Cognitive workload classification of law enforcement officers using physiological responses.

Motor vehicle crashes (MVCs) are a leading cause of death for law enforcement officers (LEOs) in the U.S. LEOs and more specifically novice LEOs (nLEOs) are susceptible to high cognitive workload while driving which can lead to fatal MVCs. The objective of this study was to develop a machine learning algorithm (MLA) that can estimate cognitive workload of LEOs while performing secondary tasks in a patrol vehicle. A ride-along study was conducted with 24 nLEOs. Participants performed their normal patrol operations while their physiological responses such as heartrate, eye movement, and galvanic skin response were recorded using unobtrusive devices. Findings suggested that the random forest algorithm could predict cognitive workload with relatively high accuracy (>70%) given that it was entirely reliant on physiological signals. The developed MLA can be used to develop adaptive in-vehicle technology based on real-time estimation of cognitive workload, which can reduce the risk of MVCs in police operations.

Physical effort of middle-aged women in a university hospital - Field tests in comparison to standardized cardiopulmonary exercise testing (CPET).

Physical effort of workload of female employees in the healthcare system is perceived to rise. Research focused mainly on physical activity levels of registered nurses (RN). Therefore, we investigated physical strain during daily routine of other hospital workers next to RN. O2uptake, heart rate, breathing frequency and ventilation were measured in 33 female medical (associate) professionals (MAP) and Cleaners&Helpers (Cl&H) using Oxycon Mobile. Physical work load was compared to standardized CPET. Wilcoxon-test and ANOVA were calculated using SPSS 20.0. Cl&H performed heavy-lifting and had the lowest power during CPET. The O2-uptake for heavy-lifting as strong effort, differed significantly from office work (p < 0.001) and bedside-patient-care (p = 0.001). Compared with metabolic equivalent (MET) cleaning, heavy-lifting, and office work are underestimated. Bedside-patient-care, walking, pushing performed by MAP are overestimated. While Cl&H had the lowest maximal power in CPET, their work required the highest O2-uptake. The tasks are underestimated in the MET-tables.

Model to estimate the nursing workload required by trauma victims on intensive care unit discharge.

AIM: To validate a model to estimate the nursing workload required by trauma victims on intensive care unit (ICU) discharge. BACKGROUND: Identifying a reliable model of nursing workload measurement that can assist professionals. METHODS: A prospective cohort study conducted in 2010 (first phase) and 2015 (second phase) with 342 trauma victims admitted into the ICU of four hospitals located in São Paulo, Brazil. The original model was created during the first phase and included the Simplified Acute Physiology Score and New Injury Severity Score variables. Coefficients of determination (R2 ) were calculated to identify the reliability. RESULTS: The original model presented high reliability (R2  = 44%) in the hospital of origin, and unsatisfactory performance (R2  < 4%) in the other institutions. An improvement in R2 was observed after adjusting the coefficients for each hospital. CONCLUSION: For the Nursing Activities Score prediction of survivors for ICU discharge, trauma centres must validate the original model with coefficient adjustments for their population, or preferably derive their own models. IMPLICATIONS FOR NURSING MANAGEMENT: Although models are useful in predicting discharge of these ICU patients, for treatment continuity after critical care and for organising services, the study showed that they should be evaluated prior to use for nursing management.

Workloads and burnout of nursing workers / Cargas de trabajo y agotamiento de la salud de los trabajadores de la enfermería / Cargas de trabalho e os desgastes à saúde dos trabalhadores da enfermagem

ABSTRACT Objective: to identify workloads in nursing work and its association with nursing worker burnout. Method: a cross-sectional study, including 211 nursing workers from a university hospital, between July and August 2016. For the analysis, the descriptive statistics, Chi-Square Test, Fisher's Exact Test and Mann Whitney U-Test were used. Results: the most evidenced loads were biological. A significant association was found between workloads and workers' occupation, as well as a significant association between workloads and worker burnout. Burnout caused upper limb pain, neck and lumbar pain, lower limb pain, muscle spasm, lower limb edema, mental fatigue, headache, nervousness, and forgetfulness. Conclusion: workloads identification is a subsidy for the promotion of interventions that minimize the burnout generated to the health of the nursing worker.

RESUMEN Objetivo: identificar las cargas de trabajo presentes en el trabajo de la Enfermería y su asociación con los desgastes a la salud de los trabajadores. Método: el estudio transversal, incluyendo 211 trabajadores de enfermería de un hospital universitario, entre julio y agosto de 2016. Para análisis, se utilizó estadística descriptiva y las Pruebas Qui-Cuadrado, Exacto de Fisher y Mann Whitney. Resultados: las cargas más evidenciadas fueron las biológicas. Se verificó una asociación significativa entre las cargas de trabajo y la función de los trabajadores, así como una asociación significativa entre cargas de trabajo y desgastes a la salud de los trabajadores. Los síntomas de agotamiento fueron dolor en miembros superiores, dolor en región cervical y lumbar, dolor en miembros inferiores, contractura muscular, edema en miembros inferiores, cansancio mental, cefalea, nerviosismo y olvido. Conclusión: la identificación de las cargas de trabajo sirve de subsidio para promoción de intervenciones que minimicen los desgastes generados a la salud del trabajador de la Enfermería.

RESUMO Objetivo: identificar as cargas de trabalho presentes no trabalho da Enfermagem e a sua associação com os desgastes à saúde dos trabalhadores. Método: estudo transversal, incluindo 211 trabalhadores de enfermagem de um hospital universitário, entre julho e agosto de 2016. Para análise, utilizou-se estatística descritiva e os Testes Qui-Quadrado, Exato de Fisher e Mann Whitney. Resultados: as cargas mais evidenciadas foram as biológicas. Verificou-se associação significativa entre as cargas de trabalho e a função dos trabalhadores, assim como associação significativa entre cargas de trabalho e desgastes à saúde dos trabalhadores. Os desgastes foram dor em membros superiores, dor em região cervical e lombar, dor em membros inferiores, contratura muscular, edema em membros inferiores, cansaço mental, cefaleia, nervosismo e esquecimento. Conclusão: a identificação das cargas de trabalho serve de subsídio para promoção de intervenções que minimizem os desgastes gerados à saúde do trabalhador da Enfermagem.

Workloads and burnout of nursing workers.

OBJECTIVE: to identify workloads in nursing work and its association with nursing worker burnout. METHOD: a cross-sectional study, including 211 nursing workers from a university hospital, between July and August 2016. For the analysis, the descriptive statistics, Chi-Square Test, Fisher's Exact Test and Mann Whitney U-Test were used. RESULTS: the most evidenced loads were biological. A significant association was found between workloads and workers' occupation, as well as a significant association between workloads and worker burnout. Burnout caused upper limb pain, neck and lumbar pain, lower limb pain, muscle spasm, lower limb edema, mental fatigue, headache, nervousness, and forgetfulness. CONCLUSION: workloads identification is a subsidy for the promotion of interventions that minimize the burnout generated to the health of the nursing worker.

Atomic Head Movement Analysis for Wearable Four-Dimensional Task Load Recognition.

Physical activity recognition using wearable sensors has achieved good performance in discriminating heterogeneous activities for health monitoring, but there has been less investigation of sedentary activities, e.g., desk work, which is often physically homogenous, to improve health in office environments. In this study, we explored head movement as a new sensing modality for physical and mental activity analysis. A new algorithm which segments gyroscope signals into atomic head movement events is proposed. Instead of recognizing activities in terms of predefined categories, we recognized four dimensions of task load: cognitive, perceptual, communicative, and physical, analogous to current manual workload assessment methods like NASA-TLX. We collected head movement data from 24 participants who wore a tri-axial inertial sensor at head while performing multiple tasks with varying load levels at office. An average of 70% accuracy was achieved for recognizing cognitive load levels, and more than 80% for the other three load types. The proposed event features outperformed a set of 181 features from previous physical activity recognition studies. We also demonstrated that these atomic event features are diagnostic of different load types in cross-load type classification, showing the promise of physical and mental load monitoring for health.

Objective measures of workload in healthcare: a narrative review.

PURPOSE: Workload is a critical concept in the evaluation of performance and quality in healthcare systems, but its definition relies on the perspective (e.g. individual clinician-level vs unit-level workload) and type of available metrics (e.g. objective vs subjective measures). The purpose of this paper is to provide an overview of objective measures of workload associated with direct care delivery in tertiary healthcare settings, with a focus on measures that can be obtained from electronic records to inform operationalization of workload measurement. DESIGN/METHODOLOGY/APPROACH: Relevant papers published between January 2008 and July 2018 were identified through a search in Pubmed and Compendex databases using the Sample, Phenomenon of Interest, Design, Evaluation, Research Type framework. Identified measures were classified into four levels of workload: task, patient, clinician and unit. FINDINGS: Of 30 papers reviewed, 9 used task-level metrics, 14 used patient-level metrics, 7 used clinician-level metrics and 20 used unit-level metrics. Key objective measures of workload include: patient turnover (n=9), volume of patients (n=6), acuity (n=6), nurse-to-patient ratios (n=5) and direct care time (n=5). Several methods for operationalization of these metrics into measurement tools were identified. ORIGINALITY/VALUE: This review highlights the key objective workload measures available in electronic records that can be utilized to develop an operational approach for quantifying workload. Insights gained from this review can inform the design of processes to track workload and mitigate the effects of increased workload on patient outcomes and clinician performance.

Dimensioning of nursing staff in outpatient chemotherapy: application of the Workload Indicators of Staffing Need / Dimensionamiento de profesionales enfermeros en quimioterapia ambulatoria: aplicación del método Workload Indicators of Staffing Need / Dimensionamento de profissionais de enfermagem em quimioterapia ambulatorial: aplicação do método Workload Indicators of Staffing Need

ABSTRACT Objective: To apply the method developed by the World Health Organization, called Workload Indicators of Staffing Need for dimensioning the nursing staff for the care of cancer patients in a Chemotherapy outpatient clinic. Method: This is a quantitative, observational, documentary field study with an intentional sample. Prospective data were collected through the work sampling method. Results: Seventeen nurses and 12 nursing technicians participated in the study. A total of 3,727 observations were performed and were obtained the mean times and the relative working time of 23 nurses' interventions and 18 nursing technicians' interventions. The interventions corresponded to 88.5% of the relative working time of nurses and 83.9% of nursing technicians. Personal activities accounted for 8.2% of the relative working time of nurses and 7.9% of nursing technicians. The reliability test resulted in 86.3% concordance. Conclusion: The similarity between the staff required according to the method studied and the current staff showed that the Workload Indicators of Staffing Need has great potential and applicability for dimensioning nursing professionals safely.

RESUMEN Objetivo: Aplicar el método elaborado por la Organización Mundial de la Salud, denominado Workload Indicators of Staffing Need, a fin de dimensionar al equipo de enfermería para el cuidado a pacientes oncológicos en Ambulatorio de Quimioterapia. Método: Se trata de una investigación de campo observacional y documental, con abordaje cuantitativo y muestra intencional. Los datos prospectivos fueron recogidos mediante la técnica de muestreo del trabajo. Resultados: Participaron en la investigación 17 enfermeros y 12 técnicos de enfermería. Fueron realizadas 3.727 observaciones, obteniéndose tiempos medios y ocupación relativa de 23 intervenciones de enfermeros y 18 intervenciones de técnicos de enfermería. Las intervenciones correspondieron al 88,5% de la ocupación relativa de los enfermeros y el 83,9% de los técnicos de enfermería. La actividad personal fue responsable del 8,2% de la ocupación relativa de los enfermeros y el 7,9% de los técnicos de enfermería. La prueba de confiabilidad resultó en el 86,3% de concordancia. Conclusión: La semejanza entre el cuadro proyectado por el método estudiado y el existente evidenció que el Workload Indicators of Staffing Need tiene gran potencial y aplicabilidad para dimensionar a los profesionales enfermeros con seguridad.

RESUMO Objetivo: Aplicar o método elaborado pela Organização Mundial da Saúde, denominado Workload Indicators of Staffing Need, para dimensionar a equipe de enfermagem para o cuidado de pacientes oncológicos em Ambulatório de Quimioterapia. Método: Trata-se de uma pesquisa de campo observacional e documental, com abordagem quantitativa e amostra intencional. Os dados prospectivos foram coletados por meio da técnica amostragem do trabalho. Resultados: Participaram da pesquisa 17 enfermeiros e 12 técnicos de enfermagem. Foram realizadas 3.727 observações, sendo obtidos tempos médios e ocupação relativa de 23 intervenções de enfermeiros e 18 intervenções de técnicos de enfermagem. As intervenções corresponderam a 88,5% da ocupação relativa dos enfermeiros e 83,9% dos técnicos de enfermagem. A atividade pessoal foi responsável por 8,2% da ocupação relativa dos enfermeiros e 7,9% dos técnicos de enfermagem. O teste de confiabilidade resultou em 86,3% de concordância. Conclusão: A semelhança entre o quadro projetado pelo método estudado e o existente evidenciou que o Workload Indicators of Staffing Need tem grande potencial e aplicabilidade para dimensionar os profissionais de enfermagem com segurança.

Validity and reliability of the Turkish version of the Physical Workload Questionnaire.

BACKGROUND: Although it is necessary to regularly record and assess physical workloads in a workplace to prevent work-related musculoskeletal disorders, there is no easy to use, valid and reliable questionnaire such as the Physical Workload Questionnaire (PWQ) in Turkish. OBJECTIVE: To linguistically and culturally adapt the PWQ into Turkish, and to examine the validity and reliability of this adapted version. METHODS: One hundred twenty-six participants were recruited. All participants filled in the Oswestry Disability Index (ODI) and the Nordic Musculoskeletal Questionnaire. To determine test-retest reliability, all participants filled in the PWQ after a time interval of one week. RESULTS: There was a significant difference in the PWQ indices between the participants with an occupation requires less vs. higher workload (p < 0.05). The PWQ index was significantly correlated with the proximal musculoskeletal symptoms (ρ= 0.301, p < 0.05), but not significantly correlated with distal musculoskeletal symptoms (ρ= 0.121, p > 0.05). The PWQ index was significantly correlated with the ODI (ρ= 0.193, p < 0.05). The internal consistency of the PWQ was excellent (α= 0.865) and item-total correlations were acceptable. Test-retest reliability was high (ICC = 0.865). CONCLUSIONS: The PWQ is the unique valid and reliable questionnaire available in Turkish for assessing physical workload due to body posture and strenuous effort during work.

Classification of driving workload affected by highway alignment conditions based on classification and regression tree algorithm.

OBJECTIVE: Guaranteeing a safe and comfortable driving workload can contribute to reducing traffic injuries. In order to provide safe and comfortable threshold values, this study attempted to classify driving workload from the aspects of human factors mainly affected by highway geometric conditions and to determine the thresholds of different workload classifications. This article stated a hypothesis that the values of driver workload change within a certain range. METHODS: Driving workload scales were stated based on a comprehensive literature review. Through comparative analysis of different psychophysiological measures, heart rate variability (HRV) was chosen as the representative measure for quantifying driving workload by field experiments. Seventy-two participants (36 car drivers and 36 large truck drivers) and 6 highways with different geometric designs were selected to conduct field experiments. A wearable wireless dynamic multiparameter physiological detector (KF-2) was employed to detect physiological data that were simultaneously correlated to the speed changes recorded by a Global Positioning System (GPS) (testing time, driving speeds, running track, and distance). Through performing statistical analyses, including the distribution of HRV during the flat, straight segments and P-P plots of modified HRV, a driving workload calculation model was proposed. Integrating driving workload scales with values, the threshold of each scale of driving workload was determined by classification and regression tree (CART) algorithms. RESULTS: The driving workload calculation model was suitable for driving speeds in the range of 40 to 120 km/h. The experimental data of 72 participants revealed that driving workload had a significant effect on modified HRV, revealing a change in driving speed. When the driving speed was between 100 and 120 km/h, drivers showed an apparent increase in the corresponding modified HRV. The threshold value of the normal driving workload K was between -0.0011 and 0.056 for a car driver and between -0.00086 and 0.067 for a truck driver. CONCLUSION: Heart rate variability was a direct and effective index for measuring driving workload despite being affected by multiple highway alignment elements. The driving workload model and the thresholds of driving workload classifications can be used to evaluate the quality of highway geometric design. A higher quality of highway geometric design could keep driving workload within a safer and more comfortable range. This study provided insight into reducing traffic injuries from the perspective of disciplinary integration of highway engineering and human factor engineering.

Feature Weight Driven Interactive Mutual Information Modeling for Heterogeneous Bio-Signal Fusion to Estimate Mental Workload.

Many people suffer from high mental workload which may threaten human health and cause serious accidents. Mental workload estimation is especially important for particular people such as pilots, soldiers, crew and surgeons to guarantee the safety and security. Different physiological signals have been used to estimate mental workload based on the n-back task which is capable of inducing different mental workload levels. This paper explores a feature weight driven signal fusion method and proposes interactive mutual information modeling (IMIM) to increase the mental workload classification accuracy. We used EEG and ECG signals to validate the effectiveness of the proposed method for heterogeneous bio-signal fusion. The experiment of mental workload estimation consisted of signal recording, artifact removal, feature extraction, feature weight calculation, and classification. Ten subjects were invited to take part in easy, medium and hard tasks for the collection of EEG and ECG signals in different mental workload levels. Therefore, heterogeneous physiological signals of different mental workload states were available for classification. Experiments reveal that ECG can be utilized as a supplement of EEG to optimize the fusion model and improve mental workload estimation. Classification results show that the proposed bio-signal fusion method IMIM can increase the classification accuracy in both feature level and classifier level fusion. This study indicates that multi-modal signal fusion is promising to identify the mental workload levels and the fusion strategy has potential application of mental workload estimation in cognitive activities during daily life.

Developing a caseload classification tool for community nursing.

Acuity and dependency in the community nursing caseload in combination with safe staffing levels are a national issue of concern. Current evidence suggests that there are no clear approaches to determining staff capacity and skill mix in these community settings. As community nursing caseloads are large with differing complexities, there is a need to allocate community nursing with the best skill mix to achieve the best patient outcomes. A city-wide service improvement initiative developed a tool to classify and categorise patient demand and this was linked to an electronic patient record system. The aim was to formulate an effective management response to different levels of acuity and dependency within community nursing teams and a consensus approach was used to allow the definition of complexity for twelve packages of care. The tool was piloted by a group of community nurses to assess the validity as a method to achieve a caseload classification. Seventy nurses were trained and applied the tool to 3000 patient referrals. Based on this, standards of care were agreed including expectations of assessment, intervention, visit length and frequency. Community nursing caseloads can now be organised according to acuity and complexity of patient need, which determines allocation of staff and skill mix.

Pattern Classification of Instantaneous Cognitive Task-load Through GMM Clustering, Laplacian Eigenmap, and Ensemble SVMs.

The identification of the temporal variations in human operator cognitive task-load (CTL) is crucial for preventing possible accidents in human-machine collaborative systems. Recent literature has shown that the change of discrete CTL level during human-machine system operations can be objectively recognized using neurophysiological data and supervised learning technique. The objective of this work is to design subject-specific multi-class CTL classifier to reveal the complex unknown relationship between the operator's task performance and neurophysiological features by combining target class labeling, physiological feature reduction and selection, and ensemble classification techniques. The psychophysiological data acquisition experiments were performed under multiple human-machine process control tasks. Four or five target classes of CTL were determined by using a Gaussian mixture model and three human performance variables. By using Laplacian eigenmap, a few salient EEG features were extracted, and heart rates were used as the input features of the CTL classifier. Then, multiple support vector machines were aggregated via majority voting to create an ensemble classifier for recognizing the CTL classes. Finally, the obtained CTL classification results were compared with those of several existing methods. The results showed that the proposed methods are capable of deriving a reasonable number of target classes and low-dimensional optimal EEG features for individual human operator subjects.

Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals.

An artificial neural network (ANN) model was developed in the present study to classify the level of a driver's cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%).

Pediatric Echocardiography by Work Relative Value Units: Is Study Complexity Adequately Captured?

BACKGROUND: Present resource-based relative value unit (RVU) assignment for echocardiography is based on Current Procedural Terminology (CPT) codes, which do not incorporate complexity of diagnosis, time spent for image acquisition, or interpretation of echocardiograms. The objective of this study was to determine whether CPT-based RVU assignment accurately reflects physician effort in performing and interpreting pediatric echocardiographic examinations. METHODS: Cardiac complexity category (CCC) and physician time for study interpretation of 123 echocardiograms (June to September 2013) were prospectively assigned. Categories included (1) focused effusion/function evaluation, (2) normal anatomy/focused preterm infant studies, (3) acquired heart disease, (4) congenital heart disease excluding single ventricles, (5) single ventricles including heterotaxy syndrome, and (6) hearts on mechanical support. Subsequently, a random sample of echocardiograms (March to August 2013) were retrospectively analyzed, and each study was assigned a CCC and an extrapolated median interpretation time (MIT) on the basis of prospective data collection. Assigned work RVUs based on CPT codes were recorded. Comparisons were made between CCC and time for study interpretation, work RVUs, number of images acquired, and total scan time. RESULTS: A total of 933 echocardiograms were analyzed: 198 (21%), 174 (19%), 98 (11%), 359 (35%), 84 (9%), and 20 (2%) studies in CCCs 1 to 6, respectively. Total scan time, MIT, number of images, and work RVUs were different among CCCs (P < .0001). However, among the more complex studies (CCCs 2-5), work RVUs were similar, while number of images obtained and MIT were different (P < .001). Correlation analysis showed no association between work RVUs and CCC, total scan, or number of images per study. Compared with older patients, work RVUs of studies in children <2 years of age were lower, while all other markers of study complexity were higher (P < .05). CONCLUSIONS: Current CPT-based assignment of work RVUs does not discriminate study complexity and physician effort. The results of this study highlight the need for a refined system that accurately assesses physician effort in pediatric echocardiography.

Workload and cortisol levels in helicopter combat pilots during simulated flights / Carga mental y niveles de cortisol en pilotos de helicóptero de combate en vuelos simulados / Carga de trabalho e níveis de cortisol em pilotos de helicópteros de combate durante voos simulados

Objective. Examine and compare the cortisol levels before and after a simulated flight related to workload in experienced helicopter combat pilots, searching for physiological levels of anxiety. Method. 15 volunteer Spanish Army helicopter combat pilots (36.83 ± 8.04 years) were studied before and after a simulated flight (eight new tasks). Salivary cortisol was measured by DRG salivary cortisol ELISA, and we studied workload using the NASA-TLX. Results. The differences in the mean values of cortisol level before (5.33 ± 1.55) and after the task at the flight simulator (4.47 ± 0.73) are statistically significant (t14 = 3.301; p = .005) with a high effect size (d = 0.75). Similar significant differences were also found (t14 = 3.301; p = .005) between the workload before (19.76 ± 10.54), and after the task (24.82 ± 10.42; medium effect size d = −0.48). No significant relationships were found between the cortisol levels and the workload. Conclusions. Cortisol levels in saliva and workload are the usual in stress situations, and change inversely: workload increases at the end of the task, whereas the cortisol levels decrease after the simulated flight. The somatic anxiety decreases as the task is done. In contrast, when the pilots are faced with new and demanding tasks, even if they fly this type of helicopter in different conditions, the workload increases toward the end of the task. From an applied point of view, these findings should impact the tactical, physical and mental training of such pilots (AU)

Objetivo. Examinar y comparar los niveles de cortisol antes y después de un vuelo simulado en relación con la carga de trabajo de pilotos de helicópteros con experiencia de combate, en busca de niveles fisiológicos de la ansiedad. Método. Se estudió a 15 pilotos de helicópteros voluntarios del Ejército Español (36.83 ± 8.04 años) antes y después de un vuelo simulado compuesto por 8 tareas nuevas. El cortisol salival se midió por DRG Cortisol ELISA y la carga de trabajo con el NASA-TLX. Resultados. Las diferencias entre los valores medios de nivel de cortisol antes (5.33 ± 1.55) y después de la tarea en el simulador de vuelo (4.47 ± 0.73) son estadísticamente significativas (t14 = 3.301; p = 0.005; elevado tamaño de efecto, d = 0.75), así como (t14 = 3.301; p = 0.005) entre la carga de trabajo antes (19.76 ± 10.54) y después de la tarea (24.82 ± 10.42; tamaño de efecto medio, d = −0.48). No hubo relaciones significativas entre los niveles de cortisol y la carga de trabajo. Conclusiones. Los niveles de cortisol en saliva y la carga de trabajo son habituales en situaciones de estrés, y cambian inversamente: la carga de trabajo aumenta al final de la tarea, mientras que los niveles de cortisol —y de ansiedad somática— disminuyen después del vuelo simulado. En cambio, frente a tareas nuevas y exigentes, la carga de trabajo aumenta al final. Estos hallazgos deberían afectar la planificación del entrenamiento táctico, físico y mental de estos pilotos (AU)

Objetivo. Examinar e comparar os níveis de cortisol antes e depois de voo simulado em relação a carga de trabalho de experientes pilotos de helicóptero de combate, procurando por níveis fisiológicos de ansiedade. Métodos. 15 voluntários pilotos de helicópteros de combate do exército espanhol (36.83 ± 8.04 años) foram estudados antes e depois de um voo simulado (8 novas tarefas). Cortisol salivar foi mensurado por DRG Cortisol salivar ELISA, e foi estudado a carga de trabalho usando o NASA-TLX. Resultados. As diferenças nos valores médios dos níveis de cortisol antes (5.33 ± 1.55) e depois da tarefa no simulador de voo (4.47 ± 0.73) foram estatisticamente significantes (t14 = 3.301; p = .005) com o tamanho do efeito (d = 0.75). Diferenças significantes similares também foram encontradas (t14 = 3.301; p = .005) entre a carga de trabalho antes (19.76 ± 10.54), e depois da tarefa (24.82 ± 10.42); tamanho do efeito médio (d = −0.48). Nenhuma relação significativa foi encontrada entre os níveis de cortisol e a carga de trabalho. Conclusão. Níveis de cortisol na saliva e carga de trabalho são comuns em situações de estresse, e mudam inversamente: a carga de trabalho aumenta ao final da tarefa, enquanto o nível de cortisol diminui depois do voo simulado. A ansiedade somática diminui quando a tarefa acaba. Em contraste, quando os pilotos enfrentam uma nova e exigente tarefa, mesmo que eles voem no mesmo tipo de helicóptero em diferentes situações, a carga de trabalho aumenta em direção ao final da tarefa. Para um ponto de vista aplicável, os achados devem impactar o treinamento tático, físico e mental destes pilotos (AU)

[Nursing workload in a coronary unit according to the Nursing Activities Score]. / Carga de trabalho em unidade coronariana Segundo o Nursing Activities Score.

OBJECTIVE: this study aimed to using the Nursing Activities Score to assess nursing workload in a coronary care unit, to assess the distribution of workload between shifts, and to compare the current staff of the care unit with that recommended by the instrument. METHOD: this was a longitudinal study, conducted in a teaching hospital in Southern Brazil, between April to June 2012. RESULTS: A total of 604 NAS measures were obtained from the 61 patients included. The mean workload per shift was 47% (±12), with the greatest workload being reported in the afternoon shifts. CONCLUSION: according to the NAS, a mean of two and a maximum of 2.4 nursing professionals would be required per shift to meet all patient demands, suggesting that the current staff size in the CCU is adequate. The NAS was successful in assessing nursing workload and changes in patient demands over time.

[Expectations, requirements and limitations of future task sharing between the nursing profession and the medical profession: results from the Care-N Study M-V]. / Erwartungen, Wünsche und Grenzen der künftigen Aufgabenteilung von Pflege und Medizin - Ergebnisse der Care-N Study M-V.

BACKGROUND: The aging population causes a sustained increase in demand of medical and nursing care services. At the same time health care professionals are aging, too. This leads to a growing number of health care gaps. Therefore, the health care system needs to be reformed. This includes a reallocation of task between some of the health care professions. AIMS: This article addresses developments, potentials and limitations in the context of the future allocation of tasks between the nursing and the medical profession. Aim is to specify the future task sharing between nurses and physicians regarding expectations, requirements and limitations. METHODS: We conducted questionnaire based Delphi interviews with an interdisciplinary group of experts. (type aggregation of ideas). RESULTS: In the future, to expert's point of view, nurses will take over routine tasks in the medical and nursing health care supply. Task sharing by substitution is regarded with skepticism by experts. It requires a long time perspective and an early involvement of all stakeholders. CONCLUSIONS: Germany is at the beginning of the process of the future task sharing between nurses and physicians. The realization requires a comprehensive political support and further development of concepts including scientific implementation and evaluation.