413 resultados para Data validation


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Background Early feeding practices lay the foundation for children’s eating habits and weight gain. Questionnaires are available to assess parental feeding but overlapping and inconsistent items, subscales and terminology limit conceptual clarity and between study comparisons. Our aim was to consolidate a range of existing items into a parsimonious and conceptually robust questionnaire for assessing feeding practices with very young children (<3 years). Methods Data were from 462 mothers and children (age 21–27 months) from the NOURISH trial. Items from five questionnaires and two study-specific items were submitted to a priori item selection, allocation and verification, before theoretically-derived factors were tested using Confirmatory Factor Analysis. Construct validity of the new factors was examined by correlating these with child eating behaviours and weight. Results Following expert review 10 factors were specified. Of these, 9 factors (40 items) showed acceptable model fit and internal reliability (Cronbach’s α: 0.61-0.89). Four factors reflected non-responsive feeding practices: ‘Distrust in Appetite’, ‘Reward for Behaviour’, ‘Reward for Eating’, and ‘Persuasive Feeding’. Five factors reflected structure of the meal environment and limits: ‘Structured Meal Setting’, ‘Structured Meal Timing’, ‘Family Meal Setting’, ‘Overt Restriction’ and ‘Covert Restriction’. Feeding practices generally showed the expected pattern of associations with child eating behaviours but none with weight. Conclusion The Feeding Practices and Structure Questionnaire (FPSQ) provides a new reliable and valid measure of parental feeding practices, specifically maternal responsiveness to children’s hunger/satiety signals facilitated by routine and structure in feeding. Further validation in more diverse samples is required.

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Hospital disaster resilience can be defined as “the ability of hospitals to resist, absorb, and respond to the shock of disasters while maintaining and surging essential health services, and then to recover to its original state or adapt to a new one.” This article aims to provide a framework which can be used to comprehensively measure hospital disaster resilience. An evaluation framework for assessing hospital resilience was initially proposed through a systematic literature review and Modified-Delphi consultation. Eight key domains were identified: hospital safety, command, communication and cooperation system, disaster plan, resource stockpile, staff capability, disaster training and drills, emergency services and surge capability, and recovery and adaptation. The data for this study were collected from 41 tertiary hospitals in Shandong Province in China, using a specially designed questionnaire. Factor analysis was conducted to determine the underpinning structure of the framework. It identified a four-factor structure of hospital resilience, namely, emergency medical response capability (F1), disaster management mechanisms (F2), hospital infrastructural safety (F3), and disaster resources (F4). These factors displayed good internal consistency. The overall level of hospital disaster resilience (F) was calculated using the scoring model: F = 0.615F1 + 0.202F2 + 0.103F3 + 0.080F4. This validated framework provides a new way to operationalise the concept of hospital resilience, and it is also a foundation for the further development of the measurement instrument in future studies.

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The present study explores reproducing the closest geometry of a high pressure ratio single stage radial-inflow turbine applied in the Sundstrans Power Systems T-100 Multipurpose Small Power Unit. The commercial software ANSYS-Vista RTD along with a built in module, BladeGen, is used to conduct a meanline design and create 3D geometry of one flow passage. Carefully examining the proposed design against the geometrical and experimental data, ANSYS-TurboGrid is applied to generate computational mesh. CFD simulations are performed with ANSYS-CFX in which three-dimensional Reynolds-Averaged Navier-Stokes equations are solved subject to appropriate boundary conditions. Results are compared with numerical and experimental data published in the literature in order to generate the exact geometry of the existing turbine and validate the numerical results against the experimental ones.

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Computational models in physiology often integrate functional and structural information from a large range of spatio-temporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and scepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace and refine animal experiments. A fundamental requirement to fulfil these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations between experiments, models and simulations in cardiac electrophysiology. We describe the processes, data and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. Validation must therefore take into account the complex interplay between models, simulations and experiments. Key points for developing strategies for validation are: 1) understanding sources of bio-variability is crucial to the comparison between simulation and experimental results; 2) robustness of techniques and tools is a pre-requisite to conducting physiological investigations using the MSE system; 3) definition and adoption of standards facilitates interoperability of experiments, models and simulations; 4) physiological validation must be understood as an iterative process that defines the specific aspects of electrophysiology the MSE system targets, and is driven by advancements in experimental and computational methods and the combination of both.

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Background: The Lower Limb Functional Index (LLFI) is a relatively recently published regional outcome measure. The development article showed the LLFI had robust and valid clinimetric properties with sound psychometric and practical characteristics when compared to the Lower Limb Extremity Scale (LEFS) criterion standard. Objective: The purpose of this study was cross cultural adaptation and validation of the LLFI Spanish-version (LLFI-Sp) in a Spanish population. Methods: A two stage observational study was conducted. The LLFI was initially cross-culturally adapted to Spanish through double forward and single backward translation; then subsequently validated for the psychometric characteristics of validity, internal consistency, reliability, error score and factor structure. Participants (n = 136) with various lower limb conditions of >12 weeks duration completed the LLFI-Sp, Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and the Euroqol Health Questionnaire 5 Dimensions (EQ-5D-3 L). The full sample was employed to determine internal consistency, concurrent criterion validity, construct validity and factor structure; a subgroup (n = 45) determined reliability at seven days concurrently completing a global rating of change scale. Results: The LLFI-Sp demonstrated high but not excessive internal consistency (α = 0.91) and high reliability (ICC = 0.96). The factor structure was one-dimensional which supported the construct validity. Criterion validity with the WOMAC was strong (r = 0.77) and with the EQ-5D-3 L fair and inversely correlated (r = -0.62). The study limitations included the lack of longitudinal data and the determination of responsiveness. Conclusions: The LLFI-Sp supports the findings of the original English version as being a valid lower limb regional outcome measure. It demonstrated similar psychometric properties for internal consistency, validity, reliability, error score and factor structure.

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Stormwater pollution is linked to stream ecosystem degradation. In predicting stormwater pollution, various types of modelling techniques are adopted. The accuracy of predictions provided by these models depends on the data quality, appropriate estimation of model parameters, and the validation undertaken. It is well understood that available water quality datasets in urban areas span only relatively short time scales unlike water quantity data, which limits the applicability of the developed models in engineering and ecological assessment of urban waterways. This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset. It was found that the application of MCCV is likely to result in a more realistic measure of model coefficients than LOO. Most importantly, MCCV and LOO were found to be effective in model validation when dealing with a small sample size which hinders detailed model validation and can undermine the effectiveness of stormwater quality management strategies.

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Study Design Delphi panel and cohort study. Objective To develop and refine a condition-specific, patient-reported outcome measure, the Ankle Fracture Outcome of Rehabilitation Measure (A-FORM), and to examine its psychometric properties, including factor structure, reliability, and validity, by assessing item fit with the Rasch model. Background To our knowledge, there is no patient-reported outcome measure specific to ankle fracture with a robust content foundation. Methods A 2-stage research design was implemented. First, a Delphi panel that included patients and health professionals developed the items and refined the item wording. Second, a cohort study (n = 45) with 2 assessment points was conducted to permit preliminary maximum-likelihood exploratory factor analysis and Rasch analysis. Results The Delphi panel reached consensus on 53 potential items that were carried forward to the cohort phase. From the 2 time points, 81 questionnaires were completed and analyzed; 38 potential items were eliminated on account of greater than 10% missing data, factor loadings, and uniqueness. The 15 unidimensional items retained in the scale demonstrated appropriate person and item reliability after (and before) removal of 1 item (anxious about footwear) that had a higher-than-ideal outfit statistic (1.75). The “anxious about footwear” item was retained in the instrument, but only the 14 items with acceptable infit and outfit statistics (range, 0.5–1.5) were included in the summary score. Conclusion This investigation developed and refined the A-FORM (Version 1.0). The A-FORM items demonstrated favorable psychometric properties and are suitable for conversion to a single summary score. Further studies utilizing the A-FORM instrument are warranted. J Orthop Sports Phys Ther 2014;44(7):488–499. Epub 22 May 2014. doi:10.2519/jospt.2014.4980

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Introduction We have previously shown that the concentrations of D-dimer are significantly elevated in saliva compared with plasma. Saliva offers several advantages compared with blood analysis. We hypothesised that human saliva contains plasminogen activator inhibitor-1 (PAI-1) and that the concentrations are not affected by the time of saliva collection. The aim was to adopt and validate an immunoassay to quantify PAI-1 concentrations in saliva and to determine whether saliva collection time has an influence in the measurement. Materials and methods Two saliva samples (morning and afternoon) from the same day were collected from healthy subjects (N = 40) who have had no underlying heart conditions. A customized AlphaLISA® immunoassay (PerkinElmer®, MA, USA) was adopted and used to quantify PAI-1 concentrations. We validated the analytical performance of the customized immunoassay by calculating recovery of known amount of analyte spiked in saliva. Results: The recovery (95.03%), intra- (8.59%) and inter-assay (7.52%) variations were within the acceptable ranges. The median salivary PAI-1 concentrations were 394 pg/mL (interquartile ranges (IQR) 243.4-833.1 pg/mL) in the morning and 376 (129.1-615.4) pg/mL in the afternoon and the plasma concentration was 59,000 (24,000-110,000) pg/mL. Salivary PAI-1 did not correlate with plasma (P = 0.812). Conclusions The adopted immunoassay produced acceptable assay sensitivity and specificity. The data demonstrated that saliva contains PAI-1 and that its concentration is not affected by the time of saliva collection. There is no correlation between salivary and plasma PAI-1 concentrations. Further studies are required to demonstrate the utility of salivary PAI-1 in CVD risk factor studies.

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The objective of this work is to formulate a nonlinear, coupled model of a container ship during parametric roll resonance, and to validate the model using experimental data.

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Critical to the research of urban morphologists is the availability of historical records that document the urban transformation of the study area. However, thus far little work has been done towards an empirical approach to the validation of archival data in this field. Outlined in this paper, therefore, is a new methodology for validating the accuracy of archival records and mapping data, accrued through the process of urban morphological research, so as to establish a reliable platform from which analysis can proceed. The paper particularly addresses the problems of inaccuracies in existing curated historical information, as well as errors in archival research by student assistants, which together give rise to unacceptable levels of uncertainty in the documentation. The paper discusses the problems relating to the reliability of historical information, demonstrates the importance of data verification in urban morphological research, and proposes a rigorous method for objective testing of collected archival data through the use of qualitative data analysis software.

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This study reported on the validation of the psychometric properties, the factorability, validity, and sensitivity of the Dysexecutive Questionnaire (DEX) in 3 clinical and nonclinical samples. A mixed sample of 997 participants—community (n = 663), psychiatric (depressed [n = 92] and anxious [n = 122]), and neurologically impaired (n = 120)—completed self-report questionnaires assessing executive dysfunction, depression, anxiety, stress, general self-efficacy, and satisfaction with life. Before analyses the data were randomly split into 2 subsets (A and B). Exploratory factor analysis performed on Subset A produced a 3-factor model (Factor 1: Inhibition, Factor 2: Volition, and Factor 3: Social Regulation) in which 15 of the original 20 items provided a revised factor structure that was superior to all other structures. A series of confirmatory factor analyses performed on Subset B confirmed that this revised factor structure was valid and reliable. The revised structure, labeled the DEX-R, was found to be a reliable and valid tool for assessing behavioral symptoms of dysexecutive functioning in mixed community, psychiatric, and neurological samples.

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Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.

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Background No tool exists to measure self-efficacy for overcoming lymphedema-related exercise barriers in individuals with cancer-related lymphedema. However, an existing scale measures confidence to overcome general exercise barriers in cancer survivors. Therefore, the purpose of this study was to develop, validate and assess the reliability of a subscale, to be used in conjunction with the general barriers scale, for determining exercise barriers self-efficacy in individuals facing lymphedema-related exercise barriers. Methods A lymphedema-specific exercise barriers self-efficacy subscale was developed and validated using a cohort of 106 cancer survivors with cancer-related lymphedema, from Brisbane, Australia. An initial ten-item lymphedema-specific barrier subscale was developed and tested, with participant feedback and principal components analysis results used to guide development of the final version. Validity and test-retest reliability analyses were conducted on the final subscale. Results The final lymphedema-specific subscale contained five items. Principal components analysis revealed these items loaded highly (> 0.75) on a separate factor when tested with a well-established nine-item general barriers scale. The final five-item subscale demonstrated good construct and criterion validity, high internal consistency (Cronbach’s alpha=0.93) and test-retest reliability (ICC=0.67, p< 0.01). Conclusions A valid and reliable lymphedema-specific subscale has been developed to assess exercise barriers self-efficacy in individuals with cancer-related lymphedema. This scale can be used in conjunction with an existing general exercise barriers scale to enhance exercise adherence in this understudied patient group.

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Abstract Background The purpose of this study was the development of a valid and reliable “Mechanical and Inflammatory Low Back Pain Index” (MIL) for assessment of non-specific low back pain (NSLBP). This 7-item tool assists practitioners in determining whether symptoms are predominantly mechanical or inflammatory. Methods Participants (n = 170, 96 females, age = 38 ± 14 years-old) with NSLP were referred to two Spanish physiotherapy clinics and completed the MIL and the following measures: the Roland Morris Questionnaire (RMQ), SF-12 and “Backache Index” (BAI) physical assessment test. For test-retest reliability, 37 consecutive patients were assessed at baseline and three days later during a non-treatment period. Face and content validity, practical characteristics, factor analysis, internal consistency, discriminant validity and convergent validity were assessed from the full sample. Results A total of 27 potential items that had been identified for inclusion were subsequently reduced to 11 by an expert panel. Four items were then removed due to cross-loading under confirmatory factor analysis where a two-factor model yielded a good fit to the data (χ2 = 14.80, df = 13, p = 0.37, CFI = 0.98, and RMSEA = 0.029). The internal consistency was moderate (α = 0.68 for MLBP; 0.72 for ILBP), test-retest reliability high (ICC = 0.91; 95%CI = 0.88-0.93) and discriminant validity good for either MLBP (AUC = 0.74) and ILBP (AUC = 0.92). Convergent validity was demonstrated through similar but weak correlations between the ILBP and both the RMQ and BAI (r = 0.34, p < 0.001) and the MLBP and BAI (r = 0.38, p < 0.001). Conclusions The MIL is a valid and reliable clinical tool for patients with NSLBP that discriminates between mechanical and inflammatory LBP. Keywords: Low back pain; Psychometrics properties; Pain measurement; Screening tool; Inflammatory; Mechanical

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Despite being used since 1976, Delusions-Symptoms-States-Inventory/states of Anxiety and Depression (DSSI/sAD) has not yet been validated for use among people with diabetes. The aim of this study was to examine the validity of the personal disturbance scale (DSSI/sAD) among women with diabetes using Mater-University of Queensland Study of Pregnancy (MUSP) cohort data. The DSSI subscales were compared against DSM-IV disorders, the Mental Component Score of the Short Form 36 (SF-36 MCS), and Center for Epidemiologic Studies Depression Scale (CES-D). Factor analyses, odds ratios, receiver operating characteristic (ROC) analyses and diagnostic efficiency tests were used to report findings. Exploratory factor analysis and fit indices confirmed the hypothesized two-factor model of DSSI/sAD. We found significant variations in the DSSI/sAD domain scores that could be explained by CES-D (DSSI-Anxiety: 55%, DSSI-Depression: 46%) and SF-36 MCS (DSSI-Anxiety: 66%, DSSI-Depression: 56%). The DSSI subscales predicted DSM-IV diagnosed depression and anxiety disorders. The ROC analyses show that although the DSSI symptoms and DSM-IV disorders were measured concurrently the estimates of concordance remained only moderate. The findings demonstrate that the DSSI/sAD items have similar relationships to one another in both the diabetes and non-diabetes data sets which therefore suggest that they have similar interpretations.