Racism, anti-racist practice and social work: articulating the teaching and learning experiences of Black social workers

In the mid 1990s a Black practice teacher programme was established in Manchester and Merseyside with the primary aim to increase the number of Black practice teachers in social work organisations, and in turn provide a supportive and encouraging learning environment for Black student social workers whilst on placement. In the north‐west of England research has been undertaken, to establish the quality of the practice teaching and student learning taking place with Black practice teachers and students. This paper is an exploration of the ideas generated within the placement process that particularly focused on the discourse of racism and ant‐racist practice. Black students and practice teachers explain their understanding of racism and anti‐racist practice within social work. From the research, the paper will critique some of the ideas concerning anti‐racism. In particular, it will question whether anti‐racist social work practice needs to be re‐evaluated in the light of a context with new migrants, asylum seekers and refugees. It will concluded, by arguing that whilst the terms anti‐racism, Black and Minority Ethnic have resonance as a form of political strategic essentialism, it is important to develop more positive representations in the future

Protocol for a randomized controlled trial of a specialized health coaching intervention to prevent excessive gestational weight gain and postpartum weight retention in women: the HIPP study

BackgroundPregnancy is a time of significant physiological and physical change for women. In particular, it is a time at which many women are at risk of gaining excessive weight. We describe the rationale and methods of the Health in Pregnancy and Post-birth (HIPP) Study, a study which aims primarily to determine the effectiveness of a specialized health coaching (HC) intervention during pregnancy, compared to education alone, in preventing excessive gestational weight gain and postpartum weight retention 12 months post birth. A secondary aim of this study is to evaluate the mechanisms by which our HC intervention impacts on weight management both during pregnancy and post birth.Methods/DesignThe randomized controlled trial will be conducted with 220 women who have a BMI &gt; 18.5 (American IOM cut-off for normal weight), are 18 years of age or older, English speaking, no history of disordered eating or diabetes and are less than 18 weeks gestation at recruitment. Women will be randomly allocated to either a specialized HC intervention group or an Education Alone group. Our specialized HC intervention has two components: (1) one-on-one sessions with a Health Coach, and (2) two by two hour educational group sessions led by a Health Coach. Women in the Education Alone group will receive two by two hour educational group sessions with no HC components. Body Mass Index, waist circumference, and psychological factors including motivation, readiness to change, symptoms of depression and anxiety, and body dissatisfaction will be assessed at baseline (14-16 weeks gestation), and again at follow-up: 32 weeks gestation, 6 weeks, 6 months and 12 months postpartum.DiscussionOur study responds to the urgent need to design effective interventions in pregnancy to prevent excessive gestational weight gain and postpartum weight retention. Our pregnancy HC intervention is novel and innovative and has been designed to be easily adopted by health professionals who work with pregnant women, such as obstetricians, midwives, allied health professionals and health psychologists. <br /

Self-Objectification Among Physically Active Women

This article discusses self-objectification among physically active women

Hospital Event Simulation Model: Arrivals to Discharge

Many Australian public hospitals operate under strict resource constraints. Arguably, this is manifested in higher incidence of ambulance ramping and patient flow congestion episodes, which has led to an increase in public complaints and, possibly, sub-optimal health outcomes for patients. Consequently, there is a well accepted need to make best use of all available information and domain knowledge to ensure that hospital resources and expertise are utilised more efficiently, for the benefit of patients. The latter is not a simple task since hospital operations involve complex interactions among many groups of health professionals utilising limited physical facilities and equipment. This is further complicated by the inherent variability of patient responses to treatments. Indeed, the stochastic nature of the demand process, as well as uncertainty in durations of medical treatments and patient recovery, lead to probabilistically distributed bed availability. Fortunately, in Australia, hospitals are ”data rich” in the sense that reliable records of patient journeys have been kept for many years. While older data may reflect procedures and priorities that are no longer in place, data from recent years may be regarded as quite robust, especially in cities that have not experienced major demographic changes. Thus there is an opportunity to apply modern tools of mathematical, statistical and simulation modelling to enhance our understanding of key processes that influence a hospital’s operations. The understanding so obtained can then be used to assist hospital staff in devising operational procedures that are likely to minimise disruption without adversely impacting the public service provided to the patient population. In this paper we outline the Hospital Event Simulation Model: Arrivals to Discharge (HESMAD) to describe the patterns of patient flows within the Flinders Medical Centre, an urban teaching hospital. The logical design of HESMAD was developed through extensive consultation with colleagues from the hospital. In particular, patients within HESMAD are not modelled as identical entities, rather, they are assigned different attribute values such as mode of arrival, triage category and division to reflect the typical profile of all patients. Patients go through a set of physical units and process modules that model various physical areas, processes, interactions and behaviours within the hospital to replicate a wide spectrum of patient journeys. Hospital and patient data from 2012 to 2013 were used to fit various probability distributions, for instance the waiting times for treatment or discharges. The model allows for a realistic representation of patient flows, at a level of resolution that was deemed appropriate by the hospitals data management experts. The model has been validated against historical data and through consultation with health care and hospital experts. Within space limitation we provide an outline and a brief discussion of HESMAD’s structure, features, capabilities, design decisions and development. In addition, we provide a brief case study demonstrating the potential applicability of HESMAD for ’what if’ analyses of hospital interventions. While all discussions are specific to the Flinders Medical Centre, the methodology used within HESMAD is generic enough to apply to other public hospitals in Australia