%0 Journal Article
%T Patient knowledge in anaesthesia: Psychometric development of the RAKQ-The Rotterdam anaesthesia Knowledge questionnaire.
%A van den Heuvel SF
%A van Eeren H
%A Hoeks SE
%A Panasewicz A
%A Jonker P
%A Ismail SY
%A van Busschbach JJ
%A Stolker RJ
%A Korstanje JH
%J PLoS One
%V 19
%N 7
%D 2024
%M 38995908
%F 3.752
%R 10.1371/journal.pone.0299052
%X The transition from in-person to digital preoperative patient education requires effective methods for evaluating patients' understanding of the perioperative process, risks, and instructions to ensure informed consent. A knowledge questionnaire covering different anaesthesia techniques and instructions could fulfil this need. We constructed a set of items covering common anaesthesia techniques requiring informed consent and developed the Rotterdam Anaesthesia Knowledge Questionnaire (RAKQ) using a structured approach and Item Response Theory. A team of anaesthetists and educational experts developed the initial set of 60 multiple-choice items, ensuring content and face validity. Next, based on exploratory factor analysis, we identified seven domains: General Anaesthesia-I (regarding what to expect), General Anaesthesia-II (regarding the risks), Spinal Anaesthesia, Epidural Anaesthesia, Regional Anaesthesia, Procedural sedation and analgesia, and Generic Items. This itemset was filled out by 577 patients in the Erasmus MC, Rotterdam, and Albert Schweitzer Hospital, Dordrecht, the Netherlands. Based on factor loadings (≥0.25) and considering clinical relevance this initial item set was reduced to 50 items, distributed over the seven domains. Each domain was processed to produce a separate questionnaire. Through an iterative process of item selection to ensure that the questionnaires met the criteria for Item Response Theory modelling, 40 items remained in the definitive set of seven questionnaires. Finally, we developed an Item Response Theory model for each questionnaire and evaluated its reliability. 1-PL and 2-PL models were chosen based on best model fit. No item misfit (S-χ2, p<0.001 = misfit) was detected in the final models. The newly developed RAKQ allows practitioners to assess their patients' knowledge before consultation to better address knowledge gaps during consultation. Moreover, they can decide whether the level of knowledge is sufficient to obtain digital informed consent without face-to-face education. Researchers can use the RAKQ to compare new methods of patient education with traditional methods.