Dataset Information

Inter-rater reliability of AMSTAR is dependent on the pair of reviewers.

ABSTRACT:

Background

Inter-rater reliability (IRR) is mainly assessed based on only two reviewers of unknown expertise. The aim of this paper is to examine differences in the IRR of the Assessment of Multiple Systematic Reviews (AMSTAR) and R(evised)-AMSTAR depending on the pair of reviewers.

Methods

Five reviewers independently applied AMSTAR and R-AMSTAR to 16 systematic reviews (eight Cochrane reviews and eight non-Cochrane reviews) from the field of occupational health. Responses were dichotomized and reliability measures were calculated by applying Holsti's method (r) and Cohen's kappa (?) to all potential pairs of reviewers. Given that five reviewers participated in the study, there were ten possible pairs of reviewers.

Results

Inter-rater reliability varied for AMSTAR between r = 0.82 and r = 0.98 (median r = 0.88) using Holsti's method and ? = 0.41 and ? = 0.69 (median ? = 0.52) using Cohen's kappa and for R-AMSTAR between r = 0.77 and r = 0.89 (median r = 0.82) and ? = 0.32 and ? = 0.67 (median ? = 0.45) depending on the pair of reviewers. The same pair of reviewers yielded the highest IRR for both instruments. Pairwise Cohen's kappa reliability measures showed a moderate correlation between AMSTAR and R-AMSTAR (Spearman's ? =0.50). The mean inter-rater reliability for AMSTAR was highest for item 1 (? = 1.00) and item 5 (? = 0.78), while lowest values were found for items 3, 8, 9 and 11, which showed only fair agreement.

Conclusions

Inter-rater reliability varies widely depending on the pair of reviewers. There may be some shortcomings associated with conducting reliability studies with only two reviewers. Further studies should include additional reviewers and should probably also take account of their level of expertise.

SUBMITTER: Pieper D

PROVIDER: S-EPMC5504630 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Inter-rater reliability of AMSTAR is dependent on the pair of reviewers.

Pieper Dawid D Jacobs Anja A Weikert Beate B Fishta Alba A Wegewitz Uta U

BMC medical research methodology 20170711 1

<h4>Background</h4>Inter-rater reliability (IRR) is mainly assessed based on only two reviewers of unknown expertise. The aim of this paper is to examine differences in the IRR of the Assessment of Multiple Systematic Reviews (AMSTAR) and R(evised)-AMSTAR depending on the pair of reviewers.<h4>Methods</h4>Five reviewers independently applied AMSTAR and R-AMSTAR to 16 systematic reviews (eight Cochrane reviews and eight non-Cochrane reviews) from the field of occupational health. Responses were d ...[more]

PMID: 28693497

Similar Datasets

Project description:Background: There has been a groundswell of national support for transparent tracking and dissemination of PhD career outcomes. In 2017, individuals from multiple institutions and professional organizations met to create the Unified Career Outcomes Taxonomy (UCOT 2017), a three-tiered taxonomy to help institutions uniformly classify career outcomes of PhD graduates. Early adopters of UCOT 2017, noted ambiguity in some categories of the career taxonomy, raising questions about its consistent application within and across institutions. Methods: To test and evaluate the consistency of UCOT 2017, we calculated inter-rater reliability across two rounds of iterative refinement of the career taxonomy, classifying over 800 PhD alumni records via nine coders. Results: We identified areas of discordance in the taxonomy, and progressively refined UCOT 2017 and an accompanying Guidance Document to improve inter-rater reliability across all three tiers of the career taxonomy. However, differing interpretations of the classifications, especially for faculty classifications in the third tier, resulted in continued discordance among the coders. We addressed this discordance with clarifying language in the Guidance Document, and proposed the addition of a flag system for identification of the title, rank, and prefix of faculty members. This labeling system provides the additional benefit of highlighting the granularity and the intersectionality of faculty job functions, while maintaining the ability to sort by - and report data on - faculty and postdoctoral trainee roles, as is required by some national and federal reporting guidelines. We provide specific crosswalk guidance for how a user may choose to incorporate our suggestions while maintaining the ability to report in accordance with UCOT 2017. Conclusions: Our findings underscore the importance of detailed guidance documents, coder training, and periodic collaborative review of career outcomes taxonomies as PhD careers evolve in the global workforce. Implications for coder-training and use of novice coders are also discussed.

Project description:PurposeFirst, to evaluate inter-rater reliability when human raters estimate the reading performance of visually impaired individuals using the MNREAD acuity chart. Second, to evaluate the agreement between computer-based scoring algorithms and compare them with human rating.MethodsReading performance was measured for 101 individuals with low vision, using the Portuguese version of the MNREAD test. Seven raters estimated the maximum reading speed (MRS) and critical print size (CPS) of each individual MNREAD curve. MRS and CPS were also calculated automatically for each curve using two different algorithms: the original standard deviation method (SDev) and a non-linear mixed effects (NLME) modeling. Intra-class correlation coefficients (ICC) were used to estimate absolute agreement between raters and/or algorithms.ResultsAbsolute agreement between raters was 'excellent' for MRS (ICC = 0.97; 95%CI [0.96, 0.98]) and 'moderate' to 'good' for CPS (ICC = 0.77; 95%CI [0.69, 0.83]). For CPS, inter-rater reliability was poorer among less experienced raters (ICC = 0.70; 95%CI [0.57, 0.80]) when compared to experienced ones (ICC = 0.82; 95%CI [0.76, 0.88]). Absolute agreement between the two algorithms was 'excellent' for MRS (ICC = 0.96; 95%CI [0.91, 0.98]). For CPS, the best possible agreement was found for CPS defined as the print size sustaining 80% of MRS (ICC = 0.77; 95%CI [0.68, 0.84]). Absolute agreement between raters and automated methods was 'excellent' for MRS (ICC = 0.96; 95% CI [0.88, 0.98] for SDev; ICC = 0.97; 95% CI [0.95, 0.98] for NLME). For CPS, absolute agreement between raters and SDev ranged from 'poor' to 'good' (ICC = 0.66; 95% CI [0.3, 0.80]), while agreement between raters and NLME was 'good' (ICC = 0.83; 95% CI [0.76, 0.88]).ConclusionFor MRS, inter-rater reliability is excellent, even considering the possibility of noisy and/or incomplete data collected in low-vision individuals. For CPS, inter-rater reliability is lower. This may be problematic, for instance in the context of multisite investigations or follow-up examinations. The NLME method showed better agreement with the raters than the SDev method for both reading parameters. Setting up consensual guidelines to deal with ambiguous curves may help improve reliability. While the exact definition of CPS should be chosen on a case-by-case basis depending on the clinician or researcher's motivations, evidence suggests that estimating CPS as the smallest print size sustaining about 80% of MRS would increase inter-rater reliability.

Project description:PurposeThere is limited knowledge on the reliability of risk of bias (ROB) tools for assessing internal validity in systematic reviews of exposure and frequency studies. We aimed to identify and then compare the inter-rater reliability (IRR) of six commonly used tools for frequency (Loney scale, Gyorkos checklist, American Academy of Neurology [AAN] tool) and exposure (Newcastle-Ottawa scale, SIGN50 checklist, AAN tool) studies.MethodsSix raters independently assessed the ROB of 30 frequency and 30 exposure studies using the three respective ROB tools. Articles were rated as low, intermediate, or high ROB. We calculated an intraclass correlation coefficient (ICC) for each tool and category of ROB tool. We compared the IRR between ROB tools and tool type by inspection of overlapping ICC 95% CIs and by comparing their coefficients after transformation to Fisher's Z values. We assessed the criterion validity of the AAN ROB tools by calculating an ICC for each rater in comparison with the original ratings from the AAN.ResultsAll individual ROB tools had an IRR in the substantial range or higher (ICC point estimates between 0.61 and 0.80). The IRR was almost perfect (ICC point estimate > 0.80) for the AAN frequency tool and the SIGN50 checklist. All tools were comparable in IRR, except for the AAN frequency tool which had a significantly higher ICC than the Gyorkos checklist (p = 0.021) and trended towards a higher ICC when compared to the Loney scale (p = 0.085). When examined by category of ROB tool, scales, and checklists had a substantial IRR, whereas the AAN tools had an almost perfect IRR. For the criterion validity of the AAN ROB tools, the average agreement between our raters and the original AAN ratings was moderate.ConclusionAll tools had substantial IRRs except for the AAN frequency tool and the SIGN50 checklist, which both had an almost perfect IRR. The AAN ROB tools were the only category of ROB tools to demonstrate an almost perfect IRR. This category of ROB tools had fewer and simpler criteria. Overall, parsimonious tools with clear instructions, such as those from the AAN, may provide more reliable ROB assessments.

Project description:ObjectivesTo investigate the intra- and inter-rater reliability of the total radiomics quality score (RQS) and the reproducibility of individual RQS items' score in a large multireader study.MethodsNine raters with different backgrounds were randomly assigned to three groups based on their proficiency with RQS utilization: Groups 1 and 2 represented the inter-rater reliability groups with or without prior training in RQS, respectively; group 3 represented the intra-rater reliability group. Thirty-three original research papers on radiomics were evaluated by raters of groups 1 and 2. Of the 33 papers, 17 were evaluated twice with an interval of 1 month by raters of group 3. Intraclass coefficient (ICC) for continuous variables, and Fleiss' and Cohen's kappa (k) statistics for categorical variables were used.ResultsThe inter-rater reliability was poor to moderate for total RQS (ICC 0.30-055, p < 0.001) and very low to good for item's reproducibility (k - 0.12 to 0.75) within groups 1 and 2 for both inexperienced and experienced raters. The intra-rater reliability for total RQS was moderate for the less experienced rater (ICC 0.522, p = 0.009), whereas experienced raters showed excellent intra-rater reliability (ICC 0.91-0.99, p < 0.001) between the first and second read. Intra-rater reliability on RQS items' score reproducibility was higher and most of the items had moderate to good intra-rater reliability (k - 0.40 to 1).ConclusionsReproducibility of the total RQS and the score of individual RQS items is low. There is a need for a robust and reproducible assessment method to assess the quality of radiomics research.Clinical relevance statementThere is a need for reproducible scoring systems to improve quality of radiomics research and consecutively close the translational gap between research and clinical implementation.Key points• Radiomics quality score has been widely used for the evaluation of radiomics studies. • Although the intra-rater reliability was moderate to excellent, intra- and inter-rater reliability of total score and point-by-point scores were low with radiomics quality score. • A robust, easy-to-use scoring system is needed for the evaluation of radiomics research.

Dataset Information

Inter-rater reliability of AMSTAR is dependent on the pair of reviewers.

Background

Methods

Results

Conclusions

Publications

Inter-rater reliability of AMSTAR is dependent on the pair of reviewers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets