IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i17p6142-d403193.html
   My bibliography  Save this article

Factors Influencing Walking and Exercise Adherence in Healthy Older Adults Using Monitoring and Interfacing Technology: Preliminary Evidence

Author

Listed:
  • Andrea Albergoni

    (Department of Biomedical Sciences for Health, University of Milan, 20133 Milan, Italy
    Centro Polifunzionale di Scienze Motorie, University of Genoa, 16132 Genoa, Italy
    Department of Neuroscience (DINOGMI), University of Genoa, 16148 Genoa, Italy
    Department of Patient Care and Measurements, Philips Research, 5656AE Eindhoven, The Netherlands)

  • Florentina J. Hettinga

    (School of Sport Rehabilitation and Exercise Sciences, University of Essex, Colchester CO4 3WA, UK
    Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle NE1 8ST, UK)

  • Wim Stut

    (Department of Chronic Disease Management, Philips Research, 5656AE Eindhoven, The Netherlands)

  • Francesco Sartor

    (Department of Patient Care and Measurements, Philips Research, 5656AE Eindhoven, The Netherlands
    School of Sport Rehabilitation and Exercise Sciences, University of Essex, Colchester CO4 3WA, UK
    College of Health and Behavioural Science, Bangor University, Bangor LL57 2EF, UK)

Abstract

Background: Monitoring and interfacing technologies may increase physical activity (PA) program adherence in older adults, but they should account for aspects influencing older adults’ PA behavior. This study aimed at gathering preliminary wrist-based PA adherence data in free-living and relate these to the influencing factors. Methods: Ten healthy older adults (4 females, aged 70–78 years) provided health, fatigue, activity levels, attitude towards pacing, and self-efficacy information and performed a 6 min-walk test to assess their fitness. After a baseline week they followed a two-week walking and exercise intervention. Participants saw their progress via a purposely designed mobile application. Results: Walking and exercise adherence did not increase during the intervention ( p = 0.38, p = 0.65). Self-efficacy decreased ( p = 0.024). The baseline physical component of the Short Form Health Survey was the most predictive variable of walking adherence. Baseline perceived risk of over-activity and resting heart rate (HR rest ) were the most predictive variables of exercise adherence. When the latter two were used to cluster participants according to their exercise adherence, the fitness gap between exercise-adherent and non-adherent increased after the intervention ( p = 0.004). Conclusions: Risk of over-activity and HR rest profiled short-term exercise adherence in older adults. If confirmed in a larger and longer study, these could personalize interventions aimed at increasing adherence.

Suggested Citation

  • Andrea Albergoni & Florentina J. Hettinga & Wim Stut & Francesco Sartor, 2020. "Factors Influencing Walking and Exercise Adherence in Healthy Older Adults Using Monitoring and Interfacing Technology: Preliminary Evidence," IJERPH, MDPI, vol. 17(17), pages 1-18, August.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:17:p:6142-:d:403193
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/17/6142/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/17/6142/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andrea Fuente-Vidal & Myriam Guerra-Balic & Oriol Roda-Noguera & Javier Jerez-Roig & Joel Montane, 2022. "Adherence to eHealth-Delivered Exercise in Adults with no Specific Health Conditions: A Scoping Review on a Conceptual Challenge," IJERPH, MDPI, vol. 19(16), pages 1-19, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tong, Jianfeng & Liu, Zhenxing & Zhang, Yong & Zheng, Xiujuan & Jin, Junyang, 2023. "Improved multi-gate mixture-of-experts framework for multi-step prediction of gas load," Energy, Elsevier, vol. 282(C).
    2. Asma Shaheen & Javed Iqbal, 2018. "Spatial Distribution and Mobility Assessment of Carcinogenic Heavy Metals in Soil Profiles Using Geostatistics and Random Forest, Boruta Algorithm," Sustainability, MDPI, vol. 10(3), pages 1-20, March.
    3. Ramón Ferri-García & María del Mar Rueda, 2022. "Variable selection in Propensity Score Adjustment to mitigate selection bias in online surveys," Statistical Papers, Springer, vol. 63(6), pages 1829-1881, December.
    4. Manuel J. García Rodríguez & Vicente Rodríguez Montequín & Francisco Ortega Fernández & Joaquín M. Villanueva Balsera, 2019. "Public Procurement Announcements in Spain: Regulations, Data Analysis, and Award Price Estimator Using Machine Learning," Complexity, Hindawi, vol. 2019, pages 1-20, November.
    5. Sangjin Kim & Jong-Min Kim, 2019. "Two-Stage Classification with SIS Using a New Filter Ranking Method in High Throughput Data," Mathematics, MDPI, vol. 7(6), pages 1-16, May.
    6. Foutzopoulos, Giorgos & Pandis, Nikolaos & Tsagris, Michail, 2024. "Predicting full retirement attainment of NBA players," MPRA Paper 121540, University Library of Munich, Germany.
    7. Zhao-Yue Chen & Hervé Petetin & Raúl Fernando Méndez Turrubiates & Hicham Achebak & Carlos Pérez García-Pando & Joan Ballester, 2024. "Population exposure to multiple air pollutants and its compound episodes in Europe," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    8. Schrader, Silja & Graham, Sonia & Campbell, Rebecca & Height, Kaitlyn & Hawkes, Gina, 2024. "Grower attitudes and practices toward area-wide management of cropping weeds in Australia," Land Use Policy, Elsevier, vol. 137(C).
    9. Piotr Pomorski & Denise Gorse, 2023. "Improving Portfolio Performance Using a Novel Method for Predicting Financial Regimes," Papers 2310.04536, arXiv.org.
    10. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2022. "A babel of web-searches: Googling unemployment during the pandemic," Labour Economics, Elsevier, vol. 74(C).
    11. Hakan Pabuccu & Adrian Barbu, 2023. "Feature Selection with Annealing for Forecasting Financial Time Series," Papers 2303.02223, arXiv.org, revised Feb 2024.
    12. Abolfazl Mollalo & Kiara M. Rivera & Behzad Vahedi, 2020. "Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States," IJERPH, MDPI, vol. 17(12), pages 1-13, June.
    13. Chunyang Huang & Shaoliang Zhang, 2023. "Explainable artificial intelligence model for identifying Market Value in Professional Soccer Players," Papers 2311.04599, arXiv.org, revised Nov 2023.
    14. Faisal Alsayegh & Moh A Alkhamis & Fatima Ali & Sreeja Attur & Nicholas M Fountain-Jones & Mohammad Zubaid, 2022. "Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-15, January.
    15. Basso, Franco & Cox, Tomás & Pezoa, Raúl & Maldonado, Tomás & Varas, Mauricio, 2024. "Characterizing last-mile freight transportation using mobile phone data: The case of Santiago, Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).
    16. Franck Ramaharo & Fitiavana Randriamifidy, 2023. "Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms," Papers 2401.13671, arXiv.org.
    17. Yu, Yang & Yu, Qinghua & Luo, RunSen & Chen, Sheng & Yang, Jiebo & Yan, Fuwu, 2024. "Degradation and polarization curve prediction of proton exchange membrane fuel cells: An interpretable model perspective," Applied Energy, Elsevier, vol. 365(C).
    18. Weichun Zhang & Yunyi Zhang & Xin Zhang & Wei Wu & Hongbin Liu, 2024. "The Spatiotemporal Variability of Soil Available Phosphorus and Potassium in Karst Region: The Crucial Role of Socio-Geographical Factors," Land, MDPI, vol. 13(6), pages 1-21, June.
    19. Jamei, Mehdi & Ali, Mumtaz & Karbasi, Masoud & Xiang, Yong & Ahmadianfar, Iman & Yaseen, Zaher Mundher, 2022. "Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach," Applied Energy, Elsevier, vol. 326(C).
    20. Gang Chen & Xianju Li & Weitao Chen & Xinwen Cheng & Yujin Zhang & Shengwei Liu, 2014. "Extraction and application analysis of landslide influential factors based on LiDAR DEM: a case study in the Three Gorges area, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 509-526, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:17:p:6142-:d:403193. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.