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

Using the Pictor technique to reflect on collaborative working in undergraduate nursing and midwifery placements

Pictor is a visual technique for exploring episodes of collaborative working, and has been developed for use in health care research at the Centre for Applied Psychological Research at the University of Huddersfield. This thesis explores whether the technique could usefully translate into a tool for reflection for students of nursing and midwifery, investigating how the features of the technique facilitate reflection, how students evaluate the technique, and how talk elicited using Pictor might dovetail with existing models of reflection. Findings indicate that Pictor facilitates in-depth talk about care and collaboration focused around patients (nursing) and women in labour (midwifery), including the discomforts of learning to be a practitioner, how the challenges of practice are met, and how reflection works for students on-the-ground during their placement experiences. Students found the technique easy and enjoyable to use. Implications of the research include Pictor's possible use as a tool for individual and group reflection, eliciting thinking which meets the same criteria as existing written models of reflection, and suggest the potential for a secondary analysis of the interview data with a view to making links with traditional taxonomies of learning

Setting "survivorship" in context : the role of everyday resources in adjusting to life after cancer treatment with curative intent

Background: The number of people living beyond cancer in the UK is rapidly increasing, and their supportive care needs are a pressing issue. Patients treated with curative intent move on to a self management pathway, which uses checklists to measure care requirements. Patients are expected to consider ways of addressing their own psychosocial needs. The focus of care on the quantification of needs and the cognitive strategies used to manage them fails to take the subtleties of patients’ social and material context into account. Research suggests that the self management agenda does not adequately acknowledge the challenges of day-to-day experiences of illness, and how people engage with their resources to adapt to life after treatment.Aim of the study: To explore how everyday social and material resources can be used to adapt to life in the year beyond cancer treatment with curative intent.Methods: In 2014–15, in-depth interviews were conducted with twenty-six people recently treated for breast, colorectal or prostate cancer (twenty using photo elicitation), followed by seventeen longitudinal interviews approximately six months later. Participants from a range of social backgrounds were recruited through clinics in Yorkshire and the Humber. The method of analysis was constructivist grounded theory.Findings: Treatment with curative intent is interpreted as turning a curve in life’s pathway, requiring gradual reorientation. This is shaped by three processes. In Responding to diagnosis and treatment, participants drew on past identities to reinforce their sense of self, and personalised care was crucial. In Using social resources for meaning-making, perspectives from the worlds of the family, clinic and workplace contributed to participants’ understanding of their situation, and the “survivor” label was rejected. Developing assets for recovery involved consolidating the meaning of their illness, negotiating personal change, and using material and environmental resources to regain control, create comfort and chase continuity.Conclusion: People with good prognoses have a unique outlook on adaptation after treatment. Finding ways of assessing the assets that people do have, rather than what they do not have, is a good starting point for follow-up care. Everyday resources can be used to address three key objectives in adaptation: control, comfort and continuity

An Extended Empirical Saddlepoint Approximation for Intractable Likelihoods

The challenges posed by complex stochastic models used in computational ecology, biology and genetics have stimulated the development of approximate approaches to statistical inference. Here we focus on Synthetic Likelihood (SL), a procedure that reduces the observed and simulated data to a set of summary statistics, and quantifies the discrepancy between them through a synthetic likelihood function. SL requires little tuning, but it relies on the approximate normality of the summary statistics. We relax this assumption by proposing a novel, more flexible, density estimator: the Extended Empirical Saddlepoint approximation. In addition to proving the consistency of SL, under either the new or the Gaussian density estimator, we illustrate the method using two examples. One of these is a complex individual-based forest model for which SL offers one of the few practical possibilities for statistical inference. The examples show that the new density estimator is able to capture large departures from normality, while being scalable to high dimensions, and this in turn leads to more accurate parameter estimates, relative to the Gaussian alternative. The new density estimator is implemented by the esaddle R package, which can be found on the Comprehensive R Archive Network (CRAN)

"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

From unskilled to employable: using a qualitative examination of the ‘Placement Timeline Research Method’ to explore student professional and personal development whilst on multiple WIL experiences.

This paper explores the method and findings of a qualitative examination into multiple work integrated learning (MWIL) placements. The research consisted of 14 reflective interviews with students from across discipline areas who had undertaken a series of work placements. The range of MWIL experiences included professional placements in nursing and youth work, yearlong placements in accountancy and engineering, self-directed WIL experiences in arts, informal and part-time placements. The aim of this study was to explore the transitions that took place throughout multiple placements that helped the student to become a work ready and an effective professional. A research method, 'Placement Timeline' was developed. This allows a reflective structure for the researcher to tease out skill development and work readiness. All interviews were transcribed and coded using NVivo qualitative software. The paper will discuss selected findings from the research. These provide insights into how multiple WIL experiences may benefit students in their preparation for work. In effect it was as if the work readiness and skills relating to an uncertain and ever changing job market skills were fast tracked over MWIL.This research highlights the key transitional features of MWIL

Variance propagation for density surface models

Data from the SCANS-II project were supported by the EU LIFE Nature programme (project LIFE04NAT/GB/000245) and governments of range states: Belgium, Denmark, France, Germany, Ireland, Netherlands, Norway, Poland, Portugal, Spain, Sweden, and UK. This work was funded by OPNAV N45 and the SURTASS LFA Settlement Agreement, and being managed by the US Navy’s Living Marine Resources program under Contract No. N39430-17-C-1982, US Navy, Chief of Naval Operations (Code N45), grant number N00244-10-1-0057 and the International Whaling Commission.Spatially explicit estimates of population density, together with appropriate estimates of uncertainty, are required in many management contexts. Density surface models (DSMs) are a two-stage approach for estimating spatially varying density from distance sampling data. First, detection probabilities—perhaps depending on covariates—are estimated based on details of individual encounters; next, local densities are estimated using a GAM, by fitting local encounter rates to location and/or spatially varying covariates while allowing for the estimated detectabilities. One criticism of DSMs has been that uncertainty from the two stages is not usually propagated correctly into the final variance estimates. We show how to reformulate a DSM so that the uncertainty in detection probability from the distance sampling stage (regardless of its complexity) is captured as an extra random effect in the GAM stage. In effect, we refit an approximation to the detection function model at the same time as fitting the spatial model. This allows straightforward computation of the overall variance via exactly the same software already needed to fit the GAM. A further extension allows for spatial variation in group size, which can be an important covariate for detectability as well as directly affecting abundance. We illustrate these models using point transect survey data of Island Scrub-Jays on Santa Cruz Island, CA, and harbour porpoise from the SCANS-II line transect survey of European waters. Supplementary materials accompanying this paper appear on-line.Publisher PDFPeer reviewe