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.

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.

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.

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.

Bridges to life: evaluation of an in-prison restorative justice intervention.

Restorative justice initiatives have been identified as primarily, if not exclusively, useful as a "front-end" diversionary option reserved for non violent property crimes and minor assaults. In-prison restorative justice programs are rare and have not been examined for their impact on recidivism. Bridges to Life (BTL) is a voluntary, manualized, ecumenical faith-based restorative justice program offered to incarcerated offenders who are within nine months of their release. A survey of BTL graduates (n=1021) found an appreciatively lower recidivism rate than the general population of released inmates. Quantitative and qualitative analyses suggest that BTL helps break through offenders' denial and self-centeredness, exposing them to the impact of their actions and helping them feel the pain their crimes created. Possible reasons for the positive nature of participants' responses are advanced. The use of in-prison restorative justice programs to facilitate offender re-entry is also discussed.

Keeping families engaged: the effects of home-based family therapy enhanced with experiential activities.

Engagement of high-risk adolescents and their families in treatment is a considerable challenge for service providers and agencies. Despite its importance, little research has been conducted that explores this important treatment process. To address this gap, a test of an innovative method to improve engagement in family therapy was undertaken. Findings of this study of 42 intervention group families and 41 comparison group families (N=83) suggest that augmenting in-home family therapy with short and creative experiential activities can significantly increase engagement and retention in treatment. Further research of engagement as a mechanism of change in family-based treatment is needed.