Understanding adolescents’ diet and eating behaviours is crucial for informing public health strategies and policies, allowing interventions to be tailored effectively to enhance dietary patterns and improve overall health and quality of life. This study examined dietary patterns, dietary diversity, eating habits, food choice and the factors influencing these among adolescent girls in the Mion District, Ghana. A convergent parallel mixed-method design employing in-depth interviews (n = 30), two focus group discussions (n = 10) and survey data from 882 mother-daughter pairs was used. Key findings indicate that approximately 90% of girls achieved the minimum dietary diversity for women of reproductive age (MDD-W), with most consuming three meals daily. Staples were eaten daily, while fruits and unhealthy foods were less frequently eaten. Moderate/severe food insecurity was negatively associated with the MDD-W, whereas larger household size was positively correlated with the MDD-W. Older girls were less likely to eat breakfast, while household crop farm diversity increased the odds of eating supper on weekends. Moderate/severe food insecurity was inversely associated with intake of animal-sourced foods (ASFs), fruit, and unhealthy foods but positively correlated with vegetable consumption in the past month. Maternal non-literacy was linked to a lower intake of unhealthy foods, while specific ethnic backgrounds negatively influenced ASF intake. Wealthier households demonstrated higher consumption of staples. Qualitatively, health considerations, availability, taste, and cravings were major influencers of food choices. Food aversions were often tied to intolerance, fatigue from consuming the same foods repeatedly, and preferences related to taste and texture. These findings underscore the need for targeted nutritional interventions considering socio-economic and household factors to improve adolescent girls’ dietary habits and overall health.

Latent class models in the social and behavioral sciences have remained structurally simple. One reason for this is that inference in statistical models can be computationally difficult. Methods for approximate inference, known as variational approximations, which have been developed in the machine learning, graphical modeling and statistical physics literatures, can be used to alleviate the computational difficulties of inference for latent variable models. The aim of the present article is to set these methods alongside some social and behavioral science literature to which they are relevant, and in particular to consider their potential for “categorical causal modeling”, using latent class analysis. We have collated a number of popular categorical-data models with latent variables and causal structure, typically incorporating a Markovian structure. The efficacy of the approximation methods has been demonstrated through simulations related to an important behavioral science model.

Product architecture decisions are made early in the product development process and have far-reaching effects. Unless anticipated through experience or intuition, many of these effects may not be apparent until much later in the development process, making changes to the architecture costly in time, effort and resources. Many researchers through the years have studied various elements of product architecture and their effects. By using a repeatable process for aggregating statements on the effects of architecture strategies from a selection of the literature on the topic and storing them in a systematic database, this information can then be recalled and presented in the form of a Product Architecture Strategy and Effect (PASE) matrix. PASE matrices allow for the identification, comparison, evaluation, and then selection of the most desirable product architecture strategies before expending resources along a specific development path. This paper introduces the PASE Database and matrix and describes their construction and use in guiding design decisions. This paper also provides metrics for understanding the robustness of this database.

We compare detailed observations of multiple H2O maser transitions around the red supergiant star VY CMa with models to constrain the physical conditions in the complex outflows. The temperature profile is consistent with a variable mass loss rate but the masers are mostly concentrated in dense clumps. High-excitation lines trace localised outflows near the star.

Background: Despite a higher prevalence of traumatic spinal cord injury (TSCI) amongst Canadian Indigenous peoples, there is a paucity of studies focused on Indigenous TSCI. We present the first Canada-wide study comparing TSCI amongst Canadian Indigenous and non-Indigenous peoples. Methods: This study is a retrospective analysis of prospectively-collected TSCI data from the Rick Hansen Spinal Cord Injury Registry (RHSCIR) from 2004-2019. We divided participants into Indigenous and non-Indigenous cohorts and compared them with respect to demographics, injury mechanism, level, severity, and outcomes. Results: Compared with non-Indigenous patients, Indigenous patients were younger, more female, less likely to have higher education, and less likely to be employed. The mechanism of injury was more likely due to assault or transportation-related trauma in the Indigenous group. The length of stay for Indigenous patients was longer. Indigenous patients were more likely to be discharged to a rural setting, less likely to be discharged home, and more likely to be unemployed following injury. Conclusions: Our results suggest that more resources need to be dedicated for transitioning Indigenous patients sustaining a TSCI to community living and for supporting these patients in their home communities. A focus on resources and infrastructure for Indigenous patients by engagement with Indigenous communities is needed.

Transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is possible among symptom-free individuals. Patients are avoiding medically necessary healthcare visits for fear of becoming infected in the healthcare setting. We screened 489 symptom-free healthcare workers for SARS-CoV-2 and found no positive results, strongly suggesting that the prevalence of SARS-CoV-2 was <1%.

Design & Manufacture Knowledge Mapping is a critical activity in medium-to-large organisations supporting many organisational activities. However, techniques for effective mapping of knowledge often employ interviews, consultations and appraisals. Although invaluable in providing expert insight, the application of such methods is inherently intrusive and resource intensive. This paper presents word co-occurrence graphs as a means to automatically generate knowledge maps from technical documents and validates against expert generated knowledge maps.