Use of Ecological Momentary Assessment to Measure Dyspnea in COPD.

Dyspnea is an unpredictable and distressing symptom of chronic obstructive pulmonary disease (COPD). Dyspnea is challenging to measure due to the heterogeneity of COPD and recall bias associated with retrospective reports. Ecological Momentary Assessment (EMA) is a technique used to collect symptoms in real-time within a natural environment, useful for monitoring symptom trends and risks of exacerbation in COPD. EMA can be integrated into mobile health (mHealth) platforms for repeated data collection and used alongside physiological measures and behavioral activity monitors. The purpose of this paper is to discuss the use of mHealth and EMA for dyspnea measurement, consider clinical implications of EMA in COPD management, and identify needs for future research in this area.

Interprofessional education interventions in undergraduate students of musculoskeletal healthcare professions: a scoping review protocol.

INTRODUCTION: Enhancing interprofessional education (IPE) fosters collaborative efforts among healthcare professionals specializing in musculoskeletal (MSK) care. This approach presents a valuable opportunity to address the pressing MSK disease burden in developing countries, with high prevalence rates and limited resources. While an abundance of literature on the various elements of IPE among healthcare students and professionals exists, shared contexts of practice of South African MSK disciplines are not currently developed through IPE at higher education level, establishing a need for South African formalised curricular IPE interventions with an explicit focus on undergraduate students of MSK healthcare professions. METHODS AND ANALYSIS: The intended scoping review protocol is guided by the framework set out by Arksey and O'Malley, where the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews will guide the process of reporting. English sources (qualitative and quantitative methodological studies, conference papers and proceedings, systematic reviews, grey literature, unpublished materials, theses and dissertations) from the electronic databases PubMed, Scopus, ERIC and ProQuest with no date restriction will be included. A researcher, an independent reviewer and research librarian will search and extract data from abstracts and full texts for this scoping review, where any arising disagreements will be resolved by discussion. Reference lists of relevant literature will be scrutinised. Relevant literature will be recorded on a referencing software and deduplicated. The data collection will take place between May and October 2023. The findings will be reported narratively with the use of tables. ETHICS AND DISSEMINATION: This scoping review does not require ethical approval as all literature used already exists in the public domain with no involvement of human participants. The findings from this planned review will be submitted to peer-reviewed journals and will be presented at higher education conferences. This scoping review protocol was registered on Open Science Framework with the registration osf.io/c27n4.

What factors influence couples' decisions to have children? Evidence from a systematic scoping review.

BACKGROUND: One of the most significant demographic challenges over the past three decades has been the substantial reduction in fertility rates, worldwidely. As a developing country, Iran has also experienced a rapid decline in fertility over the past decades. Understanding factors influencing fertility is essential for development programs. Moreover, it's crucial to study the parameters that affect the intention for childbearing in any society. Therefore, through a systematic scoping review, the present study investigates the factors influencing couples' decisions toward childbearing. METHODS: This study was a systematic scoping review conducted in 2023. To design and conduct this scoping review, Joanna Briggs Institute's Protocol (Institute TJB, The Joanna Briggs Institute Reviewers ' manual 2015; methodology for JBI scoping reviews, 2015) was used and the framework presented by Levac et al. (2010) was also used as a guide for conducting this review. Studies were searched in three main databases including ISI Web of Sciences, PubMed, and Scopus, using a predefined search strategy. Google Scholar was also used for complementary search. The search period was from 2002 to 2022. RESULTS: A total of 18,454 studies were identified across three primary databases. After evaluating articles in three distinct phases based on title, abstract, and full-text, 46 articles were deemed eligible for inclusion in the scoping review. The qualitative analysis of the collected data from the selected studies through the scoping review led to classifying factors influencing households' desire for childbearing into eight main themes and 101 sub-themes. The main themes associated with factors impacting households' intention for childbearing encompass individual determinants, demographic and familial influencing factors, cultural elements, social factors, health-related aspects, economic considerations, insurance-related variables, and government support/incentive policies. CONCLUSIONS: Comprehensive and holistic attention from governments and officials toward the various factors affecting households' intention and behavior regarding childbearing appears beneficial and effective. Furthermore, given the relative ineffectiveness of some of the current government's supportive/incentive policies to increase couples' desire for childbearing, it seems necessary to review and amend these policies. This review should address the most significant challenges and factors contributing to couples' reluctance to childbearing or strengthen factors that can play a substantial role in fostering fertility and childbearing desires.

Green R & D investment, ESG reporting, and corporate green innovation performance.

Given the contradictory empirical evidence on the relationship between green R&D expenditure and corporate Green Innovation performance (GIP), The present research study is a distinctive investigation into the moderating impacts of ESG reporting on this relationship. We utilized a data collection of 3,846, firm-year observations of A-share listed firms in China from 2016 to 2022 from CSMAR and Bloomberg databases. The firm's Corporate GIP is assessed and measured by looking at the total quantity of green patents. Lastly, models with multiple regression analyses and fixed effects were employed. The findings show that ESG reporting has a positive and significant impact on the association between corporate GIP and green R&D expenditure, implying its compensating and supportive function in the form of green signals in green outputs. This research could help executives and lawmakers, especially in developing countries to build innovative environmental strategies for business sustainability.

Defining acceptable data collection and reuse standards for queer artificial intelligence research in mental health: protocol for the online PARQAIR-MH Delphi study.

INTRODUCTION: For artificial intelligence (AI) to help improve mental healthcare, the design of data-driven technologies needs to be fair, safe, and inclusive. Participatory design can play a critical role in empowering marginalised communities to take an active role in constructing research agendas and outputs. Given the unmet needs of the LGBTQI+ (Lesbian, Gay, Bisexual, Transgender, Queer and Intersex) community in mental healthcare, there is a pressing need for participatory research to include a range of diverse queer perspectives on issues of data collection and use (in routine clinical care as well as for research) as well as AI design. Here we propose a protocol for a Delphi consensus process for the development of PARticipatory Queer AI Research for Mental Health (PARQAIR-MH) practices, aimed at informing digital health practices and policy. METHODS AND ANALYSIS: The development of PARQAIR-MH is comprised of four stages. In stage 1, a review of recent literature and fact-finding consultation with stakeholder organisations will be conducted to define a terms-of-reference for stage 2, the Delphi process. Our Delphi process consists of three rounds, where the first two rounds will iterate and identify items to be included in the final Delphi survey for consensus ratings. Stage 3 consists of consensus meetings to review and aggregate the Delphi survey responses, leading to stage 4 where we will produce a reusable toolkit to facilitate participatory development of future bespoke LGBTQI+-adapted data collection, harmonisation, and use for data-driven AI applications specifically in mental healthcare settings. ETHICS AND DISSEMINATION: PARQAIR-MH aims to deliver a toolkit that will help to ensure that the specific needs of LGBTQI+ communities are accounted for in mental health applications of data-driven technologies. The study is expected to run from June 2024 through January 2025, with the final outputs delivered in mid-2025. Participants in the Delphi process will be recruited by snowball and opportunistic sampling via professional networks and social media (but not by direct approach to healthcare service users, patients, specific clinical services, or via clinicians' caseloads). Participants will not be required to share personal narratives and experiences of healthcare or treatment for any condition. Before agreeing to participate, people will be given information about the issues considered to be in-scope for the Delphi (eg, developing best practices and methods for collecting and harmonising sensitive characteristics data; developing guidelines for data use/reuse) alongside specific risks of unintended harm from participating that can be reasonably anticipated. Outputs will be made available in open-access peer-reviewed publications, blogs, social media, and on a dedicated project website for future reuse.

Access to child developmental assessment services in culturally and linguistically diverse metropolitan Sydney: a retrospective cohort analysis.

BACKGROUND: Despite the increasing prevalence of neurodevelopmental disorders (NDD), data regarding access to child development services have remained limited globally. Long wait times are a major barrier to developmental assessments, impacting on care and outcomes. The aim is to retrospectively analyse the demographic profile and prioritisation of patients seen at a child developmental assessment service (CDAS) in a vulnerable region of Sydney, and explore factors affecting wait times. METHODS: Data was collated and analysed for 2354 patients from 2018 to 2022. Socio-Economic Indexes for Areas (SEIFA) were collated from the Australian Bureau of Statistics. Descriptive statistics were used for demographic data and various statistical methods were used to analyse the relationships and impact of factors likely to affect wait lists. RESULTS: The median age was 51 months (IQR41-61) and males comprised 73.7% of the cohort. 64% of children were from culturally and linguistically diverse backgrounds (CALD) and 47% lived in the most disadvantaged suburbs. The median wait time was 302.5 days (IQR175-379) and 70% of children were seen within 12 months. CALD patients and children over 5-years had shorter wait times. Most children with Global Developmental Delay (GDD) were from the lowest four SEIFA deciles and waited longer for an appointment. 42.6% were seen within the priority allocated time or sooner. Children with ASD and/or severe GDD were prioritised to be seen earlier. Overall, the study could not demonstrate any difference in the wait times according to the prioritisation groups. CONCLUSION: This study provides insights into the profile, prioritisation processes and wait lists of children seen by CDAS in South Western Sydney with high rates of social vulnerability and presents an argument to discuss benchmarking targets with service providers. It identifies the need to prioritise children living in suburbs with socioeconomic disadvantage and refine prioritisation and data collection processes to improve wait times.

Cost Analysis of Short Messaging Service and Peer Navigator Interventions for Linking and Retaining Adults Recently Diagnosed With HIV in Care in South Africa.

INTRODUCTION: Large proportions of people living with HIV (PLHIV) in sub-Saharan Africa are not linked to or retained in HIV care. There is a critical need for cost-effective interventions to improve engagement and retention in care and inform optimal allocation of resources. METHODS: We estimated costs associated with a short message service (SMS) plus peer navigation (SMS+PN) intervention; an SMS-only intervention; and standard of care (SOC), within the I-Care cluster-randomized trial to improve HIV care engagement for recently diagnosed PLHIV. We employed a uniform cost data-collection protocol to quantify resources used and associated costs for each intervention. RESULTS: Compared with SOC, the SMS+PN intervention cost $1284 ($828-$2859) more per additional patient linked to care within 30 days and $1904 ($1158-$5343) more per additional patient retained in care at 12 months, while improving linkage by 24% (95% CI: 11 to 36) and retention by 16% (95% CI: 6 to 26). By contrast, the SMS-only intervention cost $198 ($93-dominated) more per additional patient linked to care and $697 ($171-dominated) more per additional patient retained in care but was not significantly associated with improvements in linkage (12%; 95% CI: -1 to 25) or retention (3%; 95% CI: -7 to 14) compared with SOC. The efficiency of the SMS+PN intervention could be improved by 46%, to $690 more per additional patient linked and $1023 more per additional patient retained in care, if implemented within the Department of Health using more efficient distribution of staff resources. DISCUSSION: Findings suggest that scale-up of the SMS+PN intervention could benefit patients, improving care and health outcomes while being cost-effective.

Technology, data, people, and partnerships in addressing unmet social needs within Medicaid Managed Care.

BACKGROUND: Individuals with unmet social needs experience adverse health outcomes and are subject to greater inequities in health and social outcomes. Given the high prevalence of unmet needs among Medicaid enrollees, many Medicaid managed care organizations (MCOs) are now screening enrollees for unmet social needs and connecting them to community-based organizations (CBOs) with knowledge and resources to address identified needs. The use of screening and referral technology and data sharing are often considered key components in programs integrating health and social services. Despite this emphasis on technology and data collection, research suggests substantial barriers exist in operationalizing effective systems. METHODS: We used qualitative methods to examine cross-sector perspectives on the use of data and technology to facilitate MCO and CBO partnerships in Kentucky, a state with high Medicaid enrollment, to address enrollee social needs. We recruited participants through targeted sampling, and conducted 46 in-depth interviews with 26 representatives from all six Kentucky MCOs and 20 CBO leaders. Qualitative descriptive analysis, an inductive approach, was used to identify salient themes. RESULTS: We found that MCOs and CBOs have differing levels of need for data, varying incentives for collecting and sharing data, and differing valuations of what data can or should do. Four themes emerged from interviewees' descriptions of how they use data, including 1) to screen for patient needs, 2) to case manage, 3) to evaluate the effectiveness of programs, and 4) to partner with each other. Underlying these data use themes were areas of alignment between MCOs/CBOs, areas of incongruence, and areas of tension (both practical and ideological). The inability to interface with community partners for data privacy and ownership concerns contributes to division. Our findings suggest a disconnect between MCOs and CBOs regarding terms of their technology interfacing despite their shared mission of meeting the unmet social needs of enrollees. CONCLUSIONS: While data and technology can be used to identify enrollee needs and determine the most critical need, it is not sufficient in resolving challenges. People and relationships across sectors are vital in connecting enrollees with the community resources to resolve unmet needs.

Reporting of equity in observational epidemiology: A methodological review.

Background: Observational studies can inform how we understand and address persisting health inequities through the collection, reporting and analysis of health equity factors. However, the extent to which the analysis and reporting of equity-relevant aspects in observational research are generally unknown. Thus, we aimed to systematically evaluate how equity-relevant observational studies reported equity considerations in the study design and analyses. Methods: We searched MEDLINE for health equity-relevant observational studies from January 2020 to March 2022, resulting in 16 828 articles. We randomly selected 320 studies, ensuring a balance in focus on populations experiencing inequities, country income settings, and coronavirus disease 2019 (COVID-19) topic. We extracted information on study design and analysis methods. Results: The bulk of the studies were conducted in North America (n = 95, 30%), followed by Europe and Central Asia (n = 55, 17%). Half of the studies (n = 171, 53%) addressed general health and well-being, while 49 (15%) focused on mental health conditions. Two-thirds of the studies (n = 220, 69%) were cross-sectional. Eight (3%) engaged with populations experiencing inequities, while 22 (29%) adapted recruitment methods to reach these populations. Further, 67 studies (21%) examined interaction effects primarily related to race or ethnicity (48%). Two-thirds of the studies (72%) adjusted for characteristics associated with inequities, and 18 studies (6%) used flow diagrams to depict how populations experiencing inequities progressed throughout the studies. Conclusions: Despite over 80% of the equity-focused observational studies providing a rationale for a focus on health equity, reporting of study design features relevant to health equity ranged from 0-95%, with over half of the items reported by less than one-quarter of studies. This methodological study is a baseline assessment to inform the development of an equity-focussed reporting guideline for observational studies as an extension of the well-known Strengthening Reporting of Observational Studies in Epidemiology (STROBE) guideline.

Regional differences in health resource allocation: a longitudinal study in the Chengdu-Chongqing economic circle, China.

OBJECTIVE: To analyse regional differences in health resource allocation in the Chengdu-Chongqing economic circle. DESIGN: A longitudinal analysis that collected data on health resource allocation from 2017 to 2021. SETTING: The number of beds, health technicians, licensed (assistant) physicians, registered nurses and financial allocations per 1000 population in the 42 regions of Chengdu-Chongqing economic circle were used for the analysis. METHODS: The entropy weight technique for order preference by similarity to an ideal solution (TOPSIS) method and the rank sum ratio (RSR) method were used to evaluate the health resource allocation. RESULTS: The number of licensed (assistant) physicians per 1000 population in the Chengdu-Chongqing economic circle (3.01) was lower than the average in China (3.04) in 2021. According to the entropy weight-TOPSIS method, Yuzhong in Chongqing had the largest C-value and the highest ranking. Jiangbei in Chongqing and Chengdu and Ya'an in Sichuan Province had higher C-values and were ranked in the top 10. Jiangjin, Hechuan, Tongnan and Zhongxian in Chongqing and Guang'an in Sichuan Province had lower C-values and were all ranked after the 30th place. According to the RSR method, the 42 regions were divided into three grades of good, medium and poor. The health resource allocations of Yuzhong, Jiangbei, Nanchuan, Jiulongpo and Shapingba in Chongqing and Chengdu and Ya'an in Sichuan Province were of good grade, those of Tongnan, Jiangjin, Yubei and Dazu in Chongqing and Guang'an and Dazhou in Sichuan Province were of poor grade, and the rest of the regions were of medium grade. CONCLUSION: The regional differences in health resource allocation in the Chengdu-Chongqing economic circle were more obvious, the health resource allocation in Chongqing was more polarised and the health resource allocation in Sichuan Province was more balanced, but the advantaged regions were not prominent enough.

A comprehensive study on non-governmental actors in shaping grassland ecological compensation within legal frameworks.

Ecological compensation has emerged as a crucial institutional framework for managing the interplay between ecological preservation and economic development in China. This study focuses on the specific case of grassland ecological compensation to investigate the protection of rights and interests of non-governmental subjects. By utilizing data derived from questionnaire responses, this study examines the legal rights, obligations, and responsibilities associated with grassland ecological compensation. Statistical techniques such as Z-distribution, chi-square test, and non-parametric measures of correlation are employed to analyze the collected data, which are presented using tables and graphs. Furthermore, this research evaluates the current state of rights and interests of compensation subjects engaged in ecological compensation practices, aiming to enhance our comprehension and assessment of the extent to which the ecological compensation system safeguards the rights and interests of individuals. The findings show that a substantial number of respondents see current grassland ecological compensation methods in China as reasonable but insufficient, indicating a need for method diversification. There's a clear preference for a shared responsibility model over government-only funding, especially in regions with large grassland areas. This highlights the necessity for adaptable laws and a legal framework that accommodates diverse stakeholder needs. Additionally, the importance of clear property rights is emphasized for sustainable land use. The study suggests legislative reform towards a more equitable and effective approach to grassland conservation, providing valuable recommendations for refining and advancing the ecological compensation system.Author name 1 (Ziqi Liu) mismatch between ms and metadata. We have foolowed metadata. Kindly check and confirm.The metadata is right. Thank you.

MoodSensing: A smartphone app for digital phenotyping and assessment of bipolar disorder.

BACKGROUND: Daily life tracking has proven to be of great help in the assessment of patients with bipolar disorder. Although there are many smartphone apps for tracking bipolar disorder, most of them lack academic verification, privacy policy and long-term maintenance. METHODS: Our developed app, MoodSensing, aims to collect users' digital phenotyping for assessment of bipolar disorder. The data collection was approved by the Institutional Review Board. This study collaborated with professional clinicians to ensure that the app meets both clinical needs and user experience requirements. Based on the collected digital phenotyping, deep learning techniques were applied to forecast participants' weekly HAM-D and YMRS scale scores. RESULTS: In experiments, the data collected by our app can effectively predict the scale scores, reaching the mean absolute error of 0.84 and 0.22 on the scales. The statistical data also demonstrate the increase in user engagement. CONCLUSIONS: Our analysis reveals that the developed MoodSensing app can not only provide a good user experience, but also the recorded data have certain discriminability for clinical assessment. Our app also provides relevant policies to protect user privacy, and has been launched in the Apple Store and Google Play Store.

Assessing economic implications for micro, small and medium enterprises in Thailand post Covid-19 lockdown.

Micro, Small, and Medium-sized Enterprises (MSMEs) in Thailand were assessed in this study to determine the short-term and long-term economic effects of post-COVID- 19 -, with the goal of developing policy guidelines that focus on the methods and strategies that will further develop and help recover these sectors. MSMEs are the most vulnerable and require assistants to combat the pandemic. This study assesses the perspectives of stakeholders on the development of mechanisms and the strategies applied to support vulnerable groups in Thailand, which mostly consist of women and children. The main data collection was gathered through online questionnaires that were distributed to various stakeholder groups. The tools used for analysis were advanced quantitative analysis tools that aid in achieving this research study's objectives, and data was examined primarily through the usage of path modeling, structural equation modeling (SEM), and descriptive analysis was among the methods used. The findings reveal that in the short term, MSMEs' ability to respond to COVID-19 implications has a significant impact on both financial and non-financial performance. Non-financial performance, on the other hand, is more affected by adaptability than financial performance. Demand shock from lockdowns and other COVID-19 cautionary interventions has a negative and significant impact on MSMEs' adaptability, financial performance, and non-financial performance. The demand shocks increased the vulnerability of MSMEs significantly but it was found that proper management of demand shock has helped stabilized and improve MSMEs' financial and non-financial performances, as well as helped decrease their vulnerability. When it comes to government policy, the focus is usually on enhancing the flexibility and financial performance of MSMEs. The government's legislative actions have little impact on MSMEs' non-financial performance and vulnerability. This could be because the majority of the programs are more focused on providing financial assistance to businesses or their consumers. COVID-19's supply and demand shock only hindered MSMEs' ability to respond to the changes and challenges caused by the pandemic, according to vendors. The vulnerability of MSMEs caused by COVID-19 creates grave effects on their financial performance. The findings of this research paper will assist policymakers in identifying the most vulnerable aspects of MSMEs, as well as their expectations- and determine the forms of support that will be required to combat the current and future pandemic situations that may occur in Thailand. In addition, it will aid policymakers in the establishment of procedures and supporting strategies for MSMEs to reduce the unemployment rate and stimulate the Thai economy, among other factors of improvement.

Salmonellosis outbreak archive in China: data collection and assembly.

Infectious disease outbreaks transcend the medical and public health realms, triggering widespread panic and impeding socio-economic development. Considering that self-limiting diarrhoea of sporadic cases is usually underreported, the Salmonella outbreak (SO) study offers a unique opportunity for source tracing, spatiotemporal correlation, and outbreak prediction. To summarize the pattern of SO and estimate observational epidemiological indicators, 1,134 qualitative reports screened from 1949 to 2023 were included in the systematic review dataset, which contained a 506-study meta-analysis dataset. In addition to the dataset comprising over 50 columns with a total of 46,494 entries eligible for inclusion in systematic reviews or input into prediction models, we also provide initial literature collection datasets and datasets containing socio-economic and climate information for relevant regions. This study has a broad impact on advancing knowledge regarding epidemic trends and prevention priorities in diverse salmonellosis outbreaks and guiding rational policy-making or predictive modeling to mitigate the infringement upon the right to life imposed by significant epidemics.

2024 Adult Compendium of Physical Activities: A third update of the energy costs of human activities.

BACKGROUND: The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity (PA) across studies. The original version was updated in 2000, and again in 2011, and has been widely used to support PA research, practice, and public health guidelines. METHODS: This 2024 update was tailored for adults 19-59 years of age by removing data from those ≥60 years. Using a systematic review and supplementary searches, we identified new activities and their associated measured metabolic equivalent (MET) values (using indirect calorimetry) published since 2011. We replaced estimated METs with measured values when possible. RESULTS: We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers. We added 303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults. We added a Major Heading (Video Games). The 2024 Adult Compendium includes 1114 PAs (912 with measured and 202 with estimated values) across 22 Major Headings. CONCLUSION: This comprehensive update and refinement led to the creation of The 2024 Adult Compendium, which has utility across research, public health, education, and healthcare domains, as well as in the development of consumer health technologies. The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.

Mobile Crowdsensing in Ecological Momentary Assessment mHealth Studies: A Systematic Review and Analysis.

As mobile devices have become a central part of our daily lives, they are also becoming increasingly important in research. In the medical context, for example, smartphones are used to collect ecologically valid and longitudinal data using Ecological Momentary Assessment (EMA), which is mostly implemented through questionnaires delivered via smart notifications. This type of data collection is intended to capture a patient's condition on a moment-to-moment and longer-term basis. To collect more objective and contextual data and to understand patients even better, researchers can not only use patients' input via EMA, but also use sensors as part of the Mobile Crowdsensing (MCS) approach. In this paper, we examine how researchers have embraced the topic of MCS in the context of EMA through a systematic literature review. This PRISMA-guided review is based on the databases PubMed, Web of Science, and EBSCOhost. It is shown through the results that both EMA research in general and the use of sensors in EMA research are steadily increasing. In addition, most of the studies reviewed used mobile apps to deliver EMA to participants, used a fixed-time prompting strategy, and used signal-contingent or interval-contingent self-assessment as sampling/assessment strategies. The most commonly used sensors in EMA studies are the accelerometer and GPS. In most studies, these sensors are used for simple data collection, but sensor data are also commonly used to verify study participant responses and, less commonly, to trigger EMA prompts. Security and privacy aspects are addressed in only a subset of mHealth EMA publications. Moreover, we found that EMA adherence was negatively correlated with the total number of prompts and was higher in studies using a microinteraction-based EMA (µEMA) approach as well as in studies utilizing sensors. Overall, we envision that the potential of the technological capabilities of smartphones and sensors could be better exploited in future, more automated approaches.

Pandemic Management: Health Data and Public Health Surveillance.

The inefficiency of the healthcare system in addressing pandemics is highlighted after COVID-19 which is mostly rooted in data availability and accuracy. As it is believed we might witness more pandemics in future, our research's main objective is to propose an integrated health system to support healthcare preparedness for future infectious outbreaks and pandemics. The system could support managers and authorities in healthcare and disaster management, and policymakers through data collection, sharing, and analysis.

Investigating the characteristics of health-related data collection tools used in randomised controlled trials in low-income and middle-income countries: protocol for a systematic review.

INTRODUCTION: Health-related data collection tools, including digital ones, have become more prevalent across clinical studies in the last number of years. However, using digital data collection tools in low-income and middle-income countries presents unique challenges. In this review, we aim to provide an overview of the data collection tools currently being used in randomised controlled trials (RCTs) conducted in low-resource settings and evaluate the tools based on the characteristics outlined in the modified Mobile Survey Tool framework. These include functionality, reliability, usability, efficiency, maintainability, portability, effectiveness, cost-benefit, satisfaction, freedom from risk and context coverage. This evidence may provide a guide to selecting a suitable data collection tool for researchers planning to conduct research in low-income and middle-income countries for future studies. METHODS AND ANALYSIS: Searches will be conducted in four electronic databases: PubMed, CINAHL, Web of Science and EMBASE. For inclusion, studies must be a RCT, mention a health-related data collection tool and conducted in a low- and middle-income country. Only studies with available full-text and written in English will be included. The search was restricted to studies published between January 2005 and June 2023. This systematic review will use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) tool. Two review authors will screen the titles and abstracts of search results independently for inclusion. In the initial screening process, the full-text articles will be retrieved if the abstract contains limited information about the study. Disagreements will be resolved through discussion. If the disagreement cannot be resolved, a third author (JO'D) will adjudicate. The study selection process will be outlined in a PRISMA flow-diagram. Data will be analysed using a narrative synthesis approach. The included studies and their outcomes will be presented in a table. ETHICS AND DISSEMINATION: Formal ethical approval is not required as primary data will not be collected in this study. The findings from this systematic review will be published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42023405738.

Federated clustered multi-domain learning for health monitoring.

Wearable Internet of Things (WIoT) and Artificial Intelligence (AI) are rapidly emerging technologies for healthcare. These technologies enable seamless data collection and precise analysis toward fast, resource-abundant, and personalized patient care. However, conventional machine learning workflow requires data to be transferred to the remote cloud server, which leads to significant privacy concerns. To tackle this problem, researchers have proposed federated learning, where end-point users collaboratively learn a shared model without sharing local data. However, data heterogeneity, i.e., variations in data distributions within a client (intra-client) or across clients (inter-client), degrades the performance of federated learning. Existing state-of-the-art methods mainly consider inter-client data heterogeneity, whereas intra-client variations have not received much attention. To address intra-client variations in federated learning, we propose a federated clustered multi-domain learning algorithm based on ClusterGAN, multi-domain learning, and graph neural networks. We applied the proposed algorithm to a case study on stress-level prediction, and our proposed algorithm outperforms two state-of-the-art methods by 4.4% in accuracy and 0.06 in the F1 score. In addition, we demonstrate the effectiveness of the proposed algorithm by investigating variants of its different modules.

Adapting national data systems for donor transition: comparative analysis of experience from Georgia and China.

Health management information systems (HMISs) are essential in programme planning, budgeting, monitoring and evidence-informed decision-making. This paper focuses on donor transitions in two upper-middle-income countries, China and Georgia, and explores how national HMIS adaptations were made and what facilitated or limited successful and sustainable transitions. This comparative analytical case study uses a policy triangle framework and a mixed-methods approach to explore how and why adaptations in the HMIS occurred under the Gavi Alliance and the Global Fund-supported programmes in China and Georgia. A review of published and grey literature, key informant interviews and administrative data analysis informed the study findings. Contextual factors such as the global and country context, and health system and programme needs drove HMIS developments. Other factors included accountability on a national and international level; improvements in HMIS governance by establishing national regulations for clear mandates of data collection and reporting rules and creating institutional spaces for data use; investing in hardware, software and human resources to ensure regular and reliable data generation; and capacitating national players to use data in evidence-based decision-making for programme and transition planning, budgeting and outcome monitoring. Not all the HMIS initiatives supported by donors were sustained and transitioned. For the successful adaptation and sustainable transition, five interlinked and closely coordinated support areas need to be considered: (1) coupling programme design with a good understanding of the country context while considering domestic and external demands for information, (2) regulating appropriate governance and management arrangements enhancing country ownership, (3) avoiding silo HMIS solutions and taking integrative approach, (4) ensuring the transition of funding onto domestic budget and enforcing fulfilment of the government's financial commitments and finally (5) investing in technologies and skilled human resources for the HMIS throughout all levels of the health system. Neglecting any of these elements risks not delivering sustainable outcomes.