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The Platt 3p (P3p) model of mental health interventions
Get PDFPurpose - This paper introduces the Platt 3p model (P3p), an innovative framework aiming to address
the mental health needs of young people. The model comprises three dimensions: past, present, and potential, on which any mental health intervention should act in order to improve
mental health outcomes.
Design/methodology/approach - A conceptual analysis is made that uses an interdisciplinary approach to draw on existing
research and theories from psychology, developmental science, and educational interventions to create the P3p model.
Findings - The P3p model presents a multi-layered approach that considers subjective, individual, and
group-level variables that should be considered in comprehensive mental health
interventions. It accommodates systemic barriers and individual differences, thus creating the
potential for more targeted, effective interventions.
Originality - The P3p model is novel in its integrative approach, fusing elements from disparate theories
into a singular framework. This flexibility allows for person-centred, adaptable interventions
that are tailored to individual needs.
Research limitations/implications -Though every effort has been made to provide a robust theoretical foundation, the model has yet to be empirically validated. Future research is taking place to apply the model in school
settings to assess its practical efficacy
Social virtual reality helps to reduce feelings of loneliness and social anxiety during the Covid-19 pandemic.
Get PDFEvidence shows that the Covid-19 pandemic caused increased loneliness, anxiety and greater social isolation due to social distancing policies. Virtual reality (VR) provides users with an easy way to become engaged in social activities without leaving the house. This study focused on adults, who were socialising in Altspace VR, a social VR platform, during the Covid-19 pandemic and it explored whether social VR could alleviate feelings of loneliness and social anxiety. A mixed-methods research design was applied. Participants (n = 74), aged 18-75, completed a questionnaire inside the social VR platform to measure levels of loneliness (UCLA 20-item scale) and social anxiety (17-item SPIN scale) in the social VR platform (online condition) and real world (offline condition). Subsequently, a focus group (n = 9) was conducted to gather insights into how and why participants were using the social VR platform. Findings from the questionnaire revealed significantly lower levels of loneliness and social anxiety when in the social VR platform. Lower levels of loneliness and social anxiety were also associated with participants who socialised with a regular group of friends. In addition, findings from the focus group suggested that being part of an online group facilitates stronger feelings of belonging. Social VR can be used as a valuable intervention to reduce feelings of loneliness and social anxiety. Future studies should continue to establish whether social VR can help to encourage group formation and provide people with enhanced social opportunities beyond the COVID-19 pandemic
The economic and social implications of food waste management and its impacts when converted to herald new business opportunities - a case study of Rawalpindi, Pakistan
Get PDFThe problem of food waste affects not only the economy but also society and the environment. Previous
and current studies show that measures have been put in place to combat the recurring social and
economic issues caused by the inefficiency of food waste management; however, this is a long way
towards achieving global goals. This research aims to bridge the gap by evaluating the importance of
efficiently handling urban household food waste and its correlation between economic and social factors.
It focuses on Rawalpindi, a metropolitan city in Pakistan. The core theme is value creation–leveraging the
benefit of a zero-value resource to achieve social and economic benefits through the operational
management of food waste in Pakistan’s crumbling economy.
It is observed in the case of Pakistan that there are many risks involved to the environment and the wellbeing of people, such as diseases and negative externalities associated with the improper handling of food
waste. A sequential explanatory mixed method was used. Data were collected using a self-completed
questionnaire administered to urban households (n=176), in-depth interviews with heads of household
(n-21), and five focus groups (n=24).
The research revealed a need for more knowledge about the immense potential of food waste; most
people are incognizant of converting it into a valuable resource. The research further revealed that social
and economic factors were not only concerns but also cultural and behavioural aspects that contribute to
the issue of household food waste. Individuals experienced challenges in collecting food waste as it ended
up in general waste due to the unavailability of a collection mechanism. Major concerns for the
households were electric power cuts and extreme weather conditions.
Implementing effective and efficient policies will add value to a valuable resource by minimizing and
making the most of food waste. The study further recommends developing a mechanism for collecting
and optimizing food waste so this nonvalue resource can be turned into a valuable resource
Professional commercial dance: creative curriculum tracking trends
Get PDFCommercial dance is an area that is largely neglected within the dance field,
specifically in the United Kingdom. However, as a dance form, this is accessed and
seen the most within broader society through recent technological advancements and
mass media. There is a significant lack of academic research and literature that
explores commercial dance as an industry and from an educational perspective. This
research conceptualises the current position of commercial dance within the United
Kingdom and explores the dance curriculum within HE and conservatoire
environments. It evaluates curriculum relevance and currency to prepare graduates
for commercial dance employment effectively. In addition, this research considers the
wider dance industry and societal trends and their influences on curriculum design and
delivery.
This study uses a qualitative methodology through an interpretive narrative approach,
exploring the lived experiences of students, educational leaders, recent graduates,
and industry employers. These experiences are gathered through semi-structured
interviews, focus group interviews and observations within the field of dance that afford
and enrich the study with real-world, real-time data. This research concludes that
commercial dance is not a form of dance, but an umbrella term used to describe any
dance form used for monetary purposes. The study highlights a hierarchy within the
dance field between ‘traditional’ Western dance forms and those that sit under the commercial umbrella. This research also establishes that recent technological
advancements have significantly impacted how the commercial dance industry
operates, alongside the broader impact on professional dance training. Furthermore, this research highlights the negative long-term impact that authoritarian and traditional
dance pedagogies have on students and graduates.
To conclude, this research recommends that dance education must embrace
technological advancements and the influence these have upon the dance industry
whilst affording greater status to the value of commercial dance. The dance field
should also acknowledge that ‘commercial dance’ is not a form of dance, but a generic
term used to describe several dance forms and a wider employment industry
Diagnostic and cost‐effectiveness of axial skeleton MRI in staging high‐risk prostate cancer
Get PDFCurrent literature suggests that axial skeleton magnetic resonance imaging (AS‐MRI) is more sensitive than Tc 99m bone scintigraphy (BS) for detecting bone metastases (BM) in high‐risk prostate cancer (PCa). However, BS is still widely performed. Its diagnostic accuracy has been studied; however, its feasibility and cost implications are yet to be examined. Methods: We reviewed all patients with high risk PCa undergoing AS‐MRI over a 5‐year period. AS‐MRI was performed on patients with histologically confirmed PCa and either PSA > 20 ng/ml, Gleason ≥8, or TNM Stage ≥T3 or N1 disease. All AS‐MRI studies were obtained using a 1.5‐T AchievaPhilips™MRI scanner. We compared the AS‐MRI positivity and equivocal rate with that of BS. Data were analysed according to Gleason score, T‐stage and PSA. Multivariate logistic regression analyses were used to quantify the strength of association between positive scans and clinical variables. Feasibility and burden of expenditure was also evaluated. Results: Five hundred three patients with a median age of 72 and a mean PSA of 34.8 ng/ml were analysed. Eighty‐eight patients (17.5%) were positive for BM on AS‐MRI (mean PSA 99 [95% CI 69.1–129.9]). Comparatively 409 patients (81.3%) were negative for BM on AS‐MRI (mean PSA 24.7 (95% CI [21.7–27.7]) (p = 0.007); 1.2% (n = 6) of patients had equivocal results (mean PSA 33.4 [95% CI 10.5–56.3]). There was no significant difference in age (p = 0.122) between this group and patients with a positive scan, but there was a significant difference in PSA (p = 0.028), T stage (p = 0.006) and Gleason score (p = 0.023). In comparison with BS, AS‐MRI detection rate was equivalent or higher compared with the literature. Based on NHS tariff calculations, there would be a minimum cost saving of £8406.89. All patients underwent AS‐MRI within 14 days. Conclusion: The use of AS‐MRI to stage BM in high‐risk PCa is both feasible and results in a reduced burden of expenditure
Bibliometric analysis of scientific literature on mental health research in Africa
No full textThis bibliometric study presents a comprehensive summary of literature published on mental health research in Africa. The region has a
large number of scientific studies conducted in this area. The purpose
of this study was to investigate the contributions of African researchers
to global mental research. It also investigated the quantity of research
and publications about Africa. Bibliographic information for the analysis was retrieved from the Web of Science database. Over 11,960 and
1,144 articles from 1900 to the present were culled and examined respectively. Using scientific mapping tools and performance analysis methods,
this study pinpointed the top countries, institutions, collaboration patterns, prolific authors, and developing themes in this research field.
Although the results showed that African scholars contributed significantly to worldwide research and publication on mental health, the
number of publications that are exclusively about Africa is only 0.09% of the global output. A closer look at the data showed that South Africa
really outperformed all other countries in terms of research output. Anxiety, depression, and Covid-19 were the three most common terms used
by authors. The results are noteworthy for the academic community
because they provided a historical context for mental health studies
Stars in the making : the rise of UK migrant entrepreneurs
Get PDFThe UK used to be primarily an emigration country, but in recent years, far more migrants have
arrived at the UK borders. These immigrants play a vital role in the country's entrepreneurial
landscape, with many starting businesses contributing to the economy's growth and
development. Migrant entrepreneurs are essential to the UK's entrepreneurial ecosystem,
contributing to economic growth and job creation. However, starting and running a business in
a new country can be challenging, particularly for migrants who face cultural, language, and
regulatory barriers. Therefore, to thrive as a migrant entrepreneur in the UK, specific skills are
necessary. This paper examines the experiences of Nigerian immigrant entrepreneurs in the
UK, focusing on identifying challenges, opportunities and critical entrepreneurship skills
immigrant entrepreneurs need to succeed in the UK business landscape
Traffic sign recognition for autonomous vehicle using optimized YOLOv7 and convolutional block attention module
Get PDFThe infrastructure and construction of roads are crucial for the economic and social development of a region, but traffic-related challenges like accidents and congestion persist. Artificial Intelligence (AI) and Machine Learning (ML) have been used in road infrastructure and construction, particularly with the Internet of Things (IoT) devices. Object detection in Computer Vision also plays a key role in improving road infrastructure and addressing traffic-related problems. This study aims to use You Only Look Once version 7 (YOLOv7), Convolutional Block Attention Module (CBAM), the most optimized object-detection algorithm, to detect and identify traffic signs, and analyze effective combinations of adaptive optimizers like Adaptive Moment estimation (Adam), Root Mean Squared Propagation (RMSprop) and Stochastic Gradient Descent (SGD) with the YOLOv7. Using a portion of German traffic signs for training, the study investigates the feasibility of adopting smaller datasets while maintaining high accuracy. The model proposed in this study not only improves traffic safety by detecting traffic signs but also has the potential to contribute to the rapid development of autonomous vehicle systems. The study results showed an impressive accuracy of 99.7% when using a batch size of 8 and the Adam optimizer. This high level of accuracy demonstrates the effectiveness of the proposed model for the image classification task of traffic sign recognition
Modified CNN with Adam and Nadam optimizers for emotion recognition using facial expressions
Get PDFPeople communicate using one of the communication types
of facial expressions. Human feelings are detected through
facial expressions to interpret their present state of mood. It
stimulates researchers to work in the field of emotion
recognition. The design of deep learning models is essential
to interpret the human current mind state by capturing the
pattern of the facial gesture through their facial expressions.
This study proposed a customized Convolutional Neural
Network (CNN) with various optimizers Adaptive Moment
Estimation (Adam) and Nesterov-accelerated Adaptive
Moment Estimation (Nadam) to improve emotion
recognition using the dataset FER-2013. The customized
proposed model is designed by varying the number of
convolution layers, filters, filter sizes, and optimizers. The
emotions are recognized using softmax activation in the
output layer. The experimental results have proved that the
proposed model classified the facial expressions with
accuracy of 0.841, 0.826 using Nadam and Adam optimizers
respectively
Decision-analysis modelling of effectiveness and cost-effectiveness of pharmacological thromboprophylaxis for surgical inpatients, using variable risk assessment models or other strategies
Get PDFBackground
Surgical inpatients are at risk of venous thromboembolism (VTE) which can be life-threatening or result in chronic complications. Thromboprophylaxis reduces VTE risk but incurs costs and may increase bleeding risk. Risk assessment models (RAMs) are currently used to target thromboprophylaxis at high-risk patients.
Objective
To determine the balance of cost, risk, and benefit for different thromboprophylaxis strategies in adult surgical inpatients, excluding major orthopaedic surgery, critical care and pregnant women.
Methods
Decision analytic modelling to estimate the following outcomes for alternative thromboprophylaxis strategies: thromboprophylaxis usage; VTE incidence and treatment; major bleeding; chronic thromboembolic complications; and overall survival. Strategies compared were: no thromboprophylaxis; thromboprophylaxis for all; and thromboprophylaxis given according to RAMs (Caprini and Pannucci). Thromboprophylaxis is assumed to be given for the duration of hospitalisation. The model evaluates life-time costs and quality-adjusted life-years (QALYs) within England’s health and social care services.
Results
Thromboprophylaxis for all surgical inpatients had a 70% probability of being the most cost-effective strategy (at a £20,000 per QALY threshold). RAM-based prophylaxis would be the most cost-effective strategy if a RAM with higher sensitivity (99.9%) were available for surgical inpatients. QALY gains were mainly due to reduced post-thrombotic complications. The optimal strategy was sensitive to several other factors including: risk of VTE, bleeding and post thrombotic syndrome; duration of prophylaxis and patient age.
Conclusions
Thromboprophylaxis for all eligible surgical inpatients appeared to be the most cost-effective strategy. Default recommendations for pharmacological thromboprophylaxis, with the potential to ‘opt-out’, may be superior to a complex risk-based ‘opt-in’ approach