The Tesserae Project

Mattingly, Stephen M.; Gregg, Julie; Audia, Pino G.; Bayraktaroglu, Ayse Elvan; Campbell, Andrew T.; Chawla, Nitesh V.; Swain, Vedant Das; Choudhury, Munmun De; D’Mello, Sidney K.; Dey, Anind K.; Gao, Ge; Jagannath, Krithika; Jiang, Kaifeng; Lin, Suwen; Liu, Qiang; Mark, Gloria; Martínez, Gonzalo J.; Masaba, Kizito; Mirjafari, Shayan; Moskal, Edward; Mulukutla, Raghu; Nies, Kari; Reddy, Manikanta D.; Robles-Granda, Pablo; Saha, Koustuv; Sirigiri, Anusha; Striegel, Aaron

doi:10.1145/3290607.3299041

Cited by 76 publications

(10 citation statements)

References 7 publications

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“…We used our Tesserae [42] study-a 1-year, large-scale, multimodal study of working professionals with a rich set of psychological and health-related data to extract meaningful variables that explain variations in compliance.…”

Section: Methodsmentioning

confidence: 99%

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study (Preprint)

Martínez¹,

Mattingly²,

Robles-Granda³

et al. 2020

Preprint

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BACKGROUND Longitudinal studies using wearable sensors to track numerous attributes such as physical activity, sleep, and heart rate can benefit from reductions in missing data. Maximizing compliance through participant engagement is one method to reduce missing data and poor compliance can reduce the return on the heavy investment of time and money into large-scale studies. OBJECTIVE This paper aims to identify to what extent compliance can be prospectively predicted from individual attributes and initial compliance and to identify the most predictive features. METHODS We define compliance with Ecological Momentary Assessments (EMAs) as the response rate, and wearable compliance as the proportion of 30-minute windows with data throughout a year-long multi-modal study of information workers. study participation. We analyze 31 individual characteristics (e.g. demographics, personality) and behavioral variables (e.g early compliance, study portal use) and select 14 variables to create beta regression models to predict compliance with Ecological Momentary Assessments (EMAs) two months out and wearable compliance one year out. We survey study participation and correlate the results with compliance. RESULTS Our modeling of compliance indicates that up to 23% of the variance in compliance with EMAs and 15% of the variance in compliance with our smartwatch wearing protocol could be predicted through a survey of demographics and personality. Likelihood of higher EMA and wearable compliance was associated with being older (EMA P=.027 and wearable P<.001), not having a supervisory role (EMA P<.001 and wearable P<.001), speaking English as a first language (EMA P=.051, wearable P=.057), having had a wearable prior to joining the study (EMA P=.051 and wearable P<.001), being more conscientious (EMA P=.024 and wearable P<.001), being more introverted (EMA P<.001 and wearable P<.001). Additionally, likelihood of higher wearable compliance was also associated with being less agreeable (P<.001) and less neurotic (P=.057). Further, including early compliance in the second week of the study can help explain more variance and reduce prediction error, with up to 66% of the variance in EMA compliance and 63% in wearable compliance explained. Finally, we report that compliance in the study correlated with our participants’ self-reflection on ease of participation, usefulness of our compliance portal, timely resolution of issues, and compensation adequacy, suggesting these as avenues to improving compliance. CONCLUSIONS We recommend conducting an initial two-week pilot to measure trait-like compliance and identify participants at risk of long-term non-compliance. We recommend oversampling based on participants' individual characteristics to avoid introducing bias in the sample when excluding data based on non-compliance. Finally, we recommend the use of an issue tracking portal and special care on troubleshooting to help participants maintain compliance.

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Section: Methodsmentioning

confidence: 99%

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study (Preprint)

Martínez¹,

Mattingly²,

Robles-Granda³

et al. 2020

Preprint

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“…The data utilized in this article come from the Tesserae study, which recruited 757 participants throughout different companies across the United States, concentrated around four major organizations (21). The study followed participants for 1 year, collecting demographics, psychometrics, fitness tracker data, and life events.…”

Section: Studymentioning

confidence: 99%

“…To ensure completeness in the data collection, participants were required to wear their Garmin 80% of the time and received monetary compensation if this threshold was met. For a complete detailing of the study, we refer to the reader to (21).…”

Section: Studymentioning

confidence: 99%

Examining Response to Negative Life Events Through Fitness Tracker Data

Faust

Feldman

Lin

et al. 2021

Front. Digit. Health

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Negative life events, such as the death of a loved one, are an unavoidable part of life. These events can be overwhelmingly stressful and may lead to the development of mental health disorders. To mitigate these adverse developments, prior literature has utilized measures of psychological responses to negative life events to better understand their effects on mental health. However, psychological changes represent only one aspect of an individual's potential response. We posit measuring additional dimensions of health, such as physical health, may also be beneficial, as physical health itself may be affected by negative life events and measuring its response could provide context to changes in mental health. Therefore, the primary aim of this work was to quantify how an individual's physical health changes in response to negative life events by testing for deviations in their physiological and behavioral state (PB-state). After capturing post-event, PB-state responses, our second aim sought to contextualize changes within known factors of psychological response to negative life events, namely coping strategies. To do so, we utilized a cohort of professionals across the United States monitored for 1 year and who experienced a negative life event while under observation. Garmin Vivosmart-3 devices provided a multidimensional representation of one's PB-state by collecting measures of resting heart rate, physical activity, and sleep. To test for deviations in PB-state following negative life events, One-Class Support Vector Machines were trained on a window of time prior to the event, which established a PB-state baseline. The model then evaluated participant's PB-state on the day of the life event and each day that followed, assigning each day a level of deviance relative to the participant's baseline. Resulting response curves were then examined in association with the use of various coping strategies using Bayesian gamma-hurdle regression models. The results from our objectives suggest that physical determinants of health also deviate in response to negative life events and that these deviations can be mitigated through different coping strategies. Taken together, these observations stress the need to examine physical determinants of health alongside psychological determinants when investigating the effects of negative life events.

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“…We also call for the HCI community to think more about our own ethical responsibilities, particularly how we can promote study of a participant's self-knowledge and self-understanding when we are deploying selftracking systems for our own gains. For example, large-scale deployments of location and activity-monitoring applications have contributed important insights into the behaviors of students (e.g., StudentLife [286]) and of office workers (e.g., the Tesserae Project [187]). It is worth considering whether the self-tracking tools we use to collect data can provide individual study participants insights into their own behaviors without interfering with the study's integrity.…”

Section: Highlighting Privacy and Ethical Concerns Furthermentioning

confidence: 99%

Mapping and Taking Stock of the Personal Informatics Literature

Epstein

Caldeira

Figueiredo

et al. 2020

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

119

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The research community on the study and design of systems for personal informatics has grown over the past decade. To take stock of what the topics the field has studied and methods the field has used, we map and label 523 publications from ACM's library, IEEE Xplore, and PubMed. We surface that the literature has focused on studying and designing for health and wellness domains, an emphasis on understanding and overcoming barriers to data collection and reflection, and progressively fewer contributions involving artifacts being made. Our mapping review suggests directions future research could explore, such as identifying and resolving barriers to tracking stages beyond collection and reflection, engaging more with domain experts, and further discussing the privacy and ethical concerns around tracked data.

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The Tesserae Project

Cited by 76 publications

References 7 publications

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study (Preprint)

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study (Preprint)

Examining Response to Negative Life Events Through Fitness Tracker Data

Mapping and Taking Stock of the Personal Informatics Literature

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