What should a person with relapsing-remitting multiple sclerosis know? - Focus group and survey data of a risk knowledge questionnaire (RIKNO 2.0)

  • C Heesen
  • J Pöttgen
  • A C Rahn
  • K Liethmann
  • J Kasper
  • L Vahter
  • J Drulovic
  • A Van Nunen
  • D Wilkie
  • Y Beckmann
  • F Paul
  • A Giordano
  • A Solari
  • AutoMS-group

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.

Bibliografische Daten

OriginalspracheEnglisch
ISSN2211-0348
DOIs
StatusVeröffentlicht - 11.2017
PubMed 29141808