C Heesen1, J Pöttgen2, A C Rahn3, K Liethmann4, J Kasper5, L Vahter6, J Drulovic7, A Van Nunen8, D Wilkie9, Y Beckmann10, F Paul11, S Köpke12, A Giordano13, A Solari14. 1. Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany. Electronic address: heesen@uke.de. 2. Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany; Neurologische Klinik, Universitätsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany. Electronic address: j.poettgen@uke.de. 3. Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany; Unit of Health Sciences and Education, University of Hamburg, Papendamm 21, 20146 Hamburg, Germany. Electronic address: a.rahn@uke.de. 4. Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany; Unit of Health Sciences and Education, University of Hamburg, Papendamm 21, 20146 Hamburg, Germany. Electronic address: Katrin.Liethmann@uni-hamburg.de. 5. Faculty of Health Sciences, Arctic University of Norway, 9073 Tromsø, Norway. Electronic address: k@sper.info. 6. Department of Neurology, West-Tallinn Central Hospital, Paldiski mnt. 68, 10617 Tallinn, Estonia. Electronic address: liina.vahter123@gmail.com. 7. Institute of Neurology, Clinical Center of Serbia, University of Belgrade, Dr. Subotića Starijeg 6, 11000 Beograd, Serbia. Electronic address: jelena.drulovic@kcs.ac.rs. 8. National MS-Centrum, Melsbroek, Vereeckenstraat 44, 1820 Melsbroek, Belgium. Electronic address: an.vannunen@mscenter.be. 9. Clinical Trials Unit, Department of Neurology, Imperial College, Room 10L18 (Lab Block, Charing Cross Campus, Hammersmith, London W6 8RF, UK. Electronic address: d.wilkie@imperial.ac.uk. 10. Department of Neurology, Ataturk Training and Research Hospital, Faculty of Medicine, Konak Mahallesi, İnönü Cad. 269. Sok. No:102, 35150 Karabağlar, Izmir, Turkey. Electronic address: ybeckmann@gmail.com. 11. NeuroCure Clinical Research Center and Clinical and Experimental Multiple Sclerosis Research Center, Department of Neurology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany. Electronic address: Friedemann.Paul@charite.de. 12. Institute for Social Medicine and Epidemiology, University of Lübeck, Ratzeburger Allee 160, D-23562 Lübeck, Germany. Electronic address: sascha.koepke@uksh.de. 13. Unit of Neuroepidemiology, Foundation IRCCS Neurological Institute C. Besta, Milan, Via Celoria 11, 20133 Milan, Italy. Electronic address: Andrea.Giordano@istituto-besta.it. 14. Unit of Neuroepidemiology, Foundation IRCCS Neurological Institute C. Besta, Milan, Via Celoria 11, 20133 Milan, Italy. Electronic address: Alessandra.Solari@istituto-besta.it.
Abstract
BACKGROUND: Risk knowledge is relevant to make informed decisions in multiple sclerosis (MS). The risk knowledge questionnaire for relapsing-remitting MS (RIKNO 1.0) was developed and piloted in Germany. OBJECTIVE: To produce a revised RIKNO 2.0 questionnaire using mixed methodology in a European setting. METHODS: The questionnaire was translated in seven languages. MS patient and health professional (HP) expert feedback was obtained from Germany, Italy, Estonia, Serbia, and the UK. A German web-based survey of RIKNO 2.0 compared the tool with the MS Knowledge Questionnaire (MSKQ), each one used with two versions (with/without a "don't know" DN option). RESULTS: While RIKNO 2.0 was considered difficult, it was rated as highly educational. One item was reframed, and two new items were added. The web-based German survey (n = 708 completers) showed that the DN version did not increase participation rate and did not produce significantly higher scores. Internal consistency (Cronbach alpha) without SN response was 0.73. RIKNO 2.0 scores showed normality distribution irrespective of the answering format. Item difficulty was high ranging from 0.07 to 0.79. Less than 50% of questions were answered correctly (mean 8.9) compared to 80.4% in the MSKQ (mean 20.1). Higher numeracy competency and education were significantly, albeit weakly, associated to higher scores for both RIKNO 2.0 and MSKQ. CONCLUSION: Including "don't know" options in knowledge questionnaires does not increase percentage of correct replies. RIKNO 2.0 is a complex questionnaire to be used in an educational context and studies on patient information. The tool is now available in seven languages.
RCT Entities:
BACKGROUND: Risk knowledge is relevant to make informed decisions in multiple sclerosis (MS). The risk knowledge questionnaire for relapsing-remitting MS (RIKNO 1.0) was developed and piloted in Germany. OBJECTIVE: To produce a revised RIKNO 2.0 questionnaire using mixed methodology in a European setting. METHODS: The questionnaire was translated in seven languages. MS patient and health professional (HP) expert feedback was obtained from Germany, Italy, Estonia, Serbia, and the UK. A German web-based survey of RIKNO 2.0 compared the tool with the MS Knowledge Questionnaire (MSKQ), each one used with two versions (with/without a "don't know" DN option). RESULTS: While RIKNO 2.0 was considered difficult, it was rated as highly educational. One item was reframed, and two new items were added. The web-based German survey (n = 708 completers) showed that the DN version did not increase participation rate and did not produce significantly higher scores. Internal consistency (Cronbach alpha) without SN response was 0.73. RIKNO 2.0 scores showed normality distribution irrespective of the answering format. Item difficulty was high ranging from 0.07 to 0.79. Less than 50% of questions were answered correctly (mean 8.9) compared to 80.4% in the MSKQ (mean 20.1). Higher numeracy competency and education were significantly, albeit weakly, associated to higher scores for both RIKNO 2.0 and MSKQ. CONCLUSION: Including "don't know" options in knowledge questionnaires does not increase percentage of correct replies. RIKNO 2.0 is a complex questionnaire to be used in an educational context and studies on patient information. The tool is now available in seven languages.
Authors: Anne Christin Rahn; Alessandra Solari; Heleen Beckerman; Richard Nicholas; David Wilkie; Christoph Heesen; Andrea Giordano Journal: Int J MS Care Date: 2020-12-28
Authors: Andrea Giordano; Katrin Liethmann; Sascha Köpke; Jana Poettgen; Anne Christin Rahn; Jelena Drulovic; Yesim Beckmann; Jaume Sastre-Garriga; Ian Galea; Marco Heerings; Peter Joseph Jongen; Eik Vettorazzi; Alessandra Solari; Christoph Heesen Journal: PLoS One Date: 2018-11-29 Impact factor: 3.240
Authors: Nicole Krause; Karin Riemann-Lorenz; Tanja Steffen; Anne Christin Rahn; Jana Pöttgen; Jan-Patrick Stellmann; Sascha Köpke; Tim Friede; Andrea Icks; Markus Vomhof; Herbert Temmes; Markus van de Loo; Stefan M Gold; Christoph Heesen Journal: BMJ Open Date: 2021-02-16 Impact factor: 2.692
Authors: 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 Journal: Pilot Feasibility Stud Date: 2021-01-07