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Health Data: Representation and (In)visibility
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.ORCID iD: 0000-0001-5620-6305
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Health data requires context to be understood. I show how, by examining two areas: self-surveillance, with a focus on representation of bodily data, and mass-surveillance, with a focus on representing populations. I critically explore how Information and Communication Technology (ICT) can be made to represent individuals and populations, and identify implications of such representations. My contributions are: (i) the design of a self-tracking stress management system, (ii) the design of a mass-surveillance system based on mobile phone data, (iii) an empirical study exploring how users of a fitness tracker make sense of their generated data, (iv) an analysis of the discourse of designers of a syndrome surveillance system, (v) a critical analysis of the design process of a mass-surveillance system, and (vi) an analysis of the historicity of the concepts and decisions taken during the design of a stress management system. I show that producing health data, and subsequently the technological characteristics of algorithms that produce them depend on factors present in the ICT design process. These factors determine how data is made to represent individuals and populations in ways that may selectively make invisible parts of the population, determinants of health, or individual conception of self and wellbeing. In addition, I show that the work of producing data does not stop with the work of the engineers who produce ICT-based systems: maintenance is constantly required.

Abstract [sv]

För att förstå hälsodata krävs sammanhang. Jag visar hur detta kan erhållas, genom två fallstudier: en om självövervakning, med fokus på representation av kroppsdata, samt en om massövervakning, med fokus på representation av populationer. Jag granskar kritiskt hur informationsteknologi (IT) kan fås att representera såväl individer som populationer och vilka följder det får. Mina bidrag är: (i) utformningen av ett självövervakningssystem för stresshantering, (ii) utformningen av ett massövervakningssystem baserat på data från mobiltelefonanvändning, (iii) en empirisk studie av hur användare av en hälsosensor begriper det data som sensorn genererar, (iv) en diskursiv analys av hur syndromövervakningssystem utformas, (v) en kritisk analys av processer kring att utforma ett massövervakningssystem, samt (vi) en analys av den historiska korrektheten i begrepp och beslutsfattande i samband med utformningen av ett stresshanteringssystem. Jag visar att produktion av hälsodata, liksom tekniska beskrivningar av de algoritmer som används i den processen, beror av faktorer som hänger samman med IT-utformningsprocessen. Dessa faktorer avgör sedan hur data kan fås att representera individer och populationer på sätt som kan rendera delar av en population, hälsodeterminanter, eller individens självuppfattning och förståelse av välmående osynliga. Jag visar också att arbetet med att producera data inte är avslutat i och med det ingenjörsarbete som krävs för att IT-systemen ska byggas: konstant underhåll krävs också.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. , 61 p.
Series
TRITA-ICT-ECS AVH, ISSN 1653-6363 ; 14:17
Series
SICS Dissertation Series, ISSN 1101-1335 ; 72
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-158909ISBN: 978-91-7595-403-5 (print)OAI: oai:DiVA.org:kth-158909DiVA: diva2:779968
Public defence
2015-01-29, Sal B, Electrum, KTH-ICT, Isafordsgatan 16, Kista, 14:00 (English)
Opponent
Supervisors
Note

QC 20150114

Available from: 2015-01-14 Created: 2015-01-13 Last updated: 2015-03-03Bibliographically approved
List of papers
1. Mind the body!: designing a mobile stress management application encouraging personal reflection
Open this publication in new window or tab >>Mind the body!: designing a mobile stress management application encouraging personal reflection
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2010 (English)In: Proceedings of the 8th ACM conference on designing interactive systems, 2010, 47-56 p.Conference paper, Published paper (Refereed)
Abstract [en]

We have designed a stress management biofeedback mobile service for everyday use, aiding users to reflect on both positive and negative patterns in their behavior. To do so, we embarked on a complex multidisciplinary design journey, learning that: detrimental stress results from complex processes related to e.g. the subjective experience of being able to cope (or not) and can therefore not be measured and diagnosed solely as a bodily state. We learnt that it is difficult, sometimes impossible, to make a robust analysis of stress symptoms based on biosensors worn outside the laboratory environment they were designed for. We learnt that rather than trying to diagnose stress, it is better to mirror short-term stress reactions back to them, inviting their own interpretations and reflections. Finally, we identified several experiential qualities that such an interface should entail: ambiguity and openness to interpretation, interactive history of prior states, fluency and aliveness.

Keyword
16, 27, 28, acknowledged that long-term stress, and what to do, biosensors, can lead to chronic, difficult to know when, illnesses, interactional empowerment, it is, stress, such as cardiovascular problems, the limit is reached, wearability
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-158903 (URN)10.1145/1858171.1858182 (DOI)2-s2.0-78149355233 (Scopus ID)
Conference
8th ACM Conference on Designing Interactive Systems, DIS 2010; Aarhus; Denmark; 16 August 2010
Note

QC 20150114

Available from: 2015-01-13 Created: 2015-01-13 Last updated: 2016-12-18Bibliographically approved
2. Knowing Your Population: Privacy-Sensitive Mining of Massive Data
Open this publication in new window or tab >>Knowing Your Population: Privacy-Sensitive Mining of Massive Data
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2013 (English)In: Network and Communication Technologies, ISSN 1927-064X, Vol. 2, no 1, 34-51 p.Article in journal (Refereed) Published
Abstract [en]

Location and mobility patterns of individuals are important to environmental planning, societal resilience, public health, and a host of commercial applications. Mining telecommunication traffic and transactions data for such purposes is controversial, in particular raising issues of privacy. However, our hypothesis is that privacy-sensitive uses are possible and often beneficial enough to warrant considerable research and development efforts. Our work contends that peoples’ behavior can yield patterns of both significant commercial, and research, value. For such purposes, methods and algorithms for mining telecommunication data to extract commonly used routes and locations, articulated through time-geographical constructs, are described in a case study within the area of transportation planning and analysis. From the outset, these were designed to balance the privacy of subscribers and the added value of mobility patterns derived from their mobile communication traffic and transactions data. Our work directly contrasts the current, commonly held notion that value can only be added to services by directly monitoring the behavior of individuals, such as in current attempts at location-based services. We position our work within relevant legal frameworks for privacy and data protection, and show that our methods comply with such requirements and also follow best-practices.

Place, publisher, year, edition, pages
Canadian Center of Science and Education, 2013
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-139379 (URN)10.5539/nct.v2n1p34 (DOI)
Note

QC 20140114

Available from: 2014-01-10 Created: 2014-01-10 Last updated: 2015-01-14Bibliographically approved
3. Sensemaking in Intelligent Data Analytics
Open this publication in new window or tab >>Sensemaking in Intelligent Data Analytics
2015 (English)In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987Article in journal (Refereed) Epub ahead of print
Abstract [en]

A systemic model for making sense of health data is presented, in which networked foresight complements intelligent data analytics. Data here serves the goal of a future systems medicine approach by explaining the past and the current, while foresight can serve by explaining the future. Anecdotal evidence from a case study is presented, in which the complex decisions faced by the traditional stakeholder of results—the policymaker—are replaced by the often mundane problems faced by an individual trying to make sense of sensor input and output when self-tracking wellness. The conclusion is that the employment of our systemic model for successful sensemaking integrates not only data with networked foresight, but also unpacks such problems and the user practices associated with their solutions.

Keyword
Artificial intelligence Massive data Health data Intelligent data analytics Syndromic surveillance Sensemaking
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-158906 (URN)10.1007/s13218-015-0349-0 (DOI)
Note

QP 2015

Available from: 2015-01-13 Created: 2015-01-13 Last updated: 2017-12-05Bibliographically approved
4. Detecting the Visible: The Discursive Construction of Health Threats in a Syndromic Surveillance System Design
Open this publication in new window or tab >>Detecting the Visible: The Discursive Construction of Health Threats in a Syndromic Surveillance System Design
2014 (English)In: Societies, ISSN 2075-4698, Vol. 4, no 3, 399-413 p.Article in journal (Refereed) Published
Abstract [en]

Information and communication technologies are not value-neutral tools that reflect reality; they privilege some forms of action, and they limit others. We analyze reports describing the design, development, testing and evaluation of a European Commission co-funded syndromic surveillance project called SIDARTHa (System for Information on Detection and Analysis of Risks and Threats to Health). We show that the reports construct the concept of a health threat as a sudden, unexpected event with the potential to cause severe harm and one that requires a public health response aided by surveillance. Based on our analysis, we state that when creating surveillance technologies, design choices have consequences for what can be seen and for what remains invisible. Finally, we argue that syndromic surveillance discourse privileges expertise in developing, maintaining and using software within public health practice, and it prioritizes standardized and transportable knowledge over local and context-dependent knowledge. We conclude that syndromic surveillance contributes to a shift in broader public health practice, with consequences for fairness if design choices and prioritizations remain invisible and unchallenged.

Keyword
ICT, discourse, epidemiology, public health surveillance, syndromic surveillance
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-158902 (URN)10.3390/soc4030399 (DOI)
Note

QC 20150114

Available from: 2015-01-13 Created: 2015-01-13 Last updated: 2015-01-14Bibliographically approved
5. Positions in technology design: A case study of a stress management system
Open this publication in new window or tab >>Positions in technology design: A case study of a stress management system
(English)Manuscript (preprint) (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-158907 (URN)
Note

QS 2015

Available from: 2015-01-13 Created: 2015-01-13 Last updated: 2015-01-14Bibliographically approved
6. Data-driven knowledge production in software engineering
Open this publication in new window or tab >>Data-driven knowledge production in software engineering
(English)Manuscript (preprint) (Other academic)
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-158908 (URN)
Note

QS 2015

Available from: 2015-01-13 Created: 2015-01-13 Last updated: 2015-01-14Bibliographically approved

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