Understanding social needs screening and demographic data collection in primary care practices serving Maryland Medicare patients.

BACKGROUND: Health outcomes are strongly impacted by social determinants of health, including social risk factors and patient demographics, due to structural inequities and discrimination. Primary care is viewed as a potential medical setting to assess and address individual health-related social needs and to collect detailed patient demographics to assess and advance health equity, but limited literature evaluates such processes. METHODS: We conducted an analysis of cross-sectional survey data collected from n = 507 Maryland Primary Care Program (MDPCP) practices through Care Transformation Requirements (CTR) reporting in 2022. Descriptive statistics were used to summarize practice responses on social needs screening and demographic data collection. A stepwise regression analysis was conducted to determine factors predicting screening of all vs. a targeted subset of beneficiaries for unmet social needs. RESULTS: Almost all practices (99%) reported conducting some form of social needs screening and demographic data collection. Practices reported variation in what screening tools or demographic questions were employed, frequency of screening, and how information was used. More than 75% of practices reported prioritizing transportation, food insecurity, housing instability, financial resource strain, and social isolation. CONCLUSIONS: Within the MDPCP program there was widespread implementation of social needs screenings and demographic data collection. However, there was room for additional supports in addressing some challenging social needs and increasing detailed demographics. Further research is needed to understand any adjustments to clinical care in response to identified social needs or application of data for uses such as assessing progress towards health equity and the subsequent impact on clinical care and health outcomes.

Usability of an Automated System for Real-Time Monitoring of Shared Decision-Making for Surgery: Mixed Methods Evaluation.

BACKGROUND: Improving shared decision-making (SDM) for patients has become a health policy priority in many countries. Achieving high-quality SDM is particularly important for approximately 313 million surgical treatment decisions patients make globally every year. Large-scale monitoring of surgical patients' experience of SDM in real time is needed to identify the failings of SDM before surgery is performed. We developed a novel approach to automating real-time data collection using an electronic measurement system to address this. Examining usability will facilitate its optimization and wider implementation to inform interventions aimed at improving SDM. OBJECTIVE: This study examined the usability of an electronic real-time measurement system to monitor surgical patients' experience of SDM. We aimed to evaluate the metrics and indicators relevant to system effectiveness, system efficiency, and user satisfaction. METHODS: We performed a mixed methods usability evaluation using multiple participant cohorts. The measurement system was implemented in a large UK hospital to measure patients' experience of SDM electronically before surgery using 2 validated measures (CollaboRATE and SDM-Q-9). Quantitative data (collected between April 1 and December 31, 2021) provided measurement system metrics to assess system effectiveness and efficiency. We included adult patients booked for urgent and elective surgery across 7 specialties and excluded patients without the capacity to consent for medical procedures, those without access to an internet-enabled device, and those undergoing emergency or endoscopic procedures. Additional groups of service users (group 1: public members who had not engaged with the system; group 2: a subset of patients who completed the measurement system) completed user-testing sessions and semistructured interviews to assess system effectiveness and user satisfaction. We conducted quantitative data analysis using descriptive statistics and calculated the task completion rate and survey response rate (system effectiveness) as well as the task completion time, task efficiency, and relative efficiency (system efficiency). Qualitative thematic analysis identified indicators of and barriers to good usability (user satisfaction). RESULTS: A total of 2254 completed surveys were returned to the measurement system. A total of 25 service users (group 1: n=9; group 2: n=16) participated in user-testing sessions and interviews. The task completion rate was high (169/171, 98.8%) and the survey response rate was good (2254/5794, 38.9%). The median task completion time was 3 (IQR 2-13) minutes, suggesting good system efficiency and effectiveness. The qualitative findings emphasized good user satisfaction. The identified themes suggested that the measurement system is acceptable, easy to use, and easy to access. Service users identified potential barriers and solutions to acceptability and ease of access. CONCLUSIONS: A mixed methods evaluation of an electronic measurement system for automated, real-time monitoring of patients' experience of SDM showed that usability among patients was high. Future pilot work will optimize the system for wider implementation to ultimately inform intervention development to improve SDM. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2023-079155.

Ambient air concentrations of plant protection products: Data collection for the combined air concentration database and associated risk assessment.

CropLife Europe collected literature values from monitoring studies measuring air concentrations of Plant Protection Products (PPPs) that may be inhaled by humans located in rural areas but not immediately adjacent to PPP applications. The resulting "Combined Air Concentration Database" (CACD) was used to determine whether air concentrations of PPPs reported by the French "Agency for Food, Environmental and Occupational Health & Safety" (ANSES) are consistent with those measured by others to increase confidence in values of exposure to humans. The results were put into risk assessment context. Results show that 25-90% of samples do not contain measurable PPP concentrations. Measured respirable fractions were below EU default air concentrations used for risk assessment for resident exposure by the European Food Safety Authority. All measured exposures in the CACD were also below established toxicological endpoints, even when considering the highest maximum average reported concentrations and very conservative inhalation rates. The highest recorded air concentration was for prosulfocarb (0.696 µg/m³ measured over 48 h) which is below the EFSA default limit of 1 µg/m³ for low volatility substances. In conclusion, based on the CACD, measured air concentrations of PPPs are significantly lower than EFSA default limits and relevant toxicological reference values.

A Novel Electronic Record System for Documentation and Efficient Workflow for Community Health Workers: Development and Usability Study.

BACKGROUND: The COVID-19 pandemic added to the decades of evidence that public health institutions are routinely stretched beyond their capacity. Community health workers (CHWs) can be a crucial extension of public health resources to address health inequities, but systems to document CHW efforts are often fragmented and prone to unneeded redundancy, errors, and inefficiency. OBJECTIVE: We sought to develop a more efficient data collection system for recording the wide range of community-based efforts performed by CHWs. METHODS: The Communities Organizing to Promote Equity (COPE) project is an initiative to address health disparities across Kansas, in part, through the deployment of CHWs. Our team iteratively designed and refined the features of a novel data collection system for CHWs. Pilot tests with CHWs occurred over several months to ensure that the functionality supported their daily use. Following implementation of the database, procedures were set to sustain the collection of feedback from CHWs, community partners, and organizations with similar systems to continually modify the database to meet the needs of users. A continuous quality improvement process was conducted monthly to evaluate CHW performance; feedback was exchanged at team and individual levels regarding the continuous quality improvement results and opportunities for improvement. Further, a 15-item feedback survey was distributed to all 33 COPE CHWs and supervisors for assessing the feasibility of database features, accessibility, and overall satisfaction. RESULTS: At launch, the database had 60 active users in 20 counties. Documented client interactions begin with needs assessments (modified versions of the Arizona Self-sufficiency Matrix and PRAPARE [Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences]) and continue with the longitudinal tracking of progress toward goals. A user-specific automated alerts-based dashboard displays clients needing follow-up and upcoming events. The database contains over 55,000 documented encounters across more than 5079 clients. Available resources from over 2500 community organizations have been documented. Survey data indicated that 84% (27/32) of the respondents considered the overall navigation of the database as very easy. The majority of the respondents indicated they were overall very satisfied (14/32, 44%) or satisfied (15/32, 48%) with the database. Open-ended responses indicated the database features, documentation of community organizations and visual confirmation of consent form and data storage on a Health Insurance Portability and Accountability Act-compliant record system, improved client engagement, enrollment processes, and identification of resources. CONCLUSIONS: Our database extends beyond conventional electronic medical records and provides flexibility for ever-changing needs. The COPE database provides real-world data on CHW accomplishments, thereby improving the uniformity of data collection to enhance monitoring and evaluation. This database can serve as a model for community-based documentation systems and be adapted for use in other community settings.

The development of an automated assessment system for resistance training movement.

Portable data collection devices and machine learning (ML) have been combined in autonomous movement analysis models for resistance training (RT) movements. However, input features for these models were mostly extracted empirically and subsequent models demonstrated limited interpretability and generalisability to real-world settings. This study aimed to investigate the utility of interpretable and generalisable modelling techniques and several data-driven feature extraction (FE) methods. This was achieved by developing machine learning movement analysis models for the barbell back squat and deadlift using markerless motion capture. 61 participants performed submaximal and maximal repetitions of both RT movements. Movement data was collected using two Azure Kinect cameras. Joint and segment kinematic variables were calculated from the collected depth imaging, and input features were extracted using traditional, manual FE methods and novel data-driven techniques. Classifiers were developed for several predefined technical deviations for both movements. Many of the addressed technical deviations could be classified with good levels of accuracy (≥70%) while the remainder were poor (55%-60%). Additionally, data-driven FE techniques were comparable to previous, traditional FE methods. Interpretable and generalisable modelling techniques can be utilised to good effect for certain classification tasks while data-driven FE techniques did not provide a consistent advantage over traditional FE methods.

Evaluating registry-based trial economics: Results from the STRESS clinical trial.

Background: Registry-based trials have the potential to reduce randomized clinical trial (RCT) costs. However, observed cost differences also may be achieved through pragmatic trial designs. A systematic comparison of trial costs across different designs has not been previously performed. Methods: We conducted a study to compare the current Steroids to Reduce Systemic inflammation after infant heart surgery (STRESS) registry-based RCT vs. two established designs: pragmatic RCT and explanatory RCT. The primary outcome was total RCT design costs. Secondary outcomes included: RCT duration and personnel hours. Costs were estimated using the Duke Clinical Research Institute's pricing model. Results: The Registry-Based RCT estimated duration was 31.9 weeks greater than the other designs (259.5 vs. 227.6 weeks). This delay was caused by the Registry-Based design's periodic data harvesting that delayed site closing and statistical reporting. Total personnel hours were greatest for the Explanatory design followed by the Pragmatic design and the Registry-Based design (52,488 vs 29,763 vs. 24,480 h, respectively). Total costs were greatest for the Explanatory design followed by the Pragmatic design and the Registry-Based design ($10,140,263 vs. $4,164,863 vs. $3,268,504, respectively). Thus, Registry-Based total costs were 32 % of the Explanatory and 78 % of the Pragmatic design. Conclusion: Total costs for the STRESS RCT with a registry-based design were less than those for a pragmatic design and much less than an explanatory design. Cost savings reflect design elements and leveraging of registry resources to improve cost efficiency, but delays to trial completion should be considered.

Trial Participants' Perceptions of the Impact of Ecological Momentary Assessment on Smoking Behaviors: Qualitative Analysis.

Background: Ecological momentary assessment (EMA) is an increasingly used tool for data collection in behavioral research, including smoking cessation studies. As previous addiction research suggests, EMA has the potential to elicit cue reactivity by triggering craving and increasing behavioral awareness. However, there has been limited evaluation of its potential influence on behavior. Objective: By examining the perspectives of research participants enrolled in a tobacco treatment intervention trial, this qualitative analysis aims to understand the potential impact that EMA use may have had on smoking behaviors that may not have otherwise been captured through other study measures. Methods: We performed a qualitative analysis of in-depth interviews with participants enrolled in a pilot randomized controlled trial of a tobacco treatment intervention that used SMS text messaging to collect EMA data on smoking behaviors. In the pilot randomized controlled trial, combustible cigarette and e-cigarette use and smoking-related cravings were measured as part of an EMA protocol, in which SMS text messaging served as a smoking diary. SMS text messaging was intended for data collection only and not designed to serve as part of the intervention. After a baseline assessment, participants were asked to record daily nicotine use for 12 weeks by responding to text message prompts that they received 4 times per day. Participants were prompted to share their experiences with the EMA text messaging component of the trial but were not directly asked about the influence of EMA on their behaviors. Transcripts were coded according to the principles of the framework for applied research. The codes were then examined, summarized, and grouped into themes based on the principles of grounded theory. Results: Interviews were analyzed for 26 participants. The themes developed from the analysis suggested the potential for EMA, in the form of an SMS text messaging smoking diary, to influence participants' smoking behaviors. The perceived impacts of EMA text messaging on smoking behaviors were polarized; some participants emphasized the positive impacts of text messages on their efforts to reduce smoking, while others stressed the ways that text messaging negatively impacted their smoking reduction efforts. These contrasting experiences were captured by themes reflecting the positive impacts on smoking behaviors, including increased awareness of smoking behaviors and a sense of accountability, and the negative impacts on emotions and smoking behaviors, including provoking a sense of guilt and triggering smoking behaviors. Conclusions: The collection of EMA smoking behavior data via SMS text messaging may influence the behaviors and perceptions of participants in tobacco treatment interventions. More research is needed to determine the magnitude of impact and mechanisms, to account for the potential effects of EMA. A broader discussion of the unintended effects introduced by EMA use is warranted among the research community.

Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

Results of multi-actor collaboration in risk analysis: a simplified risk assessment toolkit for rapid detection of emerging risks.

The dynamic field of food safety faces continuous challenges, prompting stakeholders to develop collaborative actions for improved food safety systems. As part of these actions, the EU-FORA fellowship programme was dedicated to a multi-actor collaboration addressing risks of the unregulated mycotoxins T-2 and HT-2 toxins in oats. Critical gaps in risk assessment procedures were identified, leading to a joint effort to develop a strategy for rapid data collection and risk assessment, including the development of a risk assessment toolkit comprising of a training manual and two intuitive Microsoft® Excel files. The toolkit enables efficient data collection and processing, facilitating risk assessment calculations and rapid risk detection. Applying the toolkit to assess T-2 and HT-2 toxin risks in Belgian oats revealed minimal concerns, except for children aged 3-9 years, likely due to an overestimation. The toolkit is available on the FoodSafety4EU Platform and will be refined based on user feedback, promoting better risk assessment practices. This approach empowers stakeholders, from professionals to policymakers, fostering collaboration and enhancing food safety practices.

Opportunities to improve the adoption of health-related quality of life evidence as part of the French Health Technology Assessment process.

OBJECTIVES: Patient's health-related quality of life (HRQoL) is an important outcome measure that is considered by many payers and health technology assessment (HTA) bodies in the evaluation of treatments. We aimed to identify opportunities for HRQoL to be further incorporated into the assessment of the French HTA by comparing three health systems. We put forward recommendations that could bring further innovations to French patients. METHODS: We reviewed methodologies by the French, German and British HTA, and conducted a systematic review of all French (n = 312) and German (n = 175) HTA appraisals from 01 January 2019 to 31 December 2021. We also setup an advisory board of 11 ex-HTA leaders, payers, methodologists, healthcare providers and patient advocates, from France, Britain and Germany, to discuss opportunities to improve acceptance and adoption of HRQoL evidence in France. RESULTS: Our systematic review of HTA appraisals showed a higher HRQoL data rejection rate in France: in > 75% of cases the HRQoL evidence submitted was not accepted for the assessment (usually for methodological reasons, for example, data being considered exploratory; 16-75% of the appraisals mentioned HRQoL evidence, varying by therapeutic area). Overall, we found the French HTA to be more restrictive in its approach than IQWiG. CONCLUSIONS: Based on these findings we articulate collaborative proposals for industry and the HAS to improve acceptance of HRQoL evidence and create a positive feedback loop between HAS and industry along four dimensions (1) patient perception, (2) testing hierarchy, (3) trial design and (4) data collection.

Database quality assessment in research in paramedicine: a scoping review.

BACKGROUND: Research in paramedicine faces challenges in developing research capacity, including access to high-quality data. A variety of unique factors in the paramedic work environment influence data quality. In other fields of healthcare, data quality assessment (DQA) frameworks provide common methods of quality assessment as well as standards of transparent reporting. No similar DQA frameworks exist for paramedicine, and practices related to DQA are sporadically reported. This scoping review aims to describe the range, extent, and nature of DQA practices within research in paramedicine. METHODS: This review followed a registered and published protocol. In consultation with a professional librarian, a search strategy was developed and applied to MEDLINE (National Library of Medicine), EMBASE (Elsevier), Scopus (Elsevier), and CINAHL (EBSCO) to identify studies published from 2011 through 2021 that assess paramedic data quality as a stated goal. Studies that reported quantitative results of DQA using data that relate primarily to the paramedic practice environment were included. Protocols, commentaries, and similar study types were excluded. Title/abstract screening was conducted by two reviewers; full-text screening was conducted by two, with a third participating to resolve disagreements. Data were extracted using a piloted data-charting form. RESULTS: Searching yielded 10,105 unique articles. After title and abstract screening, 199 remained for full-text review; 97 were included in the analysis. Included studies varied widely in many characteristics. Majorities were conducted in the United States (51%), assessed data containing between 100 and 9,999 records (61%), or assessed one of three topic areas: data, trauma, or out-of-hospital cardiac arrest (61%). All data-quality domains assessed could be grouped under 5 summary domains: completeness, linkage, accuracy, reliability, and representativeness. CONCLUSIONS: There are few common standards in terms of variables, domains, methods, or quality thresholds for DQA in paramedic research. Terminology used to describe quality domains varied among included studies and frequently overlapped. The included studies showed no evidence of assessing some domains and emerging topics seen in other areas of healthcare. Research in paramedicine would benefit from a standardized framework for DQA that allows for local variation while establishing common methods, terminology, and reporting standards.

Reconsidering the Use of Population Health Surveys for Monitoring of Mental Health.

Monitoring of the mental health status of the population and assessment of its determinants are 2 of the most relevant pillars of public mental health, and data from population health surveys could be instrumental to support them. Although these surveys could be an important and suitable resource for these purposes, due to different limitations and challenges, they are often relegated to the background behind other data sources, such as electronic health records. These limitations and challenges include those related to measurement properties and cross-cultural validity of the tools used for the assessment of mental disorders, their degree of representativeness, and possible difficulties in the linkage with other data sources. Successfully addressing these limitations could significantly increase the potential of health surveys in the monitoring of mental disorders and ultimately maximize the impact of the relevant policies to reduce their burden at the population level. The widespread use of data from population health surveys, ideally linked to electronic health records data, would enhance the quality of the information available for research, public mental health decision-making, and ultimately addressing the growing burden of mental disorders.

A Mixed-Methods Assessment of the Feasibility of Conducting Neurosurgical Clinical Research in Uganda.

BACKGROUND: Clinical research is necessary to evaluate neurosurgical interventions, yet clinical trials are conducted less frequently in low- and middle-income countries. Because specific barriers, facilitating factors, and strategies for neurosurgical clinical research in Uganda have not been previously identified, this study evaluated neurosurgical providers' perspectives on clinical research and documentation patterns of neurosurgical variables at Mulago National Referral Hospital. METHODS: Retrospective review of 166 neurosurgical patient charts assessed the frequency of documentation of key variables. Twenty-two providers working in neurosurgery participated in 6 focus group discussions with qualitative analysis utilizing the framework method. RESULTS: Chart review showed that primary diagnosis (99.4%), pupil light response (97.6%), and computed tomography scan results (93.3%) were documented for most patients. Cranial nerve exam (61.5%), pupil size (69.9%), and time to neurosurgical intervention (45%) were documented less frequently. On average, Glasgow Coma Scale was documented for 86.6% of days hospitalized, while vital signs were documented for 12.3%. In most focus group discussions, participants identified follow-up, financing, recruitment, time, approval, and sociocultural factors as research barriers. Participants described how the current health workforce facilitates successful research. To improve research capacity, suggested strategies focused on research networks, data collection, leadership, participant recruitment, infrastructure, and implementation. CONCLUSIONS: At Mulago National Referral Hospital, there was variability in the frequency of documentation of neurosurgical variables, which may impact data collection for future studies. While multiple barriers were identified, sociocultural, financing, and time barriers greatly impacted neurosurgical clinical research. Despite that, identified facilitating factors and strategies could be utilized to support neurosurgical research capacity growth.

Development of a Preventive Health Screening Procedure Enabling Supportive Service Planning for Home-Dwelling Older Adults (PORI75): Protocol for an Action Research Study.

BACKGROUND: In Finland, at least 1 in 4 residents will be >75 years of age in 2030. The national aging policy has emphasized the need to improve supportive services to enable older people to live in their own homes for as long as possible. OBJECTIVE: This study aimed to develop a preventive health screening procedure for home-dwelling older adults aged 75 years to enable the use of clinical patient data for purposes of strategic planning of supportive services in primary care. METHODS: The action research method was applied to develop the health screening procedure with selected validated health measures in cooperation with the local practicing interprofessional health care teams from 10 primary care centers in the Social Security Center of Pori, Western Finland (99,485 residents, n=11,938, 12% of them >75 years). The selection of evidence-based validated health measures was based on the national guide to screen factors increasing fall risk and the national functioning measures database. The cut-off points of the selected health measures and laboratory tests were determined in consecutive consensus meetings with the local primary care physicians, with decisions based on internationally validated measures, national current care guidelines, and local policies in clinical practice. RESULTS: The health screening procedure for 75-year-old residents comprised 30 measures divided into three categories: (1) validated self-assessments (9 measures), (2) nurse-conducted screenings (14 measures), and (3) laboratory tests (7 measures). The procedure development process comprised the following steps: (1) inventory and selection of the validated health measures and laboratory tests, (2) training of practical nurses to perform screenings for the segment of 75-year-old residents and to guide them to possible further medical actions, (3) creation of research data from clinical patient data for secondary use purposes, (4) secondary data analysis, and (5) consensus meeting after the pilot test of the health screening procedure for 75-year-old residents procedure in 2019 based on the experiences of health care professionals and collected research data. CONCLUSIONS: The developed preventive health screening procedure for 75-year-old residents enables the use of clinical patient data for purposes of strategic planning of supportive services in primary care if the potential bias by a low participation rate is controlled. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48753.

Qualitative Methodology in Translational Health Research: Current Practices and Future Directions.

Translational health research is an interdisciplinary field aimed at bridging the gap between basic science studies, preventative studies, and clinical practice to improve health-related outcomes. Qualitative research methods provide a unique perspective on the emotional, social, cultural, and contextual factors that influence health and healthcare and thus are recognized as valuable tools for translational health research. This approach can be embedded within a mixed method design which complements the quantitative findings. This methodological paper aims to provide a comprehensive review of the fundamental concepts and methodologies used in qualitative research, emphasizing their utilization and significance in translational health research. Several approaches to qualitative research methodology are discussed in this review, including ethnography, phenomenology, grounded theory, case study, and action research. Theoretical frameworks such as the social-ecological model, intersectionality, and participatory action research are also examined to provide a structure for understanding and interpreting complex health issues. This methodological paper also reviews commonly used sampling techniques such as purposive, snowball, convenience, theoretical, and maximum variation sampling, along with data collection methods such as in-depth interviews, focus groups, observation, document analysis, and participatory methods. Moreover, data analysis techniques such as thematic analysis, grounded theory, content analysis, narrative analysis, and reflexive analysis, are discussed in the context of translational health. Overall, this review highlights the challenges and opportunities of using qualitative methods in current practice, while also discussing future directions and providing valuable guidance and insights to researchers interested in conducting qualitative research in translational health.

Making Home: The Role of Social Networks on Identity, Health, and Quality of Life Among Rural Lesbian and Gay Older Adults.

Background and Objectives: Gay and lesbian older persons face a host of health inequalities related to their identity as they age. Challenges to health access and appropriate social support may be even more exacerbated for those living in rural environments; this may be due to the lack of supportive and affirming social connections. This project aimed to explore and describe the social networks and the relationship of these social networks to identity, health, and quality of life of gay and lesbian individuals in rural communities. Research Design and Methods: Social network data on network type, size, and social capital were collected and supplemented by quantitative questionnaires relating to health, quality of life, marginalization, and identity. Results: Participants (N = 25) were recruited from three states. Thirteen participants self-identified as gay and 12 as lesbian. All but one identified as non-Hispanic White. The average age of all participants was 60.32 years. Findings indicate that rural gay and lesbian individuals develop networks with little consideration for network members' acceptance of their identity. Participants reported an average network size of 9.32 individuals. Gay men reported higher perceptual affinity (.69) than lesbian participants (.62). Lesbian networks showed significantly (p = .0262) greater demographic similarity (.58) than aging gay men's networks (.55). Aging gay men (.89) reported statistically stronger (p = .0078) network ties than aging lesbian females (.78). Among participants in this study, network size is not correlated with the health and quality of life of rural aging lesbian and gay individuals. Still, personal identity congruence does appear to relate to health and quality of life. Discussion and Implications: The findings highlight the collective need to continue research into sexual minority aging and rural sexual minority aging, particularly employing novel methods.

Task Assignment Optimization in Multi-UAV-Assisted WSNs Considering Energy Budget and Sensor Distribution Characteristics.

In emergency situations, such as disaster area monitoring, deadlines for data collection are strict. The task time minimization problem concerning multi-UAV-assisted data collection in wireless sensor networks (WSNs), with different distribution characteristics, such as the geographical or importance of the information of the sensors, is studied. Our goal is to minimize the mission time for UAVs by optimizing their assignment, trajectory, and deployment locations, while the UAV energy constraint is taken into account. For the coupling relationship between the task assignment, trajectory, and hover position, it is not easy to solve the mixed integer non-convex problem directly. The problem is divided into two sub-problems: (1) UAV task assignment problem and (2) trajectory and hover position optimization problem. To solve this problem, an assignment algorithm, based on sensor distribution characteristics (AASDC), is proposed. The simulation results show that the collection time of our scheme is shorter than that of existing comparison schemes when using the same data size.

Observation-based data-gathering method to support the assessment of the use of cultural ecosystem services in urban green spaces.

Urban green spaces (UGS), such as parks, gardens, forests, and green infrastructure, supply numerous regulating, provisioning and cultural ecosystem services to urban communities, which is key for their wellbeing. To effectively plan and design UGS, it is crucial to understand how people use them and the factors that influence their usage. The diverse range of factors includes cultural, socioeconomic, demographic, seasonal, and spatial aspects, which present a challenge for studying these areas. Data collection methods based on observation enable capturing of high-quality data that reflect the behaviours in UGS, providing valuable insights for urban planners and policymakers. Standardised protocols and frameworks facilitate knowledge gathering, allowing researchers and practitioners to build upon evidence for effective urban planning and policymaking. This work aims to develop a method based on a mobile app to collect observation-based data on UGS usage efficiently.•Mobile app to collect georeferenced information on observed activities, basic sociodemographic characteristics, time and seasonal factors, and park characteristics, including the spatial distribution of park recreational equipment.•App optimised for fast and accurate data collection.•Focused on cultural ecosystem services.

A realist review of digitally delivered child development assessment and screening tools: Psychometrics and considerations for future use.

BACKGROUND: Developmental screening improves the detection of developmental concerns, yet numerous children are not screened/assessed. Remote child developmental tool administration has been utilized to increase screening and assessment accessibility. METHOD: We conducted a realist review to: (1) identify existing multi-domain child development assessment and screening tools for children 0-5 years; (2) review psychometric data on their digital (i.e., only administered remotely) administration; and (3) explore contextual factors relevant to their digital administration. We searched APA PsycInfo, MEDLINE, CINAHL, and ERIC to identify tools and papers on their psychometrics. We reference-searched included articles and searched Google for relevant grey literature. RESULTS: Of 33 multi-domain child development tools identified in objective one, five tools (in five studies) were delivered digitally and compared to traditional (e.g., paper) delivery (i.e., objective two). Studies evaluated within-group equivalence reliability (k = 2) and between-group equivalence (k = 3). Within-group equivalence reliability was established for the Vineland Adaptive Behavior Scales, and domains (e.g., gross motor) of the Ages and Stages Questionnaires 2nd edition (ASQ-2) and Revised Prescreening Denver Questionnaire (R-PDQ). Between group equivalence was demonstrated for Developmental Neuropsychological Assessment, 2nd Edition (NEPSY-II) subtests and Bayley Scales of Infant and Toddler Development, 3rd edition (Bayley-3) items. In another between group evaluation, web-based and paper versions of the ASQ-2 were deemed generally equivalent. Digital Bayley-3 inter-observer reliability ranged from 0.82 to 1.0. Examiner support, time, tool modifications, family resources, and comfort promotion supported digital administration. CONCLUSION: Digitally delivered ASQ-2, R-PDQ, Vineland, and Bayley-3 and NEPSY-II components show promise for equivalence with traditional administration.