Telehealth Depression Treatments for Older Adults

2015-11-11 18:53:49 | BioPortfolio


This study aims to find an effective and sustainable approach to reducing disparities in accessing mental health services for an underserved and growing population group of low-income, racially diverse, homebound older adults. It will compare two aging-service integrated, teledelivered depression treatments for these seniors. One model is short-term problem-solving therapy by licensed clinicians; the second model is self-care management support by trained lay advisors. The findings are expected to create a foundation of information for guiding the implementation of acceptable, effective, and sustainable depression care within widely available aging-service infrastructures.


The long-term objective of the proposed study is to improve access to depression treatments for low-income, racially diverse homebound seniors, a population experiencing significant disparities in mental health care due to their homebound and low-income status. Specific aims are to compare the acceptability, clinical effectiveness, treatment cost, and budget impact of the two teledelivered treatment delivery models: problem-solving therapy (PST) by licensed clinicians and self-care management (SCM) support by trained lay mental health workers/advisors. The interventionists will be integrated into an aging-service agency; hence, integrated tele-PST (IT-PST) ad integrated tele-SCM (IT-SCM). Although tele-psychotherapy is likely to be an effective mental health service delivery model for the target population, the current and projected shortage of such clinicians and the costs of deploying highly trained professionals pose barriers to this model's widespread real-world adoption and sustainability. A more plausible option may indeed have to utilize trained lay mental health workers. The study participants will be 276 low-income, racially diverse homebound seniors who are served by a home-delivered meal (HDM) program and other aging-service agencies in Austin, Tex. In a 3-arm, pragmatic clinical trial with randomization prior to consent (a preferred public health approach), the participants will receive five sessions of IT-PST, five sessions of IT-SCM, or five telephone check-in calls (for the usual care-UC-group). Our first hypothesis is that IT-PST and IT-SCM will be equally acceptable to the participants. Our second hypothesis is that both IT-PST and IT-SCM will be more effective than UC in reducing depressive symptoms, although IT-PST may be more effective than IT-SCM. Symptoms will be assessed with the 24-item Hamilton Depression Rating Scale (HAMD) at 12, 24, and 36 weeks after baseline. Additional outcomes will be depression-free days (DFDs) and disability (WHODAS 2.0). Our third hypothesis is that IT-SCM will have a lower delivery cost than IT-PST, but both IT-PST and IT-SCM will be more cost-effective than usual care. The analyses include (a) comparisons of delivery costs between IT-PST and IT-SCM; (b) assessment of cost-effectiveness (CEA) based on DFDs and health-related quality adjusted life-year measured by EuroQol-5 (EQ-5D); and (3) budget impact (BIA) of IT-PST relative to IT-SCM. Both CEA and BIA will employ a hybrid public program perspective of the AoA and the Centers for Medicare and Medicaid. Public health significance of this study is that the data will help aging-service providers and funders assess respective strengths and weaknesses of each model as a sustainable approach to providing depression care for an underserved and growing population group and improving their access to evidence-based mental health services. (The terms older adults and seniors are used interchangeably because the latter term is frequently used in aging services.)

Study Design

Allocation: Randomized, Endpoint Classification: Efficacy Study, Intervention Model: Parallel Assignment, Masking: Open Label, Primary Purpose: Treatment






University of Texas at Austin
United States


Not yet recruiting


University of Texas at Austin

Results (where available)

View Results


Published on BioPortfolio: 2015-11-11T18:53:49-0500

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