Activity tracker-based intervention to increase physical activity in patients with type 2 diabetes and healthy individuals: study protocol for a randomized controlled trial
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WHO. World health statistics 2021: monitoring health for the SDGs, sustainable development goals. Geneva: World Health Organisation; 2021.
Du Y, Heidemann C, Gößwald A, Schmich P, Scheidt-Nave C. Prevalence and comorbidity of diabetes mellitus among non-institutionalized older adults in Germany - results of the national telephone health interview survey 'German Health Update (GEDA)' 2009. BMC Public Health. 2013;13:166.
Rawshani A, Rawshani A, Franzén S, Eliasson B, Svensson A-M, Miftaraj M, et al. Mortality and Cardiovascular Disease in Type 1 and Type 2 Diabetes. N Engl J Med. 2017;376(15):1407–18.
Tsilidis KK, Kasimis JC, Lopez DS, Ntzani EE, Ioannidis JPA. Type 2 diabetes and cancer: umbrella review of meta-analyses of observational studies. BMJ. 2015;350:g7607.
Mühlenbruch K, Joost H-G, Boeing H, Schulze M. Prediction of risk for type 2 diabetes in the German population with the updated DRT (DIfE-GERMAN DIABETES-RISK-TEST). Ernährungs Umschau. 2014;61:M306–M9.
Pan A, Wang Y, Talaei M, Hu FB, Wu T. Relation of active, passive, and quitting smoking with incident type 2 diabetes: a systematic review and meta-analysis. Lancet Diabetes Endocrinol. 2015;3(12):958–67.
Kolb H, Martin S. Environmental/lifestyle factors in the pathogenesis and prevention of type 2 diabetes. BMC Med. 2017;15(1):131.
Toplak H, Leitner DR, Harreiter J, Hoppichler F, Wascher TC, Schindler K, et al. "Diabesity"-Obesity and type 2 diabetes. Wiener Klinische Wochenschrift. 2019;131(Suppl 1):71–6.
Kautzky-Willer A, Harreiter J, Abrahamian H, Weitgasser R, Fasching P, Hoppichler F, et al. [Sex and gender-specific aspects in prediabetes and diabetes mellitus-clinical recommendations] (Update 2019). Wiener Klinische Wochenschrift. 2019;131(Suppl 1):221–8.
Merlotti C, Morabito A, Ceriani V, Pontiroli AE. Prevention of type 2 diabetes in obese at-risk subjects: a systematic review and meta-analysis. Acta Diabetologica. 2014;51(5):853–63.
Sigal RJ, Kenny GP, Wasserman DH, Castaneda-Sceppa C. Physical activity/exercise and type 2 diabetes. Diabetes Care. 2004;27(10):2518–39.
Zanuso S, Jimenez A, Pugliese G, Corigliano G, Balducci S. Exercise for the management of type 2 diabetes: a review of the evidence. Acta Diabetologica. 2010;47(1):15–22.
BÄK, KBV, AWMF. Nationale Versorgungs Leitlinie Therapie des Typ-2-Diabetes. Langfassung. 1. Auflage. Berlin: Bundesärztekammer, Kassenärztliche Bundesvereinigung, Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften; 2013.
Boniol M, Dragomir M, Autier P, Boyle P. Physical activity and change in fasting glucose and HbA1c: a quantitative meta-analysis of randomized trials. Acta Diabetologica. 2017;54(11):983–91.
Zhang X, Imperatore G, Thomas W, Cheng YJ, Lobelo F, Norris K, et al. Effect of lifestyle interventions on glucose regulation among adults without impaired glucose tolerance or diabetes: A systematic review and meta-analysis. Diabetes Res Clin Pract. 2017;123:149–64.
Cavero-Redondo I, Peleteiro B, Álvarez-Bueno C, Artero EG, Garrido-Miguel M, Martinez-Vizcaíno V. The Effect of Physical Activity Interventions on Glycosylated Haemoglobin (HbA1c) in Non-diabetic Populations: A Systematic Review and Meta-analysis. Sports Med. 2018;48(5):1151–64.
Grace A, Chan E, Giallauria F, Graham PL, Smart NA. Clinical outcomes and glycaemic responses to different aerobic exercise training intensities in type II diabetes: a systematic review and meta-analysis. Cardiovasc Diabetol. 2017;16(1):37.
Byrne H, Caulfield B, De Vito G. Effects of Self-directed Exercise Programmes on Individuals with Type 2 Diabetes Mellitus: A Systematic Review Evaluating Their Effect on HbA1c and Other Metabolic Outcomes, Physical Characteristics, Cardiorespiratory Fitness and Functional Outcomes. Sports Med. 2017;47(4):717–33.
Cloostermans L, Wendel-Vos W, Doornbos G, Howard B, Craig CL, Kivimaki M, et al. Independent and combined effects of physical activity and body mass index on the development of Type 2 Diabetes - a meta-analysis of 9 prospective cohort studies. Int J Behav Nutr Phys Act. 2015;12:147.
Brickwood K-J, Watson G, O'Brien J, Williams AD. Consumer-Based Wearable Activity Trackers Increase Physical Activity Participation: Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth. 2019;7(4):e11819.
Bort-Roig J, Gilson ND, Puig-Ribera A, Contreras RS, Trost SG. Measuring and influencing physical activity with smartphone technology: a systematic review. Sports Med. 2014;44(5):671–86.
Rote AE. Physical activity intervention using Fitbits in an introductory college health course. Health Educ J. 2016;76(3):337–48.
Kooiman TJM, de Groot M, Hoogenberg K, Krijnen WP, van der Schans CP, Kooy A. Self-tracking of Physical Activity in People With Type 2 Diabetes: A Randomized Controlled Trial. Comput Inform Nurs. 2018;36(7):340–9.
Hendrikx J, Ruijs LS, Cox LG, Lemmens PM, Schuijers EG, Goris AH. Clinical Evaluation of the Measurement Performance of the Philips Health Watch: A Within-Person Comparative Study. JMIR Mhealth Uhealth. 2017;5(2):e10–e.
Van Laerhoven K, Gellersen H, Malliaris Y. Long-Term Activity Monitoring with a Wearable Sensor Node. 3rd Intl Workshop on Body Sensor Nodes. Boston: IEEE Press; 2006.
Cadmus-Bertram LA, Marcus BH, Patterson RE, Parker BA, Morey BL. Randomized Trial of a Fitbit-Based Physical Activity Intervention for Women. Am J Prev Med. 2015;49(3):414–8.
Baskerville R, Ricci-Cabello I, Roberts N, Farmer A. Impact of accelerometer and pedometer use on physical activity and glycaemic control in people with Type 2 diabetes: a systematic review and meta-analysis. Diabetic Med. 2017;34(5):612–20.
Gal R, May AM, van Overmeeren EJ, Simons M, Monninkhof EM. The Effect of Physical Activity Interventions Comprising Wearables and Smartphone Applications on Physical Activity: a Systematic Review and Meta-analysis. Sports Med Open. 2018;4(1):42.
McCallum C, Rooksby J, Gray CM. Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review. JMIR Mhealth Uhealth. 2018;6(3):e58.
Kim Y, Lumpkin A, Lochbaum M, Stegemeier S, Kitten K. Promoting physical activity using a wearable activity tracker in college students: A cluster randomized controlled trial. J Sports Sci. 2018;36:1–8.
Evenson KR, Goto MM, Furberg RD. Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. 2015;12:159.
Feehan LM, Geldman J, Sayre EC, Park C, Ezzat AM, Yoo JY, et al. Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data. JMIR Mhealth Uhealth. 2018;6(8):e10527.
de Vries HJ, Kooiman TJM, van Ittersum MW, van Brussel M, de Groot M. Do activity monitors increase physical activity in adults with overweight or obesity? A systematic review and meta-analysis. Obesity. 2016;24(10):2078–91.
Cooper C, Gross A, Brinkman C, Pope R, Allen K, Hastings S, et al. The impact of wearable motion sensing technology on physical activity in older adults. Exper Gerontol. 2018;112:9–19.
Coughlin SS, Stewart J. Use of Consumer Wearable Devices to Promote Physical Activity: A Review of Health Intervention Studies. J Environ Health Sci. 2016;2(6):sp.
Miyauchi M, Toyoda M, Kaneyama N, Miyatake H, Tanaka E, Kimura M, et al. Exercise Therapy for Management of Type 2 Diabetes Mellitus: Superior Efficacy of Activity Monitors over Pedometers. J Diabetes Res. 2016;2016:7.
World Medical Association. World Medical Association Declaration of Helsinki - Ethical Principles for Medical Research involving Human Subjects. Bull World Health Organ. 2001;79(4):372–4.
Rütten A, Pfeifer K, Gediga G, Hartung V, Klamroth S, Burlacu I, et al. Menschen in Bewegung bringen. Strukturen schaffen, Bewegung fördern, lebenslang bewegen. Köln: Bundeszentrale für gesundheitliche Aufklärung; 2019.
Williams G. Bangle.js is an open, hackable smartwatch. Espruino. 2021 [15.11.2021]. Available from: https://www.espruino.com/Bangle.js.
Grunert K. Overview of JavaScript Engines for Resource-Constrained Microcontrollers. 5th International Conference on Smart and Sustainable Technologies (SpliTech) 23-26 Sept. 2020. New Jersey: IEEE; 2020.
Hoelzemann A, Pithan JS, Van Laerhoven K. Open-Source Data Collection for Activity Studies at Scale. In: Ahad MAR, Inoue S, Roggen D, Fujinami K, editors. Sensor- and Video-Based Activity and Behavior Computing. Smart Innovation, Systems and Technologies. Vol. 291. Singapore: Springer; 2022. p. 27–38.
Chomistek AK, Yuan C, Matthews CE, Troiano RP, Bowles HR, Rood J, et al. Physical Activity Assessment with the ActiGraph GT3X and Doubly Labeled Water. Med Sci Sports Exerc. 2017;49(9):1935–44.
Jones D, Crossley K, Dascombe B, Hart HF, Kemp J. Validity and reliability of the fitbit flex™ and actigraph gt3x+ at jogging and running speeds. Int J Sports Phys Ther. 2018;13(5):860–70.
Belmon LS, Middelweerd A, Te Velde SJ, Brug J. Dutch Young Adults Ratings of Behavior Change Techniques Applied in Mobile Phone Apps to Promote Physical Activity: A Cross-Sectional Survey. JMIR Mhealth Uhealth. 2015;3(4):e103.
Chia GLC, Anderson A, McLean LA. Behavior Change Techniques Incorporated in Fitness Trackers: Content Analysis. JMIR Mhealth Uhealth. 2019;7(7):e12768.
Middelweerd A, Mollee JS, van der Wal CN, Brug J, Te Velde SJ. Apps to promote physical activity among adults: a review and content analysis. Int J Behav Nutr Phys Act. 2014;11:97.
Swartz MC, Lewis ZH, Swartz MD, Martinez E, Lyons EJ. Brief Report: Active Ingredients for Adherence to a Tracker-Based Physical Activity Intervention in Older Adults. J Appl Gerontol. 2017;38(7):1023–34.
Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30(5):777–81.
CONSORT. CONSORT 2010 Flow Diagram: CONsolidated Standards Of Reporting Trials. CONSORT Group. 2020 [17.06.2020]. Available from: http://www.consort-statement.org/.
Moher D, Hopewell S, Schulz KF, Montori V, Gøtzsche PC, Devereaux PJ, et al. CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c869.
Statistisches Bundesamt. Demographische Standards für persönlich-mündliche und schriftliche Befragungen. Fragebogen und Listen. 6. überarbeitete Auflage ed. Wiesbaden: Statistisches Bundesamt; 2016.
Robert Koch-Institut. Fragebogen zur Studie "Gesundheit in Deutschland aktuell" GEDA 2014/2015-EHIS. J Health Monit. 2017;2(1):105–35.
Bös K, Abel T, Woll A, Niemann S, Tittlbach S, Schott N. Der Fragebogen zur Erfassung des motorischen Funktionsstatus (FFB-MOT). Diagnostica. 2002;48(2):101–11.
Fuchs R, Klaperski S, Gerber M, Seelig H. Messung der Bewegungs- und Sportaktivität mit dem BSA-Fragebogen: Eine methodische Zwischenbilanz. Zeitschrift für Gesundheitspsychologie. 2015;23(3):60–76.
Marcus BH, Selby VC, Niaura RS, Rossi JS. Self-efficacy and the stages of exercise behavior change. Res Q Exerc Sport. 1992;63(1):60–6.
Schwarzer R. Modeling Health Behavior Change: How to Predict and Modify the Adoption and Maintenance of Health Behaviors. Appl Psychol. 2008;57(1):1–29.
Elsborg P, Wikman JM, Nielsen G, Tolver A, Elbe AM. Development and initial validation of the Volition in Exercise Questionnaire (VEQ). Measure Phys Educ Exerc Sci. 2017;21(2):57–68.
Brehm W, Duan Y, Mair T, Strobl H, Tittlbach S. Körperlich-sportliche Aktivität als Gesundheitsverhalten - Methodenband: Bayreuther Beiträge zur Sportwissenschaft, Heft 12. Bayreuth: Universität Bayreuth: Institut für Sportwissenschaft; 2010.
Lehnert K. BMZI - Berner Motiv- und Zielinventar im Freizeit- und Gesundheitssport. Diagnostica. 2011;57(3):146–59.
Brand R. Die affektive Einstellungskomponente und ihr Beitrag zur Erklärung von Sportpartizipation. Zeitschrift Fur Sportpsychologie Z Sportpsychol. 2006;13(4):147–55.
Brehm W, Pahmeier I, Tiemann M, Gesundheitsförderung durch sportliche Aktivierung. Qualitätsmerkmale und Qualitätskontrollen sportlicher Aktivierungsprogramme zum Erhalt und zur Wiederherstellung von Gesundheit und Wohlbefinden. Bayreuth: Universität Bayreuth; 1994.
Gerber M, Fuchs R, Pühse U. Einfluss eines Kurz-Interventionsprogramms auf das Bewegungsverhalten und seine psychologischen Voraussetzungen bei Übergewichtigen und Adipösen: Die Basler MoVo-LISA-Studie. Zeitschrift für Gesundheitspsychologie. 2010;18(4):159–69.
Rammstedt B, Kemper C, Klein MC, Beierlein C, Kovaleva A. Eine kurze Skala zur Messung der fünf Dimensionen der Persönlichkeit: Big-Five-Inventory-10 (BFI-10) [A Short Scale for Assessing the Big Five Dimensions of Personality - 10 Item Big Five Inventory (BFI-10)]. Methoden Daten Analysen. 2013;7(2):233–49.
Beierlein C, Kemper C, Kovaleva A, Rammstedt B. Kurzskala zur Erfassung allgemeiner Selbstwirksamkeitserwartungen (ASKU) [Short Scale for Measuring General Self-efficacy Beliefs (ASKU)]. Methoden Daten Analysen. 2013;7(2):251–78.
Zhou L, Bao J, Setiawan IMA, Saptono A, Parmanto B. The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study. JMIR Mhealth Uhealth. 2019;7(4):e11500.
Lin J, Wurst R, Paganini S, Hohberg V, Kinkel S, Göhner W, et al. A group- and smartphone-based psychological intervention to increase and maintain physical activity in patients with musculoskeletal conditions: study protocol for a randomized controlled trial (“MoVo-App”). Trials. 2020;21(1):502.
Schulz KF, Grimes DA. Reihe Epidemiologie 6: Generierung von Randomisierungslisten in randomisierten Studien: Zufall, nicht Auswahl. ZaeFQ. 2007;101(1):419–26.
R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. 2020 [18.06.2020]. Available from: https://www.R-project.org/.
Snow G. Package ‘blockrand’. Vienna: R Foundation for Statistical Computing; 2020 [17.06.2020]. Available from: https://cran.r-project.org/web/packages/blockrand/blockrand.pdf.
Bellach B. Leitlinien und Empfehlungen zur Sicherung von Guter Epidemiologischer Praxis (GEP). Eine Mitteilung der Arbeitsgruppe Epidemiologische Methoden der Deutschen Arbeitsgemeinschaft Epidemiologie (DAE). Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz. 2000;43(6):468–75.
Gabrys L, Schmidt C, Heidemann C, Baumert J, Du Y, Paprott R, et al. Diabetes Surveillance in Germany – Background, concept and prospects: Robert Koch-Institut, Epidemiologie und Gesundheitsberichterstattung; 2017.
Gabrys L, Heidemann C, Baumert J, Teti A, Du Y, Paprott R, et al. Selecting and defining indicators for diabetes surveillance in Germany. J Health Monitor. 2018;S3:3–21.
Robert Koch-Institut. Health monitoring and health indicators in Europe. J Health Monit. 2017;2(1):3–20.
Crites SL, Fabrigar LR, Petty RE. Measuring the Affective and Cognitive Properties of Attitudes: Conceptual and Methodological Issues. Personal Soc Psychol Bull. 1994;20(6):619–34.
Knight J, Baber C. A Tool to Assess the Comfort of Wearable Computers. Human Factors. 2005;47:77–91.
Karas M, Bai J, Strączkiewicz M, Harezlak J, Glynn NW, Harris T, et al. Accelerometry data in health research: challenges and opportunities. Stat Biosci. 2019;11(2):210–37.
Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307–10.
Langer W. In: Langer W, editor. Die Analyse von Paneldaten als Mehrebenenmodell. Wiesbaden: VS Verlag für Sozialwissenschaften; 2009. p. 223–99.
Burnham KP, Anderson DR. Multimodel Inference: Understanding AIC and BIC in Model Selection. Sociol Methods Res. 2004;33(2):261–304.
VanderWeele TJ, Mathur MB. Some desirable properties of the Bonferroni Correction: Is the Bonferroni Correction really so bad? Am J Epidemiol. 2019;188(3):617–8.
Ranganathan P, Pramesh CS, Aggarwal R. Common pitfalls in statistical analysis: Intention-to-treat versus per-protocol analysis. Perspect Clin Res. 2016;7(3):144–6.
Kabisch M, Ruckes C, Seibert-Grafe M, Blettner M. Randomisierte kontrollierte Studien. Dtsch Arztebl Int. 2011;108(39):663–8.
Van Domelen DR. Package ‘accelerometry’. Vienna: R Foundation for Statistical Computing; 2018 [11.11.2021]. Available from: https://cran.r-project.org/web/packages/accelerometry/index.html.