JMIR Publications

ABSTRACT

Background:

Digital health technologies are increasingly being integrated into mental health care. However, the adoption of these technologies can be influenced by patients' digital literacy and attitudes, which may vary based on sociodemographic factors. This variability necessitates a better understanding of patient digital literacy and attitudes to prevent a digital divide, which can worsen existing healthcare disparities.

Objective:

This study aimed to assess digital literacy and attitudes toward digital health technologies among a diverse psychiatric outpatient population. Additionally, the study sought to identify clusters of patients based on their digital literacy and attitudes and to compare sociodemographic characteristics among these clusters.

Methods:

A survey was distributed to adult psychiatric patients with various diagnoses in an urban outpatient psychiatry program. The survey included a demographic questionnaire, a digital literacy questionnaire, and a digital health attitudes questionnaire. Multiple linear regression analyses were used to identify predictors of digital literacy and attitudes. Cluster analysis was performed to categorize patients based on their responses. Pairwise comparisons and one-way ANOVA were conducted to analyze differences between clusters.

Results:

A total of N= 256 patients were included in the analysis. The mean age of participants was 32 years (SD 12.6, range 16-70). The sample was racially/ethnically diverse: White (38.9%), Black (15.2%), Latinx (17.2%), Asian (23.0%), and Other (5.7%). Digital literacy was high for technologies such as smartphones, videoconferencing, and social media (items with >75% of participants reporting at least some use), but lower for health apps, mental health apps, wearables, and virtual reality (items with <42% reporting at least some use). Attitudes toward using technology in clinical care were generally positive (9 out of 10 items received >75% positive score), particularly for communication with providers and health data sharing. Older age (P<.001) and lower educational attainment (P<.001) negatively predicted digital literacy scores, but no demographic variables predicted attitude scores. Cluster analysis identified three patient groups. Relative to the other clusters, Cluster 1 (n=30) had lower digital literacy and intermediate acceptance of digital technology. Cluster 2 (n=50) had higher literacy and lower acceptance. Cluster 3 (n=176) displayed both higher literacy and acceptance. Significant between-cluster differences were observed in mean age and education level between clusters (P<.001), with Cluster 1 participants being older and having lower levels of formal education.

Conclusions:

High digital literacy and acceptance of digital technologies were observed among our patients, indicating a generally positive outlook for digital health clinics. Our results also found that patients of older age and lower formal levels of educational attainment had lower digital literacy, highlighting the need for targeted interventions to support those who may struggle with adopting digital health tools.