Public Survey Research Articles

Tree parameter extraction method based on new remote sensing technology and terrestrial laser scanning technology

Ground LiDAR is a terrestrial LiDAR system that is often used for terrain and geomorphic mapping. Ground-based LiDAR can be used to collect more local and short-range data, making it ideal for mapping smaller areas with high precision. In order to solve the rapid extraction of tree parameters in the national public welfare forest survey, the ground-based LIDAR was used to obtain the point cloud of trees, and the point cloud data was registered, denoised, normalized, sliced, parameter extracted, etc., and the parameters of individual trees in the forest were obtained. The Bland-Altman consistency test is used to test whether the method of extracting tree parameters from point clouds is consistent with the traditional measurement method. The experimental results show that the point cloud data obtained by the ground-based LIDAR can quickly, conveniently and accurately extract the tree parameters, which is consistent with the traditional tree parameter extraction method, and has the advantages than the traditional tree parameter measurement, such as point cloud, image and traceability. It has a unique advantage in establishing a tree database. It is suggested that LIDAR should be used for forest survey in the future.

Characterizing participants who respond to text, email, phone calls, or postcards in a SARS-CoV-2 prevalence study

IntroductionMultiple modalities and frequencies of contact are needed to maximize recruitment in many public health surveys. The purpose of this analysis is to characterize respondents to a statewide SARS-CoV-2 testing study whose participation followed either postcard, phone outreach or electronic means of invitation. In addition, we examine how participant characteristics differ based upon the number of contacts needed to elicit participation.MethodsThis is a cross-sectional analysis of survey data collected from participants who were randomly selected to represent Indiana residents and were invited to be tested for Covid-19 in April 2020. Participants received invitations via postcard, text/emails, and/or robocalls/texts based upon available contact information. The modality, and frequency of contacts, that prompted participation was determined by when the notification was sent and when the participant responded and subsequently registered to participate in the study. Chi square analyses were used to determine differences between groups and significant findings were analyzed using multinomial logistic regression.ResultsRespondents included 3,658 individuals and were stratified by postcards (7.9%), text/emails (26.5%), and robocalls/text (65.7%) with 19.7% registering after 1 contact, 47.9% after 2 contacts, and 32.4% after 3 contacts encouraging participation. Females made up 54.6% of the sample and responded at a higher rate for postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%) as compared to males (χ2 = 7.43, p = 0.025). Compared to males, females responded at a higher percentage after 1 contact (21.4 vs. 17.9%, χ2 = 7.6, p = 0.023). Those over 60 years responded most often after 2 contacts (χ2 = 27.5, p < 0.001) when compared to others at younger age groups. In regression analysis, participant sex (p = 0.036) age (p = 0.005), educational attainment (p = < 0.0001), and being motivated by “free testing” (p = 0.036) were correlated with participation in the prevalence study.DiscussionResearchers should be aware that the modality of contact as well as the number of prompts used could influence differential participation in public health studies. Our findings can inform researchers developing studies that rely on selective participation by study subjects. We explore how to increase participation within targeted demographic groups using specific modalities and examining frequency of contact.

The Gaia-ESO Survey: The DR5 analysis of the medium-resolution GIRAFFE and high-resolution UVES spectra of FGK-type stars

The Gaia-ESO Survey is an European Southern Observatory (ESO) public spectroscopic survey that targeted 105 stars in the Milky Way covering the major populations of the disk, bulge and halo. The observations were made using FLAMES on the VLT obtaining both UVES high (R ~ 47 000) and GIRAFFE medium (R ~ 20 000) resolution spectra. The analysis of the Gaia-ESO spectra was the work of multiple analysis teams (nodes) within five working groups (WG). The homogenisation of the stellar parameters within WG11 (high resolution observations of FGK stars) and the homogenisation of the stellar parameters within WG10 (medium resolution observations of FGK stars) is described here. In both cases, the homogenisation was carried out using a Bayesian Inference method developed specifically for the Gaia-ESO Survey by WG11. The method was also used for the chemical abundance homogenisation within WG11, however, the WG10 chemical abundance data set was too sparsely populated so basic corrections for each node analysis were employed for the homogenisation instead. The WG10 homogenisation primarily used the cross-match of stars with WG11 as the reference set in both the stellar parameter and chemical abundance homogenisation. In this way the WG10 homogenised results have been placed directly onto the WG11 stellar parameter and chemical abundance scales. The reference set for the metal-poor end was sparse which limited the effectiveness of the homogenisation in that regime. For WG11, the total number of stars for which stellar parameters were derived was 6 231 with typical uncertainties for Teff, log g and [Fe/H] of 32 K, 0.05 and 0.05 respectively. One or more chemical abundances out of a possible 39 elements were derived for 6 188 of the stars. For WG10, the total number of stars for which stellar parameters were derived was 76 675 with typical uncertainties for Teff, log g and [Fe/H] of 64 K, 0.15 and 0.07 respectively. One or more chemical abundances out of a possible 30 elements were derived for 64177 of the stars.

Health sciences faculty publication patterns and related information-seeking behavior.

This study aims to explore how health science faculty publication patterns at a large public research university have changed over time and examine how productivity relates to their information-seeking behavior and perception of the academic library. Two datasets were utilized: one consisted of publication records of health sciences faculty spanning a 15-year period, while the other was from a faculty survey exploring faculty's perception of and satisfaction with library resources and services related to their research. Health sciences faculty publication patterns have changed over time, characterized by greater productivity, collaboration, and use of literature in their publications. Faculty's literature use correlates with productivity, as evidenced by both datasets. The survey revealed that faculty with more publications tend to rely more on online journals and Interlibrary Loan (ILL). Similarly, the publication data indicated that less productive faculty tended to use fewer references in their publications. The publication data and survey results offer valuable insights into the health sciences faculty's information-seeking behavior and productivity. Online access to information has been effective in facilitating use of information, as indicated by the greater incorporation of references in publications. The study highlights the changing publication patterns and productivity of health sciences faculty, as well as the role academic libraries play in supporting their research and publishing activities. Although multiple variables influence faculty access to and use of information, faculty attitudes towards the library and use of the library are related to faculty research and productivity.

The Next Generation Deep Extragalactic Exploratory Public (NGDEEP) Survey

We present the Next Generation Deep Extragalactic Exploratory Public (NGDEEP) Survey, a deep slitless spectroscopic and imaging Cycle 1 JWST treasury survey designed to constrain feedback mechanisms in low-mass galaxies across cosmic time. NGDEEP targets the Hubble Ultra Deep Field (HUDF) with NIRISS slitless spectroscopy ( flim,line,5σ≈1.2× 10−18 erg s−1 cm−2) to measure metallicities and star formation rates (SFRs) for low-mass galaxies through the peak of the cosmic SFR density (0.5 < z < 4). In parallel, NGDEEP targets the HUDF-Par2 parallel field with NIRCam ( mlim,5σ=30.6−30.9 ) to discover galaxies to z > 12, constraining the slope of the faint end of the rest-ultraviolet luminosity function. NGDEEP overlaps with the deepest HST Advanced Camera for Surveys optical imaging in the sky, F435W in the HUDF ( mlim,F435W=29.6 ) and F814W in HUDF-Par2 ( mlim,F814W=30 ), making this a premier HST+JWST deep field. As a treasury survey, NGDEEP data are public immediately, and we will rapidly release data products and catalogs in the spirit of previous deep-field initiatives. In this paper we present the NGDEEP survey design, summarize the science goals, and detail plans for the public release of NGDEEP reduced data products.

The short version of the Sexual Distress Scale (SDS-3): Measurement invariance across countries, gender identities, and sexual orientations

BackgroundThe three-item Sexual Distress Scale (SDS-3) has been frequently used to assess distress related to sexuality in public health surveys and research on sexual wellbeing. However, its psychometric properties and measurement invariance across cultural, gender and sexual subgroups have not yet been examined. This multinational study aimed to validate the SDS-3 and test its psychometric properties, including measurement invariance across language, country, gender identity, and sexual orientation groups. MethodsWe used global survey data from 82,243 individuals (Mean age=32.39 years; 40.3 % men, 57.0 % women, 2.8 % non-binary, and 0.6 % other genders) participating in the International Sexual Survey (ISS; https://internationalsexsurvey.org/) across 42 countries and 26 languages. Participants completed the SDS-3, as well as questions regarding sociodemographic characteristics, including gender identity and sexual orientation. ResultsConfirmatory factor analysis (CFA) supported a unidimensional factor structure for the SDS-3, and multi-group CFA (MGCFA) suggested that this factor structure was invariant across countries, languages, gender identities, and sexual orientations. Cronbach's α for the unidimensional score was 0.83 (range between 0.76 and 0.89), and McDonald's ω was 0.84 (range between 0.76 and 0.90). Participants who did not experience sexual problems had significantly lower SDS-3 total scores (M = 2.99; SD=2.54) compared to those who reported sexual problems (M = 5.60; SD=3.00), with a large effect size (Cohen's d = 1.01 [95 % CI=-1.03, -0.98]; p < 0.001). ConclusionThe SDS-3 has a unidimensional factor structure and appears to be valid and reliable for measuring sexual distress among individuals from different countries, gender identities, and sexual orientations.

Community-based irrigation management in Indonesia (Case study: Musi Rawas Regency, Bandung Regency, and Soppeng Regency)

Indonesia is an agricultural country that relies on the food sector.Irrigation infrastructure plays an important role to support the sector. It is therefore the sustainability of irrigation is vital. Community-based management of irrigation has been developed in Indonesia to support the development, operation, and and maintenance of irrigation. The aim of this study is to explore community-based irrigation management to support the sustainability of irrigation infrastructure. Three locations were choosed as case study; Musi Rawas, Bandung, and Soppeng Regency. The data analysis method used is qualitative analysis. The results of this study indicate that community groups are involved in determining irrigation development, such as holding public consultations, site selection, surveys, land acquisition, cooperation, operation, and maintenance. However, this community group does not yet have a robust organizational role because it has not provided rules, sanctions, or solutions to solve problems in the field. In addition, there is a lack of government support for community groups. Realizing a sustainable community-based irrigation system requires a high role of the community in irrigation management and support from the government in supporting the capacity of community groups and financing participatory activities.

Sound the Alarm: The Sonographer Shortage Is Echoing Across Healthcare.

The growth in ultrasound usage necessitates concurrent growth in the number of sonographers. Despite the increasing importance of ultrasound, there is a shortage of sonographers in the United States that has never been specifically quantified. This study examines recent trends in the number of ultrasound exams, sonography graduates, open sonographer positions, and wages. This retrospective study uses public databases and surveys including the Medical Expenditure Panel Survey (MEPS), Bureau of Labor Statistics (BLS), Integrated Postsecondary Education Data System (IPEDS), and Zippia, a human resources platform to determine metrics. These metrics include the number of ultrasound exams conducted in the United States (excluding inpatient setting), number of sonographers and sonographer wages, sonography graduates, and open sonographer positions. Ultrasound exams in the United States from 2011 to 2021 increased from 38.6 million to 59.8 million (+55.1%,) while the number of sonographers (2011-2021) increased from 54,760 to 78,640 (+43.6%). There was a significant difference between supply and demand of sonographers with the number of sonography graduates (2011-2021) increasing from 4,386 to 5,393 (+23.0%) while the number of open sonographer positions (2012-2021) increased from 18,462 to 25,162 (+36.3%). From 2011 to 2021, the increase in the number of ultrasound exams has significantly outpaced the increase in the number of sonographers. Furthermore, the increase in demand for sonographers has grown significantly faster than the supply, leading to a shortage and consequent strain on the healthcare system. To address the shortage, the number of sonography school openings should be increased, and the attendant challenges addressed.

Answering the call: An evaluation of the Educate to Innovate campaign’s efforts to increase and diversify science, technology, engineering, and mathematics college graduates

Increasing and diversifying STEM college graduates, and consequently the STEM workforce, remains a pressing national priority. As such, the purpose of this quantitative study was to evaluate the Educate to Innovate campaign within higher education. Using preexisting public survey data together with interrupted and comparative interrupted time series techniques, this inquiry aimed to determine whether STEM education has been rejuvenated and broadened or if there remains work to be done. Results ultimately showed that the campaign exerted a statistically significant positive effect on the trend of STEM college graduates. However, no significant difference in the trend between STEM college graduates who are women and STEM college graduates who are men or between minority and nonminority STEM college graduates was observed. Such comprehension is both timely and useful as individuals and organizations along with federal, state, and local policymakers continue to refine and tailor the development of future STEM education interventions.

Rest-frame UV Colors for Faint Galaxies at z ∼ 9–16 with the JWST NGDEEP Survey

We present measurements of the rest-frame UV spectral slope, β, for a sample of 36 faint star-forming galaxies at z ∼ 9–16 discovered in one of the deepest JWST NIRCam surveys to date, the Next Generation Deep Extragalactic Exploratory Public Survey. We use robust photometric measurements for UV-faint galaxies (down to M UV ∼ −16), originally published in Leung et al., and measure values of the UV spectral slope via photometric power-law fitting to both the observed photometry and stellar population models obtained through spectral energy distribution (SED) fitting with Bagpipes. We obtain a median and 68% confidence interval for β from photometric power-law fitting of βPL=−2.7−0.5+0.5 and from SED fitting, βSED=−2.3−0.1+0.2 for the full sample. We show that when only two to three photometric detections are available, SED fitting has a lower scatter and reduced biases than photometric power-law fitting. We quantify this bias and find that after correction the median βSED,corr=−2.5−0.2+0.2 . We measure physical properties for our galaxies with Bagpipes and find that our faint ( MUV=−18.1−0.9+0.7 ) sample is low in mass ( log[M*/M⊙]=7.7−0.5+0.5 ), fairly dust-poor ( Av=0.1−0.1+0.2 mag), and modestly young ( log[age]=7.8−0.8+0.2 yr) with a median star formation rate of log(SFR)=−0.3−0.4+0.4M⊙yr−1 . We find no strong evidence for ultrablue UV spectral slopes (β ∼ −3) within our sample, as would be expected for exotically metal-poor (Z/Z ⊙ < 10−3) stellar populations with very high Lyman continuum escape fractions. Our observations are consistent with model predictions that galaxies of these stellar masses at z ∼ 9–16 should have only modestly low metallicities (Z/Z ⊙ ∼ 0.1–0.2).

Differential impact of environmental factors on airborne live bacteria and inorganic particles in an underground walkway.

We previously reported that variations in the number and type of bacteria found in public spaces are influenced by environmental factors. However, based on field survey data alone, whether the dynamics of bacteria in the air change as a result of a single environmental factor or multiple factors working together remains unclear. To address this, mathematical modeling may be applied. We therefore conducted a reanalysis of the previously acquired data using principal component analysis (PCA) in conjunction with a generalized linear model (Glm2) and a statistical analysis of variance (ANOVA) test employing the χ2 distribution. The data used for the analysis were reused from a previous public environmental survey conducted at 8:00-20:00 on May 2, June 1, and July 5, 2016 (regular sampling) and at 5:50-7:50 and 20:15-24:15 on July 17, 2017 (baseline sampling) in the Sapporo underground walking space, a 520-meter-long underground walkway. The dataset consisted of 60 samples (22 samples for "bacterial flora"), including variables such as "temperature (T)," "humidity (H)," "atmospheric pressure (A)," "traffic pedestrians (TP)," "number of inorganic particles (Δ5: 1-5 μm)," "number of live airborne bacteria," and "bacterial flora." Our PCA with these environmental factors (T, H, A, and TP) revealed that the 60 samples could be categorized into four groups (G1 to G4), primarily based on variations in PC1 [Loadings: T(-0.62), H(-0.647), TP(0.399), A(0.196)] and PC2 [Loadings: A(-0.825), TP(0.501), H(0.209), T(-0.155)]. Notably, the number of inorganic particles significantly increased from G4 to G1, but the count of live bacteria was highest in G2, with no other clear pattern. Further analysis with Glm2 indicated that changes in inorganic particles could largely be explained by two variables (H/TP), while live bacteria levels were influenced by all explanatory variables (TP/A/H/T). ANOVA tests confirmed that inorganic particles and live bacteria were influenced by different factors. Moreover, there were minimal changes in bacterial flora observed among the groups (G1-G4). In conclusion, our findings suggest that the dynamics of live bacteria in the underground walkway differ from those of inorganic particles and are regulated in a complex manner by multiple environmental factors. This discovery may contribute to improving public health in urban settings.

Would You Rather: Quantifying TBI Survivor Perceptions of Functional Status via Their Surrogates.

To quantify health utilities of the Glasgow Outcome Scale-Extended (GOSE) states after actual Traumatic Brain Injury (TBI). Recovery after TBI is measured using the GOSE, a validated clinical trial endpoint. A recent public survey quantified the health utilities of some GOSE states after hypothetical TBI as worse than death. However, no health utilities exist for disability after actual TBI. This national computer-adaptive survey followed EQUATOR-CHERRIES guidelines and recruited adult TBI survivors (injury>1y prior) via their available surrogates. Using a standard gamble approach in randomized order, participants gave preferences for post-TBI categorical health states ranging from GOSE 2-8. We calculated median [interquartile range, IQR] health utilities for each GOSE state, from -1 (worse than death) to 1 (full health), with 0 as reference (death, GOSE 1). Of 515 eligible, 298 surrogates (58%) consented and completed the scenarios on TBI survivors' behalf. TBI survivors had a current median GOSE 5 [3-7]. GOSE 2, GOSE 3, and GOSE 4 were rated worse than death by 89%, 64%, and 38%, respectively. The relationship was nonlinear, and intervals were unequal between states, with a bimodal distribution for GOSE 4. In this index study of actual post-TBI disability, poor neurologic outcomes represented by GOSE 2-4 were perceived as worse than death by at least one in three survivors. Similar to previously reported public perceptions after a hypothetical TBI, these long-term perceptions may inform earlier post-TBI shared decision making, as well as help shape value-based research and quality of care. II, Economic & Value-based Evaluations.

Surrogate Perception of Disability after Hospitalization for Traumatic Brain Injury.

The Glasgow Outcome Scale Extended (GOSE) is a measure of recovery after traumatic brain injury (TBI). Public surveys rate some GOSE states as worse than death. Direct family experience caring for patients with TBI may impact views of post-TBI disability. We conducted a national cross-sectional computer-adaptive survey of surrogates of TBI dependents incurring injury more than 1 year earlier. Using a standard gamble approach in randomized order, surrogates evaluated preferences for post-TBI GOSE states from GOSE 2 (bedridden, unaware) to GOSE 8 (good recovery). We calculated median (interquartile range [IQR]) health utilities for each post-TBI state, ranging from -1 to 1, with 0 as reference (death = GOSE 1), and assessed sociodemographic associations using proportional odds logistic regression modeling. Of 515 eligible surrogates, 298 (58%) completed scenarios. Surrogates were median aged 46 (IQR 35 to 60), 54% married, with Santa Clara strength of faith 14 (10 to 18). TBI dependents had a median GOSE5 (3 to 7). Median (IQR) health utility ratings for GOSE 2, GOSE 3, and GOSE 4 were -0.06 (-0.50 to -0.01), -0.01 (-0.30 to 0.45), and 0.30 (-0.01 to 0.80), rated worse than death by 91%, 65%, and 40%, respectively. Surrogates rated GOSE 4 (daily partial help) worse than the general population. Married surrogates rated GOSE 4 higher (p < 0.01). Higher strength of faith was associated with higher utility scores across GOSE states (p = 0.034). In this index study of surrogate perceptions about disability after TBI, poor neurologic outcomes-vegetative, needing all-day or partial daily assistance-were perceived as worse than death by at least 1 in 3 surrogates. Surrogate perceptions differed from the unexposed public. Long-term perceptions about post-TBI disability may inform earlier, tailored shared decision-making after neurotrauma.

Comparative Study of Cultural Landscape Perception in Historic Districts from the Perspectives of Tourists and Residents

From a human-centric perspective, improving the spatial quality of historical districts is a key focus in achieving their refined governance. Based on a public survey performed in Zhangzhou Ancient City, we explored the differences in the perception of cultural landscape genes (CLGs) between residents and tourists with different individual characteristics, utilizing non-parametric tests and box-plot analysis methods. The findings indicate the following: Tourists have a stronger perception of CLGs related to site layout and architectural features than residents, while residents have a stronger perception of cultural customs. Gender-related differences in the perception of CLG are only significant among tourists, with females showing a higher level of CLG perception than males. Residents of different age groups show a “U-shaped” distribution in their perception of CLGs related to site layout, whereas senior tourists have a lower cognitive perception level. People with lower educational backgrounds among residents tend to perceive cultural customs more significantly, whereas tourists with diverse educational backgrounds do not perceive them as having a significant impact. Residence location, visit frequency, duration of residence, and residence nature are key positive factors affecting the perception of CLGs. Our study highlights the significance of considering the users’ characteristics in enhancing the refined governance of historical districts.

Antibiotics Use, Resistance and Self-medication Practices among Healthcare Workers in a Federal Teaching Hospital in Southwest, Nigeria

Antimicrobial resistance is a major threat to global health, and inappropriate drug use, including antibiotic self-medication, has been identified as an important factor in developing countries. This study assessed the knowledge, and attitude of antibiotic use and antibiotics resistance, as well as the practice of self-medication among healthcare workers. This is a cross-sectional study conducted in a federal teaching hospital in Southwest, Nigeria among 320 healthcare workers selected through a two-stage sampling technique. A thirty-four-item self-administered semi-structured questionnaire adapted from the questionnaire on antibiotic resistance: multi-country public awareness survey by the WHO was used for data collection. Descriptive statistics, cross-tabulation and logistic regression were carried out using SPSS version 25.0. The mean ±SD age of the participants was 36.3 ±9.2years and over one-third (37.5%) of them had 6-10years of experience. About two-thirds (66.3%) of the participants had good knowledge about antibiotic use and resistance while only 39.4% had positive attitudes. The prevalence of self-medication with antibiotics was 30%. The identified positive predictors of antibiotics self-medication included having primary education (AOR:5.874, 95%CI:1.020-33.836) compared with tertiary education, poor knowledge (AOR:1.683, 95%CI:1.015-2.789) compared with good knowledge about antibiotic use and resistance as well as negative attitude (AOR:1.861, 95%CI:1.102-3.143) compared with a positive attitude towards antibiotic use and resistance. The level of knowledge and attitude in this study was suboptimal. Self-medication was linked with a lower level of education, poor knowledge, and a negative attitude. Therefore, we recommend the provision of appropriate health education to promote the rational use of antibiotics.

Tracking mosquito-borne diseases via social media: a machine learning approach to topic modelling and sentiment analysis

Mosquito-borne diseases (MBDs) are a major threat worldwide, and public consultation on these diseases is critical to disease control decision-making. However, traditional public surveys are time-consuming and labor-intensive and do not allow for timely decision-making. Recent studies have explored text analytic approaches to elicit public comments from social media for public health. Therefore, this study aims to demonstrate a text analytics pipeline to identify the MBD topics that were discussed on Twitter and significantly influenced public opinion. A total of 25,000 tweets were retrieved from Twitter, topics were modelled using LDA and sentiment polarities were calculated using the VADER model. After data cleaning, we obtained a total of 6,243 tweets, which we were able to process with the feature selection algorithms. Boruta was used as a feature selection algorithm to determine the importance of topics to public opinion. The result was validated using multinomial logistic regression (MLR) performance and expert judgement. Important issues such as breeding sites, mosquito control, impact/funding, time of year, other diseases with similar symptoms, mosquito-human interaction and biomarkers for diagnosis were identified by both LDA and experts. The MLR result shows that the topics selected by LASSO perform significantly better than the other algorithms, and the experts further justify the topics in the discussion.

NGDEEP Epoch 1: Spatially Resolved Hα Observations of Disk and Bulge Growth in Star-forming Galaxies at z ∼ 0.6–2.2 from JWST NIRISS Slitless Spectroscopy

We study the Hα equivalent width (EW(Hα)) maps of 19 galaxies at 0.6 < z < 2.2 in the Hubble Ultra Deep Field using NIRISS slitless spectroscopy as part of the Next Generation Deep Extragalactic Exploratory Public Survey. Our galaxies mostly lie on the star formation main sequence with stellar masses between 109 and 1011 M ⊙, characterized as “typical” star-forming galaxies at these redshifts. Leveraging deep Hubble Space Telescope and JWST images, spanning 0.4–4.8 μm, we perform spatially resolved fitting of the spectral energy distributions for these galaxies and construct specific star formation rate (sSFR) and stellar-mass-weighted age maps with a spatial resolution of ∼1 kpc. The pixel-to-pixel EW(Hα) increases with increasing sSFR and with decreasing age. The average trends are slightly different from the relations derived from integrated fluxes of galaxies from the literature, suggesting complex evolutionary trends within galaxies. We quantify the radial profiles of EW(Hα), sSFR, and age. The majority (84%) of galaxies show positive EW(Hα) gradients, in line with the inside-out quenching scenario. A few galaxies (16%) show inverse (and flat) EW(Hα) gradients, possibly due to merging or starbursts. We compare the distributions of EW(Hα) and sSFR to star formation history (SFH) models as a function of galactocentric radius. We argue that the central regions of galaxies have experienced at least one rapid star formation episode, which leads to the formation of the bulge, while their outer regions (e.g., disks) grow via more smoothly varying SFHs. These results demonstrate the ability to study resolved star formation in distant galaxies with JWST NIRISS.

Bayesian Multi-View Clustering given complex inter-view structure.

Multi-view datasets are becoming increasingly prevalent. These datasets consist of different modalities that provide complementary characterizations of the same underlying system. They can include heterogeneous types of information with complex relationships, varying degrees of missingness, and assorted sample sizes, as is often the case in multi-omic biological studies. Clustering multi-view data allows us to leverage different modalities to infer underlying systematic structure, but most existing approaches are limited to contexts in which entities are the same across views or have clear one-to-one relationships across data types with a common sample size. Many methods also make strong assumptions about the similarities of clusterings across views. We propose a Bayesian multi-view clustering approach (BMVC) which can handle the realities of multi-view datasets that often have complex relationships and diverse structure. BMVC incorporates known and complex many-to-many relationships between entities via a probabilistic graphical model that enables the joint inference of clusterings specific to each view, but where each view informs the others. Additionally, BMVC estimates the strength of the relationships between each pair of views, thus moderating the degree to which it imposes dependence constraints. We benchmarked BMVC on simulated data to show that it accurately estimates varying degrees of inter-view dependence when inter-view relationships are not limited to one-to-one correspondence. Next, we demonstrated its ability to capture visually interpretable inter-view structure in a public health survey of individuals and households in Puerto Rico following Hurricane Maria. Finally, we showed that BMVC clusters integrate the complex relationships between multi-omic profiles of breast cancer patient data, improving the biological homogeneity of clusters and elucidating hypotheses for functional biological mechanisms. We found that BMVC leverages complex inter-view structure to produce higher quality clusters than those generated by standard approaches. We also showed that BMVC is a valuable tool for real-world discovery and hypothesis generation.

Examining cancer screening disparities by race/ethnicity and insurance groups: A comparison of 2008 and 2018 National Health Interview Survey (NHIS) data in the United States.

Pervasive differences in cancer screening among race/ethnicity and insurance groups presents a challenge to achieving equitable healthcare access and health outcomes. However, the change in the magnitude of cancer screening disparities over time has not been thoroughly examined using recent public health survey data. A retrospective cross-sectional analysis of the 2008 and 2018 National Health Interview Survey (NHIS) database focused on breast, cervical, and colorectal cancer screening rates among race/ethnicity and insurance groups. Multivariable logistic regression models were used to assess the relationship between cancer screening rates, race/ethnicity, and insurance coverage, and to quantify the changes in disparities in 2008 and 2018, adjusting for potential confounders. Colorectal cancer screening rates increased for all groups, but cervical and mammogram rates remained stagnant for specific groups. Non-Hispanic Asians continued to report consistently lower odds of receiving cervical tests (OR: 0.42, 95% CI: 0.32-0.55, p<0.001) and colorectal cancer screening (OR: 0.55, 95% CI: 0.42-0.72, p<0.001) compared to non-Hispanic Whites in 2018, despite significant improvements since 2008. Non-Hispanic Blacks continued to report higher odds of recent cervical cancer screening (OR: 1.98, 95% CI: 1.47-2.68, p<0.001) and mammograms (OR: 1.32, 95% CI: 1.02-1.71, p<0.05) than non-Hispanic Whites in 2018, consistent with higher odds observed in 2008. Hispanic individuals reported improved colorectal cancer screening over time, with no significant difference compared to non-Hispanics Whites in 2018, despite reporting lower odds in 2008. The uninsured status was associated with significantly lower odds of cancer screening than private insurance for all three cancers in 2008 and 2018. Despite an overall increase in breast and colorectal cancer screening rates between 2008 and 2018, persistent racial/ethnic and insurance disparities exist among race/ethnicity and insurance groups. These findings highlight the importance of addressing underlying factors contributing to disparities among underserved populations and developing corresponding interventions.

Addressing ADL ability in people with poststroke cognitive impairments: A Danish survey of clinical practice

Background In Denmark, stroke represents a leading disability cause. While people with difficulties in performing activities of daily living (ADL) due to poststroke cognitive impairments are often referred to occupational therapy, limited knowledge is available on the nature of these services. Aim/Objective To explore how Danish occupational therapists describe their practice when addressing decreased ADL ability in people with poststroke cognitive impairments in hospital and municipality settings. Material and Methods National, cross-sectorial, web-based public survey. Results 244 occupational therapists accessed the survey; 172 were included in the analysis. Most respondents could indicate the theory guiding their reasoning; half used standardised assessments. Regarding intervention, restorative and acquisitional models were preferred; specific strategies were identified. Intensity: 30-45 min 3-4 times/week in hospitals; 30-60 min 1-2 times/week in municipalities. Conclusions Therapists report to be guided by theory in their reasoning. Standardised assessments are used to a higher extend than previously reported. Still, the results invite critical reflections on correct use of assessment instruments, content and intensity of interventions, and how therapists keep themselves updated. Significance The results document the need for practice improvements and may inform the definition of standard care in future trials.