From Quantified Self to Quality of Life

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Standard

From Quantified Self to Quality of Life. / Wac, Katarzyna.

Digital Health: Scaling Healthcare to the World. ed. / Homero Rivas; Katarzyna Wac. Springer, 2018. p. 83-108 (Health Informatics Series).

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Harvard

Wac, K 2018, From Quantified Self to Quality of Life. in H Rivas & K Wac (eds), Digital Health: Scaling Healthcare to the World. Springer, Health Informatics Series, pp. 83-108. https://doi.org/10.1007/978-3-319-61446-5_7

APA

Wac, K. (2018). From Quantified Self to Quality of Life. In H. Rivas, & K. Wac (Eds.), Digital Health: Scaling Healthcare to the World (pp. 83-108). Springer. Health Informatics Series https://doi.org/10.1007/978-3-319-61446-5_7

Vancouver

Wac K. From Quantified Self to Quality of Life. In Rivas H, Wac K, editors, Digital Health: Scaling Healthcare to the World. Springer. 2018. p. 83-108. (Health Informatics Series). https://doi.org/10.1007/978-3-319-61446-5_7

Author

Wac, Katarzyna. / From Quantified Self to Quality of Life. Digital Health: Scaling Healthcare to the World. editor / Homero Rivas ; Katarzyna Wac. Springer, 2018. pp. 83-108 (Health Informatics Series).

Bibtex

@inbook{11337ec6bcd64b39af68c87fa4add14e,
title = "From Quantified Self to Quality of Life",
abstract = "“Know Thyself” is a motto leading the Quantified Self (QS) movement, which at first originated as a “hobby project” driven by self-discovery, and is now being leveraged in wellness and healthcare. QS practitioners rely on the wealth of digital data originating from wearables, applications, and self-reports that enable them to assess diverse domains of their daily life. That includes their physical state (e.g., mobility, steps), psychological state (e.g., mood), social interactions (e.g., a number of Facebook “likes”) and environmental context they are in (e.g., pollution). The World Health Organization (WHO) recognizes these four QS domains as contributing to individual{\textquoteright}s Quality of Life (QoL), with health spanning across all the four domains. The collected QS data enables an individual{\textquoteright}s state and behavioral patterns to be assessed through these different QoL domains, based on which individualized feedback can be provided, in turn enabling to improve the individual{\textquoteright}s state and QoL. The evidence of causality between QS and QoL is still being established, as only data from limited cases and domains exist so far. In this chapter, we discuss the state of this evidence via a semi-systematic review of the exemplary QS practices documented in 609 QS practitioners{\textquoteright} talks and a review of the 438 latest available personal wearable technologies enabling QS. We discuss the challenges and opportunities for the QS to become an integral part of the future of healthcare and QoL-driven solutions. Some of the opportunities include using QS technologies as different types of affordances supporting the goal-oriented actions by the individual, in turn improving their QoL.",
keywords = "Human-computer interaction, Mobile health, Tracking and selfmanagement systems, Ubiquitous computing and sensors, Physiologic modeling and disease processes",
author = "Katarzyna Wac",
year = "2018",
doi = "10.1007/978-3-319-61446-5_7",
language = "English",
isbn = "978-3-319-61445-8",
series = "Health Informatics Series",
publisher = "Springer",
pages = "83--108",
editor = "Rivas, {Homero } and Katarzyna Wac",
booktitle = "Digital Health",
address = "Switzerland",

}

RIS

TY - CHAP

T1 - From Quantified Self to Quality of Life

AU - Wac, Katarzyna

PY - 2018

Y1 - 2018

N2 - “Know Thyself” is a motto leading the Quantified Self (QS) movement, which at first originated as a “hobby project” driven by self-discovery, and is now being leveraged in wellness and healthcare. QS practitioners rely on the wealth of digital data originating from wearables, applications, and self-reports that enable them to assess diverse domains of their daily life. That includes their physical state (e.g., mobility, steps), psychological state (e.g., mood), social interactions (e.g., a number of Facebook “likes”) and environmental context they are in (e.g., pollution). The World Health Organization (WHO) recognizes these four QS domains as contributing to individual’s Quality of Life (QoL), with health spanning across all the four domains. The collected QS data enables an individual’s state and behavioral patterns to be assessed through these different QoL domains, based on which individualized feedback can be provided, in turn enabling to improve the individual’s state and QoL. The evidence of causality between QS and QoL is still being established, as only data from limited cases and domains exist so far. In this chapter, we discuss the state of this evidence via a semi-systematic review of the exemplary QS practices documented in 609 QS practitioners’ talks and a review of the 438 latest available personal wearable technologies enabling QS. We discuss the challenges and opportunities for the QS to become an integral part of the future of healthcare and QoL-driven solutions. Some of the opportunities include using QS technologies as different types of affordances supporting the goal-oriented actions by the individual, in turn improving their QoL.

AB - “Know Thyself” is a motto leading the Quantified Self (QS) movement, which at first originated as a “hobby project” driven by self-discovery, and is now being leveraged in wellness and healthcare. QS practitioners rely on the wealth of digital data originating from wearables, applications, and self-reports that enable them to assess diverse domains of their daily life. That includes their physical state (e.g., mobility, steps), psychological state (e.g., mood), social interactions (e.g., a number of Facebook “likes”) and environmental context they are in (e.g., pollution). The World Health Organization (WHO) recognizes these four QS domains as contributing to individual’s Quality of Life (QoL), with health spanning across all the four domains. The collected QS data enables an individual’s state and behavioral patterns to be assessed through these different QoL domains, based on which individualized feedback can be provided, in turn enabling to improve the individual’s state and QoL. The evidence of causality between QS and QoL is still being established, as only data from limited cases and domains exist so far. In this chapter, we discuss the state of this evidence via a semi-systematic review of the exemplary QS practices documented in 609 QS practitioners’ talks and a review of the 438 latest available personal wearable technologies enabling QS. We discuss the challenges and opportunities for the QS to become an integral part of the future of healthcare and QoL-driven solutions. Some of the opportunities include using QS technologies as different types of affordances supporting the goal-oriented actions by the individual, in turn improving their QoL.

KW - Human-computer interaction

KW - Mobile health

KW - Tracking and selfmanagement systems

KW - Ubiquitous computing and sensors

KW - Physiologic modeling and disease processes

U2 - 10.1007/978-3-319-61446-5_7

DO - 10.1007/978-3-319-61446-5_7

M3 - Book chapter

SN - 978-3-319-61445-8

T3 - Health Informatics Series

SP - 83

EP - 108

BT - Digital Health

A2 - Rivas, Homero

A2 - Wac, Katarzyna

PB - Springer

ER -

ID: 199034657