From physiological complexity to data interactions-A case study of recordings from exercise monitoring.

The popularity of nonlinear analysis has been growing simultaneously with the technology of effort monitoring. Therefore, considering the simple methods of physiological data collection and the approaches from the information domain, we proposed integrating univariate and bivariate analysis for the rest and effort comparison. Two sessions separated by an intensive training program were studied. Nine subjects participated in the first session (S1) and seven in the second session (S2). The protocol included baseline (BAS), exercise, and recovery phase. During all phases, electrocardiogram (ECG) was recorded. For the analysis, we selected corresponding data lengths of BAS and exercise usually lasting less than 5 min. We found the utility of the differences between original data and their surrogates for sample entropy Sdiff and Kullback-Leibler divergence KLDdiff. Sdiff of heart rate variability was negative in BAS and exercise but its sensitivity for phases discrimination was not satisfactory. We studied the bivariate analysis of RR intervals and corresponding QT peaks by Interlayer Mutual Information (IMI) and average edge overlap (AVO) markers. While the IMI parameter decreases in exercise conditions, AVO increased in effort compared to BAS. These findings conclude that researchers should consider a bivariate analysis of extracted RR intervals and corresponding QT datasets, when only ECG is recorded during tests.

On investigating drivers' attention allocation during partially-automated driving.

The use of partially-automated systems require drivers to supervise the system functioning and resume manual control whenever necessary. Yet literature on vehicle automation show that drivers may spend more time looking away from the road when the partially-automated system is operational. In this study we answer the question of whether this pattern is a manifestation of inattentional blindness or, more dangerously, it is also accompanied by a greater attentional processing of the driving scene. Participants drove a simulated vehicle in manual or partially-automated mode. Fixations were recorded by means of a head-mounted eye-tracker. A surprise two-alternative forced-choice recognition task was administered at the end of the data collection whereby participants were quizzed on the presence of roadside billboards that they encountered during the two drives. Data showed that participants were more likely to fixate and recognize billboards when the automated system was operational. Furthermore, whereas fixations toward billboards decreased toward the end of the automated drive, the performance in the recognition task did not suffer. Based on these findings, we hypothesize that the use of the partially-automated driving system may result in an increase in attention allocation toward peripheral objects in the road scene which is detrimental to the drivers' ability to supervise the automated system and resume manual control of the vehicle.

Virtual Interviews and the Pediatric Emergency Medicine Match Geography: A National Survey.

Introduction: Virtual interviews (VI) are now a permanent part of pediatric emergency medicine (PEM) recruitment, especially given the cost and equity advantages. Yet inability to visit programs in person can impact decision-making, leading applicants to apply to more programs. Moreover, the cost advantages of VI may encourage applicants to apply to programs farther away than they might otherwise have been willing or able to travel. This could create unnecessary strain on programs. We conducted this study to determine whether PEM fellowship applicants would apply to a larger number of programs and in different geographic patterns with VI (2020 and 2021) as compared to in-person interviews (2018 and 2019). Methods: We conducted an anonymous national survey of all PEM fellows comparing two cohorts: current fellows who interviewed inperson (applied in 2018/2019) and fellows who underwent VIs in 2020/2021 (current fellows and those recently matched in 2021). The study took place in March-April 2022. Questions focused on geographic considerations during interviews and the match. We used descriptive statistics, chi-square and t-tests for analysis. Results: Overall response rate was 42% (231/550); 32% (n = 74) interviewed in person and 68% (n = 157) virtually. Fellows applied to a median of 4/6 geographic regions (interquartile range 2, 5). Most applied for fellowship both in the same region as residency (216, 93%) and outside (192, 83%). Only the Pacific region saw a statistically significant increase in applicants during VI (59.9% vs 43.2%, P = 0.02). There was no statistical difference in the number of programs applied to during in-person vs VI (mean difference (95% confidence interval 0.72, -2.8 - 4.2). A majority matched in their preferred state both during VI (60.4%) and in-person interviews (65.7%). The difference was not statistically significant (P = 0.45). Conclusion: While more PEM fellowship applicants applied outside the geographic area where their residency was and to the Pacific region, there was no overall increase in the number of programs or geographic areas PEM applicants applied to during VI as compared to in-person interview seasons. As this was the first two years of VI, ongoing data collection will further identify trends and the impactof VI.

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.

Understanding the risks of co-exposures in a changing world: a case study of dual monitoring of the biotoxin domoic acid and Vibrio spp. in Pacific oyster.

Assessing the co-occurrence of multiple health risk factors in coastal ecosystems is challenging due to the complexity of multi-factor interactions and limited availability of simultaneously collected data. Understanding co-occurrence is particularly important for risk factors that may be associated with, or occur in similar environmental conditions. In marine ecosystems, the co-occurrence of harmful algal bloom toxins and bacterial pathogens within the genus Vibrio may impact both ecosystem and human health. This study examined the co-occurrence of Vibrio spp. and domoic acid (DA) produced by the harmful algae Pseudo-nitzschia by (1) analyzing existing California Department of Public Health monitoring data for V. parahaemolyticus and DA in oysters; and (2) conducting a 1-year seasonal monitoring of these risk factors across two Southern California embayments. Existing public health monitoring efforts in the state were robust for individual risk factors; however, it was difficult to evaluate the co-occurrence of these risk factors in oysters due to low number of co-monitoring instances between 2015 and 2020. Seasonal co-monitoring of DA and Vibrio spp. (V. vulnificus or V. parahaemolyticus) at two embayments revealed the co-occurrence of these health risk factors in 35% of sampled oysters in most seasons. Interestingly, both the overall detection frequency and co-occurrence of these risk factors were considerably less frequent in water samples. These findings may in part suggest the slow depuration of Vibrio spp. and DA in oysters as residual levels may be retained. This study expanded our understanding of the simultaneous presence of DA and Vibrio spp. in bivalves and demonstrates the feasibility of co-monitoring different risk factors from the same sample. Individual programs monitoring for different risk factors from the same sample matrix may consider combining efforts to reduce cost, streamline the process, and better understand the prevalence of co-occurring health risk factors.

Remote Monitoring and Data Collection for Decentralized Clinical Trials.

Importance: Less than 5% of patients with cancer enroll in a clinical trial, partly due to financial and logistic burdens, especially among underserved populations. The COVID-19 pandemic marked a substantial shift in the adoption of decentralized trial operations by pharmaceutical companies. Objective: To assess the current global state of adoption of decentralized trial technologies, understand factors that may be driving or preventing adoption, and highlight aspirations and direction for industry to enable more patient-centric trials. Design, Setting, and Participants: The Bloomberg New Economy International Cancer Coalition, composed of patient advocacy, industry, government regulator, and academic medical center representatives, developed a survey directed to global biopharmaceutical companies of the coalition from October 1 through December 31, 2022, with a focus on registrational clinical trials. The data for this survey study were analyzed between January 1 and 31, 2023. Exposure: Adoption of decentralized clinical trial technologies. Main Outcomes and Measures: The survey measured (1) outcomes of different remote monitoring and data collection technologies on patient centricity, (2) adoption of these technologies in oncology and all therapeutic areas, and (3) barriers and facilitators to adoption using descriptive statistics. Results: All 8 invited coalition companies completed the survey, representing 33% of the oncology market by revenues in 2021. Across nearly all technologies, adoption in oncology trials lags that of all trials. In the current state, electronic diaries and electronic clinical outcome assessments are the most used technology, with a mean (SD) of 56% (19%) and 51% (29%) adoption for all trials and oncology trials, respectively, whereas visits within local physician networks is the least adopted at a mean (SD) of 12% (18%) and 7% (9%), respectively. Looking forward, the difference between the current and aspired adoption rate in 5 years for oncology is large, with respondents expecting a 40% or greater absolute adoption increase in 8 of the 11 technologies surveyed. Furthermore, digitally enabled recruitment, local imaging capabilities, and local physician networks were identified as technologies that could be most effective for improving patient centricity in the long term. Conclusions and Relevance: These findings may help to galvanize momentum toward greater adoption of enabling technologies to support a new paradigm of trials that are more accessible, less burdensome, and more inclusive.

Validity and reliability of the Foot Care Scale for Older Diabetics in Turkish society.

BACKGROUND: Older patients with diabetes have behaviors and practices in foot care that differ from those of younger patients. There is a need for a tool to assess the foot care of patients with diabetes who are over the age of 65 years. PURPOSE: This study aimed to assess the validity and reliability of the long and short versions of the Foot Care Scale for Older Diabetics (FCS-OD) in Turkish society. METHODS: A total of 172 older patients with diabetes participated in the study. Language validity, content validity, construct validity, Cronbach's alpha coefficient value, item-scale correlations, parallel form reliability, and test-retest correlations were used to assess the Turkish version of FCS-OD. A patient identification form, FCS-OD, Diabetic Foot Care Self-Efficacy Scale, and Foot Self-Care Behavior Scale were used for data collection. RESULTS: Turkish versions of the FCS-OD, both short and long versions, were at acceptable levels regarding their content (content validity index: 0.964, 0.975) and construct (factor loadings > 0.4). Both versions of the scale showed a high level of internal consistency as demonstrated by Cronbach's alpha values (short version, 0.802; long version, 0.905) and item-scale correlations (> 0.3). Both versions of the scale were stable over time and compared to the parallel forms. CONCLUSIONS: Both versions of the scale were found to be valid and reliable for Turkish society with regard to psychometric properties.

Birthweight trends and their explanatory factors in Hungary between 1999 and 2018: an analysis of the Hungarian Tauffer registry.

BACKGROUND: The increasing birthweight trend stopped and even reversed in several high income countries in the last 20 years, however the reason for these changes is not well characterized. We aimed to describe birthweight trends of term deliveries in Hungary between 1999 and 2018 and to investigate potential maternal and foetal variables that could drive these changes. METHODS: We analysed data from the Hungarian Tauffer registry, a compulsory anonymized data collection of each delivery. We included all singleton term deliveries in 1999-2018 (n = 1,591,932). We modelled birthweight trends separately in 1999-2008 and 2008-2018 in hierarchical multiple linear regression models adjusted for calendar year, newborn sex, maternal age, gestational age at delivery, and other important determinants. RESULTS: Median birthweights increased from 3250/3400 g (girl/boy) to 3300/3440 g from 1999 to 2008 and decreased to 3260/3400 g in 2018. When we adjusted for gestational age at delivery the increase in the first period became more pronounced (5.4 g/year). During the second period, similar adjustment substantially decreased the rate of decline from 2.5 to 1.4 g/year. Further adjustment for maternal age halved the rate of increase to 2.4 g/year in the first period. During the second period, adjustment for maternal age had little effect on the estimate. CONCLUSIONS: Our findings of an increasing birthweight trend (mostly related to the aging of the mothers) in 1999-2008 may forecast an increased risk of cardiometabolic diseases in offsprings born in this period. In contrast, the decreasing birthweight trends after 2008 may reflect some beneficial effects on perinatal morbidity. However, the long-term effect cannot be predicted, as the trend is mostly explained by the shorter pregnancies.

Birthweights showed an increase followed by a decrease in several high income countries in the last 20 years, however the reasons for these changes is not well described. Thus, we aimed to investigate birthweight trends and their potential explanatory factors in Hungary between 1999 and 2018. We used registry data of all deliveries from Hungary in 1999­2018 (n = 1 591 932). Birthweights increased from 3250/3400 g (girl/boy) to 3300/3440 g from 1999 to 2008 and decreased to 3260/3400 g until 2018. Maternal age explained approximately half of increase in the first period, while a substantial part of the decrease in the second period was explained by the presence of shorter pregnancies. The increasing birthweights in 1999­2008 may forecast an increased risk of cardiometabolic diseases in offsprings born in this period. In contrast, the decreasing birthweight trends after 2008 may reflect some beneficial effects on perinatal morbidity. However, its long-term consequences cannot be predicted, as the trend is mostly explained by the shorter pregnancies.

Introducing the Pi-CON Methodology to Overcome Usability Deficits during Remote Patient Monitoring.

The adoption of telehealth has soared, and with that the acceptance of Remote Patient Monitoring (RPM) and virtual care. A review of the literature illustrates, however, that poor device usability can impact the generated data when using Patient-Generated Health Data (PGHD) devices, such as wearables or home use medical devices, when used outside a health facility. The Pi-CON methodology is introduced to overcome these challenges and guide the definition of user-friendly and intuitive devices in the future. Pi-CON stands for passive, continuous, and non-contact, and describes the ability to acquire health data, such as vital signs, continuously and passively with limited user interaction and without attaching any sensors to the patient. The paper highlights the advantages of Pi-CON by leveraging various sensors and techniques, such as radar, remote photoplethysmography, and infrared. It illustrates potential concerns and discusses future applications Pi-CON could be used for, including gait and fall monitoring by installing an omnipresent sensor based on the Pi-CON methodology. This would allow automatic data collection once a person is recognized, and could be extended with an integrated gateway so multiple cameras could be installed to enable data feeds to a cloud-based interface, allowing clinicians and family members to monitor patient health status remotely at any time.

Designing user-centered decision support systems for climate disasters: What information do communities and rescue responders need during floods?

Flooding events are the most common natural hazard globally, resulting in vast destruction and loss of life. An effective flood emergency response is necessary to lessen the negative impacts of flood disasters. However, disaster management and response efforts face a complex scenario. Simultaneously, regular citizens attempt to navigate the various sources of information being distributed and determine their best course of action. One thing is evident across all disaster scenarios: having accurate information and clear communication between citizens and rescue personnel is critical. This research aims to identify the diverse needs of two groups, rescue operators and citizens, during flood disaster events by investigating the sources and types of information they rely on and information that would improve their responses in the future. This information can improve the design and implementation of existing and future spatial decision support systems (SDSSs) during flooding events. This research identifies information characteristics crucial for rescue operators and everyday citizens' response and possible evacuation to flooding events by qualitatively coding survey responses from rescue responders and the public. The results show that including local input in SDSS development is crucial for improving higher-resolution flood risk quantification models. Doing so democratizes data collection and analysis, creates transparency and trust between people and governments, and leads to transformative solutions for the broader scientific community.

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.

Insect detect: An open-source DIY camera trap for automated insect monitoring.

Insect monitoring is essential to design effective conservation strategies, which are indispensable to mitigate worldwide declines and biodiversity loss. For this purpose, traditional monitoring methods are widely established and can provide data with a high taxonomic resolution. However, processing of captured insect samples is often time-consuming and expensive, which limits the number of potential replicates. Automated monitoring methods can facilitate data collection at a higher spatiotemporal resolution with a comparatively lower effort and cost. Here, we present the Insect Detect DIY (do-it-yourself) camera trap for non-invasive automated monitoring of flower-visiting insects, which is based on low-cost off-the-shelf hardware components combined with open-source software. Custom trained deep learning models detect and track insects landing on an artificial flower platform in real time on-device and subsequently classify the cropped detections on a local computer. Field deployment of the solar-powered camera trap confirmed its resistance to high temperatures and humidity, which enables autonomous deployment during a whole season. On-device detection and tracking can estimate insect activity/abundance after metadata post-processing. Our insect classification model achieved a high top-1 accuracy on the test dataset and generalized well on a real-world dataset with captured insect images. The camera trap design and open-source software are highly customizable and can be adapted to different use cases. With custom trained detection and classification models, as well as accessible software programming, many possible applications surpassing our proposed deployment method can be realized.

EMinsight: a tool to capture cryoEM microscope configuration and experimental outcomes for analysis and deposition.

The widespread adoption of cryoEM technologies for structural biology has pushed the discipline to new frontiers. A significant worldwide effort has refined the single-particle analysis (SPA) workflow into a reasonably standardized procedure. Significant investments of development time have been made, particularly in sample preparation, microscope data-collection efficiency, pipeline analyses and data archiving. The widespread adoption of specific commercial microscopes, software for controlling them and best practices developed at facilities worldwide has also begun to establish a degree of standardization to data structures coming from the SPA workflow. There is opportunity to capitalize on this moment in the maturation of the field, to capture metadata from SPA experiments and correlate the metadata with experimental outcomes, which is presented here in a set of programs called EMinsight. This tool aims to prototype the framework and types of analyses that could lead to new insights into optimal microscope configurations as well as to define methods for metadata capture to assist with the archiving of cryoEM SPA data. It is also envisaged that this tool will be useful to microscope operators and facilities looking to rapidly generate reports on SPA data-collection and screening sessions.

[Registration of national health registry-based research]. / Registrering av forskning baserad på nationella hälsoregister.

In medical research as a whole, frequent inaccurate or biased findings are of international concern. One measure against reporting biases is study registration before the start of data collection (preregistration), preferably together with the statistical analysis plan. This meta-research study systematically evaluated registration of Swedish observational research based on national health registries. In a random sample of registry-based observational studies published 2010-2022, very few were preregistered with a publicly available analysis plan (<1 procent). Ideas from the meta-research literature can be leveraged to strengthen the brand of Swedish registry-based observational studies and counteract reporting bias.

FoodEx2 Harmonization of the Food Consumption Database from the Italian IV SCAI Children's Survey.

Estimating the habitual food and nutrient intakes of a population is based on dietary assessment methods that collect detailed information on food consumption. Establishing the list of foods to be used for collecting data in dietary surveys is central to standardizing data collection. Comparing foods across different data sources is always challenging. Nomenclatures, detail, and classification into broad food groups and sub-groups can vary considerably. The use of a common system for classifying and describing foods is an important prerequisite for analyzing data from different sources. At the European level, EFSA has addressed this need through the development and maintenance of the FoodEx2 classification system. The aim of this work is to present the FoodEx2 harmonization of foods, beverages, and food supplements consumed in the IV SCAI children's survey carried out in Italy. Classifying foods into representative food categories predefined at European level for intake and exposure assessment may lead to a loss of information. On the other hand, a major advantage is the comparability of data from different national databases. The FoodEx2 classification of the national food consumption database represented a step forward in the standardization of the data collection and registration. The large use of FoodEx2 categories at a high level of detail (core and extended terms) combined with the use of descriptors (facets) has minimized information loss and made the reference food categories at country level comparable with different food databases at national and international level.

'Joining the Dots: Linking Prenatal Drug Exposure to Childhood and Adolescence' - research protocol of a population cohort study.

INTRODUCTION: Prenatal drug exposure (PDE) is one of the most important causes of child harm, but comprehensive information about the long-term outcomes of the families is difficult to ascertain. The Joining the Dots cohort study uses linked population data to understand the relationship between services, therapeutic interventions and outcomes of children with PDE. METHODS AND ANALYSIS: Information from routinely collected administrative databases was linked for all births registered in New South Wales (NSW), Australia between 1 July 2001 and 31 December 2020 (n=1 834 550). Outcomes for seven mutually exclusive groups of children with varying prenatal exposure to maternal substances of addiction, including smoking, alcohol, prescription/illicit drugs and neonatal abstinence syndrome will be assessed. Key exposure measures include maternal drug use type, maternal social demographics or social determinants of health, and maternal physical and mental health comorbidities. Key outcome measures will include child mortality, academic standardised testing results, rehospitalisation and maternal survival. Data analysis will be conducted using Stata V.18.0. ETHICS AND DISSEMINATION: Approvals were obtained from the NSW Population and Health Services Research Ethics Committee (29 June 2020; 2019/ETH12716) and the Australian Capital Territory Health Human Research Ethics Committee (11 October 2021; 2021-1231, 2021-1232, 2021-1233); and the Aboriginal Health and Medical Research Council (5 July 2022; 1824/21), and all Australian educational sectors: Board of Studies (government schools), Australian Independent Schools and Catholic Education Commission (D2014/120797). Data were released to researchers in September 2022. Results will be presented in peer-reviewed academic journals and at international conferences. Collaborative efforts from similar datasets in other countries are welcome.

Understanding the implementation and sustainability needs of evidence-based programs for racial and ethnic minoritized older adults in under-resourced communities with limited aging services.

BACKGROUND: Evidence-based programs (EBPs) for older adults effectively improve health outcomes. However, there is a limited understanding of the unique needs of service providers as they consider adopting, implementing, and maintaining programs for older minority adults in low-income communities with limited aging services. METHODS: We conducted semi-structured interviews with key informants of community-based organizations (CBOs) to understand implementation and sustainability needs of CBOs within four racial and ethnically diverse Los Angeles County geographic areas. We performed thematic analysis of interview transcripts. RESULTS: Interviews were conducted with representatives from 25 senior-serving agencies providing aging-related EBPs. CBO representatives reported implementing EBPs in 8 domains: Falls Prevention (68%), Mental Health (64%), Caregiver Health (48%), Chronic Disease Management (48%), Diabetes Management (36%), Arthritis Management (28%), Physical Activity (24%), and Multiple Conditions Management (8%). Themes are presented using the six domains of the Bass and Judge framework for factors impacting successful and sustained EBP implementation. CBOs in low-income and diverse communities described unique challenges with tailoring interventions based on local community context (literacy, language), cultural context, and locally available resources (technology, safe community spaces, transportation) and faced resource-intensive administrative burdens through staff turnover, data collection, sustainable funding, and networking. CONCLUSIONS: Serving racial and ethnic communities has unique challenges that require tailored approaches and additional resources to ensure equitable access to EBPs for all communities. We describe suggestions for enhancing the effective adoption of EBPs among service agencies in under-resourced and diverse aging communities serving populations with aging-related health disparities.

Quantifying holistic capacity response and healthcare resilience in tackling COVID-19: Assessment of country capacity by MCDM.

The resilience of a country during the COVID-19 pandemic was determined based in whether it was holistically prepared and responsive. This resilience can only be identified through systematic data collection and analysis. Historical evidence-based response indicators have been proven to mitigate pandemics like COVID-19. However, most databases are outdated, requiring updating, derivation, and explicit interpretation to gain insight into the impact of COVID-19. Outdated databases do not show a country's true preparedness and response capacity, therefore, it undermines pandemic threat. This study uses up-to-date evidence-based pandemic indictors to run a cross-country comparative analysis of COVID-19 preparedness, response capacity, and healthcare resilience. PROMETHEE-a multicriteria decision making (MCDM) technique-is used to quantify the strengths (positive) and weaknesses (negative) of each country's COVID-19 responses, with full ranking (net) from best to least responsive. From 22 countries, South Korea obtained the highest net outranking value of 0.1945, indicating that it was the most resilient, while Mexico had the lowest (-0.1428). Although countries were underprepared, there was a robust response to the pandemic, especially in developing countries. This study demonstrates the performance and response capacity of 22 key countries to resist COVID-19, from which other countries can compare their statutory capacity ranking in order to learn/adopt the evidence-based responses of better performing countries to improve their resilience.

COCCOS study: Developing a transition program for adolescents with chronic conditions using Experience-Based Co-Design. A study protocol.

BACKGROUND: During adolescence, adolescents and young adults (AYAs) are expected to transfer their care from the pediatric environment towards an adult-focused setting. To prevent an abrupt transfer of care, it is recommended to provide AYAs with chronic conditions an adequate transition program. The aim of this paper is to describe the study protocol for the development of a transition program for AYAs with common chronic conditions (COCCOS study), using the Experience-Based Co-Design (EBCD) methodology. METHODS AND ANALYSIS: A qualitative, participatory study is conducted in Flanders (Belgium). Study participants are AYAs (n≥15, 14-25 years old, diagnosed with type 1 diabetes, asthma, or obesity), their families, and healthcare providers (n≥15). The study is composed of eight EBCD stages: clinical site observations, in-depth interviews, trigger film, healthcare providers' feedback event, AYAs' feedback event, joint event, co-design workshops, and a celebration event. Photovoice will take place as a starting point of EBCD. Data will be analyzed using thematic analysis. RESULTS: Data collection has started in January 2023 and is expected to be completed in May 2024. As of August 2023, over 15 clinical site observations have been conducted. A total of 18 AYAs, two parents, six healthcare providers have been enrolled and a total of 20 interviews have been conducted. CONCLUSION: Advancing transitional care is essential for tackling negative health outcomes. Applying the innovative participatory EBCD methodology will reveal key elements of transitional care for AYAs with common chronic conditions in the development of a person-centered transition program. PRACTICE IMPLICATIONS: Study findings will apply key elements of transitional care of AYAs with chronic conditions in the development of an adequate transition program.

Emergency Nurses' Reasons for Not Recommending Their Hospital to Clinicians as a Good Place to Work.

Importance: Half of emergency nurses report high burnout and intend to leave their job in the next year. Whether emergency nurses would recommend their workplace to other clinicians may be an important indicator of a hospital's ability to recruit clinicians. Objective: To examine why emergency nurses do not recommend their hospital to other clinicians as a good place to work. Design, Setting, and Participants: This qualitative study used directed content analysis of open-text responses (n = 142) from the RN4CAST-NY/IL survey of registered nurses licensed in New York and Illinois between April 13 and June 22, 2021. Inductive and deductive analytic approaches guided study theme development informed by the Social Ecological Model. The collected data were analyzed from April to June 2023. Main Outcomes and Measures: Nurses who answered "probably not" or "definitely not" to the survey question, "Would you recommend your place of employment as a good place to work?" were prompted to provide a rationale in an open-text response. Results: In this qualitative study of 142 emergency nurses (mean [SD] age, 43.5 [12.5] years; 113 [79.6%] female; mean [SD] experience, 14.0 [12.2] years), 94 (66.2%) were licensed to work in New York and the other 48 (33.8%) in Illinois. Five themes and associated subthemes emerged from the data. Themes conveyed understaffing of nurses and ancillary support (theme 1: unlimited patients with limited support); inadequate responsiveness from unit management to work environment safety concerns (theme 2: unanswered calls for help); perceptions that nurses' licenses were in jeopardy given unsafe working conditions and compromised care quality (theme 3: license always on the line); workplace violence on a patient-to-nurse, clinician-to-nurse, and systems level (theme 4: multidimensional workplace violence); and nurse reports of being undervalued by hospital management and unfulfilled at work in delivering suboptimal care to patients in unsafe working conditions (theme 5: undervalued and unfulfilled). Conclusions and Relevance: This study found that emergency department nurses did not recommend their workplace to other clinicians as a good place to work because of poor nurse and ancillary staffing, nonresponsive hospital leadership, unsafe working conditions, workplace violence, and a lack of feeling valued. These findings inform aspects of the work environment that employers can address to improve nurse recruitment and retention.