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What Happens When Individuals Answer Questionnaires in Two Different Languages.

ABSTRACT: The aim of the present study was to compare scores from the English and the Spanish versions of two well-known measures of psychological distress using a within-subject approach. This method involved bilingual participants completing both measures in four conditions. For two groups of people, measures were offered in the same language both times and for the other two groups, each language version was offered, the order differing between the groups. The measures were the Clinical Outcomes in Routine Evaluation-Outcome Measure and the Schwartz Outcome Scale-10, both originally created in English and then translated to Spanish. In total, 109 bilingual participants (69.7% women) completed the measures in two occasions and were randomly allocated to the four conditions (English-English, English-Spanish, Spanish-English and Spanish-Spanish). Linear mixed effects models were performed to provide a formal null hypothesis test of the effect of language, order of completion and their interaction for each measure. The results indicate that for the total score of the Clinical Outcomes in Routine Evaluation-Outcome Measure just language had a significant effect, but no significant effects were found for completion order or the language by order interaction. For the Schwartz Outcome Scale-10 scores, none of these effects were statistically significant. This method offers some clear advantages over the more prevalent psychometric methods of testing score comparability across measure translations.

SUBMITTER: Paz C

PROVIDER: S-EPMC8260934 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundA widely discussed design issue in patient satisfaction questionnaires is the optimal length and labelling of the answering scale. The aim of the present study was to compare intra-individually the answers on two response scales to five general questions evaluating patients' perception of hospital care.MethodsBetween November 2011 and January 2012, all in-hospital patients at a Swiss University Hospital received a patient satisfaction questionnaire on an adjectival scale with three to four labelled categories (LS) and five redundant questions displayed on an 11-point end-anchored numeric scale (NS). The scales were compared concerning ceiling effect, internal consistency (Cronbach's alpha), individual item answers (Spearman's rank correlation), and concerning overall satisfaction by calculating an overall percentage score (sum of all answers related to the maximum possible sum).ResultsThe response rate was 41% (2957/7158), of which 2400 (81%) completely filled out all questions. Baseline characteristics of the responders and non-responders were similar. Floor and ceiling effect were high on both response scales, but more pronounced on the LS than on the NS. Cronbach's alpha was higher on the NS than on the LS. There was a strong individual item correlation between both answering scales in questions regarding the intent to return, quality of treatment and the judgement whether the patient was treated with respect and dignity, but a lower correlation concerning satisfactory information transfer by physicians or nurses, where only three categories were available in the LS. The overall percentage score showed a comparable distribution, but with a wider spread of lower satisfaction in the NS.ConclusionsSince the longer scale did not substantially reduce the ceiling effect, the type of questions rather than the type of answering scale could be addressed with a focus on specific questions about concrete situations instead of general questions. Moreover, the low correlation in questions about information provision suggests that only three possible response choices are insufficient. Further investigations are needed to find a more sensitive scale discriminating high-end ratings. Otherwise, a longitudinal within-hospital or a cross-sectional between-hospital comparison of patient care is questionable.

Project description:BackgroundClinical symptoms in children with pulmonary diseases are frequently non-specific. Rare diseases such as primary ciliary dyskinesia (PCD), cystic fibrosis (CF) or protracted bacterial bronchitis (PBB) can be easily missed at the general practitioner (GP).ObjectiveTo develop and test a questionnaire-based and data mining-supported tool providing diagnostic support for selected pulmonary diseases.MethodsFirst, interviews with parents of affected children were conducted and analysed. These parental observations during the pre-diagnostic time formed the basis for a new questionnaire addressing the parents' view on the disease. Secondly, parents with a sick child (e.g. PCD, PBB) answered the questionnaire and a data base was set up. Finally, a computer program consisting of eight different classifiers (support vector machine (SVM), artificial neural network (ANN), fuzzy rule-based, random forest, logistic regression, linear discriminant analysis, naive Bayes and nearest neighbour) and an ensemble classifier was developed and trained to categorise any given new questionnaire and suggest a diagnosis. For estimating the diagnostic accuracy, we applied ten-fold stratified cross validation.ResultsAll questionnaires of patients suffering from CF, asthma (AS), PCD, acute bronchitis (AB) and the healthy control group were correctly diagnosed by the fusion algorithm. For the pneumonia (PM) group 19/21 (90.5%) and for the PBB group 17/18 (94.4%) correct diagnoses could be reached. The program detected the correct diagnoses with an overall sensitivity of 98.8%. Receiver operating characteristics (ROC) analyses confirmed the accuracy of this diagnostic tool. Case studies highlighted the applicability of the tool in the daily work of a GP.ConclusionFor children with symptoms of pulmonary diseases a questionnaire-based diagnostic support tool using data mining techniques exhibited good results in arriving at diagnostic suggestions. In the hands of a doctor, this tool could be of value in arousing awareness for rare pulmonary diseases such as PCD or CF.

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What Happens When Individuals Answer Questionnaires in Two Different Languages.

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