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UGSpace is the institutional repository of the University of Ghana. UGSpace is an open access electronic archive for the collection, preservation and distribution of digital materials to:
- facilitate the deposit of digital content of a scholarly or heritage nature
- and ultimately share, preserve and promote the intellectual output of the University in a managed environment.
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- Review books or articles provide a critical and constructive analysis of existing published literature in a field, through summary, analysis, and comparison, often identifying specific gaps or problems and providing recommendations for future research. These are considered as secondary literature since they generally do not present new data from the author's experimental work. Review articles can be of three types, broadly speaking: literature reviews, systematic reviews, and meta-analyses. It also the researcher to stay abreast of new literature in the field.
- Grey literature consists of research and information produced outside conventional publishing channels, such as reports, policy briefs, working papers, and conference materials. It offers valuable insights and data that complement peer-reviewed sources, supporting research, policy, and practice.
- The J. H. Kwabena Nketia Archives preserve Ghanaian and African cultural heritage through music, oral traditions, photographs, and audiovisual collections. Guided by Professor Nketia’s vision that African traditional arts must be collected, preserved, practiced, and continually inspire creative expression, the Archives serve as a living resource for scholarship, teaching, and innovation
Recent Submissions
Item type:Item, Access status: Open Access , Deep SEM: Integrating Deep Neural Networks Into Structural Equation Modelling With The SEMdeep Package In R(Methodological Innovations, 2026-05-05) Osei, I.; Carie, C.A.; Marapelli, B.; Boadu, D.O.; Anamalamudi, S.Structural Equation Modelling (SEM) has been widely applied in information systems, psychology, marketing, management, and other social science disciplines, providing a powerful framework for analysing relationships among latent variables. However, traditional SEM methods rely on assumptions of linearity and normality, which may limit their ability to represent complex or nonlinear data patterns. Recent advances in computational modelling have introduced Deep SEM (or Neural SEM), an approach that integrates deep learning components within SEM. This hybrid framework combines SEM’s theoretical and explanatory strengths with the representational flexibility of neural networks. In this paper, we provide an overview of Deep SEM, demonstrate its implementation in R using the SEMdeep package, and compare its explanatory and predictive behaviour with that of a traditional covariance-based SEM under identical data conditions. Using an illustrative and parsimonious neural architecture, the results show that Deep SEM yields higher in-sample explained variance across endogenous constructs while preserving the dominant theoretical pathways identified by SEM. These findings suggest that Deep SEM offers a complementary extension to conventional SEM, enabling researchers to explore potential nonlinearities while maintaining interpretability and theoretical coherence.Item type:Item, Access status: Open Access , We Are One of the Most Depressed Professionals”: Nurses' Experiences of Psychological Hazards in A District Hospital(Nursing Open, 2026-04-29) Kodom, P.N.B.; Parimah, F.; Agyemang, C.B.Aim: This study explored the occupational hazards faced by nurses in a district hospital in Ghana, analysed their psychological outcomes, and examined how emotional labour mediates nurses' behaviour in patient care. Design: A focused ethnographic study. Methods: Over the course of 11 months, data were collected purposively from 31 general nurses and one key informant using in- depth interviews, participant observation, and informal dialogues. Data were analysed thematically using network analysis, supported by NVivo 12 Plus. Rigour was enhanced through prolonged engagement, triangulation, pilot testing, member check ing, and peer debriefing. Results: Two categories of psychological hazards emerged: default hazards (unavoidable), such as patient deaths, ubiquity of sickness, and unpleasant sights; and escapable hazards (somewhat avoidable), including work- related injuries and shift- work maladaptation. These hazards triggered grief, disgust, fear, anxiety, and fatigue, which nurses managed through emotional la bour strategies: surface acting, deep acting, spiritual coping, peer support, and emotional detachment. While these strategies en abled professionalism, they often led to emotional dissonance, burnout, and strained relationships between nurses and patients. Conclusion: Occupational hazards in hospital wards carry significant psychological burdens that shape nurses' behaviour and professional conduct. Emotional labour mediates these responses, but reliance on individual coping strategies is unsustainable without institutional support. Comprehensive support systems, such as psychotherapeutic counselling during and after nursing school, are needed to mitigate the effects of these occupational hazards on healthcare providers. Patient or Public Contribution: No patient or public contribution.Item type:Item, Access status: Open Access , Obesity Rise Plateaus In Developed Nations And Accelerates In Developing Nations(Nature, 2026-05-13) Adu-Afarwuah , S.; Ezzati, M.; Zhou, B.; et al.Global reporting of obesity is commonly based on comparisons over multiple decades1 and lacks a granular and systematic analysis of its dynamics. We used 4,050 population- based studies with measured height and weight data on 232 million participants to assess the worldwide dynamics of obesity from 1980 to 2024. The rise in obesity decelerated in school-aged children and adolescents throughout the 1990s in many high-income countries, and subsequently plateaued in most at age-standardized prevalences spanning 20 percentage points, from 3–4% for girls in Japan, Denmark and France to 23% for boys in the USA. There were indications of a small decline in obesity in children and adolescents in some high-income western countries (for example, Italy, Portugal and France) since the 2000s. Similar trends were seen in some countries in Central and Eastern Europe. In adults, the rise in obesity slowed down in high-income western countries about a decade after children, followed by a plateau or possibly a small reversal of the rise in some countries (for example, Spain). In most low-income and middle-income countries, the annual absolute change in prevalence has remained stable or increased over time, even though prevalence has surpassed that of high-income countries. These highly varied dynamics suggest that the social, economic and technological trends that influence the availability, affordability and use of different foods may have helped control the rise in obesity in high-income countries, but require policy interventions in low-income and middle-income countries.Item type:Item, Access status: Open Access , Structural Equation Modelling In R: Comparing Lavaan And Seminr Packages(Methodological Innovations, 2026-05-14) Osei, I.; Carie, C.A.; Anamalamudi, S.; Boadu, D.O.; Kwakye, M.This paper compares two popular R packages for structural equation modelling (SEM) – lavaan and seminr – to help researchers understand not only how they work, but also when each is most appropriate. Although both tools allow users to estimate the same structural models, they are grounded in different methodological traditions and are designed to support different research goals. Using an identical model, we estimated results with both covariance-based SEM (lavaan) and variance based SEM (seminr) and compared their outputs, including model specification syntax, evaluation criteria, and reporting conventions. The results show that both approaches lead to substantively similar conclusions regarding the relationships between constructs, while differing in emphasis: lavaan provides richer global model-fit diagnostics, whereas seminr places greater emphasis on prediction-oriented assessment and convenient access to latent variable scores. The contribution of this study lies in its practical, hands-on demonstration rather than in a theoretical or simulation-based comparison. The findings reinforce that there is no universally “better” SEM approach; instead, methodological choice should be guided by the research objective. Researchers focussed on theory testing may benefit more from lavaan, while those prioritising prediction or exploratory analysis may find seminr more suitable. Ultimately, considering both perspectives can support more transparent, robust, and methodologically appropriate SEM applications.Item type:Item, Access status: Open Access , Solution Combustion Synthesis Of Strontium-Doped Hydroxyapatite: Effect Of Sintering And Low Compaction Pressure On The Mechanical Properties And Physiological Stability.(Materials Letters, 2021-08-05) Obada, D.O.; Salami, K.A.; Oyedeji, A.N.; Fasanya, O.O.; Dodoo-Arhin, D.; et al.The solution combustion route was used to fabricate strontium (Sr) doped hydroxyapatite (HAp). A low compaction pressure method was adopted for pelletizing the powders (Sr-HAp) prior to physical and mechanical properties measurement. Physiological stability of the pellets was conducted by immersing in Phosphate Buffer Saline (PBS) solution for 24 h. The Sr-HAp produced a comparatively higher hardness and fracture toughness of 0.38 GPa and 0.82 MPa⋅m1/2 compared with 0.20 GPa and 0.67 MPa⋅m1/2 for undoped HAp. The SEM images suggested that strontium co-existed with the calcium ion in hydroxyapatite due to the presence of irregular bead- like structures on a micro-scale. The Sr-HAp pellets were stable in Phosphate Buffer Saline solution.