JMIR Publications

ABSTRACT

Background:

Voice-controlled smart speakers and displays have unique but unproven potential for delivering eHealth interventions. Many laptop- and smartphone-based interventions have been shown to improve multiple outcomes, but voice-controlled platforms have not been tested in large-scale, rigorous trials. Older adults with multiple chronic health conditions (eg, diabetes, arthritis)—who need tools to help with daily management of their conditions—may be especially good candidates for interventions on voice-controlled devices, because these patients often have physical limitations such as tremors or vision problems that make use of laptops and smartphones challenging.

Objective:

Assess whether participants using an evidence-based intervention (ElderTree) on a smart display will experience decreased pain interference and improved quality of life and related measures in comparison to participants using ElderTree on a laptop and control participants given no device or access to ElderTree.

Methods:

291 adults age 60 and older with chronic pain plus at least 3 additional chronic conditions (eg, diabetes, arthritis) will be recruited from primary care clinics and community venues and randomized 1:1:1 to: (1) access to ElderTree on a smart display along with their usual care, (2) access to ElderTree on a touchscreen laptop along with usual care, or (3) usual care alone. All patients will be followed for 8 months. Primary outcomes are differences between groups on measures of pain interference and psychosocial quality of life. Secondary outcomes are between-groups differences on system use at 8 months, physical quality of life, pain intensity, hospital readmissions, communication with medical providers, health distress, well-being, loneliness, and irritability. We will also examine mediators and moderators of effects of ElderTree on both platforms. At 0, 4, and 8 months, patients will complete written surveys comprising validated scales selected for good psychometric properties with similar populations; ElderTree use data will be collected continuously in system logs. We will use linear mixed effect models to evaluate outcomes over time, with treatment condition and time as between-subjects factors. Separate analyses will be conducted for each outcome.

Results:

Recruitment began August 2021 and will run through April 2023; the intervention period will end December 2023.

Conclusions:

To our knowledge, this is the first study to examine with a large sample and long timeframe whether a smart device can perform as well as or better than a laptop in implementing a health intervention. The goal of ElderTree, regardless of delivery platform, is to improve patient self-management, and as a result relieve some of the burden on the healthcare system. Because patients with multiple chronic conditions are such a large cohort, the implications for cost as well as patient well-being are significant. Making the best use of current and developing technologies is a critical part of this effort. Clinical Trial: ClinicalTrials.gov NCT04798196