Validity And Inter Rater Reliability Testing Of Quality Assessment Instruments

The internal validity of a study reflects the extent to which the design and conduct of the study have prevented bias(es). One of the key steps in a systematic review is assessment of a study's internal validity, or potential for bias. This assessment serves to: (1) identify the strengths and limitations of the included studies; (2) investigate, and potentially explain heterogeneity in findings across different studies included in a systematic review; and (3) grade the strength of evidence for a given question. The risk of bias assessment directly informs one of four key domains considered when assessing the strength of evidence. With the increase in the number of published systematic reviews and development of systematic review methodology over the past 15 years, close attention has been paid to the methods for assessing internal validity. Until recently this has been referred to as “quality assessment” or “assessment of methodological quality.” In this context “quality” refers to “the confidence that the trial design, conduct, and analysis has minimized or avoided biases in its treatment comparisons.” To facilitate the assessment of methodological quality, a plethora of tools has emerged. Some of these tools were developed for specific study designs (e.g., randomized controlled trials (RCTs), cohort studies, case-control studies), while others were intended to be applied to a range of designs. The tools often incorporate characteristics that may be associated with bias; however, many tools also contain elements related to reporting (e.g., was the study population described) and design (e.g., was a sample size calculation performed) that are not related to bias. The Cochrane Collaboration recently developed a tool to assess the potential risk of bias in RCTs. The Risk of Bias (ROB) tool was developed to address some of the shortcomings of existing quality assessment instruments, including over-reliance on reporting rather than methods. Several systematic reviews have catalogued and critiqued the numerous tools available to assess methodological quality, or risk of bias of primary studies. In summary, few existing tools have undergone extensive inter-rater reliability or validity testing. Moreover, the focus of much of the tool development or testing that has been done has been on criterion or face validity. Therefore it is unknown whether, or to what extent, the summary assessments based on these tools differentiate between studies with biased and unbiased results (i.e., studies that may over- or underestimate treatment effects). There is a clear need for inter-rater reliability testing of different tools in order to enhance consistency in their application and interpretation across different systematic reviews. Further, validity testing is essential to ensure that the tools being used can identify studies with biased results. Finally, there is a need to determine inter-rater reliability and validity in order to support the uptake and use of individual tools that are recommended by the systematic review community, and specifically the ROB tool within the Evidence-based Practice Center (EPC) Program. In this project we focused on two tools that are commonly used in systematic reviews. The Cochrane ROB tool was designed for RCTs and is the instrument recommended by The Cochrane Collaboration for use in systematic reviews of RCTs. The Newcastle-Ottawa Scale is commonly used for nonrandomized studies, specifically cohort and case-control studies.

The third edition of this book was very well received by researchers working in many different fields of research. The use of that text also gave these researchers the opportunity to raise questions, and express additional needs for materials on techniques poorly covered in the literature. For example, when designing an inter-rater reliability study, many researchers wanted to know how to determine the optimal number of raters and the optimal number of subjects that should participate in the experiment. Also, very little space in the literature has been devoted to the notion of intra-rater reliability, particularly for quantitative measurements. The fourth edition of this text addresses those needs, in addition to further refining the presentation of the material already covered in the third edition. Features of the Fourth Edition include: New material on sample size calculations for chance-corrected agreement coefficients, as well as for intraclass correlation coefficients. The researcher will be able to determine the optimal number raters, subjects, and trials per subject.The chapter entitled “Benchmarking Inter-Rater Reliability Coefficients” has been entirely rewritten.The introductory chapter has been substantially expanded to explore possible definitions of the notion of inter-rater reliability.All chapters have been revised to a large extent to improve their readability.

How can we make sense of make sense of the deluge of information in the digital age? The new science of Quantitative Ethnography dissolves the boundaries between quantitative and qualitative research to give researchers tools for studying the human side of big data: to understand not just what data says, but what it tells us about the people who created it. Thoughtful, literate, and humane, Quantitative Ethnography integrates data-mining, discourse analysis, psychology, statistics, and ethnography into a brand-new science for understanding what people do and why they do it. Packed with anecdotes, stories, and clear explanations of complex ideas, Quantitative Ethnography is an engaging introduction to research methods for students, an introduction to data science for qualitative researchers, and an introduction to the humanities for statisticians--but also a compelling philosophical and intellectual journey for anyone who wants to understand learning, culture and behavior in the age of big data.

Although ability testing has been an American preoccupation since the 1920s, comparatively little systematic attention has been paid to understanding and measuring the kinds of human performance that tests are commonly used to predictâ€"such as success at school or work. Now, a sustained, large-scale effort has been made to develop measures that are very close to actual performance on the job. The four military services have carried out an ambitious study, called the Joint-Service Job Performance Measurement/Enlistment Standards (JPM) Project, that brings new sophistication to the measurement of performance in work settings. Volume 1 analyzes the JPM experience in the context of human resource management policy in the military. Beginning with a historical overview of the criterion problem, it looks closely at substantive and methodological issues in criterion research suggested by the project: the development of performance measures; sampling, logistical, and standardization problems; evaluating the reliability and content representativeness of performance measures; and the relationship between predictor scores and performance measuresâ€"valuable information that can also be useful in the civilian workplace.

The Infant Motor Profile is a practical manual on a new, evidence-based method to assess infant motor behaviour. Not only looking at what milestones the infant has reached, but also paying attention to the quality of motor behaviour – how the infant moves – this text provides professionals involved in the care of infants at risk of developmental disorders with information on five domains of motor behaviour: variation, adaptability, symmetry, fluency, and performance. Backed up by extensive, up-to-date research, it includes percentile curves so that professionals can easily interpret the infants’ scores. The profile created from the assessment informs about the infant’s current condition and their risk of developmental disorders, as well as providing suggestions for early intervention, tailored to the strengths and limitations of the infant. Used over time, it can be an excellent instrument to monitor the infant’s developmental progress. Illustrated with numerous figures and accompanied by a website hosting over 100 video clips, this text is an essential read for professionals in developmental paediatrics, including paediatric physiotherapists, occupational therapists, developmental paediatricians, neuropaediatricians, and paediatric physiatrists.

Whether the concept being studied is job satisfaction, self-efficacy, or student motivation, values and attitudes--affective characteristics--provide crucial keys to how individuals think, learn, and behave. And not surprisingly, as measurement of these traits gains importance in the academic and corporate worlds, there is an ongoing need for valid, scientifically sound instruments. For those involved in creating self-report measures, the completely updated Third Edition of Instrument Development in the Affective Domain balances the art and science of instrument development and evaluation, covering both its conceptual and technical aspects. The book is written to be accessible with the minimum of statistical background, and reviews affective constructs from a measurement standpoint. Examples are drawn from academic and business settings for insights into design as well as the relevance of affective measures to educational and corporate testing. This systematic analysis of all phases of the design process includes: Measurement, scaling, and item-writing techniques. Validity issues: collecting evidence based on instrument content. Testing the internal structure of an instrument: exploratory and confirmatory factor analyses. Measurement invariance and other advanced methods for examining internal structure. Strengthening the validity argument: relationships to external variables. Addressing reliability issues. As a graduate course between covers and an invaluable professional tool, the Third Edition of Instrument Design in the Affective Domain will be hailed as a bedrock resource by researchers and students in psychology, education, and the social sciences, as well as human resource professionals in the corporate world.

Focusing on the use of technology in survey research, this book integrates both theory and application and covers important elements of survey research including survey design, implementation and continuing data management.