Literature Collection
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References
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Articles
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Grey Literature
4600+
Opioids & SU
The Literature Collection contains over 11,000 references for published and grey literature on the integration of behavioral health and primary care. Learn More
Use the Search feature below to find references for your terms across the entire Literature Collection, or limit your searches by Authors, Keywords, or Titles and by Year, Type, or Topic. View your search results as displayed, or use the options to: Show more references per page; Sort references by Title or Date; and Refine your search criteria. Expand an individual reference to View Details. Full-text access to the literature may be available through a link to PubMed, a DOI, or a URL. References may also be exported for use in bibliographic software (e.g., EndNote, RefWorks, Zotero).
Background: Group-based models of Office-Based Opioid Treatment with buprenorphine-naloxone (B/N) are increasingly being implemented in clinical practice to increase access to care and provide additional therapeutic benefits. While previous studies reported these Group-Based Opioid Treatment (GBOT) models are feasible for providers and acceptable to patients, there has been no literature to help providers with the more practical aspects of how to create and maintain GBOT in different outpatient settings. Case series: We present 4 cases of GBOT implementation across a large academic health care system, highlighting various potential approaches for providers who seek to implement GBOT and demonstrate "success" based on feasibility and sustainability of these models. For each case, we describe the pros and cons and detail the personnel and resources involved, patient mix and group format, workflow logistics, monitoring and management, and sustainability components. Discussion: The implementation details illustrate that there is no one-size-fits-all approach, although feasibility is commonly supported by a team-based, patient-centered medical home. This approach includes the capacity for referral to higher levels of mental health and addiction support services and is bolstered by ongoing provider communication and shared resources across the health system. Future research identifying the core and malleable components to implementation, their evidence base, and how they might be influenced by site-specific resources, culture, and other contextual factors can help providers better understand how to implement a GBOT model in their unique clinical environment.

This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
This grey literature reference is included in the Academy’s Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
This grey literature reference is included in the Academy’s Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.


Background: This proof-of-concept trial examined a 6-month Prevention Plus (PP) intervention implemented in a federally qualified health center on child standardized BMI (ZBMI), using a planned clinical effect threshold of -0.16 ZBMI. The relationship between food security status and PP delivered with caregiver goals (PP+) and without caregiver goals (PP-) on energy balance behaviors (i.e., fruits and vegetables, physical activity) and child ZBMI was explored. Methods: Seventy-three, underserved children, 4-10 years of age with a BMI ≥85th percentile, were randomized to one of two interventions, PP+ and PP-, both providing 2.5 hours of contact time, implemented in five clinics by behavioral health consultants (BHCs). Outcomes were child anthropometrics (included 9-month follow-up), implementation data collected from electronic health records, and caregiver and BHC evaluations. Results: Children were 57.5% female and 78.1% Hispanic, with 32.9% from food-insecure households and 58.9% from households with an annual income of less than $20,000. Child ZBMI significantly (p < 0.05) decreased at 6 and 9 months (-0.08 ± 0.24 and -0.12 ± 0.43), with only PP+ reaching the clinical threshold at 9 months (PP+: -0.20 ± 0.42 vs. PP-: -0.05 ± 0.42). Sixty-four percent of families attended ≥50% of the sessions, and BHCs delivered 78.5% ± 23.5% of components at attended sessions. Caregivers were satisfied with the intervention and BHCs found the intervention helpful/useful. No relationship with food insecurity status and outcomes was found. Conclusions: PP+ when delivered by a primary care provider to underserved families showed promise for producing a clinically meaningful effect. Families and providers felt the intervention was a viable treatment option.

This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
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