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).

scholarly journals Comparison of Power for Multiple Comparison Procedures

2013 ◽  
Vol 4 (1) ◽  
pp. 20 ◽  
Author(s):  
Robert S. Rodger ◽  
Mark Roberts
Keyword(s):  
Error Rate ◽  
Error Rates ◽  
The Other ◽  
Group Differences ◽  
Type 1 Error ◽  
Sample Data ◽  
Bonferroni's Inequality ◽  
Post Hoc ◽  
Multiple Comparison Procedures

The number of methods for evaluating, and possibly making statistical decisions about, null contrasts - or their small sub-set, multiple comparisons - has grown extensively since the early 1950s. That demonstrates how important the subject is, but most of the growth consists of modest variations of the early methods. This paper examines nine fairly basic procedures, six of which are methods designed to evaluate contrasts chosen post hoc, i.e., after an examination of the test data. Three of these use experimentwise or familywise type 1 error rates (Scheffé 1953, Tukey 1953, Newman-Keuls, 1939 and 1952), two use decision-based type 1 error rates (Duncan 1951 and Rodger 1975a) and one (Fisher's LSD 1935) uses a mixture of the two type 1 error rate definitions. The other three methods examined are for evaluating, and possibly deciding about, a limited number of null contrasts that have been chosen independently of the sample data - preferably before the data are collected. One of these (planned t-tests) uses decision-based type 1 error rates and the other two (one based on Bonferroni's Inequality 1936, and the other Dunnett's 1964 Many-One procedure) use a familywise type 1 error rate. The use of these different type 1 error rate definitionsA creates quite large discrepancies in the capacities of the methods to detect true non-zero effects in the contrasts being evaluated. This article describes those discrepancies in power and, especially, how they are exacerbated by increases in the size of an investigation (i.e., an increase in J, the number of samples being examined). It is also true that the capacity of a multiple contrast procedure to 'unpick' 'true' differences from the sample data is influenced by the type of contrast the procedure permits. For example, multiple range procedures (such as that of Newman-Keuls and that of Duncan) permit only comparisons (i.e., two-group differences) and that greatly limits their discriminating capacity (which is not, technically speaking, their power). Many methods (those of Scheffé, Tukey's HSD, Newman-Keuls, Fisher's LSD, Bonferroni and Dunnett) place their emphasis on one particular question, "Are there any differences at all among the groups?" Some other procedures concentrate on individual contrasts (i.e., those of Duncan, Rodger and Planned Contrasts); so are more concerned with how many false null contrasts the method can detect. This results in two basically different definitions of detection capacity. Finally, there is a categorical difference between what post hoc methods and those evaluating pre-planned contrasts can find. The success of the latter depends on how wisely (or honestly well informed) the user has been in planning the limited number of statistically revealing contrasts to test. That can greatly affect the method's discriminating success, but it is often not included in power evaluations. These matters are elaborated upon as they arise in the exposition below. DOI:10.2458/azu_jmmss_v4i1_rodger

Error Variability and the Differentiation Between Apraxia of Speech and Aphasia With Phonemic Paraphasia

2013 ◽  
Vol 56 (3) ◽  
pp. 891-905 ◽  
Author(s):  
Katarina L. Haley ◽  
Adam Jacks ◽  
Kevin T. Cunningham
Keyword(s):  
Error Rate ◽  
Clinical Utility ◽  
Correlation Coefficients ◽  
Cerebral Injury ◽  
Group Differences ◽  
Future Research ◽  
Diagnostic Validity ◽  
Apraxia Of Speech ◽  
Motor Speech ◽  
Conduction Aphasia

Purpose This study was conducted to evaluate the clinical utility of error variability for differentiating between apraxia of speech (AOS) and aphasia with phonemic paraphasia. Method Participants were 32 individuals with aphasia after left cerebral injury. Diagnostic groups were formed on the basis of operationalized measures of recognized articulatory and prosodic characteristics of AOS and phonemic paraphasia. Sequential repetitions of multisyllabic words were elicited as part of a motor speech evaluation and transcribed phonetically. Four metrics of variability at the syllable and word levels were derived from these transcripts. Results The measures yielded different magnitudes of variability. There were no group differences between participants who displayed speech profiles consistent with AOS and participants who displayed speech profiles indicative of aphasia with phonemic paraphasia. Rather, correlation coefficients and analyses of covariance showed that the variability metrics were significantly mediated by overall error rate. Additionally, variability scores for individuals with salient diagnoses of AOS and conduction aphasia were inconsistent with current diagnostic guidelines. Conclusions The results do not support diagnostic validity of error variability for differentiating between AOS and aphasia with phonemic paraphasia. Future research using error variability metrics should account for overall error rate in the analysis and matching of participant groups.

scholarly journals The Nature of Error Consistency in Individuals With Acquired Apraxia of Speech and Aphasia

2017 ◽  
Vol 26 (2S) ◽  
pp. 611-630 ◽  
Author(s):  
Lauren Bislick ◽  
Malcolm McNeil ◽  
Kristie A. Spencer ◽  
Kathryn Yorkston ◽  
Diane L. Kendall
Keyword(s):  
Error Rate ◽  
Motor Planning ◽  
Stimulus Presentation ◽  
Apraxia Of Speech ◽  
Error Type ◽  
Presentation Condition ◽  
Design Error ◽  
Error Location ◽  
Phonetic Errors ◽  
Consistent Error

Purpose The primary characteristics used to define acquired apraxia of speech (AOS) have evolved to better reflect a disorder of motor planning/programming. However, there is debate regarding the feature of relatively consistent error location and type. Method Ten individuals with acquired AOS and aphasia and 11 individuals with aphasia without AOS participated in this study. In the context of a 2-group experimental design, error consistency was examined via 5 repetitions of 30 multisyllabic words. The influence of error rate, severity of impairment, and stimulus presentation condition (blocked vs. random) on error consistency was also explored, as well as between-groups differences in the types of errors produced. Results Groups performed similarly on consistency of error location; however, adults with AOS demonstrated greater variability of error type in a blocked presentation condition only. Stimulus presentation condition, error rate, and severity of impairment did not influence error consistency in either group. Groups differed in the production of phonetic errors (e.g., sound distortions) but not phonemic errors. Conclusions Overall, findings do not support relatively consistent errors as a differentiating characteristic of AOS.

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

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.

scholarly journals Comparison of Power for Multiple Comparison Procedures

2013 ◽  
Vol 4 (1) ◽  
pp. 20 ◽  
Author(s):  
Robert S. Rodger ◽  
Mark Roberts
Keyword(s):  
Error Rate ◽  
Error Rates ◽  
The Other ◽  
Group Differences ◽  
Type 1 Error ◽  
Sample Data ◽  
Bonferroni's Inequality ◽  
Post Hoc ◽  
Multiple Comparison Procedures

The number of methods for evaluating, and possibly making statistical decisions about, null contrasts - or their small sub-set, multiple comparisons - has grown extensively since the early 1950s. That demonstrates how important the subject is, but most of the growth consists of modest variations of the early methods. This paper examines nine fairly basic procedures, six of which are methods designed to evaluate contrasts chosen post hoc, i.e., after an examination of the test data. Three of these use experimentwise or familywise type 1 error rates (Scheffé 1953, Tukey 1953, Newman-Keuls, 1939 and 1952), two use decision-based type 1 error rates (Duncan 1951 and Rodger 1975a) and one (Fisher's LSD 1935) uses a mixture of the two type 1 error rate definitions. The other three methods examined are for evaluating, and possibly deciding about, a limited number of null contrasts that have been chosen independently of the sample data - preferably before the data are collected. One of these (planned t-tests) uses decision-based type 1 error rates and the other two (one based on Bonferroni's Inequality 1936, and the other Dunnett's 1964 Many-One procedure) use a familywise type 1 error rate. The use of these different type 1 error rate definitionsA creates quite large discrepancies in the capacities of the methods to detect true non-zero effects in the contrasts being evaluated. This article describes those discrepancies in power and, especially, how they are exacerbated by increases in the size of an investigation (i.e., an increase in J, the number of samples being examined). It is also true that the capacity of a multiple contrast procedure to 'unpick' 'true' differences from the sample data is influenced by the type of contrast the procedure permits. For example, multiple range procedures (such as that of Newman-Keuls and that of Duncan) permit only comparisons (i.e., two-group differences) and that greatly limits their discriminating capacity (which is not, technically speaking, their power). Many methods (those of Scheffé, Tukey's HSD, Newman-Keuls, Fisher's LSD, Bonferroni and Dunnett) place their emphasis on one particular question, "Are there any differences at all among the groups?" Some other procedures concentrate on individual contrasts (i.e., those of Duncan, Rodger and Planned Contrasts); so are more concerned with how many false null contrasts the method can detect. This results in two basically different definitions of detection capacity. Finally, there is a categorical difference between what post hoc methods and those evaluating pre-planned contrasts can find. The success of the latter depends on how wisely (or honestly well informed) the user has been in planning the limited number of statistically revealing contrasts to test. That can greatly affect the method's discriminating success, but it is often not included in power evaluations. These matters are elaborated upon as they arise in the exposition below. DOI:10.2458/azu_jmmss_v4i1_rodger

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.

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