Reducing Eating Disorder Risk Factors: A Pilot Effectiveness Trial of a Train-the-Trainer Approach to Dissemination and Implementation

Objective: Impediments limit dissemination and implementation of evidence-based interventions (EBIs), including lack of sufficient training. One strategy to increase implementation of EBIs is the train-the-trainer (TTT) model. The Body Project is a peer-led body image program that reduces eating disorder (ED) risk factors. This study examined the effectiveness of a TTT model at reducing risk factors in Body Project participants. Specifically, this study examined whether a master trainer could train a novice trainer to train undergraduate peer leaders to administer the Body Project such that individuals who received the Body Project (i.e., participants) would evidence comparable outcomes to previous trials.We hypothesized that participants would evidence reductions in ED risk factors, with effect sizes similar to previous trials. Method: Utilizing a TTT model, a master trainer trained a novice trainer to train undergraduate peer leaders to administer the Body Project to undergraduate women. Undergraduate women aged 18 years or older who received the Body Project intervention participated in the trial and completed measures at baseline, post-treatment, and five-month follow-up. Primary outcomes included body dissatisfaction, thin ideal internalization, negative affect, and ED pathology. Results: Participants demonstrated significant reductions in thin ideal internalization, ED pathology and body dissatisfaction at post-treatment and 5-month follow-up. At 5 months, using three different strategies for managing missing data, effect sizes were larger or comparable to earlier trials for 3 out of 4 variables. Discussion: Results support a TTT model for Body Project implementation and the importance of utilizing sensitivity analyses for longitudinal datasets with missing data

Using Factor Mixture Models to Evaluate the Type A/B Classification of Alcohol Use Disorders in a Heterogeneous Treatment Sample

BACKGROUND: The type A/B classification model for alcohol use disorders (AUDs) has received considerable empirical support. However, few studies examine the underlying latent structure of this subtyping model, which has been challenged as a dichotomization of a single drinking severity dimension. Type B, relative to type A, alcoholics represent those with early age of onset, greater familial risk, and worse outcomes from alcohol use. METHOD: We examined the latent structure of the type A/B model using categorical, dimensional, and factor mixture models in a mixed gender community treatment-seeking sample of adults with an AUD. RESULTS: Factor analytic models identified 2-factors (drinking severity/externalizing psychopathology and internalizing psychopathology) underlying the type A/B indicators. A factor mixture model with 2-dimensions and 3-classes emerged as the best overall fitting model. The classes reflected a type A class and two type B classes (B1 and B2) that differed on the respective level of drinking severity/externalizing pathology and internalizing pathology. Type B1 had a greater prevalence of women and more internalizing pathology and B2 had a greater prevalence of men and more drinking severity/externalizing pathology. The 2-factor, 3-class model also exhibited predictive validity by explaining significant variance in 12-month drinking and drug use outcomes. CONCLUSIONS: The model identified in the current study may provide a basis for examining different sources of heterogeneity in the course and outcome of AUDs

The Female Athlete Body (FAB) Study: Rationale, Design, and Baseline Characteristics

Background: Eating Disorders (EDs) are serious psychiatric illnesses marked by psychiatric comorbidity, medical complications, and functional impairment. Research indicates that female athletes are often at greater risk for developing ED pathology versus non-athlete females. The Female Athlete Body (FAB) study is a three-site, randomized controlled trial (RCT) designed to assess the efficacy of a behavioral ED prevention program for female collegiate athletes when implemented by community providers. This paper describes the design, intervention, and participant baseline characteristics. Future papers will discuss outcomes. Methods: Female collegiate athletes (N = 481) aged 17–21 were randomized by site, team, and sport type to either FAB or a waitlist control group. FAB consisted of three sessions (1.3 h each) of a behavioral ED prevention program. Assessments were conducted at baseline (pre-intervention), post-intervention (3 weeks), and six-, 12-, and 18-month follow-ups. Results: This study achieved 96% (N = 481) of target recruitment (N = 500). Few group differences emerged at baseline. Total sample analyses revealed moderately low baseline instances of ED symptoms and clinical cases. Conclusions: Health risks associated with EDs necessitate interventions for female athletes. The FAB study is the largest existing RCT for female athletes aimed at both reduction of ED risk factors and ED prevention. The methods presented and population recruited for this study represent an ideal intervention for assessing the effects of FAB on both the aforementioned outcomes. We anticipate that findings of this study (reported in future papers) will make a significant contribution to the ED risk factor reduction and prevention literature

Arctos: A Collaborative Collection Management Solution

Arctos (arctosdb.org) is a cost-effective, online collaborative collection management solution employed by more than 180 collections to manage and provide access to >3.5 million biodiversity and cultural records and >775,000 media objects. It also forms the backbone of Harvard’s MCZBase. Arctos leads in providing museums with community-driven solutions to managing and improving collections data, and developing workflows for data cleaning and publication. Arctos integrates biological, earth science, cultural and emerging data types such as environmental DNA and microbiomes to provide a nexus for the full suite of object data, data derivatives and products, and their management. Arctos is used by museum professionals, researchers, educators, students, government agencies, NGOs, and the public.Texas Advanced Computing Center (TACC

The Universal Einstein Radius Distribution from 10,000 SDSS Clusters

We present results from strong-lens modelling of 10,000 SDSS clusters, to establish the universal distribution of Einstein radii. Detailed lensing analyses have shown that the inner mass distribution of clusters can be accurately modelled by assuming light traces mass, successfully uncovering large numbers of multiple-images. Approximate critical curves and the effective Einstein radius of each cluster can therefore be readily calculated, from the distribution of member galaxies and scaled by their luminosities. We use a subsample of 10 well-studied clusters covered by both SDSS and HST to calibrate and test this method, and show that an accurate determination of the Einstein radius and mass can be achieved by this approach "blindly", in an automated way, and without requiring multiple images as input. We present the results of the first 10,000 clusters analysed in the range $0.1<z<0.55$, and compare them to theoretical expectations. We find that for this all-sky representative sample the Einstein radius distribution is log-normal in shape, with < Log(\theta_{e}\arcsec)>=0.73^{+0.02}_{-0.03}, $\sigma=0.316^{+0.004}_{-0.002}$, and with higher abundance of large $\theta_{e}$ clusters than predicted by $\Lambda$CDM. We visually inspect each of the clusters with \theta_{e}>40 \arcsec ($z_{s}=2$) and find that $\sim20$ are boosted by various projection effects detailed here, remaining with $\sim40$ real giant-lens candidates, with a maximum of \theta_{e}=69\pm12 \arcsec ($z_{s}=2$) for the most massive candidate, in agreement with semi-analytic calculations. The results of this work should be verified further when an extended calibration sample is available.Comment: 18 pages, 15 figures, 1 table; V2 accepted to MNRAS, includes a significant revision, in particular a new discussion of the result

'It's Reducing a Human Being to a Percentage'; Perceptions of Justice in Algorithmic Decisions

Data-driven decision-making consequential to individuals raises important questions of accountability and justice. Indeed, European law provides individuals limited rights to 'meaningful information about the logic' behind significant, autonomous decisions such as loan approvals, insurance quotes, and CV filtering. We undertake three experimental studies examining people's perceptions of justice in algorithmic decision-making under different scenarios and explanation styles. Dimensions of justice previously observed in response to human decision-making appear similarly engaged in response to algorithmic decisions. Qualitative analysis identified several concerns and heuristics involved in justice perceptions including arbitrariness, generalisation, and (in)dignity. Quantitative analysis indicates that explanation styles primarily matter to justice perceptions only when subjects are exposed to multiple different styles---under repeated exposure of one style, scenario effects obscure any explanation effects. Our results suggests there may be no 'best' approach to explaining algorithmic decisions, and that reflection on their automated nature both implicates and mitigates justice dimensions.Comment: 14 pages, 3 figures, ACM Conference on Human Factors in Computing Systems (CHI'18), April 21--26, Montreal, Canad

Advancing stem cell technologies for conservation of wildlife biodiversity.

Wildlife biodiversity is essential for healthy, resilient and sustainable ecosystems. For biologists, this diversity also represents a treasure trove of genetic, molecular and developmental mechanisms that deepen our understanding of the origins and rules of life. However, the rapid decline in biodiversity reported recently foreshadows a potentially catastrophic collapse of many important ecosystems and the associated irreversible loss of many forms of life on our planet. Immediate action by conservationists of all stripes is required to avert this disaster. In this Spotlight, we draw together insights and proposals discussed at a recent workshop hosted by Revive &amp; Restore, which gathered experts to discuss how stem cell technologies can support traditional conservation techniques and help protect animal biodiversity. We discuss reprogramming, in vitro gametogenesis, disease modelling and embryo modelling, and we highlight the prospects for leveraging stem cell technologies beyond mammalian species

Prebiotic Effects of Wheat Arabinoxylan Related to the Increase in Bifidobacteria, Roseburia and Bacteroides/Prevotella in Diet-Induced Obese Mice

BACKGROUND: Alterations in the composition of gut microbiota--known as dysbiosis--has been proposed to contribute to the development of obesity, thereby supporting the potential interest of nutrients targeting the gut with beneficial effect for host adiposity. We test the ability of a specific concentrate of water-extractable high molecular weight arabinoxylans (AX) from wheat to modulate both the gut microbiota and lipid metabolism in high-fat (HF) diet-induced obese mice. METHODOLOGY/PRINCIPAL FINDINGS: Mice were fed either a control diet (CT) or a HF diet, or a HF diet supplemented with AX (10% w/w) during 4 weeks. AX supplementation restored the number of bacteria that were decreased upon HF feeding, i.e. Bacteroides-Prevotella spp. and Roseburia spp. Importantly, AX treatment markedly increased caecal bifidobacteria content, in particular Bifidobacterium animalis lactis. This effect was accompanied by improvement of gut barrier function and by a lower circulating inflammatory marker. Interestingly, rumenic acid (C18:2 c9,t11) was increased in white adipose tissue due to AX treatment, suggesting the influence of gut bacterial metabolism on host tissue. In parallel, AX treatment decreased adipocyte size and HF diet-induced expression of genes mediating differentiation, fatty acid uptake, fatty acid oxidation and inflammation, and decreased a key lipogenic enzyme activity in the subcutaneous adipose tissue. Furthermore, AX treatment significantly decreased HF-induced adiposity, body weight gain, serum and hepatic cholesterol accumulation and insulin resistance. Correlation analysis reveals that Roseburia spp. and Bacteroides/Prevotella levels inversely correlate with these host metabolic parameters. CONCLUSIONS/SIGNIFICANCE: Supplementation of a concentrate of water-extractable high molecular weight AX in the diet counteracted HF-induced gut dysbiosis together with an improvement of obesity and lipid-lowering effects. We postulate that hypocholesterolemic, anti-inflammatory and anti-obesity effects are related to changes in gut microbiota. These data support a role for wheat AX as interesting nutrients with prebiotic properties related to obesity prevention

Pregnancy length and health in giant pandas: what can metabolic and urinary endocrine markers unveil?

Mature female giant pandas usually ovulate once a year. This is followed by an obligatory luteal phase, consisting of a long-lasting corpus luteum dormancy phase (CLD; primary increase in progestogens) and a much shorter active luteal phase (AL; secondary increase in progestogens). Varying duration of both the dormant (embryonic diapause) and AL (post-embryo reactivation) phases has hampered unambiguous pregnancy length determination in giant pandas until today. Additionally, progestogen profiles have been considered not to differ between pregnant and pseudopregnant cycles. Only ceruloplasmin, 13,14-dihydro-15-keto-PGF2α (PGFM) and – more recently – estrogens have been assigned diagnostic power so far. Our study investigated the competence of metabolic (fecal output) and Urinary Specific Gravity (USpG)-normalized urinary endocrine (progestogens, PGFM, glucocorticoids (GCM) and ceruloplasmin) markers for pregnancy monitoring including defining the duration of the AL phase length. Research on 24 (6 pregnant, 8 pseudopregnant and 10 non-birth) cycles of 6 giant pandas revealed a fixed AL phase length of 42 days in giant pandas, e.g. representing 6 weeks of post- diapause development in case of pregnancy. Progestogen concentrations were significantly higher in pregnant cycles throughout the majority of the AL phase, with significant higher values during the AL phase in healthy twin compared to singleton pregnancies. GCM concentrations were also markedly higher in giant pandas expecting offspring, with a clear increase towards birth in the final 2 weeks of pregnancy. This increase in GCM was running in parallel with elevating estrogen and PGFM concentrations, and decreasing progestogens. In addition, during the AL phase, a more pronounced decrease in fecal output was obvious for pregnant females. The combined profiles of non-invasive metabolic and endocrine markers, the latter normalized based on USpG, showed a true pregnancy signature during the AL phase. The findings of this study are applicable to retrospective evaluations of non-birth cycles facilitating categorizing those into pseudopregnant or lost pregnancies, with USpG-normalization of the urinary endocrine markers as a prerequisite