Literature Collection
11K+
References
9K+
Articles
1400+
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).


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 Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.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 Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.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 Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.


OBJECTIVE: Effective treatments for opioid use disorder exist, but rural areas of the United States have a shortage of services offering such treatments. Physician bias toward patients with opioid use disorder can also limit care access, but no studies have assessed whether physician bias is a more acute barrier in rural compared with urban communities. METHODS: In total, 408 board-certified physicians in Ohio, a state with a high rate of opioid overdoses, completed an online survey examining perspectives on clinical care for patients who misuse opioids. Respondents with missing county-level data were excluded, leaving a total sample of 274. The authors used t tests to determine rural-urban differences in bias, key predictors of bias, and availability of opioid services. Multivariable regression modeling was used to estimate rural-urban differences in bias independent of key bias predictors. RESULTS: Physicians in rural areas (N=37) reported higher levels of bias toward patients with opioid use disorder than did their urban counterparts (N=237). This difference remained statistically significant even after accounting for known bias predictors and physician specialty. Physicians specializing in addiction medicine reported lower bias than did physicians not working in this specialty. CONCLUSIONS: Given existing disparities in harm reduction and addiction treatment services in rural areas, increased physician bias in counties lacking these services suggests that rural patients with opioid use disorder face numerous challenges to finding effective treatment. Bias reduction interventions should target health care professionals in rural communities where such efforts may have the most pronounced impact on improving health care access.

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.