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      Validity and reliability of the German version of the shortened thyroid-specific quality of life questionnaire (ThyPRO-39de)

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          Abstract

          Objectives

          Validation of a German version of the ThyPRO-39 questionnaire for quality of life (QoL) in patients with benign thyroid diseases.

          Design

          Internal consistency, retest reliability, and validity were to be assessed in a test-retest study.

          Methods

          The ThyPRO-39 was translated based on standard methodology. A sample of 98 patients with benign thyroid diseases was tested with the ThyPRO-39de and the generic EuroQol 5D-5L. Forty-four patients with stable symptoms after 2 weeks formed the repeated measures sample. Cronbach’s alpha was calculated for the ThyPRO-39de composite score and for each disease-specific scale. Intraclass correlations between the original and the repeated measures sample were calculated for each scale as well as Pearson correlations between various ThyPRO scales and the EuroQol. T-tests were used to test for differences in the goiter and hyperthyroid symptom scales between relevant patient groups and other patients.

          Results

          Internal consistency was between satisfactory and good, except for two scales (tiredness and cosmetic complaints/appearance). The test-retest correlation was between 0.62 and 0.8 for most scales, but below 0.5 for two scales (tiredness and impaired social life). There were significant correlations between the EuroQol index score and most aspects of the ThyPRO-39de. Only the hyperthyroid symptoms scale was specific for the relevant patient group (Graves’ disease).

          Conclusion

          The ThyPRO-39de may be recommended for use in clinical and research settings, especially with regards to the composite score. However, the underlying thyroid disease should always be kept in mind when interpreting the test results. A larger sample would be needed to implement further improvements.

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          Most cited references18

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          Coefficient alpha and the internal structure of tests

          Psychometrika, 16(3), 297-334
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            Making sense of Cronbach's alpha

            Medical educators attempt to create reliable and valid tests and questionnaires in order to enhance the accuracy of their assessment and evaluations. Validity and reliability are two fundamental elements in the evaluation of a measurement instrument. Instruments can be conventional knowledge, skill or attitude tests, clinical simulations or survey questionnaires. Instruments can measure concepts, psychomotor skills or affective values. Validity is concerned with the extent to which an instrument measures what it is intended to measure. Reliability is concerned with the ability of an instrument to measure consistently. 1 It should be noted that the reliability of an instrument is closely associated with its validity. An instrument cannot be valid unless it is reliable. However, the reliability of an instrument does not depend on its validity. 2 It is possible to objectively measure the reliability of an instrument and in this paper we explain the meaning of Cronbach’s alpha, the most widely used objective measure of reliability. Calculating alpha has become common practice in medical education research when multiple-item measures of a concept or construct are employed. This is because it is easier to use in comparison to other estimates (e.g. test-retest reliability estimates) 3 as it only requires one test administration. However, in spite of the widespread use of alpha in the literature the meaning, proper use and interpretation of alpha is not clearly understood. 2 , 4 , 5 We feel it is important, therefore, to further explain the underlying assumptions behind alpha in order to promote its more effective use. It should be emphasised that the purpose of this brief overview is just to focus on Cronbach’s alpha as an index of reliability. Alternative methods of measuring reliability based on other psychometric methods, such as generalisability theory or item-response theory, can be used for monitoring and improving the quality of OSCE examinations 6 - 10 , but will not be discussed here. What is Cronbach alpha? Alpha was developed by Lee Cronbach in 1951 11 to provide a measure of the internal consistency of a test or scale; it is expressed as a number between 0 and 1. Internal consistency describes the extent to which all the items in a test measure the same concept or construct and hence it is connected to the inter-relatedness of the items within the test. Internal consistency should be determined before a test can be employed for research or examination purposes to ensure validity. In addition, reliability estimates show the amount of measurement error in a test. Put simply, this interpretation of reliability is the correlation of test with itself. Squaring this correlation and subtracting from 1.00 produces the index of measurement error. For example, if a test has a reliability of 0.80, there is 0.36 error variance (random error) in the scores (0.80×0.80 = 0.64; 1.00 – 0.64 = 0.36). 12 As the estimate of reliability increases, the fraction of a test score that is attributable to error will decrease. 2 It is of note that the reliability of a test reveals the effect of measurement error on the observed score of a student cohort rather than on an individual student. To calculate the effect of measurement error on the observed score of an individual student, the standard error of measurement must be calculated (SEM). 13 If the items in a test are correlated to each other, the value of alpha is increased. However, a high coefficient alpha does not always mean a high degree of internal consistency. This is because alpha is also affected by the length of the test. If the test length is too short, the value of alpha is reduced. 2 , 14 Thus, to increase alpha, more related items testing the same concept should be added to the test. It is also important to note that alpha is a property of the scores on a test from a specific sample of testees. Therefore investigators should not rely on published alpha estimates and should measure alpha each time the test is administered. 14 Use of Cronbach’s alpha Improper use of alpha can lead to situations in which either a test or scale is wrongly discarded or the test is criticised for not generating trustworthy results. To avoid this situation an understanding of the associated concepts of internal consistency, homogeneity or unidimensionality can help to improve the use of alpha. Internal consistency is concerned with the interrelatedness of a sample of test items, whereas homogeneity refers to unidimensionality. A measure is said to be unidimensional if its items measure a single latent trait or construct. Internal consistency is a necessary but not sufficient condition for measuring homogeneity or unidimensionality in a sample of test items. 5 , 15 Fundamentally, the concept of reliability assumes that unidimensionality exists in a sample of test items 16 and if this assumption is violated it does cause a major underestimate of reliability. It has been well documented that a multidimensional test does not necessary have a lower alpha than a unidimensional test. Thus a more rigorous view of alpha is that it cannot simply be interpreted as an index for the internal consistency of a test. 5 , 15 , 17 Factor Analysis can be used to identify the dimensions of a test. 18 Other reliable techniques have been used and we encourage the reader to consult the paper “Applied Dimensionality and Test Structure Assessment with the START-M Mathematics Test” and to compare methods for assessing the dimensionality and underlying structure of a test. 19 Alpha, therefore, does not simply measure the unidimensionality of a set of items, but can be used to confirm whether or not a sample of items is actually unidimensional. 5 On the other hand if a test has more than one concept or construct, it may not make sense to report alpha for the test as a whole as the larger number of questions will inevitable inflate the value of alpha. In principle therefore, alpha should be calculated for each of the concepts rather than for the entire test or scale. 2 , 3 The implication for a summative examination containing heterogeneous, case-based questions is that alpha should be calculated for each case. More importantly, alpha is grounded in the ‘tau equivalent model’ which assumes that each test item measures the same latent trait on the same scale. Therefore, if multiple factors/traits underlie the items on a scale, as revealed by Factor Analysis, this assumption is violated and alpha underestimates the reliability of the test. 17 If the number of test items is too small it will also violate the assumption of tau-equivalence and will underestimate reliability. 20 When test items meet the assumptions of the tau-equivalent model, alpha approaches a better estimate of reliability. In practice, Cronbach’s alpha is a lower-bound estimate of reliability because heterogeneous test items would violate the assumptions of the tau-equivalent model. 5 If the calculation of “standardised item alpha” in SPSS is higher than “Cronbach’s alpha”, a further examination of the tau-equivalent measurement in the data may be essential. Numerical values of alpha As pointed out earlier, the number of test items, item inter-relatedness and dimensionality affect the value of alpha. 5 There are different reports about the acceptable values of alpha, ranging from 0.70 to 0.95. 2 , 21 , 22 A low value of alpha could be due to a low number of questions, poor inter-relatedness between items or heterogeneous constructs. For example if a low alpha is due to poor correlation between items then some should be revised or discarded. The easiest method to find them is to compute the correlation of each test item with the total score test; items with low correlations (approaching zero) are deleted. If alpha is too high it may suggest that some items are redundant as they are testing the same question but in a different guise. A maximum alpha value of 0.90 has been recommended. 14 Summary High quality tests are important to evaluate the reliability of data supplied in an examination or a research study. Alpha is a commonly employed index of test reliability. Alpha is affected by the test length and dimensionality. Alpha as an index of reliability should follow the assumptions of the essentially tau-equivalent approach. A low alpha appears if these assumptions are not meet. Alpha does not simply measure test homogeneity or unidimensionality as test reliability is a function of test length. A longer test increases the reliability of a test regardless of whether the test is homogenous or not. A high value of alpha (> 0.90) may suggest redundancies and show that the test length should be shortened. Conclusions Alpha is an important concept in the evaluation of assessments and questionnaires. It is mandatory that assessors and researchers should estimate this quantity to add validity and accuracy to the interpretation of their data. Nevertheless alpha has frequently been reported in an uncritical way and without adequate understanding and interpretation. In this editorial we have attempted to explain the assumptions underlying the calculation of alpha, the factors influencing its magnitude and the ways in which its value can be interpreted. We hope that investigators in future will be more critical when reporting values of alpha in their studies.
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              ISOQOL recommends minimum standards for patient-reported outcome measures used in patient-centered outcomes and comparative effectiveness research.

              An essential aspect of patient-centered outcomes research (PCOR) and comparative effectiveness research (CER) is the integration of patient perspectives and experiences with clinical data to evaluate interventions. Thus, PCOR and CER require capturing patient-reported outcome (PRO) data appropriately to inform research, healthcare delivery, and policy. This initiative's goal was to identify minimum standards for the design and selection of a PRO measure for use in PCOR and CER. We performed a literature review to find existing guidelines for the selection of PRO measures. We also conducted an online survey of the International Society for Quality of Life Research (ISOQOL) membership to solicit input on PRO standards. A standard was designated as "recommended" when >50 % respondents endorsed it as "required as a minimum standard." The literature review identified 387 articles. Survey response rate was 120 of 506 ISOQOL members. The respondents had an average of 15 years experience in PRO research, and 89 % felt competent or very competent providing feedback. Final recommendations for PRO measure standards included: documentation of the conceptual and measurement model; evidence for reliability, validity (content validity, construct validity, responsiveness); interpretability of scores; quality translation, and acceptable patient and investigator burden. The development of these minimum measurement standards is intended to promote the appropriate use of PRO measures to inform PCOR and CER, which in turn can improve the effectiveness and efficiency of healthcare delivery. A next step is to expand these minimum standards to identify best practices for selecting decision-relevant PRO measures.
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                Author and article information

                Journal
                Endocr Connect
                Endocr Connect
                EC
                Endocrine Connections
                Bioscientifica Ltd (Bristol )
                2049-3614
                06 August 2021
                01 September 2021
                : 10
                : 9
                : 1065-1072
                Affiliations
                [1 ]University Hospital for Visceral Surgery, Pius-Hospital Oldenburg, Carl von Ossietzky University, Oldenburg , Germany
                Author notes
                Correspondence should be addressed to V Uslar: verena.uslar@ 123456uol.de
                Author information
                http://orcid.org/0000-0003-3252-2076
                Article
                EC-21-0114
                10.1530/EC-21-0114
                8428020
                34355699
                3546c890-a4ac-4b02-a377-4af4155b19ea
                © The authors

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 19 July 2021
                : 06 August 2021
                Categories
                Research

                quality of life,benign thyroid disease,euroqol 5d-5l,thypro-39de,questionnaire validation

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