Wearable digital health technologies (DHTs) have the potential to improve chronic kidney disease (CKD) management through patient engagement. This study aimed to investigate and elicit preferences of individuals with CKD toward wearable DHTs designed to support self-management of their condition.

Using the results of our review of the published literature and after conducting qualitative patient interviews, five-choice attributes were identified and included in a discrete-choice experiment. The design consisted of 10-choice tasks, each comprising two hypothetical technologies and one opt-out scenario. We collected data from 113 adult patients with CKD stages 3–5 not on dialysis and analyzed their responses via a latent class model to explore preference heterogeneity.

Two patient segments were identified. In all preference segments, the most important attributes were the device appearance, format, and type of information provided. Patients within the largest preference class (70 percent) favored information provided in any format except the audio, while individuals in the other class preferred information in text format. In terms of the style of engagement with the device, both classes wanted a device that provides options rather than telling them what to do.

Our analysis indicates that user preferences differ between patient subgroups, supporting the case for offering a different design of the device for different patients’ strata, thus moving away from a one-size-fits-all service provision. Furthermore, we showed how to leverage the information from user preferences early in the R&D process to inform and support the provision of nuanced person-centered wearable DHTs.

Adherence to injectable disease-modifying treatments in patients with multiple sclerosis (MS) impacts outcomes and can be influenced by perceptions of treatment efficacy, side effects, injection frequency, and the duration of injection. This study aimed to quantify preferences for selected attributes of injectable treatments among individuals with MS in the United Kingdom and France.

Respondents with a self-reported diagnosis of MS completed an online discrete-choice-experiment survey, consisting of a series of treatment-choice questions. Each choice question presented two hypothetical treatments, each with six attributes (years until disability progression, relapses in the next 4 years, injection time, injection frequency, flu-like symptoms (FLS), and injection-site reactions), each with various levels. Mixed-logit regression analysis was used to estimate preference weights for attribute levels and to calculate the relative importance of changes in treatment attributes (vertical distance between preference weights). Minimum acceptable efficacy estimates indicate improvement in efficacy that respondents would require in exchange for worsening injection frequency and FLS.

In both countries, 100 respondents completed the survey. In the United Kingdom and France, respectively, improving the time until disability progression from 2 to 4 years, reducing injection frequency from “daily” to “every 2 weeks”, and reducing FLS from 3 days after every injection to none had a relative importance of 2.9 and 2.6, 3.0 and 3.5, and 2.5 and 3.1. Given the ranges included in the study, changes in these attributes were more important than most changes in other attributes assessed.

Reductions in the injection frequency of MS treatments and FLS can be as important to patients as improvements in treatment efficacy.