Ruth Evans

This volume, designed with the student reader in mind, is an indispensable blend of key essays in the field with specially commissioned new material by feminist scholars from the UK and the US. It includes a diversity of texts and feminist approaches, a substantial and very illuminating introduction by the editors, and an annotated list of Further Reading, offering preliminary guidance to the reader approaching the topic of gender and medieval literature for the first time. Works and writers covered include: * Chaucer * Margery Kempe * Christine de Pisan * The Katherine group of Saints' Lives * Langland's Piers Plowman * Medieval cycle drama Students of both medieval and feminist literature will find this an essential work for study and reference.

Artificial intelligence (AI) in healthcare describes algorithm-based computational techniques which manage and analyse large datasets to make inferences and predictions. There are many potential applications of AI in the care of older people, from clinical decision support systems that can support identification of delirium from clinical records to wearable devices that can predict the risk of a fall. We held four meetings of older people, clinicians and AI researchers. Three priority areas were identified for AI application in the care of older people. These included: monitoring and early diagnosis of disease, stratified care and care coordination between healthcare providers. However, the meetings also highlighted concerns that AI may exacerbate health inequity for older people through bias within AI models, lack of external validation amongst older people, infringements on privacy and autonomy, insufficient transparency of AI models and lack of safeguarding for errors. Creating effective interventions for older people requires a person-centred approach to account for the needs of older people, as well as sufficient clinical and technological governance to meet standards of generalisability, transparency and effectiveness. Education of clinicians and patients is also needed to ensure appropriate use of AI technologies, with investment in technological infrastructure required to ensure equity of access.

1. Introduction: The Second Sex and the postmodern - Ruth Evans 2. Writing from the centre: ironies of otherness and marginality - Margaret Atack 3. The influence of The Second Sex on the French feminist scene - Catherine Rodgers 4. Simone de Beauvoir: transcending fictions - Lorna Sage 5. A certain lack of symmetry: Beauvoir on autonomous agency and women's embodiment - Catriona Mackenzie 6. Reading, resistance and disempowerment - Stephen Horton 7. To become or not to become or, Must two be second? Simone de Beauvoir and The Second Sex in conversation - Nicole Ward Jouve Bibliography Index

BACKGROUND: Increasing attention is being given to the analysis of large health datasets to derive new clinical decision support systems (CDSS). However, few data-driven CDSS are being adopted into clinical practice. Trust in these tools is believed to be fundamental for acceptance and uptake but to date little attention has been given to defining or evaluating trust in clinical settings. OBJECTIVES: A scoping review was conducted to explore how and where acceptability and trustworthiness of data-driven CDSS have been assessed from the health professional's perspective. METHODS: Medline, Embase, PsycInfo, Web of Science, Scopus, ACM Digital, IEEE Xplore and Google Scholar were searched in March 2022 using terms expanded from: "data-driven" AND "clinical decision support" AND "acceptability". Included studies focused on healthcare practitioner-facing data-driven CDSS, relating directly to clinical care. They included trust or a proxy as an outcome, or in the discussion. The preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) is followed in the reporting of this review. RESULTS: 3291 papers were screened, with 85 primary research studies eligible for inclusion. Studies covered a diverse range of clinical specialisms and intended contexts, but hypothetical systems (24) outnumbered those in clinical use (18). Twenty-five studies measured trust, via a wide variety of quantitative, qualitative and mixed methods. A further 24 discussed themes of trust without it being explicitly evaluated, and from these, themes of transparency, explainability, and supporting evidence were identified as factors influencing healthcare practitioner trust in data-driven CDSS. CONCLUSION: There is a growing body of research on data-driven CDSS, but few studies have explored stakeholder perceptions in depth, with limited focused research on trustworthiness. Further research on healthcare practitioner acceptance, including requirements for transparency and explainability, should inform clinical implementation.