scholarly journals Language control in bilingual production: Insights from error rate and error type in sentence production

2020 ◽  
pp. 1-15
Author(s):  
Clara D. Martin ◽  
Nazbanou Nozari
Keyword(s):  
Noun Phrase ◽  
Error Rate ◽  
Error Rates ◽  
Sentence Production ◽  
Control Mechanisms ◽  
Cognitive Demands ◽  
Error Type ◽  
Isolated Word ◽  
Language Control ◽  
High Control

Abstract Most research showing that cognates are named faster than non-cognates has focused on isolated word production which might not realistically reflect cognitive demands in sentence production. Here, we explored whether cognates elicit interference by examining error rates during sentence production, and how this interference is resolved by language control mechanisms. Twenty highly proficient Spanish–English bilinguals described visual scenes with sentence structures ‘NP1-verb-NP2’ (NP = noun-phrase). Half the nouns and half the verbs were cognates and two manipulations created high control demands. Both situations that demanded higher inhibitory control pushed the cognate effect from facilitation towards interference. These findings suggest that cognates, similar to phonologically similar words within a language, can induce not only facilitation but robust interference.

Perceptual Characteristics of Consonant Production in Apraxia of Speech and Aphasia

2019 ◽  
Vol 28 (4) ◽  
pp. 1411-1431 ◽  
Author(s):  
Lauren Bislick ◽  
William D. Hula
Keyword(s):  
Error Rate ◽  
Error Rates ◽  
Group Differences ◽  
Diagnostic Process ◽  
Apraxia Of Speech ◽  
Contextual Variables ◽  
Error Type ◽  
Type Distribution ◽  
Phonetic Features ◽  
Syllable Position

Purpose This retrospective analysis examined group differences in error rate across 4 contextual variables (clusters vs. singletons, syllable position, number of syllables, and articulatory phonetic features) in adults with apraxia of speech (AOS) and adults with aphasia only. Group differences in the distribution of error type across contextual variables were also examined. Method Ten individuals with acquired AOS and aphasia and 11 individuals with aphasia participated in this study. In the context of a 2-group experimental design, the influence of 4 contextual variables on error rate and error type distribution was examined via repetition of 29 multisyllabic words. Error rates were analyzed using Bayesian methods, whereas distribution of error type was examined via descriptive statistics. Results There were 4 findings of robust differences between the 2 groups. These differences were found for syllable position, number of syllables, manner of articulation, and voicing. Group differences were less robust for clusters versus singletons and place of articulation. Results of error type distribution show a high proportion of distortion and substitution errors in speakers with AOS and a high proportion of substitution and omission errors in speakers with aphasia. Conclusion Findings add to the continued effort to improve the understanding and assessment of AOS and aphasia. Several contextual variables more consistently influenced breakdown in participants with AOS compared to participants with aphasia and should be considered during the diagnostic process. Supplemental Material https://doi.org/10.23641/asha.9701690

P30 The effects of introducing electronic prescribing for paediatric chemotherapy using aria on prescribing error rates at a primary treatment centre

2018 ◽  
Vol 103 (2) ◽  
pp. e2.33-e2
Author(s):  
Peter Cook ◽  
Andy Fox
Keyword(s):  
Acute Lymphoblastic Leukaemia ◽  
Error Rate ◽  
Lymphoblastic Leukaemia ◽  
Error Rates ◽  
Electronic Prescribing ◽  
Patient Specific ◽  
Prescribing Errors ◽  
Prescribing Error ◽  
Error Type ◽  
Before And After

IntroductionPrescribing of medication in children is a very complex process that involves an understanding of paediatric physiology, disease states, medication used and pharmacokinetics as well as patient specific details, their co-morbidities and their clinical condition. The most common medication errors have been identified as dosing, route of administration, and frequency of administration. Computerised provider order entry has been shown to reduce the number of prescribing errors related to chemotherapy as well as the likelihood of dose and calculation errors in paediatric chemotherapy prescribing. Locally, paediatric chemotherapy is prescribed on pre-printed paper prescriptions. Adaptation and implementation of ARIA electronic prescribing (EP) system for use in paediatric chemotherapy was undertaken by a Specialist Paediatric Oncology Pharmacist and was rolled out for use in January 2016 for patients with acute lymphoblastic leukaemia.MethodThe United Kingdom National Randomised Trial for Children and Young Adults with Acute Lymphoblastic Leukaemia and Lymphoma 2011 (UKALL, 2011) was developed for use on EP, with prescribing of all other chemotherapy remaining on paper. The number and type of prescribing errors were collected during a pre-implementation phase from January 2015 to June 2015. After the introduction of EP and following a 2 month acclimatisation period, a second period of data collection took place between March 2016 and July 2016. Overall prescribing error rates and the frequency of each error type were calculated both before and after implementation.ResultsBefore the introduction of EP for paediatric chemotherapy, the overall error rate was 18.4% with a total of 16 different errors seen. Post implementation, overall error rate increased to 25.7% (p<0.001) with a total of 10 different errors seen. After introduction of EP, prescribing error rates on paper were 30.6% and on EP were 7.0% (p<0.001). Only 5 different error types were seen with electronic prescribing. The most commonly seen errors in prescribing with paper, both before and after were almost eliminated with the introduction of EP.ConclusionThe introduction of EP has resulted in a significant reduction in prescribing error rates compared to paper based prescribing for paediatric chemotherapy. Overall the prescribing error rate increased after the introduction of EP but this was related to an increased rate on the paper prescriptions. One possible reason for this was the use of dual systems for prescribing. In addition there was unforeseen relocation and building work within the paediatric cancer unit, which affected prescribing time allocation. There were also several staff shortages within the prescribing team after implementation and this resulted in an increased workload on the remaining chemotherapy prescribers. All these issues could have attributed to the increase in error rates. The most common errors seen with chemotherapy prescribing have been reduced with EP as protocols have been developed with a focus on prescribing safety. Further work is needed as more prescribing takes place on EP to assess the full impact it has on paediatric chemotherapy error rates.

scholarly journals Effectiveness of a ‘do not interrupt’ vest intervention to reduce medication errors during medication administration: a multicenter cluster randomized controlled trial

BMC Nursing ◽  
2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Sarah Berdot ◽  
Aurélie Vilfaillot ◽  
Yvonnick Bezie ◽  
Germain Perrin ◽  
Marion Berge ◽  
...  
Keyword(s):  
Risk Factors ◽  
Error Rate ◽  
Medication Administration ◽  
Error Rates ◽  
Clinical Impact ◽  
Control Group ◽  
Error Type ◽  
Administration Error ◽  
The Impact ◽  
Experimental Group

Abstract Background The use of a ‘do not interrupt’ vest during medication administration rounds is recommended but there have been no controlled randomized studies to evaluate its impact on reducing administration errors. We aimed to evaluate the impact of wearing such a vest on reducing such errors. The secondary objectives were to evaluate the types and potential clinical impact of errors, the association between errors and several risk factors (such as interruptions), and nurses’ experiences. Methods This was a multicenter, cluster, controlled, randomized study (March–July 2017) in 29 adult units (4 hospitals). Data were collected by direct observation by trained observers. All nurses from selected units were informed. A ‘Do not interrupt’ vest was implemented in all units of the experimental group. A poster was placed at the entrance of these units to inform patients and relatives. The main outcome was the administration error rate (number of Opportunities for Error (OE), calculated as one or more errors divided by the Total Opportunities for Error (TOE) and multiplied by 100). Results We enrolled 178 nurses and 1346 patients during 383 medication rounds in 14 units in the experimental group and 15 units in the control group. During the intervention period, the administration error rates were 7.09% (188 OE with at least one error/2653 TOE) for the experimental group and 6.23% (210 OE with at least one error/3373 TOE) for the control group (p = 0.192). Identified risk factors (patient age, nurses’ experience, nurses’ workload, unit exposition, and interruption) were not associated with the error rate. The main error type observed for both groups was wrong dosage-form. Most errors had no clinical impact for the patient and the interruption rates were 15.04% for the experimental group and 20.75% for the control group. Conclusions The intervention vest had no impact on medication administration error or interruption rates. Further studies need to be performed taking into consideration the limitations of our study and other risk factors associated with other interventions, such as nurse’s training and/or a barcode system. Trial registration The PERMIS study protocol (V2–1, 11/04/2017) was approved by institutional review boards and ethics committees (CPP Ile de France number 2016-A00211–50, CNIL 21/03/2017, CCTIRS 11/04/2016). It is registered at ClinicalTrials.gov (registration number: NCT03062852, date of first registration: 23/02/2017).

SP3 The effect of electronic prescribing and medicines administration systems (epmass) on paediatric medication errors

2018 ◽  
Vol 103 (2) ◽  
pp. e1.23-e1
Author(s):  
Aragon Octavio ◽  
Fayyaz Goher ◽  
Gill Andrea ◽  
Morecroft Charles
Keyword(s):  
Medication Errors ◽  
Error Rate ◽  
Error Rates ◽  
Electronic Prescribing ◽  
Prescribing Errors ◽  
Error Type ◽  
Common Error ◽  
Period 2 ◽  
The Difference ◽  
Paediatric Prescribing

BackgroundThe complex nature of paediatric prescribing makes this population more vulnerable to medication errors.1Electronic Prescribing and Medicines Administration Systems (EPMASs) have been suggested to improve paediatric medication safety by reducing prescribing errors.AimTo identify and compare the number and nature of paediatric medication errors pre and post introduction of an EPMAS at a tertiary paediatric hospital.MethodologyPharmacists collected data monthly on the number of new items prescribed and the number of errors (if any) detected in these prescriptions following methodology from the EQUIP study.2 The EPMAS Meditechv6 was introduced in June 2015. Data analysed included forms from 1st-January-2015 to 30th-June-2015 (period 1: pre-EPMAS) and 1st-January-2016 to 30th-June-2016 (period 2: post-EPMAS). The analysis aimed to investigate the rate, type and severity of errors as well as the prescriber grade, prescribing stage and drug class associated with each. Descriptive statistical methods were used to analyse the frequency and nature of errors pre and post implementation of Meditech. Statistical significance was tested using a contingency Chi-squared (χ2) test for the difference in error rates across both periods and a Mann-Whitney test for the difference between the severities of errors across both periodsResultsAn increase of 6.4% in error rate was detected post-Meditech introduction with 67 errors in 1706 items (3.9%) during period 1 and 151 errors in 1459 items (10.3%) during period 2 (p<0.001, χ2 test). FY2 doctors and ‘admission stage’ were associated with the highest error rates across both periods. Minor severity errors were the most common in both periods, with 55.2% in period 1% and 66.2% in period 2. No statistical difference was detected (p=0.403) in the severity of errors reported although the proportion of significant and serious errors decreased from 38.8% to 27.8% and 6.0% to 0.7% respectively. No errors were classed to be potentially lethal in period 1, however there was one such incident in period 2. Underdosing was the most common error type in period 1 (22.4%), falling to 4.0% in period 2. Omission on admission was the most common error type in period 2, with an error rate of 37.7% vs 20.9% in period 1. Antibacterials and analgesics were the most common classes of drugs involved in errors in both periods, although a wider range of drug classes were involved in errors post Meditech introductionConclusionA significant increase of 6.4% in error rate was found post implementation of Meditech highlighting the concept of EPMAS-facilitated errors. The positive effect of EPMASs is also apparent as the incidence of significant and serious errors decreased in period 2, although this difference was not statistically significant. Reaching definitive conclusions is difficult due to the lack of available research into the effects of EPMASs on paediatric prescribing and due to methodological limitations. However, it can be suggested that introducing functions such as comprehensive decision support and dose calculators may overcome the shortcomings of the current system3 and allow for the true benefits of EPMASs in improving paediatric medication safety to be demonstrated.ReferencesNational Patient Safety Agency. Review of patient safety for children and young people 2009. England: National Reporting and Learning Services. http://www.nrls.npsa.nhs.uk/resources/?entryid45=5986 [Accessed: 29th October 2016].Dornan T, et al. An in-depth investigation into causes of prescribing errors by foundation trainees in relation to their medical education: EQUIP study. Final Report to the General Medical Council 2009. http://www.gmcuk.org/FINAL_Report_prevalence_and_causes_of_prescribing_errors.pdf_28935150.pdf [Accessed: 9th November 2016].Johnson KB, Lehmann CU. Electronic prescribing in paediatrics: Toward safer and more effective medication management. Paediatrics 2013;131(4):e1350–e1356. doi:10.1542/peds.2013-0193

Correction: “Influence of Selection Bias on the Test Decision – A Simulation Study”

2014 ◽  
Vol 53 (05) ◽  
pp. 343-343
Keyword(s):  
Selection Bias ◽  
Simulation Study ◽  
Error Rate ◽  
Type I Error ◽  
Block Size ◽  
Error Rates ◽  
Type I ◽  
Type I Error Rate ◽  
Representation Error ◽  
Numeric Representation

We have to report marginal changes in the empirical type I error rates for the cut-offs 2/3 and 4/7 of Table 4, Table 5 and Table 6 of the paper “Influence of Selection Bias on the Test Decision – A Simulation Study” by M. Tamm, E. Cramer, L. N. Kennes, N. Heussen (Methods Inf Med 2012; 51: 138 –143). In a small number of cases the kind of representation of numeric values in SAS has resulted in wrong categorization due to a numeric representation error of differences. We corrected the simulation by using the round function of SAS in the calculation process with the same seeds as before. For Table 4 the value for the cut-off 2/3 changes from 0.180323 to 0.153494. For Table 5 the value for the cut-off 4/7 changes from 0.144729 to 0.139626 and the value for the cut-off 2/3 changes from 0.114885 to 0.101773. For Table 6 the value for the cut-off 4/7 changes from 0.125528 to 0.122144 and the value for the cut-off 2/3 changes from 0.099488 to 0.090828. The sentence on p. 141 “E.g. for block size 4 and q = 2/3 the type I error rate is 18% (Table 4).” has to be replaced by “E.g. for block size 4 and q = 2/3 the type I error rate is 15.3% (Table 4).”. There were only minor changes smaller than 0.03. These changes do not affect the interpretation of the results or our recommendations.

Reducing Culture Reporting Errors in the Microbiology Laboratory

2019 ◽  
Vol 152 (Supplement_1) ◽  
pp. S131-S132
Author(s):  
Kathryn Hogan ◽  
Beena Umar ◽  
Mohamed Alhamar ◽  
Kathleen Callahan ◽  
Linoj Samuel
Keyword(s):  
Real Time ◽  
Error Rate ◽  
Reporting System ◽  
Error Rates ◽  
Tracking Errors ◽  
Corrective Measures ◽  
Safety Awareness ◽  
Before And After ◽  
Set Up ◽  
System Errors

Abstract Objectives There are few papers that characterize types of errors in microbiology laboratories and scant research demonstrating the effects of interventions on microbiology lab errors. This study aims to categorize types of culture reporting errors found in microbiology labs and to document the error rates before and after interventions designed to reduce errors and improve overall laboratory quality. Methods To improve documentation of error incidence, a self-reporting system was changed to an automatic reporting system. Errors were categorized into five types Gram stain (misinterpretations), identification (incorrect analysis), set up labeling (incorrect patient labels), procedures (not followed), and miscellaneous. Error rates were tracked according to technologist, and technologists were given real-time feedback by a manager. Error rates were also monitored in the daily quality meeting and frequently detected errors were discussed at staff meetings. Technologists attended a year-end review with a manager to improve their performance. To maintain these changes, policies were developed to monitor technologist error rate and to define corrective measures. If a certain number of errors per month was reached, technologists were required to undergo retraining by a manager. If a technologist failed to correct any error according to protocol, they were also potentially subject to corrective measures. Results In 2013, we recorded 0.5 errors per 1,000 tests. By 2018, we recorded only 0.1 errors per 1,000 tests, an 80% decrease. The yearly culture volume from 2013 to 2018 increased by 32%, while the yearly error rate went from 0.05% per year to 0.01% per year, a statistically significant decrease (P = .0007). Conclusion This study supports the effectiveness of the changes implemented to decrease errors in culture reporting. By tracking errors in real time and using a standardized process that involved timely follow-up, technologists were educated on error prevention. This practice increased safety awareness in our micro lab.

Evaluation of eavesdropping error-rates in higher-dimensional QKD system implemented using dynamic spatial modes

2021 ◽  
Author(s):  
Muhammad Kamran ◽  
Tahir Malik ◽  
Muhammad Mubashir Khan
Keyword(s):  
Error Rate ◽  
Photon Number ◽  
Error Rates ◽  
Security And Privacy ◽  
Practical Implementation ◽  
Secret Key ◽  
Decoy State ◽  
Rate Analysis ◽  
Higher Dimensional ◽  
Spatial Modes

Secure exchange of cryptographic keys is extremely important for any communication system where security and privacy of data is desirable. Although classical cryptographic algorithms provide computationally secure methods for secret key exchange, quantum key distribution (QKD) provides an extraordinary means to this end by guaranteeing unconditional security. Any malicious interception of communication by a man-in-the-middle on a QKD link immediately alerts sender and receiver by introducing an unavoidable error-rate. Higher-dimensional QKD protocols such as KMB09 exhibit higher eavesdropping error-rates with improved intrusion detection but their practical implementation is still awaited. In this paper, we present the design and implementation of KMB09 protocol using Laguerre–Gaussian orbital angular momentum to demonstrate and highlight the advantages of using dynamic spatial modes in QKD system. A complete error-rate analysis of KMB09 protocol implementation is presented with two different types of eavesdropping error-rates. Furthermore, we also demonstrate the decoy state method to show the robustness of the protocol against photon-number-splitting attack.

Application of the False Discovery Rate to Quantitative Trait Loci Interval Mapping With Multiple Traits

Genetics ◽  
2002 ◽  
Vol 161 (2) ◽  
pp. 905-914 ◽  
Author(s):  
Hakkyo Lee ◽  
Jack C M Dekkers ◽  
M Soller ◽  
Massoud Malek ◽  
Rohan L Fernando ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
False Discovery Rate ◽  
Error Rate ◽  
Quantitative Trait ◽  
Interval Mapping ◽  
Error Rates ◽  
Multiple Traits ◽  
Test Statistic ◽  
False Discovery ◽  
Trait Loci

Abstract Controlling the false discovery rate (FDR) has been proposed as an alternative to controlling the genomewise error rate (GWER) for detecting quantitative trait loci (QTL) in genome scans. The objective here was to implement FDR in the context of regression interval mapping for multiple traits. Data on five traits from an F2 swine breed cross were used. FDR was implemented using tests at every 1 cM (FDR1) and using tests with the highest test statistic for each marker interval (FDRm). For the latter, a method was developed to predict comparison-wise error rates. At low error rates, FDR1 behaved erratically; FDRm was more stable but gave similar significance thresholds and number of QTL detected. At the same error rate, methods to control FDR gave less stringent significance thresholds and more QTL detected than methods to control GWER. Although testing across traits had limited impact on FDR, single-trait testing was recommended because there is no theoretical reason to pool tests across traits for FDR. FDR based on FDRm was recommended for QTL detection in interval mapping because it provides significance tests that are meaningful, yet not overly stringent, such that a more complete picture of QTL is revealed.

Kurzweil Reading Machine: A Partial Evaluation of Its Optical Character Recognition Error Rate

1979 ◽  
Vol 73 (10) ◽  
pp. 389-399
Author(s):  
Gregory L. Goodrich ◽  
Richard R. Bennett ◽  
William R. De L'aune ◽  
Harvey Lauer ◽  
Leonard Mowinski
Keyword(s):  
Error Rate ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Partial Evaluation ◽  
Error Rates ◽  
Recognition Error ◽  
Optical Character ◽  
Printed Materials ◽  
High Level

This study was designed to assess the Kurzweil Reading Machine's ability to read three different type styles produced by five different means. The results indicate that the Kurzweil Reading Machines tested have different error rates depending upon the means of producing the copy and upon the type style used; there was a significant interaction between copy method and type style. The interaction indicates that some type styles are better read when the copy is made by one means rather than another. Error rates varied between less than one percent and more than twenty percent. In general, the user will find that high quality printed materials will be read with a relatively high level of accuracy, but as the quality of the material decreases, the number of errors made by the machine also increases. As this error rate increases, the user will find it increasingly difficult to understand the spoken output.

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