Personalised Recommendations in Mental Health Apps: The Impact of Autonomy and Data Sharing

TL;DR

This study investigates how autonomy and data sharing influence user preferences and engagement in mental health apps, revealing a discrepancy between expressed preferences and actual usage patterns.

Contribution

It provides novel insights into the effects of autonomous experience and data sharing preferences on engagement in personalized mental health app recommendations.

Findings

Users prefer personalized guidance but engage more with autonomous choices.

Sharing questionnaire data does not significantly impact app usage.

A mix of autonomy and recommendations enhances user engagement.

Abstract

The recent growth of digital interventions for mental well-being prompts a call-to-arms to explore the delivery of personalised recommendations from a user's perspective. In a randomised placebo study with a two-way factorial design, we analysed the difference between an autonomous user experience as opposed to personalised guidance, with respect to both users' preference and their actual usage of a mental well-being app. Furthermore, we explored users' preference in sharing their data for receiving personalised recommendations, by juxtaposing questionnaires and mobile sensor data. Interestingly, self-reported results indicate the preference for personalised guidance, whereas behavioural data suggests that a blend of autonomous choice and recommended activities results in higher engagement. Additionally, although users reported a strong preference of filling out questionnaires instead of sharing their mobile data, the data source did not have any impact on the actual app use. We discuss the implications of our findings and provide takeaways for designers of mental well-being applications.