mHealth interventions to reduce stress in healthcare workers (fitcor): study protocol for a randomized controlled trial | Trials
Dragano N. Arbeitsstress als Risikofaktor für kardiovaskuläre Erkrankungen. Aktuelle Kardiologie. 2018;7(05):368–72.
Google Scholar
Järvelin-Pasanen S, Sinikallio S, Tarvainen MP. Heart rate variability and occupational stress-systematic review. Ind Health. 2018;56(6):500–11.
Google Scholar
Lim J, Bogossian F, Ahern K. Stress and coping in Australian nurses: a systematic review. Int Nurs Rev. 2010;57(1):22–31.
Google Scholar
Halpin Y, Terry LM, Curzio J. A longitudinal, mixed methods investigation of newly qualified nurses’ workplace stressors and stress experiences during transition. J Adv Nurs. 2017;73(11):2577–86.
Google Scholar
Heinen MM, van Achterberg T, Schwendimann R, Zander B, Matthews A, Kózka M, et al. Nurses’ intention to leave their profession: a cross sectional observational study in 10 European countries. Int J Nurs Stud. 2013;50(2):174–84.
Google Scholar
Jacobs K, Kuhlmey A, Greß S, Klauber J, Schwinger A. Pflege-Report 2019: Mehr Personal in der Langzeitpflege-aber woher? Berlin: Springer Nature; 2020.
Hasselhorn HM, Conway PM, Widerszal-Bazyl M, Simon M, Tackenberg P, Schmidt S, et al. Contribution of job strain to nurses’ consideration of leaving the profession–Results from the longitudinal European nurses’ early exit study. Scand J Work Environ Health. 2008;34(6):75.
McVicar A. Workplace stress in nursing: a literature review. J Adv Nurs. 2003;44(6):633–42.
Google Scholar
Moustaka E, Constantinidis TC. Sources and effects of work-related stress in nursing. Health Sci J. 2010;4(4):210.
van Schalkwijk FJ, Blessinga AN, Willemen AM, van der Werf YD, Schuengel C. Social support moderates the effects of stress on sleep in adolescents. J Sleep Res. 2015;24(4):407–13.
Google Scholar
Stults-Kolehmainen MA, Sinha R. The effects of stress on physical activity and exercise. Sports Med. 2014;44(1):81–121.
Google Scholar
Da Estrela C, McGrath J, Booij L, Gouin J-P. Heart rate variability, sleep quality, and depression in the context of chronic stress. Ann Behav Med. 2021;55(2):155–64.
Google Scholar
Schneider D, Winter V, Schreyögg J. Job demands, job resources, and behavior in times of sickness: an analysis across German nursing homes. Health Care Manag Rev. 2018;43(4):338–47.
Google Scholar
Dong H, Zhang Q, Sun Z, Sang F, Xu Y. Sleep disturbances among Chinese clinical nurses in general hospitals and its influencing factors. BMC Psychiatry. 2017;17(1):1–9.
Google Scholar
Yaribeygi H, Panahi Y, Sahraei H, Johnston TP, Sahebkar A. The impact of stress on body function: a review. EXCLI J. 2017;16:1057.
Google Scholar
Gu B, Tan Q, Zhao S. The association between occupational stress and psychosomatic wellbeing among Chinese nurses: a cross-sectional survey. Medicine (Baltimore). 2019:98(22):e15836. https://doi.org/10.1097/MD.0000000000015836.
Richardson S, Shaffer JA, Falzon L, Krupka D, Davidson KW, Edmondson D. Meta-analysis of perceived stress and its association with incident coronary heart disease. Am J Cardiol. 2012;110(12):1711–6.
Google Scholar
Clark MM, Warren BA, Hagen PT, Johnson BD, Jenkins SM, Werneburg BL, et al. Stress level, health behaviors, and quality of life in employees joining a wellness center. Am J Health Promot. 2011;26(1):21–5.
Google Scholar
Vrijkotte TGM, van Doornen LJP, Geus EJC de. Effects of work stress on ambulatory blood pressure, heart rate, and heart rate variability. Hypertension 2000; 35(4):880–886.
Chandola T, Britton A, Brunner E, Hemingway H, Malik M, Kumari M, et al. Work stress and coronary heart disease: what are the mechanisms? Eur Heart J. 2008;29(5):640–8 Cited 2022 May 29.
Google Scholar
Borchini R, Veronesi G, Bonzini M, Gianfagna F, Dashi O, Ferrario MM. Heart rate variability frequency domain alterations among healthy nurses exposed to prolonged work stress. IJERPH. 2018;15(1):113.
Google Scholar
Kim H-G, Cheon E-J, Bai D-S, Lee YH, Koo B-H. Stress and heart rate variability: a meta-analysis and review of the literature. Psychiatry Investig. 2018;15(3):235.
Google Scholar
Delaney JP, Brodie D. Effects of short-term psychological stress on the time and frequency domains of heart-rate variability. Perceptual Motor Skills. 2000;91(2):515–24.
Google Scholar
Endukuru CK, Tripathi S. Evaluation of cardiac responses to stress in healthy individuals-a non invasive evaluation by heart rate variability and Stroop test. Int J Sci Res. 2016;5:286–9.
Filaire E, Portier H, Massart A, Ramat L, Teixeira A. Effect of lecturing to 200 students on heart rate variability and alpha-amylase activity. Eur J Appl Physiol. 2010;108(5):1035–43.
Google Scholar
Kang MG, Koh SB, Cha BS, Park JK, Woo JM, Chang SJ. Association between job stress on heart rate variability and metabolic syndrome in shipyard male workers. Yonsei Med J. 2004;45(5):838–46.
Google Scholar
Uusitalo A, Mets T, Martinmäki K, Mauno S, Kinnunen U, Rusko H. Heart rate variability related to effort at work. Appl Ergonomics. 2011;42(6):830–8.
Google Scholar
Antelmi I, Paula RS de, Shinzato AR, Peres CA, Mansur AJ, Grupi CJ. Influence of age, gender, body mass index, and functional capacity on heart rate variability in a cohort of subjects without heart disease. Am J Cardiol 2004; 93(3):381–385.
Voss A, Schroeder R, Heitmann A, Peters A, Perz S. Short-term heart rate variability—influence of gender and age in healthy subjects. PLoS One. 2015;10(3):e0118308.
Google Scholar
Molfino A, Fiorentini A, Tubani L, Martuscelli M, Fanelli FR, Laviano A. Body mass index is related to autonomic nervous system activity as measured by heart rate variability. Eur J Clin Nutr. 2009;63(10):1263–5.
Google Scholar
Felber Dietrich D, Schindler C, Schwartz J, Barthélémy J-C, Tschopp J-M, Roche F, et al. Heart rate variability in an ageing population and its association with lifestyle and cardiovascular risk factors: results of the SAPALDIA study. Europace. 2006;8(7):521–9.
Google Scholar
Yi SH, Lee K, Shin D-G, Kim JS, Ki H-C. Differential association of adiposity measures with heart rate variability measures in Koreans. Yonsei Med J. 2013;54(1):55–61.
Google Scholar
Hottenrott K, Hoos O, Esperer HD. Herzfrequenzvariabilität und sport. Herz Kardiovaskuläre Erkrankungen. 2006;31(6):544–52.
Tonello L, Rodrigues FB, Souza JWS, Campbell CSG, Leicht A, Boullosa DA. The role of physical activity and heart rate variability for the control of work related stress. Front Physiol. 2014;5:67.
Google Scholar
Bakker AB, de Vries JD. Job Demands-Resources theory and self-regulation: new explanations and remedies for job burnout. Anxiety Stress Coping. 2021;34(1):1–21.
Google Scholar
Pluut H, Ilies R, Curşeu PL, Liu Y. Social support at work and at home: Dual-buffering effects in the work-family conflict process. Organ Behav Hum Decision Processes. 2018;146:1–13.
Google Scholar
Yu F, Raphael D, Mackay L, Smith M, King A. Personal and work-related factors associated with nurse resilience: a systematic review. Int J Nurs Stud. 2019;93:129–40.
Google Scholar
Basińska MA, Sołtys M. Personal resources and flexibility in coping with stress depending on perceived stress in a group of cancer patients. HPR. 2020;8(2):107–19.
Google Scholar
Goetz K, Beutel S, Mueller G, Trierweiler-Hauke B, Mahler C. Work-related behaviour and experience patterns of nurses. Int Nurs Rev. 2012;59(1):88–93.
Google Scholar
Thun S, Bakker AB. Empowering leadership and job crafting: The role of employee optimism. Stress Health. 2018;34(4):573–81.
Google Scholar
Bayraktar S, Jiménez A. Self-efficacy as a resource: a moderated mediation model of transformational leadership, extent of change and reactions to change. J Organ Chang Manage. 33;301–17.
Broetje S, Jenny GJ, Bauer GF. The key job demands and resources of nursing staff: an integrative review of reviews. Front Psychol. 2020;11:84.
Google Scholar
Chang P-Y, Chiou S-T, Lo W-Y, Huang N, Chien L-Y. Stressors and level of stress among different nursing positions and the associations with hyperlipidemia, hyperglycemia, and hypertension: a national questionnaire survey. BMC Nurs. 2021;20(1):250.
Google Scholar
Chiou S-T, Chiang J-H, Huang N, Chien L-Y. Health behaviors and participation in health promotion activities among hospital staff: which occupational group performs better? BMC Health Serv Res. 2014;14:474.
Google Scholar
Gerber M, Pühse U. Do exercise and fitness protect against stress-induced health complaints? A review of the literature. Scand J Public Health. 2009;37(8):801–19.
Google Scholar
Vander Elst T, Cavents C, Daneels K, Johannik K, Baillien E, van den Broeck A, et al. Job demands-resources predicting burnout and work engagement among Belgian home health care nurses: a cross-sectional study. Nurs Outlook. 2016;64(6):542–56.
Google Scholar
Khoury B, Sharma M, Rush SE, Fournier C. Mindfulness-based stress reduction for healthy individuals: a meta-analysis. J Psychosom Res. 2015;78(6):519–28.
Google Scholar
Caldwell K, Harrison M, Adams M, Quin RH, Greeson J. Developing mindfulness in college students through movement-based courses: effects on self-regulatory self-efficacy, mood, stress, and sleep quality. J Am Coll Health. 2010;58(5):433–42.
Google Scholar
Edwards KM, Wilson KL, Sadja J, Ziegler MG, Mills PJ. Effects on blood pressure and autonomic nervous system function of a 12-week exercise or exercise plus DASH-diet intervention in individuals with elevated blood pressure. Acta Physiologica. 2011;203(3):343–50.
Google Scholar
Chan CB, Ryan DAJ, Tudor-Locke C. Health benefits of a pedometer-based physical activity intervention in sedentary workers. Prev Med. 2004;39(6):1215–22.
Google Scholar
Tucker S, Farrington M, Lanningham-Foster LM, Clark MK, Dawson C, Quinn GJ, et al. Worksite physical activity intervention for ambulatory clinic nursing staff. Workplace Health Safety. 2016;64(7):313–25.
Google Scholar
Stratton E, Lampit A, Choi I, Calvo RA, Harvey SB, Glozier N. Effectiveness of eHealth interventions for reducing mental health conditions in employees: a systematic review and meta-analysis. PLoS One. 2017;12(12):e0189904.
Google Scholar
Phillips EA, Gordeev VS, Schreyögg J. Effectiveness of occupational e-mental health interventions: a systematic review and meta-analysis of randomized controlled trials. Scand J Work Environ Health. 2019;45(6):560–76.
Google Scholar
Bischoff LL, Otto A-K, Hold C, Wollesen B. The effect of physical activity interventions on occupational stress for health personnel: a systematic review. Int J Nurs Stud. 2019;97:94–104 Cited 2022 May 29.
Google Scholar
Babanataj R, Mazdarani S, Hesamzadeh A, Gorji MH, Cherati JY. Resilience training: Effects on occupational stress and resilience of critical care nurses. Int J Nurs Pract. 2019;25(1):e12697.
Google Scholar
Lan HK, Subramanian P, Rahmat N, Kar PC. The effects of mindfulness training program on reducing stress and promoting well-being among nurses in critical care units. Australian J Advanced Nurs. 2014;31(3):22–31.
Mealer M, Conrad D, Evans J, Jooste K, Solyntjes J, Rothbaum B, et al. Feasibility and acceptability of a resilience training program for intensive care unit nurses. Am J Crit Care. 2014;23(6):e97–105.
Google Scholar
Stanulewicz N, Knox E, Narayanasamy M, Shivji N, Khunti K, Blake H. Effectiveness of lifestyle health promotion interventions for nurses: a systematic review. IJERPH. 2019;17(01):17.
Google Scholar
Chesak SS, Cutshall SM, Bowe CL, Montanari KM, Bhagra A. Stress management interventions for nurses: critical literature review. J Holist Nurs. 2019;37(3):288–95.
Google Scholar
Schulz M, Damkröger A, Voltmer E, Löwe B, Driessen M, Ward M, et al. Work-related behaviour and experience pattern in nurses: impact on physical and mental health. J Psychiatr Mental Health Nurs. 2011;18(5):411–7.
Google Scholar
Alayli-Goebbels AFG, Dellaert BGC, Knox SA, Ament AJHA, Lakerveld J, Bot SDM, et al. Consumer preferences for health and nonhealth outcomes of health promotion: results from a discrete choice experiment. Value Health. 2013;16(1):114–23 Cited 2022 May 27.
Google Scholar
O’Keeffe M, O’Sullivan P, Purtill H, Bargary N, O’Sullivan K. Cognitive functional therapy compared with a group-based exercise and education intervention for chronic low back pain: a multicentre randomised controlled trial (RCT). Br J Sports Med. 2020;54(13):782–9.
Google Scholar
Wienert J, Kuhlmann T, Storm V, Reinwand D, Lippke S. Latent user groups of an eHealth physical activity behaviour change intervention for people interested in reducing their cardiovascular risk. Res Sports Med. 2019;27(1):34–49.
Google Scholar
Ketelaar SM, Nieuwenhuijsen K, Bolier L, Smeets O, Sluiter JK. Improving work functioning and mental health of health care employees using an e-mental health approach to workers’ health surveillance: pretest–posttest study. Safety Health Work. 2014;5(4):216–21.
Google Scholar
Baumann H, Meixner C, Wollesen B. Voraussetzungen zur Vermittlung digitaler Gesundheitskompetenzen durch Sportlehrkräfte im Zuge der SARS-CoV-2-Pandemie – Eine explorative Mixed-Methods-Studie im Schulkontext. Zeitschrift für Studium und Lehre in der Sportwissenschaft – Themenheft Digitalisierung in der Sportlehrer*innenbildung. 2022:1:5-18. Available from https://issuu.com/sporthochschule-koeln/docs/zsls-themenheft_-_digitalisierung_heft_2_-_01-22-_.
Thranberend T, Knöppler K, Neisecke T. Gesundheits-Apps: Bedeutender Hebel für Patient Empowerment–Potenziale jedoch bislang kaum genutzt. Spotlight Gesundheit. 2016;2:1–8.
Harrer M, Adam SH, Fleischmann RJ, Baumeister H, Auerbach R, Bruffaerts R, et al. Effectiveness of an internet-and app-based intervention for college students with elevated stress: randomized controlled trial. J Med Internet Res. 2018;20(4):e9293.
Google Scholar
Economides M, Martman J, Bell MJ, Sanderson B. Improvements in stress, affect, and irritability following brief use of a mindfulness-based smartphone app: a randomized controlled trial. Mindfulness. 2018;9(5):1584–93.
Google Scholar
Fischer F. Digitale Interventionen in Prävention und Gesundheitsförderung: Welche Form der Evidenz haben wir und welche wird benötigt? Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz. 2020;63(6):674–80.
Google Scholar
Bischoff LL, Baumann H, Meixner C, Nixon P, Wollesen B. App-tailoring requirements to increase stress management competencies within families: cross-sectional survey Study. J Med Internet Res. 2021;23(7):e26376.
Google Scholar
Heber E, Ebert DD, Lehr D, Cuijpers P, Berking M, Nobis S, et al. The benefit of web- and computer-based interventions for stress: a systematic review and meta-analysis. J Med Internet Res. 2017;19(2):e32.
Google Scholar
Kramer U. Wie gut sind Gesundheits-Apps? Aktuelle Ernährungsmedizin. 2017;42(03):193–205.
Google Scholar
Calear AL, Christensen H, Mackinnon A, Griffiths KM. Adherence to the MoodGYM program: outcomes and predictors for an adolescent school-based population. J Affect Disord. 2013;147(1-3):338–44.
Google Scholar
Lustria MLA, Cortese J, Noar SM, Glueckauf RL. Computer-tailored health interventions delivered over the Web: review and analysis of key components. Patient Educ Counsel. 2009;74(2):156–73.
Google Scholar
Lustria MLA, Noar SM, Cortese J, van Stee SK, Glueckauf RL, Lee J. A meta-analysis of web-delivered tailored health behavior change interventions. J Health Commun. 2013;18(9):1039–69.
Google Scholar
Fleischmann RJ, Harrer M, Zarski A-C, Baumeister H, Lehr D, Ebert DD. Patients’ experiences in a guided Internet-and App-based stress intervention for college students: a qualitative study. Internet Interventions. 2018;12:130–40.
Google Scholar
Baumann H, Fiedler J, Wunsch K, Woll A, Wollesen B. mHealth interventions to reduce physical inactivity and sedentary behavior in children and adolescents: systematic review and meta-analysis of randomized controlled trials. JMIR Mhealth Uhealth. 2022;10(5):e35920.
Google Scholar
Connor-Smith JK, Flachsbart C. Relations between personality and coping: a meta-analysis. J Personal Soc Psychol. 2007;93(6):1080.
Google Scholar
Ghaban W, Hendley R. How different personalities benefit from gamification. Interact Comput. 2019;31(2):138–53 Cited 2022 May 31.
Google Scholar
Chan A-W, Tetzlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Krleža-Jerić K, et al. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Internal Med. 2013;158(3):200–7.
Google Scholar
Faul F, Erdfelder E, Lang A-G, Buchner A. G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175–91.
Google Scholar
Head KJ, Noar SM, Iannarino NT, Grant HN. Efficacy of text messaging-based interventions for health promotion: a meta-analysis. Soc Sci Med. 2013;97:41–8.
Google Scholar
Krebs P, Prochaska JO, Rossi JS. A meta-analysis of computer-tailored interventions for health behavior change. Prev Med. 2010;51(3-4):214–21.
Google Scholar
Rongen A, Robroek SJW, van Lenthe FJ, Burdorf A. Workplace health promotion: a meta-analysis of effectiveness. Am J Prev Med. 2013;44(4):406–15 Available from: URL: https://www.sciencedirect.com/science/article/pii/S0749379713000123.
Google Scholar
Wollesen B, Menzel J, Lex H, Mattes K. The BASE-program—A multidimensional approach for health promotion in companies. In: Healthcare, vol. 4: Multidisciplinary Digital Publishing Institute. p. 91.
Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–96.
Warttig SL, Forshaw MJ, South J, White AK. New, normative, English-sample data for the Short Form Perceived Stress Scale (PSS-4). J Health Psychol. 2013;18(12):1617–28.
Google Scholar
Cole RJ, Kripke DF, Gruen W, Mullaney DJ, Gillin JC. Automatic sleep/wake identification from wrist activity. Sleep. 1992;15(5):461–9.
Google Scholar
Hirshkowitz M, Whiton K, Albert SM, Alessi C, Bruni O, DonCarlos L, et al. National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health. 2015;1(1):40–3.
Google Scholar
Buysse DJ, Reynolds CF III, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.
Google Scholar
Hinz A, Glaesmer H, Brähler E, Löffler M, Engel C, Enzenbach C, et al. Sleep quality in the general population: psychometric properties of the Pittsburgh Sleep Quality Index, derived from a German community sample of 9284 people. Sleep Med. 2017;30:57–63.
Google Scholar
Chung F, Yegneswaran B, Liao P, Chung SA, Vairavanathan S, Islam S, et al. STOP questionnaire: a tool to screen patients for obstructive sleep apnea. J Am Soc Anesthesiologists. 2008;108(5):812–21.
Bassett D, Tudor-Locke C. How many steps/day are enough? Preliminary pedometer indices for public health. Sports Med. 2004;34:1–8.
Google Scholar
Livesey G. Energy and protein requirements the 1985 report of the 1981 Joint FAO/WHO/UNU Expert Consultation. Nutr Bull. 1987;12(3):138–49.
Google Scholar
Froböse I, Wallmann-Sperlich B. Studienbericht DKV Report 2016 “Wie gesund lebt Deutschland”. Zentrum gür Gesundheit der deutschen Sporthochschule Köln [cited 2022 May 31].
World Health Organization. Obesity: preventing and managing the global epidemic: World Health Organization; 2000.
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.
Google Scholar
Schaarschmidt U, Fischer AW. Arbeitsbezogenes Verhaltens-und Erlebensmuster AVEM. 3. überarbeitete Auflage, Frankfurt a. M.: Swets & Zeitlinger 2008.
Rath HM, Steimann M, Ullrich A, Rotsch M, Zurborn K-H, Koch U, et al. Psychometric properties of the Occupational Stress and Coping Inventory (AVEM) in a cancer population. Acta Oncol. 2015;54(2):232–42.
Google Scholar
Balgiu BA. The psychometric properties of the Big Five inventory-10 (BFI-10) including correlations with subjective and psychological well-being. Global J Psychol Res. 2018;8(2):61–9.
Boß L, Lehr D, Reis D, Vis C, Riper H, Berking M, et al. Reliability and validity of assessing user satisfaction with web-based health interventions. J Med Internet Res. 2016;18(8):e5952.
Google Scholar
Zhang M, Zhang P, Liu Y, Wang H, Hu K, Du M. Influence of perceived stress and workload on work engagement in front-line nurses during COVID-19 pandemic. J Clin Nurs. 2021;30(11-12):1584–95 Cited 2022 May 29.
Google Scholar
Wollesen B, Hagemann D, Pabst K, Schlüter R, Bischoff LL, Otto A-K, et al. Identifying individual stressors in geriatric nursing staff—a cross-sectional study. IJERPH. 2019;16(19):3587.
Google Scholar
Hasson H, Arnetz JE. Nursing staff competence, work strain, stress and satisfaction in elderly care: a comparison of home-based care and nursing homes. J Clin Nurs. 2008;17(4):468–81 Cited 2022 May 29.
Google Scholar
van Reeth O, Weibel L, Spiegel K, Leproult R, Dugovic C, Maccari S. PHYSIOLOGY OF SLEEP (REVIEW)–Interactions between stress and sleep: from basic research to clinical situations. Sleep Med Rev. 2000;4(2):201–19 Cited 2022 May 29.
Google Scholar
Janwantanakul P, Sitthipornvorakul E, Paksaichol A. Risk factors for the onset of nonspecific low back pain in office workers: a systematic review of prospective cohort studies. J Manipulative Physiol Ther. 2012;35(7):568–77 Cited 2022 May 29.
Google Scholar
Greenwood-Van Meerveld B, Johnson AC. Mechanisms of stress-induced visceral pain. J Neurogastroenterol Motil. 2018;24(1):7–18 Cited 2022 May 29.
Google Scholar
Zhang Y, Flum M, Kotejoshyer R, Fleishman J, Henning R, Punnett L. Workplace participatory occupational health/health promotion program: facilitators and barriers observed in three nursing homes. J Gerontol Nurs. 2016;42(6):34–42.
Google Scholar
Jenkins C, Smythe A, Galant-Miecznikowska M, Bentham P, Oyebode J. Overcoming challenges of conducting research in nursing homes. Nurs Older People. 2016;28(5).
Heuel L, Lübstorf S, Otto A-K, Wollesen B. Chronic stress, behavioral tendencies, and determinants of health behaviors in nurses: a mixed-methods approach. BMC Public Health. 2022;22(1):624 Cited 2022 May 31.
Google Scholar
Klasnja P, Hekler EB, Shiffman S, Boruvka A, Almirall D, Tewari A, et al. Microrandomized trials: an experimental design for developing just-in-time adaptive interventions. Health Psychol. 2015;34S:1220–8 Cited 2022 May 29.
Google Scholar
Otto A-K, Gutsch C, Bischoff LL, Wollesen B. Interventions to promote physical and mental health of nurses in elderly care: a systematic review. Prev Med. 2021;148:106591.
Google Scholar
Kononova A, Li L, Kamp K, Bowen M, Rikard RV, Cotten S, et al. The use of wearable activity trackers among older adults: focus group study of tracker perceptions, motivators, and barriers in the maintenance stage of behavior change. JMIR Mhealth Uhealth. 2019;7(4):e9832 Cited 2022 May 29.
Google Scholar
Wongvibulsin S, Martin SS, Saria S, Zeger SL, Murphy SA. An individualized, data-driven digital approach for precision behavior change. Am J Lifestyle Med. 2020;14(3):289–93 Cited 2022 May 29.
Google Scholar
Klimova B, Poulova P. Older People and Technology Acceptance. In: Zhou J, Salvendy G, editors. Human aspects of IT for the aged population. Acceptance, Communication and Participation, vol. 10926. Cham: Springer International Publishing; 2018.
Google Scholar
link