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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 Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
BACKGROUND: Depression and chronic pain are commonly comorbid, mutually reinforcing, and debilitating. Emerging approaches to mobile behavioral health care (mHealth) promise to improve outcomes for patients with comorbid depression and chronic pain by integrating with existing care models to bolster support and continuity between clinical visits; however, the evidence base supporting the use of mHealth to augment care for this patient population is limited. OBJECTIVE: To develop an evidence base that sets the stage for future research, we aimed to explore the associations between changes in depression severity and various integrated care models, with and without mHealth augmentation, among patients with comorbid depression and nonmalignant chronic pain. METHODS: Our team leveraged retrospective, real-world data from 3837 patients with comorbid depression and nonmalignant chronic pain who received integrated behavioral health care (IBH) at a subspecialty pain clinic. We analyzed one IBH-only, non-mHealth cohort (n=2765), an mHealth-augmented cohort (n=844), and a collaborative care (CoCM)+mHealth cohort (n=136), which were supported by the NeuroFlow mHealth platform, and a pre-CoCM mHealth cohort (n=92), which was supported by the mHealth platform for 3 months prior to beginning the chronic pain treatment. We evaluated changes in depression severity between treatment cohorts via longitudinal analyses of both clinician- and mHealth-administered Patient Health Questionnaire-9 (PHQ-9) assessments. RESULTS: mHealth-augmented integrated care led to significantly greater proportions of patients reaching clinical benchmarks for reduction (725/844, 86% vs 2112/2765, 76%), response (689/844, 82% vs 2027/2765, 73%), and remission (629/844, 75% vs 1919/2765, 69%) compared with integrated care alone. Furthermore, hierarchical regression modeling revealed that patients who received mHealth-augmented psychiatric CoCM experienced the greatest sustained reductions in on-average depression severity compared with other cohorts, irrespective of clinical benchmarks. In addition, patients who engaged with an mHealth platform before entering CoCM experienced a 7.2% reduction in average depression severity before starting CoCM treatment. CONCLUSIONS: Our findings suggest that mHealth platforms have the potential to improve treatment outcomes for patients with comorbid chronic pain and depression by providing remote measurement-based care, tailored interventions, and improved continuity between appointments. Moreover, our study set the stage for further research, including randomized controlled trials to evaluate causal relationships between mHealth engagement and treatment outcomes in integrated care settings.
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.