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Multivariate versus univariate latent trajectory modelling:a comparison of class recovery performance and implications for multivariate model building strategies
No full textThe Group-based multi-trajectory model (GBMTM) extends the univariate Group-based trajectory model (GBTM) to analyse multivariate longitudinal data by identifying subgroups with similar developmental patterns across multiple outcomes. This method has gained popularity for exploring complex phenomena from developmental and relational perspectives across various empirical fields. Despite its utility, comparing GBMTM with preliminary GBTM analyses poses challenges due to potential discrepancies in trajectory characteristics such as numbers, sizes, levels, and shapes across outcomes. These differences suggest a complex data-generative process not fully understood. Our study aims to bridge this knowledge gap by examining how longitudinal data features impact class enumeration and parameter recovery in GBMTM and GBTM through extensive simulations. We highlight the influence of several factors on multivariate clustering, notably outcomes' class separation and the strength of univariate class correspondence. By addressing analytical and interpretational challenges, our findings offer practical guidelines for GBMTM, illustrated with real-world data examples
Faecal incontinence core outcome set:an international Delphi consensus exercise among patients, health-care professionals, and researchers
No full textFaecal incontinence is a debilitating anorectal disorder that can severely affect a person's quality of life. The variability in reported outcomes in studies on treatments for faecal incontinence complicates the synthesis of evidence, thereby weakening treatment recommendations. Furthermore, the emphasis on clinical outcomes often neglects outcomes that are crucial to patients' daily lives. Incorporating diverse stakeholder perspectives, we aimed to develop a core outcome set (COS)—a minimum set of outcomes that should be measured in future studies evaluating the efficacy of a treatment in adults with faecal incontinence. Following guidelines from the COMET initiative, this study proceeded through three steps: identifying outcomes via patient interviews and a systematic literature review; ranking and refining outcomes through two rounds of Delphi surveys involving patients, health-care professionals, and researchers; and finalising the COS through a consensus meeting with relevant stakeholders. Round 1 of the Delphi survey included 109 participants (73 health-care professionals and researchers and 36 patients) and round 2 involved 74 participants (54 and 20, respectively). In both rounds, participants ranked the importance of potential outcomes on a 9-point Likert scale. Of the 58 outcomes that entered round 1 and the three that were later added, 27 outcomes were voted out and the remaining 34 were discussed during a consensus meeting to finalise the COS. The final COS encompasses 13 outcomes: seven quality of life-related outcomes (quality of life, influence on daily activities, social functioning, treatment satisfaction, enjoyment in life, embarrassment, and peace of mind) and six clinical outcomes (severity of faecal incontinence, number of faecal incontinence episodes, urgency, stool consistency, adverse events, and adherence to therapy). This study establishes what outcomes should be included in a COS for use in faecal incontinence research, but future research is needed to identify the appropriate measurement instruments for each outcome and to establish appropriate timing for their assessment, which will further refine outcome definitions before this COS can be implemented. Once these aspects are clarified, the COS can be adopted into faecal incontinence research, which we hope will ultimately improve clinical care
The impact of sugar-sweetened beverages tax policy on cases of diabetes, depression, heart attacks, hypertension, and stroke in the 35 years and 40 years cohorts of South Africa
No full textIn 2018, South Africa became the first African country to implement a sugar-sweetened beverages (SSB) tax policy. This study evaluates its impact on diabetes, depression, heart attacks, hypertension, and stroke among South Africans aged 35 and 40. Data from 2016 to 2017 (control group) and 2018-2021 (treatment group) were analysed using an Instrumental Variables (IV) estimation model. Results indicate a 16% reduction in diabetes and 23% reduction in depression for the 35-year cohort, while the 40-year cohort saw 6% and 16% decreases, respectively. Heart attacks dropped by 36% and 12%, hypertension by 30% and 10%, and strokes by 16% and 6% in the respective cohorts. The effects were more significant in men and in the younger 35-year cohort, particularly among Black African and Mixed-Race groups, and people from low socio-economic backgrounds. Overall, the policy effectively reduces these health issues, suggesting that higher tax rates could enhance brain health outcomes
Multivariate versus univariate latent trajectory modelling:a comparison of class recovery performance and implications for multivariate model building strategies
No full textThe Group-based multi-trajectory model (GBMTM) extends the univariate Group-based trajectory model (GBTM) to analyse multivariate longitudinal data by identifying subgroups with similar developmental patterns across multiple outcomes. This method has gained popularity for exploring complex phenomena from developmental and relational perspectives across various empirical fields. Despite its utility, comparing GBMTM with preliminary GBTM analyses poses challenges due to potential discrepancies in trajectory characteristics such as numbers, sizes, levels, and shapes across outcomes. These differences suggest a complex data-generative process not fully understood. Our study aims to bridge this knowledge gap by examining how longitudinal data features impact class enumeration and parameter recovery in GBMTM and GBTM through extensive simulations. We highlight the influence of several factors on multivariate clustering, notably outcomes' class separation and the strength of univariate class correspondence. By addressing analytical and interpretational challenges, our findings offer practical guidelines for GBMTM, illustrated with real-world data examples
3D bioprinting in tissue engineering:current state-of-the-art and challenges towards system standardization and clinical translation
No full textOver the past decade, three-dimensional (3D) bioprinting has made significant progress, transforming into a key innovation in tissue engineering. Despite the early strides, critical challenges remain in 3D bioprinting that must be addressed to accelerate clinical translation. In particular, there is still a long way to go before functionally-mature, clinically-relevant tissue equivalents are developed. Current limitations range from the sub-optimal bioink properties and degree of biomimicry of bioprintable architectures, to the lack of stem/progenitor cells for massive cell expansion, and fundamental knowledge regarding in vitro culturing conditions. In addition to these problems, the absence of guidelines and well-regulated international standards is creating uncertainty among the biofabrication community stakeholders regarding the reliable and scalable production processes. This review aims at exploring the latest developments in 3D bioprinting approaches, including various additive manufacturing techniques and their applications. A thorough discussion of common bioprinting techniques and recent progresses are compiled along with notable recent studies. Later we discuss the current challenges in clinical application of 3D bioprinting and the major bottlenecks in the commercialization of 3D bioprinted tissue equivalents, including the longevity of bioprinted organs, meeting biomechanical requirements, and the often underrated ethical and legal aspects. Amidst the progress of regulatory efforts for regenerative medicine, we also present an overview of the current regulatory concerns which should be taken into account to translate bioprinted tissues into clinical practice. At last, this review emphasizes future directions in 3D bioprinting that includes the transformative ideas such as bioprinting in microgravity and the integration of artificial intelligence. The study concludes with a discussion on the need for collaborative efforts in resolving the technical and regulatory constraints to improve the quality, reliability, and reproducibility of bioprinted tissue equivalents to ultimately accomplish their successful clinical implementation.</p
Can we share data? - Kinematic consistency during walking in three different treadmill-based laboratories
No full textBACKGROUND: Three-dimensional gait analysis is crucial for diagnosis and treatment planning. Treadmill-based laboratories efficiently collect 3D gait data over many consecutive steps. Pooling/sharing data across treadmill-based laboratories could enhance clinical utility. However, the inter-laboratory consistency of gait kinematics from treadmill-based systems is unknown. RESEARCH QUESTION: How consistent are lower-limb kinematics of healthy subjects measured in three different treadmill-based gait laboratories? METHODS: Eighteen volunteers (14 women; 27 ± 9 years; BMI 24 ± 3 kg/m ) walked in three treadmill-based laboratories (Motek Medical, The Netherlands) within one week. Per laboratory, participants completed 3-minute walking trials (0.9, 1.1, 1.3 m/s) wearing a non-weight-bearing harness and identical clothes and shoes. The same marker-set (Human-Body Model 2) and virtual reality configurations were used. Statistical Parametric Mapping was used to compare time-normalized kinematic curves of the lower-limb, averaged over 40 steps, between laboratories. Root mean square differences (RMSD) calculated over periods of the gait cycle with statistically significant differences were considered clinically meaningful when > 5°. RESULTS AND SIGNIFICANCE: Kinematics curves from all laboratories followed similar patterns. Only 17 % of all curves displayed clinically relevant differences. These differences included more knee flexion in laboratory 2 compared to the others (RMSD 6.0-8.6°) and less hip flexion in laboratory 3 compared to laboratory 2 (all speeds) and to laboratory 1 (1.3 m/s; RMSD 5.4-6.4°). Reported differences are likely due to varying operator protocols rather than to the measurement system. The findings indicate that inter-laboratory data sharing using such infrastructure is possible but training to align protocols is essential
AI in Early and Primary Education:Societal, Classroom, and Teacher Perspectives on Ethical and Pedagogical Integration
No full textThe integration of artificial intelligence (AI) in education (AIEd) comes along with both opportunities and challenges, particularly in ensuring its alignment with pedagogical principles and the teachers’ needs. This chapter explores the role of AIEd from the perspective of particular teacher needs, classroom dynamics, and broader societal implications. Employing the digital divide theory, we reflect upon the potential inequalities of AI and its impact in education. Furthermore, we discuss the findings of our systematic literature review on the current use of AIEd with particular emphasis on pre-school and primary education. Our results indicated that while AIEd applications in pre-school and primary education promise efficiencies in personalized learning and administrative tasks, their development and implementation often overlook critical pedagogical considerations and teacher guidance. Last, the chapter argues that teachers play an essential role in bridging the gap between technology and effective teaching, ensuring that the AIEd applications will not just be technologically advanced but also aligned with the learning goals and course design needs. Collaboration between different stakeholders (researchers, teachers, developers) is essential to create AI tools that are user-friendly, ethically sound, and tailored to meet diverse student needs
Private vs. Public Schooling:The role of school composition
No full textPublicly funded private schooling is a common feature of many education systems, yet its implications for educational equity and effectiveness remain contested. While private schools often exhibit higher student achievement, the sources of this advantage are not well understood. In particular, differences in student composition-especially in terms of socioeconomic status (SES)-are likely to play a key role. This paper examines how school-level SES composition contributes to achievement differences between public and private schools. Using propensity score matching (PSM) on data from 22,441 French ninth-grade students, we find that private school students outperform their public school peers in mathematics and French, with especially large effects for low-SES students, an underrepresented group in private schools. While school composition explains only part of these effects, it accounts for a substantial share of the performance gap among high-SES students, rendering the adjusted effect statistically indistinguishable from zero. These findings highlight which students benefit most from private schooling and point to the need for further research into the mechanisms underlying performance differences across school sectors