Cutting Ties with Pro-Ana: A Narrative Inquiry Concerning the Experiences of Pro-Ana Disengagement from Six Former Site Users.

Websites advocating the benefits of eating disorders (“Pro-Ana”) tend to reinforce and maintain restrictive eating and purging behaviors. Yet remarkably, no study has explored individual accounts of disengagement from these sites and the associated meanings. Using narrative inquiry, this study sought to address this gap. From the interviews of six women, two overarching storylines emerged. The first closely tied disengagement to recovery with varying positions of personal agency claimed: this ranged from enforced and unwelcomed breaks that ignited change, to a personal choice that became viable through the development of alternative social and personal identities. A strong counternarrative to “disengagement as recovery” also emerged. Here, disengagement from Pro-Ana was storied alongside a need to retain an ED lifestyle. With “recovery” being just one reason for withdrawal from Pro-Ana sites, clinicians must remain curious about the meanings individuals ascribe to this act, without assuming it represents a step toward recovery.Peer reviewedFinal Accepted Versio

Transient elastohydrodynamic lubrication analysis of a novel metal-on-metal hip prosthesis with a non-spherical femoral bearing surface

Effective lubrication performance of metal-on-metal hip implants only requires optimum conformity within the main loaded area, while it is advantageous to increase the clearance in the equatorial region. Such a varying clearance can be achieved by using non-spherical bearing surfaces for either acetabular or femoral components. An elastohydrodynamic lubrication model of a novel metal-on-metal hip prosthesis using a non-spherical femoral bearing surface against a spherical cup was solved under loading and motion conditions specified by ISO standard. A full numerical methodology of considering the geometric variation in the rotating non-spherical head in elastohydrodynamic lubrication solution was presented, which is applicable to all non-spherical head designs. The lubrication performance of a hip prosthesis using a specific non-spherical femoral head, Alpharabola, was analysed and compared with those of spherical bearing surfaces and a non-spherical Alpharabola cup investigated in previous studies. The sensitivity of the lubrication performance to the anteversion angle of the Alpharabola head was also investigated. Results showed that the non-spherical head introduced a large squeeze-film action and also led to a large variation in clearance within the loaded area. With the same equatorial clearance, the lubrication performance of the metal-on-metal hip prosthesis using an Alpharabola head was better than that of the conventional spherical bearings but worse than that of the metal-on-metal hip prosthesis using an Alpharabola cup. The reduction in the lubrication performance caused by the initial anteversion angle of the non-spherical head was small, compared with the improvement resulted from the non-spherical geometry

The Utility of Functional Movement Assessment on NBA Players

Professional basketball related injuries have not declined over the last decade despite improvements in training and conditioning or medical advancements in diagnostics, surgery, or rehabilitation. A descriptive epidemiological study of 80% of the National Basketball Association (NBA) teams over 17 years reported an injury incidence of 19.1 per 1000 athlete exposures, and 59,179 games missed due to injury. Starkey found that the there has been a 12.4% increase in game-related injuries in the NBA in a 10-year period from the 1988 - 1997 seasons. It is suspected that increased contact within the NBA along with improved player athleticism, size, power, and speed have contribute to the rise in injuries. The most commonly reported injuries in the NBA as reported via the greatest number of days missed include ankle sprains, patellofemoral inflammation, knee sprains, and lumbar strains. Recent trends involve less focus on specific physical or clinical measures and increased attention on the assessment of functional movement patterns for the purpose of predicting the likelihood of injury. The Functional Movement Screen (FMSTM) was introduced as a pre-participation examination intended to evaluate the quality of seven basic movement patterns that require a balance of both mobility and stability. The functional movements tested include: deep squat, hurdle step, in-line lunge, shoulder mobility, active straight leg raise, trunk stability push-up, and rotary stability. It is designed to assess the extremes of specific movements and positions for the purpose of identifying potential limitation, compensation, and asymmetry in individuals without obvious pathology. Recent literature has linked this screen to injury prediction in numerous populations that may be predisposed to injury, including professional football players, firefighters, collegiate female athletes, elite track and field athletes, military personnel. The majority of reliability studies conclude that the FMSTM has good intra-rater reliability. While some researchers conclude that reliability increases with additional training and clinical experience, others claim that the FMS intra-rater reliability was not improved with FMS certification. Inter- rater reliability was reported in recent studies to range from moderate and good to high. The Y-balance Test (YBT) is pre-participation assessment used to screen individuals who may have potential for lower extremity injury. This test involves the examination of dynamic balance and postural control. While research is still lacking regarding the validity and utility of the YBT-LQ, the SEBT has been reported to have a moderate to strong effect size and that this test was reliable and valid as a dynamic predictor to lower extremity injuries. No studies have investigated the outcomes of YBT as an injury predictor in professional basketball athletes or the relationship of these factors with functional movement screens.https://ecommons.udayton.edu/dpt_symposium/1011/thumbnail.jp

The lowa farmer and world war II

World War II is the biggest fact in the Iowa farm situation. Though Iowa is far removed from air bombing and submarine torpedoing, it is on the battle front so far as economic and social effects of the war are concerned. Iowa’s commercial agriculture underwent terrific strain during and following World War I, and the pressures arising out of World War II promise to be similar, although less severe. It is the purpose of this report to estimate what some of these pressures will be. An understanding of the social and economic forces at work is necessary before plans can be made and action taken to ease the shock of war. The experience of the earlier war helps us to understand these forces, but that experience must be interpreted in light of the changed situation today

Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy

Methane (CH) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH. To address this limitation, we developed novel CH prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH production (g CH/animal·d, ANIM-B models) and CH yield (g CH/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin’s concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH emissions from sheep, providing valuable insights for future research and mitigation strategies.Te authors gratefully acknowledge funding for this project from the USDA National Institute of Food and Agriculture (Award number: 2014-67003-21979). Te animal and microbial data originated from a study funded by the Pastoral Greenhouse Gas Research Consortium (www.pggrc.co.nz)

Mitigation of methane and nitrous oxide emissions from animal operations: III. A review of animal management mitigation options

The goal of this review was to analyze published data on animal management practices that mitigate enteric methane (CH4) and nitrous oxide (N2O) emissions from animal operations. Increasing animal productivity can be a very effective strategy for reducing greenhouse gas (GHG) emissions per unit of livestock product. Improving the genetic potential of animals through planned cross-breeding or selection within breeds and achieving this genetic potential through proper nutrition and improvements in reproductive efficiency, animal health, and reproductive lifespan are effective approaches for improving animal productivity and reducing GHG emission intensity. In subsistence production systems, reduction of herd size would increase feed availability and productivity of individual animals and the total herd, thus lowering CH4 emission intensity. In these systems, improving the nutritive value of low-quality feeds for ruminant diets can have a considerable benefit on herd productivity while keeping the herd CH4 output constant or even decreasing it. Residual feed intake may be a tool for screening animals that are low CH4 emitters, but there is currently insufficient evidence that low residual feed intake animals have a lower CH4 yield per unit of feed intake or animal product. Reducing age at slaughter of finished cattle and the number of days that animals are on feed in the feedlot can significantly reduce GHG emissions in beef and other meat animal production systems. Improved animal health and reduced mortality and morbidity are expected to increase herd productivity and reduce GHG emission intensity in all livestock production systems. Pursuing a suite of intensive and extensive reproductive management technologies provides a significant opportunity to reduce GHG emissions. Recommended approaches will differ by region and species but should target increasing conception rates in dairy, beef, and buffalo, increasing fecundity in swine and small ruminants, and reducing embryo wastage in all species. Interactions among individual components of livestock production systems are complex but must be considered when recommending GHG mitigation practices

Internet-delivered cognitive behavior therapy for anxiety and insomnia in a higher education context

© 2015 Taylor & Francis. Background and Objectives: Anxiety and insomnia can be treated with internet-delivered Cognitive Behavioral Therapy (iCBT). iCBT may be well-suited to students who are known to be poor help-seekers and suffer these symptoms. iCBT can offer easy access to treatment and increase service availability. The aim of this study was to evaluate the efficacy of anxiety and insomnia iCBT programs in students. Design: A randomized, controlled study. Methods: Students were randomly allocated to intervention (“Anxiety Relief”: n = 43; “Insomnia Relief”: n = 48; control: n = 47). Interventions lasted six weeks. Outcome measures were the State-Trait Anxiety Inventory and the Pittsburgh Sleep Quality Index. Results: Significant within-group reductions in anxiety (t(31) = 2.00, p =.03) with moderate between-groups (compared to control) effect size (d =.64) and increases in sleep quality (t(31) = 3.46, p =.002) with a moderate between-groups effect size (d =.55) were found for completers of the anxiety program from pre-to post-intervention. Significant within-group increases in sleep quality were found for completers of the insomnia program from pre-to post-intervention (t(35) = 4.28, p >.001) with a moderate between-groups effect size (d =.51). Conclusions: Findings support the use of iCBT for anxiety and insomnia in students, and indicate that further research is needed

Brain-behaviour modes of covariation in healthy and clinically depressed young people.

Understanding how variations in dimensions of psychometrics, IQ and demographics relate to changes in brain connectivity during the critical developmental period of adolescence and early adulthood is a major challenge. This has particular relevance for mental health disorders where a failure to understand these links might hinder the development of better diagnostic approaches and therapeutics. Here, we investigated this question in 306 adolescents and young adults (14-24 y, 25 clinically depressed) using a multivariate statistical framework, based on canonical correlation analysis (CCA). By linking individual functional brain connectivity profiles to self-report questionnaires, IQ and demographic data we identified two distinct modes of covariation. The first mode mapped onto an externalization/internalization axis and showed a strong association with sex. The second mode mapped onto a well-being/distress axis independent of sex. Interestingly, both modes showed an association with age. Crucially, the changes in functional brain connectivity associated with changes in these phenotypes showed marked developmental effects. The findings point to a role for the default mode, frontoparietal and limbic networks in psychopathology and depression.Wellcome Trus

Brain-behaviour modes of covariation in healthy and clinically depressed young people

Abstract: Understanding how variations in dimensions of psychometrics, IQ and demographics relate to changes in brain connectivity during the critical developmental period of adolescence and early adulthood is a major challenge. This has particular relevance for mental health disorders where a failure to understand these links might hinder the development of better diagnostic approaches and therapeutics. Here, we investigated this question in 306 adolescents and young adults (14–24 y, 25 clinically depressed) using a multivariate statistical framework, based on canonical correlation analysis (CCA). By linking individual functional brain connectivity profiles to self-report questionnaires, IQ and demographic data we identified two distinct modes of covariation. The first mode mapped onto an externalization/internalization axis and showed a strong association with sex. The second mode mapped onto a well-being/distress axis independent of sex. Interestingly, both modes showed an association with age. Crucially, the changes in functional brain connectivity associated with changes in these phenotypes showed marked developmental effects. The findings point to a role for the default mode, frontoparietal and limbic networks in psychopathology and depression