The relationship between Big-5 personality traits and cognitive ability in older adults - a review.

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The relationship between Big-5 personality traits and cognitive ability in older adults – a review a

a

Rachel G. Curtis , Tim D. Windsor & Andrea Soubelet

b

a

School of Psychology, Faculty of Social and Behavioural Sciences, Flinders University, Adelaide, SA 5001, Australia b

Campus Saint Jean d’Angely, Institut des SHS de Nice – LAPCOS, Université de Nice-Sophia Antipolis, 06357 Nice Cedex 4, France Published online: 28 Feb 2014.

To cite this article: Rachel G. Curtis, Tim D. Windsor & Andrea Soubelet (2014): The relationship between Big-5 personality traits and cognitive ability in older adults – a review, Aging, Neuropsychology, and Cognition: A Journal on Normal and Dysfunctional Development, DOI: 10.1080/13825585.2014.888392 To link to this article: http://dx.doi.org/10.1080/13825585.2014.888392

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Aging, Neuropsychology, and Cognition, 2014 http://dx.doi.org/10.1080/13825585.2014.888392

The relationship between Big-5 personality traits and cognitive ability in older adults – a review Rachel G. Curtisa*, Tim D. Windsora and Andrea Soubeletb a


School of Psychology, Faculty of Social and Behavioural Sciences, Flinders University, Adelaide, SA 5001, Australia; bCampus Saint Jean d’Angely, Institut des SHS de Nice – LAPCOS, Université de Nice-Sophia Antipolis, 06357 Nice Cedex 4, France (Received 2 August 2013; accepted 23 January 2014) It is well established that fundamental aspects of cognition such as memory and speed of processing tend to decline with age; however, there is substantial between-individual variability in levels of cognitive performance in older adulthood and in rates of change in cognitive abilities over time. Recent years have seen an increasing number of studies concerned with examining personality characteristics as possible predictors of some of this variability in cognitive aging. The purpose of this article is to review the literature, and identify patterns of findings regarding the relationships between personality (focusing on the Big-5) and cognitive ability across nonclinical populations of older adults. Possible mechanisms underlying associations of personality characteristics with cognition are reviewed, and assessed in the context of the current literature. Some relatively consistent relationships are identified, including positive associations between openness and cognitive ability, and associations of conscientiousness with slower rates of cognitive decline. However, the relationships between several personality traits and cognitive abilities in older adults remain unclear. We suggest some approaches to research design and analysis that may help increase our understanding of how personality differences may contribute to cognitive aging. Keywords: personality; Big-5; cognitive ability; cognitive aging; older adults

In recent years gerontologists have become increasingly interested in the extent to which personality characteristics are related to cognitive aging. While examination of the implications of personality for physical health has a long history in the behavioral and biomedical sciences (Smith & Spiro, 2002), recent perspectives on cognitive aging have identified the potential for different aspects of personality to also influence cognition into later life. Personality traits describe differences in typical cognitive and affective experience that have implications for behavior. Personality may therefore affect risk of cognitive decline through, for example, response to stress, health behaviors, and cognitively stimulating activity. Specifically, strong tendencies toward negative emotionality (as captured by constructs such as neuroticism) might over time have deleterious effects on aspects of brain structure and function. Conversely, traits characteristic of positivity (e.g., optimism, openness) potentially protect against cognitive decline in an indirect manner by facilitating effective coping, and engagement with life (Hertzog, Kramer, Wilson, & Lindenberger, 2008). Understanding the relationship between personality and cognitive ability in older adults is, therefore, important for the identification of those at risk of

*Corresponding author. Email: [email protected] © 2014 Taylor & Francis


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R.G. Curtis et al.

cognitive decline, and for development of interventions aimed at reducing cognitive decline and promoting successful cognitive aging. More than 20 years ago, Gold and Arbuckle (1990) published a review of early research concerned with personality and cognitive aging. Our aim is to provide an updated perspective by synthesizing research from before and after this review, and identifying patterns of findings regarding the relationships between personality and cognitive ability in older adults in the population. We provide a qualitative review, allowing for the varied nature of cognitive abilities assessed in the literature, and focusing on discussion of possible mechanisms linking personality with cognitive aging rather than making statistical comparisons using meta-analysis. While research has produced inconsistent results, we aim to establish how some of the inconsistencies may have arisen and how these issues might be addressed in future research. Finally, we identify approaches to research design and analysis that may help increase our understanding of the directional nature of personality–cognition relationships, and the mechanisms underlying these relationships. Previous research has revealed associations of personality characteristics with pathological cognitive decline including mild cognitive disorder, Alzheimer’s disease, and other dementias (see Low, Harrison, and Lackersteen (2013) for a recent meta-analysis). In the present review, we extend perspectives on personality and cognitive aging by focusing on studies of nonclinical populations. We also limit our review to studies that have operationalized personality from the perspective of the Five-Factor Model. Studies have shown a number of additional personality characteristics to be associated with cognitive ability in older adults, including need for cognition (e.g., Soubelet & Salthouse, 2010), typical intellectual engagement (e.g., Dellenbach & Zimprich, 2008), and perceived control (e.g., Windsor & Anstey, 2008). However, we exclude such additional characteristics in order to keep the review focused and allow in-depth analysis of key personality traits. We base our review on the Five-Factor Model because there is a general consensus that the Big-5 (neuroticism, extraversion, openness, agreeableness and conscientiousness) are largely representative of the most basic factors of adult personality (Costa & McCrae, 1992b). In addition, the Five-Factor Model is empirically derived, has been replicated cross-culturally, and has been shown to be relevant for adults of all ages (Costa & McCrae, 2003). The Big-5 personality traits have also been shown to predict outcomes in areas such as subjective well-being, psychopathology, physical health, and longevity (e.g., Ozer & Benet-Martínez, 2006). Table 1 outlines the key characteristics and findings of the studies that form the basis of this review. Relevant studies were identified by searches of PsycINFO, ScienceDirect, and ProQuest Central databases in late November 2012. Search terms included combinations of the words personality, Big-5, neuroticism, emotional stability, extraversion, openness, intellect, conscientiousness, agreeableness, cognition, cognitive functioning, cognitive performance, cognitive aging, cognitive decline, and older adults. We also conducted citation reference searches for a number of early studies. After compiling a preliminary list of studies, we reviewed the references cited in each for additional studies. Studies were limited to those written in English, and those using nonclinical samples. We focus the review on older adults and therefore included only studies with participants over 60 years of age. Thus, this review does not allow for comparison of personality– cognition relationships across the life span. The articles identified through the search processes described above provided an initial basis for identifying possible mechanisms underlying personality–cognition links. Our discussion of mechanisms was also informed by literature outlining more general perspectives on the significance of

64.7(4.5) 57–81, at follow-up

69.4(4.1), 62–79 at final follow-up

326, 0%

Canada (see Gold et al., 1995)

Canada (follow-up 132, 0% on Gold et al., 1995)

Arbuckle et al. (1992)


285, 49%

N/A, 65–93

Canada

L, 45 yrs (T1-T3 45 yrs; T2-T3 5yrs)

L, 40 yrs

CS

EPI

EPI

EPI

NEO-PI-S

Younger 23.7(N/A), CS 18–35; Older 69.9 (N/A), 60–90


Younger 39, 64%; Older 39, 69%

USA

Personality scale Neo-PI-R

Design CS

67.2(8.66), 49–90

Age M(SD), Range

Allen et al. (2011)

n, % Female

Baltimore Study of 291, 70% Black Aging, USA

Study, location

Personality and cognition in older adults.

Aiken-Morgan et al. (2012)

First author (year)

Table 1. Control factors

Age, education, intellectual activity, EPI Lie score g, episodic memory, Age, health, WM intellectual activities, occupation happiness, stressful life events Age, pre-war Verbal ability education (vocabulary, analogies, arithmetic), nonverbal ability (picture completion, anomalies, paper formboard)

Memory

STM, LTM

Verbal learning, WM Age, gender, education

Cognition constructs


E

(Continued )

No associations with change in cognition Higher E was associated with less vocabulary growth T1-T3 and T2-T3. Negatively associated with vocabulary growth T1T3. Higher E was associated with greater decline in paper formboard T1-T3.

N

E

Negatively associated with WM memory at follow-up Positively associated with g and with one of three episodic memory measures at follow-up

Negatively associated with verbal learning No associations Positively associated with verbal learning Positively associated with verbal learning and WM No associations for younger adults. Older adults high in E showed better LTM than those low in E. Not associated with STM for older adults Negatively associated with memory

Significant associations

N

N, E

E

A

E, C O

N

Personality construct

Aging, Neuropsychology, and Cognition 3

Baker and Bichsel (2006)

Austin et al. (2002)

First author (year)

Table 1.

n, % Female

Swedish adoption/ twin study of aging Canada

CS

N/A, 55–74

CS

CS

N/A, 50–96

N/A

CS

Design

N/A, 50–96

Age M(SD), Range

M(SE): Young 33.85 CS Young 135, 58%; (1.22), 19–60; cognitively cognitively comparable older comparable older 123, 62%; 69.20(.54), 61– cognitively 89; cognitively superior older superior older 123, 69% 70.11(.57), 61–89

602, N/A

1348, N/A Manchester longitudinal study of cognitive aging, England 1912, N/A Newcastle longitudinal study of cognitive aging, England Edinburgh Artery 424, N/A Study, Scotland

Study, location

(Continued ).

g

g

g

g


The Big-5 Inventory- Fluid reasoning, 44 comprehension, visual–spatial thinking, auditory processing, processing speed, STM, LTM

NEO-PI, EPI-short form

NEO-FFI

EPQ

EPQ

Personality scale

age

age

age

age

Control factors


A

C

O

N, E, C, A O N, E, C O A N E

N, E

N E


(Continued )

Negatively associated with g Not associated with g Positively associated with g Not associated with g Positively associated with g Negatively associated with g No associations Negatively associated with comprehension in young adults and long-term retrieval in comparable older adults Positively associated with comprehension and STM in young adults, auditory processing in comparable older adults, and visual–spatial thinking in superior older adults Positively associated with auditory processing in superior older adults. Negatively asssociated with comprehension in superior older adults

Negatively associated with g

Negatively associated with g Not associated with g


4 R.G. Curtis et al.

Ginkgo Evaluation 602, 41.9% of Memory study, USA

Chapman et al. (2012)

488, 62%

USA

Boyle et al. (2010)

78.6(3.1), 72–91

N/A, 65+

72.0(6.2), 60–85

398, 53%

Charlotte County Healthy Aging Study, USA

Booth et al. (2006)

40(11), 20–70

Age M(SD), Range

160, 0%

n, % Female

Poland

Study, location

(Continued ).

Biernacki and Tarnowski (2011)

First author (year)

Table 1.

L, 7 yrs

CS

CS

CS

Design

NEO-FFI

NEO-FFI

NEO-FFI

EPQ-R (Polish)

Personality scale

Control factors

g

g, EF

g, EF, episodic memory

N

Age, gender, education, medical illness burden Age, gender, education, race, health, disease history, depression, alcohol use, smoking, BMI, APOE genotype, death


A

C

O

E

N

E, A N

C

E Age, education, other N personality traits O

Latency time, motor Age, fluid ability time, dividing attention, field of vision, tracking deviation, omitted reactions



(Continued )

Negatively associated with average g. Higher N was associated with a higher rate of decline Negatively associated with average g. Not associated with rate of decline Positively associated with average g. Not associated with rate of decline Not associated with average g. Higher C was associated with more gradual decline Not associated with average g or rate of decline

No associations with any variable, as N increased, the positive relationship between age and latency time, tracking deviation, and omitted responses increased. As N increased, the negative relationship between age and field of vision increased No associations Negatively associated with 1 of 2 EF tasks Positively associated with g and memory Positively associated with 1 of 2 EF tasks No associations Negatively associated with g



USA

326, 0% Canada (see Arbuckle et al., 1992)

The Lothian Birth Cohort 1921, Scotland

Denburg et al. (2009)

Gold et al. (1995)

Gow et al. (2005)

550, 57.5%

152, 63%

Young 140, 0%; Middle-aged adults 711, 0%; Older 109, 0%

Normative Aging Study, USA

Costa et al. (1976)

n, % Female

Study, location

(Continued ).

First author (year)

Table 1.

CS

10.9(0.3), 10.5–11.5 L, approx 68 yrs at baseline; 79.1 (0.6), N/A at follow-up (referred to as 11, 79)

64.8(4.4), N/A at follow-up

IPIP (measure at follow-up)

EPI

NEO-FFI

CS Young 48.6(11.9), 26–64; Older 74.0 (5.6), 65–85

Personality scale 16PF

Design

Young 31.7(2.28), N/ CS A; Middle-aged 43.7(5.54), N/A; Older 60.3(5.24), N/A; Total, N/A 25-82

Age M(SD), Range

Control factors

IQ

Verbal abilities (vocabulary, analogies, arithmetic), nonverbal abilities (spatial ability)

EF

Age, gender, education


E, C, A

O

N

E

E, O, C, A N

N

O

Age, SES, education N Verbal ability, manual dexterity, pattern analysis E capability (fluid ability)



(Continued )

Anxious participants had worse verbal ability than adjusted participants. No effect of age Extraverted participants had worse pattern analysis capability scores than introverted participants. No effect of age Open participants open showed significantly better pattern analysis performance than closed participants. No effect of age. No association in younger adults. Negatively associated with EF in older adults No association Negatively associated with arithmetic and vocabulary at baseline. Negatively associated with vocabulary at follow-up Not associated with any abilities at baseline. Negatively associated with all verbal tasks and 1 of 3 spatial ability tasks at follow-up Negatively associated with IQ at 11 and 79. Remained negatively associated with IQ at 79 after adjusting for IQ at 11 Positively associated with IQ at 11 and 79. Not associated with IQ at 79 after adjusting for IQ at 11 No associations



Graham and Lachman (2012)

First author (year)

Table 1.

n, % Female

4974, N/A Midlife in the United States Study (MIDUS)

Study, location

(Continued ).

55(12.4), 28–84 at follow-up

Age M(SD), Range

Personality scale

L, 8–10 yrs MIDUS survey

Design

Control factors

C A

O

E

N Age, gender, Reasoning, WM, education, health, processing speed, hearing problems reaction time, episodic memory, verbal fluency




(Continued )

Negatively associated with WM and reasoning. Change in N was related to reasoning for all ages: those stable and low in N had higher scores than those who were stable and high, increasing or decreasing. Change in N was related to reaction time for older adults only: those who were stable or decreased in N had faster reaction times than those who increased Negatively associated with reasoning. Change in E was not related to any ability Positively associated with reasoning, verbal fluency, WM, and episodic memory. Change in O was associated with reasoning for all ages: those stable and high in O had higher reasoning than those stable and low, increasing or decreasing No associations Negatively associated with reasoning, reaction time, and verbal fluency. Change in A was not related to any cognitive ability



Australia

Victoria Longitudinal Study, Canada

Senior Odyssey project, USA

Maastricht Aging Study, Netherlands

Hultsch et al. (1999)

Jackson et al. (2012)

Jelicic et al. (2003)

Study, location

(Continued ).

Gregory et al. (2010)

First author (year)

Table 1.

63.3(N/A), 49–81 at L, 3 yrs follow-up

185, 47.6%

Exp.

L, 6 yrs

CS

Design

72.9(7.7), 60-94

N/A, 55–86 at baseline

N/A, 74–90

Age M(SD), Range

183, 65%

229, 59.4%

70, 62.9%

n, % Female

EPQ-R-S (Dutch)

IPIP-AB5C

NEO-PI

NEO-PI-R

Personality scale

Control factors


O

N

Inductive reasoning

g, processing speed, Age, gender, education EF, verbal ability, delayed recall

C, A

O

O Verbal ability, fluid reasoning, memory (immediate, delayed, WM) Self-reported health, N Processing speed, active lifestyle, episodic memory, novel information WM, processing comprehension E speed, verbal fluency, vocabulary, world knowledge



(Continued )

Negatively associated with comprehension speed. Not associated with decline in any ability Negatively associated with world knowledge and vocabulary. Higher E was associated with less decline in comprehension and semantic speed Positively associated with world knowledge, vocabulary and verbal fluency. Not associated with decline in any ability. No cross-sectional relationships; not analysed longitudinally Positively associated with inductive reasoning at pre-test. O increased in the intervention group only. Changes in O were positively associated with changes in inductive reasoning. Changes in inductive reasoning did not mediate the effect of group on changes in O No associations

Positively associated with verbal ability, fluid reasoning, immediate and delayed memory



SwedishAdoption/ Twin Study of Aging

USA

Sharp et al. (2010)

Soubelet and Salthouse (2010)

Soubelet (2011) France

The Lothian Birth Cohort 1921, Scotland

Mõttus, Johnson, Starr, et al. (2012)

164, 62%

2257, 64.6%

857, 59%

209, 52.6%

Interdisciplinary 287, 31% study on aging, Switzerland

Meier et al. (2002)

711, 48.4%

n, % Female

Australian community survey

Study, location

(Continued ).

Jorm et al. (1993)

First author (year)

Table 1.

CS

CS

Design

49.8(18.8), 19–96

50.3(18.6), 18–96

CS

CS

N/A, 50+ at baseline L, 20 yrs

86.6(0.42), 86–87 at L, 7 yrs follow-up

N/A, 68–95

N/A, 70+

Age M(SD), Range

50-item IPIP

50-item IPIP

Six-items from NEO-PI

50-item IPIP

Freiburger PersonalityInventory

EPQ-R-S

Personality scale

Control factors


C

Gender, independent N, A E functioning, physical fitness O

E

N

E

N

Fluid ability, Age crystallized ability, memory, perceptual speed Gender Fluid ability, processing speed, episodic memory, WM

C

O

Verbal ability, spatial Education, activities O of daily living, ability, memory, cardiovascular processing speed, disease g

IQ

Age, education g, verbal ability, processing speed, EF, world knowledge, episodic memory, reaction time Episodic memory Age, gender, (free recall, education recognition)



(Continued )

Negatively associated with g, processing speed and episodic memory for men, and reaction time for women Negatively associated with verbal ability for men Negatively associated with free recall Positively associated with episodic memory No associations Higher age 79 IQ predicted lower E at 87 Higher age 79 IQ predicted higher O at 87 IQ did not predict level of C, but higher age 79 IQ predicted less decline in C. Change in C was not associated with change in IQ Positively associated with performance in each cognitive domain and g at age 65. Not associated with rate of decline in any variable Positively associated with all abilities. No attenuation of the relationship after controlling for activity engagement Negatively associated with fluid ability and WM only. 68.4% of the positive association between age and C was explained by fluid ability for those with lower levels of education only



Age M(SD), Range

Design

Swedish Adoption/ 704, 59% Twin Study of Aging

USA

Wetherell et al. (2002)

Williams et al. (2010)

58, 62%

4790, 58%

SardiNIA project, Italy

Sutin et al. (2011)

69.9(6.3), 60–85

63.7(8.6), N/A

42.6(16.3), 14-94

CS

L, up to 9 yrs

CS

Young 26.3(6.0), 18– CS Young 663, 60%; 39; Middle-aged Middle-aged 870, 50.8(5.5), 40–59; 71%; Older 784, Older 70.5(7.6), 61% 60–96

n, % Female

USA

Study, location

(Continued ).

Soubelet and Salthouse (2011)

First author (year)

Table 1.

NEO-PI-R

EPI (9 items)

NEO-PI-R

50-item IPIP

Personality scale

Episodic memory, WM, processing speed, verbal ability, visuospatial ability EF

Verbal fluency

Fluid ability, crystallized ability, memory, perceptual speed


Age, education

Age, gender, education

Gender, age, age2, education

Age (within age group)

Control factors


N E, O, C, A

N

A

C

E, O

N

A

C

O

E

N


(Continued )

Negatively associated with EF Not associated with EF Positively associated with EF

Negatively associated with fluid ability for older adults only Negatively associated with fluid and crystallized abilities. No effect of age Positively associated with all abilities. No effect of age Positively associated with perceptual speed for middleaged adults only Negatively associated with fluid ability for middle-aged adults only Negatively associated with verbal fluency Positively associated with verbal fluency Positively associated with verbal fluency only for those with lower education Not associated with verbal fluency No associations moderated by age Negatively associated with episodic memory, processing speed and visuospatial ability only. Not associated with decline in any ability



CS Middle-aged 43.7 (0.93), 42–46; Older 62.5(0.94), 60–64

NEO-FFI

L, up to NEO-FFI (6 items) 12 yrs (M = 6.2)

Control factors

Fluid intelligence, crystallized intelligence

As above

As above

As above

As above

Age, gender, Episodic memory, education WM, visuospatial ability, verbal ability, perceptual speed, g


O

N

C

N


Negatively associated with baseline g and every ability. High N was associated with increased rates of decline in g. Specifically, N was associated with increased decline in episodic memory only Not associated with baseline g. Higher C was associated with reduced rates of decline in g, episodic memory, verbal ability, WM, and perceptual speed Higher N was associated with a lower level and more rapid decline in g. Specifically, N was negatively related to baseline function in each cognitive domain, and with more rapid decline in episodic memory only. Positively associated with fluid and crystallized intelligence in middle-aged adults (23% and 50% of variance explained, respectively) and older adults (29% and 50% of variance explained, respectively).


Note: N/A = not available, CS = cross-sectional, L = longitudinal, Exp = experimental, NEO-PI-R = NEO Personality Inventory-Revised, NEO-PI-S = NEO Personality Inventory – Short Form, NEO-FFI = NEO Five-Factor Inventory, EPI = Eysenck Personality Inventory, EPQ = Eysenck Personality Questionnaire, EPQ-R = Eysenck Personality Questionnaire – Revised, EPQR-S = Eysenck Personality Questionnaire – Revised Short Form, IPIP = International Personality Item Pool, 16PF = Cattell’s 16 Personality Factor Questionnaire, N = neuroticism, E = extraversion, O = openness, C = conscientiousness, A = agreeableness, g = general cognitive ability, STM = short-term memory, LTM = long-term memory, WM = working memory, EF = executive functioning.

Middle-aged 679, Interdisciplinary 48.3%; Older Study on Adult 572, 48.4% Development, Germany

76.8(7.7), N/A at baseline

1,256, 70.7%

Religious Orders Study; Rush Memory and Aging Project, USA

Zimprich et al. (2009)

NEO-FFI Healthy participants L, up to 12 yrs 73.5(6.5); AD (M = 7.9) developed during follow-up 80 (6.5), at baseline

920, N/A

L, up to 9 NEO-FFI yrs (M = 5.9)

Religious Orders Study, USA

75.2(7.0), N/A

Wilson, Schneider, Arnold, Bienias, & Bennett (2007) Wilson, Schneider, Boyle, et al. (2007)

Personality scale

797, 68.4%

Design

Religious Orders Study, USA

Age M(SD), Range

Wilson et al. (2003)

n, % Female

Study, location

(Continued ).

First author (year)

Table 1.



12

R.G. Curtis et al.


lifestyle and individual difference characteristics for cognitive aging (e.g., Bielak, 2010; Hertzog et al., 2008). Neuroticism Neuroticism refers to the tendency to be emotionally unstable, and to experience negative emotions such as anger, anxiety, and depression (Costa & McCrae, 1992a; McCrae & John, 1992). There are two hypothesized mechanisms that propose how neuroticism may be negatively associated with measures of cognitive ability in older adults. The first suggests that individuals high in neuroticism experience more anxiety, which can impair performance during testing (Moutafi, Furnham, & Paltiel, 2004; Sutin et al., 2011; Wetherell, Reynolds, Gatz, & Pedersen, 2002). Neuroticism is positively correlated with state (Moutafi, Furnham, & Tsaousis, 2006) and trait anxiety (Jylhä & Isometsä, 2006; Muris, Roelofs, Rassin, Franken, & Mayer, 2005), which have been shown to have a negative effect on cognitive performance in older adults (Salthouse, 2012; Stillman, Rowe, Arndt, & Moser, 2012). It has been suggested that individuals high in neuroticism may perform poorly on cognitive tasks because they are distracted by worry-related thoughts (Gold & Arbuckle, 1990; Meier, Perrig-Chiello, & Perrig, 2002), or because their sympathetic nervous system is more easily aroused in response to stress (Biernacki & Tarnowski, 2011). Activation of the hypothalamic–pituitary–adrenal (HPA) axis in response to stress triggers the adrenal glands to release the stress hormones glucocorticoids (cortisol) and catecholamines (adrenaline and noradrenaline), which can impair cognitive performance (e.g., Lupien et al., 1997; Lupien, Maheu, Tu, Fiocco, & Schramek, 2007; Wolf, Schommer, Hellhammer, McEwen, & Kirschbaum, 2001). The second hypothesis proposes that neuroticism is negatively related to cognitive ability because prolonged arousal experienced by individuals with higher neuroticism causes neuronal damage over time (Boyle et al., 2010; Chapman et al., 2012; Jorm et al., 1993). Individuals with higher levels of neuroticism experience greater stress in their daily lives (e.g., Bolger & Schilling, 1991; Suls & Martin, 2005). Chronic stress can lead to prolonged activation of the HPA axis, and therefore excess glucocorticoids (hypercortisolemia), which can accelerate the rate of normative hippocampal atrophy (Sapolsky, 1994). Furthermore, neuroticism is negatively related to cerebral volume in middle aged and older adults (Jackson, Balota, & Head, 2011; Wright, Feczko, Dickerson, & Williams, 2007), and decline in brain volume with age is greater in individuals with higher neuroticism (Jackson et al., 2011; Knutson, Momenan, Rawlings, Fong, & Hommer, 2001). A number of studies have examined relationships between neuroticism and cognitive abilities in older adults using cross-sectional data. The majority of studies examining general cognitive functioning and working memory have reported that higher neuroticism is associated with poorer cognitive test performance (e.g., Wilson et al., 2003, see Table 1); however, several studies have also reported nonsignificant cross-sectional associations (e.g., Jelicic et al., 2003, see Table 1). Results of studies examining associations of neuroticism with cognitive variables other than general ability and working memory have been inconsistent. However, studies have shown that neuroticism is negatively related to fluid reasoning (e.g., Baker & Bichsel, 2006), and to a fluid ability composite reflecting both reasoning and spatial ability (Soubelet & Salthouse, 2011). Among the studies in Table 1 that reported correlation coefficients, correlations between neuroticism and various cognitive abilities ranged from −.16 to −.50. Neuroticism was reported to explain 1% variance in general cognitive ability (Aiken-Morgan et al., 2012), 1.1% of variance in executive functioning (Booth, Schinka, Brown, Mortimer, & Borenstein,


Aging, Neuropsychology, and Cognition

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2006), 2% of variance in memory (Gow, Whiteman, Pattie, & Deary, 2005), and 2% of variance in fluid ability (Soubelet & Salthouse, 2011) in adjusted analyses. The available cross-sectional research suggests that among non-impaired older adults higher levels of neuroticism are most consistently related to poorer general cognitive functioning, working memory, and fluid reasoning. Such findings do not, however, suggest the mechanism by which these relationships occur. Moutafi et al. (2006) found that neuroticism is no longer related to intelligence in young and middle-aged adults when the effects of test anxiety are removed. It may be useful to assess whether the relationship between intelligence and neuroticism is also mediated by test anxiety in older adults. It is possible, however, that test anxiety also reflects the individual’s propensity to experience stress in everyday life, and that long-term effects of stress, or acute cognitive interference resulting from stress exposure (Sliwinski, Smyth, Hofer, & Stawski, 2006; Stawski, Mogle, & Sliwinski, 2011) could also account for some of the associations outlined above. Only a few longitudinal studies have examined the effects of neuroticism on rate of change in older adults’ cognitive ability. Chapman et al. (2012) found that higher neuroticism was associated with a steeper rate of global cognitive decline over 7 years. Wilson et al. (2003) and Wilson, Schneider, Boyle, et al. (2007) also found that higher neuroticism was associated with more rapid global cognitive decline over an average of 6 years, but further analyses in both studies revealed that neuroticism was associated with decline in episodic memory only. Effect sizes were not reported. Four additional longitudinal studies have not found associations between neuroticism and decline in cognitive ability (e.g., Arbuckle, Maag, Pushkar, & Chaikelson, 1998; Hultsch, Hertzog, Small, & Dixon, 1999; Jelicic et al., 2003; Wetherell et al., 2002). There is limited evidence to support the hypothesis that prolonged arousal experienced by individuals with higher neuroticism causes neuronal damage over time, with less than half of the reviewed studies showing a significant relationship between neuroticism and rate of cognitive decline. In addition, in studies that showed a significant relationship between neuroticism and cognitive decline, causation my not be in the predicted direction; a decline in cognitive ability may have caused older adults to become more anxious, with increasing anxiety reflected in higher neuroticism scores. One limitation of the current literature is that personality is typically measured only once at baseline. Only two studies measured change in neuroticism over time (Graham & Lachman, 2012; Mõttus, Johnson, Starr, & Deary, 2012); however, Graham and Lachman (2012) did not evaluate whether change in neuroticism was associated with change in cognitive ability, and Mõttus, Johnson, Starr, et al. (2012) found no change in neuroticism over time. Although there have been reports of impressive stability in personality traits over time (e.g., Löckenhoff et al., 2008; Lucas & Donnellan, 2011; Mõttus, Johnson, & Deary, 2012; Roberts & DelVecchio, 2000), there is evidence that some mean level changes do occur throughout adulthood, including in old age (see Allemand, Steiger, and Hill (2013) and Caspi, Roberts, and Shiner (2005) for review). Neuroticism tends to decrease with age in cognitively healthy adults (Roberts, Walton, & Viechtbauer, 2006); however, studies also show considerable interindividual variability in rates of change in neuroticism (e.g., Allemand, Zimprich, & Hertzog, 2007; Mroczek & Spiro, 2003), suggesting that neuroticism should not be viewed only as a predictor, but also as a potential outcome of aging-related processes and neuropathology (Roberts & Mroczek, 2008). Change in neuroticism should therefore be measured in future longitudinal studies to evaluate whether neuroticism increases as cognitive ability decreases, and if so, whether change in neuroticism precede or follows change in cognition.

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Openness Openness refers to the tendency to be creative, curious, sensitive to aesthetics, and open to new ideas and experiences (Costa & McCrae, 1992a; McCrae & John, 1992). Individuals with greater openness have a predisposition to ponder ideas; think creatively (Sharp, Reynolds, Pedersen, & Gatz, 2010); and actively pursue novel, cognitively stimulating experiences (McCrae, 1994). Thus, it has been hypothesized that individuals high in openness are more likely to engage in stimulating activities (e.g., reading newspapers, working on cross-word puzzles, and using a computer) that positively affect cognitive ability, contribute to cognitive reserve, and help to maintain cognitive functioning in older age (Chapman et al., 2012; Gow et al., 2005; Gregory, Nettelbeck, & Wilson, 2010; Sharp et al., 2010; Soubelet & Salthouse, 2010). Individuals with greater cognitive reserve have a more efficient, higher capacity cognitive network (Stern, 2009), and a greater ability to utilize alternative networks or cognitive strategies in response to increased cognitive demand (Stern, 2002). Individuals with greater cognitive reserve may therefore cope better with brain pathology and age-related changes in the brain (Stern, 2009). Cognitive reserve is influenced by experiences at all stages of life, including in late life (Stern, 2009). This suggests that older adults who engage in more activities may have more efficient processing abilities, and may have greater cognitive ability than less active older adults. In addition, the disuse theory of cognitive aging predicts that activity engagement in older adults can assist in the maintenance of cognitive abilities, while the disuse of these abilities can lead to the loss of such skills (Salthouse, 1991). This is commonly known as the ‘use it or lose it’ hypothesis (e.g., Bielak, 2010; Salthouse, 2006). The influence of activity engagement on cognitive ability could follow one of two patterns: Differential preservation suggests that activity engagement influences the trajectory of cognitive change with age, so that more active individuals show a slower rate of cognitive decline than less active individuals (Salthouse, 2006). If openness influences the maintenance of higher cognitive functioning through a predisposition to engage in cognitively stimulating activities, differential preservation suggests that older adults with higher openness would experience smaller age-related declines in cognitive functioning than older adults with lower openness. Preserved differentiation suggests that more active individuals had higher cognitive ability than less active individuals, and that the influence of openness on cognitive ability is the same over the lifespan (Salthouse, 2006). Older adults with higher openness would therefore have a higher level of cognitive functioning than older adults with lower openness, but would experience a similar trajectory of cognitive decline. An alternative hypothesis proposes causation in the opposite direction, suggesting that intelligence influences the development and maintenance of openness. It is suggested that individuals with lower intelligence may have more difficulty coping with novel or challenging experiences, and may therefore be less open to new experiences than individuals with higher intelligence (Moutafi, Furnham, & Crump, 2003). While cognitive ability may affect the development of openness in younger adults, it may also be relevant for the maintenance of openness in older adults; Williams, Suchy, and Kraybill (2010) suggest that as executive functioning declines with age, novel experiences may become more stressful and difficult to handle. Older adults may therefore become less open, favoring familiar experiences, and avoiding novel situations. Thus, older adults with better preserved cognitive abilities may experience less decline in openness in older age.



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Results of studies that have examined cross-sectional associations of openness with cognition have been somewhat mixed (see Table 1); however, where statistically reliable associations have been reported they have typically shown that higher openness is associated with better performance. For example, studies have reported positive associations of openness with general cognitive ability (e.g., Austin et al., 2002), fluid reasoning (e.g., Graham & Lachman, 2012), spatial ability (Sharp et al., 2010), episodic memory (e.g., Aiken-Morgan et al., 2012), and verbal ability (e.g., Sutin et al., 2011). To date, longitudinal studies have not produced evidence to indicate that openness is associated with differential rates of change in general cognitive ability (Chapman et al., 2012), spatial ability (Sharp et al., 2010), memory (Sharp et al., 2010), or verbal ability (Hultsch et al., 1999). Graham and Lachman (2012) found that while openness tended to decrease over time, older adults who remained stable and high in openness over an 8–10 year period had higher reasoning ability than those who remained stable and low in openness or either increased or decreased in openness. Where effect sizes have been reported, correlation coefficients range from 0.13 to 0.53. The reported variance in cognitive abilities explained by openness was 3% for general cognitive ability (Booth et al., 2006), and ranged from 1.5% to 6.6% for memory measures (Booth et al., 2006; Gregory et al., 2010; Soubelet & Salthouse, 2010, 2011), 1.2% to 2% for processing speed (Soubelet & Salthouse, 2010, 2011), 2.3% to 29% for fluid ability, and 11.6% to 50% for crystallized ability measures (Soubelet & Salthouse, 2010, 2011; Zimprich, Allemand, & Dellenbach, 2009). The cross-sectional findings reported above, coupled with the absence of associations between openness and rates of cognitive change in longitudinal studies, provide more compelling support for the preserved differentiation hypothesis than the differential preservation hypothesis. Although a number of authors have argued that links between openness and cognitive functioning are likely to be mediated by activity engagement, only Soubelet and Salthouse (2010) have examined this possibility empirically. They found that openness was positively associated with functioning in four cognitive domains; however, contrary to the mediation hypothesis, the relationships remained unchanged after controlling for activity engagement. Additional studies performing mediation analyses would be useful in order to further evaluate this hypothesis. In particular, longitudinal studies will be important for assessing whether change in openness is associated with cognitive functioning via change in activity engagement. Few studies have tested the reverse-causality hypothesis that intelligence influences individuals’ openness to experience. If cognitive ability influences older adults’ openness, decline in cognitive ability would be expected to relate to decline in openness over time. Mõttus, Johnson, Starr, et al. (2012) aimed to test this association, but found no longitudinal change in openness over a 7-year study interval. Graham and Lachman (2012) reported a mean decrease in openness over an 8–10 year interval, but did not examine covariation with cognitive abilities. It may be useful for future research to evaluate whether longitudinal decline in cognitive ability is associated with decline in openness in older adults. It is possible, however, that third variable effects are relevant to links between openness and cognition. The “common cause hypothesis” suggests that, while sensory deprivation could account for the relationship between sensory abilities and cognition in older adults, age differences in both sensory abilities and cognition may reflect age-associated changes in the brain (Lindenberger & Baltes, 1994) and central nervous system (Anstey, Lord, & Williams, 1997). This is supported by findings that variables of a nonpsychological nature that are associated with biological aging are also predictive of cognitive aging, including lower limb strength (Anstey et al., 1997), and olfaction (Dulay & Murphy, 2002). In regard to present literature, the relationship between openness and cognitive ability in older adults


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may not be causal. Rather, general physical and functional decline could reduce older adults’ openness to new experiences, and at the same time be linked to declining cognitive ability. Cognitive training studies may provide some insight into the mechanisms underlying the openness–cognition relationship. Jackson, Hill, Payne, Roberts, and Stine-Morrow (2012) randomly assigned older adults to either a 16-week induction reasoning training program or control group. They found that openness increased in the intervention group only, and that changes in openness were positively associated with changes in inductive reasoning. Interestingly, changes in inductive reasoning did not mediate the effect of group membership on change in openness, suggesting that engaging in the program led participants to view themselves as more open independently of the increase in their reasoning ability. Further intervention studies that measure longitudinal change in openness may be useful in order to clarify how openness and cognitive ability are related in older adults; however, the question of the direction of causation in the openness–cognition relationship may not be easily resolvable. It is possible that the relationship between openness and cognitive ability in older adults is bidirectional; openness may influence the development and maintenance of older adults’ cognitive ability, and may also be influenced by older adults’ cognitive ability. The application of bivariate dual-change score models (e.g., McArdle & Hamagami, 2001) to data from studies that include longitudinal assessments of both openness and cognitive abilities may help to clarify the nature of causal associations between openness and cognitive ability at the within-person level. Extraversion Extraversion refers to the tendency to be assertive and social, and to experience positive affect and seek excitement (Costa & McCrae, 1992a; McCrae & John, 1992). Numerous possible mechanisms have been proposed linking extraversion with cognition. Several focus on the possible influences of extraversion on test-taking ability. First, individuals high in extraversion have a higher speed of response, higher assertiveness, and lower arousal, which may provide performance advantages and lower distraction during cognitive testing (Chamorro-Premuzic & Furnham, 2004). A contrary argument suggests that higher extraversion could impair cognitive-test performance due to extraverts being more easily distracted due to discomfort with the formal testing situation and a lower tolerance for repetition (Costa, Fozard, McCrae, & Bossé, 1976; Gold & Arbuckle, 1990), and being less likely to spend time attempting to solve difficult problems (Baker & Bichsel, 2006). In addition, Robinson (1989) suggests that there is a curvilinear relationship between extraversion and cognitive performance because different situations may require different levels of arousal for optimal performance. While introverts maintain a high level of arousal and extraverts maintain a low level of arousal, those who are moderately extraverted are able to move between high and low arousal states. A fourth hypothesis proposes that extraversion has an indirect positive influence on older adults’ cognitive ability. In older age, individuals may experience less social stimulation due to, for example, the loss of social interactions in the workplace, and may also experience a decline in sensory function. Citing the theory of selective optimization and compensation (see, e.g., Baltes & Smith (2003); and Baltes (1997)), Meier et al. (2002) argue that individuals high in extraversion may compensate for these losses by seeking stimulation, protecting against cognitive decline in a similar manner to the way in which an active lifestyle is argued to protect against age-related cognitive decline (cf. Hertzog et al., 2008). The final hypothesis proposes a positive relationship between



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extraversion and long-term memory, suggesting that extraverts experience higher positive affect which, when experienced during encoding, creates contextual markers that are stored with the memory trace and enhance subsequent memory retrieval (Allen, Kaut, Baena, Lien, & Ruthruff, 2011). Findings for cross-sectional relationships between extraversion and cognitive abilities in older adults are relatively inconsistent, with different studies reporting positive, negative, and nonsignificant associations across a range of different cognitive measures (see Table 1). For example, a negative association between extraversion and general cognitive functioning has been found in four samples of older adults (Arbuckle, Gold, Andres, Schwartzman, & Chaikelson, 1992; Austin et al., 2002; Chapman et al., 2012; Mõttus, Johnson, Starr, et al., 2012), however, no association has been found in six samples (Austin et al., 2002; Booth et al., 2006; Gow et al., 2005; Jorm et al., 1993). With some exceptions (see Table 1), extraversion has generally not been found to relate to working memory or short-term episodic memory. Studies have, however, reported a positive association between extraversion and long-term memory (Allen et al., 2011; Baker & Bichsel, 2006). Where reported, negative correlations between extraversion and cognitive abilities ranged from −0.11 to −0.28, while positive correlations ranged from 0.09 to 0.22. The variance in cognitive abilities explained by extraversion is reported to be 4% for memory (Arbuckle, Gold, & Andres, 1986), 2% for fluid abilities, and 4% for crystallized abilities (Soubelet & Salthouse, 2011). Few studies have examined the relationship between extraversion and cognitive decline. Arbuckle et al. (1998) found that higher extraversion predicted less vocabulary growth and greater decline in one of two spatial ability tests over 45 years from young to older adulthood. Hultsch et al. (1999) found that high extraversion was associated with less decline in processing speed over 6 years (Hultsch et al., 1999). However, nonsignificant relationships with decline in global cognitive functioning, working and episodic memory, and verbal abilities have also been shown (see Table 1). Only Hultsch et al. (1999) provided correlation coefficients for the relationship between extraversion and cognitive change, reporting coefficients of −0.19 and −0.23 for the relationship between extraversion and change in two measures of processing speed. Studies have shown that, while extraversion declined over time, change in extraversion was not associated with cognitive ability (Graham & Lachman, 2012; Mõttus, Johnson, Starr, et al., 2012). The literature does not support the hypothesis that older adults high in extraversion gain advantage from a higher speed of response or lower distractibility as compared to older adults lower in extraversion, since few positive cross-sectional associations between extraversion and cognitive performance have been found. However, the positive association between extraversion and long-term memory found in two studies is consistent with the hypothesis that extraverts experience higher positive affect, which enhances memory encoding and subsequent memory retrieval. Support is limited for the hypothesis that individuals high in extraversion may be more easily distracted during testing, since negative associations of extraversion and cognitive functioning are not consistent across different studies. The hypothesis that a curvilinear relationship exists between extraversion and intelligence in older adults has not been a focus of research. Only Austin et al. (2002) included tests of quadratic relationships between personality and cognition; however, they found no significant quadratic effects. The hypothesis that older adults high in extraversion seek greater stimulation, which is protective of the effects of age-related cognitive decline, received little support. Only a few studies have evaluated the effects of extraversion on cognitive decline, and the findings are not consistent. Further longitudinal research on the effects of extraversion

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on cognitive decline would be useful in order to clarify this relationship. In particular, studies that examine engagement in socially and intellectually stimulating activities as potential intervening variables (MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002) could help to clarify possible mechanisms. It should, however, be noted here that evidence regarding the protective effects of an engaged lifestyle is still emerging. Although there is some evidence that activity engagement is related to better cognitive performance in older adulthood (Bielak, 2010; Hertzog et al., 2008), a number of studies have found that activity engagement is related to level but not decline in cognitive abilities (e.g., Bielak, Anstey, Christensen, & Windsor, 2012; Mitchell et al., 2012; see Salthouse (2006) for review). Conscientiousness Conscientiousness refers to the tendency to be persistent, organized, and goal-directed, and to show self-control and self-discipline (Costa, McCrae & Dye, 1991; McCrae & John, 1992). Three hypotheses have been proposed to describe the possible relationship between conscientiousness and cognitive ability. First, it has been suggested that conscientiousness is positively related to cognitive functioning in older adults because conscientiousness influences health behaviors that are protective against age-related changes in the brain (Sutin et al., 2011; Wilson, Schneider, Arnold, et al., 2007). For example, conscientiousness is positively related to exercise (Rhodes & Smith, 2006), which leads to a larger volume in the prefrontal cortex and reduces age-related atrophy in the frontal, parietal, and temporal cortices (Bugg & Head, 2011; Colcombe et al., 2003). A second hypothesis suggests that better cognitive functioning allows individuals to maintain previous levels of conscientiousness as they age (Mõttus, Johnson, Starr, et al., 2012). A third hypothesis proposes a negative relationship between conscientiousness and cognitive ability, whereby individuals with low cognitive ability become more organized, hardworking, and persistent over time as a means of compensating for their low ability, whereas individuals with higher cognitive abilities are able to achieve desired goals with relatively lower levels of conscientiousness (Chamorro-Premuzic & Furnham, 2004; Moutafi et al., 2004). This relationship could occur in adults of all ages, but may be particularly relevant for older adults experiencing age-related cognitive decline, as they may become more conscientious in order to maintain previous levels of cognitive performance as they age (Soubelet, 2011). Existing studies have provided little empirical evidence to support links between conscientiousness and cognitive abilities in older adults. Although four studies have found significant relationships with some cognitive abilities (Booth et al., 2006; Chapman et al., 2012; Soubelet, 2011; Wilson, Schneider, Arnold, et al., 2007), studies have typically found no association of conscientiousness with general cognitive ability, verbal ability, working memory, episodic memory, fluid reasoning, visual–spatial thinking, executive functioning, or processing speed (see Table 1). Only Soubelet (2011) reported correlation coefficients for the relationship between conscientiousness and cognitive abilities in a wide age range sample, which were −0.21 for working memory and −0.22 for fluid ability, after controlling for age. Booth et al. (2006) reported that 2.6% of variance in executive functioning was explained by conscientiousness. Whereas the cross-sectional research findings have been inconsistent, two longitudinal studies have produced findings to suggest that conscientiousness may contribute to differential preservation of cognitive abilities. Specifically, conscientiousness has been found to be associated with reduced rates of decline in general cognitive ability over 7 years



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(Chapman et al., 2012), and with reduced rates of decline in general cognitive ability, verbal ability, working memory, episodic memory, and processing speed over an average of 8 years (Wilson, Schneider, Arnold, et al., 2007). Effect sizes were not reported. It is difficult to determine whether any one or some combination of the hypothesized mechanisms outlined above accounts for the relationship between conscientiousness and cognitive decline. The finding that higher conscientiousness is related to reduced cognitive decline provides some support for the hypothesis that conscientiousness influences health behaviors that protect older adults from the effects of cognitive aging; however, neither Chapman et al. (2012) or Wilson, Schneider, Arnold, et al. (2007) measured positive or negative health behaviors. Future research should evaluate whether the relationship between conscientiousness and cognitive decline in older adults is mediated by engagement in health behaviors in order to provide further support for this hypothesis. Mõttus, Johnson, Starr, et al. (2012) argue that the finding that lower IQ at age 79 predicted more longitudinal decline in conscientiousness from ages 81 to 87 supports the hypothesis that better cognitive functioning allows individuals to maintain previous levels of conscientiousness as they age. This hypothesis has yet to be assessed by other studies. Interestingly, although both cognitive functioning and conscientiousness declined with age, Mõttus, Johnson, Starr, et al. did not find that decline in cognitive functioning was associated with decline in conscientiousness. Such a relationship would be expected if maintaining cognitive functioning allows an individual to maintain their level of conscientiousness. Evaluation of longitudinal data assessing the relationship between longitudinal change in conscientiousness and cognitive functioning may be useful in order to further assess this hypothesis. Soubelet’s (2011) finding that the positive relationship between age and conscientiousness was partially mediated by fluid ability supports the hypothesis that older adults become more conscientious in order to compensate for a decline in cognitive performance with age. However, no negative relationships between conscientiousness and cognitive ability in older adults have been reported by other authors. Some studies have shown an increase in conscientiousness in older adults using cross-sectional analyses, but a decrease in conscientiousness in older adults using longitudinal analyses (e.g., Wortman, Lucas, & Donnellan, 2012). The hypothesis that older adults become more conscientious in order to maintain previous levels of cognitive performance as they age may therefore be evaluated more effectively by assessing longitudinal change in both cognitive ability and conscientiousness in order to clarify how changes in these variables are related. To date, only Mõttus, Johnson, Starr, et al. (2012) have reported results based on assessment of longitudinal changes in both conscientiousness and cognitive ability. Although they found that change in conscientiousness was not associated with change in IQ, further evaluation of this hypothesis may be useful. Agreeableness Agreeableness refers to the tendency to be altruistic, trusting, modest, and compliant (Costa et al., 1991; Costa & McCrae, 1992a). Current research provides no conceptual rationale for a relationship between agreeableness and cognitive ability in healthy older adults. A number of studies discussed above have, however, explored whether a relationship between agreeableness and cognitive functioning might be present. With some exceptions (see Table 1), the available evidence indicates that agreeableness is not reliably associated with general cognitive ability (e.g., Chapman et al., 2012), memory (e.g., Baker & Bichsel, 2006), or executive functioning (e.g., Denburg et al., 2009) in older adults.

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Whether agreeableness is related to alternative fluid or crystallized abilities including reasoning, processing speed, and verbal abilities is less clear, with positive, negative, and nonsignificant relationships emerging (see Table 1). Where effect sizes were provided, positive correlation coefficients ranged from 0.18 to 0.38, while one reported negative correlation coefficient was −0.14. With only a small number of studies addressing these abilities, no conclusions can currently be drawn with any confidence regarding possible links between agreeableness and cognition in older adulthood. Importantly, a clear theoretical basis for predicting associations is needed to guide selection of appropriate covariates, and possible moderating and mediating variables. In sum, a more systematic approach is needed to better establish whether agreeableness might be expected to predict cognitive aging, or whether the statistically significant relationships that have emerged to date are more likely to reflect chance findings. Summary A number of relatively consistent findings have emerged in the literature, with openness and conscientiousness appearing to be most consistently related to cognitive ability in older adults. Specifically, although openness has not been found to be related to executive functioning or cognitive decline, openness has been shown to be positively related to level of general cognitive ability, fluid ability, episodic memory, and verbal ability. Conscientiousness has not generally been related to level of any cognitive ability; however, two studies have shown that higher conscientiousness is associated with reduced rates of decline in general cognitive ability. One of these studies also showed that higher conscientiousness is associated with reduced rates of decline in episodic memory, verbal ability, working memory, and perceptual speed. Few consistent findings have emerged for the remaining personality traits. Research suggests that extraversion is positively associated with long-term memory, but is not associated with executive functioning, processing speed, or auditory processing. Agreeableness has been consistently unrelated to general cognitive ability, memory, and executive functioning. Findings for neuroticism are somewhat mixed; although a number of studies showed neuroticism to be negatively related to general cognitive ability, working memory, and fluid reasoning; several studies have also reported nonsignificant cross-sectional associations. Findings for the association of extraversion, agreeableness, and neuroticism with other cognitive abilities and rate of cognitive decline are also mixed. General cognitive ability, fluid ability, memory, and verbal ability appear to be the dimensions of cognition most often related to personality. However, they are not related to all of the Big-5 personality traits, and are related only cross-sectionally with openness and longitudinally with conscientiousness. This highlights the likelihood of heterogeneity in the mechanisms by which personality traits may influence older adults’ cognitive ability. Methodological considerations Some of the inconsistencies in findings between studies may be partly attributable to the methodological differences between the studies, such as the use of different measures of personality. In comparing the studies in this review, we assume that the personality scales used are equivalent measures of the specified personality factor; however, scores from individuals who were assessed using two or more personality scales have been found to correlate only moderately, although relationships were slightly higher between scores from scales that were developed from the Five-Factor Model (Pace & Brannick, 2010).



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In the present review, findings regarding the relationships between neuroticism and cognitive ability in older adults do not appear to differ between studies using personality measures based on the Five-Factor Model of personality (e.g., NEO-FFI) and those based on Eysenck’s three factor model (e.g., EPI); however, extraversion showed more negative associations with cognitive ability in studies using personality measures based on Eysenck’s model, as compared to those based on the Five-Factor Model. There is also great heterogeneity in the measures of cognitive ability used in the literature. This may be particularly problematic where a single measure is employed to assess a cognitive ability. Different tests of the same ability may correlate only moderately with each other and therefore show inconsistent associations with personality. For example, this may be the reason why Hultsch et al. (1999) found that extraversion was associated with vocabulary, but not with reading comprehension, and Booth et al. (2006), who tested the relationship between executive functioning and personality, found that neuroticism was significantly related to the Trail Making Test only, whereas conscientiousness was related to the Stroop Color Word test only. It is difficult to form conclusions from such results, or to predict whether the nature of a relationship between personality and one ability measure would generalize to other measures of that ability. It may be useful for future research to use latent variable modeling approaches in a structural equation modeling context to examine associations of personality with cognitive domains defined using multiple indicators, thereby explicitly estimating and reducing the impact of measurement error (e.g., Muthén, 2002). It is also possible that studies utilizing smaller samples did not have adequate statistical power to detect potentially meaningful associations. This may particularly be the case for the analysis of relationships with neuroticism, where (with the exception of the Swedish Adoption/Twin Study of Aging, Austin et al., 2002) studies that did not show a significant negative cross-sectional association between neuroticism and general cognitive functioning were based on samples of fewer than 400 participants, whereas studies that did find a significant relationship had samples ranging from 424 (Edinburgh Artery Study, Austin et al., 2002) to 1912 participants (Newcastle longitudinal study of cognitive aging, Austin et al., 2002). Different sample characteristics across studies may also be a source of the inconsistent findings. For example, 17.5% of participants developed Alzheimer’s disease in Wilson, et al.’s (2003) study, and 38% developed mild cognitive impairment in Wilson, Schneider, Boyle, et al.’s (2007) study. Chapman et al. (2012) used data from a study on the effects of Ginkgo biloba in the prevention of dementia (DeKosky et al., 2008), in which approximately 17% of participants developed dementia. Although data from participants with mild cognitive impairment at baseline were excluded from analysis, it is likely that some participants who did not present with cognitive impairment at the commencement of the study developed dementia during the follow-up period. Neuroticism is a risk factor for the development of dementia (see Low et al. (2013) for review). Participants higher in neuroticism may have been more likely to develop dementia during these studies, and may therefore have been more likely to show an increased rate of cognitive decline. The relationships between neuroticism and cognitive change found by these studies may therefore be overestimated by the influence of participants with cognitive impairment. Wetherell et al. (2002) and Jelicic et al. (2003) excluded participants with dementia and found no relationship between neuroticism and cognitive decline. No further studies report the number of participants with cognitive impairment. Further longitudinal research excluding participants with cognitive impairment may be useful in order to determine whether neuroticism and cognitive functioning are negatively related in healthy older adults, or only in those


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experiencing pathological cognitive decline. Similarly, conscientiousness reduces the risk for dementia (Low et al., 2013), and although both Wilson, Schneider, Arnold, et al. (2007) and Chapman et al. (2012) found a significant relationship between conscientiousness and cognitive decline, both studies included participants with dementia. Future research should exclude participants with cognitive impairment in order to determine whether conscientiousness and cognitive functioning are negatively related in samples of healthy older adults. The literature shows some inconsistent results in the relationships between personality and cognitive ability in older adults, as outlined above. We have identified some possible reasons for such heterogeneity of findings, and how some of these inconsistencies might be resolved. For example, using multiple measures of cognitive ability and samples excluding participants with cognitive impairment may help clarify whether these inconsistencies have arisen because studies have failed to show relationships that exist in the population, or whether some of the significant relationships between personality and cognitive ability are likely to have occurred by chance or are due to specific characteristics of the sample. Directions for future research An important step forward in developing a better understanding of the possible role of personality in influencing cognitive aging is likely to depend on more focused empirical attempts to identify underlying mechanisms. Evaluation of the literature on the relationship between personality and cognitive ability in older adults has identified a number of possible directions for future research in this area. For example, it may be useful to measure whether salivary cortisol (a proxy for activation of the HPA axis) mediates the relationship between neuroticism and cognitive performance, and whether hippocampal atrophy or decline in cerebral volume mediate the relationship between neuroticism and cognitive decline. Future research should also test whether activity engagement mediates the relationship between openness and level of cognitive performance, and whether health behaviors mediate the relationship between conscientiousness and cognitive decline. Examination of theoretically relevant moderators of personality–cognition relationships may also be useful. For example, education may moderate the relationship between conscientiousness and cognitive ability. It is possible that conscientious is positively correlated with cognitive ability in individuals with low education, as high conscientiousness may partly compensate for the effects of low education on cognitive ability, but may be unrelated to cognitive ability in individuals with high education. Soubelet (2011) found that over 68% of the positive association between age and conscientiousness was explained by fluid ability, but this effect was significant only among those with lower levels of education. In addition, Sutin et al. (2011) found a positive association between conscientiousness and verbal fluency only for those with lower education. Health may also moderate the relationship between conscientiousness and cognitive ability. If conscientiousness influences health behaviors that are protective against age-related changes in the brain, the effects may be minimal in healthy older adults, but may be more consistently evident in those with poorer health. Those with poor health who are high in conscientiousness may be more likely to adhere to treatment or to engage in other positive health behaviors and lifestyle changes that may be protective of the effects of poor health and may delay cognitive decline. There is also a need for longitudinal studies that examine correlated changes in personality and cognitive ability in older adults. Few studies measured changes in personality over time; however, population mean levels of traits have been found to



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change over the lifespan, and there are interindividual differences in the rate of change (e. g., Allemand et al., 2007; Roberts et al., 2006; Wortman et al., 2012). Such analyses are particularly important with regard to the relationships between openness, conscientiousness, and cognitive ability, given the above theoretical reasons suggesting the possibility of reverse- and bi-directional causality. Longitudinal measurement of personality would allow the use of bivariate dual-change score models (e.g., McArdle & Hamagami, 2001), which may help to clarify the direction of these relationships by enabling measurement of the effects of personality on subsequent cognitive decline, and the effects of cognitive ability level on subsequent personality change. Previous research has focused on the unique variance in cognitive ability explained by personality traits independently; however, future research may wish to consider the possibility that personality traits have an interactive effect on older adults’ cognitive ability. For example, neuroticism may influence cognitive performance depending on the level of conscientiousness. Roberts, Smith, Jackson, and Edmonds (2009) found that older adults higher in neuroticism reported lower subjective health and more functional limitations; however, the association of neuroticism with poorer health outcomes was reduced for those high in conscientiousness. It is possible that anxiety about one’s declining health or functional capacity leads to an increase in positive health behaviors in people high in conscientiousness, which may protect against cognitive decline. A related and potentially valuable approach to considering the combined effects of personality traits on older adults’ cognitive ability is the identification of personality types or profiles. A variable-centered approach to personality focuses on differences among individuals on independent traits (Robins, John, Caspi, Moffitt, & Stouthamer-Loeber, 1996). This is a common approach to the study of personality; however, it does not allow consideration of the configuration of traits, or the structure of personality, within the individual (Asendorpf, 2002, 2006). A person-centered approach to personality focuses on the organization of traits within a person (Robins et al., 1996), and individuals may be classified into types that consist of individuals with a similar personality structure (Asendorpf, 2006). For example, Robins et al. (1996) identified three personality types in children and young adults; resilient, overcontrolled, and undercontrolled, which have since been replicated using cluster analysis (e.g., Asendorpf, Borkenau, Ostendorf, & Van Aken, 2001; Asendorpf & van Aken, 1999; Schnabel, Asendorpf, & Ostendorf, 2002). Resilient individuals tend to be low in neuroticism and high in extraversion, conscientiousness, agreeableness, and openness. Overcontrolled individuals are characterized by high neuroticism and low extraversion, while uncontrolled individuals are characterized by low agreeableness and conscientiousness. These types have been shown to predict a number of outcome variables, including cognitive competence in children (Asendorpf & van Aken, 1999), and shyness, sociability, self-esteem, and loneliness in young adults (Asendorpf et al., 2001). To our knowledge, no one has attempted to replicate these types in older adults. Although a number of studies have failed to replicate these types (e.g., Asendorpf, 2002; Boehm, Asendorpf, & Avia, 2002; Herzberg & Roth, 2006), or show their predictive value to be greater than that of the continuous scales of the Big-5 traits (Asendorpf, 2003; Costa, Herbst, McCrae, Samuels, & Ozer, 2002), a systematic approach to the identification of personality types in older adults may be useful in order examine personality type as a predictor of cognitive ability and decline. Another important avenue for future research is consideration of individual facets (distinct but highly correlated characteristics) within the Big-5 personality traits. For example, conscientiousness is comprised of competence, order, dutifulness, achievement striving, self-discipline, and deliberation (Costa & McCrae, 1992a). Few researchers have


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explored the relationships of individual personality facets with cognitive ability in older adults (see Aiken-Morgan et al., 2012; Graham & Lachman, 2014; Gregory et al., 2010; Sutin et al., 2011; Williams et al., 2010), and existing evidence is mixed. Exploration of facet relationships may shed light on nonsignificant trait associations, particularly where facets may influence cognitive ability in opposing directions within one personality trait. For example, Aiken-Morgan et al. (2012) found that conscientiousness was not related to verbal fluency; however, examination of individuals facets of conscientiousness revealed that competence and self-discipline were positively related to verbal fluency, while deliberation was negatively related. The emergence of consistent relationships between personality and cognitive ability in older adults contributes to our understanding of individual differences in cognitive ability and in rates of change in cognitive ability over time. Given that personality is relatively enduring, the effects of personality on cognitive ability are likely to be fairly persistent. It may therefore seem that knowledge of the relationship between personality and cognitive ability is of limited use in mitigating the risk of cognitive decline. However, some personality traits may be open to influence. Jackson et al. (2012) found that older adults who took part in an inductive reasoning training program showed increases in openness. Moreover, the most useful application of this knowledge may come from consideration of the processes behind personality–cognition relationships, rather than the manipulation of personality itself. Knowledge of specific risk factors associated with individual difference characteristics such as personality might enable interventions to be better tailored to individuals’ needs. For example, if individuals with low conscientiousness are at greater risk of cognitive decline because they engage in fewer positive health behaviors, it may be useful to develop a program aimed at encouraging these individuals to regularly engage in behaviors such as physical exercise. For those low in openness, it may be more useful to promote engagement in cognitively stimulating activities. It is, however, important to remain mindful of the fact that although the literature suggests a number of relationships between personality and cognition, we do not currently have a well-developed understanding of the causal direction, or the mechanisms underlying these relationships. We hope that the suggestions presented here will be useful in guiding future research design and analysis to these ends. Conclusion Research suggests that neuroticism may be negatively related to general cognitive ability, working memory, and fluid reasoning; however, several studies have reported nonsignificant cross-sectional associations. Openness is positively related to older adults’ cognitive ability cross-sectionally, but studies to date have not produced evidence to suggest that individuals higher in openness show slower rates of cognitive decline. Conversely, conscientiousness has typically not been found to predict level of older adults’ cognitive ability, but emerging evidence suggests that higher conscientiousness is associated with reduced rates of cognitive decline. Research suggests that extraversion is positively associated with long-term memory, but is not associated with executive functioning, processing speed, or auditory processing. Agreeableness has not generally been related to general cognitive ability, memory, or executive functioning in older adults. Numerous questions remain about the specific nature of personality–cognition associations and the mechanisms underlying them. We have identified several methodological issues and suggestions for future research which we hope will contribute to ongoing efforts to better understand the extent to which personality differences contribute to cognitive aging.


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Funding Tim Windsor is the recipient of an Australian Research Council Future Fellowship [#FT100100228].


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