Skip to content

Advertisement

BMC Geriatrics

Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

The role of gender in the association between personality and task priority in older adults’ dual-tasking while walking

BMC GeriatricsBMC series – open, inclusive and trusted201818:1

https://doi.org/10.1186/s12877-017-0691-1

Received: 28 February 2017

Accepted: 18 December 2017

Published: 2 January 2018

Abstract

Background

Falls are a major problem for older adults. Many falls occur when a person’s attention is divided between two tasks, such as a dual task (DT) involving walking. Most recently, the role of personality in walking performance was addressed; however, its association with DT performance remains to be determined.

Methods

This cross-sectional study of 73 older, community-dwelling adults explores the association between personality and DT walking and the role of gender in this relationship. Personality was evaluated using the five-factor model. Single-task (ST) and DT assessment of walking-cognitive DT performance comprised a 1-min walking task and an arithmetic task performed separately (ST) and concurrently (DT). Dual-task costs (DTCs), reflecting the proportional difference between ST and DT performance, were also calculated.

Results

Gender plays a role in the relationship between personality and DT. Extraversion was negatively associated with DTC-motor for men (ΔR2 = 0.06, p < 0.05). Conscientiousness was positively associated with DTC-cognition for women (ΔR2 = 0.08, p < 0.01).

Conclusion

These findings may lead to effective personality-based early detection and intervention for fall prevention.

Keywords

PersonalityDual-taskOlder adultsDual-task costExtraversionConscientiousness

Background

Advanced age is often accompanied by mobility limitations [1]. Over 35% of adults age 70 and above, and the majority of those age 85 and above, have clinically diagnosable gait abnormalities [1]. Older adults who experience gait abnormalities often rely more on executive than on automatic control of walking, and this greater reliance on executive control has been associated with increased risk of falls [2, 3]. The most common approach to extracting insights about executive versus automatic control of walking is the dual-task (DT) paradigm [3]. Indeed, most everyday situations that involve walking—walking while talking on the phone, or crossing the street while paying attention to a complex scene—require performing two tasks simultaneously. Efficient allocation of attention between two tasks is critical to maintaining safety during walking and to reducing fall accidents [4]. However, often older adults divide their attention inefficiently between a task involving balance, or postural control, and a cognitive task. Instead of prioritizing the postural task and choosing the “posture first strategy,” they opt for the “cognitive first strategy” and compromise their safety [5, 6]. Thus, evaluating task prioritization is critical to illuminating older adults’ DT performance.

DT interference occurs when there are competing demands for attentional resources [7]. Specifically, when the attentional demands of the two tasks exceed the total attention capacity, performance of the motor task, the cognitive task, or both may decline relative to single-task (ST) performance [3]. Wollesen et al. [8] reviewed theories that explain how people divide attention during different DT situations, that is, the difference between ST and DT performance, or proportional DT costs (DTCs). The main theories they discussed are the limited resources hypothesis, the cross domain model, the supra postural task model, and the prioritization model. Their main claim is that each can explain different DT combinations and that no single model fits all task combinations. For example, higher DTCs in the motor task, which are often accompanied by prioritization of the cognitive task, are associated with decreased walking automaticity and an increased risk of falls in older adults [3, 8, 9]. Most studies that explore DT performance in older adults evaluate either cognitive or motor performance, without considering DTCs for both tasks [10]. Such an approach does not provide the information necessary to understand resource allocation dynamics between the tasks [11] or to draw a comprehensive picture of attentional resource allocation in two tasks [3].

Previous studies have identified a number of factors affecting the decreased automaticity in walking tasks and the general DT impairment observed in older adults. The main factors studied were physiological age-related changes [3, 12] including nervous system damage, proprioception, touch, pain, cognition, biomechanical constraints, and hearing. Most of these factors are associated with the aging process itself and develop late in life. Most recently, however, two studies emphasize the need to further explore individual differences, personal traits, and their influences on walking deterioration over the lifespan [10, 12]. The ability to DT begins early in life and develops over the lifespan [10]. Thus, DT research should take into account factors that may influence DT through the lifespan and not only aging-associated factors [6, 10]. Personality has been linked to both the risk of developing age-related disabilities and to longevity [13], as well as to walking deterioration [14]. Moreover, psychological theories have linked fear of falling and anxiety to falls [15]. The link between anxiety and personality is well established [16, 17]. However, the contribution of personality to DT walking deterioration and prioritization with aging, which increases risk of falls, remains to be explored.

In health research, personality is often assessed by means of the five-factor model (FFM, also known as the Big Five) [13, 18]. The FFM classifies most personality traits under one of five dimensions: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to experience [18]. Personality has been linked to many health outcomes that are relevant for older adults, including motor function [19], gait speed [20] and muscle strength [21], mortality [22], and morbidity [23] and mobility [24]. Several specific pathways may explain relationships between personality and deterioration in DT walking. Cognitive pathways suggest that high Openness and high Conscientiousness are associated with slower rates of cognitive decline in aging (for a review, see Curtis et al. [25]). Behavioral pathways suggest that some personality factors, such as low Conscientiousness and high Neuroticism, are strong predictors of unhealthy behaviors, including physical inactivity and excess body weight, that result in limited walking abilities [26]. Another indirect pathway links personality type and the increased likelihood of developing chronic or acute illnesses, which in turn might initiate a process that leads to mobility dysfunction or that speeds its progression [27]. Thus, the link between personality and aging, longevity, and morbidity is well established. However, the link between personality and mobility decline in older adults is rarely explored.

Although the topic has scarcely been studied, few personality traits have been associated with mobility performance, and the findings are discrepant. For example, higher levels of Extraversion and Conscientiousness were found to be associated with reduced risk of disability with aging [28]. Another study emphasized the contribution of higher Openness in protecting against mobility deterioration [20]. These studies relied on self-reporting of mobility performance. Yet, even with more objective measures, findings are ambivalent. Tolea and colleagues demonstrate that higher Conscientiousness, but not Openness, is associated with faster initial gait speed and less decline over a 3-year period. Also, people characterized by high Neuroticism, either in isolation or in combination with low Extraversion and low Conscientiousness, are more prone to having low muscle strength [21]. Most recently, LeMonda et al. [29] showed for the first time that older adults with high Neuroticism and low Extraversion demonstrate greater DTC for both the cognitive and the motor task during DT walking when compared to other combinations of Extraversion and Neuroticism. This study paved the way for the establishment of the relationships between personality and the ability to divide attention while walking and performing another task. However, several questions remain about the roles of the other three FFM traits in relation to DT and personality, and about whether gender plays a role in this association.

Research on the association between personality and mobility is in its infancy. The evidence is mixed, and an exploration of functional mobility that represents the relationship between the full spectrum of personality factors (as modeled by the FFM) and DT walking has yet to occur. Expanding our understanding of this relationship may contribute to developing new, tailored fall-prevention strategies for elderly adults by enabling early detection of people at risk based on personality type. Thus, the objective of the current study is to explore the association between personality and DT walking performance in community-dwelling older adults. Based on our previous investigation [24], we hypothesize that people with higher Extraversion and higher Conscientiousness perform DT better and thus have lower DTC.

Following the body of evidence on gender differences in DT gait performance [30, 31] and in the levels of the FFM [32], we also investigated gender differences in the association between the FFM and DT prioritization, in addition to using gender as a control variable. However, because no past study focused on gender differences in the effects of the FFM on DTC, we tested these gender differences on an exploratory basis only.

Methods

Sample

To calculate the sample size, we used G-Power analysis software [33] and considered an OLS regression model with five independent variables, six covariates and two interactions; defining a medium effect size (f2 = 0.15) of α = 0.05, a power of .80 required a total sample of 78 participants.

Participants

In this cross-sectional study, 90 participants were recruited (55 female and 35 male), and 10 did not meet the inclusion criteria (for five Hebrew was not the first language, two reported back pain during walking and three did not complete the protocol). We have full data for 73 community-dwelling older adults (mean age 75 years, SD 6.0, 35 males and 38 females) recruited through advertisements in their communities. Inclusion criteria were being age 65 or older, being able to walk independently, and being able to speak, understand and read Hebrew. The study procedures were approved by the University of Haifa’s Institutional Review Board.

Tasks and procedures

Data were collected in community centers by one investigator (SD). Data collection sessions lasted 90 min and included collection of demographic information about participants’ age, gender, disease burden (the presence of neurologic or musculoskeletal diagnosis such as cerebral vascular accident, Parkinson disease, Alzheimer disease or multiple sclerosis; severe orthopedic limitations such as acute back pain or a total hip or knee replacement; significant hearing or vision loss not corrected with hearing aids or glasses), and number of weekly hours customarily engaged in physical activity. Cognitive ability was assessed with the MoCA, which covers 10 cognitive domains using rapid, sensitive, and easy-to-administer cognitive tasks. MoCA sensitivity to detect minimal cognitive impairment (MCI) is 100%, and specificity is 87% [34]. Personality was assessed using the NEO-FFM, a short version of the original FFM [18]. It includes 60 statements on five domains of personality: Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness, rated using a five-item Likert scale ranging from 1 (extremely inaccurate) to 5 (extremely accurate). Internal consistency ranges from α = 0.70 to α = 0.86, and construct validity correlations with the original FFM range from r = 0.76 to r = 0.91 [18].

Participants were asked to perform the following three tasks in random order. Each task lasts 1 min. (a) ST 1-min walk, during which participants walked back and forth on a 10-m course. The total distance walked was recorded. (b) ST subtraction by 3, starting from a random number from 100 to 250. The number of correct answers was calculated. This task was conducted while the participant was seated. (c) DT performance of (a) and (b). This task is often used for cognitive evaluation alone, or concurrently with a motor task [35]. The number of correct answers and the distance walked were calculated. During DT performance, participants were instructed to conduct each task to their best ability.

DTCs for walking and for the cognitive task were calculated for each test. DTCs reflect the cost of DT performance compared to ST performance and are expressed as a percentage of ST performance: DTC = ([DT – ST] / ST) × 100 [36]. DTCs for the walking task are lower in young adults than in older adults and are strongly associated with an increased risk of falls in the elderly.

Statistical analyses

SPSS 19 software was used for the following analyses: (1) to perform t tests contrasting ST with DT performance, (2) to assess whether DTCs were significantly different from zero, and (3) to calculate ordinary least squares (OLS) regressions to examine the associations between personality factors and the ability to divide attention between the two tasks of walking and subtracting by 3. In the first step of the regression analysis, the main effect variables of the FFM traits were entered simultaneously, to isolate the unique effect of each domain. In the second step of the regression, potential covariates of age, gender, MoCA, body weight, physical activity and chronic disease were entered. These covariates were considered potential mediators of personality associations with DTC performance. Attenuation attributed to the possible mediators under consideration was calculated using the formula 100 × (β Model 1 − β Model 2) / (β Model 1) (e.g. Hagger-Johnson et al. [37]). In the third step, because of sex differences related to changes in both personality and mobility [38, 39], we tested gender as a moderator by using interactions of the FFM with gender. We used the centered values of the FFM in testing these interaction terms to reduce multicollinearity and to facilitate the interpretation of interactions if found in our data analyses. The regression models with the interactive associations also include the linear, centered terms. To reduce the possibility of multicollinearity among the interaction and quadratic terms and their component predictors, all predictors were centered prior to the regression runs [40]. In Table 1, only significant interactions are shown (Table 1). In order to complement the inferential statistics of P-values, the effect size of the main effects of the FFM was also calculated as the square of the Pearson correlation r (R2) to reflect the proportion of variance shared by the FFM and DTC [41].
Table 1

Participant characteristics by gender (N = 73)

Characteristic

Male mean ± SD

Female mean ± SD

P-value

Age, years

74.7 ± 6.5

73.9 ± 6.0

.738

Openness

3.31 ± .54

3.39 ± .47

.452

Neuroticism

2.52 ± .56

2.64 ± .47

.208

Agreeableness

3.69 ± .51

4.10 ± .46

.47

Conscientiousness

4.00 ± .61

3.80 ± .51

.143

Extroversion

3.23 ± .35

3.7 ± .43

.419

MoCA

22.12 ± 3.2

21.9 ± 2.9

.438

ST walk (meters)

52.93 ± 6.1

53.87 ± 7.8

.13

DT walk (meters)

41.3 ± 10.3

42.0 ± 4.9

.09

MoCA Montreal Cognitive Assessment, ST single task, DT dual task

Results

A total of 81 community-dwelling, older adults, 35 males and 38 females, completed the study. Mean age was 75 years (SD 6.0) (Table 1). The mean BMI was 26.1 (SD 4.1), and the mean MoCA score was 23.0 (SD 3.1). Of the 73 participants, 13 (16.7%) reported having experienced at least one fall in the previous year. The mean distance walked during ST was 53.96 m (SD 11.6) and during DT was 41.83 m (SD 11.46). A significant difference was found between distance walked in ST and DT (t = 11.41, df = 87, p < 0.001). The mean number of correct answers in the ST cognitive task was 26.32 (SD 9.6) and in the DT was 23 (SD 9.62). A significant difference was found between ST and DT cognitive performance (t = 4.27, df = 87, p < 0.001). The mean relative difference between walking as a ST and as a DT (DTC) was 25.57% (SD 9.5) and for the cognitive tasks was 7.5% (SD 4.3). In addition, DTCs were significantly larger for walking (t = 3.1, df = 87, p = 0.003), suggesting that participants prioritize cognitive performance at the expense of walking.

Results of the OLS regression analyses model show that the association between the FFM and the ability to divide attention between two tasks while walking was not significant. The inclusion of age, MOCA, body weight, physical activity and chronic disease in the model did not change the associations between personality traits and DT; thus, no mediating effects of the covariates were found.

Gender differences: exploratory analysis

We tested, on an exploratory basis, whether gender moderated the hypothesized associations between the FFM traits and DTC by interaction term. The results are reported in Table 2. We found that after the inclusion of the interactions, Extraversion was positively associated with DTC-motor (β = .39, p < 0.05) and that the interaction of Extraversion with gender was significant (β = −1.84, p < 0.05). The interaction was plotted according to Aiken et al. [42]. The plot (not shown) indicated that Extraversion was positively associated with DTC-motor for men only (β = .88, p < 0.05). The effect size, as based on the ΔR2 of the interactions of gender with Extraversion in the OLS regressions, was significant (ΔR2 = 0.07, p < 0.05). Additionally, we found a significant interaction between Conscientiousness and gender (β = 2.03, p < 0.01). Plotting this interaction (not shown) indicated that Conscientiousness was negatively associated with DTC-cognition for women only (β = −.32, p < 0.05). The effect size, as based on the ΔR2 of the interactions of gender with Conscientiousness, was significant (ΔR2 = 0.07, p < 0.05).
Table 2

Results of the OLS regression analyses testing the associations between the Five-Factor Model and the ability to divide attention between two tasks while walking

Variable

DTCmotor (N = 81)

DTCcog (N = 81)

B

SEB

β

95% CI

B

SEB

β

95% CI

Neuroticism

5.56

3.43

.20

−110.51-122.18

2.42

4.45

.07

−6.47-11.31

Extraversion

12.28*

6.14

.39

.02–24.53

3.52

4.84

.09

−6.14-13.17

Conscientiousness

2.42

4.05

.07

−5.66-10.50

−9.89

7.59

−.23

−25.04-5.25

Openness

−.35

4.54

−.01

−9.41-8.71

−.96

5.70

−.02

−12.33-10.41

Agreeableness

.06

4.58

.01

−9.08-9.21

−1.09

5.69

−.02

−12.46-10.27

R 2

.05

 

.03

 

Co Covariates

 Age

.13

.38

.04

−.63–.89

−.196

.49

−.052

−1.18-.79

 Gender

62.37**

25.02

1.75

12.45–112.29

−90.09*

41.52

−1.95

−172.95)--7.244(

 MoCA

−1.06

.78

−.19

−2.62-.49

−.517

1.01

−.07

−2.54-1.51

 Body weight

−1.12

.58

−.24

−2.28-.04

.390

.75

.06

−1.11-1.89(

 Physical activity

−.67

.72

−.11

−2.10-.76

−1.976*

.96

−.25

−3.90-(−.04)

 Chronic disease

.76

2.61

.03

−4.45-5.97

−1.775

3.42

−.06

−8.61-5.06

 ΔR2

 

.06

   

.06

  

 Gender × Extraversion

−19.36*

7.94

−1.84

−35.20-(−3.510)

 

  

 Gender × Conscientiousness

 

  

23.973*

10.40

2.03

3.21–44.73

 ΔR2

 

.07*

   

.07*

  

B and β nonstandardized and standardized partial regression coefficients, respectively. SEB standard error of the former, MoCA Montreal Cognitive Assessment, OLS ordinary least squares; Gender (1 = women);

*p < 0.05; **p < 0.01

Discussion

This study investigated whether prioritization strategies are associated with personality during walking in ecologically valid conditions (i.e. with DT) in community-dwelling older adults, controlling for cognitive ability, lifestyle habits, health status and gender. The association between personality and DT walking has rarely been explored. Previous studies have not considered all five traits of the FFM and have not accounted for the role of gender [29]. Overall, we did not find any support for our predicted associations between personality and DTC. However, our analysis showed that our failure to support this hypothesis could be due to the moderating effect of gender on these associations. Indeed, when we tested, on an exploratory basis, whether these associations are gender-specific, a different and interesting picture emerged. While for women Conscientiousness was negatively associated with cognitive cost, for men Extraversion was positively associated with motor cost.

The first finding emerging from this study is that women with high Conscientiousness demonstrated a relatively lower cognitive cost during DT. The added cognitive task presented in the current study, the subtraction by 3, is considered a relatively highly complex task [35]. The way in which older adults divide their attention during this task combination (walking with subtraction by 3) could be explained by either the limited resources model or by the task prioritization model [8]. Several personal factors may determine the way in which people divide their attention between two tasks: hazard estimation, postural reserve, level of familiarity with the task, mood and character. Participants with postural reserve may direct their attention to the cognitive task [43]. In line with the literature on personality and health, it is reasonable to assume that women with high Conscientiousness directed their attention more to the cognitive task and had relatively low cognitive cost due to good performance. High Conscientiousness was previously linked to better health outcomes such as increased gait speed and reduced risk for disability and mobility disorders [20, 26, 28]. Additionally, This explanation is in agreement with that of previous studies demonstrating an association between Conscientiousness and executive function [44], which is supported by neuro-imaging studies [45]. Optimal executive function is one of the key determinants of effective resource allocation and is strongly associated with a decreased risk of falls in the elderly [7].

A second relationship demonstrates that for men Extraversion is positively associated with motor cost. This finding contradicts recent studies showing that low Extraversion is associated with low ability to divide attention during DT walking in older adults [29]. Results suggest that in men with higher levels of Extraversion, the cost of performing the walking task in DT compared with ST is higher than in those with lower Extraversion. This finding could indicates a relatively unsafe walking strategy among extraverted men and ineffective ways of dividing attention. Extroversion encompasses the tendency toward positive mood, sociability, and activity [46]. The tendency to be friendly toward others and to generally have positive emotions and attitudes may indicate a predisposition to engage in a broad range of social behaviors, which include an active, busy, or engaged lifestyle that promotes better physical [47] and cognitive health [48]. These findings may indicate that men with higher extroversion may pay more attention to the cognitive task while walking. However, this finding is not consistent with previous studies that demonstrated an association between high levels of Extroversion and reduced risk for disability [28].

We may speculate that different social roles and challenges for men and women [49] account for these results. As indicated above, the two FFM factors of Extraversion and Conscientiousness have consistently been found to be significant predictors of reduced risk of disability with aging [28], but almost no past study has tested the possibility that these effects differ by gender. Future research might address this issue. The findings reported here should be interpreted in light of our study’s potential limitations. The study population comprised relatively high-functioning individuals, and the sample was relatively small. It is possible that variables not included in the study may better illuminate the association between personality traits and gait with DT. These variables could include in-home mobility monitoring with sensors, which might explain how daily routines affect personality and lead to better outcomes while walking. Finally, the cross-sectional design limited our ability to evaluate the relationship between these variables over time.

Additional research is needed to clarify the role of objective daily functioning in this relationship, and to discover other pathways to a better understanding of these relationships. In addition, a longitudinal study design should be used to evaluate these relationships over time. This study adds important information to the understanding of mobility deterioration in older adults. Understanding the contribution of personality to mobility deterioration may lead to early detection of people at risk of falls, as well as to the development of personality-tailored interventions to prevent mobility decline in the aging population.

Conclusions

Findings from this study highlight the association between personality and DT performance during walking in older adults. Specifically, they suggest that Conscientiousness and Extroversion are associated with better and safer functioning in older adults in gender-specific ways. More specifically, future researchers testing the association between personality traits and DTC should formulate gender-specific hypotheses.

Abbreviations

DT: 

Dual-task

DTC: 

Dual-task cost

FFM: 

Five-factor model

MC: 

Minimal cognitive impairment

MoCA: 

Montreal Cognitive Assessment

OLS: 

Ordinary least squares

ST: 

Single-task

Declarations

Acknowledgements

Kristen Ebert-Wagner provided language editing and copyediting.

Funding

No funding to declare.

Availability of data and materials

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

MA and GA Designed the study, supervised data collection, analyzed the data and wrote the manuscript: SD Collected the data assisted with data analysis and writing the introduction and discussion. MD assisted with data interpretation, writing the discussion and reviewed and edited the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

The study was approved by the institutional review board of the University of Haifa, Haifa, Israel. Written informed consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Nursing, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
(2)
Department of Psychology, University of Haifa, Haifa, Israel
(3)
School of Psychology, Queen’s University Belfast, Belfast, UK

References

  1. Verghese J, LeValley A, Hall CB, Katz MJ, Ambrose AF, Lipton RB. Epidemiology of gait disorders in community-residing older adults. J Am Geriatr Soc. 2006;54(2):255–61.View ArticlePubMedPubMed CentralGoogle Scholar
  2. Lewis SJ. Neurological update: emerging issues in gait disorders. J Neurol. 2015;262(6):1590–5.View ArticlePubMedGoogle Scholar
  3. Clark DJ. Automaticity of walking: functional significance, mechanisms, measurement and rehabilitation strategies. Front Hum Neurosci. 2015;9:246.PubMedPubMed CentralGoogle Scholar
  4. Plummer P, Zukowski L, Giuliani C, Hall A, Zurakowski D. Effects of physical exercise interventions on gait-related dual-task interference in older adults: a systematic review and meta-analysis. Gerontology. 2016;62(1):94–117.View ArticleGoogle Scholar
  5. Beauchet O, Annweiler C, Dubost V, Allali G, Kressig R, Bridenbaugh S, Berrut G, Assal F, Herrmann FR. Stops walking when talking: a predictor of falls in older adults? Eur J Neurol. 2009;16(7):786–95.View ArticlePubMedGoogle Scholar
  6. Schaefer S, Schellenbach M, Lindenberger U, Woollacott M. Walking in high-risk settings: do older adults still prioritize gait when distracted by a cognitive task? Exp Brain Res. 2015;233(1):79–88.View ArticlePubMedGoogle Scholar
  7. Yogev-Seligmann G, Hausdorff JM, Giladi N. The role of executive function and attention in gait. Mov Disord. 2008;23(3):329–42.View ArticlePubMedGoogle Scholar
  8. Wollesen B, Voelcker-Rehage C, Regenbrecht T, Mattes K. Influence of a visual-verbal Stroop test on standing and walking performance of older adults. Neuroscience. 2016;318:166–77.View ArticlePubMedGoogle Scholar
  9. Montero-Odasso M, Verghese J, Beauchet O, Hausdorff JM. Gait and cognition: a complementary approach to understanding brain function and the risk of falling. J Am Geriatr Soc. 2012;60(11):2127–36.PubMedPubMed CentralGoogle Scholar
  10. Ruffieux J, Keller M, Lauber B, Taube W. Changes in standing and walking performance under dual-task conditions across the lifespan. Sports Med. 2015;45(12):1–20.View ArticleGoogle Scholar
  11. Doumas M, Krampe RT. Ecological relevance determines task priority in older adults’ multitasking. J Gerontol B Psychol Sci Soc Sci. 2013;70(3):377–85.View ArticlePubMedGoogle Scholar
  12. Rosso AL, Studenski SA, Chen WG, Aizenstein HJ, Alexander NB, Bennett DA, Black SE, Camicioli R, Carlson MC, Ferrucci L, Guralnik JM. Aging, the central nervous system, and mobility. J Gerontol A Biol Sci Med Sci. 2013;68(11):1379–86.Google Scholar
  13. Chapman BP, Roberts B, Duberstein P. Personality and longevity: Knowns, unknowns, and implications for public health and personalized medicine. J Aging Res. 2011;2011:Article ID 759170.View ArticleGoogle Scholar
  14. Tolea MI, Costa PT, Terracciano A, Griswold M, Simonsick EM, Najjar SS, Scuteri A, Deiana B, Orrù M, Masala M. Sex-specific correlates of walking speed in a wide age-ranged population. J Gerontol B Psychol Sci Soc Sci. 2010;65(2):174–84.View ArticleGoogle Scholar
  15. Young WR, Mark WA. How fear of falling can increase fall-risk in older adults: applying psychological theory to practical observations. Gait Posture. 2015;41(1):7–12.View ArticlePubMedGoogle Scholar
  16. Zhen R, Zhou X. Understanding the relationship between optimistic personality and anxiety among college students: the mediating role of coping style. Iran J Public Health. 2016;45(9):1229–31.PubMedPubMed CentralGoogle Scholar
  17. Gershuny BS, Sher KJ. The relation between personality and anxiety: findings from a 3-year prospective study. J Abnorm Psychol. 1998;107(2):252–62.View ArticlePubMedGoogle Scholar
  18. Costa PT, McCrae RR. Four ways five factors are basic. Pers Individ Dif. 1992;13(6):653–65.View ArticleGoogle Scholar
  19. Buchman AS, Boyle PA, Wilson RS, Leurgans SE, Arnold SE, Bennett DA. Neuroticism, extraversion, and motor function in community-dwelling older persons. Am J Geriatr Psychiatry. 2013;21(2):145–54.View ArticlePubMedPubMed CentralGoogle Scholar
  20. Tolea MI, Costa PT, Terracciano A, Ferrucci L, Faulkner K, Coday MMC, Ayonayon HN, Simonsick EM. Associations of openness and conscientiousness with walking speed decline: findings from the health, aging, and body composition study. J Gerontol B Psychol Sci Soc Sci. 2012;67(6):705–11.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Tolea MI, Terracciano A, Simonsick EM, Metter EJ, Costa PT, Ferrucci L. Associations between personality traits, physical activity level, and muscle strength. J Res Pers. 2012;46(3):264–70.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Martin LR, Friedman HS, Schwartz JE. Personality and mortality risk across the life span: the importance of conscientiousness as a biopsychosocial attribute. Health Psychol. 2007;26(4):428–36.View ArticlePubMedGoogle Scholar
  23. Sutin AR, Terracciano A, Deiana B, Uda M, Schlessinger D, Lakatta EG, Costa PT. Cholesterol, triglycerides, and the five-factor model of personality. Biol Psychol. 2010;84(2):186–91.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Agmon M, Armon G. A cross-sectional study of the association between mobility test performance and personality among older adults. BMC Geriatr. 2016;16(1):105.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Curtis RG, Windsor TD, Soubelet A. The relationship between Big-5 personality traits and cognitive ability in older adults: a review. Aging Neuropsychol Cogn. 2015;22(1):42–71.View ArticleGoogle Scholar
  26. Simonsick EM, Lafferty ME, Phillips CL, Mendes de Leon C, Kasl SV, Seeman TE, Fillenbaum G, Hebert P, Lemke JH. Risk due to inactivity in physically capable older adults. Am J Public Health. 1993;83(10):1443–50.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Verbrugge LM, Jette AM. The disablement process. Soc Sci Med. 1994;38(1):1–14.View ArticlePubMedGoogle Scholar
  28. Krueger KR, Wilson RS, Shah RC, Tang Y, Bennett DA. Personality and incident disability in older persons. Age Ageing. 2006;35(4):428–33.View ArticlePubMedGoogle Scholar
  29. LeMonda BC, Mahoney JR, Verghese J, Holtzer R. The association between high neuroticism-low extraversion and dual-task performance during walking while talking in non-demented older adults. J Int Neuropsychol Soc. 2015;21(07):519–30.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Hollman JH, Youdas JW, Lanzino DJ. Gender differences in dual task gait performance in older adults. Am J Mens Health. 2011;5(1):11–7.View ArticlePubMedGoogle Scholar
  31. Yogev-Seligmann G, Rotem-Galili Y, Mirelman A, Dickstein R, Giladi N, Hausdorff JM. How does explicit prioritization alter walking during dual-task performance? Effects of age and sex on gait speed and variability. Phys Ther. 2010;90(2):177–86.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Schmitt DP, Realo A, Voracek M, Allik J. Why can't a man be more like a woman? Sex differences in big five personality traits across 55 cultures. J Pers Soc Psychol. 2008;94(1):168.View ArticlePubMedGoogle Scholar
  33. Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149–60.View ArticlePubMedGoogle Scholar
  34. Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, Cummings JL, Chertkow H. The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9.View ArticlePubMedGoogle Scholar
  35. Al-Yahya E, Dawes H, Smith L, Dennis A, Howells K, Cockburn J. Cognitive motor interference while walking: a systematic review and meta-analysis. Neurosci Biobehav Rev. 2011;35(3):715–28.View ArticlePubMedGoogle Scholar
  36. Doumas M, Rapp MA, Krampe RT. Working memory and postural control: adult age differences in potential for improvement, task priority, and dual tasking. J Gerontol B Psychol Sci Soc Sci. 2009;64(2):193–201.View ArticlePubMedGoogle Scholar
  37. Hagger-Johnson G, Sabia S, Nabi H, Brunner E, Kivimaki M, Shipley M, Singh-Manoux A. Low conscientiousness and risk of all-cause, cardiovascular and cancer mortality over 17 years: Whitehall II cohort study. J Psychosom Res. 2012;73(2):98–103.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Feingold A. Gender differences in personality: a meta-analysis. Psychol Bull. 1994;116(3):429–56.View ArticlePubMedGoogle Scholar
  39. Cho S, Park J, Kwon O. Gender differences in three dimensional gait analysis data from 98 healthy Korean adults. Clin Biomech. 2004;19(2):145–52.View ArticleGoogle Scholar
  40. Aiken LS, West SG. Multiple regression: testing and interpreting interactions. Newbury Park: Sage Publications; 1991.Google Scholar
  41. Kelley K, Preacher KJ. On effect size. Psychol Methods. 2012;17(2):137–52.View ArticlePubMedGoogle Scholar
  42. Aiken LS, West SG, Woodward CK, Reno RR. Health beliefs and compliance with mammography-screening recommendations in asymptomatic women. Health Psychol. 1994;13(2):122–9.View ArticlePubMedGoogle Scholar
  43. Yogev-Seligmann G, Hausdorff JM, Giladi N. Do we always prioritize balance when walking? Towards an integrated model of task prioritization. Mov Disord. 2012;27(6):765–70.View ArticlePubMedGoogle Scholar
  44. Bogg T, Roberts BW. Duel or diversion? Conscientiousness and executive function in the prediction of health and longevity. Ann Behav Med. 2013;45(3):400–1.View ArticlePubMedGoogle Scholar
  45. Kapogiannis D, Sutin A, Davatzikos C, Costa P, Resnick S. The five factors of personality and regional cortical variability in the Baltimore longitudinal study of aging. Hum Brain Mapp. 2013;34(11):2829–40.View ArticlePubMedGoogle Scholar
  46. Watson D, Clark LA. Extraversion and its positive emotional core. In: Hogan R, Johnson JA, Briggs SR, editors. Handbook of personality psychology. San Diego: Academic Press; 1997. p. 767–93.View ArticleGoogle Scholar
  47. Roberts BW, Kuncel N, Shiner R, Caspi A, Goldberg L. The power of personality: a comparative analysis of the predictive validity of personality traits, SES, and IQ. Perspect Psychol Sci. 2007;2:313–45.View ArticlePubMedPubMed CentralGoogle Scholar
  48. Chamorro-Premuzic T, Bennett E, Furnham A. The happy personality: Mediational role of trait emotional intelligence. Pers Individ Dif. 2007;42(8):1633–9.View ArticleGoogle Scholar
  49. Wood W, Eagly AH. A cross-cultural analysis of the behavior of women and men: implications for the origins of sex differences. Psychol Bull. 2002;128(5):699.View ArticlePubMedGoogle Scholar

Copyright

© The Author(s). 2017

Advertisement