The effects of social support and self-efficacy on hopefulness in low-income older adults during COVID-19 pandemic.

BACKGROUND: Social support and self-efficacy play a significant role in improving positive psychological well-being in marginalized older adults. However, to date, there are few studies identifying the relationships during the COVID-19 pandemic. We examined the effect of social support and self-efficacy on hopefulness in a majority Black sample of marginalized low-income older adults during the COVID-19 pandemic. METHODS: This study used baseline data from a clinical trial designed to increase COVID-19 testing in Essex County, NJ, United States. The dataset involved participants 50 years old or older. We conducted: 1) cross-sectional descriptive/frequency statistics to understand the sociodemographic characteristics, 2) multivariate linear regression to investigate the direct relationships between social support subscales or self-efficacy and hopefulness, and 3) mediation analyses to examine the mediating role of self-efficacy in the relationship between social support and hopefulness. RESULTS: Our findings showed that self-efficacy had a partial mediating effect on the relationship between social support and hopefulness. After adjusting for covariate variables, social support subscales (i.e., emotional/informational, tangible, affectionate, positive social interaction social support) and self-efficacy were significantly associated with hopefulness. The indirect effect of social support via self-efficacy was positive and statistically significant. CONCLUSION: Self-efficacy mediated the relationship between social support and hopefulness in marginalized older adults aged 50 and over. Further research is needed to identify the various facets of positive psychological well-being using longitudinal data and a larger sample size.

Critical Dialogue and Capacity-Building Projects Reduced Alcohol and Substance Use in a Randomized Clinical Trial Among Formerly Incarcerated Men.

Background: Rates of alcohol and/or substance use (ASU) among residents of predominantly Black and marginalized communities are similar to ASU rates in White communities. Yet ASU has worse consequences in predominantly Black and marginalized communities (e.g., higher incarceration). Objective: We randomized participants to one of 16 intervention conditions using a 24 full factorial design to optimize a multilevel intervention reducing ASU among 602 formerly incarcerated men with substance-use-disorders (SUD). Candidate intervention components included (1) critical dialogue (CD; six weekly 2-hour-long group sessions vs. no CD sessions), (2) Quality of Life Wheel (QLW; six weekly 1-hour-long group sessions vs. no QLW sessions), (3) capacity building projects (CBP; six weekly 1-hour-long group sessions vs. no CBP sessions), and (4) delivery by a trained peer versus licensed facilitators. Outcome was percentage of days in which participants used alcohol, cocaine, opioid, and/or cannabis in previous 30 days. Results: Intent-to-treat analysis did not meet a priori component selection criteria due to low intervention attendance. After controlling for intervention group attendance (percentage of sessions attended), peer-delivered CD and CBP produced statistically and clinically significant main and interaction effects in ASU over 5 months. Per the multiphase optimization strategy framework, we selected peer-delivered CD and CBP for inclusion as the optimized version of the intervention with a cost of US$1,380 per 10 individuals. No adverse intervention effects occurred. Conclusion: CD and CBP were identified as the only potentially effective intervention components. Future research will examine strategies to improve attendance and test the optimized intervention against standard of care in a randomized-controlled-trial.

Policies to Reduce Child Poverty and Child Maltreatment: A Scoping Review and Preliminary Estimates of Indirect Effects.

This study includes a scoping review of prior studies investigating the effects of policy changes on child poverty rates. It further conducts an empirical analysis to estimate the relationship between child poverty rates and child maltreatment report (CMR) rates, utilizing national county-level data. The study then calculates the indirect effects of policy changes on CMR rates, mediated through child poverty rates, by integrating information from previous studies with its own empirical findings. Among the policy changes explored in prior studies, those related to a child allowance and a fully refundable Child Tax Credit demonstrate the largest indirect effects but also the highest costs. The expansion of in-kinds and near-cash benefits, such as the Supplemental Nutrition Assistance Program benefits and housing vouchers, shows moderate effects with moderate costs. Tax credits like the Earned Income Tax Credit exhibit lower effects and costs when targeted at the lowest earners, and moderate effects and costs for broader expansion. Focused tax credits, such as the Child and Dependent Care Tax Credit, had lower effects and costs, even if made fully refundable. Despite certain limitations, the study's approach yields consistent estimates with a recent simulation study, indicating its potential validity. While some proposed policy changes may seem expensive, implementing them is anticipated to substantially reduce CMR rates, with the benefits outweighing the associated costs. Overall, the findings suggest that addressing child poverty to reduce CMRs is an attractive strategy with numerous potential benefits.

Use of research electronic data capture (REDCap) in a sequential multiple assignment randomized trial (SMART): a practical example of automating double randomization.

BACKGROUND: Adaptive interventions are often used in individualized health care to meet the unique needs of clients. Recently, more researchers have adopted the Sequential Multiple Assignment Randomized Trial (SMART), a type of research design, to build optimal adaptive interventions. SMART requires research participants to be randomized multiple times over time, depending upon their response to earlier interventions. Despite the increasing popularity of SMART designs, conducting a successful SMART study poses unique technological and logistical challenges (e.g., effectively concealing and masking allocation sequence to investigators, involved health care providers, and subjects) in addition to other challenges common to all study designs (e.g., study invitations, eligibility screening, consenting procedures, and data confidentiality protocols). Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for data collection. REDCap offers unique features that support researchers' ability to conduct rigorous SMARTs. This manuscript provides an effective strategy for performing automatic double randomization for SMARTs using REDCap. METHODS: Between January and March 2022, we conducted a SMART using a sample of adult (age 18 and older) New Jersey residents to optimize an adaptive intervention to increase COVID-19 testing uptake. In the current report, we discuss how we used REDCap for our SMART, which required double randomization. Further, we share our REDCap project XML file for future investigators to use when designing and conducting SMARTs. RESULTS: We report on the randomization feature that REDCap offers and describe how the study team automated an additional randomization that was required for our SMART. An application programming interface was used to automate the double randomizations in conjunction with the randomization feature provided by REDCap. CONCLUSIONS: REDCap offers powerful tools to facilitate the implementation of longitudinal data collection and SMARTs. Investigators can make use of this electronic data capturing system to reduce errors and bias in the implementation of their SMARTs by automating double randomization. TRIAL REGISTRATION: The SMART study was prospectively registered at Clinicaltrials.gov; registration number: NCT04757298, date of registration: 17/02/2021.

Testing a digitally distributed method to recruit a network of community organizations to fight the consequences of the drug epidemic: A study in 13 American states.

To mitigate the opioid epidemic, a concerted effort to educate, prevent, diagnose, treat, and engage residents is required. In this study, a digitally distributed method to form a large network of organizations was tested with 99 counties in regions with high vulnerability to hepatitis C virus (HCV). The method involved a cascade of contacts going from email to phone calls, to videoconferencing and measuring the number of contacts required, amount of time taken, and the proportion of success at recruiting at least one community organization per county. A recruitment period of 5 months and 2118 contact attempts led to the recruitment of organizations from 73 out of our 99 target counties. Organizations belonging to health departments required more attempts and time to recruit but ultimately enrolled at higher rates than did other organizations such as coalitions and agencies. Organizations from counties more (vs. less) vulnerable to HCV outbreaks required more attempts to recruit and, using multiple recruitment methods (e.g., emails, phone calls, and Zoom meetings), improved enrollment success. Overall, this method proved to be successful at remotely engaging a large-scale network of communities with different levels of risk within a large geographic region.

Interprofessional collaboration associated with frequency of life-saving links to HIV continuum of care services in the urban environment of Newark, New Jersey.

BACKGROUND: HIV continuum of care has been used as a strategy to reduce HIV transmission rates, with timely engagement in HIV testing being the first and most critical step. This study examines interprofessional-collaboration (IPC) after controlling for agency/ provider demographics, provider training and self-efficacy as a significant predictor of how frequently HIV service providers link their clients to HIV testing. METHODS: Multilevel binary logistic regression analysis was conducted to examine the effects of IPC on links to HIV testing while controlling for demographic and agency information, provider training, and standardized measures of providers' feelings, attitudes, and opinions about IPC. Cross-sectional data from 142 providers in 13 agencies offering treatment and prevention services for HIV and substance-use disorders were collected via a survey. RESULTS: Those who scored higher on the IPC scale reported significantly higher rates of linkages to HIV testing. Compared to the null model (i.e., no predictor model), the final multilevel binary logistic regression model showed a significantly improved likelihood of linkage to HIV testing by 11.4%, p. < .05. The final model correctly classified 90.2% of links to HIV testing. Providers in agencies with smaller budgets and in agencies offering substance use disorder services were more likely to link clients to HIV testing. Younger providers who received HIV training were also more likely to link clients to HIV testing. CONCLUSIONS: Findings suggest IPC training as a potential strategy to improve linkages to HIV testing for clients at risk for HIV infection. Future research is recommended to identify specific areas of IPC that might have differential effects on links to HIV testing.

Cognitive behavioral therapy: a meta-analysis of race and substance use outcomes.

Cognitive behavioral therapy (CBT) is an effective intervention for reducing substance use. However, because CBT trials have included predominantly White samples caution must be used when generalizing these effects to Blacks and Hispanics. This meta-analysis compared the impact of CBT in reducing substance use between studies with a predominantly non-Hispanic White sample (hereafter NHW studies) and studies with a predominantly Black and/or Hispanic sample (hereafter BH studies). From 322 manuscripts identified in the literature, 16 met criteria for inclusion. Effect sizes between CBT and comparison group at posttest had similar effects on substance abuse across NHW and BH studies. However, when comparing pre-posttest effect sizes from groups receiving CBT between NHW and BH studies, CBT's impact was significantly stronger in NHW studies. T-test comparisons indicated reduced retention/engagement in BH studies, albeit failing to reach statistical significance. Results highlight the need for further research testing CBT's impact on substance use among Blacks and Hispanics.

Community Wise: Development of a Model to Address Oppression in Order to Promote Individual and Community Health.

Communities with histories of oppression have shown great resilience. Yet few health interventions focus on structural oppression as a contributor to health problems in these communities. This paper describes the development and active ingredients of Community Wise, a unique behavioral-health intervention designed to reduce substance use frequency, related health risk behaviors, and recidivism among individuals with a history of incarceration and substance abuse residing in distressed and predominantly African American communities. Community Wise, developed through the collaborative efforts of a board of service providers, researchers, consumers, and government officials, is a 12-week group intervention that aims to address behavioral-health problems by raising critical consciousness in distressed communities.

Evidence-Based Home Visiting Provisions and Child Maltreatment Report Rates: County-Level Analysis of US National Data From 2016 to 2018.

This observational ecological study examined county-level associations between evidence-based home visiting (EHV) provisions and child maltreatment report (CMR) rates, using national county-level data from 2016-2018. We found that longitudinal changes of EHV provisions were significantly negatively associated with county CMR rates while controlling for potential confounders. Our model estimated that after EHV provisions were launched in counties, their CMR rates decreased (or after they were ceased, rates increased) by 2.21 per 1000 children overall, 2.88 per 1000 children aged 0-5, 2.59 per 1000 children aged 6-11, 2.13 per 1000 male children, and 2.24 per 1000 female children. When limiting attention to EHV provisions funded by the Maternal, Infant and Early Childhood Home Visiting (MIECHV) program, we found no significant association perhaps because MIECHV-funded EHV provisions were a small subset of all EHV provisions. These findings propose potential protective impacts of county EHV provisions on overall county CMR rates. Yet, the small effect sizes suggest that EHV provisions should be considered as a part of a complete response to child maltreatment rather than in isolation. Given that EHV is provided to a very small part of the population, nevertheless, our findings suggest that expanding coverage would increase effect sizes.

The provider perception inventory: psychometrics of a scale designed to measure provider stigma about HIV, substance abuse, and MSM behavior.

Nongay identified men who have sex with men and women (NGI MSMW) and who use alcohol and other drugs are a vulnerable, understudied, and undertreated population. Little is known about the stigma faced by this population or about the way that health service providers view and serve these stigmatized clients. The provider perception inventory (PPI) is a 39-item scale that measures health services providers' stigma about HIV/AIDS, substance use, and MSM behavior. The PPI is unique in that it was developed to include service provider stigma targeted at NGI MSMW individuals. PPI was developed through a mixed methods approach. Items were developed based on existing measures and findings from focus groups with 18 HIV and substance abuse treatment providers. Exploratory factor analysis using data from 212 health service providers yielded a two dimensional scale: (1) individual attitudes (19 items) and (2) agency environment (11 items). Structural equation modeling analysis supported the scale's predictive validity (N=190 sufficiently complete cases). Overall findings indicate initial support for the psychometrics of the PPI as a measure of service provider stigma pertaining to the intersection of HIV/AIDS, substance use, and MSM behavior. Limitations and implications to future research are discussed.

Community Food Insecurity and Child Maltreatment Reports: County-Level Analysis of U.S. National Data From 2009 to 2018.

Current literature suggests that food insecurity increases child maltreatment risk. Yet, existing evidence is limited to individual-level associations among low-income, high-risk populations based on local, mostly urban data. This study aims to generalize prior findings to community-level associations in general populations, using national data including all urban-rural areas. We examined, for the first time, if food insecurity rates increase child maltreatment report (CMR) rates at the county level after controlling for potential confounders. We examined both within-community longitudinal changes (i.e., within-effects) and inter-community differences (i.e., between-effects) of food insecurity rates and their associations with CMR rates. We also examined differences by age, sex, race/ethnicity, maltreatment type, and urbanicity. We constructed longitudinal county-level data by linking multiple national databases, including all substantiated and unsubstantiated CMR records, the Map the Meal Gap's community food insecurity estimates, and Census data. The data covered over 96% of U.S. counties from 2009 to 2018. For analysis, we used within-between random effects models. Regarding between-effects, we found that in inter-community comparisons, higher food insecurity rates were significantly associated with increased CMR rates. This association was consistent by age, sex, maltreatment type, and urbanicity. For within-effects, we found that the association between longitudinal changes of food insecurity rates and CMR rates significantly differed by urbanicity. Specifically, longitudinal increases of food insecurity rates significantly increased CMR rates among large urban counties, but not among small urban and rural counties. Study findings highlight the importance of conducting further research to better understand the mechanisms through which food insecurity impact child maltreatment at both individual and community levels. Our community-level findings from general populations especially have significant implications for community-based programs and large-scale policies to achieve population-level impact on child well-being.

Longitudinal changes in the county-level relationship between opioid prescriptions and child maltreatment reports, United States, 2009-2018.

This article examines whether county opioid prescription rates were associated with county child maltreatment report (CMR) rates in the United States and whether this relationship changed over time. We linked multiple national data sets to assemble retail opioid prescription data, CMR data, rural-urban codes (to control for urbanicity), and census data (to control for other community characteristics, such as poverty rates) covering 2009-2018. Multilevel linear modeling analyzed the linked data. We found that the strength of the county-level relationship between opioid prescription rates and CMR rates increased almost linearly during the study period. The relationship was not significant in 2009-2011; it became significant in 2012 and grew stronger in the next 6 years. In 2012, there was one more CMR per 1,000 children in a county for every 14.3 more opioid prescriptions per 100 people. In 2018, the number of prescriptions related to this effect was 3.6. In other words, the county-level relationship between opioid prescriptions and CMRs was four times as strong in 2018 as it had been in 2012. This trend was also observed within all subgroups of child age and sex. By type, this trend was somewhat more pronounced for neglect, but somewhat less for sexual abuse. Our findings suggest a growing need for greater efforts to prevent child maltreatment in communities with high opioid prescription rates. Further research is warranted to reveal the underlying factors for this concerning trend. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Use of research electronic data capture (REDCap) in a sequential multiple assignment randomized trial (SMART): A practical example of automating double randomization.

Background: Adaptive interventions are often used in individualized health care to meet the unique needs of clients. Recently, more researchers have adopted the Sequential Multiple Assignment Randomized Trial (SMART), a type of research design, to build optimal adaptive interventions. SMART requires research participants to be randomized multiple times over time, depending upon their response to earlier interventions. Despite the increasing popularity of SMART designs, conducting a successful SMART study poses unique technological and logistical challenges (e.g., effectively concealing and masking allocation sequence to investigators, involved health care providers, and subjects) in addition to other challenges common to all study designs (e.g., study invitations, eligibility screening, consenting procedures, and data confidentiality protocols). Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for data collection. REDCap offers unique features that support researchers’ ability to conduct rigorous SMARTs. This manuscript provides an effective strategy for performing automatic double randomization for SMARTs using REDCap. Methods: Between January and March 2022, we conducted a SMART using a sample of adult (age 18 and older) New Jersey residents to optimize an adaptive intervention to increase COVID-19 testing uptake. In the current report, we discuss how we used REDCap for our SMART, which required double randomization. Further, we share our REDCap project XML file for future investigators to use when designing and conducting SMARTs. Results: We report on the randomization feature that REDCap offers and describe how the study team automated an additional randomization that was required for our SMART. An application programming interface was used to automate the double randomizations in conjunction with the randomization feature provided by REDCap. Conclusions: REDCap offers powerful tools to facilitate the implementation of longitudinal data collection and SMARTs. Investigators can make use of this electronic data capturing system to reduce errors and bias in the implementation of their SMARTs by automating double randomization. Trial registration: The SMART study was prospectively registered at Clinicaltrials.gov; registration number: NCT04757298, date of registration: 17/02/2021. Keywords: Research Electronic Data Capture (REDCap), randomized controlled trials (RCT), adaptive interventions, Sequential Multiple Assignment Randomized Trial (SMART), randomization, experimental design, reducing human errors, automation.

Individual and structural determinants of COVID-19 vaccine uptake in a marginalized community in the United States.

Socially and medically vulnerable groups (e.g., people 65 years or older, minoritized racial groups, non-telework essential workers, and people with comorbid conditions) experience barriers to COVID-19 prevention and treatment, increased burden of disease, and increased risk of death from COVID-19. Researchers are paying increased attention to social determinants of health (SDH) in explaining inequities in COVID-19-related health outcomes and rates of vaccine uptake. The purpose of the present manuscript is to identify clinically significant predictors of COVID-19 vaccine uptake among people who were socially and medically vulnerable to SARs-CoV-2 infection. Analysis was informed by the SDH framework and included a sample of 641 baseline surveys from participants in a clinical trial designed to increase COVID-19 testing. All participants were at high risk of developing COVID-19-related complications or dying from COVID-19. Following community-based participatory research principles, a well-established community collaborative board conducted every aspect of the study. Multiple logistic regressions were conducted to examine the relationships between individual and structural factors and COVID-19 vaccine uptake. In the final time adjusted model, we found that vaccine uptake was only predicted by specific individual-level factors: being 65 years and older, living with HIV/AIDS, and having previously received a flu vaccine or a COVID-19 test. Those reporting to believe in COVID-19-conspiracy theories were less likely to get the COVID-19 vaccine. More research is needed to identify predictors of vaccine uptake among people with comorbidities that make them more vulnerable to COVID-19 complications or death.

Surviving oppression under the rock: the intersection of New York's drug, welfare, and educational polices in the lived experiences of low-income African Americans.

Drawing on standpoint and intersectionality theories, this study explores the degree to which interactions among New York State's Rockefeller Drug Laws and educational and welfare policies have contributed to the maintenance of a culture of surveillance in which the lives of impoverished African Americans are overseen and influenced by oppressive policies and governmental institutions. Qualitative secondary analysis of longitudinal ethnographic data was conducted. Findings demonstrate multiple disadvantages that impoverished African American families struggling with substance use or sale experience. These disadvantages accumulated intergenerationally, in a snowball effect, making it difficult for participants to maintain stable lives. Findings explored the tension between participants' lived experiences and the multiple ways they either assimilated or resisted their oppression. New sensitive policies informed by standpoint, intersectionality, and Afrocentric perspectives must be developed to increase the availability of meaningful employment and strengthening impoverished African American communities.

From the Individual to the Community: Perspectives about Substance Abuse Services.

This paper argues that substance abuse interventions in distressed African-American communities must be culturally-tailored and incorporate a framework targeting changes in both individual behavior and the community. The current study employed Concept Mapping in conjunction with Community-Based Participatory Research (CBPR) principles to involve 100 community members, substance users, and service providers to examine the role of alcohol and other drugs in distressed African-American communities. Findings reveal the way participants understand the role of drugs and alcohol in their community and their perceptions of substance abuse services. The paper describes a collaborative approach to engage the community in addressing substance abuse.

Community food insecurity predicts child maltreatment report rates across Illinois zip codes, 2011-2018.

PURPOSE: We examined how longitudinal changes and inter-community differences of food insecurity rates were associated with child maltreatment report (CMR) rates at the zip code level. We assessed these associations overall, by urbanicity, and within subgroups of age, sex, and maltreatment type. METHODS: We used Illinois statewide zip code-level data from 2011 to 2018. We measured CMR rates based on Illinois child protective services records and food insecurity rates from Feeding America's Map the Meal Gap. We conducted spatial linear modeling to account for spatial dependence with controls for various socioeconomic, demographic, care burden, and instability conditions of communities. RESULTS: Both longitudinal changes and inter-community differences of food insecurity rates were significantly associated with increased CMR rates overall and within all subgroups. These associations were significant among all large urban, small urban, and rural areas, while longitudinal changes of food insecurity rates had significantly stronger associations among small urban areas compared with other areas. CONCLUSIONS: Communities experiencing higher food insecurity had higher CMR rates. Increases in food insecurity over time were associated with increases in CMR rates. These associations were reproduced within subgroups of child age, sex, maltreatment type, and urbanicity. Attention and collaborative efforts are warranted for high food insecure communities.

Optimization of a new adaptive intervention using the SMART Design to increase COVID-19 testing among people at high risk in an urban community.

BACKGROUND: COVID-19 has impacted the health and social fabric of individuals and families living across the USA, and it has disproportionately affected people living in urban communities with co-morbidities, those working in high-risk settings, refusing or unable to adhere to CDC guidelines, and more. Social determinants of health (SDH), such as stigmatization, incarceration, and poverty, have been associated with increased exposure to COVID-19 and increased deaths. While vaccines and booster shots are available, it will take time to reach herd immunity, and it is unclear how long newly developed vaccines provide protection and how effective they are against emerging variants. Therefore, prevention methods recommended by the Centers for Disease and Control (CDC)-i.e., testing, hand-washing, social distancing, contact tracing, vaccination and booster shots, and quarantine-are essential to reduce the rates of COVID-19 in marginalized communities. This project will adapt and test evidence-based HIV interventions along the prevention and treatment cascade to help address COVID-19 prevention needs. METHODS: The study aims to (1) optimize an adaptive intervention that will increase rates of testing and adherence to New Jersey State COVID-19 recommendations (testing, social distancing, quarantine, hospitalization, contact tracing, and acceptance of COVID-19 vaccination and booster shots) among high-risk populations and (2) identify predictors of testing completion and adherence to New Jersey recommendations. This study follows Community Based Participatory Research (CBPR) principles to conduct a Sequential, Multiple Assignment Randomized Trial (SMART) with 670 COVID-19 medically/socially vulnerable people. Participants will be recruited using a variety of strategies including advertisements on social media, posting fliers in public places, street outreach, facility-based, and snowball sampling. Participants complete a baseline survey and are randomized to receive navigation services or an electronic brochure. They then complete a follow-up 7 days after baseline and are randomized again to either continue with their original assignment or switch to the other intervention or critical dialog or brief counseling. Participants then complete a 5-week post-baseline follow-up. Guided by the COVID-19 Continuum of Prevention, Care, and Treatment, the analysis will explore the factors associated with COVID-19 testing within 7 days of the intervention. DISCUSSION: This paper describes the protocol of the first study to use SMART following CBPR to adapt evidence-based HIV prevention interventions to COVID-19. The findings will inform the development of an effective and scalable adaptive intervention to increase COVID-19 testing and adherence to public health recommendations, including vaccination and booster shots, among a marginalized and difficult-to-engage population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04757298 . Registered on February 17, 2021.

The Critical Dialogue Cornerstone: Suggested Practices to Guide Implementation, Facilitation and Evaluation.

There has been an increased focus on utilizing critical consciousness-focused interventions to address complex, multidimensional socio-cultural problems, particularly health inequities. These interventions usually incorporate a critical dialogue component. However, there's little guidance on how to implement, facilitate and evaluate critical dialogue to develop critical consciousness (i.e., reflecting and acting on sociopolitical inequities). This conceptual paper: 1) introduces critical dialogue and the tools used to implement critical dialogue from the literature; 2) details the development of the Community Wise intervention to present how Community Wise incorporated a critical dialogue component; 3) provides a brief overview of a proposed framework of critical consciousness development that the critical dialogue component of Community Wise could support; 4) provides an anecdotal exploration of the critical dialogue sessions used in the first pilot test of the intervention through the proposed framework of Transformative Consciousness; and 5) suggests practice guidelines for group work that incorporates facilitated critical dialogue.