Andersen's Revised Behavioral Model of Health Services Use (RBM) was used as a framework in this correlational cross-sectional study to examine factors associated with HIV testing among a sample of 251 rural African American cocaine users. All participants reported using cocaine and being sexually active within the past 30 days. Independent variables were categorized according to the RBM as predisposing, enabling, need, or health behavior factors. Number of times tested for HIV (never, one time, two to four times, five or more times) was the outcome of interest. In ordered logistic regression analyses, HIV testing was strongly associated with being female, of younger age (predisposing factors); having been tested for sexually transmitted diseases or hepatitis, ever having been incarcerated in jail or prison (enabling factors); and having had one sex partner the past 30 days (health behavior factor). Other sexual risk behaviors, drug use, health status, and perception of risk were not associated with HIV testing. Our findings confirm the importance of routine testing in all healthcare settings rather than risk-based testing.
To analyse amniotic fluid volume (AFV), specifically oligohydramnios or polyhydramnios, and associated pregnancy and neonatal outcomes in twin gestations through systematic review and meta-analysis.
Abstract Background Studies have shown that data collection by medical record abstraction (MRA) is a significant source of error in clinical research studies relying on secondary use data. Yet, the quality of data collected using MRA is seldom assessed. We employed a novel, theory-based framework for data quality assurance and quality control of MRA. The objective of this work is to determine the potential impact of formalized MRA training and continuous quality control (QC) processes on data quality over time. Methods We conducted a retrospective analysis of QC data collected during a cross-sectional medical record review of mother-infant dyads with Neonatal Opioid Withdrawal Syndrome. A confidence interval approach was used to calculate crude (Wald’s method) and adjusted (generalized estimating equation) error rates over time. We calculated error rates using the number of errors divided by total fields (“all-field” error rate) and populated fields (“populated-field” error rate) as the denominators, to provide both an optimistic and a conservative measurement, respectively. Results On average, the ACT NOW CE Study maintained an error rate between 1% (optimistic) and 3% (conservative). Additionally, we observed a decrease of 0.51 percentage points with each additional QC Event conducted. Conclusions Formalized MRA training and continuous QC resulted in lower error rates than have been found in previous literature and a decrease in error rates over time. This study newly demonstrates the importance of continuous process controls for MRA within the context of a multi-site clinical research study.
Experiences of violence and behaviors that increase the risk of acquiring a sexually transmitted infection are high among women in the United States, and they often intersect (Meyer, Springer, & Altice, 2011 Meyer, J. P., Springer, S. A., & Altice, F. L. (2011). Substance abuse, violence, and HIV in women: A literature review of the syndemic. Journal of Women's Health (2002), 20(7), 991–1006. doi:10.1089/jwh.2010.2328[Crossref] , [Google Scholar]; Montgomery et al., 2015 Montgomery, B., Rompalo, A., Hughes, J., Wang, J., Haley, D., Soto-Torres, L., & Hodder, S. (2015). Violence against women in selected areas of the united states.e1-e11. Am J Public Health, 105(10), 2156–2166 [Google Scholar]; World Health Organization (WHO), 2010 World Health Organization (WHO). (2010). Addressing violence against women and HIV/AIDS: What works?. Geneva, Switzerland: World Health Organization. [Google Scholar]). However, there are few evidence-based HIV-prevention interventions that address the special needs and challenges faced by female survivors of violence (Centers for Disease Control and Prevention, (CDC), 2017a Centers for Disease Control and Prevention. (2017a). Compendium of evidence-based interventions and best practices for HIV prevention. Atlanta, GA: Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, Sexual Transmitted Diseases and Tuberculosis Prevention. Retrieved from https://www.cdc.gov/hiv/research/interventionresearch/compendium/rr/index.html [Google Scholar]). To address this gap, we adapted and pilot-tested an existing evidence-based women-focused sexual risk-reduction intervention (The Future Is Ours) with 23 self-identified female survivors of violence. The intervention comprised eight-weekly, two-hour cognitive behavioral group sessions focusing on reducing sexual-risk and improving trauma-based coping skills. Using mixed-methods analyses, the adapted intervention was determined feasible and acceptable to participants, and preliminary results suggest that participation could reduce risk factors for sexually transmitted infections. Therefore, testing on a larger scale is warranted.
This study tests the psychometric properties and demographic variation of three culturally adapted versions of widely used religion scales—the Brief RCOPE, the Religious Support Scale, and items from the Multidimensional Measurement of Religiousness and Spirituality—in a community sample of cocaine-using African Americans. The unadapted measures have been previously validated but not in an African American cocaine-using population, which is a gap in the literature because religious institutions are important venues for health promotion in many Southern and rural areas. All the scales diverged from normality but most demonstrated acceptable internal reliability and convergent validity. Confirmatory factor analysis supported the factor structure of all scales except the Religious Support Scale. Correlations between religion scales and sample characteristics are provided and implications are discussed. Findings suggest that the factor structure and psychometric properties of the religion subscales are similar to other samples in this cohort of cocaine-using African Americans. These data provide initial support for the use of these instruments in future studies incorporating religious constructs with similar populations.
To explore the mediational effects of prejudice on the relationship between negative stereotypes and social distance (discrimination) in a sample of Veterans Administration health care providers.Data for this study were collected between August 2011 and April 2012 as part of a larger study examining provider attitudes and clinical expectations toward 2 hypothetical vignette patients: 1 with schizophrenia and 1 without schizophrenia. Survey responses from health care providers were gathered using 3 well-recognized measures: the 9-item Semantic Differential Scale, 9-item Attribution Questionnaire, and Social Distance Scale. A path model was tested using Mplus version 6 to investigate whether prejudice mediates the relation between provider stereotyping and social distance.A total of 351 health care providers responded to the survey. The results indicate that there was a significant positive correlation between provider stereotypes and prejudice (β = 0.298, P < .0001), and prejudice significantly predicted social distance (β = 0.190, P = .002). The indirect effect of stereotypes on social distance, tested using bootstrapped standard errors, was also statistically significant (β = 0.167, P = .007).Findings from this study confirm the important role of affective reactions (prejudice) in generating discriminatory behavior (social distancing) among health care providers. The findings will also help future researchers identify potential targets for interventions to decrease stigma among health care providers.
To estimate a classifier's error in predicting future observations, bootstrap methods have been proposed as reduced-variation alternatives to traditional cross-validation (CV) methods based on sampling without replacement. Monte Carlo (MC) simulation studies aimed at estimating the true misclassification error conditional on the training set are commonly used to compare CV methods. We conducted an MC simulation study to compare a new method of bootstrap CV (BCV) to k-fold CV for estimating clasification error. For the low-dimensional conditions simulated, the modest positive bias of k-fold CV contrasted sharply with the substantial negative bias of the new BCV method. This behavior was corroborated using a real-world dataset of prognostic gene-expression profiles in breast cancer patients. Our simulation results demonstrate some extreme characteristics of variance and bias that can occur due to a fault in the design of CV exercises aimed at estimating the true conditional error of a classifier, and that appear not to have been fully appreciated in previous studies. Although CV is a sound practice for estimating a classifier's generalization error, using CV to estimate the fixed misclassification error of a trained classifier conditional on the training set is problematic. While MC simulation of this estimation exercise can correctly represent the average bias of a classifier, it will overstate the between-run variance of the bias. We recommend k-fold CV over the new BCV method for estimating a classifier's generalization error. The extreme negative bias of BCV is too high a price to pay for its reduced variance.
Abstract Background Advance Care Planning via Group Visits (ACP-GV) is a patient-centered intervention facilitated by a clinician using a group modality to promote healthcare decision-making among veterans. Participants in the group document a “Next Step” to use in planning for their future care needs. The next step may include documentation of preferences in an advance directive, discussing plans with family, or anything else to fulfill their ACP needs. This evaluation seeks to determine whether there are identifiable subgroups of group participants with differing needs prior to delivery of the ACP-GV program and, if so, to use information about the subgroups to enhance the program offered to veterans in United States Department of Veterans Affairs (VA) healthcare settings. Methods We conducted a secondary analysis of national data from a quality improvement evaluation. Patient- and provider-level data from administrative healthcare records for VA users in all 50 states, territories, and the District of Columbia provides data on veterans attending ACP-GV during federal fiscal years 2018–2022 ( N = 26,857). Latent class analysis seeks to identify the various subgroups of veterans based on their level of ACP self-efficacy before attending ACP-GV and any demographic differences across the resulting subgroups of veterans attending ACP-GV. ACP self-efficacy is derived from seven items obtained from a participant worksheet used during the group. Results Analysis revealed two distinct groups of veterans, distinguishable by their pre-ACP-GV levels of one aspect of ACP self-efficacy: prior knowledge of ACP. Veterans with higher prior knowledge of ACP are associated with an identified next step focused on checking their current AD status and updating it, and veterans with lower ACP prior knowledge are associated with identifying a next step to discuss ACP more fully with family. Differences in age, sex, race, ethnicity, and marital status exist across subgroups of veterans. Conclusion Greater attention must be paid to ACP and veterans’ prior knowledge of ACP to consistently encourage annual review and status updates.
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