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Pupil perspectives on school mental health literacy interventions: Experiences of three programmes in English primary and secondary schools
Full text linkFunded by the Department for Education, Education for Wellbeing is one of England's largest research programmes for school-based mental health interventions. The aim of the programme was to evaluate pioneering ways of supporting the mental wellbeing of pupils. The programme was split into two trials: AWARE (Approaches for Wellbeing and Mental Health Literacy: Research in Education), tested in secondary school settings, and INSPIRE (INterventions in Schools for Promoting Wellbeing: Research in Education), tested in both primary and secondary school settings (see AWARE Impact Findings and INSPIRE Impact Findings for more detail). Recruitment was conducted in three waves (2018, 2019, 2022). This briefing reports findings from a qualitative investigation into children and young people’s experiences across the two trials in Wave 1. It focuses on three school-based interventions - Youth Aware of Mental Health (YAM), Strategies for Safety and Wellbeing (SSW), and The Guide - all delivered on a universal basis as part of the Education for Wellbeing programme. Other briefings relating to this programme can be found at https://www.gov.uk/government/publications/education-for-wellbeing-programmefindings. From an implementation perspective, SSW, YAM, and The Guide are all curriculumbased interventions, with a focus on education to raise awareness of mental health to improve help-seeking, mental health, and wellbeing, and so are represented together in this briefing. Experiences of Mindfulness-based exercises and Relaxation techniques are disseminated in a companion document entitled, “Pupil perspectives on approaches to school wellbeing promotion: Experiences of Mindfulness-based exercises and Relaxation techniques”. Many children and young people within the qualitative research subsample reported multiple positive outcomes from the three interventions, including increased knowledge and awareness of mental health, new real-world problem-solving skills, and social connectedness. However, issues around the organisation of the lessons, including lack of time, repetitive content, and behaviour management, were referred to as barriers to engagement. The interventions were felt to provide a fun, relaxed, and safe environment for learning, through the use of interactive, creative, or practical exercises, mutual sharing of experiences, and a more informal structure than their usual lessons. However, sometimes participants found the content boring, such as when it was repetitive, or experienced certain topics as upsetting or anxiety-provoking
Current impacts of elevated CO2 on crop nutritional quality: a review using wheat as a case study
Full text linkThis review synthesises current research findings and modelling approaches to explore the impact of elevated atmospheric carbon dioxide (eCO2) concentrations on crop productivity, water and nutrient use efficiency, plant nutritional quality, and the implications for global food security. Over recent decades, rising atmospheric CO2 levels have sparked significant concern due to their role in driving climate change. While some studies highlight the potential benefits of eCO2, such as increased crop yields and improved wateruse efficiency, many recent investigations reveal a concerning decline in crop nutritional quality. eCO2 has been shown to reduce concentrations of key nutrients, including nitrogen, minerals, vitamins, polyphenols, and other non-nutrient compounds, as well as alter gene expression. These changes are further complicated by interactions with heat stress and drought, presenting significant challenges in predicting sustainable future crop productivity. These nutritional declines exacerbate the global crisis of malnutrition and hidden hunger, threatening the achievement of Sustainable Development Goal 2 (SDG2), which aims to end hunger and ensure food security. Addressing these challenges requires further research, interdisciplinary collaboration, and innovative approaches to mitigate the adverse effects of eCO2 on crop physiology and nutritional content while maximising agricultural sustainability. This review aims to provide insights into the complex mechanisms governing crop responses to eCO2 using wheat as a model and proposes pathways for future research and agricultural practices. These strategies are critical for tackling the intricate dynamics of climate variability, ensuring nutrient-rich food production, and securing food security in the face of a rapidly changing climate
Detection of β-d-glucuronidase activity in environmental samples using 4-fluorophenyl β-d-glucuronide and 19F NMR
Full text linkCommon methods for establishing the presence of enteric bacteria polluting water supplies, or in other samples, rely on detecting the hydrolysis of model glucuronide substrates by glucuronidases to release a phenolic product quantifiable by absorbance or fluorescence. Substrates include the β-D-glucuronides of p-nitrophenol, and umbelliferyl or quercetin derivatives. One limitation is that it may be difficult or impossible to quantify the released phenolic moiety in samples that are strongly coloured or, that contain fluorescent compounds. Exploiting the sensitivity available from the 19F nucleus to changes in chemical environment which can be detected by 19F NMR spectroscopy, and the almost complete absence of 19F from naturally-occurring samples containing organic matter, which provides background-free signals, we propose a model substrate; 4-fluorophenyl β-D-glucuronide (4FP-glucuronide). The 19F NMR chemical shift position of 4FP-glucuronide changes from −121.0 ppm upon hydrolysis to release 4-fluorophenol, at −124.9 ppm (at pH 6.8), enabling detection of β-glucuronidase activity. We illustrate the use of this substrate with environmental samples from forest soil, standing water, and mud from cattle pasture. Each of these would challenge conventional methods, owing to their opacity or the presence of coloured organic material. The technique enables detection of glucuronidases, a widely-used proxy for enteric bacteria, extending the scope of testing beyond water to include environmental and other challenging samples
Racism as the fundamental cause of ethnic inequities in COVID-19 vaccine hesitancy: A theoretical framework and empirical exploration using the UK Household Longitudinal Study
Full text linkEthnic inequities in COVID-19 vaccine hesitancy have been reported in the United Kingdom (UK), and elsewhere. Explanations have mainly focused on differences in the level of concern about side effects, and in lack of trust in the development and efficacy of vaccines. Here we propose that racism is the fundamental cause of ethnic inequities in vaccine hesitancy. We introduce a theoretical framework detailing the mechanisms by which racism at the structural, institutional, and interpersonal level leads to higher vaccine hesitancy among minoritised ethnic groups. We then use data from Wave 6 of the UK Household Longitudinal Study COVID-19 Survey (November to December 2020) to empirically examine these pathways, operationalised into institutional, community, and individual-level factors. We use the Karlson–Holm–Breen method to formally compare the relationship between ethnicity and vaccine hesitancy once age and gender, sociodemographic variables, and institutional, community, and individual-level factors are accounted for. Based on the Average Partial Effects we calculate the percentage of ethnic inequities explained by each set of factors. Findings show that institutional-level factors (socioeconomic position, area-level deprivation, overcrowding) explained the largest part (42%) of the inequity in vaccine hesistancy for Pakistani or Bangladeshi people, and community-level factors (ethnic density, community cohesion, political efficacy, racism in the area) were the most important factors for Indian and Black groups, explaining 35% and 15% of the inequity, respectively. Our findings suggest that if policy intervened on institutional and community-level factors – shaped by structural and institutional racism - considerable success in reducing ethnic inequities might be achieved
Towards advanced decision-making support for shipping safety: A functional connectivity analysis
Full text linkDecision making (DM) is essential and proven to be a natural and inherent part of the success of transport systems, particularly given the fast growth of autonomous systems in transport. It is critical but remains challenging to understand and predict DM performance in transport, because operators’ mental states have not been effectively considered in complex DM processes such as ship anti-collision operations. This paper proposes an advanced decision support methodology that pioneers the incorporation of objective neurophysiological and subjective data to analyse functional connectivity in the brain and predict DM performance in ship navigation. Experiments were conducted using a functional Near-Infrared Spectroscopy (fNIRS) technology to explore the functional connectivity of two groups (low workload and high workload) and predict their DM performance in a ship collision avoidance situation. It brings brain science into transport engineering and the results generate new contributions to the existing knowledge, including (1) the establishment of a methodology to detect different workload levels in safety–critical transport systems using psychophysiological measurement; (2) analysis of brain's functional connectivity of different groups of decision makers (e.g., seafarers) with high and low workload tasks; (3) an advanced methodology to assess human reliability in complex scenarios and predict operational behaviours; (4) pioneering a human-centred approach to predict DM performance and demonstrate its feasibility in shipping. From a practical perspective, stakeholders can utilise the findings of this study to rationally evaluate human performance in transport system operations, aiding in operator qualification and certification processes. Furthermore, it is critical for adaptive automation regarding DM support in safety–critical systems
Religiosity and resilience in entrepreneurship: uncovering the underlying mechanism through the lens of spiritual capital
Full text linkDrawing on the resilience theory and espousing the spiritual capital approach, the purpose of this study is to assess the indirect effect of religiosity on Omani entrepreneurs’ psychological resilience through the intervening roles of coping with failure, perseverance, locus of control, and optimism. Design and Methodology The study adopts a quantitative design and gathers data from 125 entrepreneurs in Oman, through questionnaires. A structural equation modelling approach is used to test the hypotheses. Findings The study finds that entrepreneurs’ religiosity influences resilience indirectly through coping with failure, perseverance, and locus of control. Surprisingly, optimism played a trivial role in this dynamic. Originality It has been well acknowledged that religiosity provides a pool of resources crucial to entrepreneurs’ survival and success. However, despite this intuitive link, the mechanism whereby religiosity enhances entrepreneurial resilience remains misunderstood. This is problematic as entrepreneurs’ psychological resilience is an important attribute for survival, especially during challenging times. Hence, this study advances the current understanding of the religiosity-resilience nexus by uncovering its underlying mechanism
Investigating outcomes in a substance use treatment provider: a cross-sectional comparison of long-acting injectable buprenorphine and oral medication for opioid use disorder
Full text linkOBJECTIVES: Advances in the treatment of opioid use disorder (OUD) have seen the development of long-acting injectable opioid substitutes which could improve outcomes for people with OUD. However, comparative quantitative analysis of individual outcomes is lacking. The present study sought to investigate factors associated with prescribing long-acting injectable buprenorphine (LAIB), and changes in outcome variables compared with oral medication for OUD. DESIGN: Cross-sectional retrospective analysis of electronic health records. SETTING: Community substance use treatment service Via. Six sites shared their data between 15 August 2022 and 15 August 2023. PARTICIPANTS: Anonymised data were extracted for 235 people receiving LAIB and 266 people receiving oral medication for OUD. PRIMARY AND SECONDARY OUTCOMES: Prescribing data, sociodemographic information (age, sex, indices of multiple deprivation decile of individual's residence, primary and secondary substance, number of previous treatment episodes, employment and ethnicity) and treatment outcome profiles (substance use, physical and mental health, quality of life, employment) were extracted and analysed. To examine predictors of receiving LAIB (vs medication for OUD), we conducted logistic regression including the demographic predictors. Psychological health, physical health and quality of life scores were analysed using Welch's t-tests. RESULTS: LAIB was associated with positive changes in quality of life between the first and last assessments. Demographic and situational factors were predictors of LAIB initiation, indicating the potential for increasing health inequalities in substance use treatment. CONCLUSIONS: LAIB is associated with changes in quality of life over a 1-year period. Further research is needed to investigate the aetiology of improved well-being and outcomes over time
Power efficient random access for massive NB-IoT connectivity
Full text linkSensors enabled Internet of things (IoT) has become an integral part of the modern, digital and connected ecosystem. Narrowband IoT (NB-IoT) technology is one of its economical versions preferable when low power and resource limited sensors based applications are considered. One of the major characteristics of NB-IoT technology is its offer of reliable coverage enhancement (CE) which is achieved by repeating the transmission of signals. This repeated transmission of the same signal challenges power saving in low complexity NB-IoT devices. Additionally, the NB-IoT devices are expected to suffer from congestion due to simultaneous random access procedures (RAPs) from an enormous number of devices. Multiple RAP reattempts would further reduce the power saving in NB-IoT devices. We propose a novel power efficient RAP (PE-RAP) for reducing power consumption of NB-IoT devices in a highly congested environment. The existing RAP do not differentiate the failures due to poor channel conditions or due to collision. After the RAP failure either due to collision or poor channel, the devices can apply power ramping or can transit to a higher CE level with higher repetition configuration. In the proposed PE-RAP, the NB-IoT devices can re-ascertain the channel conditions after an RAP attempt failure such that the impediments due to poor channel are reduced. The power increments and repetition enhancements are applied only when necessary. We probabilistically obtain the chances of RAP reattempts. Subsequently, we evaluate the average power consumption by devices in different CE levels for different repetition configurations. We validate our analysis by simulation studies
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