A randomised controlled trial of the Learning Skills Together (LST) intervention to improve dementia family caregivers' self-efficacy with complex care.

Background Nearly two-thirds of family caregivers of persons living with Alzheimer's disease or related dementias (AD/ADRD) provide complex care, including medical care. Family caregivers typically receive little to no training on how to provide this care. Furthermore, family caregivers simultaneously grapple with the presence of behavioral and psychological symptoms of dementia (BPSD), diminished communication abilities, and comorbidities such as diabetes. We developed Learning Skills Together ( LST ), a six-week digitally delivered psychoeducational program, to facilitate family caregiver abilities to administer complex care tasks. The goal of the present study is to test the efficacy of LST and to reduce adverse outcomes associated with caregiving, such as depressive symptomology and negative appraisal of BPSD. Methods To test the efficacy of LST , we will conduct a two-arm single-site randomised controlled trial (RCT) with N = 200 family caregivers of persons living with AD/ADRD. Eligible family caregivers will be randomly assigned to participate in either the LST intervention or a structurally equivalent control condition focused on healthy living. All family caregivers will complete four surveys, including a baseline survey administered prior to randomisation, a post-intervention survey, and a three- and six-month follow-up survey to assess change in study outcomes. Between-group comparisons of each outcome will be evaluated using generalized estimating equation models. Mediation analyses will assess family caregiver self-efficacy as the intervention's mechanism of change in depressive symptomology and BPSD. We will also examine caregiver race, ethnicity, and gender as effect modifiers of the intervention. Discussion LST findings will inform the field of AD/ADRD and caregiving regarding optimally supporting family caregivers in managing complex care tasks. If efficacious, the LST intervention will support family caregivers in preserving their own mental health while providing complex care. Trial registration This study was registered on Clinical Trials.gov on May 6, 2023 (NCT05846984). https://clinicaltrials.gov/study/NCT05846984?cond=learning%20skills%20together&rank=2.

A randomised controlled trial of the Learning Skills Together (LST) intervention to improve dementia family caregivers' self-efficacy with complex care.

BACKGROUND: Nearly two-thirds of family caregivers of persons living with Alzheimer's disease or related dementias (AD/ADRD) provide complex care, including medical care. Family caregivers typically receive little to no training on how to provide this care. Furthermore, family caregivers simultaneously grapple with the presence of behavioral and psychological symptoms of dementia (BPSD), diminished communication abilities, and comorbidities such as diabetes. We developed Learning Skills Together (LST), a 6-week digitally delivered psychoeducational program, to facilitate family caregiver abilities to administer complex care tasks. The goal of the present study is to test the efficacy of LST and to reduce adverse outcomes associated with caregiving, such as depressive symptomology and negative appraisal of BPSD. METHODS: To test the efficacy of LST, we will conduct a two-arm single-site randomized controlled trial (RCT) with N = 200 family caregivers of persons living with AD/ADRD. Eligible family caregivers will be randomly assigned to participate in either the LST intervention or a structurally equivalent control condition focused on healthy living. All family caregivers will complete four surveys, including a baseline survey administered prior to randomization, a post-intervention survey, and a 3- and 6-month follow-up survey to assess change in study outcomes. Between-group comparisons of each outcome will be evaluated using generalized estimating equation models. Mediation analyses will assess family caregiver self-efficacy as the intervention's mechanism of change in depressive symptomology and BPSD. We will also examine caregiver race, ethnicity, and gender as effect modifiers of the intervention. DISCUSSION: LST findings will inform the field of AD/ADRD and caregiving regarding optimally supporting family caregivers in managing complex care tasks. If efficacious, the LST intervention will support family caregivers in preserving their own mental health while providing complex care. TRIAL REGISTRATION: Clinical Trials.gov NCT05846984 . This study was registered on May 6, 2023.

Project ECHO Brain Health: Assessing the Impact of a Pilot Program to Promote Self-Efficacy Among Community Health Workers.

This mixed-methods study sought to examine the impact of the Project ECHO Brain Health program on participating community health workers' (CHWs') self-efficacy to address dementia, promote brain health, and advocate for research among Latinx South Texas communities. Using an explanatory sequential design, quantitative data collected from pre- and post-program surveys were analyzed to inform the collection of qualitative data, followed by an interpretation of all findings to better understand the impact of the program on self-efficacy. Pre- and post-surveys were collected from 25 CHWs, 13 of whom later participated in individual interviews. There was a statistically significant increase in mean self-efficacy scores between the pre- and post-surveys among participants. Three categories reflecting the experiences of participants were identified from the qualitative data: addressing training needs; impact on CHWs and their practice; and community of learning. The findings suggest that Project ECHO Brain Health program is a timely intervention that may facilitate increased self-efficacy among CHWs as they navigate the impacts of dementia in their communities.

Propensity score analysis for health care disparities: a deweighting approach.

BACKGROUND: Propensity score weighting is a useful tool to make causal or unconfounded comparisons between groups. According to the definition by the Institute of Medicine (IOM), estimates of health care disparities should be adjusted for health-status factors but not for socioeconomic status (SES) variables. There have been attempts to use propensity score weighting to generate estimates that are concordant with IOM's definition. However, the existing propensity score methods do not preserve SES distributions in minority and majority groups unless SES variables are independent of health status variables. METHODS: The present study introduces a deweighting method that uses two types of propensity scores. One is a function of all covariates of health status and SES variables and is used to weight study subjects to adjust for them. The other is a function of only the SES variables and is used to deweight the subjects to preserve the original SES distributions. RESULTS: The procedure of deweighting is illustrated using a dataset from a right heart catheterization (RHC) study, where it was used to examine whether there was a disparity between black and white patients in receiving RHC. The empirical example provided promising evidence that the deweighting method successfully preserved the marginal SES distributions for both racial groups but balanced the conditional distributions of health status given SES. CONCLUSIONS: Deweighting is a promising tool for implementing the IOM-definition of health care disparities. The method is expected to be broadly applied to quantitative research on health care disparities.

Erratum: Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration - CORRIGENDUM.

[This corrects the article DOI: 10.1017/cts.2024.2.].

Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration.

Introduction: The focus on social determinants of health (SDOH) and their impact on health outcomes is evident in U.S. federal actions by Centers for Medicare & Medicaid Services and Office of National Coordinator for Health Information Technology. The disproportionate impact of COVID-19 on minorities and communities of color heightened awareness of health inequities and the need for more robust SDOH data collection. Four Clinical and Translational Science Award (CTSA) hubs comprising the Texas Regional CTSA Consortium (TRCC) undertook an inventory to understand what contextual-level SDOH datasets are offered centrally and which individual-level SDOH are collected in structured fields in each electronic health record (EHR) system potentially for all patients. Methods: Hub teams identified American Community Survey (ACS) datasets available via their enterprise data warehouses for research. Each hub's EHR analyst team identified structured fields available in their EHR for SDOH using a collection instrument based on a 2021 PCORnet survey and conducted an SDOH field completion rate analysis. Results: One hub offered ACS datasets centrally. All hubs collected eleven SDOH elements in structured EHR fields. Two collected Homeless and Veteran statuses. Completeness at four hubs was 80%-98%: Ethnicity, Race; < 10%: Education, Financial Strain, Food Insecurity, Housing Security/Stability, Interpersonal Violence, Social Isolation, Stress, Transportation. Conclusion: Completeness levels for SDOH data in EHR at TRCC hubs varied and were low for most measures. Multiple system-level discussions may be necessary to increase standardized SDOH EHR-based data collection and harmonization to drive effective value-based care, health disparities research, translational interventions, and evidence-based policy.

Heterogeneity of COVID-19 symptoms and associated factors: Longitudinal analysis of laboratory-confirmed COVID-19 cases in San Antonio.

Few studies have examined heterogeneous associations of risk factors with Coronavirus Disease-2019 (COVID-19) symptoms by type. The objectives of this study were to estimate the prevalence of and risk factors associated with COVID-19 symptoms and to investigate whether the associations differ by the type of symptoms. This study obtained longitudinal data over 6 months from laboratory-confirmed COVID-19 cases in a citywide sample in San Antonio. Sixteen symptoms of COVID-19 infection, measured at baseline and three follow-up times (1, 3, and 6 months), were analyzed using generalized estimating equations (GEE) to investigate potential risk factors while accounting for the repeated measurements. The risk factors included time in months, sociodemographic characteristics, and past or current medical and psychiatric conditions. To obtain interpretable results, we categorized these sixteen symptoms into five categories (cardiopulmonary, neuro-psychological, naso-oropharyngeal, musculoskeletal, and miscellaneous). We fitted GEE models with a logit link using each category as the outcome variable. Our study demonstrated that the associations were heterogeneous by the categories of symptoms. The time effects were the strongest for naso-oropharyngeal symptoms but the weakest for neuro-psychological symptoms. Female gender was associated with increased odds of most of the symptoms. Hispanic ethnicity was also associated with higher odds of neuro-psychological, musculoskeletal, and miscellaneous symptoms. Depression was the most robust psychiatric condition contributing to most of the symptoms. Different medical conditions seemed to contribute to different symptom expressions of COVID-19 infection.

Metabolomic profiles associated with physical activity in White and African American adult men.

BACKGROUND: Physical activity (PA) is associated with various health benefits, especially in improving chronic health conditions. However, the metabolic changes in host metabolism in response to PA remain unclear, especially in racially/ethnically diverse populations. OBJECTIVE: This study is to assess the metabolic profiles associated with the frequency of PA in White and African American (AA) men. METHODS: Using the untargeted metabolomics data collected from 698 White and AA participants (mean age: 38.0±8.0, age range: 20-50) from the Louisiana Osteoporosis Study (LOS), we conducted linear regression models to examine metabolites that are associated with PA levels (assessed by self-reported regular exercise frequency levels: 0, 1-2, and ≥3 times per week) in White and AA men, respectively, as well as in the pooled sample. Covariates considered for statistical adjustments included race (only for the pooled sample), age, BMI, waist circumstance, smoking status, and alcohol drinking. RESULTS: Of the 1133 untargeted compounds, we identified 7 metabolites associated with PA levels in the pooled sample after covariate adjustment with a false discovery rate of 0.15. Specifically, compared to participants who did not exercise, those who exercised at a frequency ≥3 times/week showed higher abundances in uracil, orotate, 1-(1-enyl-palmitoyl)-2-oleoyl-GPE (P-16:0/18:1) (GPE), threonate, and glycerate, but lower abundances in salicyluric glucuronide and adenine in the pooled sample. However, in Whites, salicyluric glucuronide and orotate were not significant. Adenine, GPE, and threonate were not significant in AAs. In addition, the seven metabolites were not significantly different between participants who exercised ≥3 times/week and 1-2 times/week, nor significantly different between participants with 1-2 times/week and 0/week in the pooled sample and respective White and AA groups. CONCLUSIONS: Metabolite responses to PA are dose sensitive and may differ between White and AA populations. The identified metabolites may help advance our knowledge of guiding precision PA interventions. Studies with rigorous study designs are warranted to elucidate the relationship between PA and metabolites.

Effects of Adjusting for Instrumental Variables on the Bias and Precision of Propensity Score Weighted Estimators: Analysis Under Complete, Near, and No Positivity Violations.

Purpose: To demonstrate that using an instrumental variable (IV) with monotonicity reduces the accuracy of propensity score (PS) weighted estimators for the average treatment effect (ATE). Methods: Monotonicity in the relationship between a binary IV and a binary treatment variable is an important assumption to identify the ATE for compliers who would only take treatment when encouraged by the IV. We perform theoretical and numerical investigations to study the impact of using the IV that satisfies monotonicity on the PS of treatment in terms of the positivity assumption, which requires that the PS be strictly between 0 and 1, and the accuracy of PS weighted estimators. Two versions of monotonicity that result in one-sided or two-sided noncompliance are considered. Results: The PS adjusting for the IV always violates the positivity assumption when noncompliance occurs in one direction (one-sided noncompliance) and is more extreme than without the IV under two-sided noncompliance. These results are valid if the probability of being encouraged to get treatment and the compliance score, the probability of being a complier, are strictly between 0 and 1. Conclusion: Using a binary IV with monotonicity as a covariate for the PS model makes the estimated PSs unnecessarily extreme, reducing the accuracy of the PS weighted estimators.

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Role of endogenous adenine in kidney failure and mortality with diabetes.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality, however, few mechanistic biomarkers are available for high risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from Chronic Renal Insufficiency Cohort (CRIC), Singapore Study of Macro-Angiopathy and Reactivity in Type 2 Diabetes (SMART2D), and the Pima Indian Study determined if urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in CRIC (HR 1.57, 1.18, 2.10) and SMART2D (HR 1.77, 1.00, 3.12). ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in CRIC (HR 2.36, 1.26, 4.39), SMART2D (HR 2.39, 1.08, 5.29), and Pima Indian study (HR 4.57, CI 1.37-13.34). Empagliflozin lowered UAdCR in non-macroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology and transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mammalian target of rapamycin (mTOR). Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Profiling compliers and noncompliers for instrumental variable analysis with covariates: A weighting approach.

Instrumental variable (IV) estimation is an essential tool to estimate the causal effect of a treatment in randomized experiments when noncompliance exists. In such studies, standard statistical approaches can be biased because compliers and noncompliers can differ in unmeasured ways that affect both the compliance behavior and outcome. Based on a few assumptions such as monotonicity, the IV estimand represents the causal effect of compliers. Profiling compliers and noncompliers has important implications because the IV estimand applies only to compliers. A method for estimating the covariate means for compliers and noncompliers has recently been proposed in political sciences literature. However, this approach requires an assumption that the instrument is randomly assigned, which confines the application of this approach to randomized experiments. In this study, we present two weighting methods for profiling compliers and noncompliers when the instrument and compliance behavior are confounded by several covariates. The proposed approach can be used for both experimental and nonexperimental studies, and hence is more broadly applicable. For the development, an instrumental propensity score is adopted to account for confounded instruments. We demonstrate the utility of the proposed methods based on simulation and real data experiments.

Collaborative Program to Evaluate Real World Data for Use in Clinical Studies and Regulatory Decision Making.

The 21st Century Cures Act allows the US Food and Drug Administration to consider real world data (RWD) for new indications or post approval study requirements. However, there is limited guidance as to the relative quality of different RWD types. The ACE-RWD program will compare the quality of EHR clinical data, EHR billing data, and linked healthcare claims data to traditional clinical trial data collection methods. ACE-RWD is being conducted alongside 5-10 ancillary studies, with five sponsors, across multiple therapeutic areas. Each ancillary study will be conducted after or in parallel with its parent clinical study at a minimum of two clinical sites. Although not required, it is anticipated that EHR clinical and EHR billing data will be obtained via EHR-to-eCRF mechanisms that are based on the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR®) standard.

Release of Oxytocin and Cortisol Is Associated With Neurobehavioral Patterns in Premature Infants.

OBJECTIVE: To examine relationships among salivary oxytocin and cortisol levels in parents and preterm infants and neurobehavioral functioning in preterm infants after skin-to-skin contact. DESIGN: A secondary analysis of a randomized crossover study. SETTING: NICU. PARTICIPANTS: Twenty-eight stable premature infants and their mothers and fathers. METHODS: Participating infants contributed 108 saliva samples that we collected 45 minutes after skin-to-skin contact and tested for oxytocin and cortisol. We randomized data collection by whether the infant was held first by the mother or by the father. We conducted linear regression to test if summary scores on the NICU Network Neurobehavioral Scale were associated with salivary oxytocin and cortisol levels. RESULTS: We found a significant negative relationship between infant oxytocin levels and the Stress scores (b = -0.07, p < .01) and the Excitability scores (b = -1.12, p = .04) among infants held skin-to-skin with their mothers. We found a significant positive relationship between infant oxytocin levels and the Self-Regulatory scores (b = 0.38, p = .05) among infants held skin-to-skin with their mothers. We found a significant positive relationship between infant cortisol level and the Stress scores (b = 0.05, p = .04), Excitability scores (b = 1.06, p = 0.05), and Asymmetrical Reflexes scores (b = 1.21, p = .03) among infants held skin-to-skin with their mothers. We only found a negative significant relationship between infant cortisol levels and the Stress scores (b = -0.03, p = .04) among infants held skin-to-skin with their fathers. CONCLUSION: We found that oxytocin is an important biomarker that may improve infant neurobehavioral functioning. The data showed a difference in oxytocin responses after skin-to-skin contact with mothers compared to fathers.

Examining the Delivery of a Tailored Chinese Mind-Body Exercise to Low-Income Community-Dwelling Older Latino Individuals for Healthy Aging: Feasibility and Acceptability Study.

BACKGROUND: Older Latino individuals are disproportionally affected by various chronic conditions including impairments in physical and cognitive functions, which are essential for healthy aging and independent living. OBJECTIVE: This study aimed to evaluate the feasibility and acceptability of FITxOlder, a 12-week mind-body exercise program, in community-dwelling low-income, predominantly older Latino individuals, and assess its preliminary effects on health parameters relevant to healthy aging and independent living. METHODS: This 12-week, single-arm, stage 1B feasibility study had a pre- and poststudy design. A total of 13 older adults (mean age 76.4, SD 7.9 years; 11/13, 85% Latino) of a congregate meal program in a senior center were enrolled. FITxOlder was a tailored Chinese mind-body exercise program using Five Animal Frolics led by a bilingual community health worker (CHW) participating twice a week at the senior center and facilitated by mobile health technology for practice at home, with incrementally increasing goals moving from once a week to at least 3 times a week. The feasibility and acceptability of the study were examined using both quantitative and qualitative data. Healthy aging-related outcomes (eg, physical and cognitive function) were assessed using paired 2-tailed t tests. Qualitative interview data were analyzed using thematic analysis. RESULTS: The attendance rate for the 24 exercise sessions was high (22.7/24, 95%), ranging from 93% (1.8/2) to 97% (1.9/2) over the 12 weeks. Participants were compliant with the incremental weekly exercise goals, with 69.2% (9/13) and 75.0% (9/12) meeting the home and program goals in the last 4 weeks, respectively. Approximately 83% (10/12) to 92% (11/12) of the participants provided favorable feedback on survey questions regarding the study and program implementation, such as program content and support, delivery by the CHW, enjoyment and appeal of the Five Animal Frolics, study burden and incentives, and safety concerns. The qualitative interview data revealed that FITxOlder was well accepted; participants reported enjoyment and health benefits and the desire to continue to practice and share it with others. The 5-time sit-to-stand test (mean change at posttest assessment=-1.62; P<.001; Cohen d=0.97) and 12-Item Short Form Health Survey physical component scores (mean change at post intervention=5.71; P=.01; Cohen d=0.88) exhibited changes with large effect sizes from baseline to 12 weeks; the other parameters showed small or medium effect sizes. CONCLUSIONS: The research findings indicated that the CHW-led and mobile health-facilitated Chinese qigong exercise program is feasible and acceptable among low-income Latino older adults. The trending health benefits of the 12-week FITxOlder program suggest it is promising to promote physical activity engagement in underserved older populations to improve health outcomes for healthy aging and independent living. Future research with larger samples and longer interventions is warranted to assess the health benefits and suitability of FITxOlder.

Community Health Worker-Led mHealth-Enabled Diabetes Self-management Education and Support Intervention in Rural Latino Adults: Single-Arm Feasibility Trial.

BACKGROUND: Latinos living in rural South Texas have a higher prevalence of diabetes, but their access to diabetes self-management education and support (DSMES) is limited. OBJECTIVE: We aimed to test the feasibility of a community health worker-led, mobile health (mHealth)-based DSMES intervention to reduce disparities in accessing DSMES in underserved rural Latino residents in South Texas. METHODS: This 12-week, single-arm, pre-post trial was delivered by trained community health workers to 15 adults with type 2 diabetes. The intervention consisted of digital diabetes education, self-monitoring, a cloud-based connected platform, and community health worker support. Feasibility was evaluated as retention, actual intervention use, program satisfaction, and barriers to implementation. We also explored the intervention's effect on weight loss and hemoglobin A1c (HbA1c). RESULTS: All 15 participants were Latino (mean age 61.87 years, SD 10.67; 9/15 female, 60%). The retention rate at posttest was 14 of 15 (93%). On average, the participants completed 37 of 42 (88%) digital diabetes education lessons with 8 participants completing all lessons. Participants spent 81/91 days (89%) step tracking, 71/91 days (78%) food logging, 43/91 days (47%) blood glucose self-monitoring, and 74/91 days (81%) weight self-monitoring. The level of program satisfaction was high. On average, participants lost 3.5 (SD 3.2) kg of body weight (P=.001), while HbA1c level remained unchanged from baseline (6.91%, SD 1.28%) to posttest (7.04%, SD 1.66%; P=.668). CONCLUSIONS: A community health worker-led mHealth-based intervention was feasible and acceptable to improve access to DSMES services for Latino adults living in rural communities. Future randomized controlled trials are needed to test intervention efficacy on weight loss and glycemic control.

Disparities in Cancer Genetic Testing and Variants of Uncertain Significance in the Hispanic Population of South Texas.

PURPOSE: Racial and ethnic disparities have included a lack of access to both genetic testing and research, resulting in poor understanding of the genomic architecture in under-represented populations. The South Texas population is primarily of Hispanic background and has been largely devoid of genetic services. We extended access to this underserved population and uncovered genetic variants previously not observed, emphasizing the need to continually improve both genomic databases and clarification of variant significance to provide meaningful patient counseling. METHODS: This study consisted of a retrospective cohort review of patients seen through a cancer genetics education and service program across 24 counties in South Texas. In total, 1,595 individuals were identified as appropriate for cancer genetic counseling and 1,377 completed genetic testing. RESULTS: Eighty percent of those receiving genetic counseling self-identified as Hispanic, 16% as non-Hispanic White (NHW), 3% as African American, and 1% as other race/ethnicity. Of reported variants, 18.8% were pathogenic and 13.7% were reported as a variant of uncertain significance (VUS). VUS was reported in 17.2% of the Hispanic individuals compared with 9% NHW (P = .005). CONCLUSION: Individuals of Hispanic ethnicity were significantly more likely to harbor a VUS compared with NHW. The extended reach into our regional communities revealed a gap in the ability to accurately interpret genomic variation with implications for advising patients on screening, prevention, and management strategies. A higher percentage of VUS also emphasizes the challenge of continued follow-up amid existing barriers that led to disparities in access. As understanding of the variants develops, hopefully gaps in knowledge of the genomic landscape will be lessened with increased clarity to provide accurate cancer risk assessment and recommendations for implementing prevention initiatives.

Antiracism Work in Schools: Using Dialectical Behavior Therapy Skills to Empower South Texas Educators.

OBJECTIVE: Implicit biases within school systems contribute to racist school cultures and policies. Black and Hispanic students are more likely to be over-policed in schools and to be penalized, especially by White teachers. Dialectical behavior therapy (DBT) skills can be taught to educators to support antiracist efforts in schools. METHOD: A virtual 2-day Train-the-Trainer antiracism workshop incorporating DBT skills was delivered to South Texas educators. DBT skills were integrated as life skills in antiracism situational role play, small group discussions, and meta-cognitive activities. Participants also received books on antiracism and an educators' toolkit to DBT and antiracism. Descriptive analysis described results from the workshop application, pre/post-workshop survey, and 6-month follow-up survey. RESULTS: Twelve educators completed the workshop application, with 10 educators reporting no history of antiracism trainings at their schools. Nine educators attended the workshop. Workshop feedback was overwhelmingly positive. A pre/post-workshop survey demonstrated growth in both teaching and use of all measured DBT skills and antiracism attitudes. Confidence in teaching and using DBT skills and changes in antiracism attitudes were sustained 6 months later. Five educators reported leading an antiracism initiative in their schools since the attendance of the workshop. CONCLUSION: A DBT-centered Train-the-Trainer antiracism workshop instilled confidence in educators to lead antiracism efforts, which resulted in the initiation of several initiatives in South Texas schools. Training educators, including teachers, counselors, and administrators, encouraged systemic antiracist change in school systems. The virtual training format may facilitate accessibility to educators who lack access to trainings; however, it may also add difficulty in building community among participants.

Subclassification estimation of the weighted average treatment effect.

Weighting and subclassification are popular approaches using propensity scores (PSs) for estimation of causal effects. Weighting is appealing in that it gives consistent estimators for various causal estimands if appropriate weights are well defined and the PS model is correctly specified. Subclassification is known to be more robust to model misspecification than weighting, but its application to diverse causal estimands is limited. In this article, we propose generalized stratum weights to implement subclassification estimators for various causal estimands. These weights include stratum weights for the average treatment effect (ATE) of the overall population and those for the ATE of the treated as special cases. For this, we incorporate strata into the expression of the weighted average treatment effect (WATE). Particularly, we identify stratum weights for the ATE for the overlap population (ATO), for which the weighting estimator is known to be most efficient among the class of WATE estimators. We show that the identified stratum weights for ATO are equivalent to the optimal stratum weights, which are the inverse variances of the stratum-specific estimators. Simulation studies demonstrate that the proposed subclassification estimator for ATO is more robust to model misspecification than the weighting estimator for ATO. We also propose augmented subclassification estimators, which are shown to be less biased than the subclassification estimators when only the outcome model is correctly specified. The practical utility of the proposed methods is illustrated in a study of right heart catheterization.

Instrumental variable estimation of truncated local average treatment effects.

Instrumental variable (IV) analysis is used to address unmeasured confounding when comparing two nonrandomized treatment groups. The local average treatment effect (LATE) is a causal estimand that can be identified by an IV. The LATE approach is appealing because its identification relies on weaker assumptions than those in other IV approaches requiring a homogeneous treatment effect assumption. If the instrument is confounded by some covariates, then one can use a weighting estimator, for which the outcome and treatment are weighted by instrumental propensity scores. The weighting estimator for the LATE has a large variance when the IV is weak and the target population, i.e., the compliers, is relatively small. We propose a truncated LATE that can be estimated more reliably than the regular LATE in the presence of a weak IV. In our approach, subjects who contribute substantially to the weak IV are identified by their probabilities of being compliers, and they are removed based on a pre-specified threshold. We discuss interpretation of the proposed estimand and related inference method. Simulation and real data experiments demonstrate that the proposed truncated LATE can be estimated more precisely than the standard LATE.