Exploring and Designing for Memory Impairments in Depression
Citation:
Qu, C., Sas, C., Doherty, G., Exploring and Designing for Memory Impairments in Depression, CHI '19 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, Scotland, May 04 - 09, 2019Abstract:
Depression is an affective disorder with distinctive autobiographical memory impairments, including negative bias, overgeneralization and reduced positivity. Several clinical therapies address these impairments, and there is an opportunity to develop new supports for treatment by considering depression-associated memory impairments within design. We report on interviews with ten experts in treating depression, with expertise in both neuropsychology and cognitive behavioral therapies. The interviews explore approaches for addressing each of these memory impairments. We found consistent use of positive memories for treating all memory impairments, the challenge of direct retrieval, and the need to support the experience of positive memories. We aim to sensitize HCI researchers to the limitations of memory technologies, broaden their awareness of memory impairments beyond episodic memory recall, and inspire them to engage with this less explored design space. Our findings open up new design opportunities for memory technologies for depression, including positive memory banks for active encoding and selective retrieval, novel cues for supporting generative retrieval, and novel interfaces to strengthen the reliving of positive memories.
Sponsor
Grant Number
Marie Curie
722022
Science Foundation Ireland (SFI)
12/CE/I2267
Author's Homepage:
http://people.tcd.ie/gdohertyDescription:
PUBLISHED
Author: Doherty, Gavin
Sponsor:
Marie CurieScience Foundation Ireland (SFI)
Other Titles:
ACM Conference on Human Factors in Computing Systems (CHI 2019)Publisher:
ACMType of material:
Conference PaperCollections
Availability:
Full text availableKeywords:
Depression, Memory impairment, Memory technologies, CuesSubject (TCD):
Digital Engagement , Human-Computer InteractionDOI:
https://doi.org/10.1145/3290605.3300740Metadata
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