Addressing Religion and Spirituality in Psychotherapy: Clients\u27 Perspectives

Twelve adult clients described the role of religion and spirituality in their lives and in therapy as a whole, as well as their specific experiences of discussing religious-spiritual topics in individual outpatient psychotherapy with nonreligiously affiliated therapists. Data were analyzed using Consensual Qualitative Research (CQR; Hill, Thompson, & Williams, 1997). Results indicated that clients were regularly involved in religious-spiritual activities, usually did not know the religious-spiritual orientation of their therapists, but often found them open to such discussions. Specific helpful discussions of religion-spirituality were often begun by clients in the 1st year of therapy, were related to clients\u27 presenting concerns, were facilitated by therapists\u27 openness, and yielded positive effects. Specific unhelpful discussions were raised equally by clients and therapists early in therapy, made clients feel judged, and evoked negative effects. Implications for practice and research are addressed

Creating Technology-enhanced Practice: A University-Home Care-Corporate Alliance

Insuring full benefit of consumer health informatics innovations requires integrating the technology into nursing practice, yet many valuable innovations are developed in research projects and never reach full integration. To avoid this outcome, a team of researchers partnered with a home care agency’s staff and patients and their corporate parent’s Information Systems and Research group to create a Technology-Enhanced Practice (TEP) designed to enhance care of home bound patients and their family care givers. The technology core of TEP, the HeartCare2 web site, was built in a collaborative process and deployed within the existing patient portal of the clinical partner. This paper describes the innovation and the experience of bringing it into full operation

Technology-Enhanced Practice for Patients with Chronic Cardiac Disease: Home Implementation and Evaluation

Objective: This 3-year field experiment engaged 60 nurses and 282 patients in the design and evaluation of an innovative home-care nursing model, referred to as technology-enhanced practice (TEP). Methods: Nurses using TEP augmented the usual care with a web-based resource (HeartCareII) that provided patients with self-management information, self-monitoring tools, and messaging services. Results: Patients exposed to TEP demonstrated better quality of life and self-management of chronic heart disease during the first 4 weeks, and were no more likely than patients in usual care to make unplanned visits to a clinician or hospital. Both groups demonstrated the same long-term symptom management and achievements in health status. Conclusion: This project provides new evidence that the purposeful creation of patient-tailored web resources within a hospital portal is possible; that nurses have difficulty with modifying their practice routines, even with a highly-tailored web resource; and that the benefits of this intervention are more discernable in the early postdischarge stages of care

Anthropology and STS: Generative interfaces, multiple locations

In this multi-authored essay, nine anthropologists working in different parts of the world take part in a conversation about the interfaces between anthropology and STS (science and technology studies). Through this conversation, multiple interfaces emerge that are heterogeneously composed according to the languages, places, and arguments from where they emerge. The authors explore these multiple interfaces as sites where encounters are also sites of difference—where complex groupings, practices, topics, and analytical grammars overlap, and also exceed each other, composing irregular links in a conversation that produces connections without producing closure

Overarching Priorities for Health and Care Research in the United Kingdom: A Coproduced Synthesis of James Lind Alliance ‘Top 10s’

Introduction: James Lind Alliance (JLA) Priority Setting Partnerships (PSPs) produce ‘Top 10’ lists of health and care research priorities through a structured, shared decision‐making process with patients or service users, carers and health or care professionals who identify questions that are most important to them. To date, over 150 PSPs in different areas of health and care have published research priorities. Some PSPs share similar priorities, which could be combined, promoted and addressed through collaborative research to increase value and reduce research waste. Aim: The aim of this study was to identify overarching themes common to JLA PSP priorities across different areas of health and care. Methods: Our analysis included ‘Top 10’ research priorities produced by UK‐based JLA PSPs between 2016 and 2020. The priorities were coded deductively by the Health Research Classification System (HRCS) health category and research activity. We then carried out online workshops with patients, service users and carers to generate new codes not already captured by this framework. Within each code, multistakeholder inductive thematic analysis was used to identify overarching themes, defined as encompassing priorities from three or more PSPs covering two or more health categories. We used codesign methods to produce an interactive tool for end users to navigate the overarching themes. Results: Five hundred and fifteen research priorities from 51 PSPs were included in our analysis. The priorities together encompassed 20 of 21 HRCS health categories, the most common being ‘generic health relevance’ (22%), ‘mental health’ (18%) and ‘musculoskeletal’ (14%). We identified 89 overarching themes and subthemes, which we organised into a hierarchy with seven top‐level themes: quality of life, caregivers and families, causes and prevention, screening and diagnosis, treatment and management, services and systems and social influences and impacts. Conclusion: There are many overarching themes common to research priorities across multiple areas of health and care. To facilitate new research and research funding, we have developed an interactive tool to help researchers, funders and patients or service users to explore these priority topics. This is freely available to download online. Patient or Public Contribution: Patients or service users and carers were involved throughout the study, including deciding the aims, designing the study, analysing priorities to identify themes, interpreting and reporting the findings

Exome sequencing and the management of neurometabolic disorders

BACKGROUND: Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. METHODS: To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. RESULTS: We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). CONCLUSIONS: Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.)

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Exome Sequencing and the Management of Neurometabolic Disorders

BACKGROUND: Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. METHODS: To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. RESULTS: We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). CONCLUSIONS: Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.)

To which world regions does the valence–dominance model of social perception apply?

Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution.C.L. was supported by the Vienna Science and Technology Fund (WWTF VRG13-007); L.M.D. was supported by ERC 647910 (KINSHIP); D.I.B. and N.I. received funding from CONICET, Argentina; L.K., F.K. and Á. Putz were supported by the European Social Fund (EFOP-3.6.1.-16-2016-00004; ‘Comprehensive Development for Implementing Smart Specialization Strategies at the University of Pécs’). K.U. and E. Vergauwe were supported by a grant from the Swiss National Science Foundation (PZ00P1_154911 to E. Vergauwe). T.G. is supported by the Social Sciences and Humanities Research Council of Canada (SSHRC). M.A.V. was supported by grants 2016-T1/SOC-1395 (Comunidad de Madrid) and PSI2017-85159-P (AEI/FEDER UE). K.B. was supported by a grant from the National Science Centre, Poland (number 2015/19/D/HS6/00641). J. Bonick and J.W.L. were supported by the Joep Lange Institute. G.B. was supported by the Slovak Research and Development Agency (APVV-17-0418). H.I.J. and E.S. were supported by a French National Research Agency ‘Investissements d’Avenir’ programme grant (ANR-15-IDEX-02). T.D.G. was supported by an Australian Government Research Training Program Scholarship. The Raipur Group is thankful to: (1) the University Grants Commission, New Delhi, India for the research grants received through its SAP-DRS (Phase-III) scheme sanctioned to the School of Studies in Life Science; and (2) the Center for Translational Chronobiology at the School of Studies in Life Science, PRSU, Raipur, India for providing logistical support. K. Ask was supported by a small grant from the Department of Psychology, University of Gothenburg. Y.Q. was supported by grants from the Beijing Natural Science Foundation (5184035) and CAS Key Laboratory of Behavioral Science, Institute of Psychology. N.A.C. was supported by the National Science Foundation Graduate Research Fellowship (R010138018). We acknowledge the following research assistants: J. Muriithi and J. Ngugi (United States International University Africa); E. Adamo, D. Cafaro, V. Ciambrone, F. Dolce and E. Tolomeo (Magna Græcia University of Catanzaro); E. De Stefano (University of Padova); S. A. Escobar Abadia (University of Lincoln); L. E. Grimstad (Norwegian School of Economics (NHH)); L. C. Zamora (Franklin and Marshall College); R. E. Liang and R. C. Lo (Universiti Tunku Abdul Rahman); A. Short and L. Allen (Massey University, New Zealand), A. Ateş, E. Güneş and S. Can Özdemir (Boğaziçi University); I. Pedersen and T. Roos (Åbo Akademi University); N. Paetz (Escuela de Comunicación Mónica Herrera); J. Green (University of Gothenburg); M. Krainz (University of Vienna, Austria); and B. Todorova (University of Vienna, Austria). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.https://www.nature.com/nathumbehav/am2023BiochemistryGeneticsMicrobiology and Plant Patholog