Sisters, Objects of Desire, or Barbarians: German Nurses in the First World War

This is a study of German nurses during the First World War that examines the differing perceptions and representations of them that appeared during the war, focusing on those of British and American nurses and German soldiers that were at odds with the ideal image of nurses. I trace British and American nurses’ opinions using nursing and medical journals and investigate the complex relationship between German nurses and soldiers using soldiers’ newspapers as a main source base. I argue that representations and perceptions of German nurses that contrasted with the ideal image of a nurse are crucial to understanding the relationships between German, British, and American nurses because the perceived deviations from the ideal image strained their relationships even after the war was over. These conflicting images are also essential to appreciating the complex relationship between German soldiers and nurses because they show that, at times, these relationships took on more than the familial characteristics featured in the ideal image to include romantic characteristics that could complicate nurses’ lives and cause concern among German military authorities and the public. This study demonstrates the complexity of these various relationships and the effect the war had on them, which extended beyond the signing of the armistice

Unidimensional Models Do Not Fit Unidimensional Mixed Format Data Better than Multidimensional Models

This dissertation examines the scaling of large scale assessments containing both dichotomous and polytomous items, mixed format assessments. Because large scale assessments are generally built to measure one construct, e.g. eighth grade mathematics, unidimensional data was generated to simulate a mixed format assessment. The test length, number of polytomous to dichotomous items per assessment and the discrimination level between dichotomous and polytomous items were varied in this study. There were five item combinations and two level of discrimination defined. The goal of this dissertation was to compare the fit of the generated data to three different Item Response Theory models; one unidimensional and two multidimensional. The first model used to fit the data was the same model type used to generate the data; a 3PL IRT model in combination with the Generalized Partial Credit model. The second model was the Hierarchical MIRT Model. The final model was the bi-factor model. The research questions examined in this study were; (1) Which of the models achieves the best model fit across simulation conditions?, and (2) Do the variables of item combination or discrimination affect the model fit? The study showed that the bi-factor model fit unidimensional data, in mixed format, better than either the unidimensional or the hierarchical MIRT models. The criterion used to make this determination was the Bayesian convergence criterions; BIC, DIC and AIC. Overall, the bi-factor model fit the unidimensional mixed format data better than the generating model fit the data. The hierarchical MIRT model did not fit the data very well, and in a few cases, did not converge. The more polytomous item included on the assessment the better the bi-factor model improved overall fit over the unidimensional model. This result suggests that noise in the data from mixed format assessments can cause the unidimensional models to fail to fail to fit the data. This study illustrates the format alone can create the appearance of dimensionality. However since the data was generated as unidimensional, this format dimensionality affect was an attribute of the data alone, not of items or examinees interactions with the items. Mixed format assessments create an artifact in the data that causes the data to factor into dimensions that are not actually present. It appears there is noise in the data of mixed format assessment that needs to accounted for when scaling

How do frontline staff use patient experience data for service improvement? Findings from an ethnographic case study evaluation

Funding Information: The authors would like to thank the following: the ward teams and senior management teams at the six participating case study sites. Neil Churchill, Angela Coulter, Ray Fitzpatrick, Crispin Jenkinson, Trish Greenhalgh and Sian Rees who were co-investigators on the study, contributing to the original design and conduct of the study. Esther Ainley and Steve Sizmur from Picker Institute Europe, who contributed to data collection and analysis. Prof. John Gabbay and Prof. Andr? le May, University of Southampton, for facilitating the learning community meetings. The members of the lay advisory panel: Barbara Bass, Tina Lonhgurst, Georgina McMasters, Carol Munt, Gillian Richards, Tracey Richards, Gordon Sturmey, Karen Swaffield, Ann Tomlime and Paul Whitehouse. The external members of the Study Steering Committee: Joanna Foster, Tony Berendt, Caroline Shuldham, Joanna Goodrich, Leigh Kendall, Bernard Gudgin and Manoj Mistry. At the time of conducting the research LL and SP were employed by the University of Oxford. Preliminary findings from the study have been presented publicly at the following conferences: European Association for Communication in Healthcare 2016; The International Society for Quality in Healthcare 2017; Health Services Research UK 2017; Medical Sociology 2018. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Publisher Copyright: © The Author(s) 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Peer reviewedPublisher PD

Measuring the relationship between bilingual exposure and social attentional preferences in autistic children

Background: Autistic children show reduced attentional preferences to social stimuli early in development, and these differences have consequences on a range of social domains. One factor that could influence development in those processes is bilingualism. Parents and practitioners frequently have unfounded concerns that bilingualism could cause delays in autistic children, yet there is little evidence to dispute this idea. While there are studies focusing on the impact of bilingualism on cognition in autistic children, no research has focused on the relationship between bilingualism and social attention. Aims: This study therefore investigated the impact of bilingual exposure on social attention in autistic (n=33) and neurotypical children (n=42) aged 6-13 years. Rather than a monolingual/bilingual comparison, participants had varying degrees of bilingual exposure, and exposure was treated as a continuous variable. Participants completed an eye-tracking task measuring visual attention to interacting versus non-interacting human figures. Results: Bilingual exposure did not affect dwell time to interacting or non-interacting figures for the neurotypical or autistic groups. However, there was a 3-way interaction between diagnosis, figure type and vocabulary scores on dwell time. Conclusions: Higher vocabulary scores in neurotypical participants was associated with significantly less dwell time to non-interacting stimuli. This is the first study to assess the effects of bilingualism on social attention; here, concerns of bilingualism are not upheld.https://www.mdpi.com/journal/languagesinpressinpres

Understanding how front-line staff use patient experience data for service improvement: an exploratory case study evaluation

Background and aim: The NHS collects a large number of data on patient experience, but there are concerns that it does not use this information to improve care. This study explored whether or not and how front-line staff use patient experience data for service improvement. Methods: Phase 1 – secondary analysis of existing national survey data, and a new survey of NHS trust patient experience leads. Phase 2 – case studies in six medical wards using ethnographic observations and interviews. A baseline and a follow-up patient experience survey were conducted on each ward, supplemented by in-depth interviews. Following an initial learning community to discuss approaches to learning from and improving patient experience, teams developed and implemented their own interventions. Emerging findings from the ethnographic research were shared formatively. Phase 3 – dissemination, including an online guide for NHS staff. Key findings: Phase 1 – an analysis of staff and inpatient survey results for all 153 acute trusts in England was undertaken, and 57 completed surveys were obtained from patient experience leads. The most commonly cited barrier to using patient experience data was a lack of staff time to examine the data (75%), followed by cost (35%), lack of staff interest/support (21%) and too many data (21%). Trusts were grouped in a matrix of high, medium and low performance across several indices to inform case study selection. Phase 2 – in every site, staff undertook quality improvement projects using a range of data sources. The number and scale of these varied, as did the extent to which they drew directly on patient experience data, and the extent of involvement of patients. Before-and-after surveys of patient experience showed little statistically significant change. Making sense of patient experience ‘data’ Staff were engaged in a process of sense-making from a range of formal and informal sources of intelligence. Survey data remain the most commonly recognised and used form of data. ‘Soft’ intelligence, such as patient stories, informal comments and daily ward experiences of staff, patients and family, also fed into staff’s improvement plans, but they and the wider organisation may not recognise these as ‘data’. Staff may lack confidence in using them for improvement. Staff could not always point to a specific source of patient experience ‘data’ that led to a particular project, and sometimes reported acting on what they felt they already knew needed changing. Staff experience as a route to improving patient experience Some sites focused on staff motivation and experience on the assumption that this would improve patient experience through indirect cultural and attitudinal change, and by making staff feel empowered and supported. Staff participants identified several potential interlinked mechanisms: (1) motivated staff provide better care, (2) staff who feel taken seriously are more likely to be motivated, (3) involvement in quality improvement is itself motivating and (4) improving patient experience can directly improve staff experience. ‘Team-based capital’ in NHS settings We propose ‘team-based capital’ in NHS settings as a key mechanism between the contexts in our case studies and observed outcomes. ‘Capital’ is the extent to which staff command varied practical, organisational and social resources that enable them to set agendas, drive process and implement change. These include not just material or economic resources, but also status, time, space, relational networks and influence. Teams involving a range of clinical and non-clinical staff from multiple disciplines and levels of seniority could assemble a greater range of capital; progress was generally greater when the team included individuals from the patient experience office. Phase 3 – an online guide for NHS staff was produced in collaboration with The Point of Care Foundation. Limitations: This was an ethnographic study of how and why NHS front-line staff do or do not use patient experience data for quality improvement. It was not designed to demonstrate whether particular types of patient experience data or quality improvement approaches are more effective than others. Future research: Developing and testing interventions focused specifically on staff but with patient experience as the outcome, with a health economics component. Studies focusing on the effect of team composition and diversity on the impact and scope of patient-centred quality improvement. Research into using unstructured feedback and soft intelligence