Trust and anxiety as primary drivers of digital health acceptance in multiple sclerosis: toward an extended disease-specific technology acceptance model - Report - MDSpire
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Trust and anxiety as primary drivers of digital health acceptance in multiple sclerosis: toward an extended disease-specific technology acceptance model
Emotional and Disease-Specific Factors Affect Digital Health Adoption in MS
Overview
This study identifies trust in technology and technological anxiety as key predictors of digital health adoption intentions among people with Multiple Sclerosis (MS). Symptom severity moderates these relationships, diminishing the impact of perceived ease of use and amplifying anxiety effects, revealing an intention–behavior gap in wearable use.
Background
Multiple Sclerosis (MS) is characterized by fluctuating cognitive and physical symptoms that may uniquely influence the adoption of digital health technologies. Traditional acceptance models like TAM and UTAUT emphasize cognitive factors such as perceived usefulness and ease of use but may not fully capture emotional and disease-specific barriers in MS. Emotional constructs such as trust in technology and technological anxiety have emerged as critical determinants in healthcare technology adoption, particularly for vulnerable populations with chronic conditions. Understanding these factors is essential to tailor digital health tools that effectively support MS patients.
Data Highlights
Measure
MS Group (n=64)
Other Chronic Conditions (n=14)
Statistical Result
Perceived Usefulness (PU)
Not significantly different
Not significantly different
p > .05
Perceived Ease of Use (PEOU)
Not significantly different
Not significantly different
p > .05
Behavioral Intention (BI)
Not significantly different
Not significantly different
p > .05
Social Influence (SI)
Not significantly different
Not significantly different
p > .05
Regular Wearable Use
Substantially lower
Higher
χ2(2) = 7.83, p = .020
Trust in Technology (TT)
Strong positive predictor of BI
Not specified
β = .52, p < .001
Technological Anxiety (TA)
Strong negative predictor of BI
Not specified
β = –.38, p < .001
Key Findings
MS patients and individuals with other chronic conditions show similar perceived usefulness, ease of use, behavioral intention, and social influence regarding digital health tools.
MS participants report significantly lower regular use of wearables compared to other chronic condition groups.
Trust in technology strongly predicts behavioral intention to use digital health applications in MS, while technological anxiety negatively impacts intention.
Perceived usefulness and ease of use contribute minimally to behavioral intention among MS patients.
Symptom severity in MS moderates acceptance pathways by weakening the effect of perceived ease of use and amplifying the negative impact of technological anxiety.
An intention–behavior gap exists in MS, indicating that positive intention does not consistently translate into actual technology use.
Clinical Implications
Digital health interventions for MS should prioritize building patient trust and reducing technological anxiety to enhance adoption. Designers and clinicians must consider symptom fluctuations that may impair ease of use and exacerbate anxiety, tailoring support accordingly. Addressing these emotional and disease-specific factors may bridge the gap between intention and actual use, improving engagement with digital health tools.
Conclusion
Emotional factors, particularly trust and anxiety, alongside symptom severity, play a pivotal role in digital health adoption among MS patients, surpassing traditional cognitive predictors. Integrating these elements into disease-specific acceptance models can guide the development of more effective digital health solutions for this population.
References
Multiple Sclerosis Research Consortium 2024 -- Emotional Factors and Disease-Specific Influences on Digital Health Adoption in Multiple Sclerosis
