Intra-rater reliability

About: Intra-rater reliability is a research topic. Over the lifetime, 2073 publications have been published within this topic receiving 140968 citations.

Intra-rater reliability and concurrent validity of quantified muscle testing for maximal knee extensors strength in men with myotonic dystrophy type 1

Abstract: Background : Myotonic dystrophy type 1 (DM1) is the most prevalent degenerative neuromuscular disease in adults. Knee extensor (KE) maximal strength loss is a strong indicator of physical limitations in DM1. A reliable, precise and accessible maximal strength evaluation method needs to be validated for this slowly progressive disease. Objective : This paper aims to assess the intra-rater reliability, the standard error of measurement (SEM), the minimal detectable change (MDC), and the concurrent validity of quantified muscle testing (QMT) using a handheld dynamometer with a gold standard: the Biodex isokinetic device. Methods:Nineteen men with the adult form of DM1 participated in this study by attending 2 visits spaced by one week. The evaluation of KE muscle strength with QMT was completed on the first visit and the same QMT evaluation in addition to the maximal muscle strength evaluation using an isokinetic device were performed on the second visit. Results : The intra-rater reliability was excellent with an intraclass correlation coefficient (ICC) of 0.98 (0.96–0.99 : 95% confidence interval). SEM and MDC values were 1.05 Nm and 2.92 Nm, respectively. Concurrent validity of QMT of KE muscle group with the Biodex was also excellent with a Spearman’s correlation of ρ= 0.98. Conclusions : The excellent concurrent validity and intra-rater reliability, and the small SEM and MDC of the QMT make this test a method of choice, in either a clinical or research setting, to precisely evaluate muscle strength impairments of the KE in men with DM1.

Reliability of the Modified Oswestry Disability Index for evaluating patients with low back pain

Abstract: Objective:To determined the reliability of the Oswestry Disability Index(ODI) for evaluating patients with low back pain.Method:22(female 9,male 13) subjects who were inpatients of the orthopedic words were evaluated using the modified ODI in Chinese before operation.They were divided into two groups:intrarater reliability group(n=10) and interrater reliability group(n=12).The patients answered the ODI.The test retest reliability was done in every 3 days and compared using a Pearson Correlation,individually.Result:The highly correlated coefficient of 0 953( t=8 851,P 0 001) and 0 912( t=7 008,P 0 01)were obtained in intrarater reliability group and interrater reliability group individually.Conclusion:The modified ODI in Chinese shows the superior reliability.This assessment method allows the evaluation of multiple parameters of the patient′s function. It can be used to study the clinical outcome of postoperation or rehabilitation in patients with low back pain.

A Bayesian network approach for human reliability analysis of power system

Abstract: Along with the improvement of equipment reliability, human error has become a great threat to the power system reliability and safety However, the research of human reliability analysis in power system is still in its infancy There is still little approach for quantitatively measuring the human reliability of power system In this paper, the definition of human reliability of power system and a human error causal framework are given firstly Secondly, with the suitable Performance Influencing Factors(PIFs) selected, the probability inference model based on Bayesian network for human reliability analysis is proposed Finally, a case study shows that the proposed methodology can integrate organizational factors, situational factors, and individual factors to quantitatively measure the human reliability of power system This approach provides forceful support for improving the human reliability of power system and has a good prospect

Reliability of the hidradenitis suppurativa clinical response in the assessment of patients with hidradenitis suppurativa.

Abstract: Background Hidradenitis suppurativa clinical response (HiSCR) is a validated clinical end point for measuring response to treatment in patients with hidradenitis suppurativa (HS). Previous studies have reported on the validity, responsiveness and meaningfulness of the HiSCR. Objective To evaluate the HiSCR for inter- and intrarater reliability characteristics. Methods A stand-alone, two-site, prospective, non-interventional observational study consisted of 22 patients, with self-reported severity between mild, moderate and severe HS. The Patient Global Impression of Change (PGI-C) scale was completed by patients at Timepoint 2. Descriptive statistics of Hurley Stage, total abscesses, total draining fistulas, total inflammatory nodules and total AN count (sum of inflammatory nodules and lesions) were reported at two timepoints. Inter-rater reliability and intrarater reliability for the HS lesion count tool were evaluated at two timepoints (baseline and Day 7) using the HS lesion count tool. Intraclass correlation (ICC) coefficients of lesion counts were calculated to evaluate inter- and intrarater reliability of lesion counts between pairs of dermatologists. Results The majority of patients demonstrated either no change or minimally worse PGI-C in HS scores. Descriptive statistics were similar between rater groups and timepoints assessed. Inter-rater ICC coefficients for abscess count at Timepoints 1 and 2 were 0.38 and 0.67. The ICC coefficients for draining fistula and AN count were ≥0.61 at both timepoints. In an exploratory model, ICC coefficients were ≥0.68 for all evaluated lesion counts. The test-retest reliability using ICC coefficients was ≥0.70 for total abscess, draining fistula, inflammatory nodule and AN count. Conclusion The HS lesion count tool had an acceptable inter- and intrarater reliability, indicating that HiSCR has a strong degree of reproducibility and consistency in the evaluation of patients with HS.

Human- Versus Machine Learning-Based Triage Using Digitalized Patient Histories in Primary Care: Comparative Study.

Abstract: Background: Smartphones have made it possible for patients to digitally report symptoms before physical primary care visits. Using machine learning (ML), these data offer an opportunity to support decisions about the appropriate level of care (triage). Objective: The purpose of this study was to explore the interrater reliability between human physicians and an automated ML-based triage method. Methods: After testing several models, a naive Bayes triage model was created using data from digital medical histories, capable of classifying digital medical history reports as either in need of urgent physical examination or not in need of urgent physical examination. The model was tested on 300 digital medical history reports and classification was compared with the majority vote of an expert panel of 5 primary care physicians (PCPs). Reliability between raters was measured using both Cohen κ (adjusted for chance agreement) and percentage agreement (not adjusted for chance agreement). Results: Interrater reliability as measured by Cohen κ was 0.17 when comparing the majority vote of the reference group with the model. Agreement was 74% (138/186) for cases judged not in need of urgent physical examination and 42% (38/90) for cases judged to be in need of urgent physical examination. No specific features linked to the model’s triage decision could be identified. Between physicians within the panel, Cohen κ was 0.2. Intrarater reliability when 1 physician retriaged 50 reports resulted in Cohen κ of 0.55. Conclusions: Low interrater and intrarater agreement in triage decisions among PCPs limits the possibility to use human decisions as a reference for ML to automate triage in primary care.