Passive location tracking through smartphone-based services offers promising avenues for mobility research, yet its reliability and analytical value remain underexplored. This study presents a comprehensive methodology for extracting commuting patterns from Google Maps Timeline (GMT) data and applies it to a 30-day longitudinal dataset on 294 participants, collected in 2024 in Southern Switzerland. We developed and released an open-source data processing methodology to convert raw GMT activity segments into discrete location bins, enabling the detection of significant places (home and workplace) and commuting trips through unsupervised algorithms. Our findings show that GMT achieves a mean location coverage of 72% across study participants and days with a 200-meter distance threshold between consecutive segments, and allows for the reliable identification of commuting trips in days in which study participants self-reported having worked. While GMT presents limitations in data completeness and algorithm transparency, it offers scalable, low-burden alternatives to traditional mobility data collection methods. Future research should explore its applicability across diverse populations and contexts, and consider open-source alternatives for enhanced transparency and control. • Google Maps Timeline (GMT) provides a passive solution for location tracking. • We provide methods to process raw GMT data into significant places and commuting trips. • We test our methods on real-world data from 294 people in Southern Switzerland. • We find a GMT coverage of 72%, and reliable home and workplaces for 65% of study participants. • GMT is a low-burden tool complementing self-reports for policy making and large-scale mobility research.

Although work-related physical disorders among surgeons are increasing globally, with potential detrimental effects on surgical performance and patient care, ergonomics is still overlooked in clinical practice. The aim of this study is to investigate ergonomics problems and perceptions in the operating room in an international cohort of surgeons to obtain baseline data necessary to plan implementation initiatives. A Checklist for Reporting Results of Internet E-Surveys (CHERRIES)-compliant internet-based survey was developed using Google Forms and distributed via surgical societies, professional associations, and collaborative networks between September 2023 and February 2024 to surgeons from different specialties worldwide. The survey consisted of 6 sections, exploring various aspects such as job history, surgical specialty, practice location and role, surgical training, and injuries related to surgical practice. A total of 1,093 responses were received from surgeons in 42 countries. Because of the open distribution model, a precise response rate could not be calculated. The decision to use an online survey as the primary data collection method was driven by several distinct advantages. Primarily, this approach facilitated access to a broad and heterogeneous sample of surgeons encompassing various specialties and geographic locations-an achievement challenging to replicate with conventional survey techniques. The digital format enabled efficient dissemination through established channels, including surgical societies, professional organizations, and collaborative networks, thereby ensuring extensive reach in a cost-effective and timely fashion. Moreover, the anonymity afforded by the online platform encouraged participants to provide honest and uninhibited responses concerning sensitive topics such as musculoskeletal discomfort and ergonomic behaviors, mitigating potential biases linked to social desirability or fear of professional consequences. The flexibility inherent to an internet-based survey also allowed respondents to participate at their convenience, which likely enhanced overall response rates and engagement among busy health care professionals worldwide. Collectively, these attributes positioned the online survey as an optimal and practical tool for capturing comprehensive baseline data on ergonomic issues within the international surgical community. The survey received a total of 1,093 responses. Up to 96.9% of surgeons reported experiencing some musculoskeletal discomfort, which were more commonly associated with laparoscopy (55.4%), followed by open surgery (32.9%). Robotic surgery had the lowest rate of pain (1.1%, P < .001). Surgery-related injuries in 9.7% of cases prevented the surgeon from performing clinical or surgical duties, and in 13.4% of cases musculoskeletal pain necessitated absence from work or job leave. Overall, 31.4% of the respondents implemented risk mitigation strategies in the operating room with microbreaks and intraoperative stretching. Seventy-three percent of the responders have never followed formal training, lectures, or discussions about ergonomics. Laparoscopic surgery significantly impacts surgeons; to mitigate the effects of musculoskeletal disorders on individual surgeons and the broader surgical workforce, innovations such as robotic surgery and ergonomic education may offer potential benefits; these descriptive findings highlight the need for further research to evaluate their role in reducing the burden of work-related musculoskeletal issues.

Healthcare professionals work within an imperfect, multi-faceted system and cannot shoulder the burden of responsibility for unintentional patient harm. Patient safety governance aims to address the challenges of patient safety through monitoring systems and processes to provide assurance of patient safety and quality of care. The evidence suggests that healthcare staff demonstrate mixed views towards patient safety governance processes and varying attitudes towards hospital patient safety climates. This study aims to explore the insights of both healthcare staff and senior healthcare decision makers into patient safety governance and its associated patient safety processes. It aims to capture the attitudes of healthcare staff towards hospital patient safety climates. The researchers intend to identify the gaps in patient safety governance between praxis and theory, with the view of developing recommendations to address these gaps. This research study is convergent parallel in design, with two study strands occurring simultaneously. It is set in four Irish teaching hospitals located in one regional area. A methodological pluralistic approach, using both qualitative and quantitative methods, will be applied to allow the researchers to adopt the most suitable methodology for data collection, analysis and data interpretation to fulfil the study aims. The study consists of three groups. Qualitative methods will apply to Groups 1 and 2, where consenting participants will be given a choice to engage with a focus group or semi-structured interview. The data collected through these methods will be analysed using the six phases of reflexive thematic analysis. Quantitative methods will apply to Group 3, where consenting participants will complete an electronic questionnaire. The quantitative data will be described in statistical terms using the Stata Now statistical package. Data integration will occur during the data interpretation phase, using a weaving approach in a narrative format where the qualitative and quantitative data findings will be compared thematically. The intention of this study is to broaden the corpus of academic understanding into healthcare staff's insights of patient safety processes and their attitudes towards hospital patient safety climates comparatively to evidence-based best practice for patient safety governance. This study will be carried out using a methodological pluralistic approach, allowing the researchers to choose the most appropriate methods for data collection, analysis and interpretation. The researchers will then identify the current gaps in patient safety governance practice in a small group of Irish hospitals in one healthcare region. These gaps will then be assessed and explored with implementation plans developed to address the gaps, through decision makers and policy development within healthcare.

Background:This paper aims to understand whether and how the Italian healthcare context has embraced sustainability accounting and reporting practices. Specifically, it investigates if the sector has developed institutional pressures that drive public healthcare organisations toward the adoption of sustainability disclosure.Methods:The researchers employed document analysis as a qualitative research method for data collection and analysis. The research team analysed a total of 80 institutional and corporate documents, divided into 10 documents from the regional programming phase and 70 from the corporate monitoring phase.Results:The analysis shows that Italian healthcare organisations are lagging in adopting sustainability documents. Furthermore, the analysed disclosures do not refer to the United Nations Sustainable Development Goals (SDGs), as they are compiled according to national legislation designed well before the introduction of the SDGs framework.Discussion & Conclusion:The lack of institutional pressures across public sector organisations has hindered the development of a solid culture of sustainability reporting in the public healthcare sector. This research contributes at two levels: practically, it advances the accounting and reporting literature by examining the availability of such practices in the public sector; theoretically, it sheds light on the development and role of institutional pressures for sustainability reporting in Italian public hospitals.

As algorithm-based decision support tools become increasingly integrated into clinical workflows, particularly with the popularization of artificial intelligence, the conceptualization and operationalization of demographic variables such as sex and gender have implications for how these variables are measured and interpreted. Misalignment between variable labels, response categories, and underlying data sources may introduce measurement error or ambiguity in algorithm inputs, potentially affecting clinical interpretation and downstream decision-making. This concern reflects issues of variable specification rather than terminology alone. The objective of this study is to evaluate how sex and gender are labeled, operationalized, and aligned with underlying source data in clinical decision-support tools. In May 2025, we conducted a cross-sectional review of clinical tools available on MDCalc, a widely-used online repository of clinical decision-support tools derived from biomedical research and clinical guidelines. We assessed tools with a demographic input labeled as sex, gender, or both. Main measures were the presence and operationalization of sex or gender variables within tool interfaces and corresponding primary references. Variable labeling (sex or gender), response categories (e.g., male/female or man/woman), reported data collection methods in primary references, and concordance between tool interfaces and source literature. Tools were also qualitatively categorized by potential clinical impact (high, medium, low). Among 821 tools screened, 84 (10.2%) included a sex or gender variable. Of these, 69 (82.1%) labeled the variable as sex and 15 (17.9%) as gender. Binary response categories were used in 83 tools (98.8%). Sex-gender conflation occurred in 16 tools (19.0%), reflecting inconsistencies between variable labels and response categories used as inputs. Primary references were available for 76 tools (90.5%); among those that explicitly reported sex or gender collection, 18 (25.7%) demonstrated sex-gender conflation. Most tools were classified as having medium (51.2%) or high (33.3%) potential clinical impact. Sex and gender are inconsistently labeled and operationalized in clinical decision-support tools. One in five tools demonstrated misalignment between variable labels, response categories, and underlying source data. Greater conceptual clarity and transparency of sex and gender variables may reduce ambiguity and strengthen the validity, interpretability, and equity of algorithm-based clinical decision tools.

Waste management is a significant global issue resulting from rapid population growth, unchecked consumption patterns, urbanization, and inadequate community participation. The waste management process involves segregation, collection, transportation, responsible disposal, and recycling. Cities with adequate disposal mechanisms and well-planned systems are less susceptible to ineffective waste management. Public participation and government efforts in addressing this issue remain important. Integrating communication channels to inform and educate about waste literacy is essential. This study aims to understand solid waste management initiatives implemented in Kilvelur (Urban Local Body) and the integration of communication channels in addressing waste literacy. The study aims to address the following questions: What solid waste management initiatives has the Kilvelur small urban local body adopted? What are the communication channels used to inform and educate about waste literacy? What are the challenges and gaps in the implementation of waste literacy initiatives at the urban local level? The study employed in-depth interviews with officials and the public from the Kilvelur local administration as the primary qualitative data collection method to explore waste management initiatives and the use and integration of communication channels in promoting waste literacy. Respondents were selected through purposive sampling, as they are directly involved in the design and implementation of waste management initiatives in Kilvelur. The study found that continuous information sharing on waste management significantly increased public responsibility. Effective source segregation is made possible through consistent field visits, rewards, and appreciation. The Kilvelur model shows that proper planning and effective implementation are possible by integrating all communication channels.

The global use of real-world data (RWD) for drug approval and post-marketing surveillance has increased significantly. During 2023 and 2024, the US Food and Drug Administration issued industry guidance, and the European Medicines Agency released real-world evidence framework reports to support regulatory decision making. In Japan, the Pharmaceuticals and Medical Devices Agency promotes the use of RWD, with collective efforts from the government and related industries. This report focuses on electronic health record (EHR) databases in Japan, aiming to (1) organize the characteristics of data generated from such databases, and (2) identify the challenges when using EHR databases for regulatory decision making. This report conducted an internet-based Google search using the keywords 'electronic medical record database' with the condition that the results include any of the keywords 'Japan' or 'real-world data'. Online interviews were conducted with representatives from eight EHR database companies identified as being utilized in Japan, focusing on the characteristics of each EHR database, challenges in their utilization, and future perspectives. The characteristics and limitations of current EHR databases were summarized; they offer broad coverage in terms of patient backgrounds and easier access to clinical laboratory values but are unable to track patients who transfer between hospitals due to lack of data linkage, and there may be loss of information during data abstraction. Data collection methods were mostly retrospective. Critically, there is no overall standardization between the EHR databases. Currently, EHR studies are primarily observational to verify efficacy and safety in real clinical practice and are gradually being used for post-marketing surveillance to support regulatory decision making in Japan. Addressing operational, technical, and methodological challenges in using EHR databases for regulatory approval applications requires efforts from multiple stakeholders, including industry, academia, and government.

Pregnant and lactating women are generally excluded from clinical trials during vaccine development. While the safety, inmunogenicity, efficacy, and effectiveness of the Abdala vaccine against COVID-19 have been demonstrated in the general population, there is a lack of specific information regarding its benefits for pregnant women. Consequently, this study was undertaken to evaluate the safety of the Abdala vaccine in pregnant women and their newborns, as well as to assess the maternal immune response elicited by the vaccination and its capacity for passive immunity transfer to the newborn. A simple cohort observational multicenter study was conducted across five maternity hospital in Havana City, Cuba. A hybrid approach was employed, integrating both retrospective and prospective data collection methods. The study analyzed all events occurring from the first dose of the Abdala vaccine during pregnancy, delivery, and the postpartum period, as well as those related to the fetus-/neonate. To provide contextual data from our settings as a reference for descriptive analyses, statistical information concerning some pregnancy-related and fetal-neonatal events from the same five maternity hospitals in the year 2020 was utilized (historical data). Immunogenicity analyses were conducted in a subgroup of participants from a single maternity hospital, measuring antibodies against the receptor-binding domain of SARS-CoV-2 (Anti-RBD IgG antibodies) and neutralizing antibodies (Nab) against two SARS-CoV-2 strains (D614G and Omicron B.1.1.529) were measured in both maternal and umbilical cord sera. Additionally, anti-IgA antibodies were evaluated in a colostrum samples. Antibody transfer across the placenta and breast milk was also analyzed. Various comparisons were made regarding gestational age at birth, vaccination trimester, timing from vaccination to delivery, and receipt of a booster dose, among other analyses. A formal sample size estimate was not made. Pregnant women who attended the aforementioned hospitals and met the established criteria were included in the study cohort. Descriptive statistics were utilized to characterize the study population. The Wilcoxon sum rank test was used for most immunological evaluations, while logistic regression analyses estimated the effects of different variables. The correlation between anti-RBD IgG titers in maternal and umbilical cord sera was assessed using Pearson's correlation coefficient. All statistical tests were performed at a significance level of p < 0.05. The study was conducted in five Cuban hospitals from December 2021 to June 2022, involving a total of 940 pregnant women women who received the Abdala vaccine during their pregnancy. The common adverse events reported within the 72h post-vaccination with the Abdala vaccine were consistent with previous findings using this vaccine in clinical trials and widespread vaccination campaigns in the general population, predominantly presenting as pain at the injection site (4.9%), somnolence (2.6%), and headache (2.3%). All reported events were of mild intensity. In terms of maternal morbidity, the predominant event noted was SARS-CoV-2 infection, with 83 cases (8.83%), primarily categorized as asymptomatic cases or exhibiting mild symptomatic disease. Overall, IgA titers were detected in 202 colostrum samples, with GMT of 1,227 (95% CI 986; 1,527). High anti-RBD IgG titers were found in 189 maternal and 231 umbilical cord blood samples, with GMT of 1,392.15 (95% CI 1,174; 1,651) and 1,923 (95% CI 1,625; 2,275) respectively. The placental transfer ratio (PTR) of anti-RBD IgG titers had a median of 1.54 (IQR 1.48), indicating effective transfer. The PTR of NAb exceeded 1 for both D614G and Omicron (B.1.1.529), being significantly higher in full-term newborns compared to premature newborns. The ESPIRTA study provides valuable information concerning the application of the Abdala vaccine in specific populations, such as pregnant women, which was not available prior to this study. The safety evaluation of the Abdala vaccine during pregnancy, delivery and the puerperium, as well as in fetus-newborn, revealed no safety signals, as indicated by this cohort study. Elevated anti-RBD IgG titers were detected, in both in maternal serum and cord samples, indicating a positive correlation between them. Moreover, an efficient transfer of IgG antibodies across the placenta was demonstrated. The high anti-IgA titers found in the colostrum may provide an additional advantage regarding the passive transfer of antibodies from mother to newborn through breastfeeding. Furthermore, neutralizing antibodies against two SARS-CoV-2 strains, D614 G and the more recent Omicron B.1.1.529 variant, were identified. Further research is recommended to assess the long-term safety and efficacy of the Abdala vaccine for pregnant women and their newborns.

Optimal management and turnover of accounts receivable are essential for PT XYZ, a distribution company that implements a credit sales system, to maintain smooth cash flow. Against this background, this study aims to analyze the effectiveness of accounts receivable management and the analysis of accounts receivable turnover at PT XYZ from 2022 to 2024. The research method utilizes a descriptive quantitative approach with secondary data sources, where data collection methods were conducted through observation, interviews, and documentation. The analysis methods used in this study are the accounts receivable turnover ratio analysis and the average collection period ratio analysis. The results of the study show that the accounts receivable turnover rate of PT XYZ decreased from 4.59 times in 2022, to 4.09 times in 2023, and further declined to 3.86 times per year in 2024, while the average collection period increased from 80 days to 89 days, and rose again to 95 days. It can be concluded that PT XYZ has managed its accounts receivable turnover rate effectively, but the average age of receivables has increased annually.

This study is the first to examine awareness, knowledge, and attitudes towards dyslexia among the general public in Mainland China. Using an online survey, we collected data on (a) demographics, (b) awareness of dyslexia and other common neurodevelopmental conditions, (c) knowledge of dyslexia causes, symptoms, functional impact, and assessment/intervention, and (d) attitudes towards dyslexia. A total of 1,008 adults from across all major regions of China completed the suvey. Around 70% reported having heard of dyslexia, lower than awareness of autism and ADHD, but higher than that of developmental language disorder. Respondents answered 49% of knowledge items correctly and demonstrated greater knowledge of dyslexia symptoms, followed by functional impact and causes, with weaker knowledge of dyslexia assessment and intervention. Dyslexia awareness and knowledge were higher among younger adults, females, urban residents, non-parents, and those with higher education and income, with some variation across regions. Attitudes towards dyslexia were generally positive, following similar demographic patterns. Although greater awareness was associated with higher levels of knowledge, only dyslexia knowledge uniquely predicted attitudes towards dyslexia after controlling for demographic factors. These indings highlight the need for culturally relevant, awareness-raising campaigns that promote a more accurate understanding of dyslexia. The findings should be interpreted in light of the limitations linked to sampling bias and methods of data collection. Future studies should include the voices of individuals with dyslexia to better understand how social and cultural factors in China influence their lived experiences across development.

Neglected parathyroids: Fluoride's trigger for skeletal fluorosis and endocrine domino effect.

This study assessed the challenges hindering students’ academic performance in public secondary schools and proposed the mechanisms to improve the students’ academic performance in public secondary schools. The study employed a mixed-methods study. The design of the study was Convergent parallel. Data collection methods were questionnaires, semi-structured interviews, documentary review and focus group discussions. The sample size was 381respondents. Among the challenges hindering students’ academic performance was inadequate access to learning materials. Among the mechanisms to put in place for improving academic performance, participation in school activities by parents was mostly indicated. The study concludes that both private and public investment lead to an increase in students’ academic performance, which also needs active participation of parents in school activities. The study recommends that accessibility to learning materials needs to be increased.

Understanding how disability prevalence differs between social and medical models across socioeconomic contexts helps inform policies aimed at improving the well-being of children with disabilities. Additionally, consistent data collection methods are essential to support the shift from medical to social models of disability. This study examined associations between two measures of disability: parent-reported functional limitations based on the Washington Group/UNICEF Child Functioning Module (CFM) and medically documented impairments. We analyzed data from Türkiye's 2022 child survey, which provided a comprehensive assessment of parent-reported functional limitations and medically documented impairments in 14,705 children aged 0-17 from 9,010 households. Using principal component analysis and logistic regression, we identified and tested associations between the two measures. Disability prevalence was 2% based on medically documented impairments but rose to 14.1% when using the CFM, highlighting significant discrepancies across measures. The CFM responses suggested three distinct sub-populations: (1) physical, sensory, and cognitive domains, (2) social domains, and (3) emotional domains, with each group displaying unique socioeconomic characteristics. Additionally, children with medical disability reports were three times more likely to report symptoms of depression or anxiety than those without such reports, underscoring the importance of integrating functional and clinical measures for a comprehensive understanding of disability. The findings indicate that the CFM's functional approach provided a complementary perspective to the medical model, offering global comparability and a fuller profile of childhood disability. This dual-model approach supports disability-inclusive policies by capturing a broader spectrum of functional needs, thereby aiding resource allocation and public awareness initiatives.

BackgroundCo-design methods, which create innovation tailored to the end-user needs and setting, are increasingly used to improve research uptake and impact. Peer review and methodologists have emphasised the need for early, meaningful, and continuous involvement of stakeholders, and the transparent and detailed reporting of co-design methods. The implementation of both complex interventions (such as an integrated care pathway), and technology, into healthcare is difficult and has high failure rates. Designing, implementing, and adapting interventions to ensure they work in the local context requires in-depth understanding of multiple end-users’ needs, processes, and contexts. Achieving this requires early, meaningful, and continuous engagement between multiple end-users. This study aimed to contribute to co-design research by reporting the: 1) process used to develop and test Participatory Rapid Appraisal and Focus Groups methods to co-design integrated care. 2) details of how the method was applied in the GERONTE project. 3) core steps involved in this co-design method (to facilitate use and/ or adaptation of the method).AimThe study aimed to develop, test, and evaluate a co-design method that: I. enabled early, continuous, and meaningful engagement of multiple end-users in different locations and across different design iterations. II. enabled timely feedback and checking between the end-users and design team. III. optimised end-users participation by being flexible in the time, duration, and method of data collection and feedback.Materials and methodsThe Participatory Rapid Appraisal and Focus Group to co-design integrated care method was developed in four stages. The first stage involved defining the project’s co-design needs and reviewing the co-design literature to identify how to meet these. GERONTE aimed to co-design, evaluate, and prepare for EU-wide deployment, an integrated technology-supported care pathway for older adults with cancer and other morbidities. Focus Groups and Participatory Rapid Appraisal, in combination, were chosen as an empirically-based and practical approach. Focus Groups (FG) provided a participatory-based way to collect data in order to identify and agree multiple stakeholders’ needs and collective priorities. Participatory Rapid Appraisal (PRA) provided a timely way; to gain participant feedback on the data collected; and, to ensure accuracy in the data sent to the pathway and technology design teams. The second stage involved applying the method in the GERONTE Project (using meetings between the project team, technologists, and older adults to develop a co-design protocol for the project). The third stage involved the use, refinement, evaluation, and reporting of the co-design method. The fourth stage, evaluation of the method, is ongoing.Results and discussionThis study resulted in the development of a structured approach to using Participatory Rapid Appraisal and Focus Groups in combination to co-design technology-supported integrated care. This method is proposed as an evidenced-based, practical, user-friendly way to co-design (or adapt an existing design) an integrated technology-supported care pathway. This co-design method involves three cycles of design. Each cycle involves multidisciplinary FG to collect semi-structured data followed by rapid analysis and feedback of the FG data to the participants to design or refine the intervention.

Digital twins (DTs) are vital tools to (1) model products or systems at their design stages and (2) monitor systems' conditions and predict their lifespans in their deployment stages. However, not many real-world case studies of DTs have been reported in literature to show significant benefits to Small and Medium sized Enterprises (SMEs). In this paper, DTs are proposed to predict the lifespans of used resources to pursue the sustainability of Reconfigurable Manufacturing Systems (RMSs). To illustrate the potential applications of DTs in enhancing the sustainability of real-world SMEs, a Technical Assistive Project (TAP) for the assessment of lifespans of materials storage racks is presented. The background and data collection methods are introduced, and digital models for 4 selective racks are developed to evaluate their Factor of Safety (FoS) subject to the worst loading scenarios. Parametric design studies are defined and conducted to investigate the dependence of FoS on varying loads. The results support managers' scientific decision-makings on reusing and recycling manufacturing resources in Sustainable Manufacturing.

Digital health technologies have untapped potential to transform community health systems, and they are underutilized for chronic HIV care and electronic data management in low- and middle-income countries. We describe the design, development, and use of a mobile health application in community-based HIV prevention, care, and treatment programs implemented in Ethiopia since 2017. Initially, these programs utilized aggregate data collection methods, which were fragmented, non-uniform, and largely paper-based, posing challenges to data quality and data use. Local software developers applied user-centered methods to build a Unified Data System (UDS), an innovative digital health solution aimed at standardizing case management and routine data collection procedures. Developers involved end-users, including frontline community health workers (CHWs) and program managers, in the design and development process. They also conducted field visits to understand and assess user activities and needs. Developers and program staff conducted field testing, and they made design changes iteratively to incorporate user feedback. Local implementing partners deployed 950 CHWs to use the UDS for HIV service delivery and client-level data collection offline. Data were stored centrally in the CommCare HQ web service backed by a local analytics server. The UDS was linked to Power BI for advanced data analytics and visualization. Data validation tests were performed prior to indicator computation and reporting to the next level. 1,766 mobile accounts were opened for CHWs, of which 1,628 (92.2%; 95% confidence interval [CI]=90.8%, 93.4%) have submitted data. An additional 368 of 392 web accounts (93.9%; 95% CI=91.0%, 96.0%) have been used by program managers and monitoring and evaluation experts to access the dashboard. The UDS has eliminated the tedious, manual, paper-based work associated with data (dis)aggregation and reporting by frontline CHWs and local implementing partners. Hence, the number of days to access client-level data by the local partners was reduced from 1 month to just 1 day, and the time to report on activity performance was shortened from 5 days to a half-day. Data completeness was nearly 100% and data validation tests demonstrated no invalid data elements or errors. Generally, there was a high degree of digital health technology utilization by frontline CHWs and local implementing partners for standardized HIV care, high-quality data collection, and making data-informed decisions. Lessons learned from the UDS implementation could be adapted not only to support community HIV programming but also to strengthen national electronic community health information systems.

The determinants of foreign interventions, be they military interventions or other forms of foreign involvement, are important for modern international relations and conflict studies. Nevertheless, major methodological problems with the analysis are often overlooked. This paper proposes modeling interventions as a two-stage decision-making process. The first stage determines whether a specific target state is intervenable from the perspective of a potential intervener, while the actual intervention target is selected among intervenable targets at the second stage. On this basis, we propose two solutions that allow obtaining estimates for predictors of an intervention: a statistical model that explicitly accounts for the two-stage nature of the data-generating process, and near-misses sampling. The two approaches are similar in that they treat intervention as a two-stage decision-making process. The authors utilize the second approach to create a sample of non-case observations. Two methods of data collection are used: matching and extracting information from open sources (media articles, reports, official documents). The authors conduct correlation analysis for several sample construction techniques to evaluate differences in empirical significance. The implications of the application of different sampling methods for the study of interventions are discussed.

Artificial Intelligence (AI) is revolutionizing many fields including food safety. In food safety, the available data generated within the agrifood systems can potentially feed into AI applications. This review presents an overview of the use of AI in different fields of food safety. The study introduces a framework of AI in food safety, focusing on the research domain, application context, data collection method, and AI technique. The AI tool ASReview, which uses active learning to select top-priority papers, was used to conduct the study in a systematic way. Over 150 peer-reviewed journal publications were reviewed and described according to this framework. The review concludes with a summary of the challenges for AI in food safety and an outlook of future opportunities for AI in food safety.

From Theory to Practice

ABSTRACTIntroductionFarmwork is a hazardous occupation that is particularly vulnerable to the impacts of climate change. Data collection methods are needed to understand the hazards affecting farmworkers. The objective of this study is to share lessons learned regarding the feasibility and acceptability of using wearable technology to assess the role of heat exposure on health indicators among farmworkers in Eastern North Carolina.MethodsAll participants were Latino men farmworker adults (18+ years) working in Eastern North Carolina who wore a wearable health tracker for 90 days. The participants were asked to wear the device day and night to collect information on heart rate, blood oxygenation, skin temperature variation, breathing rate, sleep, and stress. Participants were recruited with a community partner across six counties in the region.ResultsExisting community relationships with farmworkers facilitated adoption of new technologies. The participants found the wearables acceptable and easy to use. Wearable feasibility was dependent on consistent broadband internet for data uploads; however, broadband availability was low (35.7%–71.1%) across counties. The vendor's infrastructure (i.e., device and app) limited who could be recruited for the study. Climate impacted the expected length of study participation as droughts and floods cut the growing and harvesting season short, which impacted data collection.ConclusionsTesting and consideration of the structural strengths and constraints are needed for selection of data collection instruments. Research protocols need to be nimble to guarantee successful data collection for climate‐related research with minoritized workers such as farmworkers in the United States.