Race and Socioeconomic Status as Predictors of Willingness to Use Digital Mental Health Interventions or One-On-One Psychotherapy: National Survey Study

Abstract

Background There is an ongoing debate about whether digital mental health interventions (DMHIs) can reduce racial and socioeconomic inequities in access to mental health care. A key factor in this debate involves the extent to which racial and ethnic minoritized individuals and socioeconomically disadvantaged individuals are willing to use, and pay for, DMHIs. Objective This study examined racial and ethnic as well as socioeconomic differences in participants’ willingness to pay for DMHIs versus one-on-one therapy (1:1 therapy). Methods We conducted a national survey of people in the United States (N=423; women: n=204; mean age 45.15, SD 16.19 years; non-Hispanic White: n=293) through Prolific. After reading descriptions of DMHIs and 1:1 therapy, participants rated their willingness to use each treatment (1) for free, (2) for a small fee, (3) as a maximum dollar amount, and (4) as a percentage of their total monthly income. At the end of the study, there was a decision task to potentially receive more information about DMHIs and 1:1 therapy. Results Race and ethnicity was associated with willingness to pay more of one’s income, as a percent or in dollar amounts, and was also associated with information-seeking for DMHIs in the behavioral task. For most outcomes, race and ethnicity was not associated with willingness to try 1:1 therapy. Greater educational attainment was associated to willingness to try DMHIs for free, the decision to learn more about DMHIs, and willingness to pay for 1:1 therapy. Income was inconsistently associated to willingness to try DMHIs or 1:1 therapy. Conclusions If they are available for free or at very low costs, DMHIs may reduce inequities by expanding access to mental health care for racial and ethnic minoritized individuals and economically disadvantaged groups.

Prevalence and 20-year Trends in Meditation, Yoga, Guided Imagery and Progressive Relaxation Use Among US Adults From 2002 to 2022

“…The most highly represented sociodemographic subgroups among meditation users in 2022 were younger-to-middle-aged (25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44), female, White or 'Other' race, not in a relationship, more educated (bachelor, master or higher), and residing in the West (Figure 1, Table 1, Table S6). The least represented groups were young (18)(19)(20)(21)(22)(23)(24) or older (45-64, 65+), male, Hispanic race, in a relationship, less educated (less than high school, high school) and residing in the South.…”

“…Studies of meditation have highlighted potential harms that include prolonged adverse experiences among approximately 10% of users [41][42][43] . A recent cross-sectional survey found that low income and self-guided training via apps may be associated with adverse experiences, with first exposure via apps potentially associated with lasting impairment 42 (noting that lower socioeconomic groups are also more likely to try digital mental health 44 , and also experience more acute distress and greater mental health need which itself predicts adverse experiences 43,45 ). To plan appropriate public health services that maximize benefits and minimize harms, it is essential to know who is using CAM practices to understand whether they are safe, and suited to meet the needs for which they are being used.…”

Prevalence and 20-year trends in meditation, yoga, guided imagery and progressive relaxation use among US adults from 2002 to 2022

“…Studies of meditation have highlighted potential harms that include prolonged adverse experiences among approximately 10% of users 41 – 43 . A recent cross-sectional survey found that low income and self-guided training via apps may be associated with adverse experiences, with first exposure via apps potentially associated with lasting impairment 42 (noting that lower socioeconomic groups are also more likely to try digital mental health 44 , and also experience more acute distress and greater mental health need which itself predicts adverse experiences 43 , 45 ). To plan appropriate public health services that maximize benefits and minimize harms, it is essential to know who is using CAM practices to understand whether they are safe, and suited to meet the needs for which they are being used.…”