The Pictor Technique: Exploring Collaborative Working in Nursing

Pictor is a graphical visual technique with its origins in personal construct psychology and phenomenology. It was developed to explore experiences of collaborative working in health and social care contexts, but may be used in any setting where people with different backgrounds or perspectives need to interact around a specific task or goal. In this case study, we outline the principles behind the method and describe how it is used to collect data, and how such data may be analysed. We present a case example from a recent study of collaborative working among nurses and other professionals in relation to the care of people with cancer and long-term conditions. We conclude by reflecting on the strengths and weaknesses of the technique

Supporting people with active and advanced disease: a rapid review of the evidence

1.1 Background: the NCSI AAD group The National Cancer Survivorship Initiative (NCSI, 2010) was set up in response to the NHS Cancer Reform Strategy (Department of Health, 2007) as a collaboration between Macmillan Cancer Support, the Department of Health and NHS Improvement, with the goal to achieve a better understanding of the experiences of cancer survivors and to advocate for the provision of services to support them. Within this broad remit, it was recognised that there was a particular group of patients whose needs were commonly neglected; people who were experiencing the ongoing effects of cancer beyond first-line treatment but who were not at end of life. The Active and Advanced Disease (AAD) working group was created to consider issues of relevance to such people. 1.2 Aims of this review This project set out to meet the following aim: To review the literature on selected cancers in order to identify implications for the development of services to support patients experiencing difficulties associated with active and advanced disease

Marijuana Decriminalization: What does it mean in the United States?

It is well known in the drug policy field that eleven states reduced the criminal sanctions associated with possession of small amounts of marijuana. In this paper we review the eleven original decriminalization statutes, documenting key dimensions of these laws and identifying their common denominator. We then examine state laws in effect as of December 31, 1999, along the same key dimensions and show that it is impossible to uniquely identify the so-called decriminalized states. We show the extent to which non-decriminalized states have also reduced penalties associated with possession of small amounts of marijuana as early as 1989, calling into question the interpretation of studies evaluating this policy during the past decade. We conclude by showing that the inclusion of legal dimensions of the policy does not diminish the association identified between decriminalization and recent use, raising questions about how researchers should interpret such findings.

"It's not just about the patient, it's the families too.": End of life care in the home environment

Introduction: Most people when asked say they would prefer to die at home. However, ‘Death in Usual Place of Residence’ (DiUPR) does not give any real insight into the quality and experiences of care received. Additionally, DiUPR involves other family members resident in the home environment and their needs, preferences and experiences also need consideration. Aim(s) and Method(s): The aim of this work was to explore the experiences of patients and informal caregivers receiving at-home care from a specialist palliative care service. We undertook individual interviews with 11 patients and 10 significant others. We used the Pictor technique, a novel interview tool used to sensitively explore networks of support and experiences of palliative care. Interviews were analysed thematically. Results: Caring for a loved one at home was acknowledged as draining, but participants were effusive about the excellent at-home professional support they received from the specialist service. The care provided evidently recognised the needs of both patients and their families. Effective co-ordination of care, including liaison with other services was especially appreciated. Conclusion(s): With increasing trends towards DiUPR, it is vital that there are sufficient well-resourced palliative care services available in the community to support both patients and their families at the end of life. Pictor is a useful means to obtain detailed insight into individual experiences of end of life care. Care co-ordination emerged as key concern for patients receiving End of Life Care and their families

The Practice of Dyadic Interviewing: Strengths, Limitations and Key Decisions

Dyadic interviews, in which two participants are interviewed together, are becoming more popular in qualitative research, but are much less discussed in the methodological literature than individual and group forms. In this article, we consider the nature and value of dyadic interviews, recognizing them as active, relational encounters, shaped by what all parties bring to them, and infused with issues of power. Drawing on our research on altruistic motivation which involved 47 dyadic interviews conducted with 94 individuals and post-interview feedback from participants, we demonstrate the strengths and point out some of the potential pitfalls associated with the dyadic format, focusing on the practical and ethical issues in defining and recruiting dyads and the practice of conducting such interviews. We provide recommendations for researchers interested in using this method, and suggest research priorities for the further development of dyadic interviewing.Dyadische Interviews, bei denen zwei Teilnehmer*innen gemeinsam befragt werden, erfreuen sich in der qualitativen Forschung zunehmender Beliebtheit, werden aber in der methodologischen Literatur weit weniger diskutiert als Einzel- und Gruppenformen. In diesem Artikel befassen wir uns mit dem Wesen und dem Wert dyadischer Interviews, wobei wir sie als aktive, relationale Begegnungen betrachten, die von dem geprägt sind, was alle Beteiligten einbringen, und die mit Fragen der Macht verbunden sind. Auf der Grundlage unserer Forschungsarbeit zu altruistischer Motivation, die 47 dyadische Interviews mit 94 Personen und deren Feedback nach den Interviews umfasste, zeigen wir die Stärken des dyadischen Formats auf und weisen auf einige der potenziellen Fallstricke hin, die mit ihm verbunden sind, wobei wir uns auf praktische und ethische Fragen der Definition und Rekrutierung von Dyaden sowie auf die Praxis der Durchführung solcher Interviews konzentrieren. Wir geben Empfehlungen für Forscher*innen, die an der Anwendung dieser Methode interessiert sind und schlagen Forschungsprioritäten für deren weitere Entwicklung vor

Potential uses of AI for perioperative nursing handoffs: A qualitative study

OBJECTIVE: Situational awareness and anticipatory guidance for nurses receiving a patient after surgery are keys to patient safety. Little work has defined the role of artificial intelligence (AI) to support these functions during nursing handoff communication or patient assessment. We used interviews to better understand how AI could work in this context. MATERIALS AND METHODS: Eleven nurses participated in semistructured interviews. Mixed inductive-deductive thematic analysis was used to extract major themes and subthemes around roles for AI supporting postoperative nursing. RESULTS: Five themes were generated from the interviews: (1) nurse understanding of patient condition guides care decisions, (2) handoffs are important to nurse situational awareness, but multiple barriers reduce their effectiveness, (3) AI may address barriers to handoff effectiveness, (4) AI may augment nurse care decision making and team communication outside of handoff, and (5) user experience in the electronic health record and information overload are likely barriers to using AI. Important subthemes included that AI-identified problems would be discussed at handoff and team communications, that AI-estimated elevated risks would trigger patient re-evaluation, and that AI-identified important data may be a valuable addition to nursing assessment. DISCUSSION AND CONCLUSION: Most research on postoperative handoff communication relies on structured checklists. Our results suggest that properly designed AI tools might facilitate postoperative handoff communication for nurses by identifying specific elevated risks faced by a patient, triggering discussion on those topics. Limitations include a single center, many participants lacking of applied experience with AI, and limited participation rate

Young people with diabetes and their peers

Type 1 Diabetes (T1D) is amongst the most common form of chronic illness affecting young people in the UK. Self- management is crucial, but managing their T1D is often difficult for young people

Comparison of Speech Representations for Automatic Quality Estimation in Multi-Speaker Text-to-Speech Synthesis

We aim to characterize how different speakers contribute to the perceived output quality of multi-speaker Text-to-Speech (TTS) synthesis. We automatically rate the quality of TTS using a neural network (NN) trained on human mean opinion score (MOS) ratings. First, we train and evaluate our NN model on 13 different TTS and voice conversion (VC) systems from the ASVSpoof 2019 Logical Access (LA) Dataset. Since it is not known how best to represent speech for this task, we compare 8 different representations alongside MOSNet frame-based features. Our representations include image-based spectrogram features and x-vector embeddings that explicitly model different types of noise such as T60 reverberation time. Our NN predicts MOS with a high correlation to human judgments. We report prediction correlation and error. A key finding is the quality achieved for certain speakers seems consistent, regardless of the TTS or VC system. It is widely accepted that some speakers give higher quality than others for building a TTS system: our method provides an automatic way to identify such speakers. Finally, to see if our quality prediction models generalize, we predict quality scores for synthetic speech using a separate multi-speaker TTS system that was trained on LibriTTS data, and conduct our own MOS listening test to compare human ratings with our NN predictions.Comment: accepted at Speaker Odyssey 202