JMIR Publications

ABSTRACT

Background:

The availability and use of health applications (apps) continues to increase, revolutionizing the way mobile health (mHealth) interventions are delivered. Apps are increasingly used to prevent disease and facilitate wellbeing, as well as to monitor and promote healthy behavior. On a similar rise is the incidence of skin cancers, primarily affecting fair-skinned, Caucasian populations. Much of the underlying risk can be prevented through behavioral change and adequate sun protection. Self-monitoring apps have the potential to facilitate prevention by reflecting on exposure to risks (e.g. sun intensity), and encourage protective behavior (e.g. seeking shade). Achieving that requires consumer acceptance and engagement, which often comes short.

Objective:

To assess healthcare consumer preferences for sun protection with a hypothetical self-monitoring app that tracks the duration and intensity of sun exposure and provides feedback on when and how to protect the skin. We explored preferences in the context of five pre-defined and modifiable app characteristics (attributes), as well as their variation across participant characteristics.

Methods:

We conducted an unlabeled discrete choice experiment (DCE) with eight unique choice tasks, each requesting participants to choose among two app alternatives. Both app alternatives consisted of five pre-identified two-level attributes. Attribute and level identification resulted from a multi-step and multi-stakeholder qualitative approach. Participant preferences, and thus, the relative importance of attributes and their levels were estimated using conditional logit modelling. Analyses consisted of 200 usable surveys, yielding 3196 observations.

Results:

Healthcare consumers strongly preferred automatic over manual self-monitoring (OR=2.37 [95% CI from 2.06 to 2.72], no cost over a single payment of 3 CHF (OR=1.72 [95% CI from 1.49 to 1.99]), sharing their generated data with a healthcare provider of their choice over not having that option (OR=1.66 [95% CI from 1.40 to 1.97]), repeated user consents whenever app data are shared with commercial thirds over a single consent (OR=1.57 [95% CI from 1.31 to 1.88]), and customizable over non-customizable reminders OR=1.30 [95% CI, 1.09-1.54]). The attribute of self-monitoring method significantly interacted with sex and perceived personal usefulness of health apps, suggesting that female sex and lower perceived usefulness are associated with relatively weaker preferences for automatic self-monitoring.

Conclusions:

We found that a preference- and user-sensitive self-monitoring app for sun protection should be simple and adjustable, with minimal effort, time or expense requirements, as well as be interoperable and have thorough and transparent privacy infrastructure. Similar features might be desirable for preventive health apps in other areas, paving the way for future DCE’s. Nonetheless, to fully understand these preferences dynamics, further qualitative or mixed-method research on mobile self-monitoring-based sun protection, and broader preventive mobile self-monitoring is required.