Are acceptance and mindfulness‐based interventions ‘value for money’? Evidence from a systematic literature review

Objectives Acceptance and mindfulness‐based interventions (A/MBIs) are recommended for people with mental health conditions. Although there is a growing evidence base supporting the effectiveness of different A/MBIs for mental health conditions, the economic case for these interventions has not been fully explored. The aim of this systematic review was to identify and appraise all available economic evidence of A/MBIs for the management of mental health conditions. Methods Eight electronic bibliographic databases (MEDLINE, MEDLINE In‐Process & Other Non‐Indexed Citations, EMBASE, Web of Science, NHS Economic Evaluation Database (EED), Database of Abstracts of Reviews of Effects (DARE), Health Technology Assessment (HTA) database, and EconLit) were searched for relevant economic evaluations published from each database's inception date until November 2017. Study selection, quality assessment, and data extraction were carried out according to published guidelines. Results Ten relevant economic evaluations presented in 11 papers were identified. Seven of the included studies were full economic evaluations (i.e., costs and effects assessed), and three studies were partial economic evaluations (i.e., only costs were considered in the analysis). The A/MBIs that had been subjected to economic evaluation were acceptance and commitment therapy (ACT), dialectical behaviour therapy (DBT), mindfulness‐based cognitive therapy (MBCT), and mindfulness‐based stress reduction (MBSR). In terms of clinical presentations, the evaluation of cost‐effectiveness of A/MBIs has been more focused on depression and emotional unstable personality disorder with three and four economic evaluations, respectively. Three out of seven full economic evaluations observed that A/MBIs were cost‐effective for the management of mental health conditions. Nevertheless, the heterogeneity of included populations, interventions, and economic evaluation study types limits the extent to which firm conclusions can currently be made. Conclusion This first substantive review of economic evaluations of A/MBIs indicates that more research is needed before firm conclusions can be reached on the cost‐effectiveness of A/MBIs for mental health conditions. Practitioner points The findings of the review provide information that may be relevant to mental health service commissioners and decision‐makers as all economic evidence available on acceptance and mindfulness‐based interventions for mental health conditions is summarized. Evidence relating to the cost‐effectiveness and cost‐saving potential of acceptance and mindfulness‐based interventions is focused mainly on depression and emotional unstable personality disorder to date. Heterogeneity in the specific forms of acceptance and mindfulness‐based interventions may limit generalizability of the findings. The number of health economic evaluations relating to acceptance and mindfulness‐based interventions remains relatively small. Further research in this area is required

Deep learning resolves representative movement patterns in a marine predator species

The analysis of animal movement from telemetry data provides insights into how and why animals move. While traditional approaches to such analysis mostly focus on predicting animal states during movement, we describe an approach that allows us to identify representative movement patterns of different animal groups. To do this, we propose a carefully designed recurrent neural network and combine it with telemetry data for automatic feature extraction and identification of non-predefined representative patterns. In the experiment, we consider a particular marine predator species, the southern elephant seal, as an example. With our approach, we identify that the male seals in our data set share similar movement patterns when they are close to land. We identify this pattern recurring in a number of distant locations, consistent with alternative approaches from previous research

National Assessment of Human Health Effects of Climate Change in Portugal: Approach and Key Findings

In this study we investigated the potential impact of climate change in Portugal on heat-related mortality, air pollution–related health effects, and selected vectorborne diseases. The assessment used climate scenarios from two regional climate models for a range of future time periods. The annual heat-related death rates in Lisbon may increase from between 5.4 and 6 per 100,000 in 1980–1998 to between 8.5 and 12.1 by the 2020s and to a maximum of 29.5 by the 2050s, if no adaptations occur. The projected warmer and more variable weather may result in better dispersion of nitrogen dioxide levels in winter, whereas the higher temperatures may reduce air quality during the warmer months by increasing tropospheric ozone levels. We estimated the future risk of zoonoses using ecologic scenarios to describe future changes in vectors and parasites. Malaria and schistosomiasis, which are currently not endemic in Portugal, are more sensitive to the introduction of infected vectors than to temperature changes. Higher temperatures may increase the transmission risk of zoonoses that are currently endemic to Portugal, such as leishmaniasis, Lyme disease, and Mediterranean spotted fever

Multicenter study of the natural history and therapeutic responses of patients with chikungunya, focusing on acute and chronic musculoskeletal manifestations - a study protocol from the clinical and applied research in Chikungunya (REPLICK network)

BACKGROUND: Chikungunya is associated with high morbidity and the natural history of symptomatic infection has been divided into three phases (acute, post-acute, and chronic) according to the duration of musculoskeletal symptoms. Although this classification has been designed to help guide therapeutic decisions, it does not encompass the complexity of the clinical expression of the disease and does not assist in the evaluation of the prognosis of severity nor chronic disease. Thus, the current challenge is to identify and diagnose musculoskeletal disorders and to provide the optimal treatment in order to prevent perpetuation or progression to a potentially destructive disease course. METHODS: The study is the first product of the Clinical and Applied Research Network in Chikungunya (REPLICK). This is a prospective, outpatient department-based, multicenter cohort study in Brazil. Four work packages were defined: i. Clinical research; ii) Translational Science - comprising immunology and virology streams; iii) Epidemiology and Economics; iv) Therapeutic Response and clinical trials design. Scheduled appointments on days 21 (D21) ± 7 after enrollment, D90 ± 15, D120 ± 30, D180 ± 30; D360 ± 30; D720 ± 60, and D1080 ± 60 days. On these visits a panel of blood tests are collected in addition to the clinical report forms to obtain data on socio-demographic, medical history, physical examination and questionnaires devoted to the evaluation of musculoskeletal manifestations and overall health are performed. Participants are asked to consent for their specimens to be maintained in a biobank. Aliquots of blood, serum, saliva, PAXgene, and when clinically indicated to be examined, synovial fluid, are stored at -80° C. The study protocol was submitted and approved to the National IRB and local IRB at each study site. DISCUSSION: Standardized and harmonized patient cohorts are needed to provide better estimates of chronic arthralgia development, the clinical spectra of acute and chronic disease and investigation of associated risk factors. This study is the largest evaluation of the long-term sequelae of individuals infected with CHIKV in the Brazilian population focusing on musculoskeletal manifestations, mental health, quality of life, and chronic pain. This information will both define disease burden and costs associated with CHIKV infection, and better inform therapeutic guidelines

Using a logical model to predict the growth of yeast

<p>Abstract</p> <p>Background</p> <p>A logical model of the known metabolic processes in <it>S. cerevisiae </it>was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement.</p> <p>Results</p> <p>Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings.</p> <p>Conclusion</p> <p>ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750.</p