Treating Depression Among Low-Income Patients With Cancer
NCT ID: NCT00565110
Last Updated: 2017-07-24
Study Results
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View full resultsBasic Information
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COMPLETED
NA
472 participants
INTERVENTIONAL
2004-06-30
2010-07-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
TREATMENT
SINGLE
Study Groups
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Enhanced Usual Care
EUC patients receive medical center standard oncology care and supportive services routinely provided to all patients with cancer. In addition, EUC patients are given a patient focused and a family focused educational pamphlet on depression and cancer and a listing of financial and community resources (in Spanish for Spanish-speaking patients). With patient consent, as described in the informed written consent, the treating oncologist is informed via medical chart note if EUC patients screen positive for major depression. Treating oncology attending physicians, fellows and residents are invited to attend a didactic session led by the study psychiatrist on treating depression in cancer patients.
No interventions assigned to this group
ADAPt-C intervention
Intervention patients receive: first-line choice of antidepressant medication management,psychotherapy or both; depression education, and maintenance/relapse prevention counseling based on a stepped care depression treatment algorithm, treatment follow-up and feedback to the oncologist, and systems navigation; a psychiatric consultant who prescribes antidepressant medication for individual patients; and a didactic for oncologists on depression management. Cultural adaptations include: patient choice of first line treatment and degree of family participation in their depression care; PST tailored for literacy and patients with cancer; bilingual, bicultural CDCS; Spanish educational materials.
ADAPt-C intervention
Experimental Arm patients receive: first-line choice of antidepressant medication management,psychotherapy or both; depression education, and maintenance/relapse prevention counseling based on a stepped care depression treatment algorithm, treatment follow-up and feedback to the oncologist, and systems navigation; a psychiatric consultant who prescribes antidepressant medication for individual patients; and a didactic for oncologists on depression management. Cultural adaptations include: patient choice of first line treatment and degree of family participation in their depression care; PST tailored for literacy and patients with cancer; bilingual, bicultural CDCS; Spanish educational materials.
Interventions
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ADAPt-C intervention
Experimental Arm patients receive: first-line choice of antidepressant medication management,psychotherapy or both; depression education, and maintenance/relapse prevention counseling based on a stepped care depression treatment algorithm, treatment follow-up and feedback to the oncologist, and systems navigation; a psychiatric consultant who prescribes antidepressant medication for individual patients; and a didactic for oncologists on depression management. Cultural adaptations include: patient choice of first line treatment and degree of family participation in their depression care; PST tailored for literacy and patients with cancer; bilingual, bicultural CDCS; Spanish educational materials.
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
No
Sponsors
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National Cancer Institute (NCI)
NIH
University of Southern California
OTHER
Responsible Party
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Kathleen R. Ell
Professor
Principal Investigators
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Kathleen R Ell, DSW
Role: PRINCIPAL_INVESTIGATOR
University of Southern California, School of Social Work
Locations
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Los Angeles County+University of Southern California Medical Center
Los Angeles, California, United States
Countries
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References
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Ell K, Quon B, Quinn DI, Dwight-Johnson M, Wells A, Lee PJ, Xie B. Improving treatment of depression among low-income patients with cancer: the design of the ADAPt-C study. Gen Hosp Psychiatry. 2007 May-Jun;29(3):223-31. doi: 10.1016/j.genhosppsych.2007.01.005.
Other Identifiers
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USCIRB-HS-10-00466
Identifier Type: -
Identifier Source: org_study_id
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