Behind the masks:A cross-sectional study on intolerance of uncertainty, perceived vulnerability to disease and psychological flexibility in relation to anxiety and wellbeing during the COVID-19 pandemic

Early findings suggest the COVID-19 pandemic and related containment measures negatively impact mental wellbeing. This study compared the contribution and relations of three factors to anxiety and wellbeing during the pandemic in June 2020. These factors were: i) Contextual factors (e.g. exposure to COVID-19, being a keyworker, feeling lonely); ii) Cognitive appraisals: perceived vulnerability to disease (PVD) and intolerance of uncertainty (IU); and iii) psychological flexibility (PF). 603 participants aged 18 or older completed an online survey of self-report measures. Hierarchical regression analyses demonstrated PVD, IU and PF predicted state anxiety, and IU and PF predicted mental wellbeing. Some, but not all of the contextual factors also predicted state anxiety and wellbeing. The findings support cognitive appraisal theories and the PF model, lending support to an acceptance and commitment therapy (ACT) approach to public health during pandemics

Perspectives and experiences of community health workers in Brazilian primary care centers using m-health tools in home visits with community members

Abstract Background Mobile health (m-health) tools are a promising strategy to facilitate the work of community health workers (CHWs) in low- and middle-income countries (LMICs). Despite their potential value, little is known about CHWs’ experiences working with m-health tools in their outreach activities with community members. Methods To understand the benefits of and barriers to using m-health tools for CHWs, we conducted semi-structured interviews with 57 CHWs employed in six primary care centers in São Paulo, Brazil. All CHWs had experience using a cell phone application called Geohealth for collecting health and demographic data of community members. We assessed their experiences using Geohealth and recommendations for improvements. Results CHWs described key benefits of using Geohealth as helping them save time with bureaucratic paperwork, organizing the data that they needed to collect, and by replacing sheaves of paper, reducing the weight that they carried in the field. However, there were many technical and social barriers to the successful adoption of the m-health tool. Key among these were poor quality hardware, faulty software programs, and negative community member perceptions of the m-health program. The CHWs provided valuable input as to how Geohealth could be improved to fit their needs. Conclusion m-health tools have the potential to facilitate the work of CHWs in LMICs. However, such tools must be designed and implemented thoughtfully. Technical barriers related to both hardware and software must be anticipated and addressed to maximize their efficiency and successful adoption. CHW input on the design of the tool should be sought to maximize its utility and minimize barriers to use.https://deepblue.lib.umich.edu/bitstream/2027.42/138148/1/12960_2017_Article_245.pd

Chorioamnionitis: Case definition & guidelines for data collection, analysis, and presentation of immunization safety data

Chorioamnionitis is a term encompassing a broad spectrum of disease during pregnancy that is characterized by inflammation and/or infection of intrauterine structures such as the placenta, the chorion and amnion. The clinical presentation of chorioamnionitis can vary based on clinical, microbiologic, and histologic factors which interact and overlap to varying degrees

Extending an evidence hierarchy to include topics other than treatment: revising the Australian 'levels of evidence'

Background: In 1999 a four-level hierarchy of evidence was promoted by the National Health and Medical Research Council in Australia. The primary purpose of this hierarchy was to assist with clinical practice guideline development, although it was co-opted for use in systematic literature reviews and health technology assessments. In this hierarchy interventional study designs were ranked according to the likelihood that bias had been eliminated and thus it was not ideal to assess studies that addressed other types of clinical questions. This paper reports on the revision and extension of this evidence hierarchy to enable broader use within existing evidence assessment systems. Methods: A working party identified and assessed empirical evidence, and used a commissioned review of existing evidence assessment schema, to support decision-making regarding revision of the hierarchy. The aim was to retain the existing evidence levels I-IV but increase their relevance for assessing the quality of individual diagnostic accuracy, prognostic, aetiologic and screening studies. Comprehensive public consultation was undertaken and the revised hierarchy was piloted by individual health technology assessment agencies and clinical practice guideline developers. After two and a half years, the hierarchy was again revised and commenced a further 18 month pilot period. Results: A suitable framework was identified upon which to model the revision. Consistency was maintained in the hierarchy of "levels of evidence" across all types of clinical questions; empirical evidence was used to support the relationship between study design and ranking in the hierarchy wherever possible; and systematic reviews of lower level studies were themselves ascribed a ranking. The impact of ethics on the hierarchy of study designs was acknowledged in the framework, along with a consideration of how harms should be assessed. Conclusion: The revised evidence hierarchy is now widely used and provides a common standard against which to initially judge the likelihood of bias in individual studies evaluating interventional, diagnostic accuracy, prognostic, aetiologic or screening topics. Detailed quality appraisal of these individual studies, as well as grading of the body of evidence to answer each clinical, research or policy question, can then be undertaken as required.Tracy Merlin, Adele Weston and Rebecca Toohe

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Posthuman disability studies

This article explores the human through critical disability studies and the theories of Rosi Braidotti. We ask: What does it mean to be human in the twenty-first century and in what ways does disability enhance these meanings? In addressing this question we seek to work through entangled connections of nature, society, technology, medicine, biopower and culture to consider the extent to which the human might be an outdated phenomenon, replaced by Braidotti’s posthuman condition. We then introduce disability as a political category, an identity and a moment of relational ethics. Critical disability studies, we argue, are perfectly at ease with the posthuman because disability has always contravened the traditional classical humanist conception of what it means to be human. Disability also invites a critical analysis of the posthuman. We examine the ways in which disability and posthuman work together, enhancing and complicating one another in ways that raise important questions about the kinds of life and death we value. We consider three of Braidotti’s themes in relation to disability: (i) Life beyond the self: Rethinking enhancement; (ii) Life beyond the species: Rethinking animal; (iii) Life beyond death: Rethinking death. We conclude by advocating a posthuman disability studies that responds directly to contemporary complexities around the human while celebrating moments of difference and disruption

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]