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Despite evidence that precision medicine (PM) results in improved patient care, the broad adoption and implementation has been challenging across the United States (US). To better understand the perceived barriers associated with PM adoption, a quantitative survey was conducted across five stakeholders including medical oncologists, surgeons, lab directors, payers, and patients. The results of the survey reveal that stakeholders are often not aligned on the perceived challenges with PM awareness, education and reimbursement, with there being stark contrast in viewpoints particularly between clinicians, payers, and patients. The output of this study aims to help raise the awareness that misalignment on the challenges to PM adoption is contributing to broader lack of implementation that ultimately impacts patients. With better understanding of stakeholder viewpoints, we can help alleviate the challenges by focusing on multi-disciplinary education and awareness to ultimately improve patient outcomes.

Climatic variability has been acquiring an extensive consideration due to its widespread ability to impact food production and livelihoods. Climate change has the potential to intersperse global approaches in alleviating hunger and undernutrition. It is hypothesized that climate shifts bring substantial negative impacts on food production systems, thereby intimidating food security. Vast developments have been made addressing the global climate change, undernourishment, and hunger for the last few decades, partly due to the increase in food productivity through augmented agricultural managements. However, the growing population has increased the demand for food, putting pressure on food systems. Moreover, the potential climate change impacts are still unclear more obviously at the regional scales. Climate change is expected to boost food insecurity challenges in areas already vulnerable to climate change. Human-induced climate change is expected to impact food quality, quantity, and potentiality to dispense it equitably. Global capabilities to ascertain the food security and nutritional reasonableness facing expeditious shifts in biophysical conditions are likely to be the main factors determining the level of global disease incidence. It can be apprehended that all food security components (mainly food access and utilization) likely be under indirect effect via pledged impacts on ménage, incomes, and damages to health. The corroboration supports the dire need for huge focused investments in mitigation and adaptation measures to have sustainable, climate-smart, eco-friendly, and climate stress resilient food production systems. In this paper, we discussed the foremost pathways of how climate change impacts our food production systems as well as the social, and economic factors that in the mastery of unbiased food distribution. Likewise, we analyze the research gaps and biases about climate change and food security. Climate change is often responsible for food insecurity issues, not focusing on the fact that food production systems have magnified the climate change process. Provided the critical threats to food security, the focus needs to be shifted to an implementation oriented-agenda to potentially cope with current challenges. Therefore, this review seeks to have a more unprejudiced view and thus interpret the fusion association between climate change and food security by imperatively scrutinizing all factors.

Holographic-type communication (HTC) permits new levels of engagement between remote users. It is anticipated that it will give a very immersive experience while enhancing the sense of spatial co-presence. In addition to the newly revealed advantages, however, stringent system requirements are imposed, such as multi-sensory and multi-dimensional data capture and reproduction, ultra-lightweight processing, ultra-low-latency transmission, realistic avatar embodiment conveying gestures and facial expressions, support for an arbitrary number of participants, etc. In this paper, we review the current limitations to the HTC system implementation and systemize the main challenges into a few major groups. Furthermore, we propose a conceptual framework for the realization of an HTC system that will guarantee the desired low-latency transmission, lightweight processing, and ease of scalability, all accompanied with a higher level of realism in human body appearance and dynamics.

Low impact development (LID) practices are able to mitigate the detrimental effects of urbanization and climate change due to their salient design features. LID can restore the hydrology of urban areas to the pre-development functions by using distributed stormwater control and natural hydrological features. LID can help to achieve the goal of sustainable development as it promotes effective urban stormwater management. This review covers a comprehensive list of LID practices, namely bioretention cell, green roof, infiltration trench, permeable pavement, rain barrel or cistern, rooftop disconnection and vegetative swale. For each type of the LID, the recent advances covering the aspects of principles, design, performance, advantages and disadvantages and costs are systematically reviewed. Additionally, although LID has been quite broadly applied and demonstrated success in urban stormwater management in many countries, there are still some main challenges during the implementation such as clogging and water quality. Meanwhile, this review also highlights the great opportunities for further developments for LID practices to realize their wider practical application. Finally, future research directions are provided in order to give critical insights into potential future works to advance this field of research.

This study attempts to solve the challenges facing value engineering due to the shortage in the creativity stage via using an innovative tool during the ideation process to arrange the ideas’ creation; this tool is the Oriented Creativity Matrix (OCM) to ensure communication and considering the designer concern during that process. This shortage could be either the inapplicability of the proposals generated from the creativity stage or the inability to discover workable proposals. Per the previous research, many implementation challenges were reported as roadblocks impeding the value engineering proposals. To encounter those challenges, the OCM method was set, including identifying the potential altering aspects by which the sub-alternatives are generated and then composed to configure the main alternatives. Generating alternatives via the pre-identified alteration aspects promotes the coverage of all potential alternatives and ensures their performance from the perspective of each of them. Furthermore, this procedure establishes clear ground rules for the participants in the creativity stage, unifying their efforts to propose sub-alternatives to resolve the problem from an ascertained perspective rather than wasting efforts to defend their pre-desired main alternatives without due consideration for each perspective. To specify the most affective alteration aspects, a questionnaire distributed to the value engineering (VE) specialist to ensure the completeness of the included aspects and track any further alteration aspects. Per the collected data via the questionnaire, the altering aspects of completeness were statistically proved, and the OCM method was designed and elaborated to facilitate its usage in the VE ideation process.

Background Community-based treatment of possible serious bacterial infection (PSBI) in young infants, when referral to a hospital is not possible, can result in high treatment coverage and low case fatality. However, in Ethiopia, the coverage of PSBI treatment remains low, worsened by COVID-19. To understand the challenges of delivery of PSBI treatment and design and test adaptative strategies to mitigate the impact of COVID-19 on neonatal mortality, we did implementation research (IR) employing Implementation Research Logic Model (IRLM). In this paper, we describe IRLM application experiences in designing, implementing, and evaluating strategies to improve community-based treatment of PSBI during the COVID-19 pandemic in Ethiopia. Methods This IR was conducted between November 2020-April 2022 at Dembecha and Lume woredas of Amhara and Oromia regions, respectively. We employed narrative reviews, formative assessment and facilitated stakeholder engagement to develop the PSBI treatment IRLM to identify barriers, understand the conceptual linkages among determinants, choose implementation strategies, elicit mechanisms, and link to implementation outcomes. In addition, we used the IRLM to structure the capture of emerging implementation challenges and resulting strategy adaptations throughout implementation. Results This IR identified COVID-19 and multiple pre-existing contextual factors. We designed and implemented implementation strategies to address these challenges. These adaptive strategies were implemented with sufficient strength to maintain the delivery of PSBI services and improve mothers’ care-seeking behavior for their sick young infants. The IRLM offers us a clear process and path to prioritize implementation challenges, choose strategies informed by mechanisms of action, and where the adaptive implementation of community-based management of PSBI would lead to high-implementation fidelity and change in mother behavior to seek care for their sick young infants. The IRLM was also an effective tool for stakeholder engagement, easily explained and used to structure discussion and decision-making during co-design meetings. Conclusions The use of the IRLM helps us to specify the conceptual links between the implementation challenges, strategies, mechanisms of action, and outcomes to explore the complex community-based management of PSBI during complex contexts to improve high-fidelity implementation and integration of PSBI treatment in the primary healthcare delivery systems through active engagement of stakeholders.

The Ganges-Brahmaputra (GB) delta is one of the most disaster-prone areas in the world due to a combination of high population density and exposure to tropical cyclones, floods, salinity intrusion and other hazards. Due to the complexity of natural deltaic processes and human influence on these processes, structural solutions like embankments are inadequate on their own for effective hazard mitigation. This article examines nature-based solutions (NbSs) as a complementary or alternative approach to managing hazards in the GB delta. We investigate the potential of NbS as a complementary and sustainable method for mitigating the impacts of coastal disaster risks, mainly cyclones and flooding. Using the emerging framework of NbS principles, we evaluate three existing approaches: tidal river management, mangrove afforestation, and oyster reef cultivation, all of which are actively being used to help reduce the impacts of coastal hazards. We also identify major challenges (socioeconomic, biophysical, governance and policy) that need to be overcome to allow broader application of the existing approaches by incorporating the NbS principles. In addition to addressing GB delta-specific challenges, our findings provide more widely applicable insights into the challenges of implementing NbS in deltaic environments globally.

Patients with cancer frequently experience psychological and social challenges, including depression, anxiety, and isolation, which are often intensified by treatment side effects and unmet psychosocial needs. Conventional support systems are often inaccessible, under-resourced, or poorly tailored to diverse patient populations. In this context, virtual communities have emerged as promising alternatives that enable peer interaction, emotional support, and information exchange. However, their implementation and sustainability are influenced by complex sociotechnical and organizational factors that remain underexplored. This scoping review applies the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework to examine how virtual communities have been implemented in cancer care. It aims to identify key barriers and facilitators, evaluate the alignment between platform features and user needs, and synthesize evidence to inform sustainable integration into care systems. A systematic search was conducted across 6 databases (PubMed, Scopus, Embase, Web of Science, PsycINFO, and CINAHL), covering studies published between 2019 and 2024. Eligible studies were empirical and reported on the development, implementation, or evaluation of virtual communities for patients with cancer. Data were extracted using a structured Non-adoption, Abandonment, Scale-up, Spread, and Sustainability-based matrix and synthesized thematically across diverse research designs. The search yielded 322 records, of which 175 full-text studies were assessed for eligibility, and 25 studies were included in the review. These studies covered a range of virtual community formats used by patients with cancer. All included studies reported psychosocial benefits, including reduced loneliness, improved emotional well-being, and greater opportunities for experience sharing. However, key challenges remained, such as low user retention, limited participation from underrepresented groups, and difficulties integrating these platforms into existing health care systems. Few studies reported longitudinal follow-up or detailed engagement metrics, limiting insights into long-term effectiveness. Virtual communities show strong potential to address the psychosocial needs of patients with cancer, especially in underserved populations. However, to ensure long-term effectiveness, attention must be paid to inclusivity, user retention, ethical considerations, and system-level integration. Future research should incorporate standardized metrics, longitudinal designs, and equity-oriented approaches to optimize the development and implementation of virtual communities in cancer care.

Recent studies demonstrate the potential of Artificial Intelligence to support diagnosis, mortality assessment, and clinical decisions in low-and-middle-income countries (LMICs). However, explicit evidence of strategies to overcome the particular challenges for transformed health systems in these countries does not exist. The present study undertakes a review of research on the current status of artificial intelligence (AI) to identify requirements, gaps, challenges, and possible strategies to strengthen the large, complex, and heterogeneous health systems in LMICs. After introducing the general challenges developing countries face, the methodology of systematic reviews and the meta-analyses extension for scoping reviews (PRISMA-ScR) is introduced according to the preferred reporting items. Scopus and Web of Science databases were used to identify papers published between 2011-2022, from which we selected 151 eligible publications. Moreover, a narrative review was conducted to analyze the evidence in the literature about explicit evidence of strategies to overcome particular AI challenges in LMICs. The analysis of results was divided into two groups: primary studies, which include experimental studies or case studies using or deploying a specific AI solution ( = 129), and secondary studies, including opinion papers, systematic reviews, and papers with strategies or guidelines ( = 22). For both study groups, a descriptive statistical analysis was performed describing their technological contribution, data used, health context, and type of health interventions. For the secondary studies group, an in-deep narrative review was performed, identifying a set of 40 challenges gathered in eight different categories: data quality, context awareness; regulation and legal frameworks; education and change resistance; financial resources; methodology; infrastructure and connectivity; and scalability. A total of 89 recommendations (at least one per challenge) were identified. Research on applying AI and ML to healthcare interventions in LMICs is growing; however, apart from very well-described ML methods and algorithms, there are several challenges to be addressed to scale and mainstream experimental and pilot studies. The main challenges include improving the quality of existing data sources, training and modeling AI solutions based on contextual data; and implementing privacy, security, informed consent, ethical, liability, confidentiality, trust, equity, and accountability policies. Also, robust eHealth environments with trained stakeholders, methodological standards for data creation, research reporting, product certification, sustained investment in data sharing, infrastructures, and connectivity are necessary. [https://rb.gy/frn2rz].