A prospective analysis of sleep deprivation and disturbance in surgical patients

Introduction: Sleep deprivation has a potentially deleterious effect on postoperative recovery. The aim of our prospective study was to identify the factors contributing to postoperative sleep deprivation and disturbance in order to recommend improvements in postoperative care. Methods: 102 consecutive patients attending for elective general and orthopaedic surgery were interviewed preoperatively (baseline) and postoperatively on their duration of sleep, number of wakenings during the night, factors contributing to sleep loss and the use of analgesia and night sedation. Results: Patients woke up a median of 5 times in the first postoperative night compared to a median of 3 times preoperatively (p = 0.01). Pain was the predominant factor preventing sleep, affecting 39% of patients preoperatively and 48% of patients on the first postoperative day. Other factors included noise from other patients and nursing staff, and using the toilet. Analgesia was taken by more than 90% of patients in the first two days, this number gradually reducing over the postoperative period. On the other hand, in the first two postoperative days, only about 5% of patients had night sedation. Discussion and conclusions: Apart from highlighting the need for effective pain management postoperatively, we believe that our study supports the drive towards single bed bays, where steps can be taken to minimize the impact of environmental factors on sleep

Applying a new concept for strategic performance indicators

Performance measurement provides critical information for strategic decision-making about the future of national infrastructure provision. The process of developing appropriate performance indicators must be based on an understanding of the high-level desired outcomes that infrastructure systems are intended to facilitate. These outcomes may be complex and dynamic and vary across the spectrum of infrastructure stakeholders. This paper demonstrates a conceptual process for developing outcome-related performance indicators by using case studies from the UK rail and water sectors. The case studies show that the process can provide an industry-specific picture of desired outcomes across the main stakeholders, together with their dimensions and associated performance indicators (so-called partial indicators). The work highlights potential shortfalls of a sector-by-sector approach to outcome-oriented strategic performance indicators and suggests that further work is required to integrate partial indicators to provide a holistic picture that recognises the contributions often made by a variety of infrastructures to a given high-level desired outcome

A conceptual approach to strategic performance indicators

Effective decision-making for the provision and maintenance of infrastructure systems requires strategic performance indicators aligned with a clear vision of the societal benefits that infrastructure will be expected to enable and systemic awareness of interdependencies between infrastructure sectors. This paper proposes a conceptual outcome-oriented approach to strategic infrastructure performance indicators as a systemic alternative to current approaches which predominantly focus on performance within individual sectors. The conceptual approach proposed aligns performance measures with stated priorities and future aspirations rather than past performance; provides a transparent framework for decision-making; can be applied at a range of scales; and creates an evidence base against which indicator design can be justified and reviewed. Additionally, the conceptual outcome-oriented approach proposed is adaptable for application in other areas of infrastructure decision-making, in particular the development of methodologies to assess what infrastructure will be needed in the future

ICIF response to the National Infrastructure Commission: Consultation (cm 9182)

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Being There: Young People Supporting Their Friends through Tough Times

This report documents one of the largest mixed methods studies to date examining informal help support provided by young people to their friends. We report on national survey data (n=169), as well as focus group data with 34 young people aged 16 - 25 who provide support to their friends. Specifically, the study examines the experiences of friends who support friends through tough times by focusing on how they perform this support, what resources young supporters use and have access to, what constrains this support and what they might need to enable the support they provide to their friends and peers. Our findings show the critical work young people are doing as supporters and documents the careful personalised support they offer their friends. Following sector consultations and discussions with young people, we offer key recommendations to ensure young people are resourced and supported in their care practices

Characterising Conversion Points and Complex Infrastructure Systems: Creating a System Representation for Agent-Based Modelling

Infrastructure, which is used to extract, transport, store, and transform resources into products or services to meet our utility needs faces numerous challenges caused by the agency of the various actors in the system. To understand these challenges, we propose it is necessary to move beyond considering each utility system as a distinct silo. In this paper, a conversion points approach is developed to characterize multiutility systems at any scale and for any specific or theoretical location. The story is told of the development of a conversion points approach and its application is examined using an agent-based model. Transport, energy, water, waste, and telecommunications systems are governed and run independently but in practice are highly interdependent. A way to represent all utility systems in an integrated way is described and the benefits of this representation are applied to UK household consumers

Interacting for the environment:Engaging Goffman in pro-environmental action

Whilst there are profound disagreements about how more sustainable forms of living might be achieved, most research on pro-environmental action recognises it as a fundamentally social challenge – demanding shifts not merely in individuals’ attitudes and behaviours, but also in social norms, contexts and practices. Despite the social nature of the challenge, perhaps the most fundamental social medium – social interaction - remains under-theorised in this area. To address this gap, this paper applies Erving Goffman’s understandings of social interaction to an ethnographic case study of a pro- environmental change initiative called Environment Champions. The analysis shows that social interaction plays a crucially important role in shaping responses to pro-environmental change processes that has the potential to both help and hinder the spread of pro-environmental action. The paper concludes by exploring how Goffman’s ideas develop and extend current debates about pro- environmental behaviour change

An Inquiry into Model Validity When Addressing Complex Sustainability Challenges

Scientific modelling is a prime means to generate understanding and provide much-needed information to support public decision-making in the fluid area of sustainability. A growing, diverse sustainability modelling literature, however, does not readily lend itself to standard validation procedures, which are typically rooted in the positivist principles of empirical verification and predictive success. Yet, to be useful to decision-makers, models, including their outputs and the processes through which they are established must be, and must be seen to be “valid.” *is study explores what model validity means in a problem space with increasingly interlinked and fast-moving challenges. We examine validation perspectives through ontological, epistemic, and methodological lenses, for a range of modelling approaches that can be considered as “complexity-compatible.” *e worldview taken in complexity-compatible modelling departs from the more standard modelling assumptions of complete objectivity and full predictability. Drawing on different insights from complexity science, systems thinking, economics, and mathematics, we suggest a ten-dimensional framework for progressing on model validity when investigating sustainability concerns. As such, we develop a widened view of the meaning of model validity for sustainability. It includes (i) acknowledging that several facets of validation are critical for the successful modelling of the sustainability of complex systems; (ii) tackling the thorny issues of uncertainty, subjectivity, and unpredictability; (iii) exploring the realism of model assumptions and mechanisms; (iv) embracing the role of stakeholder engagement and scrutiny throughout the modelling process; and (v) considering model purpose when assessing model validity. We wish to widen the debate on the meaning of model validity in a constructive way. We conclude that consideration of all these elements is necessary to enable sustainability models to support, more effectively, decision-making for complex interdependent systems

An Inquiry into Model Validity When Addressing Complex Sustainability Challenges

Scientific modelling is a prime means to generate understanding and provide much-needed information to support public decision-making in the fluid area of sustainability. A growing, diverse sustainability modelling literature, however, does not readily lend itself to standard validation procedures, which are typically rooted in the positivist principles of empirical verification and predictive success. Yet, to be useful to decision-makers, models, including their outputs and the processes through which they are established must be, and must be seen to be “valid.” This study explores what model validity means in a problem space with increasingly interlinked and fast-moving challenges. We examine validation perspectives through ontological, epistemic, and methodological lenses, for a range of modelling approaches that can be considered as “complexity-compatible.” The worldview taken in complexity-compatible modelling departs from the more standard modelling assumptions of complete objectivity and full predictability. Drawing on different insights from complexity science, systems thinking, economics, and mathematics, we suggest a ten-dimensional framework for progressing on model validity when investigating sustainability concerns. As such, we develop a widened view of the meaning of model validity for sustainability. It includes (i) acknowledging that several facets of validation are critical for the successful modelling of the sustainability of complex systems; (ii) tackling the thorny issues of uncertainty, subjectivity, and unpredictability; (iii) exploring the realism of model assumptions and mechanisms; (iv) embracing the role of stakeholder engagement and scrutiny throughout the modelling process; and (v) considering model purpose when assessing model validity. We wish to widen the debate on the meaning of model validity in a constructive way. We conclude that consideration of all these elements is necessary to enable sustainability models to support, more effectively, decision-making for complex interdependent systems