Within-subject Measures Research Articles

Repeatability of vibration-controlled transient elastography versus magnetic resonance elastography in patients with cirrhosis: A prospective study.

Magnetic resonance elastography (MRE) and vibration-controlled transient elastography (VCTE) have the potential to assess disease progression; however, repeatability data in people with cirrhosis are lacking. We aimed to assess the effect of disease severity on measurement variability and contribute to the evidentiary basis for the qualification of repeating liver stiffness measurements (LSM) in practice and research. This prospective study included 49 adult participants (58.3% female) with cirrhosis who underwent same-day repeat LSM examinations. The primary outcome was the same-day, same-operator repeatability coefficient% (RC%) and the within-case coefficient of variation (wCV) for each modality. Secondary outcomes include the intra-class correlation coefficient (ICC). The relationship between measurement variability (interquartile for VCTE, standard deviation for MRE) and disease severity (mean liver stiffness) was evaluated by linear regression with the coefficient of determination R2 reported. Same-day repeat MRE and VCTE exams were prospectively conducted in 33 and 45 participants, respectively. The RC% appeared 82% higher for VCTE versus MRE (38% vs. 21%), with consistent findings in head-to-head analyses. The wCV for VCTE and MRE was 14% and 8% respectively, indicating VCTE has 75% higher within-subject measurement variation than MRE. ICC was excellent for LSM by VCTE (0.92) and MRE (0.96). Measurement variability increased with mean liver stiffness for VCTE (R2 = 0.78) and MRE (R2 = 0.93). Both VCTE and MRE demonstrated increased measurement variability with disease severity. However, MRE outperformed VCTE in terms of technical repeatability in patients with cirrhosis. These repeatability estimates may improve the qualification of NITs in practice.

Load and recovery monitoring in Swiss top-level youth soccer players: Exploring the associations of a new web application-based score with recognised load measures

Load and recovery monitoring in Swiss top-level youth soccer players: Exploring the associations of a new web application-based score with recognised load measures

Does visuospatial neglect contribute to standing balance within the first 12 weeks post-stroke? A prospective longitudinal cohort study.

Visuospatial neglect (VSN) has been suggested to limit standing balance improvement post-stroke. However, studies investigating this association longitudinally by means of repeated within-subject measurements early post-stroke are lacking. This prospective longitudinal cohort study evaluates the longitudinal association of egocentric and allocentric VSN severity with 1) standing balance independence and 2) postural control and weight-bearing asymmetry (WBA) during quiet standing, in the first 12 weeks post-stroke. Thirty-six hemiplegic individuals after a first-ever unilateral stroke were evaluated at weeks 3, 5, 8 and 12 post-stroke. Egocentric and allocentric VSN severity were evaluated using the Broken Hearts Test. The standing unperturbed item of the Berg Balance Scale (BBS-s) was used to clinically evaluate standing independence. Posturographic measures included measures of postural control (mediolateral (ML)/anteroposterior (AP) net center-of-pressure velocities (COPvel)) and WBA during quiet standing. A linear mixed model was used to examine longitudinal associations between egocentric and allocentric VSN, and BBS-s, COPvel-ML, COPvel-AP and WBA within the first 12 weeks post-stroke. Egocentric (β = -0.08, 95%CI[-0.15;-0.01], P = .029) and allocentric VSN severity (β = -0.09, 95%CI[-0.15; -0.04], P = .002) were significant independent factors for BBS-s scores in the first 12 weeks post-stroke. Egocentric and allocentric VSN were no significant independent factors for COPvel-ML, COPvel-AP and WBA in the first 12 weeks post-stroke. Allocentric and egocentric VSN severity were significantly associated with decreased standing independence, but not impaired postural control or greater asymmetric weight-bearing, in the early subacute post-stroke phase. This may involve traditional VSN measures being not sensitive enough to detect fine-grained VSN deficits due to a ceiling effect between 5 and 8 weeks post-stroke, once the individual regains standing ability. Future studies may require more sensitive VSN measurements to detect such deficits. Trial registration Clinicaltrials.gov. unique identifier NCT05060458.

Individual Differences in the Susceptibility to the Feature-Positive Effect

Abstract: The feature-positive effect (FPE) is the phenomenon that learning organisms are better at detecting the association between two present stimuli than between the absence of one stimulus and the presence of the other. Although the FPE was first described over 50 years ago, it remains an ill-studied and ill-understood bias. Nonetheless, the FPE can have far-reaching negative consequences in various decision-making contexts. In the present contribution, an attempt was made to document the FPE with a within-subject measurement. Initial psychometric analyses (PCA, Cronbach’s α, test–retest reliability, and concurrent validity correlations) suggest that such intraindividual measurement of the FPE is indeed possible. Consequently, individuals can be expected to differ in their susceptibility to the FPE. This individual difference factor can be measured with the described feature-positive effect test (FPET), which opens new research avenues in which FPE-proneness is taken as a starting point.

Robust neural tracking of linguistic speech representations using a convolutional neural network

Objective. When listening to continuous speech, populations of neurons in the brain track different features of the signal. Neural tracking can be measured by relating the electroencephalography (EEG) and the speech signal. Recent studies have shown a significant contribution of linguistic features over acoustic neural tracking using linear models. However, linear models cannot model the nonlinear dynamics of the brain. To overcome this, we use a convolutional neural network (CNN) that relates EEG to linguistic features using phoneme or word onsets as a control and has the capacity to model non-linear relations. Approach. We integrate phoneme- and word-based linguistic features (phoneme surprisal, cohort entropy (CE), word surprisal (WS) and word frequency (WF)) in our nonlinear CNN model and investigate if they carry additional information on top of lexical features (phoneme and word onsets). We then compare the performance of our nonlinear CNN with that of a linear encoder and a linearized CNN. Main results. For the non-linear CNN, we found a significant contribution of CE over phoneme onsets and of WS and WF over word onsets. Moreover, the non-linear CNN outperformed the linear baselines. Significance. Measuring coding of linguistic features in the brain is important for auditory neuroscience research and applications that involve objectively measuring speech understanding. With linear models, this is measurable, but the effects are very small. The proposed non-linear CNN model yields larger differences between linguistic and lexical models and, therefore, could show effects that would otherwise be unmeasurable and may, in the future, lead to improved within-subject measures and shorter recordings.

Observational Study of Pediatric Cochlear Implant Recipients: Two-year Follow-up Outcomes.

The aim of this study was to evaluate the improvements in quality of life and auditory performance via a descriptive report using patient-related outcomes measures in a group of children with cochlear implants (CI). This was a longitudinal and retrospective study based on the analysis of patient records of a total of 28 children with CI, 18 of whom had bilateral (64.3%) and 10 had unilateral (35.7%). The study included repeated within-subject measures of Hearing Implants Quality of Life (CuHI-QoL), Categories of Auditory Performance (CAP-II), Speech, Spatial, and Qualities of Hearing scale-Parents' version (SSQ-P) scales, and Implant Recipient Follow-up (IRF) form at 6-month intervals from baseline up to 24 months. During the 2-year follow-up assessments, all children with CI showed statistically significant improvement over time in their CAPII, SSQ-P, CuHI-QoL, and IRF scores (p<0.001). The most significant increase in scores occurred within the first six months following the baseline and then continued to increase gradually at a slower pace over time. A moderate negative relationship was found between the age of implantation and SSQ-P and family satisfaction scores of IRF (p<0.05). Family expectations, overall well-being, quality of life, auditory, and verbal skills increase positively with earlier CI intervention. Moreover, the subjective assessment results showed that parents-positive attitudes toward implantation, and willingness to recommend it to others have steadily increased in time. Although the cohort is relatively small and variable, the results offer a descriptive view to outcomes in real-world practice.

Exploring interindividual differences in fasting and postprandial insulin sensitivity adaptations in response to sprint interval exercise training

ABSTRACT Previous studies have concluded that wide variance in changes in insulin sensitivity markers following exercise training demonstrates heterogeneity in individual trainability. However, these studies frequently don’t account for technical, biological, and random within-subject measurement error. We used the standard deviation of individual responses (SDIR) to determine whether interindividual variability in trainability exists for fasting and postprandial insulin sensitivity outcomes following low-volume sprint interval training (SIT). We pooled data from 63 untrained participants who completed 6 weeks of SIT (n = 49; VO2max: 35 (7) mL⋅kg−1⋅min−1) or acted as no-intervention controls (n = 14; VO2max: 34 (6) mL⋅kg−1⋅min−1). Fasting and oral glucose tolerance test (OGTT)-derived measures of insulin sensitivity were measured pre- and post-intervention. SDIR values were positive and exceeded a small effect size threshold for changes in fasting glucose (SDIR = 0.27 [95%CI 0.07,0.38] mmol⋅L−1), 2-h OGTT glucose (SDIR = 0.89 [0.22,1.23] mmol⋅L−1), glucose area-under-the-curve (SDIR = 66.4 [−81.5,124.3] mmol⋅L−1⋅120min−1) and The Cederholm Index (SDIR = 7.2 [−16.0,19.0] mg⋅l2⋅mmol−1⋅mU−1⋅min−1), suggesting meaningful individual responses to SIT, whilst SDIR values were negative for fasting insulin, fasting insulin resistance and insulin AUC. For all variables, the 95% CIs were wide and/or crossed zero, highlighting uncertainty about the existence of true interindividual differences in exercise trainability. Only 2–22% of participants could be classified as responders or non-responders with more than 95% certainty. Our findings demonstrate it cannot be assumed that variation in changes in insulin sensitivity following SIT is attributable to inherent differences in trainability, and reiterate the importance of accounting for technical, biological, and random error when examining heterogeneity in health-related training adaptations. Highlights This study tested whether true interindividual variability exists for changes in insulin sensitivity and glyceamic control following 6-weeks of low volume sprint interval training (SIT). The high level of technical, biological, and random error associated with repeated measurements of insulin sensitivity and glycaemic control, means we can neither confidently conclude that there is evidence of true interindividual differences in the trainability of these outcomes following SIT, nor confidently identify responders or non-responders for such parameters. Researchers contrasting responders vs. non-responders for a given parameter, either to understand mechanisms of adaptation and/or develop physiological/genetic/epigenetic predictors of response, need to be aware that identification of responders and non-responders with sufficient certainty may not be achievable for parameters with a high level of technical, biological, and random error.

Disentangling the Influence of Data Contamination in Growth Curve Modeling: A Median Based Bayesian Approach

Growth curve models (GCMs), with their ability to directly investigate within-subject change over time and between-subject differences in change for longitudinal data, are widely used in social and behavioral sciences. While GCMs are typically studied with the normal distribution assumption, empirical data often violate the normality assumption in applications. Failure to account for the deviation from normality in data distribution may lead to unreliable model estimation and misleading statistical inferences. A robust GCM based on conditional medians was recently proposed and outperformed traditional growth curve modeling when outliers are present resulting in nonnormality. However, this robust approach was shown to perform less satisfactorily when leverage observations existed. In this work, we propose a robust double medians growth curve modeling approach (DOME GCM) to thoroughly disentangle the influence of data contamination on model estimation and inferences, where two conditional medians are employed for the distributions of the within-subject measurement errors and of random effects, respectively. Model estimation and inferences are conducted in the Bayesian framework, and Laplace distributions are used to convert the optimization problem of median estimation into a problem of obtaining the maximum likelihood estimator for a transformed model. A Monte Carlo simulation study has been conducted to evaluate the numerical performance of the proposed approach, and showed that the proposed approach yields more accurate and efficient parameter estimates when data contain outliers or leverage observations. The application of the developed robust approach is illustrated using a real dataset from the Virginia Cognitive Aging Project to study the change of memory ability.

How selves differ within and across cognitive domains: self-prioritisation, self-concept, and psychiatric traits

BackgroundHow we build and maintain representations of ourselves involves both explicit features which are consciously accessible on reflection and implicit processes which are not, such as attentional biases. Understanding relations between different ways of measuring self-cognition both within and across such cognitive domains is important for understanding how selves may differ from one another, and whether self-cognition is best understood as largely uni-dimensional or more multi-dimensional. Further, uncovering this structure should inform research around how self-cognition relates to psychiatric and psychological conditions. This study explores the relations between different constructs of self-cognition and how variability within them relates to psychiatric traits.MethodsOur final dataset includes within-subject (n = 288, general population) measures of explicit self-concept (using both the Self Concept Clarity Scale and Self Concept and Identity Measure), implicit self-prioritisation in a shape-label matching task (for both reaction time and sensitivity) and measurement of traits for five psychiatric conditions (autism, borderline personality disorder, schizophrenia, depression and anxiety). We first test whether self-cognitive measures within and across domains are correlated within individuals. We then test whether these dimensions of self-cognition support a binary distinction between psychiatric conditions that either are or are not characterised in terms of self, or whether they support self-cognition as transdiagnostically predictive of the traits associated with psychiatric conditions. To do this we run a series of planned correlations, regressions, and direct correlation comparison statistics.ResultsResults show that implicit self-prioritisation measures were not correlated with the explicit self-concept measures nor the psychiatric trait measures. In contrast, all the psychiatric traits scores were predicted, to varying degrees, by poorer explicit self-concept quality. Specifically, borderline personality disorder traits were significantly more strongly associated with composite explicit self-concept measures than any of depression, anxiety, or autism traits scores were.ConclusionsOur results suggest that selves can differ considerably, along different cognitive dimensions. Further, our results show that self-cognition may be a promising feature to include in future dimensional characterisations of psychiatric conditions, but care should be taken to choose relevant self-cognitive domains.

The Effectiveness of Unilateral Cochlear Implantation on Performance-Based and Patient-Reported Outcome Measures in Finnish Recipients.

Understanding speech is essential for adequate social interaction, and its functioning affects health, wellbeing, and quality of life (QoL). Untreated hearing loss (HL) is associated with reduced social activity, depression and cognitive decline. Severe and profound HL is routinely rehabilitated with cochlear implantation. The success of treatment is mostly assessed by performance-based outcome measures such as speech perception. The ultimate goal of cochlear implantation, however, is to improve the patient’s QoL. Therefore, patient-reported outcomes measures (PROMs) would be clinically valuable as they assess subjective benefits and overall effectiveness of treatment. The aim of this study was to assess the patient-reported benefits of unilateral cochlear implantation in an unselected Finnish patient cohort of patients with bilateral HL. The study design was a prospective evaluation of 118 patients. The patient cohort was longitudinally followed up with repeated within-subject measurements preoperatively and at 6 and 12 months postoperatively. The main outcome measures were one performance-based speech-in-noise (SiN) test (Finnish Matrix Sentence Test), and two PROMs [Finnish versions of the Speech, Spatial, Qualities of Hearing questionnaire (SSQ) and the Nijmegen Cochlear Implant Questionnaire (NCIQ)]. The results showed significant average improvements in SiN scores, from +0.8 dB signal-to-noise ratio (SNR) preoperatively to −3.7 and −3.8 dB SNR at 6 and12 month follow-up, respectively. Significant improvements were also found for SSQ and NCIQ scores in all subdomains from the preoperative state to 6 and 12 months after first fitting. No clinically significant improvements were observed in any of the outcome measures between 6 and 12 months. Preoperatively, poor SiN scores were associated with low scoring in several subdomains of the SSQ and NCIQ. Poor preoperative SiN scores and low PROMs scoring were significantly associated with larger postoperative improvements. No significant association was found between SiN scores and PROMs postoperatively. This study demonstrates significant benefits of cochlear implantation in the performance-based and patient-reported outcomes in an unselected patient sample. The lack of association between performance and PROMs scores postoperatively suggests that both capture unique aspects of benefit, highlighting the need to clinically implement PROMs in addition to performance-based measures for a more holistic assessment of treatment benefit.

Simulations found within-subject measurement variation in glycaemic measures may cause overdiagnosis of prediabetes and diabetes

ObjectiveTo determine the impact of test measurement variation on misclassification of prediabetes and diabetes in the US adult population. Study Design and SettingData from adults with no prior diagnosis of diabetes in the 2015 to 2016 National Health and Nutrition Examination Survey (NHANES) were used to simulate populations of US adults eligible for screening. Estimates of measurement variation were applied to each simulated individual's true values to generate observed values for up to five repeated screens. Results: UnderdiagnosisFor 100,000 people assessed according to ADA or USPSTF guidelines, no people with true values in the diabetes range would be underdiagnosed as normal after one screen, and between 64 and 138 people would be misclassified with prediabetes after five re-screens (depending on guideline and test used). OverdiagnosisFor 100,000 people assessed according to the guidelines, between 1,602 and 2,233 people with true values in the normal range would be over diagnosed with prediabetes after 3 re-screens. A further 627 to 1,672 people with true values in the prediabetes range would be over diagnosed with diabetes after 5 re-screens. ConclusionMeasurement variation may cause overdiagnosis of prediabetes and diabetes, as well as apparent “progression” or “regression” of either condition.

Liver and Spleen Stiffness Surveillance Through Elastography During and After Direct-Acting Antiviral Therapy in Patients With Chronic Hepatitis C.

Direct-acting antiviral agents achieve a high cure rate, resulting in early hepatic necroinflammatory resolution and sustained fibrosis regression. This study aimed to obtain longitudinal, concurrent within-subject measurements of liver stiffness (LS) and spleen stiffness (SS) and their correlates over time. Participants with hepatitis C (n=592) receiving direct-acting antiviral-based therapy were monitored through point shear-wave elastography from the treatment baseline (TW0) across follow-up visits in terms of LS and SS. Generalized linear mixed modeling indicated that all LS values (2301 visits) were negatively correlated with the follow-up times (all P < .05) from TW0 to 24 weeks (PW24) after the end of treatment (EOT) and positively correlated with baseline LS values (P < .001). The slopes of declines (preceding minus next) differed significantly (P < .001) between TW0-TW4 (treatment week 4) (0.060 [-0.050 to 0.225] meter/second/month [m/s/mo]) and TW4-EOT (0.010 [-0.030 to 0.075] m/s/mo). All SS values (1704 visits) were negatively correlated with time only at PW24 (P < .001) and positively correlated with baseline SS values (P < .001). The slopes of the SS values differed significantly (P < .001) only between EOT-PW12 (-0.010 [-0.110 to 0.083] m/s/mo) and PW12-PW24 (0.043 [-0.063 to 0.160] m/s/mo). The biphasic fast-to-slow decline in LS occurred early in the on-treatment phase, which is consistent with the resolution of hepatic necroinflammation. The slow-to-fast decline in SS occurred off treatment. Future studies should investigate the association with regressions in liver fibrosis and portal hypertension.

Notched and Nonnotched Stimuli Are Equally Effective at the Mixing-Point Level in Sound Therapy for Tinnitus Relief.

Broadband noise (nonnotched) and notched noise are common sound sources in sound therapy for tinnitus relief. Studies on sound therapy using nonnotched or notched stimuli have reported large and small tinnitus improvements depending on the participant. However, the more effective sound source remains unclear given the among-study methodology differences. This study aimed to evaluate the tinnitus relief effects of sound therapy using stimuli with different spectral characteristics. This was a prospective study involving within-subject (baseline vs. 12-month follow-up) measurements for two groups (notched noise group vs. broadband noise group). We enrolled 30 adults with subjective and tonal tinnitus (notched noise group: 16, broadband noise group: 14). The participants underwent 3-hour daily sound therapy using either notched noise or broadband noise for 12 months. The stimulus level for sound therapy was set to each participant's mixing point. Tinnitus loudness and the Korean version of the Tinnitus Primary Function Questionnaire score were measured at baseline and at the 12-month follow-up time point. Both groups showed a significant improvement in tinnitus loudness and the Korean version of the Tinnitus Primary Function Questionnaire score. Notched and nonnotched stimuli are equally effective at the mixing point in sound therapy for tinnitus relief. Individuals with difficulties in tinnitus frequency measurement could easily undergo sound therapy using nonnotched stimuli.

Nonparametric Statistical Methods in Medical Research.

KEY POINT: Nonparametric statistical tests can be a useful alternative to parametric statistical tests when the test assumptions about the data distribution are not met.In this issue of Anesthesia & Analgesia, Wang et al1 report results of a trial of the effects of preoperative gum chewing on sore throat after general anesthesia with a supraglottic airway device. The authors used the Mann-Whitney U test—a nonparametric test—to compare numerical rating scale pain scores between the groups. The majority of statistical methods—namely, parametric methods—is based on the assumption of a specific data distribution in the population from which the data were sampled. This distribution is characterized by ≥1 parameters, such as the mean and the variance for the normal (Gaussian, “bell shaped”) distribution. Parametric methods commonly seek to estimate population parameters and to test hypotheses on these parameters—for example, on means and mean differences between groups. In contrast, though the exact definition varies in literature, nonparametric methods generally do not assume a specific probability distribution. While other nonparametric methods exist, we focus here on the widely used rank-based nonparametric tests. These methods use the ranks of the data instead of their actual values and can basically be used for all data that can be ranked, including ordinal data, discrete data (like counts), and continuous data. Nonparametric methods are commonly used when data distribution assumptions of parametric tests are not met. In practice, researchers often assess whether the outcome variable is overall normally distributed and use a nonparametric test when it is not. It is worth noting, however, that rank-based nonparametric tests: usually have slightly less power than parametric tests when the underlying distributional assumptions of the parametric test are actually met, often focus on hypothesis testing rather than estimation of parameters of interest, and may not be available when more complex analyses than simple within- or between-group comparisons are required. It can thus be useful to consider whether a parametric test can be used despite apparently non-normally distributed outcome data. First, the normality assumption does not necessarily apply to the dependent variable itself but, for example, to the residuals in a linear regression model. Second, some parametric tests like the t test can be relatively robust against non-normality when the sample size is large. Third, data transformations to approximate a normal distribution can be considered. Fourth, when data follow some other well-defined distribution (eg, Poisson distribution for count data), researchers can take advantage of parametric methods designed for these specific distributions.2 The Mann-Whitney U test (also known as the Wilcoxon rank-sum test or Wilcoxon-Mann-Whitney test) used by Wang et al1 (Figure) is the nonparametric equivalent to the 2-sample t test to compare 2 independent groups. It tests the null hypothesis that both groups come from populations with the same distribution, specifically, whether randomly drawn observations from one group are more likely to be higher (or lower) than randomly drawn observations from the other group.3 Contrary to common belief, the Mann-Whitney U test does not compare the medians between groups. This is only true under the assumption that the distribution has the same shape in both groups and differs only by its location. For >2 groups, the Kruskal–Wallis test can be used as a nonparametric alternative to 1-way analysis of variance (ANOVA).Figure.: Adapted text excerpt from the statistical methods section of Wang et al1 and their Table 2. These authors used Mann-Whitney U tests to compare patient self-reported NRS pain scores (the secondary outcome), which were not normally distributed, between their chewing gum group (G Group) and the control group (C Group). NRS indicates numeric rating scale.The Wilcoxon signed rank test is used to compare 2 paired (nonindependent) groups or 2 repeated within-subject measurements, and this test assumes that the distribution of the between-group differences is symmetric. The Friedman test is the nonparametric equivalent to 1-way repeated-measures ANOVA for comparisons of >2 paired groups.4 For a nonparametric correlation analysis, Spearman rank correlation is commonly used.5

Morphological changes in the subthalamic nucleus of people with mild-to-moderate Parkinson\u2019s disease: a 7T MRI study

This project investigated whether structural changes are present in the subthalamic nucleus (STN) of people with mild-to-moderate severity of Parkinson’s disease (PD). Within-subject measures of STN volume and fractional anisotropy (FA) were derived from high-resolution 7Tesla magnetic resonance imaging (MRI) for 29 subjects with mild-to-moderate PD (median disease duration = 2.3±1.9 years) and 18 healthy matched controls. Manual segmentation of the STN was performed on 0.4 mm in-plane resolution images. FA maps were generated and FA values were averaged over the left and right STN separately for each subject. Motor sign severity was assessed using the Movement Disorders Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Linear effects models showed that STN volume was significantly smaller in the PD subjects compared to controls (p = 0.01). Further, after controlling for differences in STN volumes within or between groups, the PD group had lower FA values in the STN compared to controls (corrected p ≤ 0.008). These findings demonstrate that morphological changes occur in the STN, which likely impact the function of the hyperdirect and indirect pathways of the basal ganglia and movement control.

An Item-Level Analysis for Detecting Faking on Personality Tests: Appropriateness of Ideal Point Item Response Theory Models.

How to detect faking on personality measures has been investigated using various methods and procedures. As previous findings are mixed and rarely based on ideal point item response theory models, additional research is needed for further exploration. This study modeled the responses of personality tests using ideal point method across instructed faking and honest responding conditions. A sample of undergraduate students participated the within-subjects measures to examine how the item location parameter derived from the generalized graded unfolding model changed, and how individuals’ perception about items changed when faked. The mean test scores of faking group was positively correlated to the magnitude of within-subjects score change. The item-level analysis revealed both conscientiousness items (18.8%) and neuroticism items (50.0%) appeared significant shifts on item parameters, suggesting that response pattern changed from honest to faking conditions. The direction of the change appeared both in positive and negative way, demonstrating that faking could increase or decrease personality factor scores. The results indicated that the changes of perceptions on items could be operated by faking, offering some support for the ideal point model to be an adequate measure for detecting faking. However, the findings of diagnostic accuracy analysis also implied that the appropriateness of ideal point models for detecting faking should be under consideration, also be used with caution. Implications, further research directions, and limitations are discussed.

Vascular response to social cognitive performance measured by infrared thermography: A translational study from mouse to man.

To assess complex social recognition in mice, we previously developed the SocioBox paradigm. Unexpectedly, 4 weeks after performing in the SocioBox, mice displayed robust social avoidance during Y‐maze sociability testing. This unique “sociophobia” acquisition could be documented in independent cohorts. We therefore employed infrared thermography as a non‐invasive method of stress‐monitoring during SocioBox testing (presentation of five other mice) versus empty box. A higher Centralization Index (body/tail temperature) in the SocioBox correlated negatively with social recognition memory and, after 4 weeks, with social preference in the Y‐maze. Assuming that social stimuli might be associated with characteristic thermo‐responses, we exposed healthy men (N = 103) with a comparably high intelligence level to a standardized test session including two cognitive tests with or without social component (face versus pattern recognition). In some analogy to the Centralization Index (within‐subject measure) used in mice, the Reference Index (ratio nose/malar cheek temperature) was introduced to determine the autonomic facial response/flushing during social recognition testing. Whereas cognitive performance and salivary cortisol were comparable across human subjects and tests, the Face Recognition Test was associated with a characteristic Reference Index profile. Infrared thermography may have potential for discriminating disturbed social behaviors.

Verbal Baselining: Within-Subject Consistency of CBCA Scores across Different Truthful and Fabricated Accounts

Statement Validity Assessment (SVA) proposes that baseline statements on different events can serve as a within-subject measure of a witness’ individual verbal capabilities when evaluating scores from Criteria-based Content Analysis (CBCA). This assumes that CBCA scores will generally be consistent across two accounts by the same witness. We present a first pilot study on this assumption. In two sessions, we asked 29 participants to produce one experience-based and one fabricated baseline account as well as one experience-based and one fabricated target account (each on different events), resulting in a total of 116 accounts. We hypothesized at least moderate correlations between target and baseline indicating a consistency across both experience-based and fabricated CBCA scores, and that fabricated CBCA scores would be more consistent because truth-telling has to consider random event characteristics, whereas lies must be constructed completely by the individual witness. Results showed that differences in correlations between experience-based CBCA scores and between fabricated CBCA scores took the predicted direction (cexperience-based = .44 versus cfabricated =.61) but this difference was not statistically significant. As predicted, a subgroup of event-related CBCA criteria were significantly less consistent than CBCA total scores, but only in experience-based accounts. The discussion considers methodological issues regarding the usage of total CBCA scores and whether to measure consistency with correlation coefficients. It is concluded that more studies are needed with larger samples.

Behavioral inhibition and EEG delta-beta correlation in early childhood: Comparing a between-subjects and within-subjects approach

Heightened delta-beta correlation has been conceptualized as reflecting exaggerated neural regulation and has been implicated in anxiety. Behavioral inhibition (BI) is a temperament characterized by wariness to novelty and is a robust predictor of anxiety, but delta-beta correlation has not been investigated in relation to childhood BI. We examined the relation between BI and between-subjects (i.e., across participants) and within-subjects (i.e., across data epochs) measures of baseline EEG delta-beta correlation in 118 children. Using a between-subjects measure, children scoring high on BI had higher delta-beta correlation relative to low BI children at frontal and central, and marginally higher in parietal, brain regions. Using a within-subjects measure, continuous BI scores were positively correlated with central and parietal delta-beta correlation. Delta-beta correlation may be a neural correlate of BI in childhood that displays differences in region specificity, correlation strength, and variability of correlation values when comparing between- and within-subjects measures.

Use of Repeated Within-Subject Measures to Assess Infants' Preference for Similar Others.

Research employing single-choice paradigms in which an infant is asked to make a single choice between two puppets suggest that infants show a preference for prosocial others and those who are similar to themselves. However, the extent to which infants’ preference for similar others is stable is unknown, as are other factors within the paradigm that may influence infants’ choices. The purpose of this study (two experiments, N = 44 infants, aged 8–15 months) was to replicate and extend previous work by including (1) within-subject repeated measures and (2) an experimental manipulation of a plausible demand characteristic. Results for the first-choice trial indicated a majority of the infants did not choose the similar puppet. Results from the within-subject repeated trials also indicated that a majority of the infants did not choose the similar puppet but a majority did choose a puppet from the same side. The experimental manipulation of the demand characteristic showed no effect on infant puppet choices. These results suggest that a closer examination of the single-choice puppet paradigm for assessing infants’ social evaluation is warranted. These findings also support recommendations made by others, including publishing null findings, standardizing data collection and reporting methods, and examining individual differences by employing within-subject designs with repeated measures.