JMIR Publications

ABSTRACT

Background:

There is increasing interest in the potential uses of mobile technologies such as wearable biosensors to supplement the care of people with neurological conditions, but adherence is low, especially over long periods. If people are to benefit from these resources, we need a better long-term understanding of what influences patient engagement. Previous research suggests a several barriers and facilitators moderate engagement, but their relative importance is unknown.

Objective:

To elicit preferences and relative importance of user-generated factors influencing engagement with mobile technologies for two common neurological conditions: multiple sclerosis (MS) or epilepsy.

Methods:

People with a diagnosis of MS (n=140) or epilepsy (n=163) were asked to select their preferred technology from a series of eight vignettes containing four characteristics at different levels: privacy, clinical support, established benefit and device accuracy in a discrete choice experiment (DCE). These characteristics had previously been emphasised by people with MS and or epilepsy as influencing engagement with technology. Mixed multinomial logistic regression models were used to establish which characteristics were most likely to affect engagement. Sub-group analyses explored the effects of demographic factors (such as age, gender and education), acceptance of and familiarity with mobile technology, neurological diagnosis (MS or epilepsy) and symptoms that could influence motivation (such as depression).

Results:

Analysis of the DCE responses validated previous qualitative findings that a higher level of privacy, greater clinical support, increased perceived benefit and better device accuracy are important to people with a neurological condition. Accuracy was perceived as the most important factor, followed by privacy. Clinical support was the least valued of the attributes. People were prepared to trade a modest amount of accuracy to achieve an improvement in privacy, but less likely to make this compromise for other factors. The type of neurological condition (epilepsy or MS) did not influence these preferences, nor did the age, gender, or mental health status of the participants. Those who were less accepting of technology were the most concerned about privacy and those with a lower level of education were prepared to trade accuracy for more clinical support.

Conclusions:

For people with neurological conditions such as epilepsy and MS, accuracy, i.e. the ability to detect symptoms, is of the greatest interest. However, there are individual differences and people who are less accepting of technology may need far greater reassurance about data privacy and people with lower levels of education value greater clinician involvement. These patient preferences should be considered when designing mobile technologies.