Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis Hindawi Journal of Aging Research Volume 2018, Article ID 8917535, 9 pages https://doi.org/10.1155/2018/8917535 Research Article Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis 1,2 3 1,4 1,2 Nathalie Andre´ , Claude Ferrand, Ce´dric Albinet , and Michel Audiffren Centre de Recherches sur la Cognition et l’Apprentissage, UMR CNRS 7295, Universit´e de Poitiers, Poitiers, France Maison des Sciences de l’Homme et de la Soci´et´e, USR CNRS 3565, Universit´e de Poitiers, Poitiers, France EA 2114, Psychologie des aˆges de la vie, Universit´e François Rabelais, Tours, France Laboratoire Sciences de la Cognition, Technologie, Ergonomie (SCoTE), Universit´e de Toulouse, INU Champollion, Albi, France Correspondence should be addressed to Nathalie Andre´; nathalie.andre@univ-poitiers.fr Received 18 November 2017; Revised 18 February 2018; Accepted 22 March 2018; Published 5 April 2018 Academic Editor: Barbara Shukitt-Hale Copyright © 2018 Nathalie Andre´ et al. ,is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods. Data were collected from 243 men and women aged 55 years and older living in France using face-to- face interviews between 2011 and 2013. Results. A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers’ self-efficacy, internal memory, and attentional control strategies) of the level of PA. ,e function showed that the rate of correct prediction was 73% for the level of PA. ,e calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions. ,is study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. ,ese results are discussed in relation to successful aging. It is now well known that cognitive functions undergo 1. Introduction a decline during aging [8], and this decline is often associated Generally, physical activity adherence is examined by social with the use of compensatory cognitive strategies that could psychologists and health psychologists to prevent seden- help aging people cope with their diminished cognitive tariness. Reviews of the gerontological literature on this performances. For instance, some elderly people use external topic reveal a number of socioeconomic, demographic, memory strategies, such as writing a shopping list on a piece psychological, attitudinal, and accessibility correlates and/or of paper to compensate for a decline in episodic memory. In determinants of physical activity (PA) [1–5]. For instance, some cases, these strategies can be considered counter- productive in a long-term perspective because external when focusing on independently living elderly people, van Stralen et al. [2] and Koeneman et al. [3] reported several memory aids could stimulate negative stereotype related to moderate to strong determinants of regular PA such as age, aging by reducing perceived efficacy and perceived control gender, education, perceived health and depression, baseline on memory [9]. ,ese strategies could lead the individual to PA behavior, barriers’ self-efficacy, benefits of regular PA, reduce the cognitive resources used to initiate behaviors and, and social support. However, adherence also requires consequently, not to stimulate or maintain their self- continuous effort and strategies underpinned by executive regulation ability. ,us, each time an elderly person functions to maintain the behaviors involved in the healthy chooses to write his/her shopping list on a piece of paper to management of day-to-day living such as PA [6], diet avoid forgetting an item during shopping, he/she does not regimen, and medication [7]. stimulate his/her encoding and retrieval memory systems 2 Journal of Aging Research strategies: (1) internal strategies, such as using mental im- and consequently undermines his/her episodic memory in the long term. Fortunately, not all compensatory cognitive agery, recalling contextual cues, associating cues, or listing events; and (2) external strategies, such as making shopping strategies reduce the cognitive resources invested to cope with a problem but rather use alternate or vicarious cog- lists or writing down appointments on a calendar. Gould nitive systems, for instance, internal memory strategies [10]. et al. [27] have reported that older adults preferentially use In another respect, Lachman and Andreoletti [11] reported internal memory strategies—although this relationship is that when metacognitive beliefs were lacking, older adults mediated by depression and concerns about memory effi- were less strategic in solving problems, and this lack of cacy—to remember their medication but external memory mastery experiences reduced self-efficacy and resulted in less strategies for everyday situations. On the other hand, at- tentional control can be conceptualized as the ability to filter autonomy and more dependency. ,e relationship between cognitive functioning and information by focusing on pertinent cues and inhibiting nonpertinent cues [33]. Controlled inhibition can be con- adherence has been studied either by examining populations with cognitive impairments [12, 13] or by training pop- sidered a component of attentional control and concerns the ability to repress actions, thoughts, emotions, or impulses. ulations in cognitive processes [14–18]. ,ese studies have been principally carried out in the context of medication Attentional control was greatly examined by Hillman et al. adherence. For instance, studies have reported that older [22, 23] in relation to physical activity, and the authors people with cognitive dysfunctions show poor medication reported that PA activates the attentional system and mo- adherence compared to healthy older people [12] and that bilizes attentional resources. working memory ability or habitual prospective memory Many epidemiological studies have examined the benefits of facilitated recall of medication instructions [19, 20]. In their PA on cognition and have shown a positive relationship between higher levels of PA and a reduced risk of cognitive impairment systematic review on the efficacy of interventions to increase medication adherence among community-dwelling seniors (for a review, see [34, 35]). For instance, some studies based on ¨ large sample sizes and long follow-up periods have shown that with cognitive impairments, Kroger et al. [13] have shown that reminder strategies are promising to improve adher- older adults who had previously engaged in higher levels of PA were likely to perform better on cognitive tasks when compared ence. Finally, Karr et al. [21] have shown that regardless of the population and executive functions targeted, cognitive with participants with previously lower PA levels [36, 37]. training (specific or through physical activity) has positive Consequently, PA is hypothesized to have a protective effect on effects on adherence. To our knowledge, very few studies cognitive decline in older adults. ,e brain structures most have investigated the links between cognitive functioning negatively affected by aging are also those that benefit the most and adherence to physical activity with healthy older adults from physical activity (e.g., Colcombe et al. [38]). For in- [22–24]. As highlighted by McDonald-Miszczak et al. [25], stance, the prefrontal cortex and the hippocampus, which underlie executive functions and encoding of information in despite a lack of clear identification of the cognitive func- tions implied in the adherence process, the research liter- episodic memory, respectively, are more severely affected by aging than brain structures involved in procedural memory ature has identified several cognitive processes that can be considered to be responsible for psychological disturbances [39]. Because of this positive effect of PA on cognitive and nonadherence when they are impaired. Recently, Olson functions, it can be expected that active older adults will et al. [26] reported that cognitive functions such as working show better cognitive functioning and use better cognitive memory, controlled inhibition, attention, and task switching strategies than inactive ones. Reciprocally, better func- predicted PA adherence 6 months after the end of a PA tioning in executive functions may facilitate the mainte- program in older adults with metabolic diseases. Other nance of new healthy behaviors such as a physically active studies have identified prospective memory [14, 27], met- lifestyle [40], and consequently, it could be expected that amemory [8, 28], and attentional control [22, 29, 30] as aging people who use more effective cognitive strategies maintain a higher level of regular physical activity. determinants of high levels of cognitive functioning. It can be reasonably hypothesized that remembering planned ,e purpose of this study was to identify predictors of the level of PA among a sample of independent-living older sessions during the week (prospective memory) and inhibiting the desire to stop exercise when it is difficult healthy people from the PRAUSE project. We are particu- (controlled inhibition) are two high-level cognitive func- larly interested in the perception of use of cognitive strat- tions required to maintain the regular practice of a moderate egies rather than the effectiveness of these strategies. It can to vigorous level of PA over weeks, months, or years. On one be expected that because PA reduces the decline of cognitive hand, prospective memory is related to long-term memory functions and because the efficient functioning of cognitive and declarative memory, and it describes the ability to plan functions facilitates the use of functional strategies, we should observe differences between active and inactive older and successfully execute delayed intentions in the future [31]. People in general, and more particularly aging people, adults in the use of cognitive strategies. As suggested by West et al. [41], cognitive functions meaningfully influence use strategies to facilitate and/or solve a prospective memory task. Studies on prospective memory have demonstrated that thought and actions and determine adaptive coping to challenges in everyday life. ,e main objective of the present this cognitive process facilitates medication adherence [27]. Metamemory can be defined as the control and regulation of study was to examine whether cognitive strategies related to strategies necessary to address such memory tasks [32]. executive functions and prospective memory would predict More precisely, metamemory refers to two categories of the level of engagement in physical activity in older persons. Journal of Aging Research 3 slight depression, and a score of 20–30 corresponds to severe 2. Methods depression. 2.1. Description of Sample. ,e present study is a part of a French regional survey, a multidisciplinary research project entitled Seniors’ Autonomy Preservation in Poitou-Charentes 2.4. Physical Activity Measure. ,e level of current PA was (PRAUSE). ,e inclusion criteria to be eligible for the re- evaluated with the Historical Leisure Activity Questionnaire cruitment into PRAUSE were the following: (1) living in (HLAQ) [46]. ,is questionnaire was used to assess the Poitou-Charentes; (2) being aged 55 years or over; and (3) not history of PA weighted by relative intensity, and as suggested being institutionalized and not under guardianship or trust- by Kriska et al. [46], the list of activities was adapted to the eeship. Participants were invited to take part in the study by population. ,e HLAQ was previously used in French mail and phone. Project feasibility was tested with a pilot study, studies that demonstrated relationships between executive and three waves of data collection were necessary to include functions and level of physical activity [47, 48]. Participants a total of 466 participants. Each participant included in the were asked to report the frequency, type, intensity, and hours study performed one to three sessions of data collection of PA performed during the present year. Using the Com- according to his/her motivation. For the purposes of this study, pendium of Physical Activities Tracking Guide 2011 [49], we only 243 participants out of 466 completed all the data required obtained a specific metabolic equivalent (MET) for each PA. to test our hypotheses. ,is sample of participants included According to the HLAQ data and the compendium, we 41.57% males and had a mean age of 74.02 (SD � 9.61) years. calculated the average energy expenditure (METs-h/week) for each participant. According to the WHO recommendations, we classified the participants above 7.5 METs-h/week in the 2.2. Compliance with Ethical Standards. All participants active group and those below 7.5 METs-h/week in the inactive signed an informed consent form. ,e three data collection group. waves occurred between 2011 and 2013. All participants were visited at home, and all face-to-face questionnaires were administered by investigators who received individual 2.5. Cognitive Variables. Cognitive strategies were measured training for all data collection. ,e protocol of PRAUSE was using a questionnaire adapted from three scales: (1) the approved by two national ethics committees: (1) the “general Metamemory in Adulthood scale [50], (2) the ,ought interest and statistical quality” label from the French Na- Control Questionnaire [51], and (3) the Attentional Control tional Council of Statistical Information (CNIS, visa no. Scale [52] (Table 1). Metamemory concerns knowledge of 2012X907RG) and (2) the French National Commission on memory functioning, beliefs and affects about memory, as Informatics and Liberty (authorization no. 1593815). well as monitoring and autoregulation during memory activity [50]. ,e metamemory in adulthood scale contains 2.3. Demographic and Health Variables. Questionnaires eight subscales, from which two were selected and adapted for the study: the external strategy subscales (e.g., memos were completed with data including age, gender, perceived health status, education, depression, decisional balance, and and calendar) and the internal strategy subscales (e.g., mental imagery and word associations). ,ese scales BMI. Perceived health status was evaluated with a visual analogue scale from EuroQol-5D and consisted of assessing evaluate the means used by people to more easily find in- his/her perception of health from “best known health status” formation stored in prospective and episodic memory. ,e to “worse known health status.” ,e Decisional Balance external strategy subscales include 6 items and the internal questionnaire was based on Marcus’ version and adapted to subscale 9 items. Cronbach’s alphas for these two cognitive strategies were 0.66 and 0.70, respectively. ,e thought physical activity. It consisted of two constructs that underlie cognitive and motivational aspects of human decision control questionnaire contains five subscales designed to assess people’s tendency to use a variety of thought control making. ,ese constructs have been labeled the pros and cons of exercising, and they were each measured with 8 strategies in everyday life. Two subscales were selected and adapted for the needs of the study: the reappraisal subscale items. Participants responded to each item on a 5-point Likert-type scale ranging from totally agree (1) to totally (e.g., I try to reinterpret the thought) and the distraction subscale (e.g., I occupy myself with work instead). ,e disagree (5). Based on Bandura’s guidelines [42] and the identification of main barriers in old age reported in the reappraisal subscale includes 5 items and the distraction literature [43, 44], six barriers’ self-efficacy were included subscale 6 items. Cronbach’s alphas for these two cognitive based on health aspects (pain and fatigue), motivational strategies were 0.83 and 0.75, respectively. ,e short-form determinants (too busy and nobody to practice with), and Attentional Control Scale consisted of a 12-item self-report [52] measure combining attentional focusing that requires environmental factors (weather and accessibility). Partici- pants rated answers on a 5-point scale ranging from 1 (not voluntary control over behaviors and attentional shifting that is related to performance on switching tasks. Only the confident to overcome) to 5 (extremely confident to over- come). Cronbach’s alpha values were .76 for pros, .83 for attentional focusing strategy was evaluated in the study because of the link we posited with PA. ,is scale includes 6 cons, and .68 for barriers’ self-efficacy. Depression GDS, Depressive symptoms were assessed using the 30-item items. Participants rated answers on a 5-point scale ranging Geriatric Depression Scale validated in French by Bourque from 1 (never used) to 5 (always used) for the five strategy et al. [45]. A score of 0–9 is normal, a score of 10–19 indicates subscales. Cronbach’s alpha for this scale was 0.66. 4 Journal of Aging Research Table 1: Cognitive strategy questionnaires used in the study. External memory strategies I keep a list or otherwise note important dates, such as birthdays and anniversaries I write shopping list to help me remember I write appointments on a calendar to help me remember them I routinely keep things (keys or glasses) in a familiar spot, so I will not forget them when I need to locate them I post reminders of things I need to do in a prominent place, such as on bulletin boards or note boards When I want to take something with me, I leave it in an obvious, prominent place, such as putting my suitcase in front of the door Internal memory strategies When I am looking for something I have recently misplaced, I try to retrace my steps in order to locate it When I want to remember something, I concentrate hard on it When I try to remember a telephone number, I mentally repeat it to myself I think about the day’s activities at the beginning of the day, so I can remember what I am supposed to do I make mental images or pictures to help me remember an event or an individual I try to relate something I want to remember to something else hoping that this will increase the likelihood of my remembering later When I have trouble remembering something, I try to remember something similar in order to help me remember Reappraisal When I experience an unpleasant/unwanted thought, I challenge the thought’s validity When I experience an unpleasant/unwanted thought, I analyze the thought rationally When I experience an unpleasant/unwanted thought, I try to reinterpret the thought When I experience an unpleasant/unwanted thought, I try a different way of thinking about it When I experience an unpleasant/unwanted thought, I question the reasons for having the thought Distraction When I experience an unpleasant/unwanted thought, I call to mind positive images instead When I experience an unpleasant/unwanted thought, I occupy myself with work instead When I experience an unpleasant/unwanted thought, I think pleasant thoughts instead When I experience an unpleasant/unwanted thought, I do something that I enjoy When I experience an unpleasant/unwanted thought, I think about something else When I experience an unpleasant/unwanted thought, I keep myself busy Attentional control When concentrating on something and there are noises around me, I ask for silence When I read, I look for a calm area where I will not be distracted by people around me When I am working hard on something and I am distracted by events around me, I try to isolate myself When trying to focus my attention on something and thoughts distracting me, I chase them out of my mind When concentrating on something and hunger or thirst distracts me, I satisfy my need so that it does not worry me anymore When concentrating on something, I turn off TV or radio 2.6. Data Analysis. Descriptive statistics were examined to not depressed (6.48, SD � 4.80), used on average more in- characterize the study population. Correlation analyses and ternal memory strategies (30.28, SD � 5.21), and were not easily distracted (19.41, SD � 4.37). Participants who were t-tests were used to obtain additional descriptive in- formation and to identify a preliminary set of predictor inactive had a mean age of 77.66 (SD � 9.75), had a mean variables to be included in the discriminant analysis. Var- BMI of 28.70 (SD � 4.70), perceived themselves in worse iables with a significant difference of p< 0.05 as determined health (66.37, SD � 18.01), perceived themselves as less ca- by the above tests were entered into stepwise discriminant pable of overcoming barriers (31.85, SD � 10.06), used on analysis. ,en, a stepwise discriminant analysis was per- average less internal memory (28.76, SD � 6.61), and had formed to determine if active and inactive participants could difficulties in concentrating (20.46, SD � 5.04). be discriminated based on the following variables: age, ,e emphasis of this analysis was on understanding how gender, body mass index (BMI), perceived health status, these variables were related to each other to determine the depression, barriers’ self-efficacy, and cognitive strategies level of physical activity. We used discriminant analysis to (internal memory and attentional control). determine the linear combination of predictor variables that best classified the cases into the two groups. ,e step- wise discriminant analysis (Table 3) showed that Wilks’ 3. Results lambda, as a test of discriminant function, was significant Table 2 shows distributions of sociodemographic charac- (lambda � 0.736; χ � 72.051, df � 8, p< 0.001) and selected teristics and other covariates. Participants who were active the five following variables as determinants of physical in- had a mean age of 71.45 (SD � 8.65), had a mean BMI of activity (based on structure matrix loading): older (−0.626), 26.88 (SD � 4.94), perceived themselves on average in better perceived poor health (0.442), less use of internal memory health (75.46, SD � 14.27), perceived themselves on average strategies (0.213), attentional control (−0.196), and poor as capable of overcoming barriers (38.51, SD � 9.83), were confidence to overcome barriers to PA practice (0.555). Journal of Aging Research 5 Table 2: Sociodemographic, health, motivational, and cognitive strategies for active versus inactive participants. ,e last column shows the correlations between the variable and the level of physical activity for the population sample examined in this study (n � 243). Variables Active (n � 139) mean (SD) Inactive (n � 104) mean (SD) p Correlation coefficient ✓ Age (years) 71.45 (8.65) 77.66 (9.75) Ϯ −0.35Ϯ ✓ Gender (M/F) 71/68 29/75 Ϯ 0.23Ϯ ✓Education 10.52 (3.66) 10.20 (3.80) ns 0.05 ✓ BMI 26.88 (4.94) 28.70 (4.70) Ϯ −0.18Ϯ ✓ Perceived health status 75.46 (14.27) 66.37 (18.01) Ϯ 0.26Ϯ ✓ Depression 6.48 (4.80) 9.067 (5.05) Ϯ −0.14Ϯ Decisional variables ✓Pros 15.84 (6.14) 17.27 (6.10) ns −0.11 ✓ Barriers’ self-efficacy 38.51 (9.83) 31.85 (10.06) Ϯ 0.36Ϯ Cognitive strategies EMS (from 6 to 30) 23.86 (4.02) 24.30 (4.42) ns −0.06 IMS (from 9 to 45) 30.28 (5.16) 28.76 (6.61) Ϯ 0.12 ACS (from 6 to 30) 19.43 (3.68) 20.46 (5.04) Ϯ −0.11 DS (from 6 to 30) 20.60 (4.94) 20.21 (5.40) ns 0.04 RS (from 5 to 25) 14.58 (4.05) 13.62 (4.56) ns 0.11 ✓Variables reported as moderately to strongly significant in the literature. Variables entered in the current discriminant analysis. Ϯ � p< 0.05, ns � nonsignificant (p> 0.05). EMS: external memory strategies, IMS: internal memory strategies, ACS: attentional control strategies, DS: distraction strategies, and RS: reappraisal strategies. Table 3: Summary of interpretive measures for stepwise discriminant analysis. Predictor Standardized coefficient loadings F ratio Rank ∗∗ Age −0.626 15.239 1 Gender 0.413 1.469 BMI −0.307 3.824 Perceived health status 0.442 4.230 4 Depression −0.434 0.739 Internal memory 0.213 10.684 2 Attentional control −0.196 9.761 3 Barriers’ self-efficacy 0.555 3.948 5 Canonical correlation 0.513 Eigenvalue 0.358 Wilks’ lambda 0.736 χ 72.051; df � 8 ∗ ∗∗ p< 0.01, p< 0.001. Wilks’ lambda, which describes the proportion of total sarcopenia, or social isolation. Most studies that have ex- variance in the discriminant score not explained by differ- amined the factors associated with sedentariness or in- ences between groups, was significant, indicating that it is activity have focused on psychosocial predictors. However, unlikely that participants who were inactive and those who cognitive functions have recently been considered in ad- were active had the same means on the discriminant herence to treatment medication [12, 13], but to our functions generated from the prediction equation. knowledge, no study has examined the predictive value of Table 4 summarizes the group membership results of the cognitive strategies in adherence to PA in healthy older classification routine. Of the 104 participants who were adults. ,e aim of the present study was to identify cognitive inactive, 63 (60.6%) were correctly classified as inactive, and and psychosocial determinants of the level of PA in in- of the 139 participants who were active, 113 (81.3%) were dependently living healthy older adults in France. correctly classified as active based on the selected variables. First, no difference was observed between active and ,e overall percentage of the level of PA classifications was inactive healthy older adults when considering level of 73%, reflecting a 23% improvement over chance alone. Of education, knowledge concerning the benefits of regular PA, the variables investigated, age was the most discriminating the use of external memory strategies, cognitive and be- and barriers’ self-efficacy the least. havioral distractions, or reappraisal. ,ese results are par- tially consistent with previous literature reviews examining the relationships between sociodemographic and psycho- 4. Discussion social determinants and the level of PA [2, 3, 53]. ,e results Sedentariness and inactivity are legitimate problems in older concerning knowledge about the benefits of regular PA adults because these behaviors lead to several health suggest that information provided by the campaigns of problems such as more pronounced cognitive decline, prevention are well retained by individuals in general, 6 Journal of Aging Research Table 4: Classification results of the discriminant analysis. Group Number of cases Predicted group inactive n (%) Membership active, n (%) Inactive 104 63 (60.6%) 41 (39.4%) Active 139 24 (17.2%) 113 (81.3%) 73.03% of grouped cases were correctly classified and 26.97% of grouped cases were incorrectly classified. which appeared as a predictor of the level of PA in the regardless of their level of engagement in regular PA. As suggested by Gross and Rebok [53], however some de- present study, were already reported as predictive of mographic predictors such as gender, pros of exercising, and adherence to PA [56], more precisely, in elderly women in a level of education could be used in high-risk populations, 6-month strength training program. In this last study, barriers’ these predictors are not necessarily significant in healthy self-efficacy were a good predictor of the first three months of populations. It is interesting to note that, in the present exercise adherence and remained a significant predictor after study, active older adults scored lower on the pros scale than six months. In the present study, barriers’ self-efficacy were inactive ones. ,is result could indicate that inactive older a good predictor of regular and habitual physical activity. adults overestimate pros but are not interested or concerned Both studies suggest that barriers’ self-efficacy are a good predictor of exercise adherence from a long-term perspective, by these potential benefits. ,ree out of five cognitive strategies showed no significant differences between active possibly because this variable positively influences motiva- tion to practice by increasing effort and persistence as well and inactive older adults, with external strategies being more used than the other strategies by older adults in general as enhancing attention paid to tasks. (M � 4.82; close to “always used”), followed by distraction ,e important contribution of this study is the dis- (M � 3.43; close to “sometimes used”) and reappraisal criminant power of cognitive strategies, indicating that strategies (M � 2.36; close to “rarely used”), the latter being active older people perceive themselves as using more in- the least used and referring to problem solving. ,ese results ternal memory strategies—assessing prospective and epi- could be interpreted in two ways: (1) maintaining a high level sodic memory—and as more able of using controlled inhibition than inactive ones. In other words, these per- of PA involves specific cognitive functions and strategies and (2) practicing a high level of PA facilitates the use of higher ceptions would favor engagement in physical activity be- cause they would reinforce positive perception of one’s own cognitive functions and strategies. ,is study also revealed some interesting results con- efficacy to interact with environment. Another explanation could be that practicing moderate to high level of physical cerning predictors of the level of PA that could contribute to reinforce interventions intended to help older people adhere activity improves episodic memory and consequently fa- to long-term PA practice. ,e discriminant analysis revealed cilitates the use of internal memory by older adults and their that among the variables that emerged as significantly perception of using these strategies. Because this study was predictive of the level of PA, age, perceived health, barriers’ cross-sectional, we cannot define a causal relationship be- self-efficacy, internal memory strategies, and attentional tween these variables. Notwithstanding, a first assumption control strategies predominantly discriminated between would be that older adults who have better memory abilities and/or better attentional control engage themselves more active and inactive older participants in successfully clas- sifying 73% of participants. Concerning sociodemographic easily in active behaviors. ,is explanation is reinforced by previous research that has reported that the use of memory and psychosocial variables, these results are congruent with previous studies. First, several studies [2, 3] moderately strategies facilitates the management of daily living activities suggested that males are generally more active than females. [7], medication adherence [19, 26], and PA [15]. To our Unlike these studies, gender was not a predictor of the level knowledge, only the study carried out by Olson et al. [26] of PA in the present study. In a recent systematic review [54], reporteda relationship between attention and adherence to it appears that gender differences in walking is attenuated for PA and postulated that controlled inhibition is critical to old adults (>70 years). Second, perceived health status was successful behavior changes. In other words, attentional presently identified as a determinant of engagement in PA control ability is important for switching between goal- but not depression. However, McHugh and Lawlor [55] have directed plans and environment-based responses. Accord- ing to the temporal self-regulation model proposed by Hall reported an overadditive interaction of these two variables on hours of exercise per week such that high perceived and Fong [6], executive functions are involved in PA be- havior. However, these authors did not provide any details health status combined with low levels of depression resulted in the highest levels of exercise. In the present study, even if concerning the specific executive functions involved in depression was correlated to the level of PA, this variable did adherence, such as planning, cognitive flexibility, or con- not discriminate between active and inactive older adults. trolled inhibition. ,e present results clearly show that Consequently, it could be suggested that (1) perceived health specific cognitive functions are associated with PA behavior: status and depression share a common variance, certainly presumably, prospective memory related to internal mem- because global perceived health status includes a component ory strategies and controlled inhibition related to attentional of mental health status such as depression (r �−0.365 for this control strategies. A second assumption would be that by study) or (2) perceived health status is a better predictor of being active, older adults increase their memory abilities and their attentional control. For instance, Winnecke et al. [30] PA than depression. ,ird, and finally, barriers’ self-efficacy, Journal of Aging Research 7 reported that individuals with higher levels of PA showed Authors’ Contributions better attentional control capabilities than those who are less All authors have contributed significantly to the research active. ,is result confirms the proposition made by Hillman concept, literature review, objectives, and design of the et al. [23] that PA can activate the attentional system and study. ,ey all are in agreement with the content of the mobilize attentional resources. From that perspective, other manuscript. All authors approved the manuscript and this studies showed that controlled inhibition seems to benefit submission. more selectively from PA than from other executive func- tions [57, 58]. Studies on memory training programs re- ported that memory strategies are needed to maintain References regular activity with a low investment of cognitive resources [1] S. G. Trost, N. Owen, A. E. Bauman, J. F. Sallis, and W. Brown, [59]. For instance, Wolff et al. [59] reported that action “Correlates of adults’ participation in physical activity: review planning, defined by the authors as being strongly related to and update,” Medicine and Sciences in Sports and Exercise, memory strategies, facilitates the enactment of health be- vol. 34, no. 12, pp. 1996–2001, 2002. havior in daily life. What is interesting to note here is that [2] M. M. van Stralen, H. De Vries, A. N. Mudde, C. Bolman, memory strategies are not necessarily associated with high and L. Lechner, “Determinants of initiation and mainte- prospective memory ability. In other words, physically active nance of physical activity among older adults: a literature older adults might compensate for cognitive deficits by review,” Health Psychology Review, vol. 3, no. 2, pp. 147–207, recruiting larger frontal areas relevant for memory and/or [3] M. A. Koeneman, M. W. Verheijden, M. J. M. Chinapaw, and attentional control strategies. ,is compensatory mecha- M. Hopman-Rock, “Determinants of physical activity and nism would not necessarily consist of an increase of the exercise in healthy older adults: a systematic review,” In- efficiency of these functions but in a better use of the ternational Journal of Behavioral Nutrition and Physical Ac- cognitive strategies. ,ese strategies could, in turn, facilitate tivity, vol. 8, no. 1, p. 142, 2011. the day-to-day management of life and perceived health. [4] A. E. Bauman, R. S. Reis, J. F. Sallis, J. C. Wells, R. J. Loos, and ,ere is now substantial literature demonstrating this re- B. W. Martin, “Correlates of physical activity: why are some ciprocal effect, and our results confirm and specify the people physically active and others not?,” <e Lancet, vol. 38, theoretical position taken by Hall and Fong [6] on the no. 9838, pp. 258–271, 2012. mutual reinforcement of executive functions and PA over [5] B. Guinn and V. Vincent, “Select physical activity de- time. Our results argue in the direction of this model, and terminants in independent-living elderly,” Activities, Adap- tation & Aging, vol. 26, no. 4, pp. 17–26, 2002. particular attention should be paid to the cognitive strategies [6] P. A. Hall and G. T. Fong, “Temporal self-regulation theory: involved according to the targeted behavior. ,e present a neurobiologically informed model for physical activity study has certain limitations. First, the study employed cross- behaviour,” Frontiers in Human Neuroscience, vol. 9, p. 117, sectional data, precluding any assumptions concerning cau- sality between the five variables selected as predictors and the [7] R. L. West, D. K. Bagwell, and A. Dark-Freudeman, “Self- level of PA. Moreover, those variables and the level of PA efficacy and memory aging: the impact of a memory in- might have changed over time. Further analysis of longitu- tervention based on self-efficacy,” Aging, Neuropsychology, dinal data is warranted to clarify the relationship between and Cognition, vol. 15, no. 3, pp. 302–329, 2008. changes in the five predictors obtained and PA. Another [8] S. Colcombe and A. F. Kramer, “Fitness effects on the cog- limitation to this study is its reliance on self-reported data on nitive function of older adults: a meta-analytic study,” Psy- chological Science, vol. 14, no. 2, pp. 125–130, 2003. the five selected variables and PA. [9] B. Levy, “Stereotype embodiment: a psychological approach to aging,” Current Directions in Physical Science, vol. 18, no. 6, 5. Conclusion pp. 332–336, 2009. [10] B. Bouazzaoui, M. Isingrini, S. Fay et al., “Aging and self- Rather than seeing older people as lacking motivation for reported internal and external memory strategy uses: the role physical activities, this study identified cognitive and psy- of executive functioning,” Acta Psychologica, vol. 135, no. 1, chosocial predictors of the level of PA to evaluate the pp. 59–66, 2010. likelihood of relapses or quitting and to reduce the risk [11] M. E. Lachman and C. Andreoletti, “Strategy use mediates the factors through interventions among older people at in- relationship between control beliefs and memory perfor- creased risk of inactivity. Regardless of whether age is an mance for middle-aged and older adults,” Journal of Geron- irreversible process, this study raises awareness of the need tology: Psychological Sciences, vol. 61, no. 2, pp. P88–P94, to consider cognitive strategies as facilitators to engage in [12] F. Misokami, M. Hiroki, T. Kinoshita, T. Kumagai, K. Futura, durable PA. ,e development of specific cognitive strategies and I. Kazuhiro, “Adherence to medication regimens is an related to cognitive functions seems a relevant element to effective indicator of cognitive dysfunction in elderly in- facilitate the management of daily life and preservation from dividuals,” American Journal of Alzheimer’s Disease and Other sedentariness. Dementias, vol. 31, no. 2, pp. 132–136, 2016. [13] E. Kroger, ¨ O. Tatar, I. Vedel et al., “Improving medication Conflicts of Interest adherence among community-dwelling seniors with cognitive impairment: a systematic review of interventions,” In- ,e authors declare that there are no conflicts of interest ternational Journal of Clinical Pharmacy, vol. 39, no. 4, regarding the publication of this article. pp. 641–656, 2017. 8 Journal of Aging Research [14] A. Hering, P. G. Rendell, N. S. Rose, K. M. Schnitzspahn, and [30] A. H. Winnecke, B. Godde, E.-M. Reuter, S. Vieluf, and M. Kliegel, “Prospective memory training in older adults and C. Voelcker-Rehage, “,e association between physical ac- its relevance for successful aging,” Psychological Research, tivity and attentional control in younger and older middle- vol. 78, no. 6, pp. 892–904, 2014. aged adults: an ERP study,” GeroPsychology, vol. 25, no. 4, [15] J. R. Best, L. S. Nagamatsu, and T. Liu-Ambrose, “Im- pp. 207–221, 2012. provements to executive functions during exercise training [31] M. Kliegel, M. A. McDaniel, and G. O. Einstein, Prospective predict maintenance of physical activity over the following Memory: Cognitive, Neuroscience, Developmental, and Applied year,” Frontiers in Human Neuroscience, vol. 8, p. 353, 2014. Perspectives, Erlbaum, Mahwah, NJ, USA, 2008. [16] M. A. Wiegand, A. K. Troyer, C. Gojmerac, and K. J. Murphy, [32] A.-P. Le Berre, F. Eustache, and H. Beaunieux, “La “Facilitating change in health-related behaviors and in- metam ´ emoire: ´ theorie ´ et clinique,” Revue de Neuro- tentions: a randomized controlled trial of a multidimensional psychologie, vol. 1, no. 4, pp. 312–320, 2009. memory program for older adults,” Aging and Mental Health, [33] D. Derryberry and M. A. Reed, “Anxiety-related attentional vol. 17, no. 7, pp. 806–815, 2013. biases and their regulation by attentional control,” Journal of [17] N. L. Campbell, J. Zhan, W. Tu et al., “Self-reported medi- Abnormal Psychology, vol. 111, no. 2, pp. 225–236, 2002. cation adherence barriers among ambulatory older adults [34] M. Audiffren, N. Andre, ´ and C. Albinet, “Effets positifs de with mild cognitive impairment,” Pharmacotherapy, vol. 36, l’exercice physique chronique sur les fonctions cognitives des no. 2, pp. 196–202, 2016. seniors: bilan et perspective,” Revue de Neuropsychologie, [18] A. Hernandez-Galiot and I. Goni, “Adherence to the Medi- vol. 3, no. 4, pp. 207–225, 2011. terranean diet pattern, cognitive status and depressive [35] L. Bherer, K. I. Erickson, and T. Liu-Ambrose, “A review of symptoms in an elderly non-institutionalized population,” the effects of physical activity and exercise on cognitive and Nutricion Hospitalaria, vol. 34, no. 2, pp. 338–344, 2017. brain functions in older adults,” Journal of Aging Research, [19] S. D. Neupert and L. McDonald-Miszczak, “Younger and vol. 2013, Article ID 197326, 2 pages, 2013. older adults’ delayed recall of medication instructions: the role [36] F. Sofi, D. Valecchi, D. Bacci, R. Abbate, G. F. Gensini, and of cognitive and metacognitive predictors,” Aging, Neuro- C. Macchi, “Physical activity and risk of cognitive decline : psychology, and Cognition, vol. 11, no. 4, pp. 428–442, 2004. a meta-analysis of prospective studies,” Journal of Internal [20] K. Vedhara, E. Wadsworth, P. Norman et al., “Habitual Medicine, vol. 269, no. 1, pp. 107–117, 2011. prospective memory in elderly patient with type 2 diabetes: [37] K. Yaffe, D. Barnes, M. Nevitt, L. Y. Lui, and K. Covinsky, “A implications for medication adherence,” Psychology, Health & prospective study of physical activity and cognitive decline in Medicine, vol. 9, no. 1, pp. 17–27, 2004. elderly women: women who walk,” Archives of Internal [21] J. E. Karr, C. N. Areshenkoff, P. Rast, and M. A. Garcia- Medicine, vol. 161, no. 14, pp. 1703–1708, 2001. Barrera, “An empirical comparison of the therapeutic benefits [38] S. J. Colcombe, K. I. Erickson, N. Raz et al., “Aerobic fitness of physical exercise and cognitive training on the executive reduces brain tissue loss in aging humans,” Journal of Ger- functions of older adults: a meta-analysis of controlled trials,” ontology, vol. 58, no. 2, pp. 176–180, 2003. Neuropsychology, vol. 28, no. 6, pp. 829–845, 2014. [39] D. B. Mitchell, “How many memory system? Evidence from [22] C. H. Hillman, A. F. Kramer, A. V. Belopolsky, and D. P. Smith, “A aging,” Journal of Experimental Psychology: Learning, Mem- cross-sectional examination of age and physical activity on per- ory, and Cognition, vol. 15, no. 1, pp. 31–49, 1989. formance and event-related brain potentials in a task switching [40] J. L. Allan, D. McMinn, and M. Daly, “A bidirectional re- paradigm,” International Journal of Psychophysiology, vol. 59, no.1, lationship between executive function and health behavior: pp. 30–39, 2006. evidence, implications, and future directions,” Frontiers in [23] C. H. Hillman, K. I. Erickson, and A. F. Kramer, “Be smart, Neurosciences, vol. 10, p. 386, 2016. exercise your heart: exercise effects on brain and cognition,” [41] R. West, M. S. Beeri, J. Schmeidler et al., “Better memory Nature Reviews, vol. 9, no. 1, pp. 58–65, 2008. functioning associated with higher total and low-density li- [24] C. B. Phillips, J. D. Edwards, R. Andel, and M. Kilpatrick, “Daily poprotein cholesterol levels in very elderly subjects without physical activity and cognitive function variability in older adults,” the apolipoprotein e4 allele,” American Journal of Geriatric Journal of Aging and Physical Activity, vol. 24, no. 2, pp. 256–267, Psychiatry, vol. 16, no. 9, pp. 781–785, 2008. [42] A. Bandura, “Guide for constructing self-efficacy scales,” in [25] L. McDonald-Miszczak, S. D. Neupert, and G. Gutman, “Does Self-Efficacy Beliefs of Adolescents, F. Pajares and T. Urdan, cognitive ability explain inaccuracy in older adults’ self- Eds., pp. 307–337, Information Age Publishing, Greenwich, reported medication adherence?,” Journal of Applied Geron- CT, USA, 2006. tology, vol. 28, no. 5, pp. 560–581, 2009. [43] C. ,ogersen-Ntoumani, “An ecological model of predictors [26] E. A. Olson, S. P. Mullen, L. B. Raine, A. F. Kramer, of stages of change for physical activity in Greek older adults,” C. H. Hillman, and E. McAuley, “Integrated social and Scandinavian Journal of Medicine and Sciences in Sports, neurocognitive model of physical activity behavior in older vol. 19, no. 2, pp. 286–296, 2009. adults with metabolic disease,” Annals of Behavioral Medicine, [44] K. L. Smith, K. Carr, A. Wiseman, K. Calhoun, N. H. McNevin, vol. 51, no. 2, pp. 272–281, 2017. and P. L. Weir, “Barriers are not the limiting factor to par- [27] O. N. Gould, L. McDonald-Miszczak, and B. King, “Metacognition ticipation in physical activity in Canadian seniors,” Journal of and medication adherence: how do older adults remember?,” Aging Research, vol. 2012, Article ID 890679, 8 pages, 2012. Experimental Aging Research, vol. 23, no. 4, pp. 315–342, 1997. [45] P. Bourque, L. Blanchard, and J. Vezina, “Etude psychom´e- [28] L. Taconnat and P. Lemaire, “Fonctions executives, ´ vieil- trique de l’´echelle de depression ´ g´eriatrique,” Canadian lissement cognitif et variations strategiques,” ´ Psychologie Française, vol. 59, no. 1, pp. 89–100, 2014. Journal of Aging, vol. 9, no. 4, pp. 348–355, 1990. [29] C. Lustig, L. Hasher, and S. T. Tonev, “Distraction as a de- [46] A. M. Kriska, R. B. Sandler, J. A. Cauley, R. E. Laporte, terminant of processing speed,” Psychonomic Bulletin & Review, D. L. Hom, and G. Pambianco, “,e assessment of historical vol. 13, no. 4, pp. 619–625, 2006. physical-activity and its relation to adult bone parameters,” Journal of Aging Research 9 American Journal of Epidemiology, vol. 127, no. 5, pp. 1053– 1063, 1988. [47] G. K. Boucard, C. T. Albinet, A. Buga¨ıska, C. A. Bouquet, D. Clarys, and M. Audiffren, “Impact of chronic exercise on executive functions in aging: a selective effect to inhibition performance among middle-old adults,” Journal of Sport and Exercise Psychology, vol. 34, no. 6, pp. 808–827, 2012. [48] A. Canivet, C. T. Albinet, N. Andre´ et al., “Effects of BDNF polymorphism and physical activity on episodic memory in the elderly: a cross sectional study,” European Review of Aging and Physical Activity, vol. 12, p. 15, 2015. [49] B. E. Ainsworth, W. L. Haskell, S. D. Herrmann et al., “Compendium of physical activities: a second update of codes and MET values,” Medicine and Sciences in Sports and Ex- ercise, vol. 43, no. 8, pp. 1575–1581, 2011. [50] R. A. Dixon, D. F. Hultsch, and C. Hertzog, “,e meta- memory in adulthood (MIA) questionnaire,” Psychophar- macology Bulletin, vol. 24, no. 4, pp. 671–688, 1988. [51] A. Wells and M. I. Davies, “,e thought control question- naire: a measure of individual differences in the control of unwanted thoughts,” Behaviour Research and <erapy, vol. 32, no. 8, pp. 871–878, 1994. [52] M. T. Judah, D. M. Grant, A. C. Mills, and W. V. Lechner, “Factor structure and validation of the attentional control scale,” Cognition and Emotion, vol. 28, no. 3, pp. 433–451, [53] A. L. Gross and G. W. Rebok, “Memory training and strategy use in older adults: results from the ACTIVE study,” Psy- chology and Aging, vol. 26, no. 3, pp. 503–517, 2011. [54] T. M. Pollard and J. M. Wagnild, “Gender differences in walking (for leisure, transport and in total) across adult life: a systematic review,” BMC Public Health, vol. 17, no. 1, p. 341, [55] J. E. McHugh and B. A. Lawlor, “Perceived health status is associated with hours of exercise per week in older adults independent of physical health,” Journal of Physical Activity and Health, vol. 10, no. 8, pp. 1102–1108, 2013. [56] R. E. Rhodes, A. D. Martin, and J. E. Taunton, “Temporal relationships of self-efficacy and social support as predictors of adherence in a 6-month strength-training program for older women,” Perceptual and Motor Skills, vol. 93, no. 7, pp. 693–703, 2001. [57] G. K. Boucard, C. T. Albinet, A. Bugaiska, C. A. Bouquet, D. Clarys, and M. Audiffren, “Impact of physical activity on executive functions in aging: a selective effect on inhibition among old adults,” Journal of Sport and Exercise Psychology, vol. 34, no. 6, pp. 808–827, 2012. [58] A. L. Smiley-Oyen, K. A. Lowry, S. J. Francois, M. L. Kohut, and P. Ekkekakis, “Exercise, fitness, and neurocognitive function in older adults: the selective improvement and cardiovascular fitness hypotheses,” Annals of Behavioral Medicine, vol. 36, no. 3, pp. 280–291, 2008. [59] J. K. Wolff, L. M. Warner, J. P. Ziegelmann, S. Wurm, and M. Kliegel, “Translating good intentions into physical activity: older adults with low prospective memory ability profit from planning,” Journal of Behavioral Medicine, vol. 39, no. 3, pp. 472–482, 2016. MEDIATORS of INFLAMMATION The Scientific Gastroenterology Journal of World Journal Research and Practice Diabetes Research Disease Markers Hindawi Hindawi Publishing Corporation Hindawi Hindawi Hindawi Hindawi www.hindawi.com Volume 2018 http://www www.hindawi.com .hindawi.com V Volume 2018 olume 2013 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 International Journal of Journal of Immunology Research Endocrinology Hindawi Hindawi www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 Submit your manuscripts at www.hindawi.com BioMed PPAR Research Research International Hindawi Hindawi www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 Journal of Obesity Evidence-Based Journal of Journal of Stem Cells Complementary and Ophthalmology International Alternative Medicine Oncology Hindawi Hindawi Hindawi Hindawi Hindawi www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2013 Parkinson’s Disease Computational and Behavioural Mathematical Methods AIDS Oxidative Medicine and in Medicine Neurology Research and Treatment Cellular Longevity Hindawi Hindawi Hindawi Hindawi Hindawi www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Aging Research Hindawi Publishing Corporation

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

Download PDF
10 pages

Loading next page...
 
/lp/hindawi-publishing-corporation/cognitive-strategies-and-physical-activity-in-older-adults-a-wxOnFQ0ISg

References (65)

Publisher
Hindawi Publishing Corporation
Copyright
Copyright © 2018 Nathalie André et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ISSN
2090-2204
eISSN
2090-2212
DOI
10.1155/2018/8917535
Publisher site
See Article on Publisher Site

Abstract

Hindawi Journal of Aging Research Volume 2018, Article ID 8917535, 9 pages https://doi.org/10.1155/2018/8917535 Research Article Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis 1,2 3 1,4 1,2 Nathalie Andre´ , Claude Ferrand, Ce´dric Albinet , and Michel Audiffren Centre de Recherches sur la Cognition et l’Apprentissage, UMR CNRS 7295, Universit´e de Poitiers, Poitiers, France Maison des Sciences de l’Homme et de la Soci´et´e, USR CNRS 3565, Universit´e de Poitiers, Poitiers, France EA 2114, Psychologie des aˆges de la vie, Universit´e François Rabelais, Tours, France Laboratoire Sciences de la Cognition, Technologie, Ergonomie (SCoTE), Universit´e de Toulouse, INU Champollion, Albi, France Correspondence should be addressed to Nathalie Andre´; nathalie.andre@univ-poitiers.fr Received 18 November 2017; Revised 18 February 2018; Accepted 22 March 2018; Published 5 April 2018 Academic Editor: Barbara Shukitt-Hale Copyright © 2018 Nathalie Andre´ et al. ,is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods. Data were collected from 243 men and women aged 55 years and older living in France using face-to- face interviews between 2011 and 2013. Results. A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers’ self-efficacy, internal memory, and attentional control strategies) of the level of PA. ,e function showed that the rate of correct prediction was 73% for the level of PA. ,e calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions. ,is study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. ,ese results are discussed in relation to successful aging. It is now well known that cognitive functions undergo 1. Introduction a decline during aging [8], and this decline is often associated Generally, physical activity adherence is examined by social with the use of compensatory cognitive strategies that could psychologists and health psychologists to prevent seden- help aging people cope with their diminished cognitive tariness. Reviews of the gerontological literature on this performances. For instance, some elderly people use external topic reveal a number of socioeconomic, demographic, memory strategies, such as writing a shopping list on a piece psychological, attitudinal, and accessibility correlates and/or of paper to compensate for a decline in episodic memory. In determinants of physical activity (PA) [1–5]. For instance, some cases, these strategies can be considered counter- productive in a long-term perspective because external when focusing on independently living elderly people, van Stralen et al. [2] and Koeneman et al. [3] reported several memory aids could stimulate negative stereotype related to moderate to strong determinants of regular PA such as age, aging by reducing perceived efficacy and perceived control gender, education, perceived health and depression, baseline on memory [9]. ,ese strategies could lead the individual to PA behavior, barriers’ self-efficacy, benefits of regular PA, reduce the cognitive resources used to initiate behaviors and, and social support. However, adherence also requires consequently, not to stimulate or maintain their self- continuous effort and strategies underpinned by executive regulation ability. ,us, each time an elderly person functions to maintain the behaviors involved in the healthy chooses to write his/her shopping list on a piece of paper to management of day-to-day living such as PA [6], diet avoid forgetting an item during shopping, he/she does not regimen, and medication [7]. stimulate his/her encoding and retrieval memory systems 2 Journal of Aging Research strategies: (1) internal strategies, such as using mental im- and consequently undermines his/her episodic memory in the long term. Fortunately, not all compensatory cognitive agery, recalling contextual cues, associating cues, or listing events; and (2) external strategies, such as making shopping strategies reduce the cognitive resources invested to cope with a problem but rather use alternate or vicarious cog- lists or writing down appointments on a calendar. Gould nitive systems, for instance, internal memory strategies [10]. et al. [27] have reported that older adults preferentially use In another respect, Lachman and Andreoletti [11] reported internal memory strategies—although this relationship is that when metacognitive beliefs were lacking, older adults mediated by depression and concerns about memory effi- were less strategic in solving problems, and this lack of cacy—to remember their medication but external memory mastery experiences reduced self-efficacy and resulted in less strategies for everyday situations. On the other hand, at- tentional control can be conceptualized as the ability to filter autonomy and more dependency. ,e relationship between cognitive functioning and information by focusing on pertinent cues and inhibiting nonpertinent cues [33]. Controlled inhibition can be con- adherence has been studied either by examining populations with cognitive impairments [12, 13] or by training pop- sidered a component of attentional control and concerns the ability to repress actions, thoughts, emotions, or impulses. ulations in cognitive processes [14–18]. ,ese studies have been principally carried out in the context of medication Attentional control was greatly examined by Hillman et al. adherence. For instance, studies have reported that older [22, 23] in relation to physical activity, and the authors people with cognitive dysfunctions show poor medication reported that PA activates the attentional system and mo- adherence compared to healthy older people [12] and that bilizes attentional resources. working memory ability or habitual prospective memory Many epidemiological studies have examined the benefits of facilitated recall of medication instructions [19, 20]. In their PA on cognition and have shown a positive relationship between higher levels of PA and a reduced risk of cognitive impairment systematic review on the efficacy of interventions to increase medication adherence among community-dwelling seniors (for a review, see [34, 35]). For instance, some studies based on ¨ large sample sizes and long follow-up periods have shown that with cognitive impairments, Kroger et al. [13] have shown that reminder strategies are promising to improve adher- older adults who had previously engaged in higher levels of PA were likely to perform better on cognitive tasks when compared ence. Finally, Karr et al. [21] have shown that regardless of the population and executive functions targeted, cognitive with participants with previously lower PA levels [36, 37]. training (specific or through physical activity) has positive Consequently, PA is hypothesized to have a protective effect on effects on adherence. To our knowledge, very few studies cognitive decline in older adults. ,e brain structures most have investigated the links between cognitive functioning negatively affected by aging are also those that benefit the most and adherence to physical activity with healthy older adults from physical activity (e.g., Colcombe et al. [38]). For in- [22–24]. As highlighted by McDonald-Miszczak et al. [25], stance, the prefrontal cortex and the hippocampus, which underlie executive functions and encoding of information in despite a lack of clear identification of the cognitive func- tions implied in the adherence process, the research liter- episodic memory, respectively, are more severely affected by aging than brain structures involved in procedural memory ature has identified several cognitive processes that can be considered to be responsible for psychological disturbances [39]. Because of this positive effect of PA on cognitive and nonadherence when they are impaired. Recently, Olson functions, it can be expected that active older adults will et al. [26] reported that cognitive functions such as working show better cognitive functioning and use better cognitive memory, controlled inhibition, attention, and task switching strategies than inactive ones. Reciprocally, better func- predicted PA adherence 6 months after the end of a PA tioning in executive functions may facilitate the mainte- program in older adults with metabolic diseases. Other nance of new healthy behaviors such as a physically active studies have identified prospective memory [14, 27], met- lifestyle [40], and consequently, it could be expected that amemory [8, 28], and attentional control [22, 29, 30] as aging people who use more effective cognitive strategies maintain a higher level of regular physical activity. determinants of high levels of cognitive functioning. It can be reasonably hypothesized that remembering planned ,e purpose of this study was to identify predictors of the level of PA among a sample of independent-living older sessions during the week (prospective memory) and inhibiting the desire to stop exercise when it is difficult healthy people from the PRAUSE project. We are particu- (controlled inhibition) are two high-level cognitive func- larly interested in the perception of use of cognitive strat- tions required to maintain the regular practice of a moderate egies rather than the effectiveness of these strategies. It can to vigorous level of PA over weeks, months, or years. On one be expected that because PA reduces the decline of cognitive hand, prospective memory is related to long-term memory functions and because the efficient functioning of cognitive and declarative memory, and it describes the ability to plan functions facilitates the use of functional strategies, we should observe differences between active and inactive older and successfully execute delayed intentions in the future [31]. People in general, and more particularly aging people, adults in the use of cognitive strategies. As suggested by West et al. [41], cognitive functions meaningfully influence use strategies to facilitate and/or solve a prospective memory task. Studies on prospective memory have demonstrated that thought and actions and determine adaptive coping to challenges in everyday life. ,e main objective of the present this cognitive process facilitates medication adherence [27]. Metamemory can be defined as the control and regulation of study was to examine whether cognitive strategies related to strategies necessary to address such memory tasks [32]. executive functions and prospective memory would predict More precisely, metamemory refers to two categories of the level of engagement in physical activity in older persons. Journal of Aging Research 3 slight depression, and a score of 20–30 corresponds to severe 2. Methods depression. 2.1. Description of Sample. ,e present study is a part of a French regional survey, a multidisciplinary research project entitled Seniors’ Autonomy Preservation in Poitou-Charentes 2.4. Physical Activity Measure. ,e level of current PA was (PRAUSE). ,e inclusion criteria to be eligible for the re- evaluated with the Historical Leisure Activity Questionnaire cruitment into PRAUSE were the following: (1) living in (HLAQ) [46]. ,is questionnaire was used to assess the Poitou-Charentes; (2) being aged 55 years or over; and (3) not history of PA weighted by relative intensity, and as suggested being institutionalized and not under guardianship or trust- by Kriska et al. [46], the list of activities was adapted to the eeship. Participants were invited to take part in the study by population. ,e HLAQ was previously used in French mail and phone. Project feasibility was tested with a pilot study, studies that demonstrated relationships between executive and three waves of data collection were necessary to include functions and level of physical activity [47, 48]. Participants a total of 466 participants. Each participant included in the were asked to report the frequency, type, intensity, and hours study performed one to three sessions of data collection of PA performed during the present year. Using the Com- according to his/her motivation. For the purposes of this study, pendium of Physical Activities Tracking Guide 2011 [49], we only 243 participants out of 466 completed all the data required obtained a specific metabolic equivalent (MET) for each PA. to test our hypotheses. ,is sample of participants included According to the HLAQ data and the compendium, we 41.57% males and had a mean age of 74.02 (SD � 9.61) years. calculated the average energy expenditure (METs-h/week) for each participant. According to the WHO recommendations, we classified the participants above 7.5 METs-h/week in the 2.2. Compliance with Ethical Standards. All participants active group and those below 7.5 METs-h/week in the inactive signed an informed consent form. ,e three data collection group. waves occurred between 2011 and 2013. All participants were visited at home, and all face-to-face questionnaires were administered by investigators who received individual 2.5. Cognitive Variables. Cognitive strategies were measured training for all data collection. ,e protocol of PRAUSE was using a questionnaire adapted from three scales: (1) the approved by two national ethics committees: (1) the “general Metamemory in Adulthood scale [50], (2) the ,ought interest and statistical quality” label from the French Na- Control Questionnaire [51], and (3) the Attentional Control tional Council of Statistical Information (CNIS, visa no. Scale [52] (Table 1). Metamemory concerns knowledge of 2012X907RG) and (2) the French National Commission on memory functioning, beliefs and affects about memory, as Informatics and Liberty (authorization no. 1593815). well as monitoring and autoregulation during memory activity [50]. ,e metamemory in adulthood scale contains 2.3. Demographic and Health Variables. Questionnaires eight subscales, from which two were selected and adapted for the study: the external strategy subscales (e.g., memos were completed with data including age, gender, perceived health status, education, depression, decisional balance, and and calendar) and the internal strategy subscales (e.g., mental imagery and word associations). ,ese scales BMI. Perceived health status was evaluated with a visual analogue scale from EuroQol-5D and consisted of assessing evaluate the means used by people to more easily find in- his/her perception of health from “best known health status” formation stored in prospective and episodic memory. ,e to “worse known health status.” ,e Decisional Balance external strategy subscales include 6 items and the internal questionnaire was based on Marcus’ version and adapted to subscale 9 items. Cronbach’s alphas for these two cognitive strategies were 0.66 and 0.70, respectively. ,e thought physical activity. It consisted of two constructs that underlie cognitive and motivational aspects of human decision control questionnaire contains five subscales designed to assess people’s tendency to use a variety of thought control making. ,ese constructs have been labeled the pros and cons of exercising, and they were each measured with 8 strategies in everyday life. Two subscales were selected and adapted for the needs of the study: the reappraisal subscale items. Participants responded to each item on a 5-point Likert-type scale ranging from totally agree (1) to totally (e.g., I try to reinterpret the thought) and the distraction subscale (e.g., I occupy myself with work instead). ,e disagree (5). Based on Bandura’s guidelines [42] and the identification of main barriers in old age reported in the reappraisal subscale includes 5 items and the distraction literature [43, 44], six barriers’ self-efficacy were included subscale 6 items. Cronbach’s alphas for these two cognitive based on health aspects (pain and fatigue), motivational strategies were 0.83 and 0.75, respectively. ,e short-form determinants (too busy and nobody to practice with), and Attentional Control Scale consisted of a 12-item self-report [52] measure combining attentional focusing that requires environmental factors (weather and accessibility). Partici- pants rated answers on a 5-point scale ranging from 1 (not voluntary control over behaviors and attentional shifting that is related to performance on switching tasks. Only the confident to overcome) to 5 (extremely confident to over- come). Cronbach’s alpha values were .76 for pros, .83 for attentional focusing strategy was evaluated in the study because of the link we posited with PA. ,is scale includes 6 cons, and .68 for barriers’ self-efficacy. Depression GDS, Depressive symptoms were assessed using the 30-item items. Participants rated answers on a 5-point scale ranging Geriatric Depression Scale validated in French by Bourque from 1 (never used) to 5 (always used) for the five strategy et al. [45]. A score of 0–9 is normal, a score of 10–19 indicates subscales. Cronbach’s alpha for this scale was 0.66. 4 Journal of Aging Research Table 1: Cognitive strategy questionnaires used in the study. External memory strategies I keep a list or otherwise note important dates, such as birthdays and anniversaries I write shopping list to help me remember I write appointments on a calendar to help me remember them I routinely keep things (keys or glasses) in a familiar spot, so I will not forget them when I need to locate them I post reminders of things I need to do in a prominent place, such as on bulletin boards or note boards When I want to take something with me, I leave it in an obvious, prominent place, such as putting my suitcase in front of the door Internal memory strategies When I am looking for something I have recently misplaced, I try to retrace my steps in order to locate it When I want to remember something, I concentrate hard on it When I try to remember a telephone number, I mentally repeat it to myself I think about the day’s activities at the beginning of the day, so I can remember what I am supposed to do I make mental images or pictures to help me remember an event or an individual I try to relate something I want to remember to something else hoping that this will increase the likelihood of my remembering later When I have trouble remembering something, I try to remember something similar in order to help me remember Reappraisal When I experience an unpleasant/unwanted thought, I challenge the thought’s validity When I experience an unpleasant/unwanted thought, I analyze the thought rationally When I experience an unpleasant/unwanted thought, I try to reinterpret the thought When I experience an unpleasant/unwanted thought, I try a different way of thinking about it When I experience an unpleasant/unwanted thought, I question the reasons for having the thought Distraction When I experience an unpleasant/unwanted thought, I call to mind positive images instead When I experience an unpleasant/unwanted thought, I occupy myself with work instead When I experience an unpleasant/unwanted thought, I think pleasant thoughts instead When I experience an unpleasant/unwanted thought, I do something that I enjoy When I experience an unpleasant/unwanted thought, I think about something else When I experience an unpleasant/unwanted thought, I keep myself busy Attentional control When concentrating on something and there are noises around me, I ask for silence When I read, I look for a calm area where I will not be distracted by people around me When I am working hard on something and I am distracted by events around me, I try to isolate myself When trying to focus my attention on something and thoughts distracting me, I chase them out of my mind When concentrating on something and hunger or thirst distracts me, I satisfy my need so that it does not worry me anymore When concentrating on something, I turn off TV or radio 2.6. Data Analysis. Descriptive statistics were examined to not depressed (6.48, SD � 4.80), used on average more in- characterize the study population. Correlation analyses and ternal memory strategies (30.28, SD � 5.21), and were not easily distracted (19.41, SD � 4.37). Participants who were t-tests were used to obtain additional descriptive in- formation and to identify a preliminary set of predictor inactive had a mean age of 77.66 (SD � 9.75), had a mean variables to be included in the discriminant analysis. Var- BMI of 28.70 (SD � 4.70), perceived themselves in worse iables with a significant difference of p< 0.05 as determined health (66.37, SD � 18.01), perceived themselves as less ca- by the above tests were entered into stepwise discriminant pable of overcoming barriers (31.85, SD � 10.06), used on analysis. ,en, a stepwise discriminant analysis was per- average less internal memory (28.76, SD � 6.61), and had formed to determine if active and inactive participants could difficulties in concentrating (20.46, SD � 5.04). be discriminated based on the following variables: age, ,e emphasis of this analysis was on understanding how gender, body mass index (BMI), perceived health status, these variables were related to each other to determine the depression, barriers’ self-efficacy, and cognitive strategies level of physical activity. We used discriminant analysis to (internal memory and attentional control). determine the linear combination of predictor variables that best classified the cases into the two groups. ,e step- wise discriminant analysis (Table 3) showed that Wilks’ 3. Results lambda, as a test of discriminant function, was significant Table 2 shows distributions of sociodemographic charac- (lambda � 0.736; χ � 72.051, df � 8, p< 0.001) and selected teristics and other covariates. Participants who were active the five following variables as determinants of physical in- had a mean age of 71.45 (SD � 8.65), had a mean BMI of activity (based on structure matrix loading): older (−0.626), 26.88 (SD � 4.94), perceived themselves on average in better perceived poor health (0.442), less use of internal memory health (75.46, SD � 14.27), perceived themselves on average strategies (0.213), attentional control (−0.196), and poor as capable of overcoming barriers (38.51, SD � 9.83), were confidence to overcome barriers to PA practice (0.555). Journal of Aging Research 5 Table 2: Sociodemographic, health, motivational, and cognitive strategies for active versus inactive participants. ,e last column shows the correlations between the variable and the level of physical activity for the population sample examined in this study (n � 243). Variables Active (n � 139) mean (SD) Inactive (n � 104) mean (SD) p Correlation coefficient ✓ Age (years) 71.45 (8.65) 77.66 (9.75) Ϯ −0.35Ϯ ✓ Gender (M/F) 71/68 29/75 Ϯ 0.23Ϯ ✓Education 10.52 (3.66) 10.20 (3.80) ns 0.05 ✓ BMI 26.88 (4.94) 28.70 (4.70) Ϯ −0.18Ϯ ✓ Perceived health status 75.46 (14.27) 66.37 (18.01) Ϯ 0.26Ϯ ✓ Depression 6.48 (4.80) 9.067 (5.05) Ϯ −0.14Ϯ Decisional variables ✓Pros 15.84 (6.14) 17.27 (6.10) ns −0.11 ✓ Barriers’ self-efficacy 38.51 (9.83) 31.85 (10.06) Ϯ 0.36Ϯ Cognitive strategies EMS (from 6 to 30) 23.86 (4.02) 24.30 (4.42) ns −0.06 IMS (from 9 to 45) 30.28 (5.16) 28.76 (6.61) Ϯ 0.12 ACS (from 6 to 30) 19.43 (3.68) 20.46 (5.04) Ϯ −0.11 DS (from 6 to 30) 20.60 (4.94) 20.21 (5.40) ns 0.04 RS (from 5 to 25) 14.58 (4.05) 13.62 (4.56) ns 0.11 ✓Variables reported as moderately to strongly significant in the literature. Variables entered in the current discriminant analysis. Ϯ � p< 0.05, ns � nonsignificant (p> 0.05). EMS: external memory strategies, IMS: internal memory strategies, ACS: attentional control strategies, DS: distraction strategies, and RS: reappraisal strategies. Table 3: Summary of interpretive measures for stepwise discriminant analysis. Predictor Standardized coefficient loadings F ratio Rank ∗∗ Age −0.626 15.239 1 Gender 0.413 1.469 BMI −0.307 3.824 Perceived health status 0.442 4.230 4 Depression −0.434 0.739 Internal memory 0.213 10.684 2 Attentional control −0.196 9.761 3 Barriers’ self-efficacy 0.555 3.948 5 Canonical correlation 0.513 Eigenvalue 0.358 Wilks’ lambda 0.736 χ 72.051; df � 8 ∗ ∗∗ p< 0.01, p< 0.001. Wilks’ lambda, which describes the proportion of total sarcopenia, or social isolation. Most studies that have ex- variance in the discriminant score not explained by differ- amined the factors associated with sedentariness or in- ences between groups, was significant, indicating that it is activity have focused on psychosocial predictors. However, unlikely that participants who were inactive and those who cognitive functions have recently been considered in ad- were active had the same means on the discriminant herence to treatment medication [12, 13], but to our functions generated from the prediction equation. knowledge, no study has examined the predictive value of Table 4 summarizes the group membership results of the cognitive strategies in adherence to PA in healthy older classification routine. Of the 104 participants who were adults. ,e aim of the present study was to identify cognitive inactive, 63 (60.6%) were correctly classified as inactive, and and psychosocial determinants of the level of PA in in- of the 139 participants who were active, 113 (81.3%) were dependently living healthy older adults in France. correctly classified as active based on the selected variables. First, no difference was observed between active and ,e overall percentage of the level of PA classifications was inactive healthy older adults when considering level of 73%, reflecting a 23% improvement over chance alone. Of education, knowledge concerning the benefits of regular PA, the variables investigated, age was the most discriminating the use of external memory strategies, cognitive and be- and barriers’ self-efficacy the least. havioral distractions, or reappraisal. ,ese results are par- tially consistent with previous literature reviews examining the relationships between sociodemographic and psycho- 4. Discussion social determinants and the level of PA [2, 3, 53]. ,e results Sedentariness and inactivity are legitimate problems in older concerning knowledge about the benefits of regular PA adults because these behaviors lead to several health suggest that information provided by the campaigns of problems such as more pronounced cognitive decline, prevention are well retained by individuals in general, 6 Journal of Aging Research Table 4: Classification results of the discriminant analysis. Group Number of cases Predicted group inactive n (%) Membership active, n (%) Inactive 104 63 (60.6%) 41 (39.4%) Active 139 24 (17.2%) 113 (81.3%) 73.03% of grouped cases were correctly classified and 26.97% of grouped cases were incorrectly classified. which appeared as a predictor of the level of PA in the regardless of their level of engagement in regular PA. As suggested by Gross and Rebok [53], however some de- present study, were already reported as predictive of mographic predictors such as gender, pros of exercising, and adherence to PA [56], more precisely, in elderly women in a level of education could be used in high-risk populations, 6-month strength training program. In this last study, barriers’ these predictors are not necessarily significant in healthy self-efficacy were a good predictor of the first three months of populations. It is interesting to note that, in the present exercise adherence and remained a significant predictor after study, active older adults scored lower on the pros scale than six months. In the present study, barriers’ self-efficacy were inactive ones. ,is result could indicate that inactive older a good predictor of regular and habitual physical activity. adults overestimate pros but are not interested or concerned Both studies suggest that barriers’ self-efficacy are a good predictor of exercise adherence from a long-term perspective, by these potential benefits. ,ree out of five cognitive strategies showed no significant differences between active possibly because this variable positively influences motiva- tion to practice by increasing effort and persistence as well and inactive older adults, with external strategies being more used than the other strategies by older adults in general as enhancing attention paid to tasks. (M � 4.82; close to “always used”), followed by distraction ,e important contribution of this study is the dis- (M � 3.43; close to “sometimes used”) and reappraisal criminant power of cognitive strategies, indicating that strategies (M � 2.36; close to “rarely used”), the latter being active older people perceive themselves as using more in- the least used and referring to problem solving. ,ese results ternal memory strategies—assessing prospective and epi- could be interpreted in two ways: (1) maintaining a high level sodic memory—and as more able of using controlled inhibition than inactive ones. In other words, these per- of PA involves specific cognitive functions and strategies and (2) practicing a high level of PA facilitates the use of higher ceptions would favor engagement in physical activity be- cause they would reinforce positive perception of one’s own cognitive functions and strategies. ,is study also revealed some interesting results con- efficacy to interact with environment. Another explanation could be that practicing moderate to high level of physical cerning predictors of the level of PA that could contribute to reinforce interventions intended to help older people adhere activity improves episodic memory and consequently fa- to long-term PA practice. ,e discriminant analysis revealed cilitates the use of internal memory by older adults and their that among the variables that emerged as significantly perception of using these strategies. Because this study was predictive of the level of PA, age, perceived health, barriers’ cross-sectional, we cannot define a causal relationship be- self-efficacy, internal memory strategies, and attentional tween these variables. Notwithstanding, a first assumption control strategies predominantly discriminated between would be that older adults who have better memory abilities and/or better attentional control engage themselves more active and inactive older participants in successfully clas- sifying 73% of participants. Concerning sociodemographic easily in active behaviors. ,is explanation is reinforced by previous research that has reported that the use of memory and psychosocial variables, these results are congruent with previous studies. First, several studies [2, 3] moderately strategies facilitates the management of daily living activities suggested that males are generally more active than females. [7], medication adherence [19, 26], and PA [15]. To our Unlike these studies, gender was not a predictor of the level knowledge, only the study carried out by Olson et al. [26] of PA in the present study. In a recent systematic review [54], reporteda relationship between attention and adherence to it appears that gender differences in walking is attenuated for PA and postulated that controlled inhibition is critical to old adults (>70 years). Second, perceived health status was successful behavior changes. In other words, attentional presently identified as a determinant of engagement in PA control ability is important for switching between goal- but not depression. However, McHugh and Lawlor [55] have directed plans and environment-based responses. Accord- ing to the temporal self-regulation model proposed by Hall reported an overadditive interaction of these two variables on hours of exercise per week such that high perceived and Fong [6], executive functions are involved in PA be- havior. However, these authors did not provide any details health status combined with low levels of depression resulted in the highest levels of exercise. In the present study, even if concerning the specific executive functions involved in depression was correlated to the level of PA, this variable did adherence, such as planning, cognitive flexibility, or con- not discriminate between active and inactive older adults. trolled inhibition. ,e present results clearly show that Consequently, it could be suggested that (1) perceived health specific cognitive functions are associated with PA behavior: status and depression share a common variance, certainly presumably, prospective memory related to internal mem- because global perceived health status includes a component ory strategies and controlled inhibition related to attentional of mental health status such as depression (r �−0.365 for this control strategies. A second assumption would be that by study) or (2) perceived health status is a better predictor of being active, older adults increase their memory abilities and their attentional control. For instance, Winnecke et al. [30] PA than depression. ,ird, and finally, barriers’ self-efficacy, Journal of Aging Research 7 reported that individuals with higher levels of PA showed Authors’ Contributions better attentional control capabilities than those who are less All authors have contributed significantly to the research active. ,is result confirms the proposition made by Hillman concept, literature review, objectives, and design of the et al. [23] that PA can activate the attentional system and study. ,ey all are in agreement with the content of the mobilize attentional resources. From that perspective, other manuscript. All authors approved the manuscript and this studies showed that controlled inhibition seems to benefit submission. more selectively from PA than from other executive func- tions [57, 58]. Studies on memory training programs re- ported that memory strategies are needed to maintain References regular activity with a low investment of cognitive resources [1] S. G. Trost, N. Owen, A. E. Bauman, J. F. Sallis, and W. Brown, [59]. For instance, Wolff et al. [59] reported that action “Correlates of adults’ participation in physical activity: review planning, defined by the authors as being strongly related to and update,” Medicine and Sciences in Sports and Exercise, memory strategies, facilitates the enactment of health be- vol. 34, no. 12, pp. 1996–2001, 2002. havior in daily life. What is interesting to note here is that [2] M. M. van Stralen, H. De Vries, A. N. Mudde, C. Bolman, memory strategies are not necessarily associated with high and L. Lechner, “Determinants of initiation and mainte- prospective memory ability. In other words, physically active nance of physical activity among older adults: a literature older adults might compensate for cognitive deficits by review,” Health Psychology Review, vol. 3, no. 2, pp. 147–207, recruiting larger frontal areas relevant for memory and/or [3] M. A. Koeneman, M. W. Verheijden, M. J. M. Chinapaw, and attentional control strategies. ,is compensatory mecha- M. Hopman-Rock, “Determinants of physical activity and nism would not necessarily consist of an increase of the exercise in healthy older adults: a systematic review,” In- efficiency of these functions but in a better use of the ternational Journal of Behavioral Nutrition and Physical Ac- cognitive strategies. ,ese strategies could, in turn, facilitate tivity, vol. 8, no. 1, p. 142, 2011. the day-to-day management of life and perceived health. [4] A. E. Bauman, R. S. Reis, J. F. Sallis, J. C. Wells, R. J. Loos, and ,ere is now substantial literature demonstrating this re- B. W. Martin, “Correlates of physical activity: why are some ciprocal effect, and our results confirm and specify the people physically active and others not?,” <e Lancet, vol. 38, theoretical position taken by Hall and Fong [6] on the no. 9838, pp. 258–271, 2012. mutual reinforcement of executive functions and PA over [5] B. Guinn and V. Vincent, “Select physical activity de- time. Our results argue in the direction of this model, and terminants in independent-living elderly,” Activities, Adap- tation & Aging, vol. 26, no. 4, pp. 17–26, 2002. particular attention should be paid to the cognitive strategies [6] P. A. Hall and G. T. Fong, “Temporal self-regulation theory: involved according to the targeted behavior. ,e present a neurobiologically informed model for physical activity study has certain limitations. First, the study employed cross- behaviour,” Frontiers in Human Neuroscience, vol. 9, p. 117, sectional data, precluding any assumptions concerning cau- sality between the five variables selected as predictors and the [7] R. L. West, D. K. Bagwell, and A. Dark-Freudeman, “Self- level of PA. Moreover, those variables and the level of PA efficacy and memory aging: the impact of a memory in- might have changed over time. Further analysis of longitu- tervention based on self-efficacy,” Aging, Neuropsychology, dinal data is warranted to clarify the relationship between and Cognition, vol. 15, no. 3, pp. 302–329, 2008. changes in the five predictors obtained and PA. Another [8] S. Colcombe and A. F. Kramer, “Fitness effects on the cog- limitation to this study is its reliance on self-reported data on nitive function of older adults: a meta-analytic study,” Psy- chological Science, vol. 14, no. 2, pp. 125–130, 2003. the five selected variables and PA. [9] B. Levy, “Stereotype embodiment: a psychological approach to aging,” Current Directions in Physical Science, vol. 18, no. 6, 5. Conclusion pp. 332–336, 2009. [10] B. Bouazzaoui, M. Isingrini, S. Fay et al., “Aging and self- Rather than seeing older people as lacking motivation for reported internal and external memory strategy uses: the role physical activities, this study identified cognitive and psy- of executive functioning,” Acta Psychologica, vol. 135, no. 1, chosocial predictors of the level of PA to evaluate the pp. 59–66, 2010. likelihood of relapses or quitting and to reduce the risk [11] M. E. Lachman and C. Andreoletti, “Strategy use mediates the factors through interventions among older people at in- relationship between control beliefs and memory perfor- creased risk of inactivity. Regardless of whether age is an mance for middle-aged and older adults,” Journal of Geron- irreversible process, this study raises awareness of the need tology: Psychological Sciences, vol. 61, no. 2, pp. P88–P94, to consider cognitive strategies as facilitators to engage in [12] F. Misokami, M. Hiroki, T. Kinoshita, T. Kumagai, K. Futura, durable PA. ,e development of specific cognitive strategies and I. Kazuhiro, “Adherence to medication regimens is an related to cognitive functions seems a relevant element to effective indicator of cognitive dysfunction in elderly in- facilitate the management of daily life and preservation from dividuals,” American Journal of Alzheimer’s Disease and Other sedentariness. Dementias, vol. 31, no. 2, pp. 132–136, 2016. [13] E. Kroger, ¨ O. Tatar, I. Vedel et al., “Improving medication Conflicts of Interest adherence among community-dwelling seniors with cognitive impairment: a systematic review of interventions,” In- ,e authors declare that there are no conflicts of interest ternational Journal of Clinical Pharmacy, vol. 39, no. 4, regarding the publication of this article. pp. 641–656, 2017. 8 Journal of Aging Research [14] A. Hering, P. G. Rendell, N. S. Rose, K. M. Schnitzspahn, and [30] A. H. Winnecke, B. Godde, E.-M. Reuter, S. Vieluf, and M. Kliegel, “Prospective memory training in older adults and C. Voelcker-Rehage, “,e association between physical ac- its relevance for successful aging,” Psychological Research, tivity and attentional control in younger and older middle- vol. 78, no. 6, pp. 892–904, 2014. aged adults: an ERP study,” GeroPsychology, vol. 25, no. 4, [15] J. R. Best, L. S. Nagamatsu, and T. Liu-Ambrose, “Im- pp. 207–221, 2012. provements to executive functions during exercise training [31] M. Kliegel, M. A. McDaniel, and G. O. Einstein, Prospective predict maintenance of physical activity over the following Memory: Cognitive, Neuroscience, Developmental, and Applied year,” Frontiers in Human Neuroscience, vol. 8, p. 353, 2014. Perspectives, Erlbaum, Mahwah, NJ, USA, 2008. [16] M. A. Wiegand, A. K. Troyer, C. Gojmerac, and K. J. Murphy, [32] A.-P. Le Berre, F. Eustache, and H. Beaunieux, “La “Facilitating change in health-related behaviors and in- metam ´ emoire: ´ theorie ´ et clinique,” Revue de Neuro- tentions: a randomized controlled trial of a multidimensional psychologie, vol. 1, no. 4, pp. 312–320, 2009. memory program for older adults,” Aging and Mental Health, [33] D. Derryberry and M. A. Reed, “Anxiety-related attentional vol. 17, no. 7, pp. 806–815, 2013. biases and their regulation by attentional control,” Journal of [17] N. L. Campbell, J. Zhan, W. Tu et al., “Self-reported medi- Abnormal Psychology, vol. 111, no. 2, pp. 225–236, 2002. cation adherence barriers among ambulatory older adults [34] M. Audiffren, N. Andre, ´ and C. Albinet, “Effets positifs de with mild cognitive impairment,” Pharmacotherapy, vol. 36, l’exercice physique chronique sur les fonctions cognitives des no. 2, pp. 196–202, 2016. seniors: bilan et perspective,” Revue de Neuropsychologie, [18] A. Hernandez-Galiot and I. Goni, “Adherence to the Medi- vol. 3, no. 4, pp. 207–225, 2011. terranean diet pattern, cognitive status and depressive [35] L. Bherer, K. I. Erickson, and T. Liu-Ambrose, “A review of symptoms in an elderly non-institutionalized population,” the effects of physical activity and exercise on cognitive and Nutricion Hospitalaria, vol. 34, no. 2, pp. 338–344, 2017. brain functions in older adults,” Journal of Aging Research, [19] S. D. Neupert and L. McDonald-Miszczak, “Younger and vol. 2013, Article ID 197326, 2 pages, 2013. older adults’ delayed recall of medication instructions: the role [36] F. Sofi, D. Valecchi, D. Bacci, R. Abbate, G. F. Gensini, and of cognitive and metacognitive predictors,” Aging, Neuro- C. Macchi, “Physical activity and risk of cognitive decline : psychology, and Cognition, vol. 11, no. 4, pp. 428–442, 2004. a meta-analysis of prospective studies,” Journal of Internal [20] K. Vedhara, E. Wadsworth, P. Norman et al., “Habitual Medicine, vol. 269, no. 1, pp. 107–117, 2011. prospective memory in elderly patient with type 2 diabetes: [37] K. Yaffe, D. Barnes, M. Nevitt, L. Y. Lui, and K. Covinsky, “A implications for medication adherence,” Psychology, Health & prospective study of physical activity and cognitive decline in Medicine, vol. 9, no. 1, pp. 17–27, 2004. elderly women: women who walk,” Archives of Internal [21] J. E. Karr, C. N. Areshenkoff, P. Rast, and M. A. Garcia- Medicine, vol. 161, no. 14, pp. 1703–1708, 2001. Barrera, “An empirical comparison of the therapeutic benefits [38] S. J. Colcombe, K. I. Erickson, N. Raz et al., “Aerobic fitness of physical exercise and cognitive training on the executive reduces brain tissue loss in aging humans,” Journal of Ger- functions of older adults: a meta-analysis of controlled trials,” ontology, vol. 58, no. 2, pp. 176–180, 2003. Neuropsychology, vol. 28, no. 6, pp. 829–845, 2014. [39] D. B. Mitchell, “How many memory system? Evidence from [22] C. H. Hillman, A. F. Kramer, A. V. Belopolsky, and D. P. Smith, “A aging,” Journal of Experimental Psychology: Learning, Mem- cross-sectional examination of age and physical activity on per- ory, and Cognition, vol. 15, no. 1, pp. 31–49, 1989. formance and event-related brain potentials in a task switching [40] J. L. Allan, D. McMinn, and M. Daly, “A bidirectional re- paradigm,” International Journal of Psychophysiology, vol. 59, no.1, lationship between executive function and health behavior: pp. 30–39, 2006. evidence, implications, and future directions,” Frontiers in [23] C. H. Hillman, K. I. Erickson, and A. F. Kramer, “Be smart, Neurosciences, vol. 10, p. 386, 2016. exercise your heart: exercise effects on brain and cognition,” [41] R. West, M. S. Beeri, J. Schmeidler et al., “Better memory Nature Reviews, vol. 9, no. 1, pp. 58–65, 2008. functioning associated with higher total and low-density li- [24] C. B. Phillips, J. D. Edwards, R. Andel, and M. Kilpatrick, “Daily poprotein cholesterol levels in very elderly subjects without physical activity and cognitive function variability in older adults,” the apolipoprotein e4 allele,” American Journal of Geriatric Journal of Aging and Physical Activity, vol. 24, no. 2, pp. 256–267, Psychiatry, vol. 16, no. 9, pp. 781–785, 2008. [42] A. Bandura, “Guide for constructing self-efficacy scales,” in [25] L. McDonald-Miszczak, S. D. Neupert, and G. Gutman, “Does Self-Efficacy Beliefs of Adolescents, F. Pajares and T. Urdan, cognitive ability explain inaccuracy in older adults’ self- Eds., pp. 307–337, Information Age Publishing, Greenwich, reported medication adherence?,” Journal of Applied Geron- CT, USA, 2006. tology, vol. 28, no. 5, pp. 560–581, 2009. [43] C. ,ogersen-Ntoumani, “An ecological model of predictors [26] E. A. Olson, S. P. Mullen, L. B. Raine, A. F. Kramer, of stages of change for physical activity in Greek older adults,” C. H. Hillman, and E. McAuley, “Integrated social and Scandinavian Journal of Medicine and Sciences in Sports, neurocognitive model of physical activity behavior in older vol. 19, no. 2, pp. 286–296, 2009. adults with metabolic disease,” Annals of Behavioral Medicine, [44] K. L. Smith, K. Carr, A. Wiseman, K. Calhoun, N. H. McNevin, vol. 51, no. 2, pp. 272–281, 2017. and P. L. Weir, “Barriers are not the limiting factor to par- [27] O. N. Gould, L. McDonald-Miszczak, and B. King, “Metacognition ticipation in physical activity in Canadian seniors,” Journal of and medication adherence: how do older adults remember?,” Aging Research, vol. 2012, Article ID 890679, 8 pages, 2012. Experimental Aging Research, vol. 23, no. 4, pp. 315–342, 1997. [45] P. Bourque, L. Blanchard, and J. Vezina, “Etude psychom´e- [28] L. Taconnat and P. Lemaire, “Fonctions executives, ´ vieil- trique de l’´echelle de depression ´ g´eriatrique,” Canadian lissement cognitif et variations strategiques,” ´ Psychologie Française, vol. 59, no. 1, pp. 89–100, 2014. Journal of Aging, vol. 9, no. 4, pp. 348–355, 1990. [29] C. Lustig, L. Hasher, and S. T. Tonev, “Distraction as a de- [46] A. M. Kriska, R. B. Sandler, J. A. Cauley, R. E. Laporte, terminant of processing speed,” Psychonomic Bulletin & Review, D. L. Hom, and G. Pambianco, “,e assessment of historical vol. 13, no. 4, pp. 619–625, 2006. physical-activity and its relation to adult bone parameters,” Journal of Aging Research 9 American Journal of Epidemiology, vol. 127, no. 5, pp. 1053– 1063, 1988. [47] G. K. Boucard, C. T. Albinet, A. Buga¨ıska, C. A. Bouquet, D. Clarys, and M. Audiffren, “Impact of chronic exercise on executive functions in aging: a selective effect to inhibition performance among middle-old adults,” Journal of Sport and Exercise Psychology, vol. 34, no. 6, pp. 808–827, 2012. [48] A. Canivet, C. T. Albinet, N. Andre´ et al., “Effects of BDNF polymorphism and physical activity on episodic memory in the elderly: a cross sectional study,” European Review of Aging and Physical Activity, vol. 12, p. 15, 2015. [49] B. E. Ainsworth, W. L. Haskell, S. D. Herrmann et al., “Compendium of physical activities: a second update of codes and MET values,” Medicine and Sciences in Sports and Ex- ercise, vol. 43, no. 8, pp. 1575–1581, 2011. [50] R. A. Dixon, D. F. Hultsch, and C. Hertzog, “,e meta- memory in adulthood (MIA) questionnaire,” Psychophar- macology Bulletin, vol. 24, no. 4, pp. 671–688, 1988. [51] A. Wells and M. I. Davies, “,e thought control question- naire: a measure of individual differences in the control of unwanted thoughts,” Behaviour Research and <erapy, vol. 32, no. 8, pp. 871–878, 1994. [52] M. T. Judah, D. M. Grant, A. C. Mills, and W. V. Lechner, “Factor structure and validation of the attentional control scale,” Cognition and Emotion, vol. 28, no. 3, pp. 433–451, [53] A. L. Gross and G. W. Rebok, “Memory training and strategy use in older adults: results from the ACTIVE study,” Psy- chology and Aging, vol. 26, no. 3, pp. 503–517, 2011. [54] T. M. Pollard and J. M. Wagnild, “Gender differences in walking (for leisure, transport and in total) across adult life: a systematic review,” BMC Public Health, vol. 17, no. 1, p. 341, [55] J. E. McHugh and B. A. Lawlor, “Perceived health status is associated with hours of exercise per week in older adults independent of physical health,” Journal of Physical Activity and Health, vol. 10, no. 8, pp. 1102–1108, 2013. [56] R. E. Rhodes, A. D. Martin, and J. E. Taunton, “Temporal relationships of self-efficacy and social support as predictors of adherence in a 6-month strength-training program for older women,” Perceptual and Motor Skills, vol. 93, no. 7, pp. 693–703, 2001. [57] G. K. Boucard, C. T. Albinet, A. Bugaiska, C. A. Bouquet, D. Clarys, and M. Audiffren, “Impact of physical activity on executive functions in aging: a selective effect on inhibition among old adults,” Journal of Sport and Exercise Psychology, vol. 34, no. 6, pp. 808–827, 2012. [58] A. L. Smiley-Oyen, K. A. Lowry, S. J. Francois, M. L. Kohut, and P. Ekkekakis, “Exercise, fitness, and neurocognitive function in older adults: the selective improvement and cardiovascular fitness hypotheses,” Annals of Behavioral Medicine, vol. 36, no. 3, pp. 280–291, 2008. [59] J. K. Wolff, L. M. Warner, J. P. Ziegelmann, S. Wurm, and M. Kliegel, “Translating good intentions into physical activity: older adults with low prospective memory ability profit from planning,” Journal of Behavioral Medicine, vol. 39, no. 3, pp. 472–482, 2016. MEDIATORS of INFLAMMATION The Scientific Gastroenterology Journal of World Journal Research and Practice Diabetes Research Disease Markers Hindawi Hindawi Publishing Corporation Hindawi Hindawi Hindawi Hindawi www.hindawi.com Volume 2018 http://www www.hindawi.com .hindawi.com V Volume 2018 olume 2013 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 International Journal of Journal of Immunology Research Endocrinology Hindawi Hindawi www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 Submit your manuscripts at www.hindawi.com BioMed PPAR Research Research International Hindawi Hindawi www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 Journal of Obesity Evidence-Based Journal of Journal of Stem Cells Complementary and Ophthalmology International Alternative Medicine Oncology Hindawi Hindawi Hindawi Hindawi Hindawi www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2013 Parkinson’s Disease Computational and Behavioural Mathematical Methods AIDS Oxidative Medicine and in Medicine Neurology Research and Treatment Cellular Longevity Hindawi Hindawi Hindawi Hindawi Hindawi www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018 www.hindawi.com Volume 2018

Journal

Journal of Aging Research – Hindawi Publishing Corporation

Published: Apr 5, 2018

There are no references for this article.