It is crucial to select outcomes in clinical trials. Appropriate outcomes can improve value and significance of trials and reduce the cost of investment. This paper describes how to develop core outcome sets and core outcome measurement instrument sets with the theory of mixed methods research, so as to standardize the choice of outcomes and outcome measurement instruments in clinical trials.
ObjectivesTo understand the quantitative measurement tools for active aging and compare the index construction, applicability and application of different tools domestically and abroad, so as to provide a scientific basis for the formulation and improvement of localized measurement tools for active aging.MethodsWe performed electronical searches on PubMed, Web of Science, Elsevier, CNKI, WanFang Data, VIP, and websites of WHO, European Commission, United Nations Economic Commission for Europe from April 2002 to November 2019. Two reviewers independently screened literature and extracted data according to inclusion and exclusion criteria, and conducted a qualitative analysis and comparison of the obtained measurement tools.ResultsA total of 36 researches were included, which involved 9 original active aging quantitative measurement tools. Specifically, 3 were from Thailand, 2 were from China, 1 was from the European Union, Russia, Australia and Finland, respectively. There were 2 to 3 dimensions of the tools, 3 to 10 items of primary measurement targets, and 11 to 177 items of measurement indicators. The construction of the dimension and first-level measurement goals were mainly based on the three pillars of health, participation, and security which composed WHO’s policy framework. The indicators of tools had measured the health, participation, and security targets except for the AAQ-CHN (2012) and AAL-Thai (2016) tools. Five age-specific indicators of the use of electronic information technology equipment, voluntary services, participation in political activities, access to health care services, and lifelong learning habits appeared in the EU tool. The AAI-EU's empirical applications and related 20 studies had been published mainly in Europe, Asia, and the Americas. AAI-Thai (2006) and AAI-Thai (2014) were used in empirical researches in Asia and China, respectively, and the 3rd and 4th studies were published.ConclusionsThe indicators' design of AAI-EU (2012) has the most contemporary characteristics, the most confirmatory research and widest application. The development of Chinese localized quantitative measurement tools should take advantage of the EU and other representative measurement tools.
The COSMIN-RoB checklist includes three sections with a total of 10 boxes, which is used to evaluate risk of bias of studies on content validity, internal structure, and other measurement properties. COSMIN classifies reliability, measurement error, criteria validity, hypothesis testing for construct validity, and responsiveness as other measurement properties, which primarily focus on the quality of the (sub)scale as a whole, rather than on the item level. Among the five measurement properties, reliability, measurement error and criteria validity are the most widely used in the studies. Therefore, this paper aims to interpret COSMIN-RoB checklist with examples to guide researchers to evaluate the risk of bias of the studies on reliability, measurement error and criteria validity of PROMs.
Measurement properties studies of patient-reported outcome measures (PROMs) aims to validate the measurement properties of PROMs. In the process of designing and statistical analysis of these measurement properties studies, bias will occur if there are any defects, which will affect the quality of PROMs. Therefore, the COSMIN (consensus-based standards for the selection of health measurement instruments) team has developed the COSMIN risk of bias (COSMIN-RoB) checklist to evaluate risk of bias of studies on measurement properties of PROMs. The checklist can be used to develop systematic reviews of PROMs measurement properties, and for PROMs developers, it can also be used to guide the research design in the measurement tool development process for reducing bias. At present, similar assessment tools are lacking in China. Therefore, this article aims to introduce the primary contents of COSMIN-RoB checklist and to interpret how to evaluate risk of bias of the internal structure studies of PROMs with examples.
ObjectiveTo systematically review the research on pediatric treatment satisfaction of medication (TS-M). MethodsThe PubMed, Embase, Cochrane Library, CBM, WanFang Data, VIP, CNKI databases and medical scale websites were electronically searched to collect studies on pediatric TS-M from inception to November 2022. Two reviewers independently screened literature, and extracted data. Using descriptive analysis, we comprehensively reviewed the TS-M assessment tool selected for the studies of children. We evaluated the methodological quality and measurement properties of existing TS-M scales for children using the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) assessment criteria. ResultsA total of 157 studies were included, including 150 pediatric studies using TS-M evaluation tools and 7 studies on the development and validation of TS-M scales for children, covering 7 specific TS-M scales for children. Our review revealed that 67.3% of the pediatric studies used unvalidated self-administered TS-M questionnaires or interviews, 24.7% used adult TS-M scales, and only 6.0% used two pediatric-specific TS-M scales. The results of the quality assessment indicated that the development quality of existing TS-M pediatric scales was considered "doubtful" or "inadequate", and the internal consistency was "sufficient" but the structural validity was probably "uncertain". High-quality research on the content validity, test-retest reliability and construct validity of the pediatric TS-M scale was still lacking. ConclusionCurrently, the use of TS-M evaluation tools in pediatric studies has irrationalities: over 90% of pediatric studies use self-made questionnaires or adult scales to evaluate children's TS-M; and the existing pediatric TS-M scales globally have narrow applications, questionable development quality, and lack some measurement performance studies. Pediatric TS-M scales with a wide range of applications are lacking.