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Inter-rater Reliability Assessment of ASPECT-R: (A Study Pragmatic-Explanatory Characterization Tool-Rating).

Innovations in clinical neuroscience(2016)

Cited 29|Views3
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Abstract
OBJECTIVE:The increasing importance of real-world data for clinical and policy decision making is driving a need for close attention to the pragmatic versus explanatory features of trial designs. ASPECT-R (A Study Pragmatic-Explanatory Characterization Tool-Rating) is an instrument informed by the PRECIS tool, which was developed to assist researchers in designing trials that are more pragmatic or explanatory. ASPECT-R refined the PRECIS domains and includes a detailed anchored rating system. This analysis established the inter-rater reliability of ASPECT-R. DESIGN:Nine raters (identified from a convenience sample of persons knowledgeable about psychiatry clinical research/study design) received ASPECT-R training materials and 12 study publications. Selected studies assessed antipsychotic treatment in schizophrenia, were published in peer-reviewed journals, and represented a range of studies across a pragmatic-explanatory continuum as determined by authors (CB/LA). After completing training, raters reviewed the 12 studies and rated the study domains using ASPECT-R. Intraclass correlation coefficients were estimated for total and domain scores. Qualitative ratings then were assigned to describe the inter-rater reliability. RESULTS:ASPECT-R scores for the 12 studies were completed by seven raters. The ASPECT-R total score intraclass correlation coefficient was 0.87, corresponding to an excellent inter-rater reliability. Domain intraclass correlation coefficients ranged from 0.85 to 0.31, corresponding to excellent to poor inter-rater reliability. CONCLUSION:The inter-rater reliability of the ASPECT-R total score was excellent, with excellent to good inter-rater reliability for most domains. The fair to poor inter-rater reliability for two domains may reflect a need for improved domain definition, anchoring, or training materials. ASPECT-R can be used to help understand the pragmaticexplanatory nature of completed or planned trials.
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