Cumulative Logistic Regression Model Research Articles

Bayesian compositional models for ordinal response.

Ordinal response is commonly found in medicine, biology, and other fields. In many situations, the predictors for this ordinal response are compositional, which means that the sum of predictors for each sample is fixed. Examples of compositional data include the relative abundance of species in microbiome data and the relative frequency of nutrition concentrations. Moreover, the predictors that are strongly correlated tend to have similar influence on the response outcome. Conventional cumulative logistic regression models for ordinal responses ignore the fixed-sum constraint on predictors and their associated interrelationships, and thus are not appropriate for analyzing compositional predictors.To solve this problem, we proposed Bayesian Compositional Models for Ordinal Response to analyze the relationship between compositional data and an ordinal response with a structured regularized horseshoe prior for the compositional coefficients and a soft sum-to-zero restriction on coefficients through the prior distribution. The method was implemented with R package rstan using efficient Hamiltonian Monte Carlo algorithm. We performed simulations to compare the proposed approach and existing methods for ordinal responses. Results revealed that our proposed method outperformed the existing methods in terms of parameter estimation and prediction. We also applied the proposed method to a microbiome study HMP2Data, to find microorganisms linked to ordinal inflammatory bowel disease levels. To make this work reproducible, the code and data used in this paper are available at https://github.com/Li-Zhang28/BCO.

Linking Immigrants with Nutrition Knowledge (Project LINK): An Innovative Approach to Improve Cultural Competence in Dietetic Education.

Linking Immigrants with Nutrition Knowledge (Project LINK) was a service-learning cultural competence training programme completed by undergraduate dietetic students enrolled in the University of Saskatchewan's (USASK) nutrition and dietetic programme.This paper evaluates the impact of participation in the programme on students' cultural competence. We conducted a cross-sectional survey and qualitative analysis of reflective essays of 107 participants of Project LINK from 2011 to 2014. Cumulative logistic regression models assessed the impact of the intervention on students' cultural competencies. The Akaike information criterion compared models and Spearman correlation coefficient identified possible correlation among pre- and post-intervention data points. Student reflective essays were analyzed by inductive thematic analysis.All cultural competencies improved comparing pre- and post-participation in Project LINK. Odds of increasing one level of student knowledge were 110 times of that prior to Project LINK. Comparing student competencies before and after Project LINK, the odds of increasing one level of students' skills were six times greater, five times greater for increasing one level of students' ability to interact or encounter, and 2.8 times greater for increasing one level of students' attitude.The results of this study indicate Project LINK has successfully increased cultural competence and underscores the importance of combining opportunities for practical experience in addition to classroom-based training on cultural competence.

Breast cancer risk factors and mammographic density among 12518 average-risk women in rural China

BackgroundMammographic density (MD) is a strong risk factor for breast cancer. We aimed to evaluate the association between MD and breast cancer related risk factors among average-risk women in rural China.MethodsThis is a population-based screening study. 12518 women aged 45–64 years with complete MD data from three maternal and childcare hospitals in China were included in the final analysis. ORs and 95%CIs were estimated using generalized logit model by comparing each higher MD (BI-RADS b, c, d) to the lowest group (BI-RADS a). The cumulative logistic regression model was used to estimate the ORtrend (95%CI) and Ptrend by treating MD as an ordinal variable.ResultsOlder age (ORtrend = 0.81, 95%CI: 0.79–0.81, per 2-year increase), higher BMI (ORtrend = 0.73, 95%CI: 0.71–0.75, per 2 kg/m2), more births (ORtrend = 0.47, 95%CI: 0.41–0.54, 3 + vs. 0–1), postmenopausal status (ORtrend = 0.42, 95%CI: 0.38–0.46) were associated with lower MD. For parous women, longer duration of breastfeeding was found to be associated with higher MD when adjusting for study site, age, BMI, and age of first full-term birth (ORtrend = 1.53, 95%CI: 1.27–1.85, 25 + months vs. no breastfeeding; ORtrend = 1.45, 95%CI: 1.20–1.75, 19–24 months vs. no breastfeeding), however, the association became non-significant when adjusting all covariates. Associations between examined risk factors and MD were similar in premenopausal and postmenopausal women except for level of education and oral hormone drug usage. Higher education was only found to be associated with an increased proportion of dense breasts in postmenopausal women (ORtrend = 1.08, 95%CI: 1.02–1.15). Premenopausal women who ever used oral hormone drug were less likely to have dense breasts, though the difference was marginally significant (OR = 0.54, P = 0.045). In postmenopausal women, we also found the proportion of dense breasts increased with age at menopause (ORtrend = 1.31, 95%CI: 1.21–1.43).ConclusionsIn Chinese women with average risk for breast cancer, we found MD was associated with age, BMI, menopausal status, lactation, and age at menopausal. This finding may help to understand the etiology of breast cancer and have implications for breast cancer prevention in China.

Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing.

The delivery of education on pain neuroscience and the evidence for different treatment approaches has become a key component of contemporary persistent pain management. Chatbots, or more formally conversation agents, are increasingly being used in health care settings due to their versatility in providing interactive and individualized approaches to both capture and deliver information. Research focused on the acceptability of diverse chatbot formats can assist in developing a better understanding of the educational needs of target populations. This study aims to detail the development and initial pilot testing of a multimodality pain education chatbot (Dolores) that can be used across different age groups and investigate whether acceptability and feedback were comparable across age groups following pilot testing. Following an initial design phase involving software engineers (n=2) and expert clinicians (n=6), a total of 60 individuals with chronic pain who attended an outpatient clinic at 1 of 2 pain centers in Australia were recruited for pilot testing. The 60 individuals consisted of 20 (33%) adolescents (aged 10-18 years), 20 (33%) young adults (aged 19-35 years), and 20 (33%) adults (aged >35 years) with persistent pain. Participants spent 20 to 30 minutes completing interactive chatbot activities that enabled the Dolores app to gather a pain history and provide education about pain and pain treatments. After the chatbot activities, participants completed a custom-made feedback questionnaire measuring the acceptability constructs pertaining to health education chatbots. To determine the effect of age group on the acceptability ratings and feedback provided, a series of binomial logistic regression models and cumulative odds ordinal logistic regression models with proportional odds were generated. Overall, acceptability was high for the following constructs: engagement, perceived value, usability, accuracy, responsiveness, adoption intention, esthetics, and overall quality. The effect of age group on all acceptability ratings was small and not statistically significant. An analysis of open-ended question responses revealed that major frustrations with the app were related to Dolores' speech, which was explored further through a comparative analysis. With respect to providing negative feedback about Dolores' speech, a logistic regression model showed that the effect of age group was statistically significant (χ22=11.7; P=.003) and explained 27.1% of the variance (Nagelkerke R2). Adults and young adults were less likely to comment on Dolores' speech compared with adolescent participants (odds ratio 0.20, 95% CI 0.05-0.84 and odds ratio 0.05, 95% CI 0.01-0.43, respectively). Comments were related to both speech rate (too slow) and quality (unpleasant and robotic). This study provides support for the acceptability of pain history and education chatbots across different age groups. Chatbot acceptability for adolescent cohorts may be improved by enabling the self-selection of speech characteristics such as rate and personable tone.

Physical Activity Among Rural Men: Barriers and Preferences.

Physical activity positively affects health. Although 94% of Americans know the health benefits of regular physical activity, more than 75% do not achieve recommended levels. The objective of our study was to identify and define the key components of a physical activity intervention tailored to rural American men. We recruited rural men (N = 447) via Amazon's Mechanical Turk online platform to complete a needs assessment survey focused on their interest in a physical activity intervention, preferred intervention features, and potential intervention objectives. Data were summarized by using descriptive statistics. A cumulative logistic regression model examined associations between the men's perceived importance of physical activity to health and their interest in a physical activity intervention. Almost all participants (97.7%) rated physical activity as "at least somewhat important" to their health, and 83.9% indicated they would be "at least somewhat interested" in participating in a physical activity intervention. On a scale of 1 (not at all a barrier) to 5 (very much a barrier), motivation (mean 3.4; 95% CI, 3.3-3.5), cold weather (mean, 3.4; 95% CI, 3.3-3.5), and tiredness (mean, 3.3; 95% CI, 3.2-3.4) were rated the biggest barriers to physical activity. Becoming fitter (54.1%) was the top reason for joining a physical activity program. Preferred delivery channels for receiving an intervention were mobile application (ranked from 1 being the most preferred and 9 being the least preferred: mean, 2.8; 95% CI, 2.70-3.09) and e-mail (mean, 4.2; 95% CI, 3.92-4.36). Rural men preferred interventions that taught them how to exercise and that could be done from home. Our findings suggest US men in rural areas are receptive to physical activity programs. A systematic approach and a clear model of development are needed to tailor future physical activity interventions to the special needs of rural men.

Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods

BackgroundDays alive without life support (DAWOLS) and similar outcomes that seek to summarise mortality and non-mortality experiences are increasingly used in critical care research. The use of these outcomes is challenged by different definitions and non-normal outcome distributions that complicate statistical analysis decisions.MethodsWe scrutinized the central methodological considerations when using DAWOLS and similar outcomes and provide a description and overview of the pros and cons of various statistical methods for analysis supplemented with a comparison of these methods using data from the COVID STEROID 2 randomised clinical trial. We focused on readily available regression models of increasing complexity (linear, hurdle-negative binomial, zero–one-inflated beta, and cumulative logistic regression models) that allow comparison of multiple treatment arms, adjustment for covariates and interaction terms to assess treatment effect heterogeneity.ResultsIn general, the simpler models adequately estimated group means despite not fitting the data well enough to mimic the input data. The more complex models better fitted and thus better replicated the input data, although this came with increased complexity and uncertainty of estimates. While the more complex models can model separate components of the outcome distributions (i.e., the probability of having zero DAWOLS), this complexity means that the specification of interpretable priors in a Bayesian setting is difficult.Finally, we present multiple examples of how these outcomes may be visualised to aid assessment and interpretation.ConclusionsThis summary of central methodological considerations when using, defining, and analysing DAWOLS and similar outcomes may help researchers choose the definition and analysis method that best fits their planned studies.Trial registrationCOVID STEROID 2 trial, ClinicalTrials.gov: NCT04509973, ctri.nic.in: CTRI/2020/10/028731.

Abstract P148: Perceived Religious Influence on Health is Associated With Beneficial Cardiovascular Health Behaviors Within Predominantly Black Churches in New Orleans, Louisiana

Introduction: CVD is the leading cause of death in the US. Black populations are disproportionately affected by CVD. Further, Black populations have substantially high rates of religiosity. Previous research has demonstrated a positive correlation between religiosity and health, but the mechanisms are unclear. In this study, we describe the relationship between perceived religious influence on CVD health behaviors, risk factors and confidence in participating in medical care within predominantly Black churches in New Orleans, Louisiana. Hypothesis: Perceived religious influence on health is positively associated with CVD health behaviors, risk factors and confidence in participating in medical care. Methods: A survey in 302 members of 13 churches with predominantly Black congregations was conducted during the needs assessment of the Church-based Health Intervention to Eliminate Racial Inequalities in Cardiovascular Health (CHERISH) trial. Religious influence on health was assessed with two statements, (1) “Religious beliefs have great influence on my health” and (2) “I tend to avoid things harmful to my body because of religious beliefs” and measured with a five-point Likert scale ranging from “strongly disagree” to “strongly agree”. Outcomes included fruit and vegetable intake, physical activity, smoking status, self-reported hypertension, hypercholesterolemia, diabetes, and confidence in asking questions to provider and understanding treatment plans. Logistic regression and cumulative odds logistic regression models were used to examine the association with individual and composite outcomes, respectively, adjusting for age, sex, and education. Results: Survey respondents were 77% (233/302) female with a mean age of 65.5 years, and 72% (218/302), 56% (168/302), and 37% (111/302) reported hypertension, hypercholesterolemia, and diabetes, respectively. Perceived religious influence on health was associated with daily fruit and vegetable consumption (OR = 1.64; 95% CI: 1.01, 2.67), physical activity (OR = 1.76; 95% CI: 1.05, 2.96), composite health behaviors (OR = 1.59; 95% CI: 1.03, 2.48), confidence in asking questions to provider (OR = 3.46; 95% CI: 1.41, 9.12), and the composite confidence outcome (OR = 2.11; 95% CI: 1.06, 4.26). Avoiding harmful things because of religion was associated with physical activity (OR = 1.97; 95% CI: 1.17, 3.38) and composite health behaviors (OR = 1.56; 95% CI: 1.01, 2.42). There was no association between the exposures and self-reported hypertension, hypercholesterolemia, or diabetes. Conclusion: Perceived religious influence on health was associated with beneficial CVD health behaviors and confidence in participating in medical care. These findings may inform cultural tailoring of interventions to reduce CVD among the US Black population.

Change and Continuity in Preventive Practices Across the COVID-19 Pandemic Among Rural and Urban Latinx Immigrant Worker Families.

(1)The COVID-19 pandemic has put essential workers at high risk for contracting the disease. This study documents situational compliance with public health recommendations such as masking and social distancing among rural and urban Latinx families, with the goal of understanding change over time in COVID-19 risk reduction behaviors. (2)Respondents for 67 rural families and 44 urban families responded to repeated telephone surveys at three time points in the first year of the pandemic, providing data on use of masks and social distancing by themselves and family members while interacting with others at home, work, and in the community. Cumulative logistic regression models were employed to compare changes in risk behaviors between rural and urban groups over time. (3)While group descriptive results indicated behaviors that posed low risk at each time point, regression models revealed greater change between time points for rural than urban residents. Rural residents also had gendered patterns. (4)Patterns of change appear to reflect structural issues such as seasonal labor demand and gender roles more than pandemic fatigue or changing public health recommendations. The findings suggest that structural factors play a role in individuals complying with public health prevention measures for COVID-19.

Factors Influencing Smallholder Farmers’ Decision to Abandon Introduced Sustainable Land Management Technologies in Central Ethiopia

The Ethiopian government has made efforts to rehabilitate degraded lands using a range of sustainable land management (SLM) initiatives. One of the key components was the use of improved structural soil and water conservation (SWC) technologies. However, the effectiveness of technology adoption varies greatly among households and abandoning previously accepted measures is a typical occurrence. Thus, this study sought to discover factors influencing smallholder farmers’ decisions to abandon already accepted SWC measures. The analysis was conducted based on data collected from 525 sample households surveyed in two districts in Central Ethiopia. An ordered cumulative logistic (POM) regression model was used to examine variables explaining households’ decision behavior. The study findings have revealed that sampled households were at different adoption stages, i.e., dis-adopters (22%), pilot-level adopters (14%) and adopters (64%). The results from the POM model also show that a range of variables influenced farmers’ dis-adoption decisions. Factors such as awareness about the risks of land degradation, access to training, incentives, land fragmentation, gender, full-time labor size, gentle slope plots, economic returns on investment and post-adoption follow-up were found to substantially influence smallholder farmers’ adoption discontinuance decisions. Thus, policymakers should consider these variables in designing strategies to overcome barriers to SLM practices.

Bayesian inference of the cumulative logistic principal component regression models

Bayesian inference of the cumulative logistic principal component regression models

To meet or not to meet welfare outcome thresholds: a case-control study in dairy cow herds

Recently published thresholds allow classifying dairy cattle herds according to target, caution and alert ranges for welfare outcomes. Such normative thresholds provide one way to transparently assess production practices and are a straightforward communication tool with farmers. In an ordinal response case-control study, we investigated associations of animal, management and resource-related indicators with the risk of exceeding thresholds of prevalence for lameness, claw disorders, integument alterations and leg cleanliness. To this end, we used cumulative logistic regression models on 264 tethered and 392 loose-housed Austrian dairy herds. In tethered herds, the risk indicator average lactation milk yield was positively associated with the probability to exceed thresholds for integument alteration prevalence but negatively regarding leg cleanliness. Associations were also found for operation type regarding integument alterations (lower risk on organic vs conventional farms), for herd size regarding lameness (negative association) and dirty upper hind leg (positive association), and for percentage of fifth or higher parity cows in the herd regarding dirty lower hind leg (positive association). Stall type was identified as risk indicator regarding claw disorders (lower risk of long vs short stands). In loose housing systems, none of the analysed risk indicators was associated with the probability to exceed thresholds for total lameness and claw disorder prevalence. Negative associations with the probability to exceed caution or alert thresholds were identified for lifetime milk yield (dirty upper hind leg), lactation milk yield (dirty upper and lower hind leg), percentage of cows in the herd with a fat-protein-ratio <1 (integument alterations), and percentage of cows in the herd with a fat-protein-ratio >1.5 (dirty upper hind leg). Pasture access showed negative (severe lameness, integument alterations) and herd size positive associations (severe lameness) with the probability to exceed thresholds. Deep litter cubicles compared to raised cubicles with rubber mats showed a lower probability to exceed thresholds (integument alterations, dirty lower hind leg) as well as solid rubber compared to concrete slatted flooring in alleyways (integument alterations). Assessments carried out during the pasture period compared to during winter housing were associated with a lower risk of exceeding thresholds for leg cleanliness measures in both, tethered and loose-housed herds, and for integument alteration prevalence in tethered herds. In conclusion, no principal risk indicator was identified which consistently determined the probability of exceeding predefined thresholds of considered welfare outcomes. Nevertheless, outcome-specific factors show sufficient impact on the categorisation of farms according to prevalence ranges.

Estimation of beef cow body condition score: a machine learning approach using three-dimensional image data and a simple approach with heart girth measurements

Body condition score (BCS) is a proxy for evaluating body fat reserves. However, monitoring BCS is a time-consuming and subjective task. Thus, we aimed to develop a method for estimating the BCS of beef cows using three-dimensional (3D) body features of cows’ rump area derived from 3D camera data. Three-dimensional surface data of the rump area from 39 multiparous cows were obtained using a 3D camera, and four 3D body features were extracted. The BCSs of the cows were scored by experts, and models for predicting BCS by 3D features were developed using machine learning algorithms. The derived model yielded an overall accuracy, precision, sensitivity, and F-measure of 90%, 88%, 90%, and 88%, respectively. Additionally, we evaluated a simple practical method to estimate BCS using the difference between heart girth (HG) and tightened heart girth (THG) for 118 multiparous cows. A cumulative logistic regression model for estimating BCS by the difference was developed, and the derived generalized coefficient of determination was 0.81. These results suggest that 3D images are useful for estimating the BCS of beef cows and that the difference between HG and THG can be used to estimate BCS as a simple practical method.

Elevated serum S14 levels are associated with more severe liver steatosis by ultrasonography

S14 has been identified as a potent stimulator of de novo hepatic lipogenesis (DNL) in rodents. However, it is unclear how S14 is regulated in humans with non-alcoholic fatty liver disease (NAFLD). The aim of this study was to investigate the relationship between serum S14 and liver steatosis in humans with NAFLD. A total of 614 participants were recruited from community. Liver steatosis were evaluated according to the Ultrasonographic Fatty Liver Indicator (US-FLI), which is a semi-quantitative liver ultrasound score. Anthropometric and biochemical indices were collected for further analysis. The risk of liver steatosis severity was estimated by a cumulative logistic regression model. NAFLD was found in 52.2% of the participants. The subjects with NAFLD showed higher levels of waist circumference, body mass index, insulin resistance, aspartate aminotransferase, dyslipidemia, visceral fat, serum S14 and risk of metabolic syndrome (MetS) than those of controls. Compared with the first tertile of serum S14, the odds ratios for the risk of more severe liver steatosis were 1.22 (95% confidence interval [CI]: 0.78–1.92) for those of the second tertile and 2.08 (95% CI: 1.28–3.39) for the third tertile (P for trend < 0.05) after adjusting for confounding factors. Higher serum S14 level was not only found in NAFLD subjects but also was positively correlated with the severity of liver steatosis. S14 may play an important role in the mechanism of DNL for NAFLD in humans.

Oxygen Saturation and Postoperative Mortality in Patients With Acute Ischemic Stroke Treated by Endovascular Thrombectomy.

Monitored anesthesia care (MAC) and general anesthesia (GA) with endotracheal intubation are the 2 most used techniques for patients with acute ischemic stroke (AIS) undergoing endovascular thrombectomy. We aimed to test the hypothesis that increased arterial oxygen concentration during reperfusion period is a mechanism underlying the association between use of GA (versus MAC) and increased risk of in-hospital mortality. In this retrospective cohort study, data were collected at the Cleveland Clinic between 2013 and 2018. To assess the potential mediation effect of time-weighted average oxygen saturation (Spo2) in first postoperative 48 hours between the association between GA versus MAC and in-hospital mortality, we assessed the association between anesthesia type and post-operative Spo2 tertiles (exposure-mediator relationship) through a cumulative logistic regression model and assessed the association between Spo2 and in-hospital mortality (mediator-outcome relationship) using logistic regression models. Confounding factors were adjusted for using propensity score methods. Both significant exposure-mediator and significant mediator-outcome relationships are needed to suggest potential mediation effect. Among 358 patients included in the study, 104 (29%) patients received GA and 254 (71%) received MAC, with respective hospital mortality rate of 19% and 5% (unadjusted P value <.001). GA patients were 1.6 (1.2, 2.1) (P < .001) times more likely to have a higher Spo2 tertile as compared to MAC patients. Patients with higher Spo2 tertile had 3.8 (2.1, 6.9) times higher odds of mortality than patients with middle Spo2 tertile, while patients in the lower Spo2 tertile did not have significant higher odds compared to the middle tertile odds ratio (OR) (1.8 [0.9, 3.4]; overall P < .001). The significant exposure-mediator and mediator-outcome relationships suggest that Spo2 may be a mediator of the relationship between anesthetic method and mortality. However, the estimated direct effect of GA versus MAC on mortality (ie, after adjusting for Spo2; OR [95% confidence interval {CI}] of 2.1 [0.9-4.9]) was close to the estimated association ignoring Spo2 (OR [95% CI] of 2.2 [1.0-5.1]), neither statistically significant, suggesting that Spo2 had at most a modest mediator role. GA was associated with a higher Spo2 compared to MAC among those treated by endovascular thrombectomy for AIS. Spo2 values that were higher than the middle tertile were associated with higher odds of mortality. However, GA was not significantly associated with higher odds of death. Spo2 at most constituted a modest mediator role in explaining the relationship between GA versus MAC and mortality.

Structural change detection in ordinal time series.

Change-point detection in health care data has recently obtained considerable attention due to the increased availability of complex data in real-time. In many applications, the observed data is an ordinal time series. Two kinds of test statistics are proposed to detect the structural change of cumulative logistic regression model, which is often used in applications for the analysis of ordinal time series. One is the standardized efficient score vector, the other one is the quadratic form of the efficient score vector with a weight function. Under the null hypothesis, we derive the asymptotic distribution of the two test statistics, and prove the consistency under the alternative hypothesis. We also study the consistency of the change-point estimator, and a binary segmentation procedure is suggested for estimating the locations of possible multiple change-points. Simulation results show that the former statistic performs better when the change-point occurs at the centre of the data, but the latter is preferable when the change-point occurs at the beginning or end of the data. Furthermore, the former statistic could find the reason for rejecting the null hypothesis. Finally, we apply the two test statistics to a group of sleep data, the results show that there exists a structural change in the data.

Impact of a focused trauma course on retention of provider skills, knowledge and confidence at a regional hospital in the Dominican Republic

IntroductionRoad traffic accidents are a public health epidemic, causing significant morbidity and mortality in low- and middle-income countries. The Dominican Republic (DR) ranks among the highest road traffic fatality rates in the world. There is no formalized trauma curriculum in the DR. A short trauma course was implemented at a San Pedro de Macoris, DR hospital with pre-, post- and retention evaluation of the knowledge, skills and confidence of the providers. MethodsA 4-day trauma course was developed for medical students and residents. On days 1 and 4, providers completed pre- and post-training assessments consisting of a 40-question written exam, 1 simulation case and a trauma confidence questionnaire. Simulation cases were evaluated using a critical actions checklist and a non-technical skills scale (TNOTECHS). Assessments were repeated in 2 months to evaluate for knowledge, skill and confidence retention. A repeated measures ANOVA model was used to evaluate pre-, post- and retention training differences in the written exam, non-technical skills and critical actions scores. Confidence scores were assessed using a cumulative logistic regression model. ResultsA total of 65 people participated (36 medical students, 22 EM and 7 family medicine residents). Of the 65 participants, 39, 22 and 21 participants had complete scores for pre-post, pre-retention and post-retention comparisons respectively. Mean test scores for the written exam were 37.2, 63.5 and 52.2 for pre, post and retention results respectively. Comparisons between pre and post as well as pre and retention showed statistically significant differences (p=0.0001). Mean TNOTECHS total scores were 15.8, 21.3 and 20.8 for pre-, post- and retention results respectively with a significant difference found between pre- and post- training and pre- and retention training (p <0.05). Simulation mean checklist scores were 57.7%, 67.8% and 74.1% for pre-, post- and retention training respectively with a significant difference established between pre- and retention scores (p<0.05). Provider opinion that their ED patients received best care possible and patients’ needs were identified and addressed showed statistically significant increases. ConclusionA short trauma course can improve trauma specific knowledge, skills and confidence with significant retention at two months. A longitudinal trauma curriculum may bolster retention.

Analysis Model of Risk Factors of Urban Bus Operation Based on FTA-CLR

In order to comprehensively analyze the risk factors and accurately find the high risk factors related to accidents, an analysis model of risk factors of urban bus operation is proposed, in which the advantages of the structural analysis of the Fault Tree Analysis (FTA) and the correlation analysis of the Cumulative Logistic Regression (CLR) are combined. Firstly, based on the accident data in Northeast China, FTA is used to compile the urban bus operation fault tree. In the fault tree, 16 bus operation risk factors are classified, while the risk factors are sorted and compared from three aspects: structural importance, probability importance, and critical importance. And then, the 11 higher risk factors are selected according to the discriminant principle. Secondly, bus operation accidents are divided into fatal accidents, injury accidents, and major economic loss accidents. The CLR model is used to fit the much higher risk factors that lead to urban bus operation accidents from above 11 higher risk factors. Finally, the scientific rationality and applicability of the model are verified, through the goodness of fit test and the comparison test with the actual probability of occurrence.

The association of co-morbid asthma and overweight/obese status with healthcare utilization and caregiver perception of health in children 4–17 years, a NHANES study

Objective Asthma and obesity are two of the most common chronic childhood illnesses. The purpose of this study was to better understand the relationship between co-morbid asthma and obesity in children aged 4–17 and whether it impacts the caregiver’s perception of health and/or healthcare utilization. Methods This was a secondary analysis of the National Health and Nutrition Examination Surveys (NHANES) datasets from 2007 to 2018. Cumulative logistic regression models were used to analyze the caregiver’s perception of health, received healthcare, and overnight hospital stay as dependent variables. Asthma and weight status were included as covariates, with adjustment for age, income, head of the household’s education, gender, race, and insurance. Results The sample included 15,386 children. When looking at weight status in addition to asthma, compared to caregivers of children with current asthma and normal weight, caregivers of children with current asthma and with obesity are more likely to perceive their children as having worse health (OR = 1.73, 95%CI = [1.30, 2.32], p = 0.0003), and are more likely to have more frequent healthcare utilization but the results did not reach a statistical significance. Conclusions Caregiver’s perception of overall health was worse in caregivers of those with co-morbid obesity/asthma than in caregivers of children with asthma alone. This indicates that caregivers of children with co-morbid asthma and obesity have insight into their children’s condition and may be primed for discussion and counseling in the healthcare setting.

A Retrospective, Matched Case-Control Study on the Risk Factors of Falls and Varying Severities of Fall-Related Injuries in Inpatients.

This study was to investigate the factors that influence falls and the severity of fall-related injuries in inpatients. We adopted a retrospective, matched case-control design and conducted this study at a teaching hospital in Taiwan. Our study period ran from January 2016 to December 2019. We searched for inpatients with official fall records and obtained data from 823 patients, and then established a control group comprising 331 matching patients based on age, sex, length of hospital stay at time of fall incident, and ward type, thereby resulting in 1154 patients in all. A cumulative logistic regression model was applied to the data collected from medical records and fall incident reports to identify the factors that influence falls and the severity of fall-related injuries in inpatients. The results indicated that the use of sedatives (B = 0.49, P < 0.001), impaired consciousness (B = 0.64, P < 0.001), normal weight versus obese (B = -0.59, P = 0.008), low hemoglobin levels (B = -0.08, P = 0.003), an unsteady gait versus a normal gait (B = 1.82, P < 0.001), and history of falling within the past year (B = 0.56, P < 0.001) were correlated with the falls and the severity of fall-related injuries. Our results indicate that the use of sedatives, impaired consciousness, obesity, low hemoglobin levels, poor gait function, and history of falling within the past year are all independent factors that influence falls and the severity of fall-related injuries. This study can provide medical personnel with a reference for the identification of patients with a high risk of falling and implementation of fall prevention measures.

Nominal Modifiers in Argumentative Essays as Discriminators for Writing Course Placement Decisions

Grammatical complexity constitutes an indispensable subconstruct of L2 writing ability. Nonetheless, rating scale descriptors for grammatical complexity have heavily relied on degree modifiers or adjectives. Thus, this study attempts to explore the potential for the use of nominal modifiers as discriminators for adjacent levels of L2 writers in the context of an English Placement Test. This study analyzed 374 argumentative essays written by international undergraduates. Seven nominal modifiers in the developmental stages of grammatical complexity were examined and a cumulative ordinal logistic regression model with proportional odds was fitted to explore the relative effects of those grammar features on placement decisions. Four nominal modifiers were found to be positively associated with placement decisions, after adjusting for the effects of other variables. One educational implication is for the use of nominal modifiers to be incorporated into rating scale descriptors as discriminators for L2 writers who are not advanced enough to be exempted from an English Placement Test.