Integrated Social- and Neurocognitive Model of Physical Activity Behavior in Older Adults with Metabolic Disease

Erin A Olson; Sean P Mullen; Lauren B Raine; Arthur F Kramer; Charles H Hillman; Edward McAuley

doi:10.1007/s12160-016-9850-4

Integrated Social- and Neurocognitive Model of Physical Activity Behavior in Older Adults with Metabolic Disease

Ann Behav Med. 2017 Apr;51(2):272-281. doi: 10.1007/s12160-016-9850-4.

Authors

Erin A Olson¹, Sean P Mullen^{2

3}, Lauren B Raine², Arthur F Kramer^{4

5}, Charles H Hillman^{4

6}, Edward McAuley^{2

3

7}

Affiliations

¹ Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA. olson29@illinois.edu.
² Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
³ The Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
⁴ Department of Psychology, Northeastern University, Boston, MA, USA.
⁵ Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA.
⁶ Department of Health Sciences, Northeastern University, Boston, MA, USA.
⁷ Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

Abstract

Background: Despite the proven benefits of physical activity to treat and prevent metabolic diseases, such as diabetes (T2D) and metabolic syndrome (MetS), most individuals with metabolic disease do not meet physical activity (PA) recommendations. PA is a complex behavior requiring substantial motivational and cognitive resources. The purpose of this study was to examine social cognitive and neuropsychological determinants of PA behavior in older adults with T2D and MetS. The hypothesized model theorized that baseline self-regulatory strategy use and cognitive function would indirectly influence PA through self-efficacy.

Methods: Older adults with T2D or MetS (M _age = 61.8 ± 6.4) completed either an 8-week physical activity intervention (n = 58) or an online metabolic health education course (n = 58) and a follow-up at 6 months. Measures included cognitive function, self-efficacy, self-regulatory strategy use, and PA.

Results: The data partially supported the hypothesized model (χ² = 158.535(131), p > .05, comparative fit index = .96, root mean square error of approximation = .04, standardized root mean square residual = .06) with self-regulatory strategy use directly predicting self-efficacy (β = .33, p < .05), which in turn predicted PA (β = .21, p < .05). Performance on various cognitive function tasks predicted PA directly and indirectly via self-efficacy. Baseline physical activity (β = .62, p < .01) and intervention group assignment via self-efficacy (β = -.20, p < .05) predicted follow-up PA. The model accounted for 54.4 % of the variance in PA at month 6.

Conclusions: Findings partially support the hypothesized model and indicate that select cognitive functions (i.e., working memory, inhibition, attention, and task-switching) predicted PA behavior 6 months later. Future research warrants the development of interventions targeting cognitive function, self-regulatory skill development, and self-efficacy enhancement.

Trial registration number: The trial was registered with the clinical trial number NCT01790724.

Keywords: Behavioral adherence; Cognitive function; Older adults; Physical activity; Self-regulatory capacity; Type 2 diabetes.

MeSH terms

Aged
Cognition / physiology*
Diabetes Mellitus, Type 2 / physiopathology
Diabetes Mellitus, Type 2 / psychology*
Exercise / psychology*
Female
Health Behavior / physiology
Health Education
Humans
Male
Metabolic Syndrome / physiopathology
Metabolic Syndrome / psychology*
Middle Aged
Models, Psychological*
Neuropsychological Tests
Self Efficacy*
Self-Control*
Social Behavior

Associated data

ClinicalTrials.gov/NCT01790724

Abstract

MeSH terms

Associated data

Grants and funding