Perceived and physiological strains of societal participation in people with multiple sclerosis: a real-time assessment study
DOI:
https://doi.org/10.2340/jrm.v56.40838Keywords:
Activities of daily living, digital health, heart rate, multiple sclerosis, patient reported outcome measure, societal participationAbstract
Objective: To examine the relationship between perceived and physiological strains of real-time societal participation in people with multiple sclerosis.
Design: Observational study.
Subjects/Patients: 70 people with multiple sclerosis.
Methods: Perceived and physiological strain of societal participation (10 participation-at-location and 9 transport domains) were measured in real time using the Whereabouts smartphone app and Fitbit over 7 consecutive days. Longitudinal relationships between perceived (1 not strenuous to 10 most strenuous) and physiological strains (heart rate reserve) were examined using mixed-model analyses. Type of event (participation-at-location or transport) was added as covariate, with further adjustments for fatigue and walking ability.
Results: Median perceived strain, summarized for all societal participation domains, varied between 3 and 6 (range: 1–10), whereas physiological strain varied between 18.5% and 33.2% heart rate reserve. Perceived strain (outcome) and physiological strain were not associated (β -0.001, 95%CI -0.008; 0.005, with a 7-day longitudinal correlation coefficient of -0.001). Transport domains were perceived as less strenuous (β -0.80, 95%CI -0.92; -0.68). Higher fatigue levels resulted in higher perceived strain (all societal participation domains) (β 0.05, 95%CI 0.02; 0.08).
Conclusion: Societal participation resulted in low-to-moderate perceived and physiological strain. Perceived and physiological strain of societal participation were unrelated and should be considered different constructs in multiple sclerosis.
Downloads
References
Kister I, Bacon TE, Chamot E, Salter AR, Cutter GR, Kalina JT, et al. Natural history of multiple sclerosis symptoms. Int J MS Care 2013; 15: 146–158.
https://doi.org/10.7224/1537-2073.2012-053 DOI: https://doi.org/10.7224/1537-2073.2012-053
Heinemann AW. Measurement of participation in rehabilitation research. Arch Phys Med Rehabil 2010; 91: S1–4.
https://doi.org/10.1016/j.apmr.2009.08.155 DOI: https://doi.org/10.1016/j.apmr.2009.08.155
World Health Organization. International classification of Functioning, Disability and Health: ICF. Geneva: WHO; 2001.
Ben Ari Shevil E, Johansson S, Ytterberg C, Bergstrom J, von Koch L. How are cognitive impairment, fatigue and signs of depression related to partici-pation in daily life among persons with multiple sclerosis? Disabil Rehabil 2014; 36: 2012–2018.
https://doi.org/10.3109/09638288.2014.887797 DOI: https://doi.org/10.3109/09638288.2014.887797
Chang FH, Coster WJ, Helfrich CA. Community participation measures for people with disabilities: a systematic review of content from an international classification of functioning, disability and health perspective. Arch Phys Med Rehabil 2013; 94: 771–781.
https://doi.org/10.1016/j.apmr.2012.10.031 DOI: https://doi.org/10.1016/j.apmr.2012.10.031
Eyssen IC, Steultjens MP, Dekker J, Terwee CB. A systematic review of instruments assessing participation: challenges in defining participation. Arch Phys Med Rehabil 2011; 92: 983–997.
https://doi.org/10.1016/j.apmr.2011.01.006 DOI: https://doi.org/10.1016/j.apmr.2011.01.006
Hemmingsson H, Jonsson H. An occupational perspective on the concept of participation in the International Classification of Functioning, Disability and Health: some critical remarks. Am J Occup Ther 2005; 59: 569–576.
https://doi.org/10.5014/ajot.59.5.569 DOI: https://doi.org/10.5014/ajot.59.5.569
Magasi S, Hammel J, Heinemann A, Whiteneck G, Bogner J. Participation: a comparative analysis of multiple rehabilitation stakeholders’ perspectives. J Rehabil Med 2009; 41: 936–944.
https://doi.org/10.2340/16501977-0450 DOI: https://doi.org/10.2340/16501977-0450
Whiteneck G, Dijkers MP. Difficult to measure constructs: conceptual and methodological issues concerning participation and environmental factors. Arch Phys Med Rehabil 2009; 90: S22–35.
https://doi.org/10.1016/j.apmr.2009.06.009 DOI: https://doi.org/10.1016/j.apmr.2009.06.009
Kwiatkowski A, Marissal JP, Pouyfaucon M, Vermersch P, Hautecoeur P, Dervaux B. Social participation in patients with multiple sclerosis: correlations between disability and economic burden. BMC Neurol 2014; 14: 115.
https://doi.org/10.1186/1471-2377-14-115 DOI: https://doi.org/10.1186/1471-2377-14-115
Mikula P, Nagyova I, Krokavcova M, Vitkova M, Rosenberger J, Szilasiova J, et al. Social participation and health-related quality of life in people with multiple sclerosis. Disabil Health J 2015; 8: 29–34.
https://doi.org/10.1016/j.dhjo.2014.07.002 DOI: https://doi.org/10.1016/j.dhjo.2014.07.002
Huber M, Knottnerus JA, Green L, van der Horst H, Jadad AR, Kromhout D, et al. How should we define health? BMJ 2011; 343: d4163.
https://doi.org/10.1136/bmj.d4163 DOI: https://doi.org/10.1136/bmj.d4163
van de Velde D, Coussens M, De Baets S, Sabbe L, Vanderstraeten G, Vlerick P, et al. Application of participation in clinical practice: key issues. J Reha-bil Med 2018; 50: 679–695.
https://doi.org/10.2340/16501977-2363 DOI: https://doi.org/10.2340/16501977-2363
Ouwerkerk M, Eijssen I, van der Linden MMW, Wijnands IM, Dorssers FJG, Rietberg MB, et al. A Smartphone application to assess real-time and indi-vidual-specific societal participation: a development and usability study. Arch Phys Med Rehabil 2022; 103: 1958–1966.
https://doi.org/10.1016/j.apmr.2022.01.168 DOI: https://doi.org/10.1016/j.apmr.2022.01.168
Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 1982; 14: 377–381. DOI: https://doi.org/10.1249/00005768-198205000-00012
American College of Sports Medicine. ACSM Guidelines for Exercise Testing and Prescription. 9th ed. Indianapolis, IN: American College of Sports Medi-cine; 2014.
Bakshi R. Fatigue associated with multiple sclerosis: diagnosis, impact and management. Mult Scler 2003; 9: 219–227.
https://doi.org/10.1191/1352458503ms904oa DOI: https://doi.org/10.1191/1352458503ms904oa
Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR Jr, Tudor-Locke C, et al. 2011 Compendium of Physical Activities: a second update of codes and MET values. Med Sci Sports Exerc 2011; 43: 1575–1581.
https://doi.org/10.1249/MSS.0b013e31821ece12 DOI: https://doi.org/10.1249/MSS.0b013e31821ece12
Compagnat M, Mandigout S, David R, Lacroix J, Daviet JC, Salle JY. Compendium of physical activities strongly underestimates the oxygen cost during activities of daily living in stroke patients. Am J Phys Med Rehabil 2019; 98: 299–302.
https://doi.org/10.1097/PHM.0000000000001077 DOI: https://doi.org/10.1097/PHM.0000000000001077
Greiman L, Fleming SP, Ward B, Myers A, Ravesloot C. Life starts at home: bathing, exertion and participation for people with mobility impairment. Arch Phys Med Rehabil 2018; 99: 1289–1294.
https://doi.org/10.1016/j.apmr.2017.11.015 DOI: https://doi.org/10.1016/j.apmr.2017.11.015
Cleland BT, Ingraham BA, Pitluck MC, Woo D, Ng AV. Reliability and validity of ratings of perceived exertion in persons with multiple sclerosis. Arch Phys Med Rehabil 2016; 97: 974–982.
https://doi.org/10.1016/j.apmr.2016.01.013 DOI: https://doi.org/10.1016/j.apmr.2016.01.013
Scherr J, Wolfarth B, Christle JW, Pressler A, Wagenpfeil S, Halle M. Associations between Borg’s rating of perceived exertion and physiological measu-res of exercise intensity. Eur J Appl Physiol 2013; 113: 147–155.
https://doi.org/10.1007/s00421-012-2421-x DOI: https://doi.org/10.1007/s00421-012-2421-x
Drebinger D, Rasche L, Kroneberg D, Althoff P, Bellmann-Strobl J, Weygandt M, et al. Association between fatigue and motor exertion in patients with multiple sclerosis: a prospective study. Front Neurol 2020; 11: 208.
https://doi.org/10.3389/fneur.2020.00208 DOI: https://doi.org/10.3389/fneur.2020.00208
Motl RW, Snook EM. Confirmation and extension of the validity of the Multiple Sclerosis Walking Scale-12 (MSWS-12). J Neurol Sci 2008; 268: 69–73.
https://doi.org/10.1016/j.jns.2007.11.003 DOI: https://doi.org/10.1016/j.jns.2007.11.003
Hobart JC, Riazi A, Lamping DL, Fitzpatrick R, Thompson AJ. Measuring the impact of MS on walking ability: the 12-Item MS Walking Scale (MSWS-12). Neurology 2003; 60: 31–36.
https://doi.org/10.1212/wnl.60.1.31 DOI: https://doi.org/10.1212/WNL.60.1.31
Mokkink LB, Prinsen CA, Partcik DL, Alonse J, Bouter LM, de Vet HC, et al. COSMIN Study Design checklist for Patient-reported outcome measurement instruments; 2019. Available from: https://www.cosmin.nl/wp-content/uploads/COSMIN-study-designing-checklist_final.pdf
Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol 2007; 60: 34–42.
https://doi.org/10.1016/j.jclinepi.2006.03.012 DOI: https://doi.org/10.1016/j.jclinepi.2006.03.012
Fitbit. Fitbit Charge 2 User Manual. Available from: https://www.fitbit.com/content/assets/help/manuals/manual_charge_2_en_US.pdf
Nelson BW, Allen NB. Accuracy of consumer wearable heart rate measurement during an ecologically valid 24-hour period: intraindividual validation study. JMIR Mhealth Uhealth 2019; 7: e10828.
https://doi.org/10.2196/10828 DOI: https://doi.org/10.2196/10828
Benedetto S, Caldato C, Bazzan E, Greenwood DC, Pensabene V, Actis P. Assessment of the Fitbit Charge 2 for monitoring heart rate. PLoS One 2018; 13: e0192691.
https://doi.org/10.1371/journal.pone.0192691 DOI: https://doi.org/10.1371/journal.pone.0192691
Camarda SR, Tebexreni AS, Pafaro CN, Sasai FB, Tambeiro VL, Juliano Y, et al. Comparison of maximal heart rate using the prediction equations pro-posed by Karvonen and Tanaka. Arq Bras Cardiol 2008; 91: 311–314.
https://doi.org/10.1590/s0066-782x2008001700005 DOI: https://doi.org/10.1590/S0066-782X2008001700005
Twisk JWR. Applied longitudinal data analysis for epidemiology. 2nd ed. Cambridge: Cambridge University Press; 2013. DOI: https://doi.org/10.1017/CBO9781139342834
Field A. Discovering statistics using IBM SPSS statistics. 4th ed. London: SAGE; 2013.
Ratner B. The correlation coefficient: its values range between +1/−1, or do they? J Targeting, Measurement and Analysis for Marketing 2009; 17: 139–142.
https://doi.org/10.1057/jt.2009.5 DOI: https://doi.org/10.1057/jt.2009.5
Williams N. The Borg Rating of Perceived Exertion (RPE) scale. Occup Med 2017; 67: 404–405.
https://doi.org/10.1093/occmed/kqx063 DOI: https://doi.org/10.1093/occmed/kqx063
Rouault M, Pereira I, Galioulline H, Fleming SM, Stephan KE, Manjaly ZM. Interoceptive and metacognitive facets of fatigue in multiple sclerosis. Eur J Neurosci 2023; 58: 2603–2622.
https://doi.org/10.1111/ejn.16048 DOI: https://doi.org/10.1111/ejn.16048
Nieuwenburg-van Tilborg EM, Horstman AM, Zwarts B, de Groot S. Physical strain during activities of daily living of patients with coronary artery dise-ase. Clin Physiol Funct Imaging 2014; 34: 83–89.
https://doi.org/10.1111/cpf.12065 DOI: https://doi.org/10.1111/cpf.12065
Audulv A, Hutchinson S, Warner G, Kephart G, Versnel J, Packer TL. Managing everyday life: self-management strategies people use to live well with neurological conditions. Patient Educ Couns 2021; 104: 413–421.
https://doi.org/10.1016/j.pec.2020.07.025 DOI: https://doi.org/10.1016/j.pec.2020.07.025
Blokland IJ, Schiphorst LFA, Stroek JR, Groot FP, van Bennekom CAM, van Dieen JH, et al. Relative aerobic load of daily activities after stroke. Phys Ther 2023; 103.
https://doi.org/10.1093/ptj/pzad005 DOI: https://doi.org/10.1093/ptj/pzad005
Rampichini S, Gervasoni E, Cattaneo D, Rovaris M, Grosso C, Maggioni MA, et al. Impaired heart rate recovery after sub-maximal physical exercise in people with multiple sclerosis. Mult Scler Relat Disord 2020; 40: 101960.
https://doi.org/10.1016/j.msard.2020.101960 DOI: https://doi.org/10.1016/j.msard.2020.101960
Adamec I, Habek M. Autonomic dysfunction in multiple sclerosis. Clin Neurol Neurosurg 2013; 115 Suppl 1: S73–78.
https://doi.org/10.1016/j.clineuro.2013.09.026 DOI: https://doi.org/10.1016/j.clineuro.2013.09.026
Barnard RJ, Gardner GW, Diaco NV, MacAlpin RN, Kattus AA. Cardiovascular responses to sudden strenuous exercise: heart rate, blood pressure, and ECG. J Appl Physiol 1973; 34: 833–837.
https://doi.org/10.1152/jappl.1973.34.6.833 DOI: https://doi.org/10.1152/jappl.1973.34.6.833
Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited. J Am Coll Cardiol 2001; 37: 153–156.
https://doi.org/10.1016/s0735-1097(00)01054-8 DOI: https://doi.org/10.1016/S0735-1097(00)01054-8
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2024 Arianne S. Gravesteijn, Maaike Ouwerkerk, Isaline C.J.M. Eijssen, Heleen Beckerman, Vincent de Groot
This work is licensed under a Creative Commons Attribution 4.0 International License.
All digitalized JRM contents is available freely online. The Foundation for Rehabilitation Medicine owns the copyright for all material published until volume 40 (2008), as from volume 41 (2009) authors retain copyright to their work and as from volume 49 (2017) the journal has been published Open Access, under CC-BY-NC licences (unless otherwise specified). The CC-BY-NC licenses allow third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for non-commercial purposes, provided proper attribution to the original work.
From 2024, articles are published under the CC-BY licence. This license permits sharing, adapting, and using the material for any purpose, including commercial use, with the condition of providing full attribution to the original publication.