Modelling monotonic effects of ordinal predictors in Bayesian regression models

Community-guided, autism-adapted group cognitive behavioral therapy for depression in autistic youth (CBT-DAY): Preliminary feasibility, acceptability, and efficacy

LAY ABSTRACT

Depression in youth is a significant public health problem worldwide, particularly for autistic youth who are over twice as likely to experience depression than their non-autistic peers. Although pathways to depression are complex, emotional reactivity and negative self-esteem are two risk factors for depression in autistic and non-autistic youth. Although autistic youth are more likely to experience depression than their non-autistic peers, psychotherapy options for autistic youth are very limited; community guidance in the development and testing of psychotherapy programs is a promising approach in autism. Therefore, in this study, we designed an autism-adapted CBT-DAY, in collaboration with autistic community members. Specifically, CBT-DAY combined neurodiversity-affirming and cognitive behavioral approaches to target emotional reactivity and self-esteem in youth to improve depressive symptom severity in a group setting across 12 weeks. We examined the preliminary feasibility, acceptability, and efficacy of CBT-DAY in a pilot non-randomized trial. In addition, we implemented a rigorous protocol for assessing, monitoring, and addressing potential harms in this intervention. Results from 24 autistic youth (11-17 years old) suggest that CBT-DAY may be feasible to use in an outpatient clinical setting and generally acceptable to youth and their caregivers. Participation in CBT-DAY may be associated with significant improvements in youth emotional reactivity and self-esteem, as well as depressive symptom severity per self-report only. Exploratory analyses showed that participation in CBT-DAY may also be associated with significant improvements in internalizing symptoms. Findings demonstrate the potential promise of neurodiversity-affirming and cognitive behavioral approaches to treating depressive symptoms in some autistic youth.

Assessing the cooling potential of climate change adaptation measures in rural areas

Atmospheric heat has become a major public concern in a rapidly warming world. Evapotranspiration, however, provides effective land surface cooling during the vegetation period. Adversely, modern cultural landscapes - due to both water and potential evapotranspiration pathways lacking - are increasingly incapable of offering this important benefit. We hypothesised that concerted measures for a revived landscape water retention can fuel plant transpiration, especially during dry periods, and thus contribute to climate change adaptation by stabilising the regional climate. Seeking nature-based ways to an improved landscape water retention, we used the land surface temperature (LST) as a proxy for landscape mesoclimate. For our drought-prone rural study area, we identified potential candidate environmental predictors for which we established statistical relationships to LST. We then, from a set of potential climate change adaptation measures, mapped selected items to potential locations of implementation. Building on that, we evaluated a certain measures' probable cooling effect using (i) the fitted model and (ii) the expected expression of predictors before and after a hypothetical measure implementation. In the modelling, we took into account the spatial and temporal autocorrelation of the LST data and thus achieved realistic parameter estimates. Using the candidate predictor set and the model, we were able to establish a ranking of the effectiveness of climate adaptation measures. However, due to the spatial variability of the predictors, the modelled LST is site-specific. This results in a spatial differentiation of a measure's benefit. Furthermore, seasonal variations occur, such as those caused by plant growth. On average, the afforestation of arable land or urban brownfields, and the rewetting of former wet meadows have the largest cooling capacities of up to 3.5 K. We conclude that heat countermeasures based on fostering both evapotranspiration and landscape water retention, even in rural regions, offer promising adaptation ways to atmospheric warming.

Shrinkage priors for isotonic probability vectors and binary data modeling, with applications to dose-response modeling

Motivated by the need to model dose-response or dose-toxicity curves in clinical trials, we develop a new horseshoe-based prior for Bayesian isotonic regression modeling a binary outcome against an ordered categorical predictor, where the probability of the outcome is assumed to be monotonically non-decreasing with the predictor. The set of differences between outcome probabilities in consecutive categories of the predictor is equipped with a multivariate prior having support over simplex. The Dirichlet distribution, which can be derived from a normalized sum of independent gamma-distributed random variables, is a natural choice of prior, but using mathematical and simulation-based arguments, we show that the resulting posterior is prone to underflow and other numerical instabilities, even under simple data configurations. We propose an alternative prior based on horseshoe-type shrinkage that is numerically more stable. We show that this horseshoe-based prior is not subject to the numerical instability seen in the Dirichlet/gamma-based prior and that the horseshoe-based posterior can estimate the underlying true curve more efficiently than the Dirichlet-based one. We demonstrate the use of this prior in a model predicting the occurrence of radiation-induced lung toxicity in lung cancer patients as a function of dose delivered to normal lung tissue. Our methodology is implemented in the R package isotonicBayes and therefore suitable for use in the design of dose-finding studies or other dose-response modeling contexts.

Classifying Self-Reported Rheumatoid Arthritis Flares Using Daily Patient-Generated Data From a Smartphone App: Exploratory Analysis Applying Machine Learning Approaches

BACKGROUND

The ability to predict rheumatoid arthritis (RA) flares between clinic visits based on real-time, longitudinal patient-generated data could potentially allow for timely interventions to avoid disease worsening.

OBJECTIVE

This exploratory study aims to investigate the feasibility of using machine learning methods to classify self-reported RA flares based on a small data set of daily symptom data collected on a smartphone app.

METHODS

Daily symptoms and weekly flares reported on the Remote Monitoring of Rheumatoid Arthritis (REMORA) smartphone app from 20 patients with RA over 3 months were used. Predictors were several summary features of the daily symptom scores (eg, pain and fatigue) collected in the week leading up to the flare question. We fitted 3 binary classifiers: logistic regression with and without elastic net regularization, a random forest, and naive Bayes. Performance was evaluated according to the area under the curve (AUC) of the receiver operating characteristic curve. For the best-performing model, we considered sensitivity and specificity for different thresholds in order to illustrate different ways in which the predictive model could behave in a clinical setting.

RESULTS

The data comprised an average of 60.6 daily reports and 10.5 weekly reports per participant. Participants reported a median of 2 (IQR 0.75-4.25) flares each over a median follow-up time of 81 (IQR 79-82) days. AUCs were broadly similar between models, but logistic regression with elastic net regularization had the highest AUC of 0.82. At a cutoff requiring specificity to be 0.80, the corresponding sensitivity to detect flares was 0.60 for this model. The positive predictive value (PPV) in this population was 53%, and the negative predictive value (NPV) was 85%. Given the prevalence of flares, the best PPV achieved meant only around 2 of every 3 positive predictions were correct (PPV 0.65). By prioritizing a higher NPV, the model correctly predicted over 9 in every 10 non-flare weeks, but the accuracy of predicted flares fell to only 1 in 2 being correct (NPV and PPV of 0.92 and 0.51, respectively).

CONCLUSIONS

Predicting self-reported flares based on daily symptom scorings in the preceding week using machine learning methods was feasible. The observed predictive accuracy might improve as we obtain more data, and these exploratory results need to be validated in an external cohort. In the future, analysis of frequently collected patient-generated data may allow us to predict flares before they unfold, opening opportunities for just-in-time adaptative interventions. Depending on the nature and implication of an intervention, different cutoff values for an intervention decision need to be considered, as well as the level of predictive certainty required.

Do beta-blockers reduce negative intrusive thoughts and anxiety in cancer survivors? - An emulated trial

BACKGROUND

High rates of negative intrusive thoughts have been reported among cancer patients. Prevalent users of beta-blocker therapy have reported lower levels of cancer related intrusive thoughts than non-user. The aim of this study is to investigate if initiation of beta-blocker therapy reduces the prevalence and severity of intrusive thoughts (co-primary endpoints) and the prevalence of anxiety, depressed mood, and low quality of life (secondary endpoints) in cancer survivors.

METHODS

Data on patient-reported outcomes from three cohort studies of Swedish patients diagnosed with colon, prostate or rectal cancer were combined with data on beta-blocker prescriptions retrieved from the Swedish Prescribed Drug Register. Two randomized controlled trials were emulated. Trial 1 had follow-up 1 year after diagnosis, trial 2 had follow-up 2 years after diagnosis, baseline in both trials was 12 months before follow-up. Those who initiated beta-blocker therapy between baseline and follow-up was assigned Active group, those who did not was assigned Control group. All endpoints were analysed using Bayesian ordered logistic regression.

RESULTS

Trial 1 consisted of Active group, n = 59, and Control group, n = 3936. Trial 2 consisted of Active group, n = 87, and Control group, n = 3132. The majority of participants were men, 83% in trial 1 and 94% in trial 2. The prevalence and severity of intrusive thoughts were lower in the Active group in trial 1, but no significant differences between groups were found in either trial. The prevalence of depressed mood, worse quality of life and periods of anxiety were higher in the Active group in both trials with significant differences for quality of life in trial 1 and anxiety in trial 2.

CONCLUSIONS

The emulated trials demonstrated no evidence of a protective effect of beta-blocker therapy against intrusive thoughts. The Active group had reduced quality of life and elevated anxiety compared to the Control group.

TRIAL REGISTRATION

The three cohort studies were registered at isrctn.com/clinicaltrials.gov (ISRCTN06393679, NCT02530593 and NCT01477229).

Neural timescales reflect behavioral demands in freely moving rhesus macaques

Previous work demonstrated a highly reproducible cortical hierarchy of neural timescales at rest, with sensory areas displaying fast, and higher-order association areas displaying slower timescales. The question arises how such stable hierarchies give rise to adaptive behavior that requires flexible adjustment of temporal coding and integration demands. Potentially, this lack of variability in the hierarchical organization of neural timescales could reflect the structure of the laboratory contexts. We posit that unconstrained paradigms are ideal to test whether the dynamics of neural timescales reflect behavioral demands. Here we measured timescales of local field potential activity while male rhesus macaques foraged in an open space. We found a hierarchy of neural timescales that differs from previous work. Importantly, although the magnitude of neural timescales expanded with task engagement, the brain areas' relative position in the hierarchy was stable. Next, we demonstrated that the change in neural timescales is dynamic and contains functionally-relevant information, differentiating between similar events in terms of motor demands and associated reward. Finally, we demonstrated that brain areas are differentially affected by these behavioral demands. These results demonstrate that while the space of neural timescales is anatomically constrained, the observed hierarchical organization and magnitude is dependent on behavioral demands.

Material insecurity and religiosity: A causal analysis

Some cultural evolutionary models predict that under stressful reductions of well-being, individuals will be more attracted and fastidiously adhere to traditional systems of norms that promote solidarity and cooperation. As religious systems can bolster human relationships with a variety of mechanisms, the material insecurity hypothesis of religion posits that individual religiosity will increase under conditions of material insecurity. The bulk of the literature up to this point has been correlational and cross-national. Here, across 14 field sites, we examine the causal role that educational attainment and food insecurity play in religiosity. We find that years of formal education and food insecurity do not consistently contribute to individual religiosity cross-culturally. We conclude with a discussion of some theoretical and methodological implications. As a general workflow for cross-cultural causal research in the quantitative social sciences, the present work is a modest but necessary first step in reliably estimating causation in the material insecurity hypothesis of religiosity.

"Losses disguised as wins" in electronic gambling machines contribute to win overestimation in a large online sample

Introduction

Losses disguised as wins (LDWs) are a salient type of losing outcome common to electronic gambling machines (EGMs). These events occur when a gambling payout is less than the amount wagered (i.e., a net loss) but is nonetheless accompanied by the sounds and animations that accompany genuine wins. Previous lab-based studies have reported that participants tend to overestimate genuine wins when LDWs are present. This study reports an independent replication of these findings in a large online sample that included a substantial number of individuals reporting high-risk gambling and frequent EGM users.

Methods

This online study recruited a sample of 940 participants who were randomly assigned to view one of two brief videos. Each video displayed a short period of simulated online slot machine gambling and included 2 genuine wins and either 3 or 0 LDWs. Participants were asked to estimate the number of times a win occurred that was more than the amount bet. Participants also completed the Problem Gambling Severity Index.

Results

The mean estimated number of genuine wins was significantly larger for the condition displaying LDWs, 3.02 [95% CI = 2.82, 3.21] than the control condition, 2.14 [1.98, 2.30], t(887.66) = 6.78, d = 0.44, p <.001.

Conclusions

We replicated the LDW-triggered win overestimation effect previously reported in lab-based experiments that have recruited smaller samples. This effect was robust in both low-risk and high-risk groups, indicating that even experienced gamblers remain susceptible. Exploratory modelling suggested only a minority of individuals were uninfluenced by LDWs.

Time course and correlates of psychological distress post spinal surgery: A longitudinal study

Background

Psychological distress post lumbar spine surgery is associated with poorer outcomes. There is a scarcity of studies devoted to analyzing the risk factors associated with psychological distress in patients who have undergone lumbar fusion surgery. The purpose of this study was to (1) describe the time course and severity of psychological distress using the STarT Back Tool (SBT) and (2) determine the demographic and clinical predictors of SBT score post lumbar spine fusion surgery.

Methods

This retrospective longitudinal study analyzed 227 subjects with 1- and 2-level lumbar fusion surgery who underwent standardized assessment preoperatively and at 4 and 12 weeks postoperatively. Preoperative variables collected were demographic, clinical, and psychological variables. Postoperative psychological distress was measured by self-reported SBT. Risk factors for SBT over time were identified using ordinal and mixed-effects modelling.

Results

Although the trajectory of SBT levels declined postoperatively over time, at week-12, 20% of patients had moderate to high SBT. Postoperative SBT scores at week-4 time point was significantly greater than SBT scores at week-8 (OR = 2.7, 95% credible interval [CrI]; 1.8-3.9). Greater SBT scores at week-4 were strongly associated with greater SBT scores throughout 12 weeks of follow-up (OR = 7.3, [95% CrI; 1.2-31.4]). Greater postoperative SBT levels over time were associated with being male (OR = 2.2, 95% CrI; 1.0-3.9), greater preoperative back or leg pain intensity (OR = 2.2; 95% CrI: 1.0-4.4), greater preoperative leg weakness (OR = 4.2, 95% CrI: 1.7-7.5) and higher preoperative depression levels (OR = 4.8; 95% CrI: 1.6-10.4).

Conclusion

Postoperative SBT levels declined nonlinearly over time. However, a sizable proportion of patients had moderate to high psychological distress at week-12 postsurgery. Greater preoperative back or leg pain intensity, leg weakness and depression levels, and male gender were risk factors of greater psychological distress postsurgery. Although requiring validation, our study has identified potential modifiable risk factors which may give an opportunity to provide early (preoperative) and targeted strategies to optimize postoperative psychosocial outcomes in patients undergoing lumbar fusion surgeries.

Interpreting Rhythm as Parsing: Syntactic-Processing Operations Predict the Migration of Visual Flashes as Perceived During Listening to Musical Rhythms

Music can be interpreted by attributing syntactic relationships to sequential musical events, and, computationally, such musical interpretation represents an analogous combinatorial task to syntactic processing in language. While this perspective has been primarily addressed in the domain of harmony, we focus here on rhythm in the Western tonal idiom, and we propose for the first time a framework for modeling the moment-by-moment execution of processing operations involved in the interpretation of music. Our approach is based on (1) a music-theoretically motivated grammar formalizing the competence of rhythmic interpretation in terms of three basic types of dependency (preparation, syncopation, and split; Rohrmeier, 2020), and (2) psychologically plausible predictions about the complexity of structural integration and memory storage operations, necessary for parsing hierarchical dependencies, derived from the dependency locality theory (Gibson, 2000). With a behavioral experiment, we exemplify an empirical implementation of the proposed theoretical framework. One hundred listeners were asked to reproduce the location of a visual flash presented while listening to three rhythmic excerpts, each exemplifying a different interpretation under the formal grammar. The hypothesized execution of syntactic-processing operations was found to be a significant predictor of the observed displacement between the reported and the objective location of the flashes. Overall, this study presents a theoretical approach and a first empirical proof-of-concept for modeling the cognitive process resulting in such interpretation as a form of syntactic parsing with algorithmic similarities to its linguistic counterpart. Results from the present small-scale experiment should not be read as a final test of the theory, but they are consistent with the theoretical predictions after controlling for several possible confounding factors and may form the basis for further large-scale and ecological testing.

Microplastics could be marginally more hazardous than natural suspended solids - A meta-analysis

Microplastics (MP) are perceived as a threat to aquatic ecosystems but bear many similarities to suspended sediments which are often considered less harmful. It is, therefore pertinent to determine if and to what extent MP are different from other particles occurring in aquatic ecosystems in terms of their adverse effects. We applied meta-regressions to toxicity data extracted from the literature and harmonized the data to construct Species Sensitivity Distributions (SSDs) for both types of particles. The results were largely inconclusive due to high uncertainty but the central tendencies of our estimates still indicate that MP could be marginally more hazardous compared to suspended sediments. In part, the high uncertainty stems from the general lack of comparable experimental studies and dose-dependent point estimates. We therefore argue that until more comparable data is presented, risk assessors should act precautionary and treat MP in the 1-1000 µm size range as marginally more hazardous to aquatic organisms capable of ingesting such particles.

Discordance Between Self-Reported and Performance-Based Physical Function in Patients Who Have Knee Osteoarthritis: Associations With Pain Intensity and Negative Affect

BACKGROUND

Although self-reported measures of physical disability are strong indication criterion for total knee arthroplasty (TKA) in painful knee osteoarthritis (OA), some patients may report greater-than-observed disability. Contributing factors to this discordance are relatively unexplored. We aimed to examine whether pain and negative affect, including anxiety and depression, were associated with the discordance of self-reported measures with performance-based measures (PPM) of physical function.

METHODS

We used cross-sectional data (n = 212) from two randomized rehabilitation trials in knee OA. All patients were assessed for knee pain intensity and symptoms of anxiety and depression. Self-reported function was assessed by the Western Ontario and McMaster Universities Arthritis Index (WOMAC) physical-function subscale. Objective performance-based measures (PPMs) of physical function were assessed by timed gait and stair tests. Continuous discordance scores were quantified by the difference in percentiles between WOMAC and PPMs (WOMAC-PPM), where a positive discordance, WOMAC-PPM >0, implied greater perceived than observed disability.

RESULTS

Around 1 in 4 patients had >20 percentile units in WOMAC-PPM discordance. In Bayesian regression analyses, knee pain intensity had >99% posterior probability of positive associations with WOMAC-PPM discordance. Among patients awaiting TKA, anxiety intensity had approximately 99% probability of positive associations with discordance, and these associations had >65% probability of exceeding 10 percentile units. In contrast, depression had low (79% to 88%) probability of any association with discordance.

CONCLUSION

In patients who have knee OA, a sizable proportion reported substantially greater physical disability than actually observed. Pain and anxiety intensity, but not depression, were meaningful predictors of this discordance. If validated, our findings may help in refining patient selection criteria for TKA.

Role of light walking pace on cognition: Findings from the Maine-Syracuse Longitudinal Study

Moderate- to vigorous intensities of physical activity are recommended for health promotion, including brain health. Regular physical activity is considered a modifiable factor to delay -perhaps prevent- onset of dementias such as Alzheimer's disease. Little is known about the benefits of light physical activity. We analyzed data from a 998 community-dwelling, cognitively unimpaired participants from the Maine-Syracuse Longitudinal Study (MSLS) and investigated the role of light physical activity, defined by walking pace, across two time points. Results revealed light levels of walking pace were associated with higher performance at the first timepoint and less decline by time 2 in the domains of verbal abstract reasoning and visual scanning and tracking, which includes both processing speed and executive function skills. When examining change over time (N = 583), increasing walking pace was associated with less decline at time two for the domains of visual scanning and tracking, working memory, visual spatial ability, and working memory, but not verbal abstract reasoning. These findings highlight the relevance of light physical activity and the need to investigate its contribution to cognitive function. From a public health perspective, this may encourage more adults to adopt a light level of exercise and still reap health benefits.

Comparing the efficacy in reducing brain injury of different neuroprotective agents following neonatal hypoxia-ischemia in newborn rats: a multi-drug randomized controlled screening trial

Intrapartum hypoxia-ischemia leading to neonatal encephalopathy (NE) results in significant neonatal mortality and morbidity worldwide, with > 85% of cases occurring in low- and middle-income countries (LMIC). Therapeutic hypothermia (HT) is currently the only available safe and effective treatment of HIE in high-income countries (HIC); however, it has shown limited safety or efficacy in LMIC. Therefore, other therapies are urgently required. We aimed to compare the treatment effects of putative neuroprotective drug candidates following neonatal hypoxic-ischemic (HI) brain injury in an established P7 rat Vannucci model. We conducted the first multi-drug randomized controlled preclinical screening trial, investigating 25 potential therapeutic agents using a standardized experimental setting in which P7 rat pups were exposed to unilateral HI brain injury. The brains were analysed for unilateral hemispheric brain area loss after 7 days survival. Twenty animal experiments were performed. Eight of the 25 therapeutic agents significantly reduced brain area loss with the strongest treatment effect for Caffeine, Sonic Hedgehog Agonist (SAG) and Allopurinol, followed by Melatonin, Clemastine, ß-Hydroxybutyrate, Omegaven, and Iodide. The probability of efficacy was superior to that of HT for Caffeine, SAG, Allopurinol, Melatonin, Clemastine, ß-hydroxybutyrate, and Omegaven. We provide the results of the first systematic preclinical screening of potential neuroprotective treatments and present alternative single therapies that may be promising treatment options for HT in LMIC.

Penalized optimal scaling for ordinal variables with an application to international classification of functioning core sets

Ordinal data occur frequently in the social sciences. When applying principal component analysis (PCA), however, those data are often treated as numeric, implying linear relationships between the variables at hand; alternatively, non-linear PCA is applied where the obtained quantifications are sometimes hard to interpret. Non-linear PCA for categorical data, also called optimal scoring/scaling, constructs new variables by assigning numerical values to categories such that the proportion of variance in those new variables that is explained by a predefined number of principal components (PCs) is maximized. We propose a penalized version of non-linear PCA for ordinal variables that is a smoothed intermediate between standard PCA on category labels and non-linear PCA as used so far. The new approach is by no means limited to monotonic effects and offers both better interpretability of the non-linear transformation of the category labels and better performance on validation data than unpenalized non-linear PCA and/or standard linear PCA. In particular, an application of penalized optimal scaling to ordinal data as given with the International Classification of Functioning, Disability and Health (ICF) is provided.

A novel visual illusion paradigm provides evidence for a general factor of illusion sensitivity and personality correlates

Visual illusions are a gateway to understand how we construct our experience of reality. Unfortunately, important questions remain open, such as the hypothesis of a common factor underlying the sensitivity to different types of illusions, as well as of personality correlates of illusion sensitivity. In this study, we used a novel parametric framework for visual illusions to generate 10 different classic illusions (Delboeuf, Ebbinghaus, Rod and Frame, Vertical-Horizontal, Zöllner, White, Müller-Lyer, Ponzo, Poggendorff, Contrast) varying in strength, embedded in a perceptual discrimination task. We tested the objective effect of the illusions on errors and response times, and extracted participant-level performance scores (n=250) for each illusion. Our results provide evidence in favour of a general factor underlying the sensitivity to different illusions (labelled Factor i). Moreover, we report a positive link between illusion sensitivity and personality traits such as Agreeableness, Honesty-Humility, and negative relationships with Psychoticism, Antagonism, Disinhibition, and Negative Affect.

Neural timescales reflect behavioral demands in freely moving rhesus macaques

Previous work has demonstrated remarkably reproducible and consistent hierarchies of neural timescales across cortical areas at rest. The question arises how such stable hierarchies give rise to adaptive behavior that requires flexible adjustment of temporal coding and integration demands. Potentially, this previously found lack of variability in the hierarchical organization of neural timescales could be a reflection of the structure of the laboratory contexts in which they were measured. Indeed, computational work demonstrates the existence of multiple temporal hierarchies within the same anatomical network when the input structure is altered. We posit that unconstrained behavioral environments where relatively little temporal demands are imposed from the experimenter are an ideal test bed to address the question of whether the hierarchical organization and the magnitude of neural timescales reflect ongoing behavioral demands. To tackle this question, we measured timescales of local field potential activity while rhesus macaques were foraging freely in a large open space. We find a hierarchy of neural timescales that is unique to this foraging environment. Importantly, although the magnitude of neural timescales generally expanded with task engagement, the brain areas' relative position in the hierarchy was stable across the recording sessions. Notably, the magnitude of neural timescales monotonically expanded with task engagement across a relatively long temporal scale spanning the duration of the recording session. Over shorter temporal scales, the magnitude of neural timescales changed dynamically around foraging events. Moreover, the change in the magnitude of neural timescales contained functionally relevant information, differentiating between seemingly similar events in terms of motor demands and associated reward. That is, the patterns of change were associated with the cognitive and behavioral meaning of these events. Finally, we demonstrated that brain areas were differentially affected by these behavioral demands - i.e., the expansion of neural timescales was not the same across all areas. Together, these results demonstrate that the observed hierarchy of neural timescales is context-dependent and that changes in the magnitude of neural timescales are closely related to overall task engagement and behavioral demands.

Development and validation of a physical frailty phenotype index-based model to estimate the frailty index

BACKGROUND

The conventional count-based physical frailty phenotype (PFP) dichotomizes its criterion predictors-an approach that creates information loss and depends on the availability of population-derived cut-points. This study proposes an alternative approach to computing the PFP by developing and validating a model that uses PFP components to predict the frailty index (FI) in community-dwelling older adults, without the need for predictor dichotomization.

METHODS

A sample of 998 community-dwelling older adults (mean [SD], 68 [7] years) participated in this prospective cohort study. Participants completed a multi-domain geriatric screen and a physical fitness assessment from which the count-based PFP and the 36-item FI were computed. One-year prospective falls and hospitalization rates were also measured. Bayesian beta regression analysis, allowing for nonlinear effects of the non-dichotomized PFP criterion predictors, was used to develop a model for FI ("model-based PFP"). Approximate leave-one-out (LOO) cross-validation was used to examine model overfitting.

RESULTS

The model-based PFP showed good calibration with the FI, and it had better out-of-sample predictive performance than the count-based PFP (LOO-R², 0.35 vs 0.22). In clinical terms, the improvement in prediction (i) translated to improved classification agreement with the FI (Cohen's k_w, 0.47 vs 0.36) and (ii) resulted primarily in a 23% (95%CI, 18-28%) net increase in FI-defined "prefrail/frail" participants correctly classified. The model-based PFP showed stronger prognostic performance for predicting falls and hospitalization than did the count-based PFP.

CONCLUSION

The developed model-based PFP predicted FI and clinical outcomes more strongly than did the count-based PFP in community-dwelling older adults. By not requiring predictor cut-points, the model-based PFP potentially facilitates usage and feasibility. Future validation studies should aim to obtain clear evidence on the benefits of this approach.

Hearing Prosocial Stories Increases Hadza Hunter-Gatherers' Generosity in an Economic Game

Folk stories featuring prosocial content are ubiquitous across cultures. One explanation for the ubiquity of such stories is that stories teach people about the local socioecology, including norms of prosociality, and stories featuring prosocial content may increase generosity in listeners. We tested this hypothesis in a sample of 185 Hadza hunter-gatherers. We read participants a story in which the main character either swims with another person (control story) or rescues him from drowning (prosocial story). After hearing the story, participants played a dictator game with dried meat sticks and then were given a recall test of facts presented in the story. There was moderate evidence for a small effect of the prosocial story: participants who heard the prosocial story gave an estimated 0.22 [90% HDI: -0.12-0.57] more meat sticks than those who heard the control story. However, the association between generosity and sex, marital status, and region of residence was stronger; men gave more than women, unmarried participants gave more than married participants, and participants living in a region with more exposure to markets gave more than participants living further from markets. There was no evidence that the prosocial story was more easily recalled than the control story. These results provide some support for the hypothesis that prosocial stories can increase prosociality in listeners, though the effect of hearing a single story is small.

The iambic-trochaic law without iambs or trochees: Parsing speech for grouping and prominence

Listeners parse the speech signal effortlessly into words and phrases, but many questions remain about how. One classic idea is that rhythm-related auditory principles play a role, in particular, that a psycho-acoustic "iambic-trochaic law" (ITL) ensures that alternating sounds varying in intensity are perceived as recurrent binary groups with initial prominence (trochees), while alternating sounds varying in duration are perceived as binary groups with final prominence (iambs). We test the hypothesis that the ITL is in fact an indirect consequence of the parsing of speech along two in-principle orthogonal dimensions: prominence and grouping. Results from several perception experiments show that the two dimensions, prominence and grouping, are each reliably cued by both intensity and duration, while foot type is not associated with consistent cues. The ITL emerges only when one manipulates either intensity or duration in an extreme way. Overall, the results suggest that foot perception is derivative of the cognitively more basic decisions of grouping and prominence, and the notions of trochee and iamb may not play any direct role in speech parsing. A task manipulation furthermore gives new insight into how these decisions mutually inform each other.

Multilevel interactions between family and neighbourhood socioeconomic indices in childhood and later risks of self-harm and violent criminality in Denmark: a national cohort study

BACKGROUND

A socioeconomically disadvantaged childhood has been associated with elevated self-harm and violent criminality risks during adolescence and young adulthood. However, whether these risks are modified by a neighbourhood's socioeconomic profile is unclear. The aim of our study was to compare risks among disadvantaged young people residing in deprived areas versus risks among similarly disadvantaged individuals residing in affluent areas.

METHODS

We did a national cohort study, using Danish interlinked national registers, from which we delineated a longitudinal cohort of people born in Denmark between Jan 1, 1981, and Dec 31, 2001, with two Danish-born parents, who were alive and residing in the country when they were aged 15 years, who were followed up for a hospital-treated self-harm episode or violent crime conviction. A neighbourhood affluence indicator was derived based on nationwide income quartiles, with parental income and educational attainment indicating the socioeconomic position of each cohort member's family. Bayesian multilevel survival analyses were done to examine the moderating influences of neighbourhood affluence on associations between family socioeconomic position and sex-specific risks for the two adverse outcomes.

FINDINGS

1 084 047 cohort members were followed up for 12·8 million person-years in aggregate. Individuals of a low socioeconomic position residing in deprived neighbourhoods had a higher incidence of both self-harm and violent criminality compared with equivalently disadvantaged peers residing in affluent areas. Women from a low-income background residing in affluent areas had, on average, 95 (highest density interval 76-118) fewer self-harm episodes and 25 (15-41) fewer violent crime convictions per 10 000 person-years compared with women of an equally low income residing in deprived areas, whereas men of a low income residing in affluent areas had 61 (39-81) fewer self-harm episodes and 88 (56-191) fewer violent crime convictions per 10 000 person-years than men of a low income residing in deprived areas.

INTERPRETATION

Even in a high-income European country with comprehensive social welfare and low levels of poverty and inequality, individuals residing in affluent neighbourhoods have lower risks of self-harm and violent criminality compared with individuals residing in deprived neighbourhoods. More research is needed to explore the potential of neighbourhood policies and interventions to reduce the harmful effects of growing up in socioeconomically deprived circumstances on later risk of self-harm and violent crime convictions.

FUNDING

European Research Council, Lundbeck Foundation Initiative for Integrative Psychiatric Research, and BERTHA, the Danish Big Data Centre for Environment and Health funded by the Novo Nordisk Foundation Challenge Programme.

Geospatial analysis of patients' social determinants of health for health systems science and disparity research

Social context matters for health, healthcare processes/quality and patient outcomes. The social status and circumstances we are born into, grow up in and live under, are called social determinants of health; they drive our health, and how we access and experience care; they are the fundamental causes of disease outcomes. Such circumstances are influenced heavily by our location through neighborhood context, which relates to support networks. Geography can influence proximity to resources and is an important dimension of social determinants of health, which also encompass race/ethnicity, language, health literacy, gender identity, social capital, wealth and income. Beginning with an explanation of social determinants, we explore the use of Geospatial Analysis methods and geocoding, including the importance of collaborating with geography experts, the pitfalls of geocoding, and how geographic analysis can help us to understand patient populations within the context of Social Determinants of Health. We then explain mechanisms and methods of geospatial analysis with two examples: (1) Bayesian hierarchical regression with crossed random effects and (2) discontinuity regression i.e., change point analysis. We leveraged the local University of Utah and Yale cohorts of the Multicenter Perioperative Outcomes Group (MPOG.org ), a perioperative electronic health registry; we enriched the Utah cohort with US-census tract level social determinants of health after geocoding patient addresses and extracting social determinants of health from the National Neighborhood Database (NaNDA). We explain how to investigate the impact of US-census tract level community deprivation indices and racial/ethnic composition on (1) individual clinicians’ administration of risk-adjusted perioperative antiemetic prophylaxis, (2) patients’ decisions to defer cataract surgery at the cusp of Medicare eligibility and finally (3) methods to further characterize patient populations at risk through publicly available datasets in the context of public transit access. Our examples are not rigorous analyses, and our preliminary inferences should not be taken at face value, but rather seen as illustration of geospatial analysis processes and methods. Our worked examples show the potential utility of geospatial analysis, and in particular the power of geocoding patient addresses to extract US-census level social determinants of health from publicly available databases to enrich electronic health registries for healthcare disparity research and targeted health system level countermeasures.

COVID-19 outbreaks analysis in the Valencian Region of Spain in the prelude of the third wave

Introduction

The COVID-19 pandemic has led to unprecedented social and mobility restrictions on a global scale. Since its start in the spring of 2020, numerous scientific papers have been published on the characteristics of the virus, and the healthcare, economic and social consequences of the pandemic. However, in-depth analyses of the evolution of single coronavirus outbreaks have been rarely reported.

Methods

In this paper, we analyze the main properties of all the tracked COVID-19 outbreaks in the Valencian Region between September and December of 2020. Our analysis includes the evaluation of the origin, dynamic evolution, duration, and spatial distribution of the outbreaks.

Results

We find that the duration of the outbreaks follows a power-law distribution: most outbreaks are controlled within 2 weeks of their onset, and only a few last more than 2 months. We do not identify any significant differences in the outbreak properties with respect to the geographical location across the entire region. Finally, we also determine the cluster size distribution of each infection origin through a Bayesian statistical model.

Discussion

We hope that our work will assist in optimizing and planning the resource assignment for future pandemic tracking efforts.

Using IoT devices for sensor-based monitoring of employees' mental workload: Investigating managers' expectations and concerns

Although the objective assessment of mental workload has been a focus of human factors research, few studies have investigated stakeholders' attitudes towards its implementation in real workplaces. The present study addresses this research gap by surveying N = 702 managers in three European countries (Germany, United Kingdom, Spain) about their expectations and concerns regarding sensor-based monitoring of employee mental workload. The data confirm the relevance of expectations regarding improvements of workplace design and employee well-being, as well as concerns about restrictions of employees' privacy and sovereignty, for the implementation of workload monitoring. Furthermore, Bayesian regression models show that the examined expectations have a substantial positive association with managers' willingness to support workload monitoring in their company. Privacy concerns are identified as a significant barrier to the acceptance of workload monitoring, both in terms of their prevalence among managers and their strong negative relationship with monitoring support.

Physical activity participation in Australians with multiple sclerosis: associations with geographical remoteness

PURPOSE

Physical activity (PA) participation offers many benefits for persons with multiple sclerosis (MS). Persons with MS are significantly less active than the general population; however, there is insufficient evidence regarding the association between geographical remoteness and PA participation in persons with MS. We identify PA levels across levels of rurality in an Australian MS population.

MATERIALS AND METHODS

The Australian MS Longitudinal Study collects regular survey data from persons with MS in Australia, including demographic, clinical, and health behavioural data. Physical activity engagement was identified with the International Physical Activity Questionnaire-short form and geographical remoteness was identified from participants' postcode using the Access and Remoteness Index for Australia. Hurdle regression analysis examined the relationship between remoteness and PA participation, and level of PA, after controlling for confounding.

RESULTS

Data from 1260 respondents showed that 24% of persons with MS did not participate in any PA. Remoteness was not associated with the participation in any PA (OR 1.04; 89% highest density probability interval (HDPI) estimate 0.88, 1.22). Amongst those with any PA (n = 960), those living in more remote areas had, on average, higher levels of PA (RR 1.21; 89% HDPI estimate 1.11, 1.34).

CONCLUSIONS

Physical activity promotion does not need to differ based on geographical location. Implications for rehabilitationAlmost one quarter of persons with MS in our study recorded no participation in any physical activity (PA).Healthcare practitioners are encouraged to include the promotion of PA as part of MS management.Physical activity participation is similar for persons with MS across different geographical locations.Physical activity promotion does not need to differ based on geographical location.

Serial measurement of M. tuberculosis in blood from critically-ill patients with HIV-associated tuberculosis

BACKGROUND

Despite being highly prevalent in hospitalised patients with severe HIV-associated tuberculosis (TB) and sepsis, little is known about the mycobacteriology of Mycobacterium tuberculosis bloodstream infection (MTBBSI). We developed methods to serially measure bacillary load in blood and used these to characterise MTBBSI response to anti-TB therapy (ATT) and relationship with mortality.

METHODS

We established a microscopy method for direct visualisation of M. tuberculosis bacilli in blood using a novel lysis-concentration protocol and the fluorescent probe, 4-N,N-dimethylaminonaphthalimide-trehalose (DMN-Tre). We tested blood using GeneXpert® MTB/RIF-Ultra (Xpert-ultra) and Myco/F lytic culture after processing blood through lysis-wash steps to remove PCR inhibitors and anti-microbial drug carry-over. HIV-positive patients predicted to have MTBBSI gave blood samples 0, 4, 24, 48 and 72 h after ATT initiation. Bacillary loads were quantified using microscopy, Xpert-ultra cycle threshold, and culture time-to-positivity. Pharmacodynamics were modelled using these measures combined on an ordinal scale, including association with 12-week mortality.

FINDINGS

M. tuberculosis was detected in 27 of 28 recruited participants; 25 (89%) by blood Xpert-ultra, 22 (79%) by DMN-Tre microscopy, and 21 (75%) by Myco/F lytic blood culture. Eight (29%) participants died by 12-week follow-up. In a combined pharmacodynamic model, predicted probabilities of negative DMN-Tre microscopy, blood Xpert-ultra, or blood culture after 72 h treatment were 0·64, 0·27, and 0·94, respectively, in those who survived, compared with 0·23, 0·06, and 0·71 in those who died (posterior probability of slower clearance of MTBBSI in those that died >0·99). DMN-Tre microscopy of blood demonstrated heterogenous bacillary morphologies, including microcolonies and clumps. Bacillary cell-length varied significantly with ATT exposure (mean cell-length increase 0·13 log-µm/day; 95%CrI 0·10-0·16).

INTERPRETATION

Pharmacodynamics of MTBBSI treatment can be captured using DMN-Tre microscopy, blood Xpert-ultra and culture. This could facilitate interventional trials in severe HIV-associated TB.

FUNDING

Wellcome Trust, NIH Fogarty International Center, South African MRC, NIHR(UK), National Research Foundation of South Africa.

Life-history tradeoffs in a historical population (1896-1939) undergoing rapid fertility decline: Costs of reproduction?

Evolutionary demographers often invoke tradeoffs between reproduction and survival to explain reductions in fertility during demographic transitions. The evidence for such tradeoffs in humans has been mixed, partly because tradeoffs may be masked by individual differences in quality or access to resources. Unmasking tradeoffs despite such phenotypic correlations requires sophisticated statistical analyses that account for endogeneity among variables and individual differences in access to resources. Here we tested for costs of reproduction using N=13,663 birth records from the maternity hospital in Basel, Switzerland, 1896-1939, a period characterized by rapid fertility declines . We predicted that higher parity is associated with worse maternal and offspring condition at the time of birth, adjusting for age and a variety of covariates. We used Bayesian multivariate, multilevel models to simultaneously analyze multiple related outcomes while accounting for endogeneity, appropriately modeling non-linear effects, dealing with hierarchical data structures, and effectively imputing missing data. Despite all these efforts, we found virtually no evidence for costs of reproduction. Instead, women with better access to resources had fewer children. Barring limitations of the data, these results are consistent with demographic transitions reflecting women's investment in their own embodied capital and/or the adoption of maladaptive low-fertility norms by elites.

Patterns of Symptom Tracking by Caregivers and Patients With Dementia and Mild Cognitive Impairment: Cross-sectional Study

BACKGROUND

Individuals with dementia and mild cognitive impairment (MCI) experience a wide variety of symptoms and challenges that trouble them. To address this heterogeneity, numerous standardized tests are used for diagnosis and prognosis. myGoalNav Dementia is a web-based tool that allows individuals with impairments and their caregivers to identify and track outcomes of greatest importance to them, which may be a less arbitrary and more sensitive way of capturing meaningful change.

OBJECTIVE

We aim to explore the most frequent and important symptoms and challenges reported by caregivers and people with dementia and MCI and how this varies according to disease severity.

METHODS

This cross-sectional study involved 3909 web-based myGoalNav users (mostly caregivers of people with dementia or MCI) who completed symptom profiles between 2006 and 2019. To make a symptom profile, users selected their most personally meaningful or troublesome dementia-related symptoms to track over time. Users were also asked to rank their chosen symptoms from least to most important, which we called the symptom potency. As the stage of disease for these web-based users was unknown, we applied a supervised staging algorithm, previously trained on clinician-derived data, to classify each profile into 1 of 4 stages: MCI and mild, moderate, and severe dementia. Across these stages, we compared symptom tracking frequency, symptom potency, and the relationship between frequency and potency.

RESULTS

Applying the staging algorithm to the 3909 user profiles resulted in 917 (23.46%) MCI, 1596 (40.83%) mild dementia, 514 (13.15%) moderate dementia, and 882 (22.56%) severe dementia profiles. We found that the most frequent symptoms in MCI and mild dementia profiles were similar and comprised early hallmarks of dementia (eg, recent memory and language difficulty). As the stage increased to moderate and severe, the most frequent symptoms were characteristic of loss of independent function (eg, incontinence) and behavioral problems (eg, aggression). The most potent symptoms were similar between stages and generally reflected disruptions in everyday life (eg, problems with hobbies or games, travel, and looking after grandchildren). Symptom frequency was negatively correlated with potency at all stages, and the strength of this relationship increased with increasing disease severity.

CONCLUSIONS

Our results emphasize the importance of patient-centricity in MCI and dementia studies and illustrate the valuable real-world evidence that can be collected with digital tools. Here, the most frequent symptoms across the stages reflected our understanding of the typical disease progression. However, the symptoms that were ranked as most personally important by users were generally among the least frequently selected. Through individualization, patient-centered instruments such as myGoalNav can complement standardized measures by capturing these infrequent but potent outcomes.

Neuroticism Drives Associations Between Repetitive Behaviors and Depression in Autistic Adults

Depression is more prevalent among autistic adults than neurotypical adults, yet risk factors are incompletely understood in this population. Some research groups have focused on relationships between negative repetitive thinking and depression in the autistic population, which may explain elevated prevalence rates in line with general population findings on rumination and internalizing disorders. Little is known about associations between depression and more prototypical repetitive cognitions and/or behaviors characteristic of autism (i.e., insistence on sameness [IS] and repetitive sensorimotor [RSM] behaviors). Therefore, the present study aimed to examine associations between IS, RSM behaviors, and depressive symptoms in 762 autistic adults, and whether observed effects are confounded by additional factors (e.g., demographic factors, trait neuroticism). To test if greater IS scores were associated with greater depressive symptoms on the BDI-II, a Bayesian linear regression was conducted with BDI-II scores (dependent variable) regressed on age, gender, educational level, RSM scores, and IS scores (independent variables). To test the effects of neuroticism on observed relationships, a second regression was conducted that included all predictors from the baseline model and neuroticism. Standardized regression coefficients were tested against an interval null hypothesis of [-0.1, 0.1] to assess for practical significance. Results indicated that IS exhibited a moderate positive relationship with depressive symptoms, while RSM behaviors provided only a slight increase in predictive ability. However in the second model, neuroticism exhibited a strong positive relationship with depressive symptoms, completely attenuating the effect of IS. Associations between RSM behaviors and depressive symptoms did not meet our criteria for practical significance, particularly when neuroticism was added to the model. Neither RSM nor IS moderated the effect of neuroticism on depression. The findings from this study add to the literature on risk factors in the pathway to depression in autism, and suggest opportunities for clinical translation to screening and intervention efforts. Screening for IS in autistic individuals is a common diagnostic practice in clinical and research settings that may be leveraged to also identify those at higher risk for depression, and increasing flexibility in daily life may promote emotional regulation and distress tolerance.

PathoClock and PhysioClock in mice recapitulate human multimorbidity and heterogeneous aging

BACKGROUND

Multimorbidity is a public health concern and an essential component of aging and healthspan but understudied because investigative tools are lacking that can be translatable to capture similarities and differences of the aging process across species and variability between individuals and individual organs.

METHODS

To help address this need, body organ disease number (BODN) borrowed from human studies was applied to C57BL/6 (B6) and CB6F1 mouse strains at 8, 16, 24, and 32 months of age, as a measure of systems morbidity based on pathology lesions to develop a mouse PathoClock resembling clinically-based Body Clock in humans, using Bayesian inference. A mouse PhysioClock was also developed based on measures of physiological domains including cardiovascular, neuromuscular, and cognitive function in the same two mouse strains so that alignment with BODN was predictable.

RESULTS

Between- and within-age variabilities in PathoClock and PhysioClock, as well as between-strain variabilities. Both PathoClock and PhysioClock correlated with chronological age more strongly in CB6F1 than C57BL/6. Prediction models were then developed, designated as PathoAge and PhysioAge, using regression models of pathology and physiology measures on chronological age. PathoAge better predicted chronological age than PhysioAge as the predicted chronological and observed chronological age for PhysioAge were complex rather than linear.

CONCLUSION

PathoClock and PhathoAge can be used to capture biological changes that predict BODN, a metric developed in humans, and compare multimorbidity across species. These mouse clocks are potential translational tools that could be used in aging intervention studies.

Word Order Variation is Partially Constrained by Syntactic Complexity

Previous work suggests that when speakers linearize syntactic structures, they place longer and more complex dependents further away from the head word to which they belong than shorter and simpler dependents, and that they do so with increasing rigidity the longer expressions get, for example, longer objects tend to be placed further away from their verb, and with less variation. Current theories of sentence processing furthermore make competing predictions on whether longer expressions are preferentially placed as early or as late as possible. Here we test these predictions using hierarchical distributional regression models that allow estimates of word order and word order variation at the level of individual dependencies in corpora from 71 languages, while controlling for confounding effects from the type of dependency (e.g., subject vs. object), and the type of clause (main vs. subordinate) involved as well as from trends that are characteristic of individual languages, language families, and language contact areas. Our results show the expected correlations of length with position and variation only for two out of six dependency types (obliques and nominal modifiers) and no difference between clause types. These findings challenge received theories of across‐the‐board effects of complexity on word order and word order variation and call for theoretical models that relativize effects to specific kinds of syntactic structures and dependencies.

Functional specificity and neural integration in the aesthetic appreciation of artworks with implied motion

Although there is growing interest in the neural foundations of aesthetic experience, it remains unclear how particular mental subsystems (e.g. perceptual, affective and cognitive) are involved in different types of aesthetic judgements. Here, we use fMRI to investigate the involvement of different neural networks during aesthetic judgements of visual artworks with implied motion cues. First, a behavioural experiment (N = 45) confirmed a preference for paintings with implied motion over static cues. Subsequently, in a preregistered fMRI experiment (N = 27), participants made aesthetic and motion judgements towards paintings representing human bodies in dynamic and static postures. Using functional region-of-interest and Bayesian multilevel modelling approaches, we provide no compelling evidence for unique sensitivity within or between neural systems associated with body perception, motion and affective processing during the aesthetic evaluation of paintings with implied motion. However, we show suggestive evidence that motion and body-selective systems may integrate signals via functional connections with a separate neural network in dorsal parietal cortex, which may act as a relay or integration site. Our findings clarify the roles of basic visual and affective brain circuitry in evaluating a central aesthetic feature-implied motion-while also pointing towards promising future research directions, which involve modelling aesthetic preferences as hierarchical interplay between visual and affective circuits and integration processes in frontoparietal cortex.

Ethnic Markers without Ethnic Conflict : Why do Interdependent Masikoro, Mikea, and Vezo of Madagascar Signal their Ethnic Differences?

People often signal their membership in groups through their clothes, hairstyle, posture, and dialect. Most existing evolutionary models argue that markers label group members so individuals can preferentially interact with those in their group. Here we ask why people mark ethnic differences when interethnic interaction is routine, necessary, and peaceful. We asked research participants from three ethnic groups in southwestern Madagascar to sort photos of unfamiliar people by ethnicity, and by with whom they would prefer or not prefer to cooperate, in a wage labor vignette. Results indicate that southwestern Malagasy reliably send and detect ethnic signals; they signal less in the marketplace, a primary site of interethnic coordination and cooperation; and they do not prefer co-ethnics as cooperation partners in novel circumstances. Results from a cultural knowledge survey and calculations of cultural F_ST suggest that these ethnic groups have relatively little cultural differentiation. We concur with Moya and Boyd (Human Nature 26:1-27, 2015) that ethnicity is unlikely to be a singular social phenomenon. The current functions of ethnic divisions and marking may be different from those at the moment of ethnogenesis. Group identities may persist without group conflict or differentiation.

Using molecular testing to improve the management of thyroid nodules with indeterminate cytology: an institutional experience with review of molecular alterations

INTRODUCTION

Molecular testing has helped clinicians and cytopathologists to further categorize indeterminate thyroid fine needle aspiration (FNA) specimens. The purpose of the present study was to evaluate the accuracy of commercially available molecular tests, review their effects on patient treatment, and correlate the molecular alterations with the histologic findings.

MATERIALS AND METHODS

A pathology laboratory information system search identified thyroid FNAs performed at our institution between January 1, 2015 and June 30, 2020. The results of surgical follow-up and ancillary molecular testing were collected. We evaluated the accuracy of these tests and whether they could reduce the number of surgeries performed.

RESULTS

Our laboratory information system search identified 510 cases reported as atypia of undetermined significance, 94 as suspicious for follicular neoplasm, and 44 as suspicious for follicular neoplasm, Hurthle cell type. Of the specimens, 343 had no ancillary molecular testing, 146 were sent for ThyGenX/ThyraMIR, and 136 were sent for ThyroSeq. Of the patients without molecular testing, 50.4% had undergone follow-up surgery compared with 30.8% after ThyGenX/ThyraMIR and 38.2% after ThyroSeq testing, resulting in 38.9% and 24.2% fewer surgeries and an odds ratio of 0.04 (95% confidence interval, 0.00-0.33) and 0.14 (95% confidence interval, 0.01-0.95), respectively. For ThyGenX/ThyraMIR testing, the risk of malignancy for high and moderate to high risk alterations was 80%, 28.6% for moderate and low to moderate risk alterations, and 23.1% for low risk alterations. For ThyroSeq, the risk of malignancy was 87.5% for high risk alterations, 36.8% for intermediate to high risk alterations, 27.3% for intermediate risk alterations, and 0% for low risk alterations. The areas under the curve for ThyGenX/ThyraMIR and ThyroSeq testing were 0.65 and 0.85, respectively.

CONCLUSIONS

These findings suggest that, at our institution, both ThygenX/ThyraMIR and ThyroSeq can be used to effectively stratify cytology specimens based on the risk of malignancy and reduce the number of surgeries performed at our institution.

Productivity modifies the effects of fire severity on understory diversity

High severity fire may promote or reduce plant understory diversity in forests. However, few empirical studies test long-standing theoretical predictions that productivity may help to explain observed variation in post-fire plant diversity. Support for the influence of productivity on disturbance-diversity relationships is found predominantly in experimental grasslands, while tests over large areas with natural disturbance and productivity gradients are few and have yielded inconsistent results. Here, we measured the response of post-fire understory plant diversity to natural gradients of fire severity and productivity in a large-scale observational study in California's subalpine forests. We found that plant species richness increased with increasing fire severity and that this trend was stronger at high productivity. We used plant traits to investigate whether release from competition might contribute to increasing diversity and found that short-lived and far-dispersing species benefited more from high severity fire than their long-lived and near-dispersing counterparts. For far-dispersing species only, the benefit from high severity fire was stronger in high productivity plots where unburned species richness was lowest. Our results support theoretical connections between fire severity, productivity and plant communities that are key to predicting the consequences of increasing fire severity and frequency on diversity in the coming decades.

Can Visualization Alleviate Dichotomous Thinking? Effects of Visual Representations on the Cliff Effect

Common reporting styles for statistical results in scientific articles, such as p-values and confidence intervals (CI), have been reported to be prone to dichotomous interpretations, especially with respect to the null hypothesis significance testing framework. For example when the p-value is small enough or the CIs of the mean effects of a studied drug and a placebo are not overlapping, scientists tend to claim significant differences while often disregarding the magnitudes and absolute differences in the effect sizes. This type of reasoning has been shown to be potentially harmful to science. Techniques relying on the visual estimation of the strength of evidence have been recommended to reduce such dichotomous interpretations but their effectiveness has also been challenged. We ran two experiments on researchers with expertise in statistical analysis to compare several alternative representations of confidence intervals and used Bayesian multilevel models to estimate the effects of the representation styles on differences in researchers' subjective confidence in the results. We also asked the respondents' opinions and preferences in representation styles. Our results suggest that adding visual information to classic CI representation can decrease the tendency towards dichotomous interpretations - measured as the 'cliff effect': the sudden drop in confidence around p-value 0.05 - compared with classic CI visualization and textual representation of the CI with p-values. All data and analyses are publicly available at https://github.com/helske/statvis.

Predicting healthcare-seeking behavior based on stated readiness to act: development and validation of a prediction model

A starting point of many digital health interventions informed by the Stages of Change Model of behavior change is assessing a person's readiness to change. In this paper, we use the concept of readiness to develop and validate a prediction model of health-seeking behavior in the context of family planning. We conducted a secondary analysis of routinely collected, anonymized health data submitted by 4,088 female users of a free health chatbot in Kenya. We developed a prediction model of (future) self-reported action by randomly splitting the data into training and test data sets (80/20, stratified by the outcome). We further split the training data into 10 folds for cross-validating the hyperparameter tuning step in model selection. We fit nine different classification models and selected the model that maximized the area under the receiver operator curve. We then fit the selected model to the full training dataset and evaluated the performance of this model on the holdout test data. The model predicted who will visit a family planning provider in the future with high precision (0.93) and moderate recall (0.75). Using the Stages of Change framework, we concluded that 29% of women were in the "Preparation" stage, 21% were in the "Contemplation" stage, and 50% were in the "Pre-Contemplation" stage. We demonstrated that it is possible to accurately predict future healthcare-seeking behavior based on information learned during the initial encounter. Models like this may help intervention developers to tailor strategies and content in real-time.

Paths to social licence for tracking-data analytics in university research and services

While tracking-data analytics can be a goldmine for institutions and companies, the inherent privacy concerns also form a legal, ethical and social minefield. We present a study that seeks to understand the extent and circumstances under which tracking-data analytics is undertaken with social licence-that is, with broad community acceptance beyond formal compliance with legal requirements. Taking a University campus environment as a case, we enquire about the social licence for Wi-Fi-based tracking-data analytics. Staff and student participants answered a questionnaire presenting hypothetical scenarios involving Wi-Fi tracking for university research and services. Our results present a Bayesian logistic mixed-effects regression of acceptability judgements as a function of participant ratings on 11 privacy dimensions. Results show widespread acceptance of tracking-data analytics on campus and suggest that trust, individual benefit, data sensitivity, risk of harm and institutional respect for privacy are the most predictive factors determining this acceptance judgement.

Intrusive memories as conditioned responses to trauma cues: An empirically supported concept?

Intrusions in posttraumatic stress disorder (PTSD) are clinically understood as conditioned responses (CRs) to trauma-cues; however, experimental evidence for this is limited. We subjected 84 healthy participants to a differential conditioned-intrusion paradigm, where neutral faces served as conditioned stimuli (CSs) and aversive film clips as unconditioned stimuli (USs). While one group only completed acquisition, another group additionally received extinction. Subsequently, participants provided detailed e-diary intrusion reports. Several key findings emerged: First, participants in both groups re-experienced not only USs but also CSs as content of their intrusions. Second, intrusions were elicited by cues resembling CSs, USs, and experimental context. Third, extinction reduced probability and severity of US intrusions, and accelerated their decay, and this was particularly the case in participants showing greater cognitive (US-expectancy) and physiological (SCR) differential responding to CS+ vs. CS- at end of acquisition (i.e., conditionability). Similarly, extinction reduced CS-intrusion probability and severity, but only in participants with greater cognitive conditionability. These results support conditioning's role in re-experiencing in two critical ways: (1) Conditioning during trauma provides cues that not only function as reminder cues, but also as content of intrusions; (2) After strong conditioning, weakening the original CS-US relationship via extinction reduces intrusion formation after analogue-trauma.

A large-scale internal validation study of unsupervised virtual trichrome staining technologies on nonalcoholic steatohepatitis liver biopsies

Non-alcoholic steatohepatitis (NASH) is a fatty liver disease characterized by accumulation of fat in hepatocytes with concurrent inflammation and is associated with morbidity, cirrhosis and liver failure. After extraction of a liver core biopsy, tissue sections are stained with hematoxylin and eosin (H&E) to grade NASH activity, and stained with trichrome to stage fibrosis. Methods to computationally transform one stain into another on digital whole slide images (WSI) can lessen the need for additional physical staining besides H&E, reducing personnel, equipment, and time costs. Generative adversarial networks (GAN) have shown promise for virtual staining of tissue. We conducted a large-scale validation study of the viability of GANs for H&E to trichrome conversion on WSI (n = 574). Pathologists were largely unable to distinguish real images from virtual/synthetic images given a set of twelve Turing Tests. We report high correlation between staging of real and virtual stains ([Formula: see text]; 95% CI: 0.84-0.88). Stages assigned to both virtual and real stains correlated similarly with a number of clinical biomarkers and progression to End Stage Liver Disease (Hazard Ratio HR = 2.06, 95% CI: 1.36-3.12, p < 0.001 for real stains; HR = 2.02, 95% CI: 1.40-2.92, p < 0.001 for virtual stains). Our results demonstrate that virtual trichrome technologies may offer a software solution that can be employed in the clinical setting as a diagnostic decision aid.

The Influence of EMG-Triggered Robotic Movement on Walking, Muscle Force and Spasticity after an Ischemic Stroke

Background and Objectives: Application of the EMG-driven robotic training in everyday therapeutic processes is a modern and innovative form of neurorehabilitation among patients after stroke. Active participation of the patient contributes to significantly higher activation of the sensorimotor network during active motor control rather than during passive movement. The study objective was to determine the effect of electromyographic triggering (EMG-triggered) robotic rehabilitation device treatment on walking, muscle force, and spasticity after an ischemic stroke. Materials and Methods: A total of 60 participants with impaired motor function and gait after subacute stroke were included in the study. Each patient was randomly assigned to an intervention or control group (IG or CG). All patients, except standard therapy, underwent 1 additional session of therapy per day, 5 days a week for 6 weeks. IG had 30 min of training on the robot, while CG received exercises on the lower limb rotor. The subjects were assessed with Timed Up and Go Test (TUG), Ashworth scale, knee range of motion (ROM), Lovett Scale, and tight circumference at baseline and at weeks 2, 4, and 6. Results: For seven parameters, the values credibly increased between consecutive measurements, and for the Ashworth scale, they credibly decreased. The biggest changes were observed for the measurements made with Lovett scale. The average thigh circumference as measured 5 and 15 cm above the knee increased credibly more in the robot condition, as compared to control condition. Additionally, the decrease in Ashworth values over time, although statistically credible in both groups, was credibly higher in the robot condition. Conclusion: The inclusion of the EMG-triggered neurorehabilitation robot in the patient's daily rehabilitation plan has a positive effect on outcomes of the treatment. Both proposed rehabilitation protocols significantly improved patients' condition regarding all measured outcomes, but the spasticity and thigh circumference improved significantly better in the robotic group in comparison to controls.

Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA

Widespread acceptance of a vaccine for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will be the next major step in fighting the coronavirus disease 2019 (COVID-19) pandemic, but achieving high uptake will be a challenge and may be impeded by online misinformation. To inform successful vaccination campaigns, we conducted a randomized controlled trial in the UK and the USA to quantify how exposure to online misinformation around COVID-19 vaccines affects intent to vaccinate to protect oneself or others. Here we show that in both countries-as of September 2020-fewer people would 'definitely' take a vaccine than is likely required for herd immunity, and that, relative to factual information, recent misinformation induced a decline in intent of 6.2 percentage points (95th percentile interval 3.9 to 8.5) in the UK and 6.4 percentage points (95th percentile interval 4.0 to 8.8) in the USA among those who stated that they would definitely accept a vaccine. We also find that some sociodemographic groups are differentially impacted by exposure to misinformation. Finally, we show that scientific-sounding misinformation is more strongly associated with declines in vaccination intent.

Reconsidering the Duchenne Smile: Formalizing and Testing Hypotheses about Eye Constriction and Positive Emotion

The common view of emotional expressions is that certain configurations of facial-muscle movements reliably reveal certain categories of emotion. The principal exemplar of this view is the Duchenne smile, a configuration of facial-muscle movements (i.e., smiling with eye constriction) that has been argued to reliably reveal genuine positive emotion. In this paper, we formalized a list of hypotheses that have been proposed regarding the Duchenne smile, briefly reviewed the literature weighing on these hypotheses, identified limitations and unanswered questions, and conducted two empirical studies to begin addressing these limitations and answering these questions. Both studies analyzed a database of 751 smiles observed while 136 participants completed experimental tasks designed to elicit amusement, embarrassment, fear, and physical pain. Study 1 focused on participants' self-reported positive emotion and Study 2 focused on how third-party observers would perceive videos of these smiles. Most of the hypotheses that have been proposed about the Duchenne smile were either contradicted by or only weakly supported by our data. Eye constriction did provide some information about experienced positive emotion, but this information was lacking in specificity, already provided by other smile characteristics, and highly dependent on context. Eye constriction provided more information about perceived positive emotion, including some unique information over other smile characteristics, but context was also important here as well. Overall, our results suggest that accurately inferring positive emotion from a smile requires more sophisticated methods than simply looking for the presence/absence (or even the intensity) of eye constriction.

Harsh environments promote alloparental care across human societies

Alloparental care is central to human life history, which integrates exceptionally short interbirth intervals and large birth size with an extended period of juvenile dependency and increased longevity. Formal models, previous comparative research, and palaeoanthropological evidence suggest that humans evolved higher levels of cooperative childcare in response to increasingly harsh environments. Although this hypothesis remains difficult to test directly, the relative importance of alloparental care varies across human societies, providing an opportunity to assess how local social and ecological factors influence the expression of this behaviour. We therefore, investigated associations between alloparental infant care and socioecology across 141 non-industrialized societies. We predicted increased alloparental care in harsher environments, due to the fitness benefits of cooperation in response to shared ecological challenges. We also predicted that starvation would decrease alloparental care, due to prohibitive energetic costs. Using Bayesian phylogenetic multilevel models, we tested these predictions while accounting for potential confounds as well as for population history. Consistent with our hypotheses, we found increased alloparental infant care in regions characterized by both reduced climate predictability and relatively lower average temperatures and precipitation. We also observed reduced alloparental care under conditions of high starvation. These results provide evidence of plasticity in human alloparenting in response to ecological contexts, comparable to previously observed patterns across avian and mammalian cooperative breeders. This suggests convergent social evolutionary processes may underlie both inter- and intraspecific variation in alloparental care.