Development of short forms for screening children's dental caries and urgent treatment needs using item response theory and machine learning methods.

OBJECTIVES: Surveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children. METHODS: This cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations. RESULTS: We developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses. CONCLUSIONS: The combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.

Increasing Urban African American Women's Readiness for Pre-exposure Prophylaxis: A Pilot Study of the Women Prepping for PrEp Plus Program (WP3+).

BACKGROUND: African American women are disproportionately at risk for HIV infection. To increase women's readiness to consider taking pre-exposure prophylaxis (PrEP), we conducted a pilot study of Women Prepping for PrEP Plus (WP3+). Adapted from an evidence-based HIV risk reduction intervention for African American couples who are HIV-serodiscordant, WP3+ is a group-based culturally congruent program designed for African American women without HIV. METHODS: Women were screened for eligibility; if eligible, they were invited to participate in the four-session WP3+ group. Participants completed surveys at baseline (n = 47) and post-implementation (n = 28); surveys assessed demographics, HIV and PrEP knowledge, depression and posttraumatic stress (PTS) symptoms, substance use, sexual risk behaviors, health care-related discrimination, and social support. In a process evaluation, a subset of women completed qualitative interviews at baseline (n = 35) and post-implementation (n = 18); the interviews were designed to converge with (e.g., on HIV and PrEP knowledge) and expand upon (e.g., unmeasured perceived impacts of WP3+) quantitative measures. To triangulate with the quantitative data, deductive qualitative analysis concentrated on women's knowledge and awareness of PrEP and HIV, their relationship dynamics and challenges, and their considerations (e.g., barriers, facilitators) related to taking PrEP; inductive analysis focused on women's experiences in the intervention. RESULTS: Participants in the WP3+ intervention reported: improved proportion of condom use in the past 90 days (p < .01) and in a typical week (p < .05); reduced PTS symptoms (p < .05); increased HIV knowledge (p < .0001) and awareness of PrEP (p < .001); and greater consideration of using PrEP (p < .001). In interviews, participants expressed not only increased knowledge but also appreciation for learning how to protect themselves against HIV, communicate with their partners, and take charge of their health, and they expressed greater receptiveness to using PrEP as a result of the knowledge and skills they gained. CONCLUSIONS: The WP3+ pilot study demonstrated preliminary efficacy and acceptability as an HIV-prevention program for African American women. A controlled trial is needed to confirm its efficacy for increasing PrEP use among African American women.

Optimal parameterizing manifolds for anticipating tipping points and higher-order critical transitions.

A general, variational approach to derive low-order reduced models from possibly non-autonomous systems is presented. The approach is based on the concept of optimal parameterizing manifold (OPM) that substitutes more classical notions of invariant or slow manifolds when the breakdown of "slaving" occurs, i.e., when the unresolved variables cannot be expressed as an exact functional of the resolved ones anymore. The OPM provides, within a given class of parameterizations of the unresolved variables, the manifold that averages out optimally these variables as conditioned on the resolved ones. The class of parameterizations retained here is that of continuous deformations of parameterizations rigorously valid near the onset of instability. These deformations are produced through the integration of auxiliary backward-forward systems built from the model's equations and lead to analytic formulas for parameterizations. In this modus operandi, the backward integration time is the key parameter to select per scale/variable to parameterize in order to derive the relevant parameterizations which are doomed to be no longer exact away from instability onset due to the breakdown of slaving typically encountered, e.g., for chaotic regimes. The selection criterion is then made through data-informed minimization of a least-square parameterization defect. It is thus shown through optimization of the backward integration time per scale/variable to parameterize, that skilled OPM reduced systems can be derived for predicting with accuracy higher-order critical transitions or catastrophic tipping phenomena, while training our parameterization formulas for regimes prior to these transitions takes place.

Adherence to Antiretrovirals and HIV Viral Suppression Under COVID-19 Pandemic Interruption - Findings from a Randomized Clinical Trial Using Ingestible Sensors to Monitor Adherence.

The COVID-19 pandemic had a significant impact on vulnerable populations, including people living with HIV. California implemented a coronavirus lockdown (stay-at-home order) in March 2020, which ended in January 2021. We evaluated the pandemic's impact on both clinical outcomes of HIV RNA viral load (VL) and retention rate in a randomized clinical trial conducted from May 2018 to October 2020. The intervention group took co-encapsulated antiretrovirals (ARVs) with ingestible sensor (IS) pills from baseline through week 16. The IS system has the capacity to monitor adherence in real-time using a sensor patch, a mobile device, and supporting software. Both the IS and usual care (UC) groups were followed monthly for 28 weeks. Longitudinal mixed-effects models with random intercept and slope (RIAS) were used to fit log VL and self-reported adherence. The sample size of the study was 112 (54 in IS). Overall, the retention rate at week 28 was 86%, with 90% before the lockdown and 83% after the lockdown. The lockdown strengthened the associations between adherence and VL. Before the lockdown, a 10% increase in adherence was associated with a 0.2 unit decrease in log VL (ß = -1.88, p = 0.004), while during the lockdown, the association was a 0.41-unit decrease (ß = -2.27, p = 0.03). The pandemic did not have a significant impact on our adherence-focused intervention. Our findings regarding the intervention effect remain valid. TRIAL REGISTRATION NUMBER: NCT02797262. Date registration: September 2015.

Women-Centered Program for Women of Color (WC4WC): A Community-Based Participatory, Culturally Congruent Sexual Health Intervention in Los Angeles County, California.

The Women-Centered Program for Women of Color, a culturally congruent sexual health intervention, was implemented in 2018 in Los Angeles County, California, according to the principles of community-based participatory research: enhancing community capacity, establishing sustainable programs, and translating research findings to community settings. Participants exhibited significantly increased knowledge of and interest in preexposure prophylaxis (PrEP) and postexposure prophylaxis (PEP) over time, but no significant change in condom use was evident. Booster sessions are needed to maintain interest in PrEP and PEP given concerns about reproductive and sexual health. (Am J Public Health. 2023;113(S2):S110-S114. https://doi.org/10.2105/AJPH.2023.307296).

Association between low fluoride exposure and children's intelligence: a meta-analysis relevant to community water fluoridation.

OBJECTIVES: Previous meta-analyses have mainly focused on studies conducted in endemic fluorosis areas with relatively high fluoride concentrations. These are impoverished rural communities in China, India, and Iran, and the findings cannot be generalised to developed countries. Therefore, we investigated the association between fluoride concentrations relevant to community water fluoridation and children's cognition measured with IQ scores by synthesising effect sizes reported in observational studies. METHODS: A previous meta-analysis and the National Toxicology Program database that included a search of multiple databases and the authors' search of PubMed, Google Scholar, and Mendeley provided the data. Cross-sectional and cohort studies examining the association between fluoride and children's cognition and intelligence scores were selected. Two reviewers abstracted data using standard procedures. We performed three meta-analyses to synthesise the effects using the random effects models. RESULTS: Eight studies of standardized mean difference in IQ scores from non-endemic fluorosis areas found no statistically significant difference between recommended and lower levels of fluoride (standardized mean difference = 0.07; 95% confidence interval: -0.02, 0.17; I2 = 0%), and no significant fluctuation in IQ scores across the differences in fluoride concentrations by non-linear modeling with restricted cubic spline (P = 0.21). Meta-analyses of children's and maternal spot urinary fluoride associated pooled regression coefficients (Betachildren = 0.16; 95% confidence interval: -0.40, 0.73; P = 0.57; I2 = 0%, Betamaternal = -0.92; 95% CI: -3.29, 1.46; P = 0.45; I2 = 72%) were not statistically significant. Further regression analysis by standardizing absolute mean IQ scores from lower fluoride areas did not show a relationship between F concentration and IQ scores (Model Likelihood-ratio test: P-value = 0.34.) CONCLUSIONS: These meta-analyses show that fluoride exposure relevant to community water fluoridation is not associated with lower IQ scores in children. However, the reported association observed at higher fluoride levels in endemic areas requires further investigation.

Characterization of COVID-19 Vaccine Hesitancy Among Essential Workforce Members of a Large Safety Net Urban Medical Center.

OBJECTIVES: Vaccine hesitancy among essential workers remains a significant public health challenge. We examined psychological constructs of perceived susceptibility, threat, and self-efficacy and their associations with COVID-19 vaccine hesitancy among a racially and ethnically diverse essential workforce population. METHODS: We performed a cross-sectional survey of essential workers from September-December 2020 at a large Los Angeles safety-net medical center as part of a program offering free COVID-19 serology testing. Program participants completed a standardized survey at the time of phlebotomy. Hierarchical logistic regression was utilized to determine factors independently associated with vaccine hesitancy. RESULTS: Among 1327 persons who had serology testing, 1235 (93%) completed the survey. Of these, 958 (78%) were healthcare workers. Based on expressed intent, 22% were vaccine-hesitant 78% were vaccine acceptors. In our multivariate model, vaccine hesitancy was associated with female gender [aOR = 2.09; 95% CI (1.44-3.05)], African American race [aOR = 4.32; (2.16-8.62)], LatinX ethnicity [aOR = 2.47; 95% CI (1.51-4.05)] and history of not/sometimes receiving influenza vaccination [aOR = 4.39; 95% CI (2.98-6.48)]. Compared to nurses, vaccine hesitancy was lower among physicians [aOR = 0.09; 95% CI (0.04-0.23)], non-nursing/non-physician healthcare workers [aOR = 0.55; 95% CI (0.33-0.92)], and non-healthcare care workers [aOR = 0.53; 95% CI (0.36-0.78)]. CONCLUSIONS: Among a racially/ethnically diverse group of safety net medical center essential workers, COVID-19 vaccine hesitancy was associated with racial/ethnic minority groups, employment type, and prior influenza vaccination hesitancy. Interestingly, we found no association with the Health Belief Model construct measures of perceived susceptibility, threat, and self-efficacy. Psychological constructs not assessed may be drivers of vaccine hesitancy in our population.

Ingestible sensor system for measuring, monitoring and enhancing adherence to antiretroviral therapy: An open-label, usual care-controlled, randomised trial.

BACKGROUND: Co-encapsulated antiretrovirals (ARVs) with ingestible sensor (IS) has the capacity to monitor adherence in real-time using a sensor patch, a mobile device, and supporting software. We evaluated the acceptability, effectiveness, and sustainability of the IS system with real-time text reminders. METHODS: Participants were recruited from HIV clinics in Los Angeles and were randomised 1:1 to IS or usual care (UC) group. Adherence to ARVs (primary outcome) was measured by IS system (IS group only), plasma ARV concentration, and self-report. IS-measured adherence was clustered by group-based trajectory model and was validated by ARV concentration summarized by integrated pharmacokinetic adherence measure (IPAM) score. HIV RNA viral load (VL) was compared between IS and UC group. FINDINGS: A total of 112 (IS = 54, UC = 58) participants who completed baseline with at least one follow-up data collection were included in analyses. Overall satisfaction rate for the IS system was >90%. The IPAM score was higher (0.018, 95% CI: -0.098-0.134, p = 0.75) and VL decayed faster (-0.020, 95% CI: -0.042-0.002, p = 0.08) in the IS group compared with the UC group. The ingestible sensor system was well tolerated by study participants. INTERPRETATION: The IS system was well accepted by participants and its use was associated with improved adherence and lower HIV RNA VL. The findings provide a potentially effective strategy for improving adherence. FUNDING: This work was supported by grant R01-MH110056 from the National Institute of Mental Health (NIMH)/National Institutes of Health (NIH). Y. Wang was in part supported by the NIMH/NIH award T32MH080634. E. Daar was in part supported by the National Center for Advancing Translational Sciences through UCLACTSI Grant UL1TR001881. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Generic generation of noise-driven chaos in stochastic time delay systems: Bridging the gap with high-end simulations.

Nonlinear time delay systems produce inherently delay-induced periodic oscillations, which are, however, too idealistic compared to observations. We exhibit a unified stochastic framework to systematically rectify such oscillations into oscillatory patterns with enriched temporal variabilities through generic, nonlinear responses to stochastic perturbations. Two paradigms of noise-driven chaos in high dimension are identified, fundamentally different from chaos triggered by parameter-space noise. Noteworthy is a low-dimensional stretch-and-fold mechanism, leading to stochastic strange attractors exhibiting horseshoe-like structures mirroring turbulent transport of passive tracers. The other is high-dimensional , with noise acting along the critical eigendirection and transmitted to "deeper" stable modes through nonlinearity, leading to stochastic attractors exhibiting swarm-like behaviors with power-law and scale break properties. The theory is applied to cloud delay models to parameterize missing physics such as intermittent rain and Lagrangian turbulent effects. The stochastically rectified model reproduces with fidelity complex temporal variabilities of open-cell oscillations exhibited by high-end cloud simulations.

Quantitative data collection approaches in subject-reported oral health research: a scoping review.

BACKGROUND: This scoping review reports on studies that collect survey data using quantitative research to measure self-reported oral health status outcome measures. The objective of this review is to categorize measures used to evaluate self-reported oral health status and oral health quality of life used in surveys of general populations. METHODS: The review is guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) with the search on four online bibliographic databases. The criteria include (1) peer-reviewed articles, (2) papers published between 2011 and 2021, (3) only studies using quantitative methods, and (4) containing outcome measures of self-assessed oral health status, and/or oral health-related quality of life. All survey data collection methods are assessed and papers whose methods employ newer technological approaches are also identified. RESULTS: Of the 2981 unduplicated papers, 239 meet the eligibility criteria. Half of the papers use impact scores such as the OHIP-14; 10% use functional measures, such as the GOHAI, and 26% use two or more measures while 8% use rating scales of oral health status. The review identifies four data collection methods: in-person, mail-in, Internet-based, and telephone surveys. Most (86%) employ in-person surveys, and 39% are conducted in Asia-Pacific and Middle East countries with 8% in North America. Sixty-six percent of the studies recruit participants directly from clinics and schools, where the surveys were carried out. The top three sampling methods are convenience sampling (52%), simple random sampling (12%), and stratified sampling (12%). Among the four data collection methods, in-person surveys have the highest response rate (91%), while the lowest response rate occurs in Internet-based surveys (37%). Telephone surveys are used to cover a wider population compared to other data collection methods. There are two noteworthy approaches: 1) sample selection where researchers employ different platforms to access subjects, and 2) mode of interaction with subjects, with the use of computers to collect self-reported data. CONCLUSION: The study provides an assessment of oral health outcome measures, including subject-reported oral health status and notes newly emerging computer technological approaches recently used in surveys conducted on general populations. These newer applications, though rarely used, hold promise for both researchers and the various populations that use or need oral health care.

The ATEAM study: Advances in technology to enhance PrEP adherence monitoring (ATEAM) among young men who have sex with men.

Young age has consistently correlated with lower adherence to pre-exposure prophylaxis (PrEP) in young men who have sex with men (YMSM). Digital medicine, a dynamic healthcare platform of wearable physiological sensors and mobile communication technology that can respond to medication nonadherence rapidly, has the potential in promoting PrEP adherence. We evaluated the feasibility and acceptability of Proteus Discover, a digital monitoring adherence system, to measure PrEP adherence and provide real-time feedback among cisgender YMSM and transgender women. One hundred HIV-negative young men and transgender women ages 16-24 years were enrolled in a 24-week randomized controlled crossover study to tenofovir disoproxil fumarate with emtricitabine (TDF/FTC) coencapsulated with Proteus Discover versus TDF/FTC standard-of-care. Participants in the 12-week Proteus Discover arm received weekly SMS text messages to promote pill taking based on Proteus Discover adherence data. Dried blood spots (DBS) were collected at 4-week intervals for tenofovir diphosphate (TFV-DP) in red blood cells as the referent and questionnaires were completed to assess acceptability, usability, and patterns of use. Linear mixed models analyzed the relationship between 30-day adherence measured by DBS and Proteus Discover. PrEP adherence was high overall. Adherence, as measured by DBS, was correlated with adherence as measured by Proteus Discover (p value = 0.03). Most participants reported that Proteus Discover helped them take their PrEP daily and that the system was easy to use. However, a majority (53.5%-60.5%) disagreed with the statement that wearing the patch was not an issue. There was an incremental increase in TFV-DP in DBS with adherence by Proteus Discover. More research is warranted to explore optimizing PrEP adherence for youth through real-time monitoring.

Conditional Gaussian nonlinear system: A fast preconditioner and a cheap surrogate model for complex nonlinear systems.

Developing suitable approximate models for analyzing and simulating complex nonlinear systems is practically important. This paper aims at exploring the skill of a rich class of nonlinear stochastic models, known as the conditional Gaussian nonlinear system (CGNS), as both a cheap surrogate model and a fast preconditioner for facilitating many computationally challenging tasks. The CGNS preserves the underlying physics to a large extent and can reproduce intermittency, extreme events, and other non-Gaussian features in many complex systems arising from practical applications. Three interrelated topics are studied. First, the closed analytic formulas of solving the conditional statistics provide an efficient and accurate data assimilation scheme. It is shown that the data assimilation skill of a suitable CGNS approximate forecast model outweighs that by applying an ensemble method even to the perfect model with strong nonlinearity, where the latter suffers from filter divergence. Second, the CGNS allows the development of a fast algorithm for simultaneously estimating the parameters and the unobserved variables with uncertainty quantification in the presence of only partial observations. Utilizing an appropriate CGNS as a preconditioner significantly reduces the computational cost in accurately estimating the parameters in the original complex system. Finally, the CGNS advances rapid and statistically accurate algorithms for computing the probability density function and sampling the trajectories of the unobserved state variables. These fast algorithms facilitate the development of an efficient and accurate data-driven method for predicting the linear response of the original system with respect to parameter perturbations based on a suitable CGNS preconditioner.

Using social and sexual networking mobile applications to promote HIV testing, medical care and prevention services among Latino men who have sex with men in Los Angeles County, California, USA.

HIV disproportionately affects Latinos versus Whites, with Latinos having higher rates of HIV. Additionally, many HIV-positive Latinos are unaware of their infection. Proyecto Protégete, an HIV prevention intervention developed for Latino men who have sex with men (MSM), used social and sexual networking mobile applications (apps) to recruit individuals for HIV testing and linkage to medical care and prevention services. This study occurred in Los Angeles County, California, USA from December 18, 2015 to April 22, 2017. The study's primary aim was to assess Proyecto Protégete's ability to successfully recruit Latino MSM involved in high-risk sexual activities. A secondary aim was to evaluate its capacity to promote HIV testing and linkage to HIV medical care and prevention services among this population by comparing it to two programs with similar samples. Comparisons using Fisher's Exact Test were conducted between Proyecto Protégete and the HIV testing program of the agency in which Proyecto Protégete was located and the County-funded HIV testing programs to compare the samples' rates of HIV-positive Latino MSM identified through HIV testing and linked to HIV medical care and prevention services. Participants were recruited through seven apps. In Proyecto Protégete, 9,573 individuals completed the screener, 4,657 were eligible, and 359 (7.7% of those eligible) enrolled. Among those enrolled, 79% reported anal sex without a condom in the previous twelve months; 51% reported anal sex under the influence of alcohol. The HIV positivity rates were as follows: Proyecto Protégete, 1.71%; the agency, 1.25% (p = .293, compared to Proyecto Protégete); and the County, 1.09% (p = .172, compared to Proyecto Protégete). The rates of those confirmed as new HIV-positives and linked to medical care within 30 days were as follows: Proyecto Protégete, 71.4%; the agency, 81.5% (p = .450, compared to Proyecto Protégete); and the County, 77.3% (p = .503, compared to Proyecto Protégete). Proyecto Protégete had a higher rate of linked referrals to prevention services than the agency's testing program (19.5% versus 8.3%, p < .001). Proyecto Protégete experienced successes in some areas but not in others. Future research should build on Proyecto Protégete's experiences to promote HIV-related services among Latino MSM.

Investigating Perceptions of Teachers and School Nurses on Child and Adolescent Oral Health in Los Angeles County.

This study reports the results of focus groups with school nurses and teachers from elementary, middle, and high schools to explore their perceptions of child and adolescent oral health. Participants included 14 school nurses and 15 teachers (83% female; 31% Hispanic; 21% White; 21% Asian; 14% African American; and 13% Others). Respondents were recruited from Los Angeles County schools and scheduled by school level for six one-hour focus groups using Zoom. Audio recordings were transcribed, reviewed, and saved with anonymization of speaker identities. NVivo software (QSR International, Melbourne, Australia) was used to facilitate content analysis and identify key themes. The nurses' rate of "Oral Health Education" comments statistically exceeded that of teachers, while teachers had higher rates for "Parental Involvement" and "Mutual Perception" comments. "Need for Care" was perceived to be more prevalent in immigrants to the United States based on student behaviors and complaints. "Access to Care" was seen as primarily the nurses' responsibilities. Strong relationships between community clinics and schools were viewed by some as integral to students achieving good oral health. The results suggest dimensions and questions important to item development for oral health surveys of children and parents to address screening, management, program assessment, and policy planning.

Shock trace prediction by reduced models for a viscous stochastic Burgers equation.

Viscous shocks are a particular type of extreme event in nonlinear multiscale systems, and their representation requires small scales. Model reduction can thus play an essential role in reducing the computational cost for the prediction of shocks. Yet, reduced models typically aim to approximate large-scale dominating dynamics, which do not resolve the small scales by design. To resolve this representation barrier, we introduce a new qualitative characterization of the space-time locations of shocks, named the "shock trace," via a space-time indicator function based on an empirical resolution-adaptive threshold. Unlike exact shocks, the shock traces can be captured within the representation capacity of the large scales, thus facilitating the forecast of the timing and locations of the shocks utilizing reduced models. Within the context of a viscous stochastic Burgers equation, we show that a data-driven reduced model, in the form of nonlinear autoregression (NAR) time series models, can accurately predict the random shock traces, with relatively low rates of false predictions. Furthermore, the NAR model, which includes nonlinear closure terms to approximate the feedback from the small scales, significantly outperforms the corresponding Galerkin truncated model in the scenario of either noiseless or noisy observations. The results illustrate the importance of the data-driven closure terms in the NAR model, which account for the effects of the unresolved dynamics brought by nonlinear interactions.

Condom use consistency among South African HIV serodiscordant couples following an HIV risk-reduction intervention.

Background: Although there are several ways to transmit HIV, condomless sex remains the primary mode in sub-Saharan Africa, including South Africa, with KwaZulu-Natal Province being one of the epicentres of HIV infection. This study explored the use of condoms in serodiscordant couples who were exposed to an HIV-risk reduction intervention that aimed to improve condom use and reduce the spread of HIV.Methods: A Total of 30 couples completed a paper-based questionnaire on their demographics and general health at baseline and 3 months, plus a semi-structured questionnaire with four domains. An analysis of HIV knowledge, condom use, condom use attitudes and protection perceptions about how other serodiscordant couples behave was conducted following a 12-week HIV risk reduction intervention. Participants were randomised 2:1 into intervention and control groups.Results: Condom use increased from 55% at baseline to 73.7% (p = .0047) at 3 months for the intervention group and condom use in the last 7 days increased from 53% to 86% (p = .0117). For the control group, condom use remained low at the 3 months follow up period (p = .625). HIV knowledge improved significantly from baseline to 3 months for the intervention group (p < .0001), as well as the control group (p = .0005). Negative HIV condom use attitude scores in both groups decreased significantly from baseline to 3 months; intervention group (p = .0059) and control group (p = .0007).Conclusion: HIV knowledge and condom use improved significantly, while negative condom use attitudes and HIV protection perceptions decreased significantly following exposure to a risk-reduction intervention, suggesting that HIV preventive interventions should focus on partnership interventions.

Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7.

BACKGROUND: Dental caries is the most common chronic childhood infectious disease and is a serious public health problem affecting both developing and industrialized countries, yet it is preventable in most cases. This study evaluated the potential of screening for dental caries among children using a machine learning algorithm applied to parent perceptions of their child's oral health assessed by survey. METHODS: The sample consisted of 182 parents/caregivers and their children 2-7 years of age living in Los Angeles County. Random forest (a machine learning algorithm) was used to identify survey items that were predictors of active caries and caries experience. We applied a three-fold cross-validation method. A threshold was determined by maximizing the sum of sensitivity and specificity conditional on the sensitivity of at least 70%. The importance of survey items to classifying active caries and caries experience was measured using mean decreased Gini (MDG) and mean decreased accuracy (MDA) coefficients. RESULTS: Survey items that were strong predictors of active caries included parent's age (MDG = 0.84; MDA = 1.97), unmet needs (MDG = 0.71; MDA = 2.06) and the child being African American (MDG = 0.38; MDA = 1.92). Survey items that were strong predictors of caries experience included parent's age (MDG = 2.97; MDA = 4.74), child had an oral health problem in the past 12 months (MDG = 2.20; MDA = 4.04) and child had a tooth that hurt (MDG = 1.65; MDA = 3.84). CONCLUSION: Our findings demonstrate the potential of screening for active caries and caries experience among children using surveys answered by their parents.

Stochastic rectification of fast oscillations on slow manifold closures.

The problems of identifying the slow component (e.g., for weather forecast initialization) and of characterizing slow-fast interactions are central to geophysical fluid dynamics. In this study, the related rectification problem of slow manifold closures is addressed when breakdown of slow-to-fast scales deterministic parameterizations occurs due to explosive emergence of fast oscillations on the slow, geostrophic motion. For such regimes, it is shown on the Lorenz 80 model that if 1) the underlying manifold provides a good approximation of the optimal nonlinear parameterization that averages out the fast variables and 2) the residual dynamics off this manifold is mainly orthogonal to it, then no memory terms are required in the Mori-Zwanzig full closure. Instead, the noise term is key to resolve, and is shown to be, in this case, well modeled by a state-independent noise, obtained by means of networks of stochastic nonlinear oscillators. This stochastic parameterization allows, in turn, for rectifying the momentum-balanced slow manifold, and for accurate recovery of the multiscale dynamics. The approach is promising to be further applied to the closure of other more complex slow-fast systems, in strongly coupled regimes.

Consumer Assessment of Healthcare Providers and Systems (CAHPS®) survey of experiences with ambulatory healthcare for Asians and non-Hispanic Whites in the United States.

BACKGROUND: Differences in experiences of care reported by Asian Americans (Asians) compared to non-Hispanic Whites (Whites) may be due to lack of measurement invariance. METHODS: We evaluated the three-factor structure and the equivalence of responses to the Consumer Assessment of Healthcare Providers and Systems (CAHPS®) Clinical and Group (CG-CAHPS) Adult Visit Survey 1.0 and compared care experiences of Asians and Whites. Thirteen questions were used to elicit reports about specific aspects of care and two questions assessed overall care perceptions. This analysis of the CAHPS database included 769 providers and 266,327 respondents. Most surveys (98%) were administered by mail and the rest (2%) by phone. Only 0.5% of the surveys were administered in Spanish. The sample was 64% female, 89% White and 2% Asian, 39% 65 years or older, and 32% were high school graduates or less. RESULTS: A three-factor model was supported by categorical confirmatory factor analysis using weighted least squares with mean and variance adjustment: confirmatory fit index (CFI) = 0.99 and root mean squared error of approximation (RMSEA) = 0.03). A multi-group configural invariance model also fit the data well: (CFI = 0.993, RMSEA = 0.031). Regression models indicated that Asians reported worse access, lower scores on office staff courtesy and helpfulness and rating their doctors and were less likely to recommend their doctors to family/friends than did Whites. CONCLUSIONS: Use of the CG-CAHPS Adult Visit Survey 1.0 to assess perceptions of care by Asians and Whites is supported. Quality improvement efforts are needed to address worse experiences of care among Asians in the United States.

Random forest machine learning algorithm predicts virologic outcomes among HIV infected adults in Lausanne, Switzerland using electronically monitored combined antiretroviral treatment adherence.

Machine Learning (ML) can improve the analysis of complex and interrelated factors that place adherent people at risk of viral rebound. Our aim was to build ML model to predict RNA viral rebound from medication adherence and clinical data. Patients were followed up at the Swiss interprofessional medication adherence program (IMAP). Sociodemographic and clinical variables were retrieved from the Swiss HIV Cohort Study (SHCS). Daily electronic medication adherence between 2008-2016 were analyzed retrospectively. Predictor variables included: RNA viral load (VL), CD4 count, duration of ART, and adherence. Random Forest, was used with 10 fold cross validation to predict the RNA class for each data observation. Classification accuracy metrics were calculated for each of the 10-fold cross validation holdout datasets. The values for each range from 0 to 1 (better accuracy). 383 HIV+ patients, 56% male, 52% white, median (Q1, Q3): age 43 (36, 50), duration of electronic monitoring of adherence 564 (200, 1333) days, CD4 count 406 (209, 533) cells/mm3, time since HIV diagnosis was 8.4 (4, 13.5) years, were included. Average model classification accuracy metrics (AUC and F1) for RNA VL were 0.6465 and 0.7772, respectively. In conclusion, combining adherence with other clinical predictors improve predictions of RNA.