Impact of a multimedia website with patient experiences of multiple sclerosis (PExMS) on immunotherapy decision-making: study protocol for a pilot randomised controlled trial in a mixed-methods design

Anna Barabasch, Karin Riemann-Lorenz, Christopher Kofahl, Jutta Scheiderbauer, Desiree Eklund, Ingo Kleiter, Jürgen Kasper, Sascha Köpke, Susanne Lezius, Antonia Zapf, Anne Christin Rahn, Christoph Heesen, Anna Barabasch, Karin Riemann-Lorenz, Christopher Kofahl, Jutta Scheiderbauer, Desiree Eklund, Ingo Kleiter, Jürgen Kasper, Sascha Köpke, Susanne Lezius, Antonia Zapf, Anne Christin Rahn, Christoph Heesen

Abstract

Background: A variety of management options (e.g. immunotherapies, lifestyle interventions, and rehabilitation) are available for people with relapsing-remitting multiple sclerosis (RRMS). Besides coping with the diagnosis, people with MS (pwMS) have to make complex decisions such as deciding about immunotherapies. In addition to factual information, reports of patient experiences (PEx) may support patients in decision-making. The added value of PEx in decision-making is not clear, and controlled studies are rare. Therefore, systematic methods are necessary to develop and analyse PEx. As there are no evaluated PEx for MS in Germany, we are currently creating a website presenting PEx structured according to topics and illustrated by video, audio, and text files. We aim to determine the feasibility of an intervention using PEx and evaluate whether PEx may help pwMS in their immunotherapy decision-making processes as a supplement to evidence-based information.

Methods: This project will follow the Medical Research Council framework for development and evaluation of complex interventions. After the development of a website with PEx, a randomised controlled pilot trial (pilot RCT) will be conducted in 2-3 MS centres, clinics, or rehabilitation centres including 55 pwMS and accompanied by a process evaluation. Patients with a RRMS diagnosis considering immunotherapy are eligible. The primary outcome is decision self-efficacy. Secondary outcomes include preparation for decision-making, decisional conflict, risk knowledge, confidence in active participation, affective forecasting, social support, and self-reported impact of eHealth on its users. Participants will be randomly assigned either to (i) an intervention group with 4 weeks access to an evidence-based patient information resource and the PExMS-website as an adjunct or to (ii) the control group with access to evidence-based information alone. A 6-member advisory panel involving representatives of pwMS, researchers, and neurologists, who accompany the whole project, will mentor this pilot RCT.

Discussion: The intervention was developed with systematic methods, created with active patient involvement and in critical appraisal by an expert advisory panel. The study is innovative as it contributes to the controversial evidence on the use of PEx in the context of evidence-based patient information.

Trial registration: ClinicalTrials.gov, NCT04236544.

Keywords: Decision support; Decision-making; Multiple sclerosis; Narrative information; Patient experiences; Web-based experiential information.

Conflict of interest statement

AB has received funding from Roche Pharma. CH has received research grants, congress travel compensations, and salaries for talks from Biogen, Genzyme, Sanofi-Aventis, Bayer Healthcare, Merck, Teva Pharma, Roche Pharma, and Novartis. IK has received speaker honoraria and travel funding from Bayer, Biogen, Novartis, Merck, Sanofi Genzyme, Roche; speaker honoraria from Mylan; travel funding from the Guthy-Jackson Charitable Foundation; consulted for Alexion, Bayer, Biogen, Celgene, Chugai, IQVIA, Novartis, Merck, Roche; and received research support from Chugai, Diamed. KRL, CK, JS, DE, SK, and JK declare that they have no competing interests. ACR was supported by a research grant from the National MS Society, USA (grant no. G-1508-06034).

Figures

Fig. 1
Fig. 1
Flow diagram showing the process of developing a website with PEx
Fig. 2
Fig. 2
Study flowchart

References

    1. Browne P, Chandraratna D, Angood C, Tremlett H, Baker C, Taylor BV, et al. Atlas of multiple sclerosis 2013: a growing global problem with widespread inequity. Neurology. 2014;83(11):1022–1024. doi: 10.1212/WNL.0000000000000768.
    1. WHO . Atlas multiple sclerosis resources in the world 2008. Geneva; London: World Health Organization; Multiple Sclerosis International Federation; 2008. p. 51.
    1. DMSG. Was ist Multiple Sklerose?: Häufigkeit der MS 2017. Available from: . Accessed May 2020.
    1. Ngandu T, Lehtisalo J, Solomon A, Levalahti E, Ahtiluoto S, Antikainen R, et al. A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial. Lancet (London, England) 2015;385(9984):2255–2263. doi: 10.1016/S0140-6736(15)60461-5.
    1. Hempel S, Graham GD, Fu N, Estrada E, Chen AY, Miake-Lye I, et al. A systematic review of the effects of modifiable risk factor interventions on the progression of multiple sclerosis. Mult Scler J. 2017;23(4):513–524. doi: 10.1177/1352458517690271.
    1. Heesen C, Kasper J, Segal J, Köpke S, Mühlhauser I. Decisional role preferences, risk knowledge and information interests in patients with multiple sclerosis. Mult Scler (Houndmills, Basingstoke, England) 2004;10(6):643–650. doi: 10.1191/1352458504ms1112oa.
    1. Heesen C, Schäffler N, Kasper J, Mühlhauser I, Köpke S. Suspected multiple sclerosis - what to do? Evaluation of a patient information leaflet. Mult Scler (Houndmills, Basingstoke, England) 2009;15(9):1103–1112. doi: 10.1177/1352458509106508.
    1. Heesen C, Kolbeck J, Gold SM, Schulz H, Schulz KH. Delivering the diagnosis of MS--results of a survey among patients and neurologists. Acta Neurol Scand. 2003;107(5):363–368. doi: 10.1034/j.1600-0404.2003.00086.x.
    1. Köpke S, Kern S, Ziemssen T, Berghoff M, Kleiter I, Marziniak M, et al. Evidence-based patient information programme in early multiple sclerosis: a randomised controlled trial. J Neurol Neurosurg Psychiatry. 2014;85(4):411–418. doi: 10.1136/jnnp-2013-306441.
    1. Rahn AC, Köpke S, Kasper J, Vettorazzi E, Mühlhauser I, Heesen C. Evaluator-blinded trial evaluating nurse-led immunotherapy decision coaching in persons with relapsing-remitting multiple sclerosis (DECIMS) and accompanying process evaluation: study protocol for a cluster randomised controlled trial. Trials. 2015;16:106. doi: 10.1186/s13063-015-0611-7.
    1. Brigo F, Lochner P, Tezzon F, Nardone R. Web search behavior for multiple sclerosis: an infodemiological study. Mult Scler Relat Disord. 2014;3(4):440–443. doi: 10.1016/j.msard.2014.02.005.
    1. Synnot AJ, Hill SJ, Garner KA, Summers MP, Filippini G, Osborne RH, et al. Online health information seeking: how people with multiple sclerosis find, assess and integrate treatment information to manage their health. Health Expect. 2016;19(3):727–737. doi: 10.1111/hex.12253.
    1. Beckett JM, Bird ML, Pittaway JK, Ahuja KD. Diet and multiple sclerosis: scoping review of web-based recommendations. Interact J Med Res. 2019;8(1):e10050. doi: 10.2196/10050.
    1. Newhouse N, Martin A, Jawad S, Yu L-M, Davoudianfar M, Locock L, et al. Randomised feasibility study of a novel experience-based internet intervention to support self-management in chronic asthma. BMJ Open. 2016;6(12):e013401. doi: 10.1136/bmjopen-2016-013401.
    1. Ziebland S, Powell J, Briggs P, Jenkinson C, Wyke S, Sillence E, et al. Examining the role of patients’ experiences as a resource for choice and decision-making in health care: a creative, interdisciplinary mixed-method study in digital health. Programme Grants Appl Res. 2016;4(17):1–214. doi: 10.3310/pgfar04170.
    1. Powell J, Newhouse N, Martin A, Jawad S, Yu L-M, Davoudianfar M, et al. A novel experience-based internet intervention for smoking cessation: feasibility randomised controlled trial. BMC Public Health. 2016;16(1):1156. doi: 10.1186/s12889-016-3821-3.
    1. Dillard AJ, Fagerlin A, Dal Cin S, Zikmund-Fisher BJ, Ubel PA. Narratives that address affective forecasting errors reduce perceived barriers to colorectal cancer screening. Soc Sci Med. 2010;71(1):45–52. doi: 10.1016/j.socscimed.2010.02.038.
    1. Bekker HL, Winterbottom AE, Butow P, Dillard AJ, Feldman-Stewart D, Fowler FJ, et al. Do personal stories make patient decision aids more effective? A critical review of theory and evidence. BMC Med Inform Decis Mak. 2013;13(Suppl 2):S9. doi: 10.1186/1472-6947-13-S2-S9.
    1. Engler J, Adami S, Adam Y, Keller B, Repke T, Fügemann H, et al. Using others’ experiences. Cancer patients’ expectations and navigation of a website providing narratives on prostate, breast and colorectal cancer. Patient Educ Couns. 2016;99(8):1325–1332. doi: 10.1016/j.pec.2016.03.015.
    1. Entwistle VA, France EF, Wyke S, Jepson R, Hunt K, Ziebland S, et al. How information about other people’s personal experiences can help with healthcare decision-making: a qualitative study. Patient Educ Couns. 2011;85(3):e291–e298. doi: 10.1016/j.pec.2011.05.014.
    1. Giesler JM, Keller B, Repke T, Leonhart R, Weis J, Muckelbauer R, et al. Effect of a website that presents patients’ experiences on self-efficacy and patient competence of colorectal cancer patients: web-based randomized controlled trial. J Med Internet Res. 2017;19(10):e334. doi: 10.2196/jmir.7639.
    1. Shaffer VA, Hulsey L, Zikmund-Fisher BJ. The effects of process-focused versus experience-focused narratives in a breast cancer treatment decision task. Patient Educ Couns. 2013;93(2):255–264. doi: 10.1016/j.pec.2013.07.013.
    1. Shaffer VA, Zikmund-Fisher BJ. All stories are not alike: a purpose-, content-, and valence-based taxonomy of patient narratives in decision aids. Med Decis Mak. 2013;33(1):4–13. doi: 10.1177/0272989X12463266.
    1. Winterbottom A, Bekker HL, Conner M, Mooney A. Does narrative information bias individual’s decision making? A systematic review. Soc Sci Med (1982) 2008;67(12):2079–2088. doi: 10.1016/j.socscimed.2008.09.037.
    1. Ziebland S, Wyke S. Health and illness in a connected world: how might sharing experiences on the internet affect people’s health? Milbank Q. 2012;90(2):219–249. doi: 10.1111/j.1468-0009.2012.00662.x.
    1. Wilson TD, Gilbert DT. Affective forecasting: knowing what to want. Curr Dir Psychol Sci. 2005;14(3):131–134. doi: 10.1111/j.0963-7214.2005.00355.x.
    1. Halpern J, Arnold RM. Affective forecasting: an unrecognized challenge in making serious health decisions. J Gen Intern Med. 2008;23(10):1708–1712. doi: 10.1007/s11606-008-0719-5.
    1. Kofahl C, Haack M, Nickel S, Dierks M-L. Wirkungen der gemeinschaftlichen Selbsthilfe. Münster: LIT-Verlag; 2019.
    1. Lühnen J, Albrecht M, Mühlhauser I, Steckelberg A. Leitlinie evidenzbasierte Gesundheitsinformation. Hamburg; 2017. Available from: . Accessed May 2020.
    1. Graham ID, O’Connor AM. User manual - preparation for decision making scale. Ottawa: Institute OHR; 1995.
    1. Rahn AC, Köpke S, Backhus I, Kasper J, Anger K, Untiedt B, et al. Nurse-led immunotreatment decision coaching in people with multiple sclerosis (DECIMS) – feasibility testing, pilot randomised controlled trial and mixed methods process evaluation. Int J Nurs Stud. 2018;78:26–36. doi: 10.1016/j.ijnurstu.2017.08.011.
    1. Patton MQ. Qualitative research & evaluation methods: integrating theory and practice. 4. Los Angeles; London; New Delhi; Singapore; Washington DC: SAGE; 2015. p. 806.
    1. Witzel A. The problem-centered interview [26 paragraphs]. Forum Qual Soc Res. 2000;1(1). Art. 22. Available from: . Accessed May 2020.
    1. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101. doi: 10.1191/1478088706qp063oa.
    1. Osaka W, Nakayama K. Effect of a decision aid with patient narratives in reducing decisional conflict in choice for surgery among early-stage breast cancer patients: a three-arm randomized controlled trial. Patient Educ Couns. 2017;100(3):550–562. doi: 10.1016/j.pec.2016.09.011.
    1. O’Connor A. User manual – decision self-efficacy scale1995 06/13/2019:[4 p.]. Available from: . Accessed May 2020.
    1. Bunn H, O'Connor A. Validation of client decision-making instruments in the context of psychiatry. Can J Nurs Res. 1996;28(3):13–27.
    1. Bennett C, Graham ID, Kristjansson E, Kearing SA, Clay KF, O’Connor AM. Validation of a preparation for decision making scale. Patient Educ Couns. 2010;78(1):130–133. doi: 10.1016/j.pec.2009.05.012.
    1. Heesen C, Kasper J, Fischer K, Köpke S, Rahn A, Backhus I, et al. Risk knowledge in relapsing multiple sclerosis (RIKNO 1.0)--development of an outcome instrument for educational interventions. PLoS One. 2015;10(10):e0138364. doi: 10.1371/journal.pone.0138364.
    1. Heesen C, Pöttgen J, Rahn AC, Liethmann K, Kasper J, Vahter L, et al. What should a person with relapsing-remitting multiple sclerosis know? - Focus group and survey data of a risk knowledge questionnaire (RIKNO 2.0) Mult Scler Relat Disord. 2017;18:186–195. doi: 10.1016/j.msard.2017.09.020.
    1. Marteau TM, Dormandy E, Michie S. A measure of informed choice. Health Expect. 2001;4(2):99–108. doi: 10.1046/j.1369-6513.2001.00140.x.
    1. Köpke S, Kasper J, Flachenecker P, Meißner H, Brandt A, Hauptmann B, et al. Patient education programme on immunotherapy in multiple sclerosis (PEPIMS): a controlled rater-blinded study. Clin Rehabil. 2016;31(2):250–261. doi: 10.1177/0269215516639734.
    1. Legare F, Kearing S, Clay K, Gagnon S, D'Amours D, Rousseau M, et al. Are you SURE?: assessing patient decisional conflict with a 4-item screening test. Can Fam Physician. 2010;56(8):e308–e314.
    1. Degner LF, Sloan JA, Venkatesh P. The control preferences scale. Can J Nurs Res. 1997;29(3):21–43.
    1. De Las Cuevas C, Peñate W. Validity of the control preferences scale in patients with emotional disorders. Patient Prefer Adherence. 2016;10:2351–2356. doi: 10.2147/PPA.S122377.
    1. Kelly L, Ziebland S, Jenkinson C. Measuring the effects of online health information: scale validation for the e-Health Impact Questionnaire. Patient Educ Couns. 2015;98(11):1418–1424. doi: 10.1016/j.pec.2015.06.008.
    1. Hibbard JH, Stockard J, Mahoney ER, Tusler M. Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers. Health Serv Res. 2004;39(4 Pt 1):1005–1026. doi: 10.1111/j.1475-6773.2004.00269.x.
    1. Kelly L, Jenkinson C, Ziebland S. Measuring the effects of online health information for patients: item generation for an e-health impact questionnaire. Patient Educ Couns. 2013;93(3):433–438. doi: 10.1016/j.pec.2013.03.012.
    1. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361–370. doi: 10.1111/j.1600-0447.1983.tb09716.x.
    1. Learmonth YC, Motl RW, Sandroff BM, Pula JH, Cadavid D. Validation of patient determined disease steps (PDDS) scale scores in persons with multiple sclerosis. BMC Neurol. 2013;13:37. doi: 10.1186/1471-2377-13-37.
    1. O'Connor AM. User manual stage of decision making 2003 [3]. Available from: . Accessed May 2020.
    1. Bell ML, Whitehead AL, Julious SA. Guidance for using pilot studies to inform the design of intervention trials with continuous outcomes. Clin Epidemiol. 2018;10:153–157. doi: 10.2147/CLEP.S146397.
    1. Whitehead AL, Julious SA, Cooper CL, Campbell MJ. Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable. Stat Methods Med Res. 2016;25(3):1057–1073. doi: 10.1177/0962280215588241.
    1. Sim J, Lewis M. The size of a pilot study for a clinical trial should be calculated in relation to considerations of precision and efficiency. J Clin Epidemiol. 2012;65(3):301–308. doi: 10.1016/j.jclinepi.2011.07.011.
    1. Rahn AC, Backhus I, Fuest F, Riemann-Lorenz K, Köpke S, van de Roemer A, et al. Comprehension of confidence intervals - development and piloting of patient information materials for people with multiple sclerosis: qualitative study and pilot randomised controlled trial. BMC Med Inform Decis Mak. 2016;16(1):122. doi: 10.1186/s12911-016-0362-8.

Source: PubMed

Sponsor e collaboratori

Condizioni mediche

Interventi farmacologici

3
Sottoscrivi