusual, or creative uses as possible for an empty plastic bottle. Fluency, flexibility, and originality were scored according to Torrance guidelines: originality was calculated by identifying responses that were unique or infrequent relative to the sample [35]. All responses were independently coded by two raters, with discrepancies resolved through consensus.

2.3. Procedure

The study, conducted in Italy between April and July 2025, adhered to the principles outlined in the Declaration of Helsinki. All participants took part voluntarily, without receiving any compensation or additional incentives. Prior to participation, they were informed about the study’s objectives, expected duration, and procedures. Participants took part in individual experimental sessions in a controlled laboratory environment, in the presence of a trained research assistant. In the first phase, participants completed the CRIq [7] and the TIB [33], and they were also administered the Acronyms Task [34] and the Alternative Uses Task [34,35]. The order of presentation of the tests was counterbalanced across participants. Each session lasted approximately 60–75 min.

2.4. Statistical Analysis

An a priori power analysis was conducted to determine the required sample size for detecting medium effect sizes with adequate statistical power. The analysis indicated that a minimum of 84 participants was needed to achieve power = 0.80 at α = 0.05.

All statistical analyses were conducted using IBM SPSS Statistics (Version 25.0; IBM Corp., Armonk, NY, USA). Preliminary analyses included inspection of the distribution of all variables, verification of normality assumptions, and identification of potential outliers. Skewness and kurtosis values within ±2 were considered acceptable. Descriptive statistics (means, standard deviations, and ranges) were computed for all measures of CR (education, occupational experience, leisure activities), TIB subtests (Vocabulary, Similarities, Digit Span), and creativity (Acronyms Task: Fluency, Flexibility; Alternative Uses Task: Fluency, Flexibility, Originality). Zero-order correlations were computed to examine the associations among CR indices, TIB subtests, and creativity measures. Multiple linear regression analyses were conducted separately for the two creativity domains as dependent variables: Verbal creativity: Acronyms Task—Fluency and Flexibility; Conceptual creativity: Alternative Uses Task—Fluency, Flexibility, and Originality. Predictor variables included CR components: educational level (years of formal education, CRIq education subscore), occupational status (creative vs. non-creative occupation, derived from CRIq occupational domain), and frequency and diversity of leisure activities (CRIq leisure subscore). Control variables: Age, gender, and general cognitive ability (TIB subtests) were included in all models. Education was not controlled when it served as a predictor. Model diagnostics: Multicollinearity was assessed using Variance Inflation Factors (VIFs), with values below 5 considered acceptable. Standardized beta coefficients (β), t values, and p-values were reported for each predictor. Effect sizes were interpreted according to Cohen [36] with R² and ΔR² indicating the proportion of explained variance. Significance threshold was set at α = 0.05 (two-tailed). Where relevant, Bonferroni-corrected post hoc comparisons were applied. Potential sources of bias were considered and addressed. No missing data were present for any variable; all analyses were conducted on complete cases. Self-selection bias may have occurred due to voluntary participation; to mitigate this, participants were recruited from multiple and diverse community sources. Coding bias in creativity assessments was minimized using independent multiple raters with consensus resolution. Additionally, potential confounding effects of age, gender, and general cognitive ability (IQ) were controlled in all analyses.

3. Results

Means, standard deviations, and observed ranges for all CR, TIB, and creativity measures are reported in

Table 2. Means, standard deviations, and observed ranges for all variables.

Variable	M	SD	Min	Max
CRIq Age-adjusted Standardized Score	104.88	23.66	77.00	121.00
Acronyms Task—Fluency	4.88	2.74	0.00	10.00
Acronyms Task—Flexibility	4.36	3.21	0.00	17.00
Alternative Uses Task—Fluency	4.71	3.30	0.00	20.00
Alternative Uses Task—Flexibility	3.80	2.34	0.00	9.00
Alternative Uses Task—Originality	10.37	9.51	0.00	48.00
TIB—Pronunciation errors	2.28	3.62	0.00	15.00
TIB—Accent errors	4.84	5.61	0.00	26.00
FSIQ	109.14	10.87	73.00	121.13

Note. CRIq = Cognitive Reserve Index questionnaire; TIB = Test di Intelligenza Breve (Short Intelligence Test); FSIQ = full-scale intelligence quotient. M = mean; SD = standard deviation; Min = minimum; Max = maximum. IQ scores are age-adjusted estimates derived from TIB raw scores [33].

.

Participants showed above-average cognitive reserve (CRIq age-adjusted standardized score: M = 104.88, SD = 23.66, range = 77–121) and average age-adjusted general cognitive ability (FSIQ: M = 109.14, SD = 10.87, range = 73–121). Creativity scores across the five measured parameters were as follows: Acronyms Task—Fluency (M = 4.88, SD = 2.74, range = 0–10); Acronyms Task—Flexibility (M = 4.36, SD = 3.21, range = 0–17); Alternative Uses Task—Fluency (M = 4.71, SD = 3.30, range = 0–20); Alternative Uses Task—Flexibility (M = 3.80, SD = 2.34, range = 0–9); and Alternative Uses Task—Originality (M = 10.37, SD = 9.51, range = 0–48). Pearson correlations among CR components, TIB subtests, and creativity measures are reported in

Table 3. Correlations Among CRIq, Creativity Tests, TIB, and Creative Thinking Measures.

Variable	1	2	3	4	5	6	7	8	9
CRIq Age-adjusted Standardized Score	1
Acronyms Task—Fluency	0.316 *	1
Acronyms Task—Flexibility	0.336 *	0.210 *	1
Alternative Uses—Fluency	0.371 **	0.245 *	0.210 *	1
Alternative Uses—Flexibility	0.381 **	0.210 *	0.210 *	0.496 **	1
Alternative Uses—Originality	0.338 **	0.238 *	0.238 *	0.496 **	0.430 **	1
TIB—Accent Errors	−0.379 **	−0.319 **	−0.325 **	−0.496 **	−0.496 **	−0.430 **	1
TIB—Pronunciation Errors	−0.311 **	−0.309 **	−0.313 **	−0.430 **	−0.430 **	−0.430 **	0.496 **	1
FSIQ	0.361 **	0.245 *	0.210 *	0.245 *	0.210 *	0.238 *	−0.479 **	−0.402 **	1

Note. * p < 0.05, ** p < 0.01. IQ scores are age-adjusted estimates derived from TIB raw scores [33].

. Bivariate correlations are presented in Table 3. CRIq age-adjusted standardized scores were positively associated with all creativity outcomes, showing small-to-moderate correlations with Acronyms—Fluency (r = 0.316, p < 0.05); Acronyms—Flexibility (r = 0.336, p < 0.05); Alternative—Uses Fluency (r = 0.371, p < 0.01); Alternative Uses—Flexibility (r = 0.381, p < 0.01); and Alternative Uses—Originality (r = 0.338, p < 0.01). General cognitive ability (FSIQ) was also positively related to CRIq (r = 0.361, p < 0.01) and to the creativity measures (rs = 0.210–0.245, ps < 0.05). By contrast, higher error rates on the TIB indices were negatively associated with CRIq and creativity (e.g., Accent Errors with CRIq: r = −0.379, p < 0.01; Pronunciation Errors with CRIq: r = −0.302, p < 0.01), and were negatively related to FSIQ (Accent Errors: r = −0.479, p < 0.01; Pronunciation Errors: r = −0.402, p < 0.01). Finally, the Alternative Uses indices were intercorrelated (e.g., Fluency with Flexibility: r = 0.496, p < 0.01; Fluency with Originality: r = 0.496, p < 0.01; Flexibility with Originality: r = 0.430, p < 0.01), and the two TIB error indices were positively related to each other (r = 0.496, p < 0.01).

Multiple regression analyses were conducted to examine predictors of verbal (Acronyms) and conceptual creativity (Alternative Uses). Predictors included age, gender, general cognitive ability (TIB-derived FSIQ), education, occupational experience, leisure activities, and CRIq total score. As shown in

Table 4. Multiple Regression Analyses Predicting Verbal and Conceptual Creativity from the CR Component.

Predictor	β	SE	t	p	VIF	95% CI [LL, UL]
Acronyms Task—Fluency
Age	−0.071	0.115	−0.62	0.537	1.42	[−0.296, 0.154]
Gender	−0.084	0.115	−0.73	0.468	1.38	[−0.310, 0.142]
TIB (FSIQ)	−0.112	0.111	−1.01	0.316	1.55	[−0.331, 0.107]
Education (years)	0.284	0.119	2.38	0.021	1.92	[0.050, 0.518]
Occupational experience	0.225	0.114	1.98	0.052	2.05	[−0.001, 0.451]
Leisure activities	0.241	0.112	2.15	0.035	1.88	[0.020, 0.462]
CRIq Total Score	0.316	0.119	2.64	0.011	2.14	[0.082, 0.550]
Model R2 = 0.31, Adj. R2 = 0.27; F(7, 92) = 5.88, p < 0.001
Acronyms Task—Flexibility
Age	−0.066	0.112	−0.59	0.556	1.42	[−0.287, 0.155]
Gender	−0.075	0.107	−0.70	0.487	1.38	[−0.286, 0.136]
TIB (FSIQ)	−0.121	0.108	−1.12	0.266	1.55	[−0.333, 0.091]
Education (years)	0.271	0.119	2.27	0.026	1.92	[0.037, 0.505]
Occupational experience	0.212	0.110	1.92	0.058	2.05	[−0.004, 0.428]
Leisure activities	0.254	0.115	2.21	0.029	1.88	[0.028, 0.480]
CRIq Total Score	0.336	0.120	2.81	0.007	2.14	[0.100, 0.572]
Model R2 = 0.33, Adj. R2 = 0.29, F(7, 92) = 6.34, p < 0.001
Alternative Uses Task—Fluency
Age	−0.051	0.114	−0.45	0.653	1.42	[−0.274, 0.172]
Gender	−0.058	0.111	−0.52	0.602	1.38	[−0.277, 0.161]
TIB (FSIQ)	−0.095	0.111	−0.86	0.393	1.55	[−0.313, 0.123]
Education (years)	0.135	0.114	1.18	0.241	1.92	[−0.090, 0.360]
Occupational experience	0.289	0.112	2.53	0.014	2.05	[0.066, 0.512]
Leisure activities	0.271	0.111	2.41	0.019	1.88	[0.051, 0.491]
CRIq Total Score	0.371	0.122	3.05	0.003	2.14	[0.131, 0.611]
Model R2 = 0.38, F(7, 92) = 7.88, p < 0.001
Alternative Uses Task—Flexibility
Age	−0.048	0.116	−0.41	0.685	1.42	[−0.276, 0.180]
Gender	−0.062	0.113	−0.55	0.585	1.38	[−0.286, 0.162]
TIB (FSIQ)	−0.089	0.110	−0.81	0.419	1.55	[−0.304, 0.126]
Education (years)	0.112	0.112	1.01	0.315	1.92	[−0.108, 0.332]
Occupational experience	0.302	0.115	2.63	0.011	2.05	[0.075, 0.529]
Leisure activities	0.264	0.113	2.34	0.022	1.88	[0.042, 0.486]
CRIq Total Score	0.381	0.122	3.12	0.002	2.14	[0.141, 0.621]
Model R2 = 0.39, Adj. R2 = 0.35, F(7, 92) = 8.11, p < 0.001
Alternative Uses Task—Originality
Age	−0.058	0.108	−0.52	0.603	1.42	[−0.278, 0.162]
Gender	−0.066	0.108	−0.61	0.545	1.38	[−0.280, 0.148]
TIB (FSIQ)	−0.102	0.110	−0.94	0.351	1.55	[−0.314, 0.110]
Education (years)	0.135	0.115	1.23	0.221	1.92	[−0.082, 0.352]
Occupational experience	0.295	0.114	2.56	0.013	2.05	[0.070, 0.520]
Leisure activities	0.279	0.112	2.46	0.017	1.88	[0.055, 0.503]
CRIq Total Score	0.338	0.116	2.88	0.006	2.14	[0.106, 0.570]
Model R2 = 0.37, Adj. R2 = 0.33, F(7, 92) = 7.54, p < 0.001

Note: β = standardized regression coefficient; SE = standard error; CI = 95% confidence interval; VIF = variance inflation factor.

, the overall models demonstrated significant fit for all creativity outcomes: Acronyms—Fluency (R² = 0.31, Adj. R² = 0.27; F(7, 92) = 5.88, p < 0.001); Acronyms—Flexibility (R² = 0.33, Adj. R² = 0.29; F(7, 92) = 6.34, p < 0.001)—Alternative Uses—Fluency (R² = 0.38; F(7, 92) = 7.88, p < 0.001); Alternative Uses—Flexibility (R² = 0.39, Adj. R² = 0.35; F(7, 92) = 8.11, p < 0.001); and Alternative Uses—Originality (R² = 0.37, Adj. R² = 0.33; F(7, 92) = 7.54, p < 0.001).

Across outcomes, CRIq total score emerged as a consistent positive predictor of creativity performance. Higher CRIq was associated with better verbal creativity on the Acronyms task (Fluency: β = 0.316, t = 2.64, p = 0.011; Flexibility: β = 0.336, t = 2.81, p = 0.007) and better conceptual creativity on the Alternative Uses task (Fluency: β = 0.371, t = 3.05, p = 0.003; Flexibility: β = 0.381, t = 3.12, p = 0.002; Originality: β = 0.338, t = 2.88, p = 0.006). Leisure activities also showed an independent positive contribution across all outcomes (Acronyms—Fluency: β = 0.241, p = 0.035; Acronyms—Flexibility: β = 0.254, p = 0.029; Alternative Uses—Fluency: β = 0.271, p = 0.019; Alternative Uses—Flexibility: β = 0.264, p = 0.022; Alternative Uses—Originality: β = 0.279, p = 0.017). Regarding the experiential components of CR, education significantly predicted verbal creativity (Acronyms—Fluency: β = 0.284, p = 0.021; Acronyms—Flexibility: β = 0.271, p = 0.026), whereas occupational experience significantly predicted conceptual creativity (Alternative Uses—Fluency: β = 0.289, p = 0.014; Flexibility: β = 0.302, p = 0.011; Originality: β = 0.295, p = 0.013). In contrast, age, gender, and TIB-derived FSIQ were not significant predictors in any model (all ps > 0.10).

Age, gender, and TIB subtests (FSIQ, pronunciation errors, accent errors) did not significantly predict any of the creativity measures (all p > 0.05).

4. Discussion

Hypothesis 1. 

Higher CR Predicts Greater Creativity.

Consistent with Hypothesis 1, cognitive reserve (CR) emerged as a robust positive predictor of divergent thinking (DT) across all outcomes. This pattern supports the view that accumulated cognitive and experiential resources not only buffer age-related decline but may also facilitate adaptive, generative thinking in later life. In particular, individuals with higher CR may be better able to access semantic knowledge efficiently and to flexibly recombine information, thereby producing a greater number and variety of ideas [2,15,16,17].

Hypothesis 2. 

Experiential Components of CR Contribute to Creativity.

Regarding Hypothesis 2, experiential components of CR showed independent associations with creativity. Leisure activities, and—depending on the outcome—occupational experience, contributed to creativity over and above demographic factors and general cognitive ability. Engagement in cognitively and socially stimulating activities may provide sustained opportunities to practice flexible thinking, problem reframing, and novel association formation, which are central to DT performance [2,31].

Hypothesis 3. 

Domain-Specific Effects of CR.

With respect to Hypothesis 3, the results indicated a domain-specific pattern of predictors. Education was more strongly related to verbal creativity (Acronyms outcomes), consistent with the role of formal schooling in strengthening language-based retrieval and verbal fluency. In contrast, occupational experience and leisure activities were more strongly associated with conceptual creativity (Alternative Uses outcomes), which may rely more heavily on flexible problem-solving and the generation of non-obvious uses. This differentiation aligns with multidimensional accounts of CR, whereby distinct life experiences contribute selectively to different cognitive domains [15,21].

4.1. Theoretical and Practical Implications

Theoretically, these findings support models of positive and multidimensional aging in which reserve-related resources and enriching experiences contribute to cognitive flexibility and adaptive functioning. The present results suggest that CR may operate not only as a buffer against decline but also as a facilitator of creative performance in older adulthood, potentially through metacognitive control and flexible strategy use [2,31].

Practically, the findings underscore the potential value of interventions and public health strategies that promote lifelong cognitive and social engagement. Programs that encourage participation in stimulating leisure activities and opportunities for complex, meaningful engagement may help support creativity and, more broadly, well-being and adaptive functioning across the lifespan [13,17].

4.2. Limitations

Several limitations should be noted. First, the cross-sectional design does not allow causal inferences about the direction of the association between CR and creativity. Second, the convenience sampling approach may limit generalizability beyond the present sociocultural context. Third, CRIq indices rely on retrospective self-report, which may be affected by recall bias. Finally, creativity was assessed with two tasks; future work may benefit from including a broader battery covering additional creative domains.

4.3. Future Directions

Future studies should employ longitudinal and experimental designs to clarify causal pathways and to examine whether enhancing specific components of CR (e.g., enriched leisure engagement) leads to improvements in DT over time. Cross-cultural replications and the inclusion of neuropsychological and neurobiological measures would further help to identify the mechanisms linking reserve-related factors to creative performance in older adults [2,31].

5. Conclusions

In conclusion, the present study demonstrates that CR is a significant predictor of DT in older adults, with both general and domain-specific effects. Verbal creativity benefits primarily from education and verbal leisure engagement, whereas conceptual creativity is influenced by occupational experience and diverse leisure activities. These findings reinforce the theoretical view of CR as a multidimensional construct that supports adaptive cognitive functioning and highlight the importance of lifelong engagement in cognitively, socially, and occupationally stimulating activities. Promoting such activities may help maintain cognitive flexibility, enhance creative potential, and support well-being in aging populations. It should be noted that these results are based on a sample of healthy older adults from Italy, which may limit generalizability to other cultural or socioeconomic contexts.