VIVID Brain | Designing Medication Guidance Strategies for DTx
Designing medication guidance strategies for digital therapeutics based on psychographics
VR
User Research
What is VIVID Brain?
Contributors
Understanding
High medication adherence is one of the most crucial factors for maximizing therapeutic effectiveness.
Especially in the case of Digital Therapeutics (DTx), adherence plays a much more significant role than in drug therapies, as the meaning of the dose-response relationship is limited. This is ultimately an issue directly tied to the usability of DTx.
Therefore, even if therapeutic effects are demonstrated in clinical trials, there is a possibility that such effects may not be replicated in real everyday life. While conventional drug therapy simply requires taking medication, treatment leveraging digital products can face larger adherence problems.
Particularly, NuNav Vision has been increasingly facing adherence issues because, due to the nature of the product, users must not only use a smartphone but also wear a VR headset.
In fact, the adherence rate in clinical trials was only 33% and to address this, we aimed to design a medication guidance strategy.
* Dose-response relationship: Observing how the response changes as the drug dosage increases.
How can we design effective medication guidance?
To design effective medication guidance, it is crucial to accurately understand how patients comprehend and perceive information, as well as what information they desire.
Among various methods, we utilized psychographics theory, which helps to better understand the intrinsic aspects of behavior.
In this process, research was conducted with a focus on the health lifestyle of the user group, based on the characteristic that our user group, Newnap Vision, comprises healthcare consumers.
Research
Overview
Participants
For 46 patients participating in the clinical trial
Research type
The survey was conducted in two phases. The first phase consisted of questions about the user's healthy lifestyle based on the Psychographics' A.I.O methodology.
The second phase was conducted to understand medical service utilization behavior by lifestyle type, and the Chi-square test was used to identify differences between variables in each cluster.
Interpretation
Phase 1
Clustering
Cluster analysis was conducted using the SPSS program based on the average scores of each item in the first survey.
The analysis results classified three clusters, each with sample sizes of 12, 18, and 16. These clusters were formed to have relatively equal sample sizes, making them suitable for representing each cluster.
Phase 2 -
Factor analysis
First Survey - Health Lifestyle by Cluster
✦ Cluster 1 is a group that, including a single item, generally shows relatively low scores compared to other groups. Notably, it scores very low in 'health management habits' and 'commitment to health'.
✦ Cluster 2 is the group that displays the most average scores. The scores for individual 'health values' items vary greatly, but they tend to be somewhat low in 'health management habits' and 'commitment to health'.
✦ Cluster 3 is the group with the highest average scores among the three clusters. This group shows high scores in 'health values' as well as relatively high scores in 'health management habits', 'interest in health management', and 'commitment to health'.
Second Survey - Healthcare Service Usage Patterns by Cluster
✦ Cluster 1 prioritizes trust in treatment efficacy when choosing healthcare services. Additionally, they prefer taking medications like antibiotics or painkillers when sick.
✦ Cluster 2 considers the expertise and reputation of the medical institution most important when selecting healthcare services. This cluster also prefers taking medications like antibiotics or painkillers when they are ill.
✦ Cluster 3 also values the expertise and reputation of the medical institution highly when choosing healthcare services. However, this group tends to prefer alternative therapies or taking rest over taking medications like painkillers when unwell.
Ideation
Phase 1
User Segments Modeling
After the analysis, we conducted workshops with team members to define the characteristics of each cluster, modeling user types.
The user types were categorized as Health Unconcerned, Weak-Willed, and Health Sensitive. We aimed to understand users by creating stories based on the characteristics of each type.
Phase 2
Service Communication Voice & Tone
Afterward, a text guideline was drafted according to each type's characteristics.
Voice and tone
Usage and grammar guidelines
Preferred sentence structure and style
Desired types of visual materials
In digital services, the 'linguistic elements' are crucial for interaction with users and have a direct impact on satisfaction with medication instructions.
When a service extends a friendly greeting and receives positive and gentle feedback from the channel, users can become more engaged and successfully complete tasks. Conversely, if the service behaves unexpectedly or not logically, users may feel frustrated or disappointed.
Even if similar functions and content are provided, the way communication is handled can significantly alter the relationship with the user, closely linked to the intimacy and trust with the service.
Furthermore, how, by whom, and in what manner medication guidance is provided can change a patient's adherence to medication. Therefore, text guidelines have been adapted for different user types to enhance medication compliance for users.
Phase 3
Instruction Strategy
Commercial products are recommended to conduct training more than 5 days a week.
Therefore, taking more than 3 days of rest indicates low compliance, and based on this, the medication guidance has been designed around 3 days.
The communication channels consist of 3 types: App push notifications, SMS, and ARS. The sending schedule varies for each channel,
and the content is tailored according to the user type.
IMPACT
세계 최초 뇌졸중 시야장애 DTx 상용화 성공
복약지도 및 순응도 관리를 통해 임상시험을 무사히 마치고 24년 4월 세계 최초로 뇌졸중 시야장애 디지털 치료제 상용화에 성공했습니다.