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This chapter addresses diagnostic studies, which evaluate the performance of clinical tests and tools used to detect disease. The concepts of sensitivity, specificity, positive predictive value, and negative predictive value are explained in detail, highlighting how these metrics guide clinicians in interpreting test results. The role of prevalence in influencing predictive values is emphasised, underlining the need to consider population context when applying diagnostic tools. Receiver operating characteristic (ROC) curves are introduced as a method to assess test performance across varying thresholds, enabling identification of optimal cut-off points. The chapter also explores likelihood ratios, which integrate sensitivity and specificity into a single measure to support diagnostic decision-making. Strengths of diagnostic studies include their direct clinical relevance and utility in evaluating new technologies or biomarkers. Limitations include potential spectrum bias, verification bias, and challenges in defining an appropriate gold standard. Examples from infectious disease testing and mental health screening illustrate the practical implications of study design and interpretation. The chapter concludes by positioning diagnostic research as critical for improving clinical decision-making, resource allocation, and patient outcomes. This chapter maps to syllabus sections 3.2.5–3.2.8, which cover diagnostic accuracy measures including sensitivity, specificity, predictive values, likelihood ratios, and ROC curves.
This chapter explores the issue of validity in quantitative research. It covers various types of validity, such as face, content, construct, criterion, and predictive validity, and explains how each can be measured. The chapter also discusses internal and external validity, emphasizing their importance and potential threats, including selection bias, maturation, and history effects. You will learn effective strategies for mitigating these threats to ensure the robustness of your research. Key techniques such as careful sampling, appropriate recruitment procedures, and the use of statistical methods are explored to help you establish and maintain study validity. By the end, you will be equipped to design and conduct rigorous and valid research in applied linguistics.
Otology training solely using cadavers is challenging because of scarcity and high costs. The use of additive manufacturing technology is a promising alternative. This study aimed to qualitatively validate new additive manufacturing temporal bone specimens for their realism and ability to train surgical skills.
Methods
Three additive manufacturing models generated using cadaveric temporal bones were evaluated. Three otologists with experience as trainers dissected and evaluated each specimen.
Results
The additive manufacturing specimens scored an average of 4.26 ± 0.72 (out of 5) points and received positive feedback. The agreement between the three expert raters was high (intra-class correlation coefficient of 0.745).
Conclusion
The results suggested that the additive manufacturing temporal bones were able to faithfully reproduce a training experience similar to that on cadaveric temporal bones. Further studies that investigate the effectiveness of these specimens in training surgical skills are needed before integrating them into surgical training curricula.
The Economic Freedom of the World report measures five dimensions of economic freedom, one of them being Sound Money. Compared to where it had been in decades for most of the West, inflation skyrocketed in 2021. Yet the indicator which measures inflation in the most recent year barely budged due to how it is specified and parameterized. This paper explores potential improvements on the methodology, although ultimately only modest improvements are achieved over simply changing the value of inflation that corresponds to zero (the lowest index score) in the simplest linear specification.
“Ecological validity” (EV) is classically defined as test’s ability to predict real-world functioning, either alone or together with test’s similarity to real-world tasks. In neuropsychological literature on assessment of executive functions (EF), EV is conceptualized inconsistently, leading to misconceptions about the utility of tests. The goal of this systematic review was to examine how EV is conceptualized in studies of EF tests described as ecologically valid.
Method:
MEDLINE and PsychINFO Databases were searched. PRISMA guidelines were observed. After applying inclusion and exclusion criteria, this search yielded 90 articles. Deductive content analysis was employed to determine how the term EV was used.
Results:
About 1/3 of the studies conceptualized EV as the test’s ability to predict functional outcomes, 1/3 as both the ability to predict functional outcome and similarity to real-world tasks, and 1/3 were either unclear about the meaning of the term or relied on notions unrelated to classical definitions (e.g., similarity to real-world tasks alone, association with other tests, or the ability to discriminate between populations).
Conclusions:
Conceptualizations of the term EV in literature on EF assessment vary grossly, subsuming the notions of criterion, construct, and face validity, as well as sensitivity/specificity. Such inconsistency makes it difficult to interpret clinical utility of tests that are described as ecologically valid. We call on the field to require that, at minimum, the term EV be clearly defined in all publications, or replaced with more concrete terminology (e.g., criterion validity).
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