METHODS: This pilot of a participatory modeling approach was conducted over a span of 7 sessions and included the following steps, each with an associated script: Step 1: Knowledge-Bearer and Knowledge-Interpreter recruitment Step 2: Relationship building Step 3: Session introduction, Vignette development & enrichment Step 4: Vignette analysis & constructing architecture of systems map Step 5: Augmenting architecture of systems map RESULTS: Each step of the participatory modeling approach resulted in artifacts that were valuable for both the communities and the research effort. Vignette construction resulted in narratives representing a spectrum of lived experiences, trajectories, and outcomes within a community. The collaborative analysis of vignettes yielded the Architecture of Systemic Factors map, that revealed how factors inter-relate to form a system in which lived experience of poverty occurs. A literature search provided an opportunity for the community to contextualize existing research about them using realities of lived experience.
CONCLUSION: This methodology showed that a community Knowledge Bearer can function as communicators and interpreters of their community's knowledge base, can develop coherent narratives of lived experiences within which research and knowledge is contextualized, and can collaboratively construct conceptual mappings necessary for simulation modeling. This participatory modeling approach showed that even if there already exists a vast body of research about a community, collaborating with community gives context to that research and brings together disparate findings within narratives of lived experience.
OBJECTIVE: The objective of this research is to develop and implement the Change and Health Evaluation and Response System (CHEERS) as a methodological framework, designed to facilitate the generation and ongoing monitoring of climate change and health-related data within existing Health and Demographic Surveillance Sites (HDSSs) and comparable research infrastructures.
METHODS: CHEERS uses a multi-tiered approach to assess health and environmental exposures at the individual, household, and community levels, utilizing digital tools such as wearable devices, indoor temperature and humidity measurements, remotely sensed satellite data, and 3D-printed weather stations. The CHEERS framework utilizes a graph database to efficiently manage and analyze diverse data types, leveraging graph algorithms to understand the complex interplay between health and environmental exposures.
RESULTS: The Nouna CHEERS site, established in 2022, has yielded significant preliminary findings. By using remotely-sensed data, the site has been able to predict crop yield at a household level in Nouna and explore the relationships between yield, socioeconomic factors, and health outcomes. The feasibility and acceptability of wearable technology have been confirmed in rural Burkina Faso for obtaining individual-level data, despite the presence of technical challenges. The use of wearables to study the impact of extreme weather on health has shown significant effects of heat exposure on sleep and daily activity, highlighting the urgent need for interventions to mitigate adverse health consequences.
CONCLUSION: Implementing the CHEERS in research infrastructures can advance climate change and health research, as large and longitudinal datasets have been scarce for LMICs. This data can inform health priorities, guide resource allocation to address climate change and health exposures, and protect vulnerable communities in LMICs from these exposures.
METHODS: An international working group was formed of nutrition researchers from 14 institutions in 12 different countries and on five continents. Using meetings over a period of one year, we interrogated the CONSORT statement specifically for its application to report nutrition trials.
RESULTS: We provide a total of 28 new nutrition-specific recommendations or emphasised recommendations for the reporting of the introduction (three), methods (twelve), results (five) and discussion (eight). We also added two additional recommendations that were not allocated under the standard CONSORT headings.
CONCLUSION: We identify a need to provide guidance in addition to CONSORT to improve the quality and consistency of the reporting and propose key considerations for further development of formal guidelines for the reporting of nutrition trials. Readers are encouraged to engage in this process, provide comments and conduct specific studies to inform further work on the development of reporting guidelines for nutrition trials.
METHODS: A quasi-experimental design using preprogram and postprogram questionnaires over 4 weeks with a control group (n = 75) matched for sex, age group, and socioeconomic disadvantage to program participants (n = 867). General linear mixed models assessed change in food literacy behavior frequency in 3 self-reported domains (plan and manage, selection, and preparation) and fruit and vegetable servings.
RESULTS: Postprogram, Food Sensations for Adults participants reported modest yet statistically significant score improvements in 2 of the 3 domains of food literacy behaviors in the plan and manage (12.4%) and preparation (9.8%) domains, as well as servings of vegetables (22.6% or 0.5 servings).
CONCLUSION AND IMPLICATIONS: Quasi-experimental designs indicate food literacy programs can produce modest short-term changes across a range of food literacy and dietary behaviors.
METHODS AND ANALYSIS: This mixed-method project has two phases. In phase 1, we will identify a list of patient-reported and clinical outcomes through qualitative research and systematic reviews. In phase 2, we will categorise the identified outcomes using the Core Outcome Measures in Effectiveness Trials taxonomy of core domains and the International Classification of Functioning, Disability and Health. We will develop questionnaires from the list of outcomes identified from each domain for the two-round online Delphi exercise, aiming to reach a consensus on the COS. The Delphi process will include patients, carers, researchers and healthcare participants. We will hold an online consensus meeting involving representatives of all key stakeholders to establish the final COS.
ETHICS AND DISSEMINATION: The study has been reviewed and approved by the Ethics Committee for Research Involving Human Subjects, Universiti Putra Malaysia and the Research Ethics Committee, National University of Malaysia. This proposed COS in TD will improve the value of data, facilitate high-quality evidence synthesis and evidence-based decision-making. Furthermore, we will present the results to participants, in peer-reviewed academic journals and conferences.
REGISTRATION DETAILS: Core Outcome Measures in Effectiveness Trials (COMET) Initiative database registration: http://www.comet-initiative.org/studies/details/1371.
MAIN BODY: As an exemplar, we reflect on how, in the Asthma UK Centre for Applied Research (AUKCAR), we set out to create a supportive, organised environment with the overarching value of 'keeping patients at the heart of everything we do'. The key has been in planning and creating a suitably funded organisational infrastructure with dedicated PPI researchers along with the development of and expectation to abide by an agreed set of norms and values. Specifically, expecting AUKCAR PhD students and early career researchers to engage with PPI has established a working mode that we hope will last. Regular interactions and proactive Patient Leads increase PPI network cohesion.
CONCLUSION: With adaptation, the AUKCAR PPI model can be translated to international contexts.
RESULTS: The Condorcet fusion method was examined. This approach combines the outputs of similarity searches from eleven association and distance similarity coefficients, and then the winner measure for each class of molecules, based on Condorcet fusion, was chosen to be the best method of searching. The recall of retrieved active molecules at top 5% and significant test are used to evaluate our proposed method. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints.
CONCLUSIONS: Simulated virtual screening experiments with the standard two data sets show that the use of Condorcet fusion provides a very simple way of improving the ligand-based virtual screening, especially when the active molecules being sought have a lowest degree of structural heterogeneity. However, the effectiveness of the Condorcet fusion was increased slightly when structural sets of high diversity activities were being sought.