Accounting for informative observation process in transition models of binary longitudinal outcome: Application to medical record data.

When extracting medical record data to form a retrospective cohort, investigators typically focus on a pre-specified study window, and select subjects who had hospital visits during that study window. However, such data extraction may suffer from an informative observation process, since sicker patients may have hospital visits more frequently. For example, Consecutive Pregnancy Study is a retrospective cohort study of women with multiple pregnancies in 23 Utah hospitals from 2003 to 2010, where the interest is to understand the risk factors of recurrent pregnancy outcomes, such as preterm birth. The observation process is informative in the sense that, women with adverse pregnancy outcomes may be less likely/willing/able to endure subsequent pregnancies. We proposed a three-part joint model with shared random effects structure to address this analytic complication. Particularly, a first-order transition model is used to model the longitudinal binary outcome; a gamma regression model is assumed for the inter-pregnancy intervals; a continuation ratio model specifies the probability of continuing with more births in the future. We note that the latter two parts give rise to a parametric cure-rate survival model. The performance of the proposed method was examined in extensive simulation studies, with both correctly and mis-specified models. The analyses of Consecutive Pregnancy Study data further demonstrate the inadequacies of fitting the transition model alone ignoring the informative observation process.

Measuring hand movement for suturing skill assessment: A simulation-based study.

BACKGROUND: To maximize patient safety, surgical skills education is increasingly adopting simulation-based curricula for formative skills assessment and training. However, many standardized assessment tools rely on human raters for performance assessment, which is resource-intensive and subjective. Simulators that provide automated and objective metrics from sensor data can address this limitation. We present an instrumented bench suturing simulator, patterned after the clock face radial suturing model from the Fundamentals of Vascular Surgery, for automated and objective assessment of open suturing skills. METHODS: For this study, 97 participants (35 attending surgeons, 32 residents, and 30 novices) were recruited at national vascular conferences. Automated hand motion metrics, especially focusing on rotational motion analysis, were developed from the inertial measurement unit attached to participants' hands, and the proposed suite of metrics was used to differentiate between the skill levels of the 3 groups. RESULTS: Attendings' and residents' performances were found to be significantly different from novices for all metrics. Moreover, most of our novel metrics could successfully distinguish between finer skill differences between attending and resident groups. In contrast, traditional operative skill metrics, such as time and path length, were unable to distinguish attendings from residents. CONCLUSION: This study provides evidence for the effectiveness of rotational motion analysis in assessing suturing skills. The suite of inertial measurement unit-based hand motion metrics introduced in this study allows for the incorporation of hand movement data for suturing skill assessment.

Relating process and outcome metrics for meaningful and interpretable cannulation skill assessment: A machine learning paradigm.

BACKGROUND AND OBJECTIVES: The quality of healthcare delivery depends directly on the skills of clinicians. For patients on hemodialysis, medical errors or injuries caused during cannulation can lead to adverse outcomes, including potential death. To promote objective skill assessment and effective training, we present a machine learning approach, which utilizes a highly-sensorized cannulation simulator and a set of objective process and outcome metrics. METHODS: In this study, 52 clinicians were recruited to perform a set of pre-defined cannulation tasks on the simulator. Based on data collected by sensors during their task performance, the feature space was then constructed based on force, motion, and infrared sensor data. Following this, three machine learning models- support vector machine (SVM), support vector regression (SVR), and elastic net (EN)- were constructed to relate the feature space to objective outcome metrics. Our models utilize classification based on the conventional skill classification labels as well as a new method that represents skill on a continuum. RESULTS: With less than 5% of trials misplaced by two classes, the SVM model was effective in predicting skill based on the feature space. In addition, the SVR model effectively places both skill and outcome on a fine-grained continuum (versus discrete divisions) that is representative of reality. As importantly, the elastic net model enabled the identification of a set of process metrics that highly impact outcomes of the cannulation task, including smoothness of motion, needle angles, and pinch forces. CONCLUSIONS: The proposed cannulation simulator, paired with machine learning assessment, demonstrates definite advantages over current cannulation training practices. The methods presented here can be adopted to drastically increase the effectiveness of skill assessment and training, thereby potentially improving clinical outcomes of hemodialysis treatment.

Simulator-Based Metrics for Quantifying Vascular Palpation Skill for Cannulation.

Palpation is essential for accurate diagnosis and treatment in many clinical examinations and procedures. Specifically, vascular palpation is used to diagnose cardiovascular health issues and identify anatomical landmarks in the peripheral vascular system. However, little attention has been given to quantifying what comprises skilled vascular palpation; therefore, this study aims to objectively quantify the differences between high performer (HP), mid performer (MP), and low performer (LP) behavior towards understanding vascular palpation skills. Eleven HPs, twenty-five MPs, and ten LPs completed sixteen trials on our simulator under various conditions. There were four fistulas, two skin thicknesses, and two motor vibration intensities. Finger force and location data were recorded for each trial on the simulator. We examined three types of palpation metrics: time, force, and location. All three types of metrics demonstrated statistically significant differences between HP and LP palpation behavior. Therefore, these metrics could be used for structured and standardized palpation skills training in the future, potentially improving patient outcomes.

Nursing Faculty's Perceptions of Climate Change and Sustainability.

AIM: The aim of this research study was to investigate the perceptions of climate change and sustainability of faculty teaching in associate and baccalaureate degree nursing programs in South Carolina and their attitudes toward inclusion of relevant content into the nursing curriculum. BACKGROUND: Climate change is a topic that receives limited discussion in most nursing education curricula. METHOD: This cross-sectional, descriptive study gathered data from 21 schools of nursing via an online survey consisting of demographic questions, the New Ecological Paradigm Scale, and the Sustainability Attitudes in Nursing Survey 2 and two questions regarding the current inclusion of content. RESULTS: Eighty-one percent of respondents did not include health implications of climate change in their teaching content; 67% did not include health implications of sustainability. CONCLUSION: Results provide preliminary evidence of gaps and areas of need for curricular content related to climate change and sustainability.

Assessing Opioid Use Disorder Treatments in Trials Subject to Non-Adherence via a Functional Generalized Linear Mixed-Effects Model.

The opioid crisis in the United States poses a major threat to public health due to psychiatric and infectious disease comorbidities and death due to opioid use disorder (OUD). OUD is characterized by patterns of opioid misuse leading to persistent heavy use and overdose. The standard of care for treatment of OUD is medication-assisted treatment, in combination with behavioral therapy. Medications for opioid use disorder have been shown to improve OUD outcomes, including reduction and prevention of overdose. However, understanding the effectiveness of such medications has been limited due to non-adherence to assigned dose levels by study patients. To overcome this challenge, herein we develop a model that views dose history as a time-varying covariate. Proceeding in this fashion allows the model to estimate dose effect while accounting for lapses in adherence. The proposed model is used to conduct a secondary analysis of data collected from six efficacy and safety trials of buprenorphine maintenance treatment. This analysis provides further insight into the time-dependent treatment effects of buprenorphine and how different dose adherence patterns relate to risk of opioid use.

Effects of Buprenorphine Dose and Therapeutic Engagement on Illicit Opiate Use in Opioid Use Disorder Treatment Trials.

The impact of agonist dose and of physician, staff and patient engagement on treatment have not been evaluated together in an analysis of treatment for opioid use disorder. Our hypotheses were that greater agonist dose and therapeutic engagement would be associated with reduced illicit opiate use in a time-dependent manner. Publicly-available treatment data from six buprenorphine efficacy and safety trials from the Federally-supported Clinical Trials Network were used to derive treatment variables. Three novel predictors were constructed to capture the time weighted effects of buprenorphine dosage (mg buprenorphine per day), dosing protocol (whether physician could adjust dose), and clinic visits (whether patient attended clinic). We used time-in-trial as a predictor to account for the therapeutic benefits of treatment persistence. The outcome was illicit opiate use defined by self-report or urinalysis. Trial participants (N = 3022 patients with opioid dependence, mean age 36 years, 33% female, 14% Black, 16% Hispanic) were analyzed using a generalized linear mixed model. Treatment variables dose, Odds Ratio (OR) = 0.63 (95% Confidence Interval (95%CI) 0.59−0.67), dosing protocol, OR = 0.70 (95%CI 0.65−0.76), time-in-trial, OR = 0.75 (95%CI 0.71−0.80) and clinic visits, OR = 0.81 (95%CI 0.76−0.87) were significant (p-values < 0.001) protective factors. Treatment implications support higher doses of buprenorphine and greater engagement of patients with providers and clinic staff.

Measuring Cannulation Skills for Hemodialysis: Objective Versus Subjective Assessment.

Lack of cannulation skill during hemodialysis treatments results in poor clinical outcomes due to infiltration and other cannulation-related trauma. Unfortunately, training of patient care technicians and nurses, specifically on the "technical" aspects of cannulation, has traditionally not received much attention. Simulators have been successfully deployed in many medical specialties for assessment and training of clinical skills. However, simulators have not been as widely used in nursing, especially in the context of training clinical personnel in the dialysis unit. We designed a state-of-the-art simulator for quantifying skill for hemodialysis cannulation. In this study, 52 nurses and patient care technicians with varying levels of clinical experience performed 16 cannulations on the simulator with different fistula properties. We formulated a composite metric for objectively measuring overall success of cannulation and compared this metric with subjective assessment by experts. In addition, we examined if years of clinical experience correlated with objective and subjective scores for cannulation skill. Results indicated that, while subjective and objective metrics generally correlated with each other, the objective metric was more precise and better suited for quantifying cannulation skill. Further, the simulator-based objective metric provides several advantages over subjective ratings, including providing fine-grained assessment of skill, consistency in measurement unaffected by subjective biases, and basing assessment on a more complete evaluation of performance. Years of clinical experience, however, demonstrated little correlation with either method of skill assessment. The methods presented for cannulation skill assessment in this study, if widely applied, could result in improved cannulation skill among our PCTs and nurses, which could positively impact patient outcomes in a tangible way.

Motion Smoothness Metrics for Cannulation Skill Assessment: What Factors Matter?

Medical training simulators have the potential to provide remote and automated assessment of skill vital for medical training. Consequently, there is a need to develop "smart" training devices with robust metrics that can quantify clinical skills for effective training and self-assessment. Recently, metrics that quantify motion smoothness such as log dimensionless jerk (LDLJ) and spectral arc length (SPARC) are increasingly being applied in medical simulators. However, two key questions remain about the efficacy of such metrics: how do these metrics relate to clinical skill, and how to best compute these metrics from sensor data and relate them with similar metrics? This study addresses these questions in the context of hemodialysis cannulation by enrolling 52 clinicians who performed cannulation in a simulated arteriovenous (AV) fistula. For clinical skill, results demonstrate that the objective outcome metric flash ratio (FR), developed to measure the quality of task completion, outperformed traditional skill indicator metrics (years of experience and global rating sheet scores). For computing motion smoothness metrics for skill assessment, we observed that the lowest amount of smoothing could result in unreliable metrics. Furthermore, the relative efficacy of motion smoothness metrics when compared with other process metrics in correlating with skill was similar for FR, the most accurate measure of skill. These results provide guidance for the computation and use of motion-based metrics for clinical skill assessment, including utilizing objective outcome metrics as ideal measures for quantifying skill.

Nursing Education Amid a Pandemic: Mental Health in a Time of Virtual Learning.

BACKGROUND: The unprecedented pandemic presented new stresses and challenges in nursing education impacting the mental health of nursing students. PURPOSE: The purpose of this study was to evaluate the relationship between virtual learning and the mental health of nursing students. METHOD: This study used a descriptive, cross-sectional design with a convenience sample of 256 nursing students enrolled in a baccalaureate program. Data were collected through an online survey using 2 screening tools for stress, anxiety, and depression. RESULTS: Mean sum Patient Health Questionnaire-4 scores and subscale scores suggest that more than 40% of students experienced mild to moderate levels of psychological distress. Mean sum Perceived Stress Scale-10 scores indicate 84% of students experienced moderate levels of stress, and 14% experienced high levels of stress. CONCLUSIONS: During periods of societal crisis, faculty must be hypervigilant to the mental health needs of students.

Comparison of fetal growth by maternal prenatal acetaminophen use.

BACKGROUND: Equivocal findings exist regarding prenatal acetaminophen use and various adverse neonatal and childhood health outcomes, though with no data on fetal growth. We evaluated whether fetal growth differed by maternal acetaminophen use. METHODS: Racially diverse, healthy women with low-risk antenatal profiles from 12 US clinical centers were enrolled in a prospective cohort study and followed until delivery. Ultrasound measurements of fetal parameters and self-reported prenatal acetaminophen use were collected at enrollment and up to five follow-up visits. Prenatal acetaminophen use was dichotomized as none or any. RESULTS: Among 2291 women, 932 (41%) reported the use of acetaminophen medications during the current pregnancy. Estimated growth curves of fetal parameters did not differ between women reporting use of any medication containing acetaminophen and women with no reported use of the same. CONCLUSION: Among healthy mothers with low-risk pregnancies, maternal acetaminophen use was not associated with alterations in fetal growth.

Practical issues in using generalized estimating equations for inference on transitions in longitudinal data: What is being estimated?

Generalized estimating equations (GEEs) are commonly used to estimate transition models. When the Markov assumption does not hold but first-order transition probabilities are still of interest, the transition inference is sensitive to the choice of working correlation. In this paper, we consider a random process transition model as the true underlying data generating mechanism, which characterizes subject heterogeneity and complex dependence structure of the outcome process in a very flexible way. We formally define two types of transition probabilities at the population level: "naive transition probabilities" that average across all the transitions and "population-average transition probabilities" that average the subject-specific transition probabilities. Through asymptotic bias calculations and finite-sample simulations, we demonstrate that the unstructured working correlation provides unbiased estimators of the population-average transition probabilities while the independence working correlation provides unbiased estimators of the naive transition probabilities. For population-average transition estimation, we demonstrate that the sandwich estimator fails for unstructured GEE and recommend the use of either jackknife or bootstrap variance estimates. The proposed method is motivated by and applied to the NEXT Generation Health Study, where the interest is in estimating the population-average transition probabilities of alcohol use in adolescents.

Prospective Associations of Actual and Perceived Descriptive Norms with Drinking Among Emerging Adults.

BACKGROUND: Descriptive norms are commonly associated with participant drinking. However, study participants may incorrectly perceive that their peers drink about the same amount as they do, which would bias estimates of drinking homogeneity. OBJECTIVES: This research examined the magnitude of associations between emerging adults' reports of their own drinking and peer drinking measured the previous year by measures of (1) participants' perceptions of friends' drinking; and (2) actual drinking reported by nominated peers. METHODS: The data are from annual surveys conducted in 2014 and 2015, Waves 4 and 5 (the first 2 years after high school) of 7 annual assessments as part of the NEXT Generation Health Study (n = 323). Associations of participant alcohol use with perceived friend use (five closest, closest male, and closest female friends), and with actual peer use. Logistic regression analyses estimated the magnitudes of prospective associations between each measure of peer drinking at W4 and participant drinking at W5.

Cell Phone Use While Driving: Prospective Association with Emerging Adult Use.

Secondary task engagement such as cell phone use while driving is a common behavior among adolescents and emerging adults. Texting and other distracting cell phone use in this population contributes to the high rate of fatal car crashes. Peer engagement in similar risky driving behaviors, such as texting, could socially influence driver phone use behavior. The present study investigates the prospective association between peer and emerging adult texting while driving the first year after high school. Surveys were conducted with a national sample of emerging adults and their nominated peers. Binomial logistic regression analyses, adjusting for gender, race/ethnicity, parental education, and family affluence, showed that participants (n=212) with peers (n=675) who reported frequently texting while driving, were significantly more likely to text while driving the following year (odds ratio, 3.01; 95% CI, 1.19-7.59; P=0.05). The findings are consistent with the idea that peer texting behavior influences the prevalence of texting while driving among emerging adults.

Do Young Drivers Become Safer After Being Involved in a Collision?

As drivers age, their risk of being involved in a car collision decreases. The present study investigated if this trend is due, in part, to some risky drivers having a collision early in their driving lives and subsequently reducing their risky driving after that negative experience. Accelerometers and video cameras were installed in the vehicles of 16- to 17-year-old drivers ( N = 254), allowing coders to measure the number of g-force events (i.e., events in which a threshold acceleration level was exceeded) per 1,000 miles and the number of collisions. Among the 41 participants who experienced a severe collision, the rate of g-force events dropped significantly in the 1st month after the collision, remained unchanged for the 2nd month, and increased significantly in the 3rd month. There were no changes in the rate of g-force events at comparable time points for the drivers not involved in a collision. Being involved in a collision led to a decrease in risky driving, but this may have been a temporary effect.

Variability in measures of health and health behavior among emerging adults 1 year after high school according to college status.

OBJECTIVE: To examine changes in health behaviors among US emerging adults 1 year after high school. PARTICIPANTS: The national sample of participants (N = 1,927), including those attending 4-year college/university (n = 884), 2-year colleges/technical schools (n = 588), and no college (n = 455), participated in annual spring surveys 2013-2014. METHODS: Health behaviors were assessed the last year of high school and first year of college; differences by college status controlling for previous-year values were estimated using regression analyses. RESULTS: Relative to 4-year college attendees, those attending technical school/community college were less likely to binge drink (odds ratio [OR] = 0.57, confidence interval [CI] = 0.38-0.86) but more likely to speed (OR = 1.26, CI = 1.0-2.84), consume sodas (OR = 1.57, CI = 1.0-2.47), and report lower family satisfaction (p < .01), with marginally more physical and depressive symptoms. College nonattendees reported more DWI (driving while intoxicated; OR = 1.60, CI = 1.05-2.47), soda drinking (OR = 2.51, CI = 1.76-3.59), oversleeping (OR = 4.78, CI = 3.65-8.63), and less family satisfaction (p < .04). CONCLUSIONS: Health risk behaviors among emerging adults varied by college status.

Cluster adjusted regression for displaced subject data (CARDS): Marginal inference under potentially informative temporal cluster size profiles.

Ignorance of the mechanisms responsible for the availability of information presents an unusual problem for analysts. It is often the case that the availability of information is dependent on the outcome. In the analysis of cluster data we say that a condition for informative cluster size (ICS) exists when the inference drawn from analysis of hypothetical balanced data varies from that of inference drawn on observed data. Much work has been done in order to address the analysis of clustered data with informative cluster size; examples include Inverse Probability Weighting (IPW), Cluster Weighted Generalized Estimating Equations (CWGEE), and Doubly Weighted Generalized Estimating Equations (DWGEE). When cluster size changes with time, i.e., the data set possess temporally varying cluster sizes (TVCS), these methods may produce biased inference for the underlying marginal distribution of interest. We propose a new marginalization that may be appropriate for addressing clustered longitudinal data with TVCS. The principal motivation for our present work is to analyze the periodontal data collected by Beck et al. (1997, Journal of Periodontal Research 6, 497-505). Longitudinal periodontal data often exhibits both ICS and TVCS as the number of teeth possessed by participants at the onset of study is not constant and teeth as well as individuals may be displaced throughout the study.