JMIR Publications

ABSTRACT

Background:

Background:

Digital health technologies increasingly support long-term stroke management and rehabilitation, but technophobia may hinder their acceptance and sustained use among older patients with stroke. Evidence in this population remains limited.

Objective:

Objective:

To examine the level, associated factors, and subjective experiences of technophobia toward digital health technologies among older patients with stroke and inform targeted interventions.

Methods:

Methods:

We used an explanatory sequential mixed methods design. In the quantitative phase, older patients with stroke were recruited by convenience sampling from a tertiary grade A hospital in Shanghai, China, between January 15, 2024, and January 2, 2025. Participants completed a general information questionnaire and the Chinese versions of the Technophobia Scale, the eHealth Literacy Scale, the Perceived Social Support Scale, and the Stroke Self-Efficacy Questionnaire. Univariable, correlation, and multivariable linear regression analyses were performed. Qualitative participants were purposively selected from the quantitative sample using maximum variation sampling informed by quantitative findings. Semistructured interviews conducted between February 6 and April 30, 2025, were analyzed using reflexive thematic analysis. Quantitative and qualitative findings were integrated to elucidate associated factors and their contextual manifestations.

Results:

Results:

Among 343 quantitative participants, the median technophobia score was 25.0 (IQR 22.0–33.0). Multivariable linear regression showed lower technophobia scores among patients with monthly per capita household income of RMB 5000–6999 versus less than RMB 1000 (B=−3.60, 95% CI −6.44 to −0.76; P=.013) and among occasional versus never users of digital health technologies (B=−3.98, 95% CI −6.94 to −1.03; P=.008). Higher eHealth literacy (B=−0.45, 95% CI −0.58 to −0.32; P<.001), perceived social support (B=−0.35, 95% CI −0.42 to −0.29; P<.001), and stroke self-efficacy (B=−0.08, 95% CI −0.13 to −0.02; P=.010) were also associated with lower technophobia scores. Fifteen qualitative participants were interviewed, yielding four themes: affordability of digital health technologies, adoption and proficiency in using digital health technologies, influence of social relationship networks, and resources for digital health technology competence. Integrated analysis indicated broad convergence and complementarity between the quantitative and qualitative findings.

Conclusions:

Conclusions:

Technophobia varied among older patients with stroke and was associated with monthly per capita household income, frequency of digital health technology use, eHealth literacy, perceived social support, and stroke self-efficacy. These findings suggest that technophobia is not limited to operational difficulties but may reflect the interplay of personal resources, social support, and technology-use contexts. Stroke-specific digital health interventions may need to address eHealth literacy, stroke self-efficacy, social support, and user experience to promote acceptance and use among older patients with stroke.