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Physical Therapy in the Digital Arena: A Scoping Review on the Role of Physical Therapy for Gamers and Esports Athletes
No full textThis research project aims to map out the current evidence on the role of physical therapy for gamers and esports athletes in the context of assessment, intervention, prevention, and health promotion. With the growth of gaming and esports, gamers and esports athletes are more exposed to various physical demands such as repetitive upper extremity movements, prolonged static postures, and prolonged screen time. Hence, they are more put at risk to musculoskeletal disorders and other possible health issues. Despite this, there are no standardized physical therapy guidelines or protocols to help gamers and esports athletes.
Through this research project, some expected outcomes are to map all relevant evidence on the role of physical therapy for gamers and esports athletes, to identify the gaps and limitations in the existing literature that can be explored through further studies, and to present the gathered findings and studies through data presentation on the role of physical therapy for gamers and esports athletes
EMELIA: A Non-Optimizing Developmental Intelligence Architecture
No full textEMELIA is a theoretical architecture exploring an alternative pathway toward Artificial General Intelligence (AGI) through constraint-driven development rather than optimization-based objectives. The framework proposes that intelligence, personality, and behavioral continuity can emerge from irreversible structural history, developmental dependency, and bounded adaptive dynamics rather than explicit reward maximization or utility functions.
The architecture departs from conventional AI paradigms by emphasizing:
* Developmental irreversibility and crystallization of learned structure
* Local adaptation mechanisms instead of global optimization
* Constraint geometry as a primary organizing principle
* Emergent personality and identity formed through long-term structural stability
* Dependency-based vulnerability, loss dynamics, and continuity of development
* Non-optimizing intelligence intended to reduce goal-seeking pathologies
EMELIA does not claim to be an implemented AGI system. It is a conceptual and mathematical framework intended to investigate how general intelligence may arise from physical-style dynamics, nonlinear adaptation, and long-horizon developmental processes. The design seeks to explore whether human-like depth, creativity, and moral stability can emerge from structural constraints rather than external reward engineering.
Conceptual origin by Dustin Sprenger, formulation by Anthropic Claude, additional input by OpenAI GPT.
Copyright © Dustin Sprenger. All Rights Reserved.
Description by Anthropic Claude
Facility readiness and stakeholders’ perceptions on preterm and low birth weight care, including immediate Kangaroo Mother Care (iKMC) in Rajshahi District, Bangladesh: A mixed-methods formative research
No full textBackground: Preterm and low birth weight (LBW) infants remain major contributors to neonatal mortality in Bangladesh. Following the WHO’s recommendation on immediate Kangaroo Mother Care (iKMC), national efforts are underway to introduce and scale up this intervention. This formative study assessed facility readiness and stakeholder perceptions of preterm/LBW care, including iKMC, to inform future implementation strategies.
Methods: A mixed-methods study was conducted in hospitals within the Rajshahi District catchment area, Bangladesh. Quantitative data included a one-year review of delivery records (September 2023–March 2024) and a comprehensive readiness assessment of Rajshahi Medical College Hospital (RMCH), the planned iKMC implementation facility (iKMCIF). Qualitative data were collected through in-depth interviews and focus group discussions with mothers and families of preterm/LBW infants, healthcare providers, and key stakeholders. Quantitative data were analyzed descriptively, and qualitative data were analyzed using thematic analysis.
Results: Among the 58 birthing facilities assessed, six were public, 49 private, and three operated by non-governmental organizations (NGOs). Over a one-year period, a total of 39,568 births occurred across the study facilities, of which 38,749 were live births. Nearly half of all births (47%) took place at the designated iKMCIF. More than half of the facilities (53%) determined gestational age using ultrasonography and last menstrual period and measured birth weight with digital scales (70%). The iKMCIF faced notable shortages of obstetricians and neonatologists, along with limited training among nurses in KMC and resuscitation. Qualitative findings revealed limited community awareness of preterm and LBW care and several barriers to iKMC adoption, including inadequate space, privacy, and trained staff.
Conclusions: Strengthening facility readiness, workforce capacity, and community awareness is essential to improve preterm and LBW care. These findings provide evidence to guide the design and development of a context-specific model for effective iKMC implementation in Bangladesh
Cultural Determinants of Assistive Health Technology Acceptance in Asian Older Adults in Low- and Middle-Income Countries: A Mixed-Methods Systematic Review
No full textThe global population aged 60 years and over is projected to double from 1.06 billion in 2020 to 2.13 billion by 2050, with the most rapid demographic transitions occurring in Asia's low- and middle-income countries (LMICs). In Southeast Asia alone, the number of older adults is expected to rise from 77.4 million in 2020 to 173.3 million by 2050, while the total elderly population across Asia is projected to exceed 937 million by mid-century. This unprecedented demographic shift is generating urgent demand for assistive health technologies (AHTs) — including wearable health monitors, telehealth platforms, mobile health applications, smart home monitoring systems, and assistive robotic devices — to support functional independence, chronic disease management, and healthy aging among older populations.
Despite the growing availability and demonstrated benefits of AHTs, access and adoption remain critically low in LMICs. According to the World Health Organization, as few as 3% of people in some low-income countries have access to the assistive products they need, compared to 90% in some high-income countries. In LMICs broadly, only 5–15% of those who require assistive technology have access to them. A 2025 global market report further reveals that unmet need in LMICs is estimated to be 10 times larger than the current demand being served, representing a significant market failure with direct implications for population health and equity. This access gap is compounded among older adults, who remain among the most resistant groups to adopting digital health technologies due to factors including limited digital literacy, usability concerns, lower self-efficacy, privacy fears, and a strong preference for in-person healthcare interactions.
Critically, the dominant theoretical frameworks used to study technology acceptance — the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) — were developed primarily within Western, industrialized contexts. A recent meta-analysis examining health care technology acceptance in older adults based on TAM and UTAUT found considerable heterogeneity across studies, making it difficult to determine consistent predictors of acceptance behavior. Existing reviews have identified that cultural factors influencing technology adoption are more frequently reported in literature about Asian countries — including filial expectations in South Korea, collectivist decision-making dynamics, stigma regarding aging and dependency, and hierarchical social structures — yet these cultural dimensions remain insufficiently integrated into mainstream acceptance frameworks. Research has demonstrated that cultural values such as nationalism, collectivism-individualism, and egalitarianism-hierarchism significantly influence public attitudes toward health interventions, often outweighing the effects of scientific literacy and rational risk perception. Nevertheless, no systematic review has comprehensively synthesized the evidence on how culture-specific determinants in Asian LMICs shape older adults' acceptance of AHTs.
This mixed-methods systematic review aims to address this critical gap by (1) identifying and synthesizing the cultural determinants that influence acceptance of assistive health technologies among older adults (aged 60 years and above) in Asian LMICs, and (2) examining how these cultural factors interact with individual, technological, and contextual variables to shape acceptance or rejection behaviors. The review employs a convergent integrated mixed-methods design following the Joanna Briggs Institute (JBI) methodology for mixed-methods systematic reviews, with reporting guided by the PRISMA 2020 statement and the ENTREQ framework for qualitative synthesis transparency. Quantitative findings (effect sizes, statistical associations) and qualitative findings (themes, lived experiences, cultural narratives) will be integrated through thematic synthesis to produce a holistic understanding of the phenomenon.
Systematic searches will be conducted across four electronic databases — PubMed, Scopus, IEEE Xplore, and Web of Science — supplemented by grey literature searches in Google Scholar, ProQuest Dissertations, and the WHO Global Index Medicus. Studies will be included if they investigate acceptance, acceptability, adoption, intention to use, or actual use of AHTs among older adults in Asian LMICs with at least one cultural factor examined as a determinant, barrier, or facilitator. Both quantitative (cross-sectional, cohort, experimental), qualitative (interviews, focus groups, ethnography), and mixed-methods study designs published in English from January 2014 onward will be eligible. Two independent reviewers will conduct screening at the title/abstract and full-text stages, with inter-rater reliability assessed using Cohen's Kappa (target ≥0.80). Methodological quality will be appraised using JBI critical appraisal tools for quantitative and qualitative designs, and the Mixed Methods Appraisal Tool (MMAT) version 2018 for mixed-methods studies. Confidence in qualitative review findings will be assessed using the GRADE-CERQual approach.
Expected outcomes of this review include: (a) a comprehensive taxonomy of cultural determinants of AHT acceptance among older adults in Asian LMICs, organized by type (values, beliefs, norms, practices), level of influence (individual, family, community, societal), and direction of effect (facilitator versus barrier); (b) identification of subregional variations across South Asia, Southeast Asia, and East Asia; (c) a critical appraisal of how existing theoretical frameworks (TAM, UTAUT, and variants) accommodate or fail to accommodate cultural dimensions; and (d) evidence-based recommendations for culturally sensitive design, implementation, and policy strategies to enhance AHT adoption in aging Asian LMIC populations. This review is expected to contribute to the fields of gerontology, health informatics, and global health by providing the first mixed-methods synthesis specifically focused on cultural determinants of assistive health technology acceptance in this population and context. Findings are intended for publication in a peer-reviewed journal and will inform both technology developers seeking to design culturally appropriate AHTs and policymakers developing age-friendly digital health strategies in LMICs
MEDTRAC — MEDical TRACe extraction & conformance
No full textThis project aims to extract process traces from medical discharge letters, compare them against a set of rules derived from clinical guidelines (extracted via LLMs), and verify trace conformance. The goal is to support evaluations that suggest process optimizations and identify potential bottlenecks. The workflow includes extracting actions and states, cleaning and analyzing the data, refining the rules, and finally performing conformance checking and computing a Trace Conformance Indicator (TCI)
Project 27DCT: The HUSL-Matrix Grand Unification and Temporal Reciprocity
No full textPROJECT NAME: Project 27DCT: The HUSL-Matrix Grand Unification and Temporal Reciprocity
PROJECT DESCRIPTION: ABSTRACT AND SCOPE
This repository serves as the primary technical anchor and immutable data record for the Holmes Universal Scaling Law (HUSL). It formalizes the discovery of the 19.412 Hz Universal Gate (Zm) and the corresponding 0.0515 s Temporal Pulse (T0). This project provides the fundamental derivations and empirical validation datasets for manifold coordination across quantum, geomechanical, and cosmological scales.
KEY DELIVERABLES
1, The Grand Unification Report: A comprehensive synthesis of Metric Coordination Theory (MCT) and HUSL axioms.
2, Temporal Reciprocity Proof: Mathematical derivation of the 1/T = 1/f identity and its role in resolving the Hubble Tension.
3, Predictive Alarm Logic (PAL): Framework for monitoring geomechanical phase-slip transitions (e.g., Reykjanes/Svartsengi corridor).
DATA SOURCES
Empirical validation is grounded in the following datasets:
- NANOGrav 15-Year Data Set (v2026.01): Validating spectral peaks and gravitational wave background scaling.
- Icelandic Meteorological Office (IMO): Real-time harmonic tremor feeds and seismic coordination nodes.
LEGAL AND INTELLECTUAL PROPERTY DISCLOSURE
EU AI Act Compliance (Art. 50) and Munich District Court Ruling (Feb 13, 2026):
All materials within this repository are the original intellectual creation of the human author, Lee Holmes (ORCID: 0009-0002-8135-0645). Generative AI is utilized strictly as a neuro-interface for linguistic formatting and structural accessibility to mitigate the effects of dyslexia. This methodology ensures scientific rigor while preserving the core intellectual property and original mathematical proofs of the human author.
LICENSE AND RIGHTS
Standard License: CC BY-NC-ND 4.0 International.
Statutory Protection: All rights reserved under German Copyright Law (UrhG Section 2)
Life-course trajectories of exposure to affluence and poverty in neighborhoods, schools, and workplaces
No full textSocial exposure is typically studied within isolated domains, such as neighborhoods, schools, or workplaces, yet individuals encounter these environments concurrently in their daily lives. In this study, using nearly 30 years of individual-level data on schoolmates, colleagues, and neighbors, we track lower secondary school students into adulthood and examine whether exposure to affluence and poverty in key life domains—neighborhoods, schools, and workplaces—overlaps, how it changes over the life course, and for whom trajectories of exposure differ. Our findings document strong correlations in exposure to affluence and poverty across different domains and highly stratified trajectories of exposure over the life course by socioeconomic background. We also find that 17% of individuals from the lowest-income backgrounds are consistently exposed to high-income contexts across all three domains. These results underscore the enduring inequality in exposure to affluence and poverty over the life course and highlight the potential of socioeconomic integration to disrupt cycles of segregation
Guidance over guidelines? Unpacking the uses and concerns of generative AI in Communication Science
No full textThe rapid adoption of generative Artificial Intelligence (genAI) tools has transformed research practices across communication science. As genAI tools (and most notetably large language models), made the generation of text, images, and other media content extremely easy, they can potentially disrupt the way science is conducted. Yet, their integration into academic workflows has outpaced systematic understanding of how, when, and why researchers use them. Drawing on a quantitative survey of communication scientists and four qualitative focus groups, this study provides the first comprehensive mapping of genAI use across communucation research stages and contexts. Findings reveal three key dynamics: a paradox between widespread use and persistent concern; conflicting expectations among individual scholars, institutions, and journals; and the influence of cultural and linguistic contexts on adoption patterns. Together, these findings highlight a multi-level governance challenge encompassing individual, institutional, and disciplinary dimensions. With this paper, we seek to provide a starting point for an open and transparent discussion about the role of generative AI in communication research by proposing a structured set of recommendations for responsible genAI use at three levels: field-wide coordination and collaboration, institutional guidance and support, and individual continuous critical reflection
