Rights statement: © ACM, 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in PervasiveHealth '17 Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare http://dx.doi.org/10.1145/3154862.3154877
Accepted author manuscript, 584 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Computing and mental health
T2 - 11th EAI International Conference on Pervasive Computing Technologies for Healthcare
AU - Ferrario, Maria Angela Felicita Cristina
AU - Simm, William Alexander
AU - Gradinar, Adrian Ioan
AU - Smith, Ian Craig
AU - Forshaw, Stephen
AU - Smith, Marcia Tavares
AU - Whittle, Jonathan Nicholas David
N1 - © ACM, 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in PervasiveHealth '17 Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare http://dx.doi.org/10.1145/3154862.3154877
PY - 2017/5/23
Y1 - 2017/5/23
N2 - Automated passive sensing applications and self-reported smart diaries seem to hold promise for the management of anxiety in autism and other mental health conditions. However, passive sensing often struggles with noisy data, ambiguous feedback and weak user agency over the device, whilst self-reporting relies on user-entered data which can be time consuming and cognitively demanding. To address these limitations, we explore a different approach, whereby individuals consciously actuate personal data capture and are in control of it at all times; yet, the interaction solely involves clicking a button, thus avoiding cognitive overload whilst supporting immediate reflection. We call this approach intentive computing. Through our initial investigations we found that conscious interactions cannot only provide real-time relief in anxiety management, but can also function as memory anchors irrespective of the content captured and even prior to data visualization
AB - Automated passive sensing applications and self-reported smart diaries seem to hold promise for the management of anxiety in autism and other mental health conditions. However, passive sensing often struggles with noisy data, ambiguous feedback and weak user agency over the device, whilst self-reporting relies on user-entered data which can be time consuming and cognitively demanding. To address these limitations, we explore a different approach, whereby individuals consciously actuate personal data capture and are in control of it at all times; yet, the interaction solely involves clicking a button, thus avoiding cognitive overload whilst supporting immediate reflection. We call this approach intentive computing. Through our initial investigations we found that conscious interactions cannot only provide real-time relief in anxiety management, but can also function as memory anchors irrespective of the content captured and even prior to data visualization
KW - Human Agency
KW - Human Data Interaction
KW - Participatory Design
KW - Autism
KW - Anxiety
KW - Mental Health
U2 - 10.1145/3154862.3154877
DO - 10.1145/3154862.3154877
M3 - Conference contribution/Paper
SN - 9781450363631
SP - 1
EP - 10
BT - PervasiveHealth '17 Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare
PB - ACM
CY - New York
Y2 - 23 May 2017 through 26 May 2017
ER -