Imperial College London

Professor Aldo Faisal

Faculty of EngineeringDepartment of Bioengineering

Professor of AI & Neuroscience
 
 
 
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Contact

 

+44 (0)20 7594 6373a.faisal Website

 
 
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Assistant

 

Miss Teresa Ng +44 (0)20 7594 8300

 
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Location

 

4.08Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Pieritz:2021:10.1145/3411764.3445523,
author = {Pieritz, S and Khwaja, M and Faisal, A and Matic, A},
doi = {10.1145/3411764.3445523},
pages = {1--12},
publisher = {ACM},
title = {Personalised recommendations in mental health Apps: the impact of autonomy and data sharing},
url = {http://dx.doi.org/10.1145/3411764.3445523},
year = {2021}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - 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.
AU - Pieritz,S
AU - Khwaja,M
AU - Faisal,A
AU - Matic,A
DO - 10.1145/3411764.3445523
EP - 12
PB - ACM
PY - 2021///
SP - 1
TI - Personalised recommendations in mental health Apps: the impact of autonomy and data sharing
UR - http://dx.doi.org/10.1145/3411764.3445523
UR - http://hdl.handle.net/10044/1/86835
ER -