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‘Do existential touchstones really cool?’ An exploration of therapists’ experiencing of significant personal loss and how this informs their ‘way of being’ with a client
Get PDFThis paper reports on a study that explored how person-centered therapists affected by significant personal losses experience existential touchstones, and how these experiences inform their way of being with clients. Using a heuristic inquiry approach, alongside my own heuristic journey, semi-structured interviews were conducted with three person-centered therapists and analyzed thematically. The findings both support and challenge the limited existing literature on therapist grief, suggesting that grief is a unique and identity-shaping experience that can also foster personal growth. Lived loss reshapes therapists’ subjective experiencing within therapeutic encounters. Participants described how their own experiences of loss, when supported by grief education and supervision, deepened their empathy, strengthened relational connections, and enhanced their therapeutic practice. The study highlights how personal grief, when acknowledged and integrated, can become a transformative resource in therapy, underscoring the value of experiential understanding in the development of therapeutic presence and practice
Teaching an outdated framework:navigating the Mental Health Act 1983 in nurse education
Get PDFThe Mental Health Act 1983 remains a cornerstone of mental health legislation in England and Wales; however, its outdated, paternalistic framework presents ethical challenges for nurse educators. This article explores the tensions inherent in teaching a law that is essential to practice yet widely recognised as inadequate. The authors examine the Mental Health Act’s limitations, including its failure to promote autonomy, safeguard against coercion and address racial disparities. Key omissions such as lack of statutory advocacy, absence of advance decision making, and insufficient protections for children are critically analysed. The authors argue that nurse educators must go beyond statutory instruction to foster ethical awareness, cultural sensitivity and advocacy skills in students. By embedding critical reflection and person-centred values into education, academics can prepare nurses to uphold human rights and challenge discriminatory practices, even within a flawed legal framework. Reforming the law is essential but until then, education must bridge the gap between law and ethical care
Exploring the validity of smartphone based single camera markerless motion capture technology to quantify knee range of motion in patients with knee osteoarthritis
Get PDFBackground: Single camera markerless motion capture technology offers a potential means of assessing joint function in patients with musculoskeletal disorders/diseases. The aim of this study was to determine the validity and within-session reliability of sagittal plane knee joint kinematics quantified using the Deep Vision platform in patients with knee osteoarthritis. Methods: Sagittal plane knee joint kinematics were quantified using a 3D motion capture system, the msk.ai Deep Vision platform and Kinovea in fifteen patients with knee osteoarthritis. Bland Altman plots with 95 % limits of agreement were used to assess validity and within-session reliability, with mean differences and limits of agreement explored relative to ± 5° and 10° clinically meaningful thresholds, respectively. This is based on the assumption that changes in joint angles greater than 5° are clinically meaningful. Results: Mean differences and 95 % limits of agreement were within the clinically meaningful thresholds when using the Deep Vision platform to quantify peak knee flexion and extension, and range of motion. Mean differences were within the clinically meaningful threshold for Kinovea based assessments, but 95 % limits of agreement exceeded the ± 10° clinically meaningful threshold for peak flexion and range of motion. All assessment methods displayed mean differences and 95 % confidence intervals within the clinically meaningful thresholds on average when comparing across repetitions to quantify within-session reliability. Conclusion: The findings of the study demonstrate that the msk.ai Deep Vision platform provides a valid and reliable means of quantifying peak knee flexion, extension and range of motion. Contribution of the Paper: • The Deep Vision platform, a smartphone based markerless motion capture technology, provides a valid means of measuring knee range of motion. • The Deep Vision platform displays high reliability when measuring knee range of motion.</p
Changes in Sprinting and Landing Mechanics Across 120 minutes of Soccer-specific Exercise
No full textField, A, Fischer, A, Read, DB, Sanderson, A, Graham-Smith, P, Birdsey, L, Harper, L, Bramah, C, Page, RM, and Dos’Santos, T. Changes in sprinting and landing mechanics across 120 minutes of soccer-specific exercise. J Strength Cond Res XX(X): 000–000, 2025—The aim of this study was to examine the influence of 120 minutes of simulated soccer match play on sprinting and landing mechanics. Twelve semiprofessional soccer players completed bilateral vertical drop jumps, countermovement jumps, and 30-m sprints at prematch, half-time, full-time, and post–extra time. Two-dimensional frontal plane footage was captured during jumps, and the frontal plane projection angle upon landing was measured. Sprint-running mechanics were assessed using a novel qualitative screening tool. Drop-jump height reduced 12.5% from prematch (0.32 ± 0.02 m) to extra time (0.28 ± 0.02 m, p = 0.002, d = 0.2), 11.1% from full-time to prematch (0.27 ± 0.02 m; p = 0.013, d = 2.2), and 6.3% from full-time to half-time (0.30 ± 0.02 m; p = 0.001, d = 3.0). Average landing force decreased 4.5% at extra time (1,022.7 ± 38.3 N) vs. prematch (1,068.7 ± 38.5 N; p = 0.003, d = 1.2), 5.5% at half-time (1,078.7 ± 38.3; p = 0.001, d = 0.8), and 3.8% at full-time (1,039.5 ± 38.3) vs. half-time ( p = 0.015, d = 0.3). Time to stabilization increased 14.3% at extra time (663 ± 34 ms) from 568 ± 34 ms at prematch ( p = 0.009, d = 0.3), 13.7% at half-time (572 ± 34 ms; p = 0.004, d = 0.1), and 9.1% at full-time (663 ± 34; p = 0.011, d = 0.2). Relative peak landing force was 6.9% higher at full-time (692.00 ± 44.44%) vs. half-time (644.79 ± 44.44%; p = 0.009, d = 0.4), but 6.2% lower at half-time vs. prematch (684.50 ± 44.28% ; p = 0.022, d = 0.6). Sprint mechanics movement quality deteriorated by 29.5% at half-time (2.75 ± 0.26) compared with prematch (1.95 ± 0.27; p = 0.016, d = 0.5), and by 33.4% from prematch to extra time (2.93 ± 0.27; p = 0.013, d = 0.6). Players may experience impaired neuromuscular performance, particularly during landing and sprinting, which may influence movement quality and could contribute to increased injury susceptibility, although this requires further investigation
From Statistical Analysis to Deep Learning
No full textThis chapter explores the shift from traditional statistical analysis to advanced deep learning in quantitative decision-making. It argues for integrating classical paradigms—such as descriptive and inferential statistics conducted in tools like SPSS—with modern computational techniques to address complex, large-scale challenges. The discussion highlights the pivotal role of big data platforms, including Hadoop and Spark, in enabling real-time analytics and distinguishes core machine learning algorithms from deep neural architectures designed for unstructured data. Interdisciplinary case studies in healthcare, finance, and engineering demonstrate the practical synergy of these approaches. By embracing multi-paradigm strategies, the chapter offers insights into building transparent, scalable, and effective decision-support systems across diverse domains. It concludes by addressing challenges of ethics and governance and by pointing to future directions such as explainable AI and federated learning, emphasising that robust decision-making depends on a hybridised analytical framework
Hybrid Inception-ViT Networks for Fine-Grained Single-Cell Image Classification
No full textAccurate Single-cell (SC) image classification is critical for characterizing cellular heterogeneity and supporting disease diagnostics. Conventional convolutional models often struggle due to limited data, subtle morphological differences between cell types, and class imbalance. In this work, we propose a Hybrid Inception Vision Transformer (HiViT) that combines Inception convolutional feature extraction with transformer-based attention mechanism to capture bothfine-grained texture and long-range structural context. Our framework incorporates adaptive uncertainty-aware learning via Monte Carlo dropout and data balancing through augmentation. We evaluate HiViT on the White BloodCell (WBC) classification Berkeley SC Computational Microscopy (BSCCM) dataset, covering Lymphocyte, Granulocyte, and Monocyte classes. The model achieves overall superior performance compared to classical machine learningand deep learning baselines, with class-wise recalls of 90.31% (Lymphocyte), 97.97% (Granulocyte), and 81.21% (Monocyte). Experiments highlight the effectiveness of hybrid CNN–ViT architectures for robust and uncertainty-awareSC classification, providing a foundation for extending to other biomedical image-driven analysis and diagnostic tasks
Randomised Controlled Trial of Online Behavioural Sleep Intervention for Children with Epilepsy
No full textWe evaluated the clinical and cost effectiveness of an online sleep intervention (COSI) for parents of children with epilepsy. We conducted a multicentre, parallel-group, unblinded, randomised controlled trial. We recruited children aged 4–12 years with epilepsy and sleep problems through 26 UK outpatient clinics. Participants were randomly assigned (1:1) via a computer-generated minimisation algorithm. The primary outcome was the Children’s Sleep Habits Questionnaire (CSHQ) at three months. Cost-effectiveness was estimated at six months. We conducted intention to treat analyses. 85 children were enrolled (42 SC; 43 SC+COSI). At three months, the adjusted mean CSHQ difference between arms was 3.00 (95% CI 0.06–5.93; p=0.05), indicating significant superiority of SC. Children in the SC+COSI group showed a mean 16.5-minute reduction in sleep onset latency and parents increased their knowledge. Only 23 (53%) families accessed the core materials. Incremental mean cost of SC+COSI was £1,232 (95% credibility interval £535–£3,455) with a mean incremental Quality Adjusted Life Year (QALY) of 0.00 (95% CI -0.03 to 0.04), yielding an incremental cost-effectiveness ratio of £433,167 per QALY gained a (0.04 probability of being cost-effective at the £30,000/QALY threshold). Improved objective sleep onset latency and enhanced parental knowledge suggest that the underlying behaviour change techniques hold value
"Currently Listening to…"::Curating Artist Playlists and Authenticity on Spotify
No full textThis article examines music curation and authenticity through Artist Playlists on Spotify. It charts the ways that English-speaking popular music artists based in Europe and the United States curate music through three types of Artist Playlists—Catalog Artist Playlists (CAPs), Catalog Plus Artist Playlists (CPAPs), and Non-Catalog Artist Playlists (NCAPs)—before considering how the labor and knowledge on show in this curation shapes spaces on Spotify in which to consider and assess the artists’ authenticity of expression, experience, and execution
Sense of belonging: A complementary lens to the ‘labour upon labour’ framework for underrepresented medical student experiences
No full textDevelopment and reporting of a specialised antenatal music therapy intervention using the MRC framework and TIDieR checklist
Get PDFIntroduction: Perinatal mental health can significantly impact parental and infant wellbeing. Music interventions have shown promise in improving perinatal wellbeing during pregnancy. However, research in this area remains scarce, and very few structured music therapy programmes have been developed and reported in sufficient detail to enable replication and implementation in clinical settings. This article aims to describe the development process of a novel Specialised Antenatal Music Therapy (SAMT) intervention and provide a detailed report of this using the Template for Intervention Description and Replication (TIDieR) 12-point checklist. Methods: Guided by the Medical Research Council (MRC) framework for developing complex interventions, SAMT was developed through a systematic, evidence-based, theory-driven, and stakeholder-informed process. This included: (1) assembling a multidisciplinary expert team, (2) reviewing existing research evidence and antenatal music therapy protocols, (3) understanding the context and engaging stakeholders through research and co-creation, (4) drawing on existing theories and techniques to facilitate treatment outcomes, and (5) evaluating the feasibility and efficacy through a proof-of-concept study. Results: This systematic approach resulted in the development of SAMT - a novel music therapy programme for pregnant women attending a Specialist Perinatal Mental Health Service (SPMHS) in Ireland. SAMT consists of six weekly individual music therapy sessions, each lasting 45–60 minutes, delivered either online or in-person at the SPMHS outpatient clinic in a central location. Key components include music-assisted relaxation, identifying a bonding song, musical bonding, song discussion, songwriting, creating pregnancy/birth playlists, and creative music making. Early feasibility testing indicated that the intervention was acceptable and well received by participants. Discussion/conclusion: Using the TIDieR checklist to report complex interventions provides a structured, systematic way of conveying necessary detail. This method enables music therapists, clinicians, and researchers to understand the SAMT’s underlying rationale, theoretical foundation, delivery methods, and implementation considerations, facilitating replication, refinement, and integration into perinatal mental health services and research. <p class="MsoNoSpacing"/