CBT for difficult-to-treat depression: self-regulation model

BACKGROUND: Cognitive behavioural therapy (CBT) is an effective treatment for depression but a significant minority of clients do not complete therapy, do not respond to it, or subsequently relapse. Non-responders, and those at risk of relapse, are more likely to have adverse childhood experiences, early-onset depression, co-morbidities, interpersonal problems and heightened risk. This is a heterogeneous group of clients who are currently difficult to treat. AIM: The aim was to develop a CBT model of depression that will be effective for difficult-to-treat clients who have not responded to standard CBT. METHOD: The method was to unify theory, evidence and clinical strategies within the field of CBT to develop an integrated CBT model. Single case methods were used to develop the treatment components. RESULTS: A self-regulation model of depression has been developed. It proposes that depression is maintained by repeated interactions of self-identity disruption, impaired motivation, disengagement, rumination, intrusive memories and passive life goals. Depression is more difficult to treat when these processes become interlocked. Treatment based on the model builds self-regulation skills and restructures self-identity, rather than target negative beliefs. A bespoke therapy plan is formed out of ten treatment components, based on an individual case formulation. CONCLUSIONS: A self-regulation model of depression is proposed that integrates theory, evidence and practice within the field of CBT. It has been developed with difficult-to-treat cases as its primary purpose. A case example is described in a concurrent article (Barton et al., 2022) and further empirical tests are on-going

A comparison of smartphone and paper data collection tools in the Burden of Obstructive Lung Disease (BOLD) study in Gezira state, Sudan

Introduction: Data collection using paper-based questionnaires can be time consuming and return errors affect data accuracy, completeness, and information quality in health surveys. We compared smartphone and paper-based data collection systems in the Burden of Obstructive Lung Disease (BOLD) study in rural Sudan. Methods: This exploratory pilot study was designed to run in parallel with the cross-sectional household survey. The Open Data Kit was used to programme questionnaires in Arabic into smartphones. We included 100 study participants (83% women; median age = 41.5 ± 16.4 years) from the BOLD study from 3 rural villages in East-Gezira and Kamleen localities of Gezira state, Sudan. Questionnaire data were collected using smartphone and paper-based technologies simultaneously. We used Kappa statistics and inter-rater class coefficient to test agreement between the two methods. Results: Symptoms reported included cough (24%), phlegm (15%), wheezing (17%), and shortness of breath (18%). One in five were or had been cigarette smokers. The two data collection methods varied between perfect to slight agreement across the 204 variables evaluated (Kappa varied between 1.00 and 0.02 and inter-rater coefficient between 1.00 and -0.12). Errors were most commonly seen with paper questionnaires (83% of errors seen) vs smartphones (17% of errors seen) administered questionnaires with questions with complex skip-patterns being a major source of errors in paper questionnaires. Automated checks and validations in smartphone-administered questionnaires avoided skip-pattern related errors. Incomplete and inconsistent records were more likely seen on paper questionnaires. Conclusion: Compared to paper-based data collection, smartphone technology worked well for data collection in the study, which was conducted in a challenging rural environment in Sudan. This approach provided timely, quality data with fewer errors and inconsistencies compared to paper-based data collection. We recommend this method for future BOLD studies and other population-based studies in similar settings

Evidence Base of Clinical Studies on Qi Gong: A Bibliometric Analysis

© 2020 The Authors Objective: This bibliometric study aimed to systematically and comprehensively summarize the volume, breadth and evidence for clinical research on Qigong. And this bibliometric analysis also can provide the evidence of this field. Design: Bibliometric analysis. Methods: All types of primary and secondary studies on humans were included: systematic reviews, randomized clinical trials, non-randomized controlled clinical studies, case series and case reports. Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Chinese Scientific Journal Database, Chinese Academic Conference Papers Database and Chinese Dissertation Database, PubMed and the Cochrane Library were searched from the date of inception to December 10, 2018. Bibliometric information, such as publication information, disease/condition, Qigong intervention and research results were extracted and analyzed. Results: A total of 886 clinical studies were identified: including 47 systematic reviews, 705 randomized clinical trials, 116 non-randomized controlled clinical studies, 12 case series and 6 case reports. The studies were conducted in 14 countries. The top 15 diseases/conditions studied were: diabetes, chronic obstructive pulmonary disease, hypertension, stroke, cervical spondylosis, lumbar disc herniation, insomnia, knee osteoarthritis, low back pain, and osteoporosis, Coronary heart disease, breast cancer, periarthritis of shoulder, depression, metabolic syndrome. Of the various Qigong exercises reported in these 886 clinical studies, Ba Duan Jin was the most frequently researched in 492 (55.5%) studies, followed by Health Qigong 107 (12.1%), Dao Yin Shu 85 (9.6%), Wu Qin Xi 67 (7.6%) and Yi Jin Jing 66 (7.4%). The most frequently used comparisons in randomized trials were maintaining normal way of life unchanged 149 (18.1%), the remaining controls included conventional treatment, mainly western medicine, Chinese herbal medicine, acupuncture, health education, psychological therapy, Yoga, Tai Chi and other non-drug therapy. The most frequently reported outcomes were physical function, quality of life, symptoms, pain and mental health indicators. Beneficial results from practicing Qigong were reported in 97% of studies. Conclusions: Qigong research publications have been increasing gradually. Reports on study types, participants, Qigong Intervention, and outcomes are diverse and inconsistent. There is an urgent need to develop a set of reporting standards for various interventions of Qigong. Further trials of high methodological quality with sufficient sample size and real world studies are needed to verify the effects of Qigong in health and disease management

Tryptophan depletion disinhibits punishment but not reward prediction: implications for resilience

Item does not contain fulltextRATIONALE: We have previously shown that tryptophan depletion enhances punishment but not reward prediction (Cools et al. in Neuropsychopharmacology 33:2291-2299, 2008b). This provided evidence for a valence-specific role of serotonin (which declines under depleted tryptophan) in aversive processing. Recent theoretical (Dayan and Huys in PLoS Comput Biol 4:e4, 2008) and experimental (Crockett et al. in J Neurosci 29:11993-11999, 2009) approaches have, however, further specified this role by showing that serotonin is critical for punishment-induced inhibition. OBJECTIVES: We sought to examine the role of serotonin in punishment-induced inhibition. We also examined the impact of induced mood on this effect to assess whether effects of tryptophan depletion on affective inhibition are moderated by mood. METHODS: Healthy females consumed a balanced amino acid mixture with (N = 20) or without (N = 21) the serotonin precursor tryptophan. Each subject completed either negative or neutral mood induction. All subjects completed the reward and punishment reversal learning task adopted in the previous study. RESULTS: We demonstrate a punishment prediction impairment in individuals who consumed tryptophan which was absent in individuals who were depleted of tryptophan. This effect was impervious to mood state. CONCLUSIONS: Our results suggest that serotonin promotes the inhibition of responses to punishing outcomes. This may lead to reduced punishment prediction accuracy in the presence of tryptophan and may contribute to resilience to affective disorders. Reduction of serotonin via tryptophan depletion then removes this inhibition. As such, we highlight a mechanism by which reduced serotonin can contribute to disorders of impulsivity and compulsivity as well as disorders of emotion.1 januari 201

Neutralizing and non-neutralizing monoclonal antibodies against dengue virus E protein derived from a naturally infected patient

<p>Abstract</p> <p>Background</p> <p>Antibodies produced in response to infection with any of the four serotypes of dengue virus generally provide homotypic immunity. However, prior infection or circulating maternal antibodies can also mediate a non-protective antibody response that can enhance the course of disease in a subsequent heterotypic infection. Naturally occurring human monoclonal antibodies can help us understand the protective and pathogenic roles of the humoral immune system in dengue virus infection.</p> <p>Results</p> <p>Epstein-Barr Virus (EBV) transformation of B cells isolated from the peripheral blood of a human subject with previous dengue infection was performed. B cell cultures were screened by ELISA for antibodies to dengue (DENV) envelope (E) protein. ELISA positive cultures were cloned by limiting dilution. Three IgG1 human monoclonal antibodies (HMAbs) were purified and their binding specificity to E protein was verified by ELISA and biolayer interferometry. Neutralization and enhancement assays were conducted in epithelial and macrophage-like cell lines, respectively. All three HMAbs bound to E from at least two of the four DENV serotypes, one of the HMAbs was neutralizing, and all were able to enhance DENV infection.</p> <p>Conclusions</p> <p>HMAbs against DENV can be successfully generated by EBV transformation of B cells from patients at least two years after naturally acquired DENV infections. These antibodies show different patterns of cross-reactivity, neutralizing, and enhancement activity.</p

Practical mammography

‘Digital health’ is an overarching concept that currently lacks theoretical definition and common terminology. For instance, this broad and emerging field includes all of the following terms within its lexicon: mHealth, Wireless Health, Health 2.0, eHealth, e-Patient(s), Healthcare IT/Health IT, Big Data, Health Data, Cloud Computing, Quantified Self, Wearable Computing, Gamification, and Telehealth/Telemedicine [1]. However, whilst a definition is difficult to provide, in this overview it is considered that digital health is the use of digital media to transform the way healthcare provision is conceived and delivered. We consider it does this through three basic features

Role of the mesoamygdaloid dopamine projection in emotional learning

Amygdala dopamine is crucially involved in the acquisition of Pavlovian associations, as measured via conditioned approach to the location of the unconditioned stimulus (US). However, learning begins before skeletomotor output, so this study assessed whether amygdala dopamine is also involved in earlier 'emotional' learning. A variant of the conditioned reinforcement (CR) procedure was validated where training was restricted to curtail the development of selective conditioned approach to the US location, and effects of amygdala dopamine manipulations before training or later CR testing assessed. Experiment 1a presented a light paired (CS+ group) or unpaired (CS- group) with a US. There were 1, 2 or 10 sessions, 4 trials per session. Then, the US was removed, and two novel levers presented. One lever (CR+) presented the light, and lever pressing was recorded. Experiment 1b also included a tone stimulus. Experiment 2 applied intra-amygdala R(+) 7-OH-DPAT (10 nmol/1.0 A mu l/side) before two training sessions (Experiment 2a) or a CR session (Experiment 2b). For Experiments 1a and 1b, the CS+ group preferred the CR+ lever across all sessions. Conditioned alcove approach during 1 or 2 training sessions or associated CR tests was low and nonspecific. In Experiment 2a, R(+) 7-OH-DPAT before training greatly diminished lever pressing during a subsequent CR test, preferentially on the CR+ lever. For Experiment 2b, R(+) 7-OH-DPAT infusions before the CR test also reduced lever pressing. Manipulations of amygdala dopamine impact the earliest stage of learning in which emotional reactions may be most prevalent

Collective intelligence for promoting changes in behaviour: a case study on energy conservation

Climate change is one of the biggest challenges humanity faces today. Despite of high investments in technology, battling climate change is futile without the participation of the public, and changing their perception and habits. Collective intelligence tools can play an important role in translating this “distant” concept that is climate change into practical hints for everyday life. In this paper, we report a case study grounded on collective intelligence tools to collaboratively build knowledge around energy conservation. A preliminary study to raise energy awareness in an academic environment is summarised, setting the scene to a more ambitious initiative based on personal stories to transform energy awareness into behaviour change. The role of the collective intelligence tools and other technical artefacts involved are discussed, suggesting strategies and features that contributed (or not) to users’ engagement and collective awareness. Lessons learned from both studies are reported with a sociotechnical approach as implications for design pursuing behaviour change

MGMR: leveraging RNA-Seq population data to optimize expression estimation

<p>Abstract</p> <p>Background</p> <p>RNA-Seq is a technique that uses Next Generation Sequencing to identify transcripts and estimate transcription levels. When applying this technique for quantification, one must contend with reads that align to multiple positions in the genome (multireads). Previous efforts to resolve multireads have shown that RNA-Seq expression estimation can be improved using probabilistic allocation of reads to genes. These methods use a probabilistic generative model for data generation and resolve ambiguity using likelihood-based approaches. In many instances, RNA-seq experiments are performed in the context of a population. The generative models of current methods do not take into account such population information, and it is an open question whether this information can improve quantification of the individual samples</p> <p>Results</p> <p>In order to explore the contribution of population level information in RNA-seq quantification, we apply a hierarchical probabilistic generative model, which assumes that expression levels of different individuals are sampled from a Dirichlet distribution with parameters specific to the population, and reads are sampled from the distribution of expression levels. We introduce an optimization procedure for the estimation of the model parameters, and use HapMap data and simulated data to demonstrate that the model yields a significant improvement in the accuracy of expression levels of paralogous genes.</p> <p>Conclusions</p> <p>We provide a proof of principal of the benefit of drawing on population commonalities to estimate expression. The results of our experiments demonstrate this approach can be beneficial, primarily for estimation at the gene level.</p

Food insecurity in adults with severe mental illness living in Northern England: A co-produced cross-sectional study

\ua9 2024 The Authors. Nutrition &amp; Dietetics published by John Wiley &amp; Sons Australia, Ltd on behalf of Dietitians Australia.Aim: This study aimed to explore food insecurity prevalence and experiences of adults with severe mental illness living in Northern England. Methods: This mixed-methods cross-sectional study took place between March and October 2022. Participants were adults with self-reported severe mental illness living in Northern England. The survey included demographic, health, and financial questions. Food insecurity was measured using the US Department of Agriculture Adult Food Security measure. Quantitative data were analysed using descriptive statistics and binary logistic regression; and qualitative data using content analysis. Results: In total, 135 participants completed the survey, with a mean age of 44.7 years (SD: 14.1, range: 18–75 years). Participants were predominantly male (53.3%), white (88%) and from Yorkshire (50.4%). The food insecurity prevalence was 50.4% (n = 68). There was statistical significance in food insecurity status by region (p = 0.001); impacts of severe mental illness on activities of daily living (p = 0.02); and the Covid pandemic on food access (p &lt; 0.001). The North West had the highest prevalence of food insecurity (73.3%); followed by the Humber and North East regions (66.7%); and Yorkshire (33.8%). In multivariable binary logistic regression, severe mental illness\u27 impact on daily living was the only predictive variable for food insecurity (odds ratio = 4.618, 95% confidence interval: 1.071–19.924, p = 0.04). Conclusion: The prevalence of food insecurity in this study is higher than is reported in similar studies (41%). Mental health practitioners should routinely assess and monitor food insecurity in people living with severe mental illness. Further research should focus on food insecurity interventions in this population