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The deadly coronavirus disease 2019 (COVID-19) has recently affected each corner of the world. Many governments of different countries have imposed strict measures in order to reduce the severity of the infection. In this present paper, we will study a mathematical model describing COVID-19 dynamics taking into account the government action and the individuals reaction. To this end, we will suggest a system of seven fractional deferential equations (FDEs) that describe the interaction between the classical susceptible, exposed, infectious, and removed (SEIR) individuals along with the government action and individual reaction involvement. Both human-to-human and zoonotic transmissions are considered in the model. The well-posedness of the FDEs model is established in terms of existence, positivity, and boundedness. The basic reproduction number (BRN) is found via the new generation matrix method. Different numerical simulations were carried out by taking into account real reported data from Wuhan, China. It was shown that the governmental action and the individuals' risk awareness reduce effectively the infection spread. Moreover, it was established that with the fractional derivative, the infection converges more quickly to its steady state.

This study adopts a resilience perspective to explain how companies managed to contribute innovative solutions to fight the COVID-19 crisis. We studied how five companies operating in different industries (three in automotive, one in printing, and one in rubber and plastic products manufacturing) managed to reorganize activities and employ their R&D and innovation capabilities to enhance their resilience. Simultaneously, they increased the health system’s capacity to cope with the outbreak. Through a qualitative inductive study, based on interviews with company managers, we found that the firms mobilized their resources and capabilities to expand their ability to adapt and cope with adversity at the organizational level. In addition, moved by the sensitivity to the extreme context and a perceived sense of urgency, the firms deployed the same endowments to strengthen the community’s response to a crisis. Our study shows that an organization can directly and positively foster the broader social system’s resilience. This study contributes to the innovation literature by identifying innovation capabilities as fundamental antecedents of resilience building for organizational response, paving the way for strengthening the link between resilience and innovation.

Background Adherence to ADHD medication is a complex phenomenon as the decision to adhere is influenced by a range of factors. To design tailored interventions to promote adherence, it is important to understand the factors that influence adherence in the context of its three phases: initiation, implementation and discontinuation. Objective The objective of this study was to explore the phase‐specific factors that influence adherence to medication in adults who have a diagnosis of ADHD. Methods Three focus groups (FGs) were conducted with twenty adults with ADHD in different metropolitan areas of Sydney, Australia. FGs were transcribed verbatim and thematically analysed. Results Participants’ decision to initiate medication (the initiation phase) was influenced by their perceived needs (desire to improve academic and social functioning) and concerns (fear of side‐effects) about medication following a similar process as defined by the Necessity‐Concerns Framework (NCF). The balance between benefits of medication (needs) and side‐effects (concerns) continued to determine participants’ daily medication‐taking (the implementation phase) and persistence (or discontinuation) with their medication. Forgetfulness and stigma were reported as concerns negatively impacting the implementation phase, while medication cost and dependence influenced the discontinuation phase of adherence. Conclusions Adults’ decision to initiate, continue or discontinue medication is influenced by a range of factors; some are unique to each phase while some are common across the phases. Participants balanced the needs for the medication against their concerns in determining whether to adhere to medication at each phase. It appears that the NCF has applicability when decision making about medication is explored at the three phases of adherence.

This paper explores the methodological aspects of a user‐led study investigating mental health service user experiences of targeted violence and abuse (often called 'hate crime'). 'Keeping Control' was a 16‐month qualitative study, undertaken in the context of adult safeguarding reforms in England. By collecting data on service user concepts and experiences, the research sought to address a gap in research and practice knowledge relating to targeted violence, abuse and hostility against people with mental health problems. In this paper, we discuss the significance of the design and methodology used for this study, with a particular focus on the interviews with service users. The research was both user‐led and carried out in collaboration with practitioners and academics, a form of research co‐production. Our aim is to inform researchers, practitioners and policymakers about the value of user leadership in co‐productive research with practitioners, particularly for a highly sensitive and potentially distressing topic.

The novel coronavirus has created one of the biggest social and economic challenges in recent decades. Since a critical issue in overcoming a large‐scale pandemic involves finding effective treatments for the disease, there is typically urgent pressure on the health‐care sector to develop innovations to combat the pandemic. Recently, scholars have argued that repurposing – that is, reusing an existing innovation in a different context – allows for such rapid innovation responses and can reduce costs, as the groundwork has already been laid. In this paper, we compare these benefits with the considerable disadvantages associated with innovation repurposing, including lowered barriers to entry, which can lead to declining average quality and duplicate work. Using data on 2,456 COVID‐19‐related clinical trials initiated between December 2019 and July 2020, we find that merely one‐third of the trials actually investigated drugs or vaccines, whereas the rest focused on diagnostics and crisis management issues. In the trials concerning drug testing, we find that drug repurposing is a predominant innovation strategy, but many trials tested the same (combination of) drugs. This indicates an inefficient use of resources and reductions in the average variety and novelty of clinical trials. Furthermore, the small percentage of biopharmaceutical firms involved in the search for COVID‐19 treatments raises the question of whether firms may have insufficient incentives to redirect innovation efforts to respond to the pandemic. Our paper contributes to crisis management research, the nascent debate on COVID‐19, and the emerging literature on innovation repurposing.

The preeminent target of present study is to reveal the speed characteristic of ongoing outbreak COVID-19 due to novel coronavirus. On January 2020, the novel coronavirus infection (COVID-19) detected in India, and the total statistic of cases continuously increased to 7 128 268 cases including 109 285 deceases to October 2020, where 860 601 cases are active in India. In this study, we use the Hermite wavelets basis in order to solve the COVID-19 model with time- arbitrary Caputo derivative. The discussed framework is based upon Hermite wavelets. The operational matrix incorporated with the collocation scheme is used in order to transform arbitrary-order problem into algebraic equations. The corrector scheme is also used for solving the COVID-19 model for distinct value of arbitrary order. Also, authors have investigated the various behaviors of the arbitrary-order COVID-19 system and procured developments are matched with exiting developments by various techniques. The various illustrations of susceptible, exposed, infected, and recovered individuals are given for its behaviors at the various value of fractional order. In addition, the proposed model has been also supported by some numerical simulations and wavelet-based results.

BackgroundHistorically, safety mental health research has tended to focus on risks of homicide, suicide and deaths. Although wider safety issues are now recognized in regards to mental health services, the safety of mental health transitions, a key research and policy priority according to World Health Organisation, has not been explored.ObjectiveThe purpose of this study was to investigate perceptions of safety in mental health transitions (hospital to community) amongst five stakeholder groups.Design and settingAn online, international cross‐sectional, open‐ended questionnaire.ParticipantsThere were five stakeholder participant groups: service users; families/carers; mental health‐care professionals; researchers; and end users of research.ResultsNinety‐three participants from 12 different countries responded. Three overarching themes emerged: ‘individual/clinical’, ‘systems/services’ and ‘human, behavioural and social’ elements of safe mental health transitions. Whilst there was a great focus on clinical elements from researchers and healthcare professionals, service users and carers considered safety in terms of human, behavioural and social elements of transitional safety (ie loneliness, emotional readiness for discharge) and systems/services (ie inter‐professional communication).DiscussionSafety in mental health‐care transitions is perceived differently by service users and families compared to healthcare professionals and researchers. Traditional safety indicators for care transitions such as suicide, self‐harm and risk of adverse drug events are raised as important. However, service users and families in particular have a much wider perception of transitions safety.ConclusionFuture quality and safety research and policy should consider including a service user voice and consider integration of psychosocial elements in discharge interventions.

Innovation systems have seen diverse actors attempting to tame the Covid‐19 crisis, under varying degrees of government direction. Largely neglected in scholarly and public attention, however, are ‘bottom‐up’ solutions arising from the periphery of innovation systems. Drawing on inductive case research on a fringe doctor who invented the idea of the drive‐through testing system, and two university student teams that developed coronavirus applications, this study examines how peripheral actors generate innovative, bottom‐up solutions at speed in a time of crisis. Our findings reveal that, in a crisis situation, bottom‐up solutions transpire on the basis of three innovation drivers: (a) peripheral status, expediting the commence of innovation activities; (b) interdisciplinary collaboration, enabling access to a greater spectrum of knowledge and perspectives; and (c) prior knowledge, prescribing the direction of solution generation. We also identify that system intermediaries support the innovation activities of peripheral actors, thereby helping bottom‐up solutions to become more customer facing. Such functions of intermediaries include demand articulation, technical assistance, and promulgation of generated solutions. Our findings offer theoretical implications for the literature on innovation in a time of crisis and practical implications for governments and organizations preparing themselves for the potential second wave of coronavirus emergencies, or even a completely new form of future crisis.

Background Individual patient data meta-analyses (IPD-MA) are regarded as the gold standard for systematic reviews, which also applies to systematic reviews of diagnostic test accuracy (DTA) studies. An increasing number of DTA systematic reviews with IPD-MA have been published in recent years, but there is much variation in how these IPD-MA were performed. A number of existing methods were found, but there is no consensus as to which methods are preferred as the standard methods for statistical analysis in DTA IPD-MA. Objectives To create a web-based tool which integrates recommended statistical analyses for DTA IPD-MA, and allows researchers to analyse the data and visualize the results with interactive plots. Methods A systematic methodological review was performed to identify statistical analyses and data visualization methods used in DTA IPD-MA. Methods were evaluated by the authors and recommended analyses were integrated into the IPDmada tool which is freely available online with the user interface developed with R Shiny package. Results IPDmada allows users to upload their own data, perform the meta-analysis with both continuous and dichotomized tests, and incorporate individual level covariate-adjusted analysis. All tables and figures can be exported as .csv or .pdf files. A hypothetical dataset was used to illustrate the application of IPDmada. Conclusions IPDmada will be very helpful to researchers doing DTA IPD-MA, since it not only facilitates the statistical analysis but also provides a standard framework. The introduction of IPDmada will harmonize the methods used in DTA IPD-MA and ensure the quality of such analyses. Highlights IPDmada is a newly developed web-based tool for performing statistical analysis of individual patient data meta-analysis of diagnostic accuracy and visualizing the results. The tool is freely available to all the researchers, and requiring no installation of statistical software/packages. The tool has an user-friendly interface, and allows meta-analysis on both dichotomized and continuous test results. Researchers can easily use this tool to investigate the threshold effect and covariate effect on the summary accuracy. The introduction and implementation of IPDmada will serve as a useful tool for DTA IPD-MA and increase the quality of such studies.

Background Patient and public involvement (PPI) is increasingly required in mental health services research. To empower patients to actively address depression, the GET.FEEDBACK.GP study evaluates a patient-targeted feedback intervention after depression screening using the Patient Health Questionnaire (PHQ-9). Objective To refine the patient-targeted feedback from a previous study within a participatory research team (PRT) by conducting workshops to investigate patients' needs and preferences for feedback. To evaluate the process and outcome of PPI. Design Patient and public involvement was carried out on the levels of collaboration and consultation. A PRT of patient partners and researchers planned and conducted three workshops with patients. Patients' needs were investigated using a focus group. Participants prioritized needs, discussed feedback drafts and evaluated two drafts using cognitive debriefings. Researchers of the PRT communicated the results at project level. PPI was evaluated using the Public and Patient Engagement Evaluation Tools (PPEET). Setting and participants A purposeful sampling of N = 12 patients with experiences of depression participated in at least one workshop. Results Relevant content-related needs about feedback (eg no distinction between severe and moderate symptoms), recommendations for action and patient-relevant information were considered. Needs for comprehensible, valuing, nonstigmatizing language and design elements (eg dimensional bar) were implemented. Workshops and PRT were positively evaluated. Discussion and conclusions Patient and public involvement influenced the content, wording and design of the feedback. Strengths include two levels of PPI, methodical diversity and purposeful sampling. Limitations include the lack of inclusion of patients who are unaware of their depression. The evaluated PPI concept can be useful for future studies.

Aim The aim of the study was to assess the influence of the number of hours of daily nursing care for NHPPD in medical departments on missed care and the correlation between NHPPD and in-hospital mortality. Background Patient mortality can be a consequence of missed care as it correlates with the nurse-patient ratio. One of the methods to measure missed care is the Nursing Hours per Patient Day rating. Methods The study sample included 44,809 patients including 971 deaths in 8 wards. The influence of nursing hours, nursing education, and the percentage of patients' classification on in-hospital mortality were evaluated with backward stepwise linear regression. Results One hour added to the average NHPPD in medical departments was related to a decrease in mortality rate by 6.8 per 1,000 patient days and a lower chance for the emergence of unplanned death by 36%. Conclusions The number of NHPPD and the percentage of professional nurses are factors influencing missed care and in-hospital mortality. Implications for nursing management The severe consequences of missed care, that is mortality, and the correlation between in-hospital mortality, nursing education and nursing-patient ratio, which are indicators of care quality, are arguments for maintaining adequate staffing levels to avoid missed care.

Latinos in the United States represent a disproportionate burden of illness and disease and face barriers to accessing health care and related resources. Culturally tailored, evidence‐based interventions hold promise in addressing many of these challenges. Yet, ensuring patient voice is vital in the successful development and implementation of such interventions. Thus, this paper examines the application of analytic hierarchy process (AHP) to inform the augmentation and implementation of an evidence‐based chronic disease self‐management programme for underserved Latinos living with both minor depression and chronic illness. The process of AHP allows for direct input from the individuals that would utilize such a programme, including afflicted individuals, their family members and the health educators/promotores that would be responsible for implementation. Specifically, 45 participants, including 15 individuals with chronic disease, 15 family members/caregivers and 15 promotores, partook in the Stakeholder Values Questionnaire, which elicited preferences and values regarding major goals, processes and content for the intervention. AHP was employed to analyse pairwise comparison ratings and to determine differences and similarities across stakeholder groups. This analytical technique allowed for the adaptation of the EBI to stakeholders' specific priorities and preferences and facilitated complex decision‐making. Findings not only shed light on similarities and differences between stakeholder groups, but also the magnitude of these priorities and preferences and allowed the intervention to be driven by the participants, themselves. Applying AHP was a unique opportunity to optimize the decision‐making process to inform cultural adaptation of an EBI while considering multiple viewpoints systematically.

Background A new diagnosis of complex post-traumatic stress disorder, CPTSD, has been agreed by the World Health Organization, WHO, and evidence is needed for what psychological treatment might be effective, particularly from those with experience of the disorder. We used a novel participatory approach to explore patient views and simultaneously studied the impact on the patient researchers of the research process itself. In this paper, we report on the latter section of the study how the involvement in research of patients with CPTSD affected their mental health. Symptoms of CPTSD may include emotional dysregulation, feelings of self-worthlessness and difficulties in relationships. Objective The aim of this study section was to explore whether patients' mental health could be promoted through empowering them to participate in research on CPTSD. Design The study had a qualitative, participatory design. The clinician who led the research (first author) held group meetings with patient researchers to explore the impact of the research process. The clinician also kept notes on the process in a reflective log. Setting and participants Six patient researchers participated in research with other patients with lived experience of CPTSD in an NHS outpatient unit in a London hospital. Intervention studied The research process itself was analysed in group meetings with researchers which the clinician recorded and transcribed. Findings Participation in research may promote increased self-confidence and social inclusion for those with CPTSD. Conclusion Involvement in research may be seen as an empowering intervention because patients felt it contributed to recovery.

Delineating the spatial extent and the altitudinal lower limit of mountain permafrost is difficult due to complex topo‐climatic and variable ground thermal conditions within short distances. Little information exists regarding sporadic permafrost existence, its thermal characteristics and its long‐term changes at the eastern margin of the European Alps. To reduce this gap, permafrost monitoring was initiated in 2004 in the Seckauer Tauern mountains, Austria. Research was carried out in the summit region of Mt Hochreichart (2416 m a.s.l.) and at several nearby cirques and valleys, all with rock glaciers. Geomorphic mapping, numerical permafrost modeling, measurements of the bottom temperature of the winter snow cover, continuous ground temperature monitoring, electrical resistivity tomography and optical snow cover monitoring were applied. Results indicate sporadic permafrost occurrence in the summit region with mean annual ground temperatures slightly below 0°C at the surface and −1.4°C at 2.5 m depth. Permafrost lenses also exist in the transition zone between the rock glacier and the talus slope behind attributed to coarse‐grained, blocky material causing additional ground cooling. Thanks to long‐term data, statistically significant trends of atmospheric and ground warming were observed in 2000–2018. Permafrost at this site will presumably disappear within the next few decades.

RATIONALE The wide chemical diversity and complex matrices inherent to metabolomics still pose a challenge to current analytical approaches for metabolite screening. Although dedicated front-end separation techniques combined with high-resolution mass spectrometry set the benchmark from an analytical point of view, the increasing number of samples and sample complexity demand for a compromise in terms of selectivity, sensitivity and high-throughput analyses. METHODS Prior to low-field drift tube ion mobility (IM) separation and quadrupole time-of-flight mass spectrometry (QTOFMS) detection, rapid ultrahigh-performance liquid chromatography separation was used for analysis of different concentration levels of dansylated metabolites present in a yeast cell extract. For identity confirmation of metabolites at the MS2 level, an alternating frame approach was chosen and two different strategies were tested: a data-independent all-ions acquisition and a quadrupole broad band isolation (Q-BBI) directed by IM drift separation. RESULTS For Q-BBI analysis, the broad mass range isolation was successfully optimized in accordance with the distinctive drift time to m/z correlation of the dansyl derivatives. To guarantee comprehensive sampling, a broad mass isolation window of 70 Da was employed. Fragmentation was performed via collision-induced dissociation, applying a collision energy ramp optimized for the dansyl derivatives. Both approaches were studied in terms of linear dynamic range and repeatability employing ethanolic extracts of Pichia pastoris spiked with 1 μM metabolite mixture. Example data obtained for histidine and glycine showed that drift time precision (

Fragmentation of processes and interventions plague the psychotherapies (Gilbert & Kirby, 2019). Part of the problem is that we have not agreed on a framework that could be the basis for integrating knowledge and the scientific enquiry of processes and interventions. This paper outlines an approach that brings together a variety of different disciplines in the service of consilience (Wilson, 1998, Consilience: The unity of knowledge, Vintage, New York, NY; Siegel, 2019). It presents the importance of an evolutionary framework for understanding the proclivities and dispositions for mental suffering and antisocial behaviour, and how they are choreographed in different sociodevelopmental contexts. Building on earlier models (Gilbert, 1989, Human nature and suffering, Routledge, London, UK; Gilbert, 1995, Clin. Psychol. Psychother., 2, 135; Gilbert, 1998, Br. J. Med. Psychol., 71, 353; Gilbert, 2016, Case formulation in cognitive behaviour therapy: The treatment of challenging cases, Wiley, Chichester, UK, pp. 50–89) the call is for an integrative, evolutionary, contextual, biopsychosocial approach to psychology and psychotherapy. Practitioner points Evolutionary functional analysis is part of an evolutionary, contextual, biopsychosocial approach to mental health that can serve as a scientific platform for the future developments of psychotherapy.Therapist skills and training will increasing need to focus on the multidimensional textures of mental states especially the context‐social‐body linkages.Therapies of the future will also focus more on the moral aspects of therapy and address the need to promote prosocial and ethical behaviour to self and others.

One of the key issues in the field of technology analysis and innovation management is how new technologies origin and evolve in the presence of environmental threats. We confront this problem focusing on emerging innovative solutions to cope with unexpected and harmful problems posed by crises and needing a rapid, effective response. We specifically analyze the patterns of critical innovations to cope with new coronavirus disease (COVID‐19) that is generating public health and economic issues worldwide. Accordingly, in the context of the theory of technological exaptation, we adopted a narrative approach examining vital innovations that ended up treating COVID‐19 even though they were originated to treat other diseases (more or less distant from the COVID‐19 domain), as the antiviral drug Remdesivir and the antirheumatoid arthritis drug Tocilizumab. Results reveal that technological exaptation, especially if characterized by a longer exaptive distance, is a potential driving force of innovation to cope with COVID‐19 in the short‐term and other similar issues. On this basis, we provide propositions for a more general crisis model of innovation. This study adds a new perspective that may be helpful to explain the evolution of innovation in the presence of crises, considering technological exaptation in a context of environmental threats.

Network meta-analysis (NMA) can be used to compare multiple competing treatments for the same disease. In practice, usually a range of outcomes is of interest. As the number of outcomes increases, summarizing results from multiple NMAs becomes a nontrivial task, especially for larger networks. Moreover, NMAs provide results in terms of relative effect measures that can be difficult to interpret and apply in every-day clinical practice, such as the odds ratios. In this article, we aim to facilitate the clinical decision-making process by proposing a new graphical tool, the Kilim plot, for presenting results from NMA on multiple outcomes. Our plot compactly summarizes results on all treatments and all outcomes; it provides information regarding the strength of the statistical evidence of treatment effects, while it illustrates absolute, rather than relative, effects of interventions. Moreover, it can be easily modified to include considerations regarding clinically important effects. To showcase our method, we use data from a network of studies in antidepressants. All analyses are performed in R and we provide the source code needed to produce the Kilim plot, as well as an interactive web application.

A common challenge for the development of drugs in rare diseases and special populations, eg, paediatrics, is the small numbers of patients that can be recruited into clinical trials. Extrapolation can be used to support development and licensing in paediatrics through the structured integration of available data in adults and prospectively generated data in paediatrics to derive conclusions that support licensing decisions in the target paediatric population. In this context, Bayesian analyses have been proposed to obtain formal proof of efficacy of a new drug or therapeutic principle by using additional information (data, opinion, or expectation), expressed through a prior distribution. However, little is said about the impact of the prior assumptions on the evaluation of outcome and prespecified strategies for decision-making as required in the regulatory context. On the basis of examples, we explore the use of data-based Bayesian meta-analytic-predictive methods and compare these approaches with common frequentist and Bayesian meta-analysis models. Noninformative efficacy prior distributions usually do not change the conclusions irrespective of the chosen analysis method. However, if heterogeneity is considered, conclusions are highly dependent on the heterogeneity prior. When using informative efficacy priors based on previous study data in combination with heterogeneity priors, these may completely determine conclusions irrespective of the data generated in the target population. Thus, it is important to understand the impact of the prior assumptions and ensure that prospective trial data in the target population have an appropriate chance, to change prior belief to avoid trivial and potentially erroneous conclusions.

Medical decisions for children are usually justified by the claim that they are in a child's best interests. More recently, following criticisms of the best interests standard, some advocate that the family's interests should influence medical decisions for children, although what is meant by family interests is often not made clear. I argue that at least two senses of family interests may be discerned. There is a ‘weak’ sense (as the amalgamated interests of family members) of family interests and a ‘strong’ sense (that the family itself has interests over and above the interests of individuals). I contend that there are problems with both approaches in making medical decisions for children but that the weak sense is more plausible. Despite this, I argue that claims for family interests are not helpful in making medical decisions for children.

Oxygen demand in river substrates providing important habitats for the early life stages of aquatic ecology, including lithophilous fish, can arise due to the oxidation of sediment‐associated organic matter. Oxygen depletion associated with this component of river biogeochemical cycling, will, in part, depend on the sources of such material. A reconnaissance survey was therefore undertaken to assess the relative contributions from bed sediment‐associated organic matter sources potentially impacting on the River Axe Special Area of Conservation (SAC), in SW England. Source fingerprinting, including Monte Carlo uncertainty analysis, suggested that the relative frequency‐weighted average median source contributions ranged between 19% (uncertainty range 0–82%) and 64% (uncertainty range 0–99%) for farmyard manures or slurries, 4% (uncertainty range 0–49%) and 35% (uncertainty range 0–100%) for damaged road verges, 2% (uncertainty range 0–100%) and 68% (uncertainty range 0–100%) for decaying instream vegetation, and 2% (full uncertainty range 0–15%) and 6% (uncertainty range 0–48%) for human septic waste. A reconnaissance survey of sediment oxygen demand (SOD) along the channel designated as a SAC yielded a mean SOD5 of 4 mg O2 g−1 dry sediment and a corresponding SOD20 of 7 mg O2 g−1 dry sediment, compared with respective ranges of 1–15 and 2–30 mg O2 g−1 dry sediment, measured by the authors for a range of river types across the UK. The findings of the reconnaissance survey were used in an agency (SW region) catchment appraisal exercise for informing targeted management to help protect the SAC.

In generalized linear modelling of responses and response times, the observed response time variables are commonly transformed to make their distribution approximately normal. A normal distribution for the transformed response times is desirable as it justifies the linearity and homoscedasticity assumptions in the underlying linear model. Past research has, however, shown that the transformed response times are not always normal. Models have been developed to accommodate this violation. In the present study, we propose a modelling approach for responses and response times to test and model non-normality in the transformed response times. Most importantly, we distinguish between non-normality due to heteroscedastic residual variances, and non-normality due to a skewed speed factor. In a simulation study, we establish parameter recovery and the power to separate both effects. In addition, we apply the model to a real data set.

Background: Patient and public involvement (PPI) is becoming more commonplace in mental health research. There are strong moral and ethical arguments for good quality PPI. Few studies have documented and evaluated PPI in self-harm and suicide research. Inconsistent reporting of PPI makes it difficult to discern practices that deliver quality, effective and meaningful involvement. It is important to understand and address emotional support needs of PPI members contributing to sensitive topics such as suicide and self-harm. Therefore, this study will examine the effect of PPI on self-harm and suicide research and explore patients', carers' and researchers' experiences and views in relation to the quality of PPI practice and provision of appropriate support for PPI members. Methods: This protocol outlines the longitudinal, mixed methodological approach that will be taken. Qualitative and quantitative data will be collected via baseline and repeated questionnaires, document review and semi-structured interviews. Both PPI members and researchers will be invited to participate in this study. The two-year data collection period will enable evaluation of PPI throughout the entire research cycle. An integrated approach will be taken to data analysis, using inductive thematic analysis and descriptive and repeated measures analyses, to address specified study aims. Dissemination: Findings from this study will inform practical guidance to support self-harm and suicide researchers in effectively involving people with experiential knowledge in their research. Analyses will offer insight into the effect of PPI throughout the research process and assess changes in PPI members' and researchers' experiences of involvement across a two-year period.

Despite the growing importance of ‘social value’ as a central feature of research ethics, the term remains both conceptually vague and to a certain extent operationally rigid. And yet, perhaps because the rhetorical appeal of social value appears immediate and self‐evident, the concept has not been put to rigorous investigation in terms of its definition, strength, function, and scope. In this article, we discuss how the anthropological concept of liminality can illuminate social value and differentiate and reconfigure its variegated approaches. Employing liminality as a heuristic encourages a reassessment of how we understand the mobilization of ‘social value’ in bioethics. We argue that social value as seen through the lens of liminality can provide greater clarity of its function and scope for health research. Building on calls to understand social value as a dynamic, rather than a static, concept, we emphasize the need to appraise social value iteratively throughout the entire research as something that transforms over multiple times and across multiple spaces occupied by a range of actors.

Funding support for this study is from Singapore Ministry of Education Academic Research Fund Tier 2 (MOE2015‐T2‐1‐008); Hong Kong Research Grants Council through its General Research Fund (Project 17606815); Wellcome Trust UK (GR079946/B/06/Z and GR079946/Z/06/Z). Global circuits of migration regularly separate parents from children. How families navigate this separation has changed markedly. The sharp decline in the cost of international communication makes possible new forms of transnational parenting. In many contexts, migrants are now actively engaged parents, involved in decisions, knowledgeable of children's schooling, employment, and activities, and in some cases, even conversant face‐to‐face with children via videoconferencing. These practices, however, are not universal. We use data from surveys in 3 countries to document the frequency and variability of intensive, engaged transnational parenting in the diverse global regions of Asia, Africa, and the Americas. We then ask whether the organisation of children's lives—specifically, time allocated to school homework, leisure, and household chores—varies by the degree to which migrant parents stay connected to sending homes. The gender of the migrant parent, stay‐behind caregiver, and the gender of the child emerge as explanatory factors for engaged parenting and children's time use. However, and unexpectedly, in the Philippines, migrant mothers are less likely to practice engaged parenting. In sending households, girls in two of the three countries spend more time doing household chores than boys, but parental migration does not mitigate this difference. Although we find some evidence of more traditional gender practices, we also find exceptions that suggest potentially fruitful avenues for future research. Publisher PDF

The analysis of adverse events plays an important role in the benefit assessment of drugs. Consequently, results on adverse events are an integral part of reimbursement dossiers submitted by pharmaceutical companies to health policy decision-makers. Methods applied in the analysis of adverse events commonly include simple standard methods for contingency tables. However, the results produced may be misleading if observations are censored at the time of discontinuation due to treatment switching or noncompliance, resulting in unequal follow-up periods. In this paper, we present examples to show that the application of inadequate methods for the analysis of adverse events in the reimbursement dossier can lead to a downgrading of the evidence on a drug's benefit in the subsequent assessment, as greater harm from the drug cannot be excluded with sufficient certainty. Legal regulations on the benefit assessment of drugs in Germany are presented, in particular, with regard to the analysis of adverse events. Differences in safety considerations between the drug approval process and the benefit assessment are discussed. We show that the naive application of simple proportions in reimbursement dossiers frequently leads to uninterpretable results if observations are censored and the average follow-up periods differ between treatment groups. Likewise, the application of incidence rates may be misleading in the case of recurrent events and unequal follow-up periods. To allow for an appropriate benefit assessment of drugs, adequate survival time methods accounting for time dependencies and duration of follow-up are required, not only for time-to-event efficacy endpoints but also for adverse events. © 2016 The Authors. Pharmaceutical Statistics published by John Wiley & Sons Ltd.

Summary For a continuous treatment, the generalised propensity score (GPS) is defined as the conditional density of the treatment, given covariates. GPS adjustment may be implemented by including it as a covariate in an outcome regression. Here, the unbiased estimation of the dose–response function assumes correct specification of both the GPS and the outcome‐treatment relationship. This paper introduces a machine learning method, the ‘Super Learner’, to address model selection in this context. In the two‐stage estimation approach proposed, the Super Learner selects a GPS and then a dose–response function conditional on the GPS, as the convex combination of candidate prediction algorithms. We compare this approach with parametric implementations of the GPS and to regression methods. We contrast the methods in the Risk Adjustment in Neurocritical care cohort study, in which we estimate the marginal effects of increasing transfer time from emergency departments to specialised neuroscience centres, for patients with acute traumatic brain injury. With parametric models for the outcome, we find that dose–response curves differ according to choice of specification. With the Super Learner approach to both regression and the GPS, we find that transfer time does not have a statistically significant marginal effect on the outcomes. © 2015 The Authors. Health Economics Published by John Wiley & Sons Ltd.

Do policies that shape equality in schools have effects on the type of society and polity that the citizens educated in them want? This paper examines this question by analyzing variation in the English schooling experiences using the British Cohort Study and British Panel Study. It shows that the social environment of schooling affects adults' attitudes to fairness and Conservative vote choice, but that policies targeting these social environments have weak effects. The paper theorizes that actual policy feedback in education is often limited, because the effects of policies on school experiences are mediated by the behaviors of other actors on the ground.促进学校平等的政策是否会影响处于其中的受教育公民对社会和政体形态的期望？为探讨这一问题，本文使用英国的面板数据和队列研究来检验英国学校教育的差异。本文表明，学校教育的社会环境会强烈影响学生成年后对公平的态度和对保守党的投票选择，但针对社会环境的政策所带来的这方面影响却效果微弱。本文认为，教育中的实际政策反馈往往是有限的，因为政策对学校经历的影响并非一个简单直接的过程。.

Clustered data are common in medical research. Typically, one is interested in a regression model for the association between an outcome and covariates. Two complications that can arise when analysing clustered data are informative cluster size (ICS) and confounding by cluster (CBC). ICS and CBC mean that the outcome of a member given its covariates is associated with, respectively, the number of members in the cluster and the covariate values of other members in the cluster. Standard generalised linear mixed models for cluster-specific inference and standard generalised estimating equations for population-average inference assume, in general, the absence of ICS and CBC. Modifications of these approaches have been proposed to account for CBC or ICS. This article is a review of these methods. We express their assumptions in a common format, thus providing greater clarity about the assumptions that methods proposed for handling CBC make about ICS and vice versa, and about when different methods can be used in practice. We report relative efficiencies of methods where available, describe how methods are related, identify a previously unreported equivalence between two key methods, and propose some simple additional methods. Unnecessarily using a method that allows for ICS/CBC has an efficiency cost when ICS and CBC are absent. We review tools for identifying ICS/CBC. A strategy for analysis when CBC and ICS are suspected is demonstrated by examining the association between socio-economic deprivation and preterm neonatal death in Scotland.

In this article, it is argued that grandparents' obligations originate from parental obligations (i.e from the relationship they have with their children, the parents of their grandchildren) and not from the role of grandparent per se, and any entitlements flow from the extent to which these obligations are met. The position defended is, therefore, that grandparents qua grandparents are not entitled to form or continue relationships with their grandchildren. A continuation of grandparent-grandchildren relationships may be in the interests of children, but the grandparental nature of the relationship is not decisive. What counts is the extent to which relationships children have with any adults who are not their parents are is significant to them. Sometimes, however, grandparents become parents or co-parents of their grandchildren. They then gain parental rights, and as such are as entitled, ceteris parius, as any parent to expect their relationship with the child to continue. The issue of grandparents' entitlements can come to the fore when parents separate, and grandparents are unhappy with the access they have to their grandchildren. Grandparents' obligations may become a particular issue when parents die, struggle, or fail to care for their children. This article focuses particularly on these kinds of circumstances.

All organisms have to safeguard the integrity of their genome to prevent malfunctioning and oncogenic transformation. Sophisticated DNA damage response mechanisms have evolved to detect and repair genomic lesions. With the emergence of live-cell microscopy of individual cells, we now begin to appreciate the complex spatiotemporal kinetics of the DNA damage response and can address the causes and consequences of the heterogeneity in the responses of genetically identical cells. Here, we highlight key discoveries where live-cell imaging has provided unprecedented insights into how cells respond to DNA double-strand breaks and discuss the main challenges and promises in using this technique.

Jürgen Habermas is regarded as a central bioconservative commentator in the debate on the ethics of human prenatal genetic manipulations. While his main work on this topic, The Future of Human Nature, has been widely examined in regard to his position on prenatal genetic enhancement, his arguments regarding prenatal genetic therapeutic interventions have for the most part been overlooked. In this work I do two things. First, I present the three necessary conditions that Habermas establishes for a prenatal genetic manipulation to be regarded as morally permissible. Second, I examine if mitochondrial replacement techniques meet these necessary conditions. I investigate, specifically, the moral permissibility of employing pronuclear transfer and maternal spindle transfer. I conclude that, according to a Habermasian perspective on prenatal genetic manipulation, maternal spindle transfer (without using a preselected sperm and egg) and pronuclear transfer are morally impermissible. Maternal spindle transfer is, in principle, morally permissible, but only when we have beforehand preselected a sperm and an egg for our reproductive purpose. These findings are relevant for bioconservatives, both for those who hold a Habermasian stance and for those who hold something akin to a Habermasian stance, because they answer the question: what should bioconservatives do regarding mitochondrial replacement techniques? In fact, the answer to this question does not only normatively prescribe what bioconservatives should do in terms of their personal morality, but it also points towards what kind of legislation regulating mitochondrial replacement techniques they should aim at.

Methods for individual participant data meta-analysis of survival outcomes commonly focus on the hazard ratio as a measure of treatment effect. Recently, Siannis et al. (2010, Statistics in Medicine 29:3030–3045) proposed the use of percentile ratios as an alternative to hazard ratios. We describe a novel two-stage method for the meta-analysis of percentile ratios that avoids distributional assumptions at the study level. Copyright © 2012 John Wiley & Sons, Ltd.

Occasionally, things go so wrong in a clinical trial that a change must be made. For example, the originally planned primary outcome may be measured completely unreliably. Is there any recourse? One may still be able to salvage the trial using a permutation test if a change is made before breaking the treatment blind. The solution is not a panacea; we discuss the limitations and legitimate grounds for criticism. Still, when it is needed, the procedure is preferable to rigid adherence to a design that makes no sense. Published 2012. This article is a US Government work and is in the public domain in the USA.

Network meta-analysis (multiple treatments meta-analysis, mixed treatment comparisons) attempts to make the best use of a set of studies comparing more than two treatments. However, it is important to assess whether a body of evidence is consistent or inconsistent. Previous work on models for network meta-analysis that allow for heterogeneity between studies has either been restricted to two-arm trials or followed a Bayesian framework. We propose two new frequentist ways to estimate consistency and inconsistency models by expressing them as multivariate random-effects meta-regressions, which can be implemented in some standard software packages. We illustrate the approach using the mvmeta package in Stata. Copyright © 2012 John Wiley & Sons, Ltd.

The explosion of biomedical data, both on the genomic and proteomic side as well as clinical data, will require complex integration and analysis to provide new molecular variables to better understand the molecular basis of phenotype. Currently, much data exist in silos and is not analyzed in frameworks where all data are brought to bear in the development of biomarkers and novel functional targets. This is beginning to change. Network biology approaches, which emphasize the interactions between genes, proteins and metabolites provide a framework for data integration such that genome, proteome, metabolome and other -omics data can be jointly analyzed to understand and predict disease phenotypes. In this review, recent advances in network biology approaches and results are identified. A common theme is the potential for network analysis to provide multiplexed and functionally connected biomarkers for analyzing the molecular basis of disease, thus changing our approaches to analyzing and modeling genome- and proteome-wide data.

Immune systems evolve as essential strategies to maintain homeostasis with the environment, prevent microbial assault and recycle damaged host tissues. The immune system is composed of two components, innate and adaptive immunity. The former is common to all animals while the latter consists of a vertebrate-specific system that relies on somatically derived lymphocytes and is associated with near limitless genetic diversity as well as long-term memory. Deuterostome invertebrates provide a view of immune repertoires in phyla that immediately predate the origins of vertebrates. Genomic studies in amphioxus, a cephalochordate, have revealed homologs of genes encoding most innate immune receptors found in vertebrates; however, many of the gene families have undergone dramatic expansions, greatly increasing the innate immune repertoire. In addition, domain-swapping accounts for the innovation of new predicted pathways of receptor function. In both amphioxus and Ciona, a urochordate, the VCBPs (variable region containing chitin-binding proteins), which consist of immunoglobulin V (variable) and chitin binding domains, mediate recognition through the V domains. The V domains of VCBPs in amphioxus exhibit high levels of allelic complexity that presumably relate to functional specificity. Various features of the amphioxus immune repertoire reflect novel selective pressures, which likely have resulted in innovative strategies. Functional genomic studies underscore the value of amphioxus as a model for studying innate immunity and may help reveal how unique relationships between innate immune receptors and both pathogens and symbionts factored in the evolution of adaptive immune systems.

This article reviews recent advances in ‘microbiome studies’: molecular, statistical and graphical techniques to explore and quantify how microbial organisms affect our environments and ourselves given recent increases in sequencing technology. Microbiome studies are moving beyond mere inventories of specific ecosystems to quantifications of community diversity and descriptions of their ecological function. We review the last 24 months of progress in this sort of research, and anticipate where the next 2 years will take us. We hope that bioinformaticians will find this a helpful springboard for new collaborations with microbiologists.

One of the main motivations to study amphioxus is its potential for understanding the last common ancestor of chordates, which notably gave rise to the vertebrates. An important feature in this respect is the slow evolutionary rate that seems to have characterized the cephalochordate lineage, making amphioxus an interesting proxy for the chordate ancestor, as well as a key lineage to include in comparative studies. Whereas slow evolution was first noticed at the phenotypic level, it has also been described at the genomic level. Here, we examine whether the amphioxus genome is indeed a good proxy for the genome of the chordate ancestor, with a focus on protein-coding genes. We investigate genome features, such as synteny, gene duplication and gene loss, and contrast the amphioxus genome with those of other deuterostomes that are used in comparative studies, such as Ciona, Oikopleura and urchin.

Many complex diseases such as cancer are associated with changes in biological pathways and molecular networks rather than being caused by single gene alterations. A major challenge in the diagnosis and treatment of such diseases is to identify characteristic aberrancies in the biological pathways and molecular network activities and elucidate their relationship to the disease. This review presents recent progress in using high-throughput biological assays to decipher aberrant pathways and network activities. In particular, this review provides specific examples in which high-throughput data have been applied to identify relationships between diseases and aberrant pathways and network activities. The achievements in this field have been remarkable, but many challenges have yet to be addressed.

More than 70 years after the first ex situ genebanks have been established, major efforts in this field are still concerned with issues related to further completion of individual collections and securing of their storage. Attempts regarding valorization of ex situ collections for plant breeders have been hampered by the limited availability of phenotypic and genotypic information. With the advent of molecular marker technologies first efforts were made to fingerprint genebank accessions, albeit on a very small scale and mostly based on inadequate DNA marker systems. Advances in DNA sequencing technology and the development of high-throughput systems for multiparallel interrogation of thousands of single nucleotide polymorphisms (SNPs) now provide a suite of technological platforms facilitating the analysis of several hundred of Gigabases per day using state-of-the-art sequencing technology or, at the same time, of thousands of SNPs. The present review summarizes recent developments regarding the deployment of these technologies for the analysis of plant genetic resources, in order to identify patterns of genetic diversity, map quantitative traits and mine novel alleles from the vast amount of genetic resources maintained in genebanks around the world. It also refers to the various shortcomings and bottlenecks that need to be overcome to leverage the full potential of high-throughput DNA analysis for the targeted utilization of plant genetic resources.

Life expectancy has dramatically increased in industrialized nations over the last 200 hundred years. The aging of populations carries over to clinical research and leads to an increasing representation of elderly and multimorbid individuals in study populations. Clinical research in these populations is complicated by the fact that individuals are likely to experience several potential disease endpoints that prevent some disease-specific endpoint of interest from occurrence. Large developments in competing risks methodology have been achieved over the last decades, but we assume that recognition of competing risks in the clinical community is still marginal. It is the aim of this article to address translational aspects of competing risks to the clinical community. We describe clinical populations where competing risks issues may arise. We then discuss the importance of agreement between the competing risks methodology and the study aim, in particular the distinction between etiologic and prognostic research questions. In a review of 50 clinical studies performed in individuals susceptible to competing risks published in high-impact clinical journals, we found competing risks issues in 70% of all articles. Better recognition of issues related to competing risks and of statistical methods that deal with competing risks in accordance with the aim of the study is needed. Copyright (C) 2011 John Wiley & Sons, Ltd.

Ortholog identification is used in gene functional annotation, species phylogeny estimation, phylogenetic profile construction and many other analyses. Bioinformatics methods for ortholog identification are commonly based on pairwise protein sequence comparisons between whole genomes. Phylogenetic methods of ortholog identification have also been developed; these methods can be applied to protein data sets sharing a common domain architecture or which share a single functional domain but differ outside this region of homology. While promiscuous domains represent a challenge to all orthology prediction methods, overall structural similarity is highly correlated with proximity in a phylogenetic tree, conferring a degree of robustness to phylogenetic methods. In this article, we review the issues involved in orthology prediction when data sets include sequences with structurally heterogeneous domain architectures, with particular attention to automated methods designed for high-throughput application, and present a case study to illustrate the challenges in this area.

Orthology is a powerful refinement of homology that allows us to describe more precisely the evolution of genomes and understand the function of the genes they contain. However, because orthology is not concerned with genomic position, it is limited in its ability to describe genes that are likely to have equivalent roles in different genomes. Because of this limitation, the concept of ‘positional orthology’ has emerged, which describes the relation between orthologous genes that retain their ancestral genomic positions. In this review, we formally define this concept, for which we introduce the shorter term ‘toporthology’, with respect to the evolutionary events experienced by a gene’s ancestors. Through a discussion of recent studies on the role of genomic context in gene evolution, we show that the distinction between orthology and toporthology is biologically significant. We then review a number of orthology prediction methods that take genomic context into account and thus that may be used to infer the important relation of toporthology.

The statistical language R and its Bioconductor package are favoured by many biostatisticians for processing microarray data. The amount of data produced by some analyses has reached the limits of many common bioinformatics computing infrastructures. High Performance Computing systems offer a solution to this issue. The Simple Parallel R Interface (SPRINT) is a package that provides biostatisticians with easy access to High Performance Computing systems and allows the addition of parallelized functions to R. Previous work has established that the SPRINT implementation of an R permutation testing function has close to optimal scaling on up to 512 processors on a supercomputer. Access to supercomputers, however, is not always possible, and so the work presented here compares the performance of the SPRINT implementation on a supercomputer with benchmarks on a range of platforms including cloud resources and a common desktop machine with multiprocessing capabilities. Copyright (C) 2011 John Wiley & Sons, Ltd.

Finding new uses for existing drugs, or drug repositioning, has been used as a strategy for decades to get drugs to more patients. As the ability to measure molecules in high-throughput ways has improved over the past decade, it is logical that such data might be useful for enabling drug repositioning through computational methods. Many computational predictions for new indications have been borne out in cellular model systems, though extensive animal model and clinical trial-based validation are still pending. In this review, we show that computational methods for drug repositioning can be classified in two axes: drug based, where discovery initiates from the chemical perspective, or disease based, where discovery initiates from the clinical perspective of disease or its pathology. Newer algorithms for computational drug repositioning will likely span these two axes, will take advantage of newer types of molecular measurements, and will certainly play a role in reducing the global burden of disease.

With the growing number of microRNAs (miRNAs) being identified each year, more innovative molecular tools are required to efficiently characterize these small RNAs in living animal systems. Caenorhabditis elegans is a powerful model to study how miRNAs regulate gene expression and control diverse biological processes during development and in the adult. Genetic strategies such as large-scale miRNA deletion studies in nematodes have been used with limited success since the majority of miRNA genes do not exhibit phenotypes when individually mutated. Recent work has indicated that miRNAs function in complex regulatory networks with other small RNAs and protein-coding genes, and therefore the challenge will be to uncover these functional redundancies. The use of miRNA inhibitors such as synthetic antisense 2′-O-methyl oligoribonucleotides is emerging as a promising in vivo approach to dissect out the intricacies of miRNA regulation.

Despite the common assumption that orthologs usually share the same function, there have been various reports of divergence between orthologs, even among species as close as mammals. The comparison of mouse and human is of special interest, because mouse is often used as a model organism to understand human biology. We review the literature on evidence for divergence between human and mouse orthologous genes, and discuss it in the context of biomedical research.

Pluripotent embryonic stem (ES) cells are specialized cells with a dynamic chromatin structure, which is intimately connected with their pluripotency and physiology. In recent years somatic cells have been reprogrammed to a pluripotent state through over-expression of a defined set of transcription factors. These cells, known as induced pluripotent stem (iPS) cells, recapitulate ES cell properties and can be differentiated to apparently all cell lineages, making iPS cells a suitable replacement for ES cells in future regenerative medicine. Chromatin modifiers play a key function in establishing and maintaining pluripotency, therefore, elucidating the mechanisms controlling chromatin structure in both ES and iPS cells is of utmost importance to understanding their properties and harnessing their therapeutic potential. In this review, we discuss recent studies that provide a genome-wide view of the chromatin structure signature in ES cells and iPS cells and that highlight the central role of histone modifiers and chromatin remodelers in pluripotency maintenance and induction.