scholarly journals Calculating the Test-Retest Reliability Co-efficient from Normative Retest Data for Determining Reliable Change

2010 ◽  
Vol 26 (1) ◽  
pp. 76-77 ◽  
Author(s):  
A. D. Hinton-Bayre
Keyword(s):  
Reliable Change ◽  
Retest Reliability ◽  
Test Retest Reliability

ERRATUM

2002 ◽  
Vol 8 (3) ◽  
pp. 481-481
Author(s):  
WILLIAM B. BARR ◽  
MICHAEL McCREA
Keyword(s):  
Confidence Interval ◽  
Sensitivity And Specificity ◽  
Neurocognitive Testing ◽  
Reliable Change ◽  
Retest Reliability ◽  
Sports Concussion ◽  
The Third ◽  
Test Retest Reliability

The following is a correction for an error that occurred in the Journal of the International Neuropsychological Society, Vol. 7, No. 6. The error occurred in the article titled “Sensitivity and specificity of standardized neurocognitive testing immediately following sports concussion,” pp. 693–702, by Barr and McCrea. On page 696, under the subheading “Test-Retest Reliability and Reliable Change Cut-off Scores”, the confidence interval in the third sentence should read “−2.21, +2.59”, rather than “±2.59”.

Establishing Test–Retest Reliability and Reliable Change for the King–Devick Test in High School Athletes

2019 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
R. J. Elbin ◽  
Philip Schatz ◽  
Samantha Mohler ◽  
Tracey Covassin ◽  
Jesse Herrington ◽  
...  
Keyword(s):  
High School ◽  
High School Athletes ◽  
Reliable Change ◽  
Retest Reliability ◽  
Test Retest Reliability

scholarly journals Test–Retest Reliability and Reliable Change Estimates for Four Mobile Cognitive Tests Administered Virtually in Community-Dwelling Adults

2021 ◽  
Vol 12 ◽  
Author(s):  
Ryan Van Patten ◽  
Grant L. Iverson ◽  
Mélissa A. Muzeau ◽  
Heidi A. VanRavenhorst-Bell
Keyword(s):  
Working Memory ◽  
Reaction Time ◽  
Impulse Control ◽  
Community Dwelling ◽  
Cognitive Test ◽  
Inspection Time ◽  
Reliable Change ◽  
Retest Reliability ◽  
Intraclass Correlations ◽  
Test Retest Reliability

Objective: Remote mobile cognitive testing (MCT) is an expanding area of research, but psychometric data supporting these measures are limited. We provide preliminary data on test–retest reliability and reliable change estimates in four MCTs from SWAY Medical, Inc.Methods: Fifty-five adults from the U.S. Midwest completed the MCTs remotely on their personal mobile devices once per week for 3 consecutive weeks, while being supervised with a video-based virtual connection. The cognitive assessment measured simple reaction time (“Reaction Time”), go/no-go response inhibition (“Impulse Control”), timed visual processing (“Inspection Time”), and working memory (“Working Memory”). For each cognitive test except Working Memory, we analyzed both millisecond (ms) responses and an overall SWAY composite score.Results: The mean age of the sample was 26.69years (SD=9.89; range=18–58). Of the 55 adults, 38 (69.1%) were women and 49 (89.1%) used an iPhone. Friedman’s ANOVAs examining differences across testing sessions were nonsignificant (ps>0.31). Intraclass correlations for Weeks 1–3 were: Reaction Time (ms): 0.83, Reaction Time (SWAY): 0.83, Impulse Control (ms): 0.68, Impulse Control (SWAY): 0.80, Inspection Time (ms): 0.75, Inspection Time (SWAY): 0.75, and Working Memory (SWAY): 0.88. Intraclass correlations for Weeks 1–2 were: Reaction Time (ms): 0.75, Reaction Time (SWAY): 0.74, Impulse Control (ms): 0.60, Impulse Control (SWAY): 0.76, Inspection Time (ms): 0.79, Inspection Time (SWAY): 0.79, and Working Memory (SWAY): 0.83. Natural distributions of difference scores were calculated and reliable change estimates are presented for 70, 80, and 90% CIs.Conclusion: Test–retest reliability was adequate or better for the MCTs in this virtual remote testing study. Reliable change estimates allow for the determination of whether a particular level of improvement or decline in performance is within the range of probable measurement error. Additional reliability and validity data are needed in other age groups.

scholarly journals Establishment of a reliable change index for the GAD-7

2020 ◽  
Vol 8 (1) ◽  
pp. 176-187
Author(s):  
Thomas Bischoff ◽  
Shayne R. Anderson ◽  
Joy Heafner ◽  
Rachel Tambling
Keyword(s):  
Online Community ◽  
Clinical Sample ◽  
Community Sample ◽  
Mental Healthcare ◽  
Reliable Change Index ◽  
Good Test ◽  
Reliable Change ◽  
Retest Reliability ◽  
The Mean ◽  
Test Retest Reliability

Aim It is increasingly important for mental healthcare providers and researchers to reliably assess client change, particularly with common presenting problems such as anxiety. The current study addresses this need by establishing a Reliable Change Index of 6 points for the GAD-7. Method Sample size included 116 online community participants using Amazon’s Mechanical Turk (MTurk) and archival data for 332 clinical participants. Participants completed measures of the GAD-7 and the MDI in 2 rounds. Using previously established cutoff scores and Jacobson and Truax’s (1991) method, we establish a Reliable Change Index which, when applied to 2 administrations of the GAD-7, indicates if a client has experienced meaningful change. Results For the GAD-7, the mean score for the clinical sample was 10.57. For the community sample at Time 1, the mean score was 4.14. A Pearson’s correlation was computed to assess the 14-28-day test-retest reliability of the GAD-7, r(110) = .87, indicating good test-retest reliability. Conclusion Using the RCI equation, this resulted in an RCI of 5.59. For practical use the RCI would be rounded to 6.

Test-retest reliability, practice effects and reliable change indices for the recognition memory test

2003 ◽  
Vol 42 (4) ◽  
pp. 407-425 ◽  
Author(s):  
Chris M. Bird ◽  
Kyriaki Papadopoulou ◽  
Paola Ricciardelli ◽  
Martin N. Rossor ◽  
Lisa Cipolotti
Keyword(s):  
Recognition Memory ◽  
Memory Test ◽  
Practice Effects ◽  
Reliable Change ◽  
Retest Reliability ◽  
Recognition Memory Test ◽  
Test Retest Reliability

scholarly journals Examining 3-month test-retest reliability and reliable change using the Cambridge Neuropsychological Test Automated Battery

2020 ◽  
pp. 1-9 ◽  
Author(s):  
Rune H. Karlsen ◽  
Justin E. Karr ◽  
Simen B. Saksvik ◽  
Astri J. Lundervold ◽  
Odin Hjemdal ◽  
...  
Keyword(s):  
Neuropsychological Test ◽  
Reliable Change ◽  
Retest Reliability ◽  
Test Retest Reliability

scholarly journals Concussion Biomarkers Assessed in Collegiate Student-Athletes (BASICS) I

Neurology ◽  
2018 ◽  
Vol 91 (23) ◽  
pp. e2109-e2122 ◽  
Author(s):  
Breton M. Asken ◽  
Russell M. Bauer ◽  
Steven T. DeKosky ◽  
Zachary M. Houck ◽  
Charles C. Moreno ◽  
...  
Keyword(s):  
Calcium Binding ◽  
Female Athletes ◽  
Collegiate Athletes ◽  
Serum Biomarkers ◽  
Amyloid Peptide ◽  
Reliable Change ◽  
Retest Reliability ◽  
Total Tau ◽  
Baseline Levels ◽  
Test Retest Reliability

ObjectiveTo describe variability in concussion biomarker concentrations collected from serum in a sample of healthy collegiate athletes, as well as report reliability metrics in a subsample of female athletes.MethodsIn this observational cohort study, β-amyloid peptide 42 (Aβ42), total tau, S100 calcium binding protein B (S100B), ubiquitin carboxy-terminal hydrolyzing enzyme L1 (UCH-L1), glial fibrillary acidic protein, microtubule associated protein 2, and 2′,3′-cyclic-nucleotide 3′-phosphodiesterase (CNPase) serum concentrations were measured in 415 (61% male, 40% white, aged 19.0 ± 1.2 years) nonconcussed collegiate athletes without recent exposure to head impacts. Standardized normative distributions are reported for each biomarker. We evaluated main effects (analyses of variance) of sex and race, reporting demographic-specific normative metrics when appropriate. In a subset of 31 female participants, test-retest reliability (Pearson r) and reliable change indices (80%, 90%, and 95% confidence intervals) across a 6- to 12-month interval are reported for Aβ42, total tau, S100B, and UCH-L1.ResultsMales exhibited higher UCH-L1 (p < 0.001, Cohen d = 0.75) and S100B (p < 0.001, d = 0.56) than females, while females had higher CNPase (p < 0.001, d = 0.43). Regarding race, black participants had higher baseline levels of UCH-L1 (p < 0.001, d = 0.61) and S100B (p < 0.001, d = 1.1) than white participants. Conversely, white participants had higher baseline levels of Aβ42 (p = 0.005, d = 0.28) and CNPase (p < 0.001, d = 0.46). Test-retest reliability was generally poor, ranging from −0.02 to 0.40, and Aβ42 significantly increased from time 1 to time 2.ConclusionHealthy collegiate athletes express concussion-related serum biomarkers in variable concentrations. Accounting for demographic factors such as sex and race is essential. Evidence suggested poor reliability for serum biomarkers; however, understanding how other factors influence biomarker expression, as well as knowledge of reliable change metrics, may improve clinical interpretation and future study designs.

Measuring “Language Access Profiles” in Deaf and Hard-of-Hearing Children With the DHH Language Exposure Assessment Tool

2020 ◽  
pp. 1-25
Author(s):  
Matthew L. Hall ◽  
Stephanie De Anda
Keyword(s):  
Cluster Analysis ◽  
Exposure Assessment ◽  
Hard Of Hearing ◽  
Assessment Tool ◽  
Communication Mode ◽  
Developmental Potential ◽  
Language Access ◽  
Retest Reliability ◽  
Language Exposure ◽  
Test Retest Reliability

Purpose The purposes of this study were (a) to introduce “language access profiles” as a viable alternative construct to “communication mode” for describing experience with language input during early childhood for deaf and hard-of-hearing (DHH) children; (b) to describe the development of a new tool for measuring DHH children's language access profiles during infancy and toddlerhood; and (c) to evaluate the novelty, reliability, and validity of this tool. Method We adapted an existing retrospective parent report measure of early language experience (the Language Exposure Assessment Tool) to make it suitable for use with DHH populations. We administered the adapted instrument (DHH Language Exposure Assessment Tool [D-LEAT]) to the caregivers of 105 DHH children aged 12 years and younger. To measure convergent validity, we also administered another novel instrument: the Language Access Profile Tool. To measure test–retest reliability, half of the participants were interviewed again after 1 month. We identified groups of children with similar language access profiles by using hierarchical cluster analysis. Results The D-LEAT revealed DHH children's diverse experiences with access to language during infancy and toddlerhood. Cluster analysis groupings were markedly different from those derived from more traditional grouping rules (e.g., communication modes). Test–retest reliability was good, especially for the same-interviewer condition. Content, convergent, and face validity were strong. Conclusions To optimize DHH children's developmental potential, stakeholders who work at the individual and population levels would benefit from replacing communication mode with language access profiles. The D-LEAT is the first tool that aims to measure this novel construct. Despite limitations that future work aims to address, the present results demonstrate that the D-LEAT represents progress over the status quo.

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