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Bridging the gap from medical to psychological safety assessment : a consensus study in a digital mental health context
No full textBackground
Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence.
Aims
The aim of this study was to generate an experts’ consensus on how the medical regulatory method used for assessing safety could best be adapted for DMHIs.
Method
An online Delphi study containing three rounds was conducted with an international panel of 20 experts with experience/knowledge in the field of UK digital mental health.
Results
Sixty-four items were generated, of which 41 achieved consensus (64%). Consensus emerged around ten recommendations, falling into five main themes: Enhancing the quality of adverse events data in DMHIs; Re-defining serious adverse events for DMHIs; Reassessing short-term symptom deterioration in psychological interventions as a therapeutic risk; Maximising the benefit of the Yellow Card Scheme; and Developing a harmonised approach for assessing the safety of psychological interventions in general.
Conclusion
The implementation of the recommendations provided by this consensus could improve the assessment of safety of DMHIs, making them more effective in detecting and mitigating risk
Learning legacies : better understanding of the dynamics of domestic abuse suicidality through domestic homicide reviews
No full textThis article draws on analysis of 32 Domestic Homicide Reviews (DHRs) undertaken in England and Wales in cases where the deceased took their life in the context of domestic abuse, as well as a series of 36 interviews and one focus group discussion, conducted by the authors with key stakeholders in the DHR process, including commissioners, Chairs, panel members, and bereaved families. Discussion reflects on the clear, but also complicated, causal relationship between domestic abuse and suicidality that is demonstrated through this data, with close analysis of the experiences reflected within the DHRs providing a particularly rich and textured account of victims’ navigation of complex vulnerabilities, often in plain sight of statutory and third sector services. Highlighting lessons that can, and should, be learned from these human legacies, in the closing sections of the article, we underscore the importance of recognising the compounding effects of intersecting vulnerabilities in a way that resists siloed or victim-blaming responses, while not diminishing the role and responsibility of the perpetrator(s) of abuse. We also emphasise the need for more holistic, trauma-informed, and sustainably funded support, that can connect expertise around domestic abuse more effectively and consistently with expertise on suicide prevention
Size-biased diffusion limits and the inclusion process
Get PDFWe consider the inclusion process on the complete graph with vanishing diffusivity, which leads to condensation of particles in the thermodynamic limit. Describing particle configurations in terms of size-biased and appropriately scaled empirical measures of mass distribution, we establish convergence in law of the inclusion process to a measure-valued Markov process on the space of probability measures. In the case where the diffusivity vanishes like the inverse of the system size, the derived scaling limit is equivalent to the well known Poisson-Dirichlet diffusion, offering an alternative viewpoint on these well-established dynamics. Moreover, our novel size-biased approach provides a robust description of the dynamics, which covers all scaling regimes of the system parameters and yields a natural extension of the Poisson-Dirichlet diffusion to infinite mutation rate. We also discuss in detail connections to known results on related Fleming-Viot processes
Do 14-17-month-old infants use iconic cues to interpret words?
No full textThis study investigated whether infants use iconicity in speech and gesture to interpret words. Thirty-six 14-17-month-old infants participated in a preferential looking task in which they heard a spoken non-word (e.g., “zudzud”) while observing a small and a large object (e.g., a small and a large square). All infants were presented with an iconic cue for object size (small or large) in 1) the pitch of the spoken non-word (high vs. low), 2) in gesture (small or large), or 3) congruently in both pitch and gesture (e.g., a high pitch and a small gesture indicating a small square). Infants did not show a preference for congruently sized objects in any iconic cue condition. Bayes Factor analyses supported the null hypotheses. In conclusion, we found no evidence that infants link the pitch of spoken non- words, or the iconic gestures accompanying those spoken non- words, to object size
Mental health, pain and tiredness in adults born very preterm or with very low birthweight
Get PDFAim: Adults born preterm have increased risk of mental health problems and other neurodevelopmental conditions. We aimed to investigate associations of mental health with pain and tiredness in adults born very preterm (VP; <32 weeks) or very low birthweight (VLBW; <1500 g) and at term, and whether these associations are influenced by physical activity.
Methods: As part of an EU Horizon 2020 project, individual participant data from six prospective cohort studies were harmonised for 617 VP/VLBW and 1122 term‐born participants. Mental health was assessed by the Achenbach System of Empirically Based Assessment Adult Self‐Report. Pain and tiredness were harmonised based on specific items from self‐reported questionnaires. Associations between mental health and pain or tiredness were explored by linear regression.
Results: An increase in the mental health scales internalising, externalising and total problems was associated with increased pain and tiredness in the preterm and term group alike. Results were maintained when adjusting for physical activity.
Conclusion: The findings indicate that associations between mental health, pain and tiredness in adults are independent of gestation or birthweight. Future research should explore other potential mechanisms that may underlie the increased risk of mental health problems in the preterm population
Technology-mediated discourse and second language research
No full textTechnology-mediated discourse—interaction between human beings through technological artifacts—has become an established part of everyday life in both social and institutional contexts since the introduction of the telephone in the late 1800s. Synchronous digital interaction became possible in the 1970s when written interaction, also known as text chat, was introduced at the University of Illinois, where it was known as Talkomatic (Grubbs, 2004), with asynchronous interaction (email) starting at around the same time (Gibbs, 2016). Email and chat interaction shifted the focus in technology-mediated teaching and research from interaction with computers to interaction through computers (Warschauer, 2003). Second language (L2) teachers and researchers saw the potential of technology-mediated interaction to provide learners with opportunities to interact with and learn from expert speakers of the target language, outside the classroom, in authentic social contexts. Participants in these digital exchanges were mostly geographically dispersed. However, as various technologies became widely available, researchers of L2 learning began to examine digital interaction from various methodological and theoretical perspectives, based on previous research on L1 (first language) and L2 learning and interaction, and adapted to the new digital L2 contexts of interest. This research spawned various new L2 learning journals that provided technology-mediated L2 learning researchers with a public scholarly outlet for their work. These include, in order of establishment, System (1973), CALICO (1983), ReCALL (1989), Computer Assisted Language Learning (1990) as well as the highly regarded public access journal Language Learning and Technology (1997)
What is the best way to evaluate social prescribing? A qualitative feasibility assessment for a national impact evaluation study in England
Get PDFObjectives
Despite significant investment in social prescribing in England over the last decade, we still do not know if it works, or how models of social prescribing fit within wider health and care policy and practice. This study explores current service delivery structures and assesses the feasibility of a national evaluation of the link worker model.
Methods
Semi-structured interviews were conducted between May and September 2020, with 25 key informants from across social prescribing services in England. Participants included link workers, voluntary, community and social enterprise staff, and those involved in policy and decision-making for social prescribing services. Interview and workshop transcripts were analysed thematically, adopting a framework approach.
Results
We found differences in how services are provided, including by individual link workers, and between organisations and regions. Standards, referral pathways, reporting, and monitoring structures differ or are lacking in voluntary services as compared to clinical services. People can self-refer to a link worker or be referred by a third party, but the lack of standardised processes generated confusion in both public and professional perceptions of the link worker model. We identified challenges in determining the appropriate outcomes and outcome measures needed to assess the impact of the link worker model.
Conclusions
The current varied service delivery structures in England poses major challenges for a national impact evaluation. Any future rigorous evaluation needs to be underpinned with national standardised outcomes and process measures which promote uniform data collection
Self-supervised high dynamic range imaging : what can be learned from a single 8-bit video?
Get PDFRecently, Deep Learning-based methods for inverse tone mapping standard dynamic range (SDR) images to obtain high dynamic range (HDR) images have become very popular. These methods manage to fill over-exposed areas convincingly both in terms of details and dynamic range. To be effective, deep learning-based methods need to learn from large datasets and transfer this knowledge to the network weights. In this work, we tackle this problem from a completely different perspective. What can we learn from a single SDR 8-bit video? With the presented self-supervised approach, we show that, in many cases, a single SDR video is sufficient to generate an HDR video of the same quality or better than other state-of-the-art methods
Handbook of accounting in society
No full textThe Handbook of Accounting in Society invites readers to consider the ways in which accounting affects organizations, institutions, communities, professions, and everyday life. Diverse in its reach, this Handbook campaigns for the need to reconsider our understanding of what accounting is and crucially, what it can become
