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

André, Nathalie; Ferrand, Claude; Albinet, Cédric T.; Audiffren, Michel

doi:10.1155/2018/8917535

Cited by 11 publications

(8 citation statements)

References 60 publications

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“…The level of accuracy recorded for classification model in the present study is high, compared to some of the published levels for discriminant analysis to categorise older adults based on different criterion features. Recently a study reported accuracy of 73% for five predictor variables including cognitive function to identify individuals at high risk of lapses once engaged in regular physical activity [ 35 ]. A similar lower accuracy of 78.2% was reported using five predictor variables for detecting individuals at high risk of depression among community-dwelling older adults [ 36 ].…”

Section: Discussionmentioning

confidence: 99%

Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender

Agyapong‐Badu

Warner

Samuel

et al. 2021

JCM

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A novel approach to ageing studies assessed the discriminatory ability of a combination of routine physical function tests and novel measures, notably muscle mechanical properties and thigh composition (ultrasound imaging) to classify healthy individuals according to age and gender. The cross-sectional study included 138 community-dwelling, self-reported healthy males and females (65 young, mean age ± SD = 25.7 ± 4.8 years; 73 older, 74.9 ± 5.9 years). Handgrip strength; quadriceps strength; respiratory peak flow; timed up and go; stair climbing time; anterior thigh tissue thickness; muscle stiffness, tone, elasticity (Myoton technology), and self-reported health related quality of life (SF36) were assessed. Stepwise feature selection using cross-validation with linear discriminant analysis was used to classify cases based on criterion variable derived from known effects of age on physical function. A model was trained and features selected using 126 cases with 0.92 accuracy (95% CI = 0.86–0.96; Kappa = 0.89). The final model included five features (peak flow, timed up and go, biceps brachii elasticity, anterior thigh muscle thickness, and percentage thigh muscle) with high sensitivity (0.82–0.96) and specificity (0.94–0.99). The most sensitive novel biomarkers require no volition, highlighting potentially useful tests for screening and monitoring effects of interventions on musculoskeletal health for vulnerable older people with pain or cognitive impairment.

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Section: Discussionmentioning

confidence: 99%

Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender

Agyapong‐Badu

Warner

Samuel

et al. 2021

JCM

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“…Barriers provide information about the potential constraints on action as perceived by individuals. Generally, this kind of barrier is reported more specifically by vulnerable persons, such as cancer survivors, for whom experienced nausea, fatigue, a lack of time and a lack of external support contribute to directly hindering exercise as a routine [ 79 , 80 , 81 , 82 ]. This distinction is not obvious in studies, and authors have to appropriately formulate perceived barriers when using the TTM as a theoretical framework.…”

Section: Discussionmentioning

confidence: 99%

Are Barriers the Same Whether I Want to Start or Maintain Exercise? A Narrative Review on Healthy Older Adults

André

Agbangla

2020

IJERPH

Self Cite

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To help older adults begin or adhere to regular physical exercise, several studies have endeavored to identify barriers to active behavior. However, there is a lack of information about barriers for active older people. In addition, most of the reviews of the literature compare only active people to inactive or sedentary people without examining in detail the barriers with respect to the degree of commitment to behavioral change. Finally, there is no consistency in the results of studies investigating the effects of barriers on the relationship between stages of change and exercise behavior. The first aim of this narrative review is to compare barriers that affect exercise stages of change from those that affect levels of exercise behavior in a healthy older population and the factors that can lead to relapse or dropout; the second aim is to identify the extent to which barriers hinder the relationships between stages of change and exercise behaviors. The results showed that barriers are well identified in sedentary people and in the first two stages of change (pre-contemplation and contemplation) compared to active seniors and other stages of change (preparation, action and maintenance). Consistency between the formulations of the different stages in comparison with the transtheoretical model and the definition of barriers and the limitations of measuring physical activity in the different studies are discussed. Finally, novel perspectives of research are proposed to address the flaws in the reviewed studies.

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“…Practicing exercise regularly also requires planning the exercise sessions in the coming week (i.e., goal setting), remembering when to exercise at the planned time (i.e., prospective memory), and accepting that positive effects of PA occur in the long term (i.e., delay of gratification), which are three higher cognitive functions directly related to EF 9, 40, 41. The predictive power of EF on PA engagement has been mainly demonstrated with cross-sectional studies 42, 43. To our knowledge, no intervention study has been conducted with the aim of demonstrating a causal link between an improvement in EF efficiency and adherence to exercise.…”

Section: Causal Relationship Between Efs and Effortful Control And Admentioning

confidence: 99%

The exercise–cognition relationship: A virtuous circle

Audiffren

André

2019

Journal of Sport and Health Science

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Exercise and health psychology have generated 2 sets of empirical studies guided by separate theory-driven axes. The first axis focuses on the causal relationship between chronic exercise and cognition and, more particularly, high-level cognitive functions such as executive functions (EFs). The second axis examines factors influencing the adherence process to physical activity (PA). Research conducted during the past decade shows that these 2 topics are closely linked, with EFs and effortful control playing a pivotal role in the bidirectional relationship linking PA and mental/brain health. The present article supports the idea that an individual engaged in the regular practice of effortful PA initiates a virtuous circle linking PA and effortful control in a bidirectional way. On the one hand, chronic exercise leads to an improvement of EFs and effortful control. On the other hand, gains in EFs and effortful control effectiveness lead to a reciprocal facilitation of the maintenance of PA over time. Some limitations and perspectives to this effort hypothesis are proposed in the last part of the article.

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

Cited by 11 publications

References 60 publications

Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender

Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender

Are Barriers the Same Whether I Want to Start or Maintain Exercise? A Narrative Review on Healthy Older Adults

The exercise–cognition relationship: A virtuous circle

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