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.
The COSMIN community updated the COSMIN-RoB checklist on reliability and measurement error in 2021. The updated checklist can be applied to the assessment of all types of outcome measurement studies, including clinician-reported outcome measures (ClinPOMs), performance-basd outcome measurement instruments (PerFOMs), and laboratory values. In order to help readers better understand and apply the updated COSMIN-RoB checklist and provide methodological references for conducting systematic reviews of ClinPOMs, PerFOMs and laboratory values, this paper aimed to interpret the updated COSMIN-RoB checklist on reliability and measurement error studies.
ObjectiveTo construct a framework and functional items of a scientific research assistant tool for conducting systematic review for patient-reported outcome measures. MethodsBased on the research foundation and work experience of the system evaluation of two patient-reported outcome measures systematic reviews carried out by the research group in the early stage, the framework and function system of scientific research aid tool was initially constructed, and two rounds of correspondence were carried out by Dephi expert consultation method. ResultsThe effective recovery rates of the two rounds of expert consultation questionnaires were 90% and 100%, the expert authority coefficient was 0.839, and the compatibility coefficients of suitability and importance were 0.105 and 0.177, respectively. The final the patient-reported outcome measures tool system evaluation scientific research aid tool system consists of 7 frames and 31 items. ConclusionThis study has developed a scientific and comprehensive set of functional criteria for research-assistant tools that systematically review patient-reported outcome measures based on the COSMIN methodology and it lays the foundation for subsequent tool research and development.
ObjectiveThis study aimed to systematically review the quality of psychometric properties and methodological quality of the Chinese versions of fear of falling assessment tools for the elderly, providing evidence-based guidance for medical staff in selecting high-quality assessment tools. MethodsWe systematically searched CNKI, WanFang Data, VIP, CBM, PubMed, Embase, and Web of Science databases for studies related to the evaluation of psychometric properties and methodological quality of fear of falling assessment tools for the elderly. The search spanned from the inception of the databases to January 19, 2024. Two researchers independently screened literature and extracted data using the consensus-based standards for the selection of health measurement instruments. The COSMIN risk of bias checklist and quality criteria were employed to evaluate instrument measurement characteristics and formulate final recommendations. ResultsFifteen studies involving 11 Chinese versions of fear of falling assessment tools for the elderly were included. None of the studies reported measurement error, cross-cultural validity, or responsiveness. Due to insufficient or uncertain content validity and low or below-quality evidence, all 11 tools received a recommendation of level B. ConclusionAmong the 11 instruments, the Chinese version of IFES demonstrates the most balanced measurement characteristics, along with good reliability and validity. However, further verification of other measurement characteristics of this instrument is warranted.
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.