Name
Abstract | ||
|---|---|---|
The efficacy of behavioural activation in the treatment of major depressive disorders has been established in a number of studies over the last four decades. Although a number of recent studies show that behavioural activation administered via a smartphone application has the potential to be effective in the treatment of depression, these opportunities are tempered by the problem that these interventions have high dropout rates. However, recent research finds that personalisation of content can positively influence engagement. We present MindTick, a smartphone-based behavioural activation application using a recommender system to deliver personalized content to encourage users to engage in behavioural activation activities.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3341162.3343785 | Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers |
Keywords | Field | DocType |
LinUCB, Mhealth, behavioral activation, recommender system | Recommender system,Psychological intervention,Behavioral activation,Computer science,mHealth,Human–computer interaction,Personalization,Embedded system | Conference |
ISBN | Citations | PageRank |
978-4503-6869-8 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Zhang | 1 | 220 | 69.03 |
| Geoff Jarrad | 2 | 1 | 0.72 |
| Susan A. Murphy | 3 | 136 | 15.39 |
| Niranjan Bidargaddi | 4 | 0 | 1.01 |