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Rough sleeping is a chronic experience faced by some of the most disadvantaged people in modern society. This paper describes work carried out in partnership with Homeless Link (HL), a UK-based charity, in developing a data-driven approach to better connect people sleeping rough on the streets with outreach service providers. HL's platform has grown exponentially in recent years, leading to thousands of alerts per day during extreme weather events; this overwhelms the volunteer-based system they currently rely upon for the processing of alerts. In order to solve this problem, we propose a human-centered machine learning system to augment the volunteers' efforts by prioritizing alerts based on the likelihood of making a successful connection with a rough sleeper. This addresses capacity and resource limitations whilst allowing HL to quickly, effectively, and equitably process all of the alerts that they receive. Initial evaluation using historical data shows that our approach increases the rate at which rough sleepers are found following a referral by at least 15% based on labeled data, implying a greater overall increase when the alerts with unknown outcomes are considered, and suggesting the benefit in a trial taking place over a longer period to assess the models in practice. The discussion and modeling process is done with careful considerations of ethics, transparency, and explainability due to the sensitive nature of the data involved and the vulnerability of the people that are affected.
Evidence-based treatment for panic disorder consists of disorder-specific cognitive behavioural therapy (CBT) protocols. However, most measures of CBT competence are generic and there is a clear need for disorder-specific assessment measures.
To fill this gap, we evaluated the psychometric properties of the Cognitive Therapy Competence Scale (CTCP) for panic disorder.
CBT trainees (n = 60) submitted audio recordings of CBT for panic disorder that were scored on a generic competence measure, the Cognitive Therapy Scale – Revised (CTS-R), and the CTCP by markers with experience in CBT practice and evaluation. Trainees also provided pre- to post-treatment clinical outcomes on disorder-specific patient report measures for cases corresponding to their therapy recordings.
The CTCP exhibited strong internal consistency (α = .79–.91) and inter-rater reliability (ICC = .70–.88). The measure demonstrated convergent validity with the CTS-R (r = .40–.54), although investigation into competence classification indicated that the CTCP may be more sensitive at detecting competence for panic disorder-specific CBT skills. Notably, the CTCP demonstrated the first indication of a relationship between therapist competence and clinical outcome for panic disorder (r = .29–.35); no relationship was found for the CTS-R.
These findings provide initial support for the reliability and validity of the CTCP for assessing therapist competence in CBT for panic disorder and support the use of anxiety disorder-specific competence measures. Further investigation into the psychometric properties of the measure in other therapist cohorts and its relationship with clinical outcomes is recommended.
This article argues certainty in trusts is better understood by recognising a fourth certainty: “distributional certainty”. Distributional certainty is required in private trusts that involve dividing the property between beneficiaries: their shares must be clear. Distributional uncertainty is not, as usually understood, merely an instance of uncertainty of property: it has differing consequences, special resolution techniques, and may explain “administrative unworkability” in discretionary trusts. Distributional certainty is not required in charitable trusts. But this is not, as usually understood, merely an instance of the rule that charitable trusts do not need certainty of objects: it is an independent proposition.
Remote delivery of evidence-based psychological therapies via video conference has become particularly relevant following the COVID-19 pandemic, and is likely to be an on-going method of treatment delivery post-COVID. Remotely delivered therapy could be of particular benefit for people with social anxiety disorder (SAD), who tend to avoid or delay seeking face-to-face therapy, often due to anxiety about travelling to appointments and meeting mental health professionals in person. Individual cognitive therapy for SAD (CT-SAD), based on the Clark and Wells (1995) model, is a highly effective treatment that is recommended as a first-line intervention in NICE guidance (NICE, 2013). All of the key features of face-to-face CT-SAD (including video feedback, attention training, behavioural experiments and memory-focused techniques) can be adapted for remote delivery. In this paper, we provide guidance for clinicians on how to deliver CT-SAD remotely, and suggest novel ways for therapists and patients to overcome the challenges of carrying out a range of behavioural experiments during remote treatment delivery.
Key learning aims
(1) To learn how to deliver all of the core interventions of CT-SAD remotely.
(2) To learn novel ways of carrying out behavioural experiments remotely when some in-person social situations might not be possible.
Around a quarter of patients treated in intensive care units (ICUs) will develop symptoms of post-traumatic stress disorder (PTSD). Given the dramatic increase in ICU admissions during the COVID-19 pandemic, clinicians are likely to see a rise in post-ICU PTSD cases in the coming months. Post-ICU PTSD can present various challenges to clinicians, and no clinical guidelines have been published for delivering trauma-focused cognitive behavioural therapy with this population. In this article, we describe how to use cognitive therapy for PTSD (CT-PTSD), a first line treatment for PTSD recommended by the National Institute for Health and Care Excellence. Using clinical case examples, we outline the key techniques involved in CT-PTSD, and describe their application to treating patients with PTSD following ICU.
Key learning aims
(1) To recognise PTSD following admissions to intensive care units (ICUs).
(2) To understand how the ICU experience can lead to PTSD development.
(3) To understand how Ehlers and Clark’s (2000) cognitive model of PTSD can be applied to post-ICU PTSD.
(4) To be able to apply cognitive therapy for PTSD to patients with post-ICU PTSD.
The years between 1258 and 67 comprise one of the most influential periods in the Middle Ages in England. This turbulent decade witnessed a bitter power struggle between King Henry III and his baronsover who should control the government of the realm. Before England eventually descended into civil war, a significant proportion of the baronage had attempted to transform its governance by imposingon the crown a programme of legislative and administrative reform far more radical and wide-ranging than Magna Carta in 1215. Constituting a critical stage in the development of parliament, the reformist movement would remain unsurpassed in its radicalism until the upheavals of the seventeenth century. Simon de Montfort, the baronial champion, became the first leader of a political movement to seize power and govern in the king's name. The essays collected here offer the most recent research into and ideas on this pivotal period. Several contributions focus upon the roles played in the political struggle by particular sections of thirteenth-century society, including the Midland knights and their political allegiances, aristocratic women, and the merchant elite in London. The events themselves constitute the second major theme of this volume, with subjects such as the secret revolution of 1258, Henry III's recovery of power in 1261, and the little studied maritime theatre during the civil wars of 1263-7 being considered.
Adrian Jobson is an Associate Lecturer at Canterbury Christ Church University.
Contributors: Sophie Ambler, Nick Barratt, David Carpenter, Peter Coss, Mario Fernandes, Andrew H. Hershey, Adrian Jobson, Lars Kjaer, John A. McEwan, Tony Moore, Fergus Oakes, H.W. Ridgeway, Christopher David Tilley, Benjamin L. Wild, Louise J. Wilkinson.
The unprecedented Ebola Virus Disease (EVD) outbreak in West Africa, with its first cases documented in March 2014, has claimed the lives of thousands of people, and it has devastated the health care infrastructure and workforce in affected countries. Throughout this outbreak, there has been a critical lack of health care workers (HCW), including physicians, nurses, and other essential non-clinical staff, who have been needed, in most of the affected countries, to support the medical response to EVD, to attend to the health care needs of the population overall, and to be trained effectively in infection protection and control. This lack of sufficient and qualified HCW is due in large part to three factors: 1) limited HCW staff prior to the outbreak, 2) disproportionate illness and death among HCWs caused by EVD directly, and 3) valid concerns about personal safety among international HCWs who are considering responding to the affected areas. These guidelines are meant to inform institutions who deploy professional HCWs. (Disaster Med Public Health Preparedness. 2015;9:586–590)
A number of studies have demonstrated that consuming almonds increases satiety but does not result in weight gain, despite their high energy and lipid content. To understand the mechanism of almond digestion, in the present study, we investigated the bioaccessibility of lipids from masticated almonds during in vitro simulated human digestion, and determined the associated changes in cell-wall composition and cellular microstructure. The influence of processing on lipid release was assessed by using natural raw almonds (NA) and roasted almonds (RA). Masticated samples from four healthy adults (two females, two males) were exposed to a dynamic gastric model of digestion followed by simulated duodenal digestion. Between 7·8 and 11·1 % of the total lipid was released as a result of mastication, with no significant differences between the NA and RA samples. Significant digestion occurred during the in vitro gastric phase (16·4 and 15·9 %) and the in vitro duodenal phase (32·2 and 32·7 %) for the NA and RA samples, respectively. Roasting produced a smaller average particle size distribution post-mastication; however, this was not significant in terms of lipid release. Light microscopy showed major changes that occurred in the distribution of lipid in all cells after the roasting process. Further changes were observed in the surface cells of almond fragments and in fractured cells after exposure to the duodenal environment. Almond cell walls prevented lipid release from intact cells, providing a mechanism for incomplete nutrient absorption in the gut. The composition of almond cell walls was not affected by processing or simulated digestion.
Background: Randomized controlled trials have established that individual cognitive therapy based on the Clark and Wells (1995) model is an effective treatment for social anxiety disorder that is superior to a range of alternative psychological and pharmacological interventions. Normally the treatment involves up to 14 weekly face-to-face therapy sessions. Aim: To develop an internet based version of the treatment that requires less therapist time. Method: An internet-delivered version of cognitive therapy (iCT) for social anxiety disorder is described. The internet-version implements all key features of the face-to-face treatment; including video feedback, attention training, behavioural experiments, and memory focused techniques. Therapist support is via a built-in secure messaging system and by brief telephone calls. A cohort of 11 patients meeting DSM-IV criteria for social anxiety disorder worked through the programme and were assessed at pretreatment and posttreatment. Results: No patients dropped out. Improvements in social anxiety and related process variables were within the range of those observed in randomized controlled trials of face-to-face CT. Nine patients (82%) were classified as treatment responders and seven (64%) achieved remission status. Therapist time per patient was only 20% of that in face-to-face CT. Conclusions: iCT shows promise as a way of reducing therapist time without compromising efficacy. Further evaluation of iCT is ongoing.