China
Africa
Explore chapters and articles related to this topic
Practical Considerations for Interpreting Change Following Brain Injury
Published in Mark R. Lovell, Ruben J. Echemendia, Jeffrey T. Barth, Michael W. Collins, Traumatic Brain Injury in Sports, 2020
Grant L. Iverson, Michael Gaetz
When interpreting this inventory in young athletes, the first step is to determine whether the endorsement of symptoms is normal or unusual. In this sample of 200 young men, their average score was 10.5 (SD = 11.6) and their median score was 7. Scores falling between 1 and 14 are normal, whereas scores of 25 or greater are very high (see Table 18.11). The percentile rank ranges are based on the natural distribution of total scores for the 200 athletes.
Norms and Scores
Published in Lucy Jane Miller, Developing Norm-Referenced Standardized Tests, 2020
A percentile rank indicates an individual child’s position relative to the standardization sample. It represents the percentage of the standardization group who scored at or below a given raw score.2,3,4,9 For example, if a raw score of 33 indicates a percentile rank of 80, it means that 80% of the group members had raw scores of 33 or less. Conversely, a student with a score of 33 scored as well as or better than 80% of the normative sample on the test.
Grading, reporting, and standard setting
Published in Claudio Violato, Assessing Competence in Medicine and Other Health Professions, 2018
Generally, the scores that are reported and interpreted are percentile ranks, T-scores and z-scores. The percentile rank is based on a reference group within age or year or a cohort. Criterion-referenced systems are based on absolute standards as we have seen. Together these two systems provide substantial information.
The Ability of Patients to Correctly Identify Their Hospitalist on a Patient Satisfaction Survey and the Impact of This Factor on Hospitalist Scores
Published in Hospital Topics, 2023
Michele C. Ryan, William J. Ryan, Gabriela I. Castro, Mickel Khlat, James G. Ryan
We also found significant changes in the evaluation metrics when patient who correctly identified their hospitalist were compared with patient who could not. Patients who identified their physician by name were more likely to give a top score and gave significantly higher scores on physician introduction and communication skills. The exclusion of “unidentified scores” provided modest differences in the raw score of hospitalist performance due to the narrow range of cumulative scores. However, when the results are calculated as a percentile rank the results provided dramatically different ranks. Our study adds to the existing body of literature that supports the use of patient satisfaction surveys in order to improve patients’ perception of their care, however, it also raises concerns about the ability to correctly attribute these ratings to a single provider and the use of percentile ranks as a scoring metric.
Derivation of norms for the Dutch version of the Edinburgh cognitive and behavioral ALS screen
Published in Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 2019
Leonhard A. Bakker, Carin D. Schröder, Lauriane A. Spreij, Marianne Verhaegen, Joke De Vocht, Philip Van Damme, Jan H. Veldink, Johanna M.A. Visser-Meily, Leonard H. van den Berg, Tanja C.W. Nijboer, Michael A. van Es
Given that the ECAS scores were negatively skewed, norm tables were constructed to convert scores to percentiles. Since level of education and age were correlated to performance on the ECAS, normative data should be stratified accordingly. Although the results of the multiple linear regression indicated that sex is associated with the performance on the ECAS, the derived normative data were not stratified by sex to avoid small sample strata in a stratified norm table. Stratification of the normative sample can be avoided when percentiles are derived using the residuals of the multiple linear regression model. Moreover, this method allows for a more precise estimation of the effect of age, as it is treated as a continuous variable rather than a categorical variable. The provided percentiles are the recommended metric for the clinical classification of patients with ALS. Percentile rank scores, however, are not feasible for use in studies that aim to compare groups of patients or compare scores over time, since percentiles are not suitable for further statistical analyses (26).
For single-source feedback, including the mean and percentile rank on feedback by nursing staff does not improve physician-nurse communication amongst anesthesiologists as compared to the raw score alone
Published in Journal of Communication in Healthcare, 2018
Collin Clarke, Bradley Rostas, George Nicolauo
There are, however, important considerations when assessing the ultimate value of mean score and percentile rank within feedback contexts. The importance of perceived rater credibility on feedback has been previously studied [27–29]. Unfortunately, our study did not investigate the degree to which our study population valued nursing opinion and evaluation and whether this limited the utility of the assessment piece. With that said, at least one study looking at MSF within anesthesiology demonstrated that nursing feedback was considered paramount by anesthesiologists and valued to a much larger degree than by other physicians in the peri-operative environment, namely surgeons [30]. The assessment of physicians has been shown to be reliable and feasible so long as results from an adequate number and variety of assessors are included [31]. The specific study of physician-nurse communication did not lend itself to the utilization of MSF and this may help explain why both groups demonstrated no improved performance following feedback. It is likely unrealistic to expect that simply providing feedback would have resulted in noticeably improved performance [32]. It is possible that further intervention, such as repeated, facilitated feedback would yield more useful results. Additionally, the provision of opportunities to improve on effective communication may have yielded significant improvements.