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To evaluate an abbreviated NIH Toolbox Cognition Battery (NIHTB-CB) protocol that can be administered remotely without any in-person assessments, and explore the agreement between prorated scores from the abbreviated protocol and standard scores from the full protocol.
Participant-level age-corrected NIHTB-CB data were extracted from six studies in individuals with a history of stroke, mild traumatic brain injury (mTBI), treatment-resistant psychosis, and healthy controls, with testing administered under standard conditions. Prorated fluid and total cognition scores were estimated using regression equations that excluded the three fluid cognition NIHTB-CB instruments which cannot be administered remotely. Paired t tests and intraclass correlations (ICCs) were used to compare the standard and prorated scores.
Data were available for 245 participants. For fluid cognition, overall prorated scores were higher than standard scores (mean difference = +4.5, SD = 14.3; p < 0.001; ICC = 0.86). For total cognition, overall prorated scores were higher than standard scores (mean difference = +2.7, SD = 8.3; p < 0.001; ICC = 0.88). These differences were significant in the stroke and mTBI groups, but not in the healthy control or psychosis groups.
Prorated scores from an abbreviated NIHTB-CB protocol are not a valid replacement for the scores from the standard protocol. Alternative approaches to administering the full protocol, or corrections to scoring of the abbreviated protocol, require further study and validation.
Validating phase quantification procedures of powder X-ray diffraction (XRD) data for an implementation in an ISO/IEC 17025 accredited environment has been challenging due to a general lack of suitable certified reference materials. The preparation of highly pure and crystalline reference materials and mixtures thereof may exceed the costs for a profitable and justifiable implementation. This study presents a method for the validation of XRD phase quantifications based on semi-synthetic datasets that reduces the effort for a full method validation drastically. Datasets of nearly pure reference substances are stripped of impurity signals and rescaled to 100% crystallinity, thus eliminating the need for the preparation of ultra-pure and -crystalline materials. The processed datasets are then combined numerically while preserving all sample- and instrument-characteristic features of the peak profile, thereby creating multi-phase diffraction patterns of precisely known composition. The number of compositions and repetitions is only limited by computational power and storage capacity. These datasets can be used as input files for the phase quantification procedure, in which statistical validation parameters such as precision, accuracy, linearity, and limits of detection and quantification can be determined from a statistically sound number of datasets and compositions.
Reassurance seeking (RS) is motivated by perceived general and social/relational threats across disorders, yet is often under-recognized because it occurs in covert (i.e. subtle) and overt forms. Covert safety-seeking behaviour may maintain disorders by preventing corrective learning and is therefore important to identify effectively.
This study presents the validation and psychometric analyses of a novel measure of covert and overt, general and social/relational threat-related interpersonal RS.
An initial 30-item measure was administered to an undergraduate sample (N = 1626), as well as to samples of individuals diagnosed with obsessive compulsive disorder (OCD; n = 50), anxiety disorders (n = 60) and depression (n = 30). The data were subjected to exploratory and confirmatory factor analyses, and validation analyses.
An exploratory factor analysis using principal axis factoring with oblique rotation yielded five interpretable factors, after removing four complex items. The resulting 26-item measure, the Covert and Overt Reassurance Seeking Inventory (CORSI), evidenced good convergent and divergent validity and accounted for 54.99% of the total variance after extraction. Factor correlations ranged from r = .268 to .736, suggesting that they may be tapping into unique facets of RS behaviour. In comparison with undergraduate participants, all clinical groups had significantly higher total scores [t (51.80–840) = 3.92–5.84, p < .001]. The CFA confirmed the five-factor model with good fit following the addition of four covariance terms (goodness of fit index = .897, comparative fit index = .918, Tucker–Lewis index = .907, root mean square error approximation = .061).
The CORSI is a brief, yet comprehensive and psychometrically strong measure of problematic RS. With further validation, the CORSI has potential for use within clinical and research contexts.
A novel underwater vehicle configuration with an operating principle as the Sepiida animal is presented and developed in this paper. The mathematical equations describing the movements of the vehicle are obtained using the Newton–Euler approach. An analysis of the dynamic model is done for control purposes. A prototype and its embedded system are developed for validating analytically and experimentally the proposed mathematical representation. A real-time characterization of one mass is done to relate the pitch angle with the radio of displacement of the mass. In addition, first validation of the closed-loop system is done using a linear controller.
In this article, we investigate the problem of parameter identification of spatial–temporal varying processes described by a general nonlinear partial differential equation and validate the feasibility and robustness of the proposed algorithm using a group of coordinated mobile robots equipped with sensors in a realistic diffusion field. Based on the online parameter identification method developed in our previous work using multiple mobile robots, in this article, we first develop a parameterized model that represents the nonlinear spatially distributed field, then develop a parameter identification scheme consisting of a cooperative Kalman filter and recursive least square method. In the experiments, we focus on the diffusion field and consider the realistic scenarios that the diffusion field contains obstacles and hazard zones that the robots should avoid. The identified parameters together with the located source could potentially assist in the reconstruction and monitoring of the field. To validate the proposed methods, we generate a controllable carbon dioxide (CO2) field in our laboratory and build a static CO2 sensor network to measure and calibrate the field. With the reconstructed realistic diffusion field measured by the sensor network, a multi-robot system is developed to perform the parameter identification in the field. The results of simulations and experiments show satisfactory performance and robustness of the proposed algorithms.
The Eating Assessment in Toddlers FFQ (EAT FFQ) has been shown to have good reliability and comparative validity for ranking nutrient intakes in young children. With the addition of food items (n 4), we aimed to re-assess the validity of the EAT FFQ and estimate calibration factors in a sub-sample of children (n 97) participating in the Growing Up Milk – Lite (GUMLi) randomised control trial (2015–2017). Participants completed the ninety-nine-item GUMLi EAT FFQ and record-assisted 24-h recalls (24HR) on two occasions. Energy and nutrient intakes were assessed at months 9 and 12 post-randomisation and calibration factors calculated to determine predicted estimates from the GUMLi EAT FFQ. Validity was assessed using Pearson correlation coefficients, weighted kappa (κ) and exact quartile categorisation. Calibration was calculated using linear regression models on 24HR, adjusted for sex and treatment group. Nutrient intakes were significantly correlated between the GUMLi EAT FFQ and 24HR at both time points. Energy-adjusted, de-attenuated Pearson correlations ranged from 0·3 (fibre) to 0·8 (Fe) at 9 months and from 0·3 (Ca) to 0·7 (Fe) at 12 months. Weighted κ for the quartiles ranged from 0·2 (Zn) to 0·6 (Fe) at 9 months and from 0·1 (total fat) to 0·5 (Fe) at 12 months. Exact agreement ranged from 30 to 74 %. Calibration factors predicted up to 56 % of the variation in the 24HR at 9 months and 44 % at 12 months. The GUMLi EAT FFQ remained a useful tool for ranking nutrient intakes with similar estimated validity compared with other FFQ used in children under 2 years.
To conduct a systematic review of studies for the validation of semiquantitative FFQ (SFFQ) that assess food intake in adults.
The authors conducted a systematic search in PubMed for articles published as late as January 2020 in Spanish, English, French and Portuguese. Individual searches (twelve in total) paired three hyphenated and non-hyphenated variations of ‘semiquantitative food frequency questionnaire’ with both ‘validity’ and ‘validation’ using the ‘all fields’ and the ‘title/abstract’ retrieval categories. Independent extraction of articles was performed by four authors using predefined data fields.
We searched for original SFFQ validation studies that analysed general diet composition (nutrients with or without food groups or energy analysis) in healthy adults, in any setting, and that also reported correlation coefficients.
Sixty articles were included. The preferred comparison standard for validation was food records (n 37). The main correlation coefficients used were Pearson’s (n 41), and validity coefficients varied from −0·45 to 1. Most correlation coefficients were adjusted by energy (twelve studies presented only crude values). The elements mentioned most frequently were energy, macronutrients, cholesterol, SFA, PUFA, fibre, vitamin C, Ca and Fe.
Although all these SFFQ are reported as validated, coefficients may vary across groups of foods and nutrients. Based on our findings, we suggest researchers to consult our revision before choosing a SFFQ and to review important issues about them, such as their validation, number of items, number of participants, etc. Systematic Review Registration: PROSPERO number CRD42017064716. Available at: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42017064716.
Catheter-related blood-stream infections (CRBSIs) are the most common healthcare-associated blood-stream infections. They can be diagnosed by either semi-quantitative or quantitative methods, which may differ in diagnostic accuracy. A meta-analysis was undertaken to compare the diagnostic accuracy of semi-quantitative and quantitative methods for CRBSI. A systematic search of Medline, Scopus, Cochrane and Embase databases up to January 2020 was performed and subjected to a QUADAS (quality assessment of diagnostic accuracy studies 2) tool to evaluate the risk of bias among studies. The pooled sensitivity and specificity of the methods were determined and heterogeneity was evaluated using the χ2 test and I2. Publication bias was assessed using a Funnel plot and the Egger's test. In total, 45 studies were analysed with data from 11 232 patients. The pooled sensitivity and specificity of semi-quantitative methods were 85% (95% CI 79–90%) and 84% (95% CI 79–88%), respectively; and for quantitative methods were 85% (95% CI 79–90%) and 95% (95% CI 91–97%). Considerable heterogeneity was statistically evident (P < 0.001) by both methods with a correspondingly symmetrical Funnel plot that was confirmed by a non-significant Deek's test. We conclude that both semi-quantitative and quantitative methods are highly useful for screening for CRBSI in patients and display high sensitivity and specificity. Quantitative methods, particularly paired quantitative cultures, had the highest sensitivity and specificity and can be used to identify CRBSI cases with a high degree of certainty.
To evaluate the validity and reproducibility of a 152-item semi-quantitative FFQ (SFFQ) for estimating flavonoid intakes.
Over a 1-year period, participants completed two SFFQ and two weighed 7-d dietary records (7DDR). Flavonoid intakes from the SFFQ were estimated separately using Harvard (SFFQHarvard) and Phenol-Explorer (SFFQPE) food composition databases. 7DDR flavonoid intakes were derived using the Phenol-Explorer database (7DDRPE). Validity was assessed using Spearman’s rank correlation coefficients deattenuated for random measurement error (rs), and reproducibility was assessed using rank intraclass correlation coefficients.
This validation study included primarily participants from two large observational cohort studies.
Six hundred forty-one men and 724 women.
When compared with two 7DDRPE, the validity of total flavonoid intake assessed by SFFQPE was high for both men and women (rs = 0·77 and rs = 0·74, respectively). The rs for flavonoid subclasses ranged from 0·47 for flavones to 0·78 for anthocyanins in men and from 0·46 for flavonols to 0·77 for anthocyanins in women. We observed similarly moderate (0·4–0·7) to high (≥0·7) validity when using SFFQHarvard estimates, except for flavonesHarvard (rs = 0·25 for men and rs = 0·19 for women). The SFFQ demonstrated high reproducibility for total flavonoid and flavonoid subclass intake estimates when using either food composition database. The intraclass correlation coefficients ranged from 0·69 (flavonolsPE) to 0·80 (proanthocyanidinsPE) in men and from 0·67 (flavonolsPE) to 0·77 (flavan-3-ol monomersHarvard) in women.
SFFQ-derived intakes of total flavonoids and flavonoid subclasses (except for flavones) are valid and reproducible for both men and women.
This paper reports on laboratory and field experimental results for controlled robotic manipulators operating on moving platforms with unmodeled dynamics. The aim is to validate theoretical predictions for the dependence on control parameters of an adaptive control strategy. In addition, the results provide insight into different discretizations of the continuous-time formulation, suggesting the most suitable discretization scheme for hardware implementation. The second set of experimental results, obtained from an implementation of the control framework for synchronization and consensus in networks of robotic manipulators, similarly validate theoretical predictions on the sensitivity to network communication delays.
The accuracy of sea-ice motion products provided by the National Snow and Ice Data Center (NSIDC) and the Ocean and Sea Ice Satellite Application Facility (OSI-SAF) was validated with data collected by ice drifters that were deployed in the western Arctic Ocean in 2014 and 2016. Data from both NSIDC and OSI-SAF products exhibited statistically significant (p < 0.001) correlation with drifter data. The OSI-SAF product tended to overestimate ice speed, while underestimation was demonstrated for the NSIDC product, especially for the melt season and the marginal ice zone. Monthly Lagrangian trajectories of ice floes were reconstructed using the products. Larger spatial variability in the deviation between NSIDC and drifter trajectories was observed than that of OSI-SAF, and seasonal variability in the deviation for NSIDC was observed. Furthermore, trajectories reconstructed using the NSIDC product were sensitive to variations in sea-ice concentration. The feasibility of using remote-sensing products to characterize sea-ice deformation was assessed by evaluating the distance between two arbitrary positions as estimated by the products. Compared with the OSI-SAF product, relative errors are lower (<11.6%), and spatial-temporal resolutions are higher in the NSIDC product, which makes it more suitable for estimating sea-ice deformation.
Economic models play a central role in the decision-making process of the National Institute for Health and Care Excellence (NICE). Inadequate validation methods allow for errors to be included in economic models. These errors may alter the final recommendations and have a significant impact on outcomes for stakeholders.
To describe the patterns of technical errors found in NICE submissions and to provide an insight into the validation exercises carried out by the companies prior to submission.
All forty-one single technology appraisals (STAs) completed in 2017 by NICE were reviewed and all were on medicines. The frequency of errors and information on their type, magnitude, and impact was extracted from publicly available NICE documentation along with the details of model validation methods used.
Two STAs (5 percent) had no reported errors, nineteen (46 percent) had between one and four errors, sixteen (39 percent) had between five and nine errors, and four (10 percent) had more than ten errors. The most common errors were transcription errors (29 percent), logic errors (29 percent), and computational errors (25 percent). All STAs went through at least one type of validation. Moreover, errors that were notable enough were reported in the final appraisal document (FAD) in eight (20 percent) of the STAs assessed but each of these eight STAs received positive recommendations.
Technical errors are common in the economic models submitted to NICE. Some errors were considered important enough to be reported in the FAD. Improvements are needed in the model development process to ensure technical errors are kept to a minimum.
The aim of the current study was to evaluate the accuracy of the new software eAT24 used to assess dietary intake in the National Food, Nutrition and Physical Activity Survey (IAN-AF) against urinary biomarkers: N (nitrogen), K (potassium) and Na (sodium).
We conducted a cross-sectional study. Two non-consecutive 24-h dietary recalls (24-HDR) were applied, and a 24-h urine sample was collected. We examined differences between estimates from dietary and urine measures, Pearson correlation coefficients were calculated and the Bland–Altman plots were drawn. Multiple linear regression was used to evaluate the factors associated with the difference between estimates.
Sub-sample from the Portuguese IAN-AF sampling frame.
Ninety-five adults (men and women) aged 18–84 years.
The estimated intake calculated using the dietary recall data was lower than that estimated from urinary excretion for the three biomarkers studied (protein 94·3 v. 100·4 g/d, K 3212 v. 3416 mg/d and Na 3489 v. 4003 mg/d). Considering 2 d of recall, the deattenuated correlation coefficients were 0·33, 0·64 and 0·26 for protein, K and Na, respectively. For protein, differences between dietary and urinary estimates varied according to BMI (β = −1·96, P = 0·017). The energy intake and 24-h urine volume were significantly associated with the difference between estimates for protein (β = 0·03, P < 0·001 and β = −0·02, P = 0·002, respectively), K (β = 0·71, P < 0·001 and β = −0·42, P = 0·040, respectively) and Na (β = 1·55, P < 0·001 and β = −0·81, P = 0·011, respectively).
The new software eAT24 performed well in estimating protein and K intakes, but lesser so in estimating Na intake, using two non-consecutive 24-HDR.
To assess the relative validity of a FFQ developed for the Pelotas Birth Cohort Studies.
Participants completed a ninety-two-food-item FFQ and then answered two 24-h recalls (24HR), one in-person interview and a second one by telephone, administered 14–28 d apart. Median and relative differences of energy, fifteen nutrients and eleven food groups were estimated based on the FFQ and the average of two 24HR. Nutrients were log-transformed and energy-adjusted using residual method. Validity was assessed by crude, energy-adjusted and de-attenuated Pearson and Lin’s concordance correlation coefficients. Agreement of quartiles and weighted κ were performed. Differences in energy and nutrient estimations between methods were plotted in Bland–Altman graphs.
Pelotas, southern Brazil.
Two hundred fifty-four participants randomly selected from the 1993 Pelotas Birth Cohort during the 22-year follow-up (2015).
The FFQ overestimated energy and most nutrients and food groups compared with the two 24HR. Energy-adjusted and de-attenuated Pearson correlation coefficients ranged from 0·21 to 0·66. The highest energy-adjusted and de-attenuated concordance correlation coefficients were observed for Ca (0·48), niacin (0·32), Na (0·29), vitamin C (0·28) and riboflavin (0·25). The percentage of nutrients classified into the same and opposite quartiles ranged from 36·5 to 60·3 %, and from 4·8 to 19·1 %, respectively. Weighted κ was moderate for Ca (0·51), beans and legumes (0·50) and milk and dairies (0·49).
The FFQ provides a reasonable dietary intake assessment for habitual food consumption. However, the relative validity was weak for specific nutrients and food groups.
The dietary insulin index directly estimates the postprandial insulin secretion potential of foods, whereas the empirical dietary index for hyperinsulinaemia (EDIH) assesses the insulinaemic potential of usual diets based on fasting plasma C-peptide, and is primarily reflective of insulin resistance. It is unknown whether these insulin-related indices are predictive of an integrated measure of insulin secretion. We conducted a cross-sectional analysis that included 293 non-diabetic men with 24-h urinary C-peptide data from the Men’s Lifestyle Validation Study. EDIH, dietary insulin index and dietary insulin load were calculated using validated FFQ. We conducted multivariable-adjusted linear regression to estimate relative and absolute concentrations of 24-h urinary C-peptide. In multivariable-adjusted models, we found a significant positive association between all three insulin-related dietary indices and 24-h urinary C-peptide (P < 0·05). Relative concentrations of 24-h urinary C-peptide per 1-sd increase in insulin-related dietary indices were 1·12 (95 % CI 1·02, 1·23) for EDIH, 1·18 (95 % CI 1·07, 1·29) for dietary insulin index and 1·16 (95 % CI 1·06, 1·27) for dietary insulin load. When we further adjusted for BMI, the association was attenuated for EDIH, to 1·07 (95 % CI 0·98, 1·16), and remained unchanged for dietary insulin index and dietary insulin load. In conclusion, EDIH, dietary insulin index and dietary insulin load were predictive of integrated insulin secretion assessed by 24-h urinary C-peptide. Findings after adjustment for BMI appear to confirm the relation of EDIH to insulin resistance and dietary insulin index/load to insulin secretion; the respective constructs of the two dietary indices.
How well do vignette designs capture actual behaviour in the real world? This study employs original survey data featuring both hypothetical vignettes and behavioural questions in order to assess the external validity of descriptive and causal inferences in survey experiments. The survey was conducted in a three-province, probability-proportional-to-size sample of 1,897 rural residents in China and focuses on the legal mobilization of citizens in response to grievances involving land rights. In terms of descriptive inference, we find that relative to the behavioural benchmark, hypothetical vignettes significantly over-estimate legal mobilization in response to a grievance, particularly for higher-cost actions like petitioning the government and litigating in court. We find that data from hypothetical vignettes affect causal inference as well, producing significantly different results regarding the effect of political connections and legal knowledge on legal mobilization. The study makes a contribution by identifying conditions under which hypothetical vignettes are less likely to produce valid inference. It engages a rich literature on disputing and legal mobilization in the field of Chinese politics and helps to resolve debates over the role of political connections and legal knowledge.
This chapter focuses on model evaluation and selection in Hierarchical Modelling of Species Communities (HMSC). It starts by noting that even if there are automated procedures for model selection, the most important step is actually done by the ecologist when deciding what kind of models will be fitted. The chapter then discusses different ways of measuring model fit based on contrasting the model predictions with the observed data, as well as the use of information criteria as a method for evaluating model fit. The chapter first discusses general methods that can be used to compare models that differ either in their predictors or in their structure, e.g. models with different sets of environmental covariates, models with and without spatial random effects, models with and without traits or phylogenetic information or models that differ in their prior distributions. The chapter then presents specific methods for variable selection, aimed at comparing models that are structurally identical but differ in the included environmental covariates: variable selection by the spike and slab prior approach, and reduced rank regression that aims at combining predictors to reduce their dimensionality.
This chapter covers the basics of generalised linear mixed models in the univariate context of single-species distribution modelling. The chapter starts by discussing how species distribution models relate to the theory on environmental species niches. The modelling part of the chapter first introduces the linear model, then moves to generalised models, then to mixed models with both fixed and random effects, and finally describes how the explained variance can be partitioned among the explanatory variables. The applied part of the chapter uses both simulated and real data to illustrate how the R-package HMSC-R can be used to analyse generalised linear mixed models. While these analyses are rather standard and could also be conducted with many other packages, the reader is encouraged to go through them, as they provide the simplest way of becoming familiar with the syntax of HMSC-R.
We aimed to assess the validity of maternal recall of exclusive breastfeeding (EBF) at 3 months obtained 12 months after childbirth.
A population-based birth cohort study. The gold standard is maternal report of EBF at the age of 3 months (yes or no) and age of introduction of other foods in the infant’s diet. EBF was considered when the mother reported that no liquid, semi-solid or solid food was introduced up to that moment. The variable to be validated was obtained at 12 months after childbirth when the mother was asked about the age of food introduction. The prevalence of EBF at 3 months, and sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and accuracy of 12-month recall with 95 % CI were calculated.
3700 mothers of participants of the Pelotas 2004 Birth Cohort.
The prevalence of EBF at 3 months was 27·8 % (95 % CI 26·4, 29·3) and 49·0 % (95 % CI 47·4, 50·6) according to gold standard and maternal recall, respectively. The sensitivity of maternal recall at 12 months was 98·3 % (95 % CI 97·4, 99·0), specificity 70·0 % (95 % CI 68·2, 71·7), PPV 55·8 % (95 % CI 53·4, 58·1), NPV 99·1 % (95 % CI 98·6, 99·5) and accuracy 77·9 % (95 % CI 76·6, 79·2). When the analyses were stratified by maternal and infant characteristics, the sensitivity remained around 98 %, and the specificity ranged from 64·4 to 81·8 %.
EBF recalled at the end of the first year of infant’s life is a valid measure to be used in epidemiological investigations.
This study aimed to validate a nutrition knowledge questionnaire appropriate for use in Australia.
Nutrition knowledge is essential in establishing and maintaining strategies that reduce the burden of disease and promote wellbeing. The General Nutrition Knowledge Questionnaire (GNKQ) was developed in the United Kingdom in 1999 and validated for Australia in 2008. Changes in national nutrition recommendations and food availability prompted the redevelopment and revalidation of the UK questionnaire in 2016. However, the Australian questionnaire had not been subsequently updated.
Content validity was determined using a sample of academic dietitians in Australia (n 8). Face validity was undertaken with retail employees (n 11) whose highest level of education was secondary school. Ninety-three undergraduate nutrition and engineering students at Queensland University of Technology completed the questionnaire for construct validity, and nineteen students were contacted a week later for test–retest reliability.
In the 117-scored questionnaire, nutrition students scored consistently higher in each of the four sections and overall (87 %, M 102, IQR 95, 107) compared with engineering students (77 %, M 82, IQR 76, 87·25, P < 0·01). Internal reliability of the questionnaire was high (α = 0·92) as was test–retest reliability (rs = 0·96, ICC2,1 = 0·99). AUS-R NKQ determined significant differences between individuals with known higher levels of nutrition knowledge and obtained high validity, reliability and consistency within an Australian sample.
AUS-R NKQ refined through this research is valid and would be an appropriate questionnaire for assessing the effectiveness of nutrition knowledge-based interventions for public health programmes, clinicians and researchers.