@inproceedings{
 title = {POLYHYMNIA Mood-Empowering people to cope with depression through music listening},
 type = {inproceedings},
 year = {2021},
 keywords = {Depression,Health Intervention,Machine Learning,Mood Regulation,Music Listening,Web App},
 pages = {188-193},
 publisher = {ACM},
 city = {Virtual, USA},
 id = {ab00675a-b93c-34d7-9e06-2cbce52968cb},
 created = {2021-08-31T11:17:11.812Z},
 file_attached = {true},
 profile_id = {ffa9027c-806a-3827-93a1-02c42eb146a1},
 last_modified = {2024-03-28T16:00:11.221Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {CoutinhoPolyhymnia2021},
 private_publication = {false},
 abstract = {Depression is one of the largest sources of burden of disease in the worldwide and the development of flexible, timely and easily accessible interventions is considered to be a critical direction for the future. Mood Regulation (MR) via music listening may be a viable tool support these aims if people have adequate support to make music selections that underpin healthy MR strategies. We developed a new app (POLYHYMNIA Mood) that automatically generates personalised music playlists for mood elevation and the reduction of depression symptoms and here we provide an overview of POLYHYMNIA Mood and report the results of a preliminary evaluation of its effectiveness and acceptability. Results show that listening to POLYHYMNIA Mood playlists over a period of 4 weeks led to a large reduction in negative affect and a clinically significant reduction in depression symptoms. Whereas these results should be interpreted cautiously due to the small sample size and the lack of control conditions, they provide strong support to our approach.},
 bibtype = {inproceedings},
 author = {Coutinho, Eduardo and Alshukri, Ayesh and De Berardinis, Jacopo and Dowrick, Chris},
 doi = {10.1145/3460418.3479334},
 booktitle = {UbiComp/ISWC 2021 - Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers}
}

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