Examining a proposed job retention model for adult workers with mental retardation in supported employment

This quantitative study investigated the predictive relationships and interaction between factors such as work-related social behaviors (WRSB), self-determination (SD), person-job congruency (PJC), job performance (JP), job satisfaction (JS), and job retention (JR). A convenience sample of 100 working adults with MR were selected from supported employment agencies. Data were collected using a survey test battery of standardized instruments. The hypotheses were analyzed using three multiple regression analyses to identify significant relationships. Beta weights and hierarchical regression analysis determined the percentage of the predictor variables contribution to the total variance of the criterion variables, JR, JP, and JS. ^ The findings highlight the importance of self-determination skills in predicting job retention, satisfaction, and performance for employees with MR. Consistent with the literature and hypothesized model, there was a predictive relationship between SD, JS and JR. Furthermore, SD and PJC were predictors of JP. SD and JR were predictors of JS. Interestingly, the results indicated no significant relationship between JR and JP, or between JP and JS, or between PJC and JS. This suggests that there is a limited fit between the hypothesized model and the study's findings. However, the theoretical contribution made by this study is that self-determination is a particularly relevant predictor of important work outcomes including JR, JP, and JS. This finding is consistent with Deci's (1992) Self-Determination Theory and Wehmeyer's (1996) argument that SD skills in individuals with disabilities have important consequences for the success in transitioning from school to adult and work life. This study provides job retention strategies that offer rehabilitation and HR professionals a useful structure for understanding and implementing job retention interventions for people with MR. ^ The study concluded that workers with mental retardation who had more self-determination skills were employed longer, more satisfied, and better performers on the job. Also, individuals whose jobs were matched to their interests and abilities (person-job congruency) were better at self-determination skills. ^

The mathematics anxiety of bilingual community college students

Math anxiety levels and performance outcomes were compared for bilingual and monolingual community college Intermediate Algebra students attending a culturally diverse urban commuter college. Participants (N = 618, 250 men, 368 women; 361 monolingual, 257 bilingual) completed the Abbreviated Math Anxiety Scale (AMAS) and a demographics instrument. Bilingual and monolingual students reported comparable mean AMAS scores (20.6 and 20.7, respectively) and comparable proportions of math anxious individuals (50% and 48%, respectively). Factor analysis of AMAS scores, using principal component analysis by varimax rotation, yielded similar two-factor structures for both populations -- assessment and learning content -- accounting for 65.6% of the trace for bilingual AMAS scores. Statistically significant predictor variables for levels of math anxiety for the bilingual participants included (a) preparatory course enrollment (β = .236, p = .041) with those enrolled in prior preparatory courses scoring higher, (b) education major (β = .285, p = .018) with education majors scoring higher, and (c) business major (β = .252, p = .032) with business majors scoring higher. One statistically significant predictor variable emerged for monolingual students, gender (β = -.085, p = .001) with females ranking higher. Age, income, race, ethnicity, U.S. origin, science or health science majors did not emerge as statistically significant predictor variables for either group.^ Similarities between monolingual and bilingual participants included statistically significant negative linear correlations between AMAS scores and course grades for both bilingual (r = -.178, p = .017) and monolingual participants (r = -.203, p = .001). Differences included a statistically significant linear correlation between AMAS scores and final exam grades for monolingual participants only (r = -.253, p < .0009) despite no statistically significant difference in the strength the linear relationship of the AMAS scores and the final exam scores between groups, z = 1.35, p = .1756.^ The findings show that bilingual and monolingual students report math anxiety similarly and that math anxiety has similar associations with performance measures, despite differences between predictor variables. One of the first studies on the math anxiety of bilingual community college students, the results suggest recommendations for researchers and practitioners.^

Forecasting Responses of Seagrass Distributions to Changing Water Quality Using Monitoring Data

Extensive data sets on water quality and seagrass distributions in Florida Bay have been assembled under complementary, but independent, monitoring programs. This paper presents the landscape-scale results from these monitoring programs and outlines a method for exploring the relationships between two such data sets. Seagrass species occurrence and abundance data were used to define eight benthic habitat classes from 677 sampling locations in Florida Bay. Water quality data from 28 monitoring stations spread across the Bay were used to construct a discriminant function model that assigned a probability of a given benthic habitat class occurring for a given combination of water quality variables. Mean salinity, salinity variability, the amount of light reaching the benthos, sediment depth, and mean nutrient concentrations were important predictor variables in the discriminant function model. Using a cross-validated classification scheme, this discriminant function identified the most likely benthic habitat type as the actual habitat type in most cases. The model predicted that the distribution of benthic habitat types in Florida Bay would likely change if water quality and water delivery were changed by human engineering of freshwater discharge from the Everglades. Specifically, an increase in the seasonal delivery of freshwater to Florida Bay should cause an expansion of seagrass beds dominated by Ruppia maritima and Halodule wrightii at the expense of the Thalassia testudinum-dominated community that now occurs in northeast Florida Bay. These statistical techniques should prove useful for predicting landscape-scale changes in community composition in diverse systems where communities are in quasi-equilibrium with environmental drivers.

Predictors of adolescent sexual intentions and behavior: Attitudes, parenting, and neighborhood risk

The current study was a cross-sectional examination of data collected during an HIV risk reduction intervention in south Florida. The purpose of the study was to explore the relationships between neighborhood stress, parenting, attitudes, and adolescent sexual intentions and behavior. The Theory of Planned Behavior was used as a model to guide variable selection and propose an interaction pathway between predictors and outcomes. Potential predictor variables measured for adolescents ages 13–18 (n=196) included communication about sex, parent-family connectedness, parental presence, parent-adolescent activity participation, attitudes about sex and condom use, neighborhood disorder, and exposure to violence. Outcomes were behavioral intentions and sexual behavior for the previous eight months. Neighborhood data was supplemented with ZIP Code level data from regional sources and included median household income, percentage of minority and Hispanic residents, and number of foreclosures. Statistical tests included t-tests, Pearson's correlations, and hierarchical linear regressions. Results showed that males and older adolescents reported less positive behavioral intentions than females and adolescents younger than 16. Intentions were associated with condom attitudes, sexual attitudes, and parental presence; unprotected sexual behavior was associated with parental presence. The best fit model for intentions included gender, sexual attitudes, condom attitudes, parental presence, and neighborhood disorder. The unsafe sexual behavior model included whether the participant lived with both natural parents in the previous year, and the percent of Hispanic residents in the neighborhood. Study findings indicate that more research on adolescent sexual behavior is warranted, specifically examining the differentials between variables that affect intentions and those that affect behavior. A focus on gender and age differences during intervention development may allow for better targeting and more efficacious interventions. Adding peer and media influences to the framework of attitudes, parenting, and neighborhood may offer more insight into patterns of adolescent sexual behavior risk.

A comprehensive assessment of self -report experiences of adoptive parents of special needs children in Florida

Adoption of special needs children is now seen as a life long event whereby the adoptive child and family have unique needs. The need for postplacement resources throughout the life cycle of the adoption process is evident. This exploratory-descriptive research employed a random stratified cross-sectional design. The purpose of the study was to describe, identify, examine, and assess the relative influence of identified empirically and conceptually relevant variables of self-report experiences of adoptive parents of special needs children. Primary areas of exploration included: (1) adoptive children and families' characteristics, (2) postplacement service needs, utilization and satisfaction, and (3) adoptive parents' perceptions of their adoption experiences. A proportionate stratified random mail survey was used to obtain 474 families who had adopted special needs children from the 15 geographic districts which make up the state adoption social service agency in Florida. A 144-item survey questionnaire was used to collect basic information on demographic data, service provision, and adoption experiences. Four research questions were analyzed to test the effect the predictor variables had on willingness to adopt another special needs child, successful adoption, satisfying experience, and realism about problems. All four research questions revealed that the full model and the child's antecedent and the adoptive parents' intervening variable blocks were significant in explaining the variance in the dependent variables. The child's intervening variables alone were only significant in explaining the variance for one of the dependent variables. The results of the statistical analysis on the fifth research question and the three hypotheses determined that (1) only one postplacement service, crisis intervention, had a statistically significant impact on the adoptive parents' perceived level of satisfaction with the adoption experience; (2) adoptive parents who rate their adoption as successful are more likely to express a desire to adopt another special needs child; (3) the more adequate information on the child the adoptive parents perceived that they had prior to placement, the more they perceived they were realistic about the problems they would encounter; and (4) six specific postplacement services were found to be significant in predicting successful adoptions--crisis intervention, outpatient drug/alcohol treatment, maintenance subsidy, physical therapy, special medical equipment, and family counseling. Implications for the social work field and future research are discussed. ^

The relationship of managers' self -reported leadership practices and their spirituality

The role of spirituality in leadership in business and other organizations has gained growing recognition. The purpose of this study was to explore the relationship between spirituality and nine selected transformational leadership practices. Community leaders (N = 138) in business, education, and other professions who were graduates of a 10-week leadership program, Leadership Fort Lauderdale, from 1994 to 2004 completed the Spirituality Assessment Scale (SAS), the Leadership Practices Inventory (LPI), and four transformational leadership items of the Multifactor Leadership Questionnaire (MLQ). ^ The predictor variables were participants' scores on the LPI and MLQ. The criterion variable was their score on the SAS. Stepwise multiple regression analysis was used to test the hypothesis: Is there a combination of nine selected transformational leadership practices that would account for a significant portion of the variance of each of two spirituality measures? The Definitive and Correlated dimensions and Total spirituality score of the SAS were used in the analysis. ^ Results showed that two of the LPI leadership practices were significantly related to spirituality. The variable Inspiring a Shared Vision accounted for 10% of the variance of the SAS Definitive dimension. The variable Encouraging the Heart accounted for 30% of the variance of the Correlated dimension. For the Total spirituality score, two models were revealed. In the first model, Encouraging the Heart accounted for 28% of the variance of the total spirituality score. In the second model, Encouraging the Heart and Inspiring a Shared Vision together accounted for 31% of the total spirituality score. None of the transformational leadership practices from the MLQ were significantly related to spirituality. ^ The data partially support the hypothesis: two of the nine leadership variables did in combination correlate with leaders' spirituality. The results also support at least a partial relationship between spirituality and certain transformational leadership practices among leaders in various spheres, such as education, business, and other professions. ^

The relationship of aptitude, course grades, and program length, to performance on a standards based test (NCLEX -RN)

The purpose of this study was threefold: first, to investigate variables associated with learning, and performance as measured by the National Council Licensure Examination for Registered Nurses (NCLEX-RN). The second purpose was to validate the predictive value of the Assessment Technologies Institute (ATI) achievement exit exam, and lastly, to provide a model that could be used to predict performance on the NCLEX-RN, with implications for admission and curriculum development. The study was based on school learning theory, which implies that acquisition in school learning is a function of aptitude (pre-admission measures), opportunity to learn, and quality of instruction (program measures). Data utilized were from 298 graduates of an associate degree nursing program in the Southeastern United States. Of the 298 graduates, 142 were Hispanic, 87 were Black, non-Hispanic, 54 White, non-Hispanic, and 15 reported as Others. The graduates took the NCLEX-RN for the first time during the years 2003–2005. This study was a predictive, correlational design that relied upon retrospective data. Point biserial correlations, and chi-square analyses were used to investigate relationships between 19 selected predictor variables and the dichotomous criterion variable, NCLEX-RN. The correlation and chi square findings indicated that men did better on the NCLEX-RN than women; Blacks had the highest failure rates, followed by Hispanics; older students were more likely to pass the exam than younger students; and students who passed the exam started and completed the nursing program with a higher grade point average, than those who failed the exam. Using logistic regression, five statistical models that used variables associated with learning and student performance on the NCLEX-RN were tested with a model adapted from Bloom's (1976) and Carroll's (1963) school learning theories. The derived model included: NCLEX-RNsuccess = f (Nurse Entrance Test and advanced medical-surgical nursing course grade achieved). The model demonstrates that student performance on the NCLEX-RN can be predicted by one pre-admission measure, and a program measure. The Assessment Technologies Institute achievement exit exam (an outcome measure) had no predictive value for student performance on the NCLEX-RN. The model developed accurately predicted 94% of the student's successful performance on the NCLEX-RN.

Tree Island Response to Fire and Flooding in the Short-Hydroperiod Marl Prairie Grasslands of the Florida Everglades

Within the marl prairie grasslands of the Florida Everglades, USA, the combined effects of fire and flooding usually lead to very significant changes in tree island structure and composition. Depending on fire severity and post-fire hydroperiod, these effects vary spatially and temporally throughout the landscape, creating a patchy post-fire mosaic of tree islands with different successional states. Through the use of the Normalized Difference Vegetation Index (NDVI) and three predictor variables (marsh water table elevation at the time of fire, post-fire hydroperiod, and tree island size), along with logistic regression analysis, we examined the probability of tree island burning and recovering following the Mustang Corner Fire (May to June 2008) in Everglades National Park. Our data show that hydrologic conditions during and after fire, which are under varying degrees of management control, can lead to tree island contraction or loss. More specifically, the elevation of the marsh water table at the time of the fire appears to be the most important parameter determining the severity of fire in marl prairie tree islands. Furthermore, in the post-fire recovery phase, both tree island size and hydroperiod during the first year after the fire played important roles in determining the probability of tree island recovery, contraction, or loss.

Nursing faculty intention to use service learning as pedagogy in higher education

The purpose of this study was to identify the factors that motivate nursing faculty to use service learning. The study was based on the theory of planned behavior (TPB), which implies that the target behavior of intention to use service learning in higher education is influenced by the predictor variables of behavior beliefs (attitude), normative beliefs (peer influence), and control beliefs (confidence and resources). External variables were also considered (years of teaching experience, tenure status, and the type of curriculum). Group interviews and a pilot test were conducted to create the instrument for the study, and Cronbach alpha were calculated for survey item reliability. The participants were full time undergraduate nursing faculty members (n=-160) in the Southeastern United States who taught in universities with accredited nurse education programs. Demographic data as well as scores on scaled survey responses were used to evaluate the intention of nursing faculty to use service learning in their classes. Pearson product moment correlation coefficient and path analysis were applied to the data. The correlation findings indicated that there were statistically significant relationships between behavior beliefs, normative beliefs, and control beliefs and nursing faculty intention to use service learning. The path analysis also indicated that behavior beliefs and normative beliefs were significant, while control beliefs were not a strong influence on intention to use service learning. Normative beliefs showed the strongest direct influence. The use of a community based curriculum also had a positive influence on intention, and faculty with tenure status were more likely to have positive behavior beliefs (attitude) towards service learning. Finally, as teaching experience increased, positive attitudes towards the intention to use service learning decreased. Seventy-nine percent of the variation in the intention to use service learning was explained by the theory of planned behavior, the type of curriculum, teaching experience, and tenure status. These results will assist nursing administration and faculty to design strategies to facilitate the implementation of service learning pedagogy, as well as a community based curriculum which will help meet the 21st century goals set forth from the American Association of Colleges of Nursing.

The effects of required/sequenced preparatory courses on academic success and retention at a community college

This dissertation had two purposes: first, to analyze how required sequenced college preparatory courses in mathematics, reading, and writing affect students' academic success and, second, to add to a theoretical model for predicting student retention at a community college. Grade point average, number of degree credits earned, and reenrollment rate were measured as determinants of academic success. The treatment group had a significantly higher grade point average than the control group. There was no significant difference in the number of degree credits earned or re-enrollment rate for the groups. A series of logistic regressions used the independent variables E-ASSET scores in math, reading, and writing; number of college prep areas required; credits earned; grade point average; students' status; academic restrictions/required course sequencing; sex; race; and socio-economic status to determine the predictor variables for retention. The academic variable that showed the greatest potential as a predictor for retention was grade point average. Overall, receiving financial aid was the greatest predictor for reenrollment. For a financial aid recipient the odds of reenrollment were 2.70 times more likely than if no financial aid was received.

Prevalência e fatores associados à diminuição da função pulmonar em obesos em pré-operatório de cirurgia bariátrica

Introduction: Obesity shows changes in pulmonary function and respiratory mechanics, however, little is known regarding the prevalence of worsening respiratory function when considering the increase in central or peripheral adiposity or general obesity. Objectives: To analyze the association between anthropometric adiposity and decreased lung function in obese. Materials and Methods: Patients eligible for this study obese individuals (IMC≥30kg/m2) in pre-bariatric surgery and referred for Treatment Clinic of Obesity and Related Diseases, located at the University Hospital Onofre Lopes (HUOL), from October 2005 and July 2014. The evaluation included clinical information and measurement of anthropometric measures (body mass index (BMI), body fat index (BFI) and waist circumference (WC) and neck (NC)) and spirometric. The prevalence and analysis by Poisson regression was performed considering the following outcome variables: forced vital capacity (FVC), forced expiratory volume in one second (FEV1) and Maximum Voluntary Ventilation (MVV) and as predictor variables were considered: BMI, IAC, WC and NC and as control variables: age, gender, smoking history and comorbidities (diabetes mellitus, dyslipidemia and hypertension). Statistical analysis was performed using Statistical Package for Social Sciences software (SPSS - version 20.0). Results: We analyzed 384 individuals, 75% women, mean BMI: 46.6 (± 8.7) kg/m2, IAC: 49.26 (± 9.48)%, WC: 130.84 (± 16.23) cm and NC: 42.3 (± 4.6) cm. The higher prevalence of FVC and FEV1 <80% was observed in individuals with NC above 42 cm, followed those with a BMI above 45 kg/m2. Multivariate analysis using Poisson regression showed as risk factors associated with FVC <80%, the variables: NC above 42 cm (odds ratio (OR) 2.41) and BMI over 45Kg/m2 (OR 1.71 ). As for FEV1 <80% predicted, all predictor variables were associated, with the largest odds presented by the NC (3.40). MVVV was not associated with any studied varaible. Conclusion: Individuals with NC above 42 cm had higher prevalence of reduced lung function and the NC was the measure with the highest association with reduced lung function in obese.

Downwelling spectral irradiance as measured in different depths, remote sensing reflectance and phytoplankton pigment concentration during POLARSTERN cruises ANT-XXIV/1, ANT-XXIV/4, ANT-XXVI/4 and Maria S. Merian cruise MSM18/3

The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer - MERIS - Polymer product developed by Steinmetz et al., 2011, doi:10.1364/OE.19.009783) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.

Knowledge Modeling for The Outcome of Brain Stereotactic Radiosurgery

Purpose: To build a model that will predict the survival time for patients that were treated with stereotactic radiosurgery for brain metastases using support vector machine (SVM) regression.

Methods and Materials: This study utilized data from 481 patients, which were equally divided into training and validation datasets randomly. The SVM model used a Gaussian RBF function, along with various parameters, such as the size of the epsilon insensitive region and the cost parameter (C) that are used to control the amount of error tolerated by the model. The predictor variables for the SVM model consisted of the actual survival time of the patient, the number of brain metastases, the graded prognostic assessment (GPA) and Karnofsky Performance Scale (KPS) scores, prescription dose, and the largest planning target volume (PTV). The response of the model is the survival time of the patient. The resulting survival time predictions were analyzed against the actual survival times by single parameter classification and two-parameter classification. The predicted mean survival times within each classification were compared with the actual values to obtain the confidence interval associated with the model’s predictions. In addition to visualizing the data on plots using the means and error bars, the correlation coefficients between the actual and predicted means of the survival times were calculated during each step of the classification.

Results: The number of metastases and KPS scores, were consistently shown to be the strongest predictors in the single parameter classification, and were subsequently used as first classifiers in the two-parameter classification. When the survival times were analyzed with the number of metastases as the first classifier, the best correlation was obtained for patients with 3 metastases, while patients with 4 or 5 metastases had significantly worse results. When the KPS score was used as the first classifier, patients with a KPS score of 60 and 90/100 had similar strong correlation results. These mixed results are likely due to the limited data available for patients with more than 3 metastases or KPS scores of 60 or less.

Conclusions: The number of metastases and the KPS score both showed to be strong predictors of patient survival time. The model was less accurate for patients with more metastases and certain KPS scores due to the lack of training data.

Utilizing Traditional Cognitive Measures of Academic Preparation to Predict First-Year Science, Technology, Engineering, and Mathematics (STEM) Majors' Success in Math and Science Courses

For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.

Maternal-Fetal Attachment and Health Behaviors among Women with HIV/AIDS

Background: Mothers with HIV often face personal and environmental risks for poor maternal health behaviors and infant neglect, even when HIV transmission to the infant was prevented. Maternal-fetal attachment (MFA), the pre-birth relationship of a woman with her fetus, may be the precursor to maternal caregiving. Using the strengths perspective in social work, which embeds MFA within a socio-ecological conceptual framework, it is hypothesized that high levels of maternal-fetal attachment may protect mothers and infants against poor maternal health behaviors. Objective: To assess whether MFA together with history of substance use, living marital status, planned pregnancy status, and timing of HIV diagnosis predict three desirable maternal health behaviors (pregnancy care, adherence to prenatal antiretroviral therapy–ART, and infant’s screening clinic care) among pregnant women with HIV/AIDS. Method: Prospective observation and hypothesis-testing multivariate analyses. Over 17 consecutive months, all eligible English- or Spanish-speaking pregnant women with HIV ( n = 110) were approached in the principal obstetric and screening clinics in Miami-Dade County, Florida at 24 weeks’ gestation; 82 agreed to enroll. During three data collection periods from enrollment until 16 weeks after childbirth (range: 16 to 32 weeks), participants reported on socio-demographic and predictor variables, MFA, and pregnancy care. Measures of adherence to ART and infant care were extracted from medical records. Findings: Sociodemographic, pregnancy, and HIV disease characteristics in this sample suggest changes in the makeup of HIV-infected pregnant women parallel to the evolution of the HIV epidemic in the USA over the past two decades. The MFA model predicted maternal health behaviors for pregnancy care (R2 = .37), with MFA, marital living status, and planned pregnancy status independently contributing ( = .50, = .28, = .23, respectively). It did not predict adherence to ART medication or infant care. Relevance: These findings provide the first focused evidence of the protective role of MFA against poor maternal health behaviors among pregnant women with HIV, in the presence of adverse life circumstances. Social desirability biases in some self-report measures may limit the findings. Suggestions are made for orienting future inquiry on maternal health behaviors during childbirth toward relationship and protection.