JMIR Publications

ABSTRACT

Background:

eHealth can revolutionize the way self-management support is offered to chronically-ill individuals such as those with a cardiovascular disease (CVD). However, the patients’ fluctuating motivation to actually perform self-management is an important factor to account for. Tailoring and personalizing eHealth to fit with the values of individuals promises to be an effective motivational strategy. There is already empirical knowledge about the values of importance for patients with a CVD, and there are also numerous examples of eHealth technologies. Nevertheless, how specific eHealth technologies and design features could potentially contribute to values of individuals with a CVD has not been explicitly studied before.

Objective:

The present study seeks to connect a set of empirically-validated health related values of individuals with a CVD with existing eHealth technologies and their design features. The study searches for potential connections between design features and values with the goal to advance knowledge about how eHealth technologies can actually be more meaningful and motivating for end users.

Methods:

Undertaking a technical investigation that fits with the value sensitive design framework, a content analysis of existing eHealth technologies was conducted. Eleven empirically-validated values of CVD patients were matched to 70 design features from 10 eHealth technologies that were previously identified in a systematic review. The analysis consisted mainly of a deductive coding stage performed independently by three members of the study team. In addition, researchers and developers of 6 out of the 10 reviewed technologies were contacted and provided input about potential feature-value connections.

Results:

In total, 98 connections were made between eHealth design features and patient values. This meant that some design features could contribute to multiple values. Importantly, some values were more often addressed than others. CVD patients’ values most often addressed were related to 1) having or maintaining a healthy lifestyle, 2) having an overview of personal health data, 3) having reliable information and advice, 4) having extrinsic motivators to accomplish goals or health-related activities, and 5) receiving personalized care. In contrast, values that were less often addressed concerned 6) perceiving low thresholds to access health care, 7) receiving social support, 8) preserving a sense of autonomy over life, and 9) not feeling fear, anxiety, or insecurity about health. Lastly, two largely unaddressed values were related to 10) having confidence and self-efficacy in the treatment or ability to achieve goals and 11) desiring to be seen as a person rather than a patient.

Conclusions:

Positively, existing eHealth technologies could be connected to CVD patients’ values, largely through design features that relate to educational support, self-monitoring support, behavior change support, feedback, and motivational incentives. Other design features such as reminders, prompts or cues, peer-based and expert-based human support, and general system personalization were also connected to values but in more narrow ways. The present study advanced knowledge about the potential of value sensitive eHealth technologies and design features. In future studies, the inferred feature-value connections must be validated with empirical data, which could contribute to formal theories that explain how eHealth can support the values of individuals with a CVD or similar chronic conditions.