Perspectives on Caregiver-Focused mHealth Technologies to Improve Mental Health Treatment for Low-Income Youth with ADHD

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Abstract

To examine stakeholder perspectives regarding (1) whether mobile health (mHealth) tools can improve the mental health (MH) treatment process for low-income youth with ADHD in safety net settings and (2) what functions would be helpful to improve the treatment process. This study analyzed qualitative data from a larger project that collected information from key stakeholders at four safety net clinics across Georgia. We conducted five focus groups with caregivers who had a Medicaid-insured child receiving treatment for ADHD, and 17 semi-structured interviews with clinic administrators and providers. Stakeholders shared their perspectives on strategies to improve the MH treatment process, including the use of mHealth tools. Caregivers also completed a brief survey about technology use. We present findings from a thematic analysis of the qualitative data and descriptive findings from the survey. Participants in each group of stakeholders expressed interest in mHealth tools that would (1) deliver reminders for caregivers (including appointment and medication refill reminders); (2) help caregivers obtain information about ADHD symptoms and treatment options; (3) help caregivers track information about their child’s symptoms and treatment progress; and (4) facilitate communication between caregivers and providers. While more than three-fourths of caregivers had a smartphone, providers and administrators expressed concern that access to mHealth technologies may be inconsistent if low-income families are unable to pay cellular phone bills. Caregivers, clinic administrators, and providers were supportive of enhanced mHealth technologies to improve MH care for this population.

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Cummings, J. R., Gaydos, L. M., Mensa-Kwao, A., Song, M., & Blake, S. C. (2019). Perspectives on Caregiver-Focused mHealth Technologies to Improve Mental Health Treatment for Low-Income Youth with ADHD. Journal of Technology in Behavioral Science, 4(1), 6–16. https://doi.org/10.1007/s41347-018-0066-2

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