Upload
others
View
2
Download
0
Embed Size (px)
Citation preview
Personal Informatics in Interpersonal Contexts:Towards the Design of Technology that Supports the Social Ecologies of Long-Term Mental Health Management
Elizabeth Murnane, Tara Walker, Beck Tench, Stephen Voida, Jaime Snyder
CSCW | November 6, 2018
Serious mental illness (SMI) affects
1 in 4 people in the world at some point in their lives
(World Health Organization, 2018)
!2
Bipolar Disorder (BD)
Fluctuations in • mood • energy • activity
!3
People facing SMI are adapting off-the-shelf
personal informatics tools as part of condition management
Tracking everyday activities improves outcomes and minimizes symptoms
!4
People facing SMI are adapting off-the-shelf
personal informatics tools as part of condition management
Tracking everyday activities improves outcomes and minimizes symptoms
!5
Personal Informatics, Quantified
Self
tracking reflection knowledge experimentation improvement
self-{
Personal informatics grew from an individual-centric orientation
!6
Personal Informatics, Quantified
Self
tracking reflection knowledge experimentation improvement
self-{
Personal informatics grew from an individual-centric orientation
!7
Data practices are • Socially motivated • Collaboratively conducted • Embedded in interpersonal contexts
We need to more explicitly and holistically consider the sociotechnical dimensions of personal health management
!8
We focus on the “long-tail” of self-management
• Ad-hoc, vernacular practices • Potentially outside of clinical oversight • Long-term • Flux-prone
!9
We focus on the “long-tail” of self-management
• Ad-hoc, vernacular practices • Potentially outside of clinical oversight • Long-term • Flux-prone
!10
—— A
UNI
VERS
ITY O
F CO
LORA
DO R
ESEA
RCH
STUD
Y ——
At least 18-years-old and a close family member orfriend of an individual diagnosed with bipolar
Focus groups will be held on the CU Boulder campus and at other community meeting locations in and around the Boulder area.
You’ll be paid $10 per hour. We expect the focus groups to take approximately 2 hours.
A with individuals with bipolardisorder and their close family members and friends: Discuss your with bipolar disorder, your attitude toward self-tracking and technology, and how bipolar disorder shapes (or doesn’t shape)
Emailing [email protected]
Because people need and deserve tools that better , ,and bipolar disorder.
—— A UNIVERSITY OF WASHINGTON RESEARCH STUDY ——
At least 18-years-old, diagnosed with bipolar, and haven’t been hospitalized in the last six months.
Interviews will be at the University of Washington.
You’ll be paid $25 for each interview, for a total of $75.You’ll also receive $5 at each interview for travel costs.
A series of this summer:
Discuss your experience with bipolar.
Draw, brainstorm, and play with ways to express your experience visually.
Give feedback on a series of images the research team comes up with.
Setup a or learn more by:• Calling 206-616-1094, or• Visiting http://blogs.uw.edu/bpstudy/
Because people need and deserve tools that better , ,and bipolar.
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
• Boulder area • N=8
• Individuals with BD & stakeholders
• Focus groups
• Seattle area
• N=14 • Individuals with BD • 1-on-1 in-person
interviews
Complimentary studies across 2 sites
!11
—— A
UNI
VERS
ITY O
F CO
LORA
DO R
ESEA
RCH
STUD
Y ——
At least 18-years-old and a close family member orfriend of an individual diagnosed with bipolar
Focus groups will be held on the CU Boulder campus and at other community meeting locations in and around the Boulder area.
You’ll be paid $10 per hour. We expect the focus groups to take approximately 2 hours.
A with individuals with bipolardisorder and their close family members and friends: Discuss your with bipolar disorder, your attitude toward self-tracking and technology, and how bipolar disorder shapes (or doesn’t shape)
Emailing [email protected]
Because people need and deserve tools that better , ,and bipolar disorder.
—— A UNIVERSITY OF WASHINGTON RESEARCH STUDY ——
At least 18-years-old, diagnosed with bipolar, and haven’t been hospitalized in the last six months.
Interviews will be at the University of Washington.
You’ll be paid $25 for each interview, for a total of $75.You’ll also receive $5 at each interview for travel costs.
A series of this summer:
Discuss your experience with bipolar.
Draw, brainstorm, and play with ways to express your experience visually.
Give feedback on a series of images the research team comes up with.
Setup a or learn more by:• Calling 206-616-1094, or• Visiting http://blogs.uw.edu/bpstudy/
Because people need and deserve tools that better , ,and bipolar.
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
206-
616-
1094
BPST
UDY@
UW.ED
UBL
OGS.U
W.ED
U/BP
STUD
Y
• Boulder area • N=8
• Individuals with BD & stakeholders
• Focus groups
• Seattle area
• N=14 • Individuals with BD • 1-on-1 in-person
interviews
Complimentary studies across 2 sites
!12
• Characterize relations and roles
• Formalize this social ecology
• Prosthelytize about design
Contributions
!13
• Characterize relations and roles
• Formalize this social ecology
• Prosthelytize about design
Contributions
!14
• Characterize relations and roles
• Formalize this social ecology
• Prosthelytize about design
Contributions
!15
• Characterize relations and roles
• Formalize this social ecology
• Prosthelytize about design
Contributions
!16
• Characterize relations and roles
• Formalize this social ecology
• Prosthelytize about design
Contributions
!17
!18
Bronfenbrenner’s Ecological Systems Theory (EST)
INDIVIDUAL
(sex, age, health, etc.)
MICROSYSTEM
MESOSYSTEM
EXOSYSTEM
MACROSYSTEM
Attitudes and ideologies of the culture
Social services
Neighbors
Local politics
Mass media
Industry
Family Peers
ChurchSchool
Health services
!19
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
• Individual managing SMI
• Demographics
• Condition characteristics
!20
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influencesIdeologies
Workplaces Schools
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Societalnorms
Governmentpolicies
Economictrends
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MICROLAYERClosely involved ties
Person with SMI
Family Friends
groupsgivers
Person with SMI
Care SupportHarmful • Dissatisfactory care
• Denial, shame, rejection
• Toxic, triggering influences
Helpful
• Tracking support • Emotional support • Monitoring
• Intervening
!21
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influencesIdeologies
Workplaces Schools
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Societalnorms
Governmentpolicies
Economictrends
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MICROLAYERClosely involved ties
Person with SMI
Family Friends
groupsgivers
Person with SMI
Care SupportHarmful • Dissatisfactory care
• Denial, shame, rejection
• Toxic, triggering influences
Helpful
• Tracking support • Emotional support • Monitoring
• Intervening
!22
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influencesIdeologies
Workplaces Schools
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Societalnorms
Governmentpolicies
Economictrends
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MICROLAYERClosely involved ties
Person with SMI
Family Friends
groupsgivers
Person with SMI
Care Support
Helpful
• Tracking support • Emotional support • Monitoring
• Intervening
Harmful • Dissatisfactory care
• Denial, shame, rejection
• Toxic, triggering influences
!23
Exo layer
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influencesIdeologies
Workplaces Schools
Communityorganizations
Healthinsurers
Societalnorms
Governmentpolicies
Economictrends
Person with SMI
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
Ideologies
Societalnorms
Governmentpolicies
Economictrends
Aiding & obstructing
• Financial, instrumental, and emotional needs
• Fear of being “found out” as having SMI
• Health insurance a consistent concern
!24
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influencesIdeologies
Workplaces Schools
Communityorganizations
Healthinsurers
Societalnorms
Governmentpolicies
Economictrends
Person with SMI
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
Ideologies
Societalnorms
Governmentpolicies
Economictrends
Aiding & obstructing
• Financial, instrumental, and emotional needs
• Fear of being “found out” as having SMI
• Health insurance a consistent concern
!25
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Ideologies
Workplaces Schools
Family Friends
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Person with SMI
EXOLAYERIndirect institutional influences
Workplaces Schools
Communityorganizations
Healthinsurers
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
Person with SMI
• Stigma & identity
• Tendency to conceal • Shedding societal
attitudes & accepting oneself
!26
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Ideologies
Workplaces Schools
Family Friends
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Person with SMI
EXOLAYERIndirect institutional influences
Workplaces Schools
Communityorganizations
Healthinsurers
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
Person with SMI
• Stigma & identity
• Tendency to conceal • Shedding societal
attitudes & accepting oneself
!27
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
Person with SMI
EXOLAYERIndirect institutional influences
Workplaces Schools
Communityorganizations
Healthinsurers
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
PROPERTIES
Relational & mediating roles of personal data
INTERACTIONPROPERTIES
INTERACTIONPROPERTIES
MACROLAYERSociocultural context
Ideologies
Societalnorms
Governmentpolicies
Economictrends
• Biological, psychological, and social fluctuations inherent to BD
• Transitional experiences
• SMI linked to more frequent, extreme, irrevocable changes
!28
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
Person with SMI
EXOLAYERIndirect institutional influences
Workplaces Schools
Communityorganizations
Healthinsurers
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
INFORMATICS LAYER
Valence
Intensity
Direction
Dynamism
PROPERTIES
Relational & mediating roles of personal data
INTERACTIONPROPERTIES
INTERACTIONPROPERTIES
MACROLAYERSociocultural context
Ideologies
Societalnorms
Governmentpolicies
Economictrends
• Biological, psychological, and social fluctuations inherent to BD
• Transitional experiences
• SMI linked to more frequent, extreme, irrevocable changes
!29
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
Ideologies
Societalnorms
Governmentpolicies
Economictrends
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
EXOLAYERIndirect institutional influences
Workplaces Schools
Communityorganizations
Healthinsurers
TEMPORALLAYER
TEMPORALLAYER
Rhythms, life transitions, socio-historical events
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
• Informatics artifacts and data representations of self resemble a relation
• Analog and digital media facilitate engagement with proximal and peripheral layers
!30
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
Ideologies
Societalnorms
Governmentpolicies
Economictrends
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
EXOLAYERIndirect institutional influences
Workplaces Schools
Communityorganizations
Healthinsurers
TEMPORALLAYER
TEMPORALLAYER
Rhythms, life transitions, socio-historical events
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
!31
• Informatics artifacts and data representations of self resemble a relation
• Analog and digital media facilitate engagement with proximal and peripheral layers
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
Ideologies
Societalnorms
Governmentpolicies
Economictrends
INFORMATICS LAYERRelational & mediating roles of personal data
TEMPORALLAYER
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
EXOLAYERIndirect institutional influences
Workplaces Schools
Communityorganizations
Healthinsurers
Person with SMI
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
• Richer conceptualization compared to EST’s mesosystem
!32
MACROLAYERSociocultural context
EXOLAYERIndirect institutional influences
MICROLAYERClosely involved ties
Person with SMI
Ideologies
Workplaces Schools
Family Friends
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
INFORMATICS LAYER
Communityorganizations
Healthinsurers
Care Supportgroups
Societalnorms
Governmentpolicies
Economictrends
givers
Valence
Intensity
Direction
Dynamism
INTERACTIONPROPERTIES
Relational & mediating roles of personal data
MACROLAYERSociocultural context
Ideologies
Societalnorms
Governmentpolicies
Economictrends
INFORMATICS LAYERRelational & mediating roles of personal data
TEMPORALLAYER
TEMPORAL
Rhythms, life transitions, socio-historical events
LAYER
EXOLAYERIndirect institutional influences
Workplaces Schools
Communityorganizations
Healthinsurers
Person with SMI
MICROLAYERClosely involved ties
Family Friends
Care Supportgroupsgivers
• Richer conceptualization compared to EST’s mesosystem
!33
Deeply supportive - moderately supportive - neutral/absent - irritating - abusive
Valence: positivity/negativity of a relationship
Intensity: weak/strength of a relation’s influenceTight during moments of crisis, relaxed during stable periods
Direction: who is impacting or being impactedUni-, bi-, or multi-directional influence on and of SMI at micro to macro levels
Dynamism: (in)stability of a relationshipFrom lifelong friends or entrenched cultural norms to employment turnover
!34
Deeply supportive - moderately supportive - neutral/absent - irritating - abusive
Valence: positivity/negativity of a relationship
Intensity: weak/strength of a relation’s influenceTight during moments of crisis, relaxed during stable periods
Direction: who is impacting or being impactedUni-, bi-, or multi-directional influence on and of SMI at micro to macro levels
Dynamism: (in)stability of a relationshipFrom lifelong friends or entrenched cultural norms to employment turnover
!35
Deeply supportive - moderately supportive - neutral/absent - irritating - abusive
Valence: positivity/negativity of a relationship
Intensity: weak/strength of a relation’s influenceTight during moments of crisis, relaxed during stable periods
Direction: who is impacting or being impactedUni-, bi-, or multi-directional influence on and of SMI at micro to macro levels
Dynamism: (in)stability of a relationshipFrom lifelong friends or entrenched cultural norms to employment turnover
!36
Deeply supportive - moderately supportive - neutral/absent - irritating - abusive
Valence: positivity/negativity of a relationship
Intensity: weak/strength of a relation’s influenceTight during moments of crisis, relaxed during stable periods
Direction: who is impacting or being impactedUni-, bi-, or multi-directional influence on and of SMI at micro to macro levels
Dynamism: (in)stability of a relationshipFrom lifelong friends or entrenched cultural norms to employment turnover
!37
!38
Designing new generations of tools that support the social ecologies of use
!39
•Accommodate accruing, breaking, and changing social ties
•Normative data representations can fuel scrutiny and inadequacy
•Self-tracking is about crisis mitigation and crisis management
!40
!41
•Accommodate accruing, breaking, and changing social ties
•Normative data representations can fuel scrutiny and inadequacy
•Self-tracking is about crisis mitigation and crisis management
!42
•Accommodate accruing, breaking, and changing social ties
•Normative data representations can fuel scrutiny and inadequacy
•Self-tracking is about crisis mitigation and crisis management
Advancing an emerging class of collective informatics systems
that support the social ecologies of long-term mental health management
Thank you! Questions?
Personal Informatics in Interpersonal Contexts: Towards the Design of Technology that Supports the Social Ecologies of Long-Term Mental Health Management
Elizabeth Murnane, Tara Walker, Beck Tench, Stephen Voida, Jaime Snyder