Seeking connectivity to everyday health and wellness experiences: Specificities and consequences of connective gaps in self-tracking data

Yli-Kauhaluoma, Sari; Pantzar, Mika

doi:10.1177/2055207618779714

Cited by 13 publications

(9 citation statements)

References 42 publications

(73 reference statements)

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“…When self-tracking devices are to social networks, the proportion of lower-performing friends may positively influence users’ physical activities [ 56 ]. Moreover, Yli-Kauhaluoma and Pantzar [ 87 ] examined the gap between individual experiences and self-tracking data. They found that individuals always feel upset and confused when comparing invisible or inaccurate personal health data with their daily experiences and may eventually refuse to use self-tracking devices.…”

Section: Resultsmentioning

confidence: 99%

How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review

Feng¹,

Mäntymäki²,

Dhir³

et al. 2021

J Med Internet Res

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Background Self-tracking technologies are widely used in people’s daily lives and health care. Academic research on self-tracking and the quantified self has also accumulated rapidly in recent years. Surprisingly, there is a paucity of research that reviews, classifies, and synthesizes the state of the art with respect to self-tracking and the quantified self. Objective Our objective was to identify the state of the art of self-tracking and the quantified self in terms of health and well-being. Methods We have undertaken a systematic literature review on self-tracking and the quantified self in promoting health and well-being. After a rigorous literature search, followed by inclusions, exclusions, and the application of article quality assessment protocols, 67 empirical studies qualified for the review. Results Our results demonstrate that prior research has focused on 3 stakeholders with respect to self-tracking and the quantified self, namely end users, patients and people with illnesses, and health care professionals and caregivers. We used these stakeholder groups to cluster the research themes of the reviewed studies. We identified 11 research themes. There are 6 themes under the end-user cluster: user motivation and goal setting, usage and effects of self-tracking, continuance intention and long-term usage, management of personal data, rejection and discontinuance, and user characteristics. The patient and people with illnesses cluster contains three themes: usage experience of patients and people with illnesses, management of patient-generated data, and advantages and disadvantages in the clinical context. The health care professional and caregiver cluster contains two themes: collaboration among patients, health care professionals, and caregivers, and changes in the roles of patients and professionals. Moreover, we classified the future research suggestions given in the literature into 5 directions in terms of research designs and research topics. Finally, based on our reflections on the observations from the review, we suggest four future research directions: (1) users’ cognitions and emotions related to processing and interpreting the information produced by tracking devices and apps; (2) the dark side of self-tracking (eg, its adverse psychosocial consequences); (3) self-tracking as a societal phenomenon; and (4) systemic impacts of self-tracking on health care and the actors involved. Conclusions This systematic literature review contributes to research and practice by assisting future research activities and providing practitioners with a concise overview of the state of the art of self-tracking and the quantified self.

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Section: Resultsmentioning

confidence: 99%

How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review

Feng¹,

Mäntymäki²,

Dhir³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…Unlike traditional health literacy programs that focus on delivering general health knowledge [ 39 , 51 ], specific information related to an individual’s own health data can be easier to understand because it is tied to their own health concerns. However, we must keep in mind that interpretation of automatically tracked data is sometimes unreliable or may even cause misunderstandings [ 52 , 53 ]. For example, sleep tracking apps using pressure sensors to estimate sleep hours can cause false-positive detections when people are performing other activities in bed [ 53 ].…”

Section: Discussionmentioning

confidence: 99%

“…However, because patients are not medical experts, they could not always tell which data are relevant to their health, especially if they kept track of various types of data. Although our work did not examine clinicians’ perspectives on PGD sharing, previous work has found that clinicians are also concerned about the time they need to review PGD in the clinic [ 6 , 60 ] and may even consider these data to be distracting [ 52 ]. To resolve the dilemma of clinicians having limited time and patients feeling uncertain about whether their personal health data can be helpful, an approach should be developed to help patients share their data efficiently.…”

Section: Discussionmentioning

confidence: 99%

Interrelationships Between Patients’ Data Tracking Practices, Data Sharing Practices, and Health Literacy: Onsite Survey Study

Luo¹,

Oh²,

Jean³

et al. 2020

J Med Internet Res

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Background Although the use of patient-generated data (PGD) in the optimization of patient care shows great promise, little is known about whether patients who track their PGD necessarily share the data with their clinicians. Meanwhile, health literacy—an important construct that captures an individual’s ability to manage their health and to engage with their health care providers—has often been neglected in prior studies focused on PGD tracking and sharing. To leverage the full potential of PGD, it is necessary to bridge the gap between patients’ data tracking and data sharing practices by first understanding the interrelationships between these practices and the factors contributing to these practices. Objective This study aims to systematically examine the interrelationships between PGD tracking practices, data sharing practices, and health literacy among individual patients. Methods We surveyed 109 patients at the time they met with a clinician at a university health center, unlike prior research that often examined patients’ retrospective experience after some time had passed since their clinic visit. The survey consisted of 39 questions asking patients about their PGD tracking and sharing practices based on their current clinical encounter. The survey also contained questions related to the participants’ health literacy. All the participants completed the survey on a tablet device. The onsite survey study enabled us to collect ecologically valid data based on patients’ immediate experiences situated within their clinic visit. Results We found no evidence that tracking PGD was related to self-reports of having sufficient information to manage one’s health; however, the number of data types participants tracked positively related to their self-assessed ability to actively engage with health care providers. Participants’ data tracking practices and their health literacy did not relate to their data sharing practices; however, their ability to engage with health care providers positively related to their willingness to share their data with clinicians in the future. Participants reported several benefits of, and barriers to, sharing their PGD with clinicians. Conclusions Although tracking PGD could help patients better engage with health care providers, it may not provide patients with sufficient information to manage their health. The gaps between tracking and sharing PGD with health care providers call for efforts to inform patients of how their data relate to their health and to facilitate efficient clinician-patient communication. To realize the full potential of PGD and to promote individuals’ health literacy, empowering patients to effectively track and share their PGD is important—both technologies and health care providers can play important roles.

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Section: The Gaps Between Tracking and Sharing Pgdmentioning

confidence: 99%

“…Unlike traditional health literacy programs that focus on delivering general health knowledge [39,51], specific information related to an individual's own health data can be easier to understand because it is tied to their own health concerns. However, we must keep in mind that interpretation of automatically tracked data is sometimes unreliable or may even cause misunderstandings [52,53]. For example, sleep tracking apps using pressure sensors to estimate sleep hours can cause false-positive detections when people are performing other activities in bed [53].…”

Section: Reflecting On the Relationships Between Pgd Tracking And Health Literacymentioning

confidence: 99%

Interrelationships Between Patients’ Data Tracking Practices, Data Sharing Practices, and Health Literacy: Onsite Survey Study (Preprint)

Luo¹,

Oh²,

Jean³

et al. 2020

Preprint

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BACKGROUND Despite the great promise of patient-generated data (PGD) in optimizing patient care, little is known about whether patients who track their PGD necessarily share their data with their doctors. Meanwhile, health literacy—an important construct that captures an individual’s ability to manage their health and to engage with their healthcare providers—has often been neglected in prior studies focused on PGD tracking and sharing. To utilize PGD, we need to bridge the gap between patients’ data tracking and sharing of the data by first understanding the interrelationships between these practices and factors contributing to such practices. OBJECTIVE We aimed to systematically examine the interrelationships among individual patients’ PGD tracking practices, their data sharing practices, and their health literacy. METHODS Different from prior research that often examined patients’ retrospective experience after some time had passed since their clinic visit, we surveyed 109 patients who had just met with a doctor at the University Health Center. The survey asked patients about their PGD tracking and sharing practices based on the specific clinical encounter they just had. The survey also contained questions related to participants’ health literacy. The onsite survey study enabled us to collect ecologically valid data based on patients’ immediate experiences situated within their clinic visit. RESULTS (1) We found no evidence that tracking PGD related to self-reports of “having sufficient information to manage one’s health”; however, the number of data types participants tracked positively related to their self-assessed “ability to actively engage with healthcare providers”; (2) participants’ data tracking practices and their health literacy did not relate to their data sharing practices, but their ability to engage with healthcare providers positively related to their willingness to share their data with doctors in the future; and (3) participants reported several benefits of, and barriers to, sharing their PGD with doctors. CONCLUSIONS While tracking PGD could help patients better engage with healthcare providers, it may not provide them with sufficient information to manage their health. The gaps between tracking and sharing PGD with healthcare providers call for efforts to inform patients of how their data relate to their health and to facilitate more efficient doctor-patient communication. To realize the full potential of PGD and to promote individuals’ health literacy, empowering patients to effectively track and share their PGD is important—both technologies and healthcare providers can play an important role.

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Seeking connectivity to everyday health and wellness experiences: Specificities and consequences of connective gaps in self-tracking data

Cited by 13 publications

References 42 publications

How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review

How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review

Interrelationships Between Patients’ Data Tracking Practices, Data Sharing Practices, and Health Literacy: Onsite Survey Study

Interrelationships Between Patients’ Data Tracking Practices, Data Sharing Practices, and Health Literacy: Onsite Survey Study (Preprint)

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