Group-level Differences Research Articles

Filled Pauses Produced by Autistic Adults Differ in Prosodic Realisation, but not Rate or Lexical Type

We examined the use of filled pauses in conversations between homogeneous pairs of autistic and non-autistic adults. A corpus of semi-spontaneous speech was used to analyse the rate, lexical type (nasal “uhm” or non-nasal “uh”), and prosodic realisation (rising, level or falling) of filled pauses. We used Bayesian modelling for statistical analysis. We found an identical rate of filled pauses and an equivalent preference of “uhm” over “uh” across groups, but also a robust group-level difference regarding the intonational realisation of filled pauses: non-autistic controls produced a considerably higher proportion of filled pause tokens realised with the canonical level pitch contour than autistic speakers. Despite the fact that filled pauses are a frequent and impactful part of speech, previous work on their conversational use in autism spectrum disorder (ASD) is limited. Our account is the first to analyse the intonational realisation of filled pauses in ASD and the first to investigate conversations between autistic adults in this context. Our results on rate and lexical type can help to contextualise previous research, while the novel findings on intonational realisation set the stage for future investigations.

Reliable affordances: A generative modeling approach for test-retest reliability of the affordances task.

The affordances task serves as an important tool for the assessment of cognition and visuomotor functioning, and yet its test-retest reliability has not been established. In the affordances task, participants attend to a goal-directed task (e.g., classifying manipulable objects such as cups and pots) while suppressing their stimulus-driven, irrelevant reactions afforded by these objects (e.g., grasping their handles). This results in cognitive conflicts manifesting at the task level and the response level. In the current study, we assessed the reliability of the affordances task for the first time. While doing so, we referred to the "reliability paradox," according to which behavioral tasks that produce highly replicable group-level effects often yield low test-retest reliability due to the inadequacy of traditional correlation methods in capturing individual differences between participants. Alongside the simple test-retest correlations, we employed a Bayesian generative model that was recently demonstrated to result in a more precise estimation of test-retest reliability. Two hundred and ninety-five participants completed an online version of the affordances task twice, with a one-week gap. Performance on the online version replicated results obtained under in-lab administrations of the task. While the simple correlation method resulted in weak test-retest measures of the different effects, the generative model yielded a good reliability assessment. The current results support the utility of the affordances task as a reliable behavioral tool for the assessment of group-level and individual differences in cognitive and visuomotor functioning. The results further support the employment of generative modeling in the study of individual differences.

Segregated mobility patterns amplify neighborhood disparities in the spread of COVID-19

AbstractThe global and uneven spread of COVID-19, mirrored at the local scale, reveals stark differences along racial and ethnic lines. We respond to the pressing need to understand these divergent outcomes via neighborhood level analysis of mobility and case count information. Using data from Chicago over 2020, we leverage a metapopulation Susceptible-Exposed-Infectious-Removed model to reconstruct and simulate the spread of SARS-CoV-2 at the ZIP Code level. We demonstrate that exposures are mostly contained within one’s own ZIP Code and demographic group. Building on this observation, we illustrate that we can understand epidemic progression using a composite metric combining the volume of mobility and the risk that each trip represents, while separately these factors fail to explain the observed heterogeneity in neighborhood level outcomes. Having established this result, we next uncover how group level differences in these factors give rise to disparities in case rates along racial and ethnic lines. Following this, we ask what-if questions to quantify how segregation impacts COVID-19 case rates via altering mobility patterns. We find that segregation in the mobility network has contributed to inequality in case rates across demographic groups.

Militant Leadership and Terrorism in Armed Conflict

ABSTRACT The lethality and the frequency of terrorist attacks conducted by militant organizations vary considerably. Some militants perpetrate extreme and systemic levels of terrorist violence, some only do so occasionally, and others never conduct terror operations. To predict group-level differences in this outcome, we draw on conceptual frameworks in the political science and psychology fields to argue that prior military experience shapes leaders’ willingness to engage in terrorist violence. But not all experiences are created equal. We argue that formal experiences such as those associated with military training serve as a restricting influence on terrorist violence, while less formal and less structured experiences such as time in active combat are associated with increases in future terrorist violence. Using new data on the individual backgrounds of militant leaders active between 1989 and 2013, we find support for our hypotheses. This study contributes to the academic literature by bringing the leader back into explanations of wartime terrorist activity. Our findings also carry notable policy implications for policy makers, warfighters, and counterterrorism practitioners.

A comparative study of four-year and community college students' subjective experiences of emerging adulthood, belonging needs, and well-being

Background: Research on the dimensions of emerging adulthood has disproportionately focused on students from four-year universities. Methods: Using data from the EAMMi2 project (Grahe et al., 2018), we assess whether the dimensions of emerging adulthood (as the age of possibilities, instability, identity explorations, and feeling in-between) vary between four-year university and community college students. We also explore how emerging adults compare on the need to belong and subjective well-being. Results: Four-year university students (N = 1,221) identified more strongly with the negativity/instability and feeling in-between dimensions of emerging adulthood than community college students (N = 300). Community college students, however, were higher on identity exploration, with no differences between the groups in identification with the experimentation/possibilities dimension of emerging adulthood. Four-year students reported higher well-being and higher belonging needs compared to their counterparts at community colleges. Regardless of school type, experimentation/possibilities and feeling in-between predicted higher well-being whereas negativity/instability predicted lower well-being and higher belonging needs. Conclusion: These findings highlight nuance in the experiences of emerging adulthood, as evidenced by both some shared experiences and group-level differences.

Longitudinal effects of early psychosocial deprivation on macaque executive function: Evidence from computational modelling.

Executive function (EF) describes a group of cognitive processes underlying the organization and control of goal-directed behaviour. Environmental experience appears to play a crucial role in EF development, with early psychosocial deprivation often linked to EF impairment. However, many questions remain concerning the developmental trajectories of EF after exposure to deprivation, especially concerning specific mechanisms. Accordingly, using an 'A-not-B' paradigm and a macaque model of early psychosocial deprivation, we investigated how early deprivation influences EF development longitudinally from adolescence into early adulthood. The contribution of working memory and inhibitory control mechanisms were examined specifically via the fitting of a computational model of decision making to the choice behaviour of each individual. As predicted, peer-reared animals (i.e. those exposed to early psychosocial deprivation) performed worse than mother-reared animals across time, with the fitted model parameters yielding novel insights into the functional decomposition of group-level EF differences underlying task performance. Results indicated differential trajectories of inhibitory control and working memory development in the two groups. Such findings not only extend our knowledge of how early deprivation influences EF longitudinally, but also provide support for the utility of computational modelling to elucidate specific mechanisms linking early psychosocial deprivation to long-term poor outcomes.

Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.

The disconnection hypothesis of schizophrenia proposes that symptoms of the disorder arise as a result of aberrant functional integration between segregated areas of the brain. The concept of metastability characterizes the coexistence of competing tendencies for functional integration and functional segregation in the brain, and is therefore well suited for the study of schizophrenia. In this study, we investigate metastability as a candidate neuromechanistic biomarker of schizophrenia pathology, including a demonstration of reliability and face validity. Group-level discrimination, individual-level classification, pathophysiological relevance, and explanatory power were assessed using two independent case-control studies of schizophrenia, the Human Connectome Project Early Psychosis (HCPEP) study (controls n = 53, non-affective psychosis n = 82) and the Cobre study (controls n = 71, cases n = 59). In this work we extend Leading Eigenvector Dynamic Analysis (LEiDA) to capture specific features of dynamic functional connectivity and then implement a novel approach to estimate metastability. We used non-parametric testing to evaluate group-level differences and a naïve Bayes classifier to discriminate cases from controls. Our results show that our new approach is capable of discriminating cases from controls with elevated effect sizes relative to published literature, reflected in an up to 76% area under the curve (AUC) in out-of-sample classification analyses. Additionally, our new metric showed explanatory power of between 81-92% for measures of integration and segregation. Furthermore, our analyses demonstrated that patients with early psychosis exhibit intermittent disconnectivity of subcortical regions with frontal cortex and cerebellar regions, introducing new insights about the mechanistic bases of these conditions. Overall, these findings demonstrate reliability and face validity of metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.

Perspective changes in human listeners are aligned with the contextual transformation of the word embedding space.

Word embedding representations have been shown to be effective in predicting human neural responses to lingual stimuli. While these representations are sensitive to the textual context, they lack the extratextual sources of context such as prior knowledge, thoughts, and beliefs, all of which constitute the listener's perspective. In this study, we propose conceptualizing the listeners' perspective as a source that induces changes in the embedding space. We relied on functional magnetic resonance imaging data collected by Yeshurun Y, Swanson S, Simony E, Chen J, Lazaridi C, Honey CJ, Hasson U. Same story, different story: the neural representation of interpretive frameworks. Psychol Sci. 2017:28(3):307-319, in which two groups of human listeners (n= 40) were listening to the same story but with different perspectives. Using a dedicated fine-tuning process, we created two modified versions of a word embedding space, corresponding to the two groups of listeners. We found that each transformed space was better fitted with neural responses of the corresponding group, and that the spatial distances between these spaces reflect both interpretational differences between the perspectives and the group-level neural differences. Together, our results demonstrate how aligning a continuous embedding space to a specific context can provide a novel way of modeling listeners' intrinsic perspectives.

Comparison of evoked potentials across four related developmental encephalopathies

BackgroundDeveloping biomarkers is a priority for drug development for all conditions, but vital in the rare neurodevelopmental disorders where sensitive outcome measures are lacking. We have previously demonstrated the feasibility and tracking of evoked potentials to disease severity in Rett syndrome and CDKL5 deficiency disorder. The aim of the current study is to characterize evoked potentials in two related developmental encephalopathies, MECP2 duplication syndrome and FOXG1 syndrome, and compare across all four groups to better understand the potential of these measures to serve as biomarkers of clinical severity for the developmental encephalopathies.MethodsVisual and auditory evoked potentials were acquired from participants with MECP2 duplication syndrome and FOXG1 syndrome across five sites of the Rett Syndrome and Rett-Related Disorders Natural History Study. A group of age-matched individuals (mean = 7.8 years; range = 1–17) with Rett syndrome, CDKL5 deficiency disorder, and typically-developing participants served as a comparison group. The analysis focused on group-level differences as well as associations between the evoked potentials and measures of clinical severity from the Natural History Study.ResultsAs reported previously, group-level comparisons revealed attenuated visual evoked potentials (VEPs) in participants with Rett syndrome (n = 43) and CDKL5 deficiency disorder (n = 16) compared to typically-developing participants. VEP amplitude was also attenuated in participants with MECP2 duplication syndrome (n = 15) compared to the typically-developing group. VEP amplitude correlated with clinical severity for Rett syndrome and FOXG1 syndrome (n = 5). Auditory evoked potential (AEP) amplitude did not differ between groups, but AEP latency was prolonged in individuals with MECP2 duplication syndrome (n = 14) and FOXG1 syndrome (n = 6) compared to individuals with Rett syndrome (n = 51) and CDKL5 deficiency disorder (n = 14). AEP amplitude correlated with severity in Rett syndrome and CDKL5 deficiency disorder. AEP latency correlated with severity in CDKL5 deficiency disorder, MECP2 duplication syndrome, and FOXG1 syndrome.ConclusionsThere are consistent abnormalities in the evoked potentials in four developmental encephalopathies some of which correlate with clinical severity. While there are consistent changes amongst these four disorders, there are also condition specific findings that need to be further refined and validated. Overall, these results provide a foundation for further refinement of these measures for use in future clinical trials for these conditions.

Normative model detects abnormal functional connectivity in psychiatric disorders.

The diagnosis of psychiatric disorders is mostly based on the clinical evaluation of the patient's signs and symptoms. Deep learning binary-based classification models have been developed to improve the diagnosis but have not yet reached clinical practice, in part due to the heterogeneity of such disorders. Here, we propose a normative model based on autoencoders. We trained our autoencoder on resting-state functional magnetic resonance imaging (rs-fMRI) data from healthy controls. The model was then tested on schizophrenia (SCZ), bipolar disorder (BD), and attention-deficit hyperactivity disorder (ADHD) patients to estimate how each patient deviated from the norm and associate it with abnormal functional brain networks' (FBNs) connectivity. Rs-fMRI data processing was conducted within the FMRIB Software Library (FSL), which included independent component analysis and dual regression. Pearson's correlation coefficients between the extracted blood oxygen level-dependent (BOLD) time series of all FBNs were calculated, and a correlation matrix was generated for each subject. We found that the functional connectivity related to the basal ganglia network seems to play an important role in the neuropathology of BD and SCZ, whereas in ADHD, its role is less evident. Moreover, the abnormal connectivity between the basal ganglia network and the language network is more specific to BD. The connectivity between the higher visual network and the right executive control and the connectivity between the anterior salience network and the precuneus networks are the most relevant in SCZ and ADHD, respectively. The results demonstrate that the proposed model could identify functional connectivity patterns that characterize different psychiatric disorders, in agreement with the literature. The abnormal connectivity patterns from the two independent SCZ groups of patients were similar, demonstrating that the presented normative model was also generalizable. However, the group-level differences did not withstand individual-level analysis implying that psychiatric disorders are highly heterogeneous. These findings suggest that a precision-based medical approach, focusing on each patient's specific functional network changes may be more beneficial than the traditional group-based diagnostic classification.

A deep residual model for characterization of 5D spatiotemporal network dynamics reveals widespread spatiodynamic changes in schizophrenia.

Schizophrenia is a severe brain disorder with serious symptoms including delusions, disorganized speech, and hallucinations that can have a long-term detrimental impact on different aspects of a patient's life. It is still unclear what the main cause of schizophrenia is, but a combination of altered brain connectivity and structure may play a role. Neuroimaging data has been useful in characterizing schizophrenia, but there has been very little work focused on voxel-wise changes in multiple brain networks over time, despite evidence that functional networks exhibit complex spatiotemporal changes over time within individual subjects. Recent studies have primarily focused on static (average) features of functional data or on temporal variations between fixed networks; however, such approaches are not able to capture multiple overlapping networks which change at the voxel level. In this work, we employ a deep residual convolutional neural network (CNN) model to extract 53 different spatiotemporal networks each of which captures dynamism within various domains including subcortical, cerebellar, visual, sensori-motor, auditory, cognitive control, and default mode. We apply this approach to study spatiotemporal brain dynamism at the voxel level within multiple functional networks extracted from a large functional magnetic resonance imaging (fMRI) dataset of individuals with schizophrenia (N = 708) and controls (N = 510). Our analysis reveals widespread group level differences across multiple networks and spatiotemporal features including voxel-wise variability, magnitude, and temporal functional network connectivity in widespread regions expected to be impacted by the disorder. We compare with typical average spatial amplitude and show highly structured and neuroanatomically relevant results are missed if one does not consider the voxel-wise spatial dynamics. Importantly, our approach can summarize static, temporal dynamic, spatial dynamic, and spatiotemporal dynamics features, thus proving a powerful approach to unify and compare these various perspectives. In sum, we show the proposed approach highlights the importance of accounting for both temporal and spatial dynamism in whole brain neuroimaging data generally, shows a high-level of sensitivity to schizophrenia highlighting global but spatially unique dynamics showing group differences, and may be especially important in studies focused on the development of brain-based biomarkers.

Changes in Cerebral Blood Flow in Patients Who Receive Different Durations of Hemodialysis: An Arterial Spin Labeling MRI Study.

This study aimed to determine the changes in cerebral blood flow (CBF) in patients who received different durations of hemodialysis (HD) using arterial spin labeling magnetic resonance imaging. The study included 46 patients who received HD and 24 demographically similar healthy controls (HCs). Patients who received HD were divided into three subgroups based on its duration: HD-1 (n=15, dialysis duration ≤24 months), HD-2 (n=16, dialysis duration >24 and ≤72 months), and HD-3 (n=15, dialysis duration ≥73 months). All subjects completed the Mini Mental State Examination and Montreal Cognitive Assessment tests, and the patients who received HD underwent laboratory tests. Group-level differences in the global and regional CBFs between patients who received HD and HCs were assessed. Correlation analysis was performed to evaluate the associations among CBF, clinical variables, and cognitive function. Compared with HCs, global and regional CBFs were significantly increased in the HD-1 and HD-2 groups (p<0.05), but there was no significant difference in the HD-3 group (p>0.05). However, compared with the HD-1 group, the HD-3 group had significantly decreased global and regional CBFs (p<0.05). The cognitive function was worse in patients who received long-term HD than in HCs. Increased dialysis duration and hemoglobin level were predictive risk factors for decreased CBF in patients who received long-term HD. Patients who received long-term HD with normal CBF had worse cognitive function, which may be related to increased dialysis duration.

Audiological and Demographic Factors that Impact the Precision of Speech Categorization in Cochlear Implant Users.

The ability to adapt to subtle variations in acoustic input is a necessary skill for successful speech perception. Cochlear implant (CI) users tend to show speech perception benefits from the maintenance of their residual acoustic hearing. However, previous studies often compare CI users in different listening conditions within-subjects (i.e., in their typical Acoustic + Electric configuration compared with Acoustic-only or Electric-only configurations) and comparisons among different groups of CI users do not always reflect an Acoustic + Electric benefit. Existing work suggests that CI users with residual acoustic hearing perform similarly to Electric-only listeners on phonetic voicing contrasts and unexpectedly poorer with fricative contrasts which have little energy in the range of the Acoustic + Electric listeners' acoustic hearing. To further investigate how residual acoustic hearing impacts sensitivity to phonetic ambiguity, we examined whether device configuration, age, and device experience influenced phonetic categorization in a large individual differences study. CI users with various device configurations (Electric-only N = 41; Acoustic + Electric N = 95) categorized tokens from five /b-p/ and five /s-ʃ/ minimal pair continua (e.g., bet-pet; sock-shock). We investigated age, device experience, and when applicable, residual acoustic hearing (pure tone hearing thresholds) as predictors of categorization. We also examined the relationship between phonetic categorization and clinical outcomes (CNC, AzBio) in a subset of our sample. Acoustic + Electric CI users were better able to categorize along the voicing contrast (steeper categorization slope) compared with Electric-only users, but there was no group-level difference for fricatives. There were differences within the subgroups for fricatives: bilateral users showed better categorization than unilateral users and bimodal users had better categorization than hybrid users. Age was a significant factor for voicing, while device experience was significant for fricatives. Critically, within the Acoustic + Electric group, hybrid CI users had shallower slopes than bimodal CI users. Our findings suggest residual acoustic hearing is beneficial for categorizing stop voicing, but not frication. Age impacts the categorization of voicing, while device experience matters for fricatives. For CI users with ipsilateral residual acoustic hearing, those with better hearing thresholds may be over-relying on their acoustic hearing rather than extracting as much information as possible from their CI, and thus have shallower fricative categorization.

Automation and standardization of subject-specific region-of-interest segmentation for investigation of diffusion imaging in clinical populations.

Diffusion weighted imaging (DWI) is key in clinical neuroimaging studies. In recent years, DWI has undergone rapid evolution and increasing applications. Diffusion magnetic resonance imaging (dMRI) is widely used to analyse group-level differences in white matter (WM), but suffers from limitations that can be particularly impactful in clinical groups where 1) structural abnormalities may increase erroneous inter-subject registration and 2) subtle differences in WM microstructure between individuals can be missed. It also lacks standardization protocols for analyses at the subject level. Region of Interest (ROI) analyses in native diffusion space can help overcome these challenges, with manual segmentation still used as the gold standard. However, robust automated approaches for the analysis of ROI-extracted native diffusion characteristics are limited. Subject-Specific Diffusion Segmentation (SSDS) is an automated pipeline that uses pre-existing imaging analysis methods to carry out WM investigations in native diffusion space, while overcoming the need to interpolate diffusion images and using an intermediate T1 image to limit registration errors and guide segmentation. SSDS is validated in a cohort of healthy subjects scanned three times to derive test-retest reliability measures and compared to other methods, namely manual segmentation and tract-based spatial statistics as an example of group-level method. The performance of the pipeline is further tested in a clinical population of patients with traumatic brain injury and structural abnormalities. Mean FA values obtained from SSDS showed high test-retest and were similar to FA values estimated from the manual segmentation of the same ROIs (p-value > 0.1). The average dice similarity coefficients (DSCs) comparing results from SSDS and manual segmentations was 0.8 ± 0.1. Case studies of TBI patients showed robustness to the presence of significant structural abnormalities, indicating its potential clinical application in the identification and diagnosis of WM abnormalities. Further recommendation is given regarding the tracts used with SSDS.

MRI signatures of Brain Age in the Alzheimer’s disease continuum

AbstractBackgroundAge is the biggest risk factor for Alzheimer’s disease (AD). Substantial efforts to extract age signatures from magnetic resonance imaging (MRI) of the brain have achieved impressive accuracy and demonstrated these signatures were altered by neurological disorders including AD. In this work, we develop a deep learning model to characterize brain age signatures and examine their variation over the AD continuum.MethodA 3D deep ResNet model was implemented to learn the structural signatures of brain age in predicting the chronological age of the participants. The model was trained on 7372 T1‐weighted MRI scans from a combined lifespan cohort of 5848 cognitively normal participants (age: 8‐ 95 yrs) using a 10‐fold cross validation procedure. The model was then applied to the independent ADNI cohort (N=1175, 50‐98 yrs) to examine MRI derived brain age signatures variation in the AD continuum. The difference (∆age) between model predicted age and chronological age was used as the independent variable for group comparison using univariate ANCOVA tests, controlling for sex, education, and APOE4 gene dose, among five clinical groups: normal control (NC), normal to MCI converters (NC‐MCI), stable MCI (MCIs), MCI to AD converters (MCI‐AD), and AD patients.ResultThe ResNet model achieved an MAE=3.76 yrs and R2=0.93 across 10 folds in the lifespan cohort. In the baseline data of the ADNI cohort, model derived ∆age increased along the AD continuum as expected: NC (‐1.2yrs) &lt; NC‐MCI (‐0.7yrs) &lt; MCIs (‐0.3yrs) &lt; MCI‐AD (0.7yrs) &lt;AD (1.5yrs) (F=11.24, p&lt;0.0001). Post‐hoc pairwise comparison results are summarized in Table 1/Figure 2. Although the difference between NC and NC‐MCI did not reach significance (p=0.24) for the baseline data, comparison between the two groups using data from all visits was significant (p=0.0009), suggesting more subtle differences.ConclusionA ResNet model was developed that captures the MRI signatures of brain age with high accuracy in age prediction. The model detected group level differences along the AD continuum in the expected direction. Subtle changes in brain signatures were observable in normal participants who later developed cognitive impairment. Our technique provides a novel approach to investigate the relationship between aging and AD.

Regular cannabis use modulates the impact of HIV on the neural dynamics serving cognitive control.

Cannabis use and HIV are independently associated with decrements in cognitive control. However, the combined effects of HIV and regular cannabis use on the brain circuitry serving higher-order cognition are unclear. Investigate the interaction between cannabis and HIV on neural interference effects during the flanker task and spontaneous activity in regions underlying higher-order cognition. The sample consisted of 100 participants, including people with HIV (PWH) who use cannabis, PWH who do not use cannabis, uninfected cannabis users, and uninfected nonusers. Participants underwent an interview regarding their substance use history and completed the Eriksen flanker task during magnetoencephalography (MEG). MEG data were imaged in the time-frequency domain and oscillatory maps depicting the neural flanker interference effect were probed for group differences. Voxel time series were then assessed for group-level differences in spontaneous activity. Group differences in behavioral performance were identified along with group differences in theta and alpha neural interference responses in higher-order regions across the cortex, with nonusers with HIV generally exhibiting the most aberrant responses. Likewise, time series analyses indicated that nonusers with HIV also had significantly elevated spontaneous alpha activity in the left inferior frontal and dorsolateral prefrontal cortices (dlPFC). Finally, we found that spontaneous and oscillatory alpha activity were significantly coupled in the inferior frontal cortex and dlPFC among cannabis users, but not nonusers. Regular cannabis use appears to suppress the impact of HIV on spontaneous and oscillatory alpha deficits in the left inferior frontal cortex and dlPFC.

Health literacy among adolescents: summary of some key findings from ten European countries

Abstract Introduction In research on disparities, the concept of health literacy (HL) as a set of competencies to promote and sustain health may help in understanding the disparities better and in addressing avoidable and unfair health disparities. The presentation will present some key findings on adolescents’ HL levels in ten European countries, and how HL mediates and moderates between various background factors and health outcomes. Methods Data consisted of cross-sectional data from Health Behaviour in School-aged Children (HBSC) study from year 2017/18 of ten European countries (Austria, Belgium (Fl), Czechia, England, Estonia, Finland, Germany, Macedonia, Poland, and Slovakia). Data (n = 14,590 - 22,291) of 13- and 15-year-old pupils were used. Indicators include background variables (e.g. age, gender), Health literacy, Health indicators (e.g. self-rated health (SRH) and problematic social media use (PSMU)). Analysis include (1) Mediator analysis (with Mplus): pearson correlation coefficients, path models (Mplus 7.3 and Maximum Likelihood estimator) and (2) random effects models and moderator analyses (with R-sofware). Findings HL is an independent factor explaining disparities in health (e.g. SRH), and a mediator as well as a moderator between health outcomes and background factors. Based on the national analyses HL had significant main effects in every country, but group level differences emerged only in some countries. For instance, in Finland and Belgium, among girls HL lowered the likelihood to problematic social media use, but not among boys. Discussion HL is of use in understanding and tackling health disparities among adolescents. Results confirm the need to adopt the principles of proportionate universalism when promoting HL among adolescents to avoid widening the disparities within population groups. Also, country-specific health literacy interventions are needed to secure equity in opportunities of different population groups to benefit from the HL interventions.

Can we combine 3D data obtained with a MicroScribe digitising arm and photogrammetry to address bioarchaeological research questions?

Virtual methods for studying human remains are becoming increasingly popular in bioarchaeology, and the rate of technological innovation in the last few years has been such that we now have multiple options to choose from when collecting data. This raises the question of whether datasets generated with different methods are transposable. In the study reported here, we investigated whether it is valid to combine 3D data obtained with a MicroScribe digitising arm and 3D data collected via photogrammetry. We did so by simulating a population-based analysis similar to those commonly undertaken in bioarchaeology. Our sample comprised 19 crania from two ethnic groups, Ancient Egyptians and Guanches, and the landmarks we employed pertained to facial shape.The analyses yielded several findings. First, we found that photogrammetry was significantly more precise than the MicroScribe digitising arm. Second, the photogrammetry-based method revealed the existence of facial shape differences between the two ethnic groups that were not captured by the MicroScribe-based method. Third, we found that the two methods did not consistently capture the same facial shapes—they did for one of the ethnic groups but not for the other. Fourth, the analyses indicated that using the two methods can result in ethnic group-level differences in facial shape when they are applied to individuals from a single ethnic group. Lastly, the two methods of data collection yielded different patterns of variation in facial shape. Together, these findings suggest that combining 3D landmark coordinates collected with a MicroScribe and those obtained via photogrammetry may introduce considerable error into an analysis, and, consequently, bioarchaeologists should be cautious about doing so.

A comparative study of four-year and community college students' subjective experiences of emerging adulthood, belonging needs, and well-being

Background: Research on the core features of emerging adulthood has disproportionately focused on students from four-year universities. Methods: Using data from the EAMMi2 project (Grahe et al., 2018), we assess whether the core features of emerging adulthood (as the age of possibilities, instability, identity explorations, and feeling in-between) vary between four-year university and community college students. We also explore how emerging adults compare on the need to belong and subjective well-being. Results: Four-year university students (N = 1,221) identified more strongly with the negativity/instability and feeling in-between dimensions of emerging adulthood than community college students (N = 300). Community college students, however, were higher on identity exploration, with no differences between the groups in identification with the experimentation/possibilities feature of emerging adulthood. Four-year students reported higher well-being and higher belonging needs compared to their counterparts at community colleges. Regardless of school type, experimentation/possibilities and feeling in-between predicted higher well-being whereas negativity/instability predicted lower well-being and higher belonging needs. Conclusion: These findings highlight nuance in the experiences of emerging adulthood, as evidenced by both some shared experiences and group-level differences.

Striatal reactivity during emotion and reward relates to approach-avoidance conflict behaviour and is altered in adults with anxiety or depression.

Background:We have previously reported activation in reward, salience and executive control regions during functional MRI (fMRI) using an approach–avoidance conflict (AAC) decision-making task with healthy adults. Further investigations into how anxiety and depressive disorders relate to differences in neural responses during AAC can inform their understanding and treatment. We tested the hypothesis that people with anxiety or depression have altered neural activation during AAC.Methods:We compared 118 treatment-seeking adults with anxiety or depression and 58 healthy adults using linear mixed-effects models to examine group-level differences in neural activation (fMRI) during AAC decision-making. Correlational analyses examined relationships between behavioural and neural measures.Results:Adults with anxiety or depression had greater striatal engagement when reacting to affective stimuli (p = 0.008, d = 0.31) regardless of valence, and weaker striatal engagement during reward feedback (p = 0.046, d = −0.27) regardless of the presence of monetary reward. They also had blunted amygdala activity during decision-making (p = 0.023, d = −0.32) regardless of the presence of conflict. Across groups, approach behaviour during conflict decision-making was inversely correlated with striatal activation during affective stimuli (p < 0.001, r = −0.28) and positively related to striatal activation during reward feedback (p < 0.001, r = 0.27).Limitations:Our transdiagnostic approach did not allow for comparisons between specific anxiety disorders, and our cross-sectional approach did not allow for causal inference.Conclusion:Anxiety and depression were associated with altered neural responses to AAC. Findings were consistent with the role of the striatum in action selection and reward responsivity, and they point toward striatal reactivity as a future treatment target. Blunting of amygdala activity in anxiety or depression may indicate a compensatory response to inhibit affective salience and maintain approach.