Engagement, Satisfaction, and Mental Health Outcomes Across Different Residential Subgroup Users of a Digital Mental Health Relational Agent: Exploratory Single-Arm Study (Preprint)

Author:

Forman-Hoffman Valerie LORCID,Pirner Maddison CORCID,Flom MeganORCID,Kirvin-Quamme AndrewORCID,Durden EmilyORCID,Kissinger Jennifer AORCID,Robinson AthenaORCID

Abstract

BACKGROUND

Mental illness is a pervasive worldwide public health issue. Residentially vulnerable populations, such as those living in rural medically underserved areas (MUAs) or mental health provider shortage areas (MHPSAs), face unique access barriers to mental health care. Despite the growth of digital mental health interventions using relational agent technology, little is known about their use patterns, efficacy, and favorability among residentially vulnerable populations.

OBJECTIVE

This study aimed to explore differences in app use, therapeutic alliance, mental health outcomes, and satisfaction across residential subgroups (metropolitan, nonmetropolitan, or rural), MUAs (yes or no), and MHPSAs (yes or no) among users of a smartphone-based, digital mental health intervention, Woebot LIFE (WB-LIFE). WB-LIFE was designed to help users better understand and manage their moods and features a relational agent, Woebot, that converses through text-based messages<i>.</i>

METHODS

We used an exploratory study that examined data from 255 adults enrolled in an 8-week, single-arm trial of WB-LIFE. Analyses compared levels of app use and therapeutic alliance total scores as well as subscales (goal, task, and bond), mental health outcomes (depressive and anxiety symptoms, stress, resilience, and burnout), and program satisfaction across residential subgroups.

RESULTS

Few study participants resided in nonmetropolitan (25/255, 10%) or rural (3/255, 1%) areas, precluding estimates across this variable. Despite a largely metropolitan sample, nearly 39% (99/255) resided in an MUA and 55% (141/255) in an MHPSA. There were no significant differences in app use or satisfaction by MUA or MHPSA status. There also were no differences in depressive symptoms, anxiety, stress, resilience, or burnout, with the exception of MUA participants having higher baseline depressive symptoms among those starting in the moderate range or higher (Patient Health Questionnaire-8 item scale≥10) than non-MUA participants (mean 16.50 vs 14.41, respectively; <i>P</i>=.01). Although working alliance scores did not differ by MHPSA status, those who resided in an MUA had higher goal (2-tailed <i>t</i><sub>203.47</sub>=2.21; <i>P</i>=.03), and bond (<i>t</i><sub>203.47</sub>=1.94; <i>P</i>=.05) scores at day 3 (<i>t</i><sub>192.98</sub>=2.15; <i>P</i>=.03), and higher goal scores at week 8 (<i>t</i><sub>186.19</sub>=2.28; <i>P</i>=.02) as compared with those not living in an MUA.

CONCLUSIONS

Despite the study not recruiting many participants from rural or nonmetropolitan populations, sizable proportions resided in an MUA or an MHPSA. Analyses revealed few differences in app use, therapeutic alliance, mental health outcomes (including baseline levels), or satisfaction across MUA or MHPSA status over the 8-week study. Findings suggest that vulnerable residential populations may benefit from using digital agent–guided cognitive behavioral therapy.

CLINICALTRIAL

ClinicalTrials.gov NCT05672745; https://clinicaltrials.gov/study/NCT05672745

Publisher

JMIR Publications Inc.

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