Oncotarget

Gerotarget/Focus on Aging:

Active lifestyles in older adults: an integrated predictive model of physical activity and exercise

Federica Galli, Andrea Chirico, Luca Mallia, Laura Girelli, Michelino De Laurentiis, Fabio Lucidi, Antonio Giordano, _ Gerardo Botti

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Oncotarget. 2018; 9:25402-25413. https://doi.org/10.18632/oncotarget.25352

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Abstract

Federica Galli1, Andrea Chirico1,5, Luca Mallia2, Laura Girelli3, Michelino De Laurentiis4, Fabio Lucidi1, Antonio Giordano5,6 and Gerardo Botti7

1Department of Psychology of Development and Socialization Processes, Sapienza, University of Rome, Rome, Italy

2Department of Movement, Human and Health Sciences, University of Rome, “Foro Italico”, Rome, Italy

3Department of Human, Philosophical, Educational Sciences, University of Salerno, Salerno, Italy

4Breast Department, National Cancer Institute of Naples IRCCS “G. Pascale”, Naples, Italy

5Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology College of Science and Technology, Temple University, Philadelphia, PA, U.S.A

6Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy

7Division of Pathology, Department of Experimental Oncology, G. Pascale Foundation, National Cancer Institute, IRCCS, Naples, Italy

Correspondence to:

Antonio Giordano, email: president@shro.org

Keywords: older adults; physical activity; exercise; well-being; health; Gerotarget

Received: February 16, 2018     Accepted: April 25, 2018     Published: May 22, 2018

ABSTRACT

Physical activity and exercise have been identified as behaviors to preserve physical and mental health in older adults. The aim of the present study was to test the Integrated Behavior Change model in exercise and physical activity behaviors. The study evaluated two different samples of older adults: the first engaged in exercise class, the second doing spontaneous physical activity. The key analyses relied on Variance-Based Structural Modeling, which were performed by means of WARP PLS 6.0 statistical software. The analyses estimated the Integrated Behavior Change model in predicting exercise and physical activity, in a longitudinal design across two months of assessment. The tested models exhibited a good fit with the observed data derived from the model focusing on exercise, as well as with those derived from the model focusing on physical activity. Results showed, also, some effects and relations specific to each behavioral context. Results may form a starting point for future experimental and intervention research.


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