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Life after lockdown: The experiences of older adults in a contactless digital world
Full text linkIntroduction: The digital response to the Coronavirus (COVID-19) pandemic and its effects on the lives of older adults has been well-documented, but less is known about how they experienced the post-lockdown re-emergence into a relatively contactless digital society.
Methods: We report the findings from a qualitative survey (n = 93) and subsequent interviews (n = 9) with older adults aged 50+, where they describe their struggles with some of the newly implemented digital interactions. These struggles cover a range of settings but include using contactless payments, QR codes and apps to facilitate transactions in cafes, bars, and restaurants.
Results: A thematic analysis of our data revealed the intrinsic (e.g. digital literacy) and extrinsic (e.g. malfunctioning technology) factors that limited social inclusion for these participants, and that sometimes even led to moments of public humiliation.
Discussion: Our findings shed light on some of the motivational factors that underpin the age-related digital divide, whilst also highlighting the role of self-directed agism in limiting motivations to learn new digital routines
Buffering against academic loneliness: The benefits of social media-based peer support during postgraduate study
Full text linkAlthough the support provided by social relationships may be essential to a successful student transition, the transition to postgraduate study has had little consideration from a social support perspective. The study described in this article investigated the role played by social support in postgraduate taught students’ adjustment to university, and how social media contributes to this support. Thematic analysis indicated that participants benefitted most from specialised support from peers dealing with similar academic challenges. Facebook Groups showed potential as a platform for building supportive peer networks. However, the heightened visibility of communications on this platform led some participants towards Facebook Messenger as a medium for peer contact. The study suggested that, in order to meet postgraduates’ needs, institutions could ensure postgraduate students have sufficient opportunity for collaboration within their cohorts. Additionally, while social media may aid this process, students’ individual communication preferences may inevitably influence their engagement with particular platforms
A Broken Profession both Mentally and Physically: Is Well-being the Foundation to a Healthy and Resilient Future?
No full textRecent years have seen an increasing body of literature surrounding well-being within the legal profession. The literature illustrates a profession with high levels of stress and mental health problems. The problem of poor mental health exists throughout the legal sector at all levels including students, junior lawyers, senior lawyers and the judiciary. There are numerous consequences of poor mental problems for individuals, universities, employers, the reputation of the profession and wider society. For individuals, the long-term impact on their mental and physical health; for employers, low productivity and increased sickness absence; and for the profession and wider society, unethical practice with adverse consequences for clients as lawyers struggle to cope.This article advocates for the integration of well-being into the law school curriculum. Whilst universities offer well-being services, these are usually an adjunct, distinct from the law programme. As a professional degree there has been an increased focus on skills training and ethics. Historically, well-being has not been a core component of any undergraduate law degree. The author will assert that an appreciation and understanding of well-being is as fundamental as skills and ethics within the context of a professional education. Well-being should be a core component and pervasive throughout the law school curriculum, to provide students with the tools and mechanisms to have a healthy and balanced student life that can form the basis of a healthy and balanced career
Skin Application of Menthol Enhances Maximal Isometric Lifting Performance
Full text linkOver, DM, Arjomandkhah, N, Beaumont, JD, Goodall, S, and Barwood, MJ. Skin application of menthol enhances maximal isometric lifting performance. J Strength Cond Res 37(3): 564–573, 2023—Topical application of menthol to the skin improves perception (i.e., makes subjects feel cooler) and changes submaximal neuromuscular recruitment facilitating force generation. We explored the effect of menthol (0.2% concentration; sprayed on the legs), on perception and maximal, dynamic (DLT) and isometric (IMLT) (weight) lifting tasks. Nine resistance-trained male subjects (mean ± SD: 24 ± 5 years; 75.7 ± 8.8 kg; 174 ± 10 cm; 5 repetition maximum deadlift [5RM] 132.3 ± 28.5 kg) were tested using a repeated measures design; we hypothesized that performance would improve. Before completing the DLT (i.e., deadlift performance 75% 1RM) and a midthigh pull dynamometer IMLT, subjects were sprayed with (∼125 ml) of menthol or control spray. Performance, electromyography (root mean squared [rmsEMG], rectus femoris [RF], biceps femoris [BF], and medial gastrocnemius [MG]), perceptions (leg thermal sensation [TSlegs] and comfort [TClegs] and perceived exertion [RPE] and readiness to train), heart rate, and skin temperature were measured. Data were compared using analysis of variance (effect size
) and t test to a 0.05 alpha level supported by Bayesian analysis. Dynamic lifting task performance was unchanged, although BF rmsEMG was higher (i.e., greater muscle activation in final [10th] repetition). Isometric lifting task force production was higher in the menthol spray (148 ± 30 kgf) condition (control spray 140 ± 30 kgf; p = 0.035,
= 0.444) with corresponding higher rmsEMG (BF 3.8 ± 1.46 vs. control spray 2.9 ± 0.34 V; p = 0.049,
= 0.403). TSlegs was lower after menthol spray before IMLT; subjects felt slightly cool. Menthol spray enhances isometric weightlifting performance with corresponding changes in neuromuscular activity, partially supporting our hypothesis
Predicting Sleeping Quality using Convolutional Neural Networks
Full text linkIdentifying sleep stages and patterns is an essential part of diagnosing and treating sleep disorders. With the advancement of smart technologies, sensor data related to sleeping patterns can be captured easily. In this paper, we propose a Convolution Neural Network (CNN) architecture that improves the classification performance. In particular, we benchmark the classification performance from different methods, including traditional machine learning methods such as Logistic Regression (LR), Decision Trees (DT), k-Nearest Neighbour (k-NN), Naive Bayes (NB) and Support Vector Machine (SVM), on 3 publicly available sleep datasets. The accuracy, sensitivity, specificity, precision, recall, and F-score are reported and will serve as a baseline to simulate the research in this direction in the future
The impact of entrepreneurial overconfidence on incubator effectiveness
Full text linkThe low utilization of incubator resources has been subject to much academic attention within entrepreneurship research. This study explores how entrepreneurs’ overconfidence impacts the utilization of incubator resources and influences incubation performance. Based on interviews with 8 incubators and questionnaires from 184 entrepreneurs, the findings show a negative relationship between entrepreneurs’ overconfidence and the incubation performance of start-ups. This finding emerges in the context of incubation management through the fully mediating role of entrepreneurial learning. As a moderator, the contract control of the incubator weakens the negative relationship between entrepreneurs’ overconfidence and entrepreneurial learning. The microcosm of the incubator context allows the researchers to examine the internal agent interaction. This paper explores the related literature, presents the research study, discusses the findings and provides avenues for future scholarly research on this topic
Modelling the interdependence of spatial scales in urban systems
Full text linkThe multitude of interwoven spatial scales and their relevance for urban systems has been of interest to the complexity science of cities since its conception. Today, we are well aware that urban environments are being simultaneously shaped and organised through actions at all levels. However, the fundamental question of how to reveal and quantify the interdependence of processes in between various spatial and temporal scales is less often addressed. Deepening our theoretical understanding of the multiscale spatiotemporal complexity of urban systems demands a transdisciplinary framework and the deployment of novel and advanced mathematical models. This article performs a multiscale analysis of urban structures using a large dataset of rent price values in the Ruhr area, Germany. We argue that, due to their many interacting degrees of freedom, urban systems exhibit similar features as other strongly correlated systems, for example, turbulent flows, notably the occurrence of extreme small-scale fluctuations. This analogy between urban and turbulent systems, which we support by empirical evidence, allows for the modelling of spatial structures on the basis of concepts and methods from turbulence theory. We demonstrate how by identifying the main turbulence-borrowed characteristics of an arbitrary two-dimensional urban field, it can be fully reproduced with a small number of prescribed points. Our findings have theoretical implications in the way we quantify and analyse scales in urban systems, model small-scale urban structures as well as potential policy relevance on understanding the evolution and spatial organisation of cities
Autistic Parents’ Personal Experiences of Parenting and Support: Messages from an Online Focus Group
Full text linkSocial work with autistic adults should be operated within principles of personalisation and strength-based approach. While many parents are diagnosed on the autistic spectrum as adults, their needs, different parenting styles and capabilities have been often misunderstood, or seldom respected by professionals. To address this gap, this study explored autistic parents’ experiences of parenting and support. In order to examine ‘real-life’ through the parent’s own points of view, an online focus group was used to explore seven autistic parents’ own perspectives and experiences. Data were analysed via thematic techniques. This study found that the parents claimed that autism may not impact always on their parenting capacity, and, when it does, they can succeed in raising their children, especially their autistic children, if they are provided with appropriate support services. But their parenting style and capabilities were misunderstood by professionals who used traditional pathologising assumptions on parental capacity. This study concluded that dismantling stereotypical norms of autism and lack of knowledge of autism within professionals is needed to change to properly assess autistic parent’s needs and their capacity using strength-based approach
ConvNet-based performers attention and supervised contrastive learning for activity recognition
Full text linkHuman activity recognition based on generated sensor data plays a major role in a large number of applications such as healthcare monitoring and surveillance system. Yet, accurately recognizing human activities is still challenging and active research due to people’s tendency to perform daily activities in a different and multitasking way. Existing approaches based on the recurrent setting for human activity recognition have some issues, such as the inability to process data parallelly, the requirement for more memory and high computational cost albeit they achieved reasonable results. Convolutional Neural Network processes data parallelly, but, it breaks the ordering of input data, which is significant to build an effective model for human activity recognition. To overcome these challenges, this study proposes causal convolution based on performers-attention and supervised contrastive learning to entirely forego recurrent architectures, efficiently maintain the ordering of human daily activities and focus more on important timesteps of the sensors’ data. Supervised contrastive learning is integrated to learn a discriminative representation of human activities and enhance predictive performance. The proposed network is extensively evaluated for human activities using multiple datasets including wearable sensor data and smart home environments data. The experiments on three wearable sensor datasets and five smart home public datasets of human activities reveal that our proposed network achieves better results and reduces the training time compared with the existing state-of-the-art methods and basic temporal models