Investigating Microtemporal Processes Underlying Health Behavior Adoption and Maintenance: Protocol for an Intensive Longitudinal Observational Study

Shirlene Wang; Stephen Intille; Aditya Ponnada; Bridgette Do; Alexander Rothman; Genevieve Dunton

doi:10.2196/36666

Investigating Microtemporal Processes Underlying Health Behavior Adoption and Maintenance: Protocol for an Intensive Longitudinal Observational Study

Shirlene Wang
, Stephen Intille
, Aditya Ponnada
, Bridgette Do
, Alexander Rothman
, Genevieve Dunton

Psychology (Twin Cities)

Research output: Contribution to journal › Article › peer-review

25 Scopus citations

Abstract

BACKGROUND: Young adulthood (ages 18-29 years) is marked by substantial weight gain, leading to increased lifetime risks of chronic diseases. Engaging in sufficient levels of physical activity and sleep, and limiting sedentary time are important contributors to the prevention of weight gain. Dual-process models of decision-making and behavior that delineate reflective (ie, deliberative, slow) and reactive (ie, automatic, fast) processes shed light on different mechanisms underlying the adoption versus maintenance of these energy-balance behaviors. However, reflective and reactive processes may unfold at different time scales and vary across people.

OBJECTIVE: This paper describes the study design, recruitment, and data collection procedures for the Temporal Influences on Movement and Exercise (TIME) study, a 12-month intensive longitudinal data collection study to examine real-time microtemporal influences underlying the adoption and maintenance of physical activity, sedentary behavior, and sleep.

METHODS: Intermittent ecological momentary assessment (eg, intentions, self-control) and continuous, sensor-based passive monitoring (eg, location, phone/app use, activity levels) occur using smartwatches and smartphones. Data analyses will combine idiographic (person-specific, data-driven) and nomothetic (generalizable, theory-driven) approaches to build models that may predict within-subject variation in the likelihood of behavior "episodes" (eg, ≥10 minutes of physical activity, ≥120 minutes of sedentary time, ≥7 hours sleep) and "lapses" (ie, not attaining recommended levels for ≥7 days) as a function of reflective and reactive factors.

RESULTS: The study recruited young adults across the United States (N=246). Rolling recruitment began in March 2020 and ended August 2021. Data collection will continue until August 2022.

CONCLUSIONS: Results from the TIME study will be used to build more predictive health behavior theories, and inform personalized behavior interventions to reduce obesity and improve public health.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36666.

Original language	English (US)
Article number	e36666
Journal	JMIR research protocols
Volume	11
Issue number	7
DOIs	https://doi.org/10.2196/36666
State	Published - Jul 1 2022

Bibliographical note

Funding Information:
This work is supported by the National Institutes of Health (NIH/NHLBI U01HL146327). Amy Ngyuen, Jon Kaslander, and Micaela Hewus assisted with participant recruitment, data collection, and the conduct of exit interviews. Krit Goyal, Adeeb M Arif, Binod Thapa Chhetry, Jixin Li, and Qu Tang contributed to the development of the TIME app and compliance monitoring scripts. We thank our participants of the study for their time.

Publisher Copyright:
© Shirlene Wang, Stephen Intille, Aditya Ponnada, Bridgette Do, Alexander Rothman, Genevieve Dunton

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

EMA
behavior change
chronic disease
ecological momentary assessment
emerging adulthood
longitudinal data collection
physical activity
sensing
theory
weight gain
young adult

Publisher link

10.2196/36666

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title = "Investigating Microtemporal Processes Underlying Health Behavior Adoption and Maintenance: Protocol for an Intensive Longitudinal Observational Study",

abstract = "BACKGROUND: Young adulthood (ages 18-29 years) is marked by substantial weight gain, leading to increased lifetime risks of chronic diseases. Engaging in sufficient levels of physical activity and sleep, and limiting sedentary time are important contributors to the prevention of weight gain. Dual-process models of decision-making and behavior that delineate reflective (ie, deliberative, slow) and reactive (ie, automatic, fast) processes shed light on different mechanisms underlying the adoption versus maintenance of these energy-balance behaviors. However, reflective and reactive processes may unfold at different time scales and vary across people.OBJECTIVE: This paper describes the study design, recruitment, and data collection procedures for the Temporal Influences on Movement and Exercise (TIME) study, a 12-month intensive longitudinal data collection study to examine real-time microtemporal influences underlying the adoption and maintenance of physical activity, sedentary behavior, and sleep.METHODS: Intermittent ecological momentary assessment (eg, intentions, self-control) and continuous, sensor-based passive monitoring (eg, location, phone/app use, activity levels) occur using smartwatches and smartphones. Data analyses will combine idiographic (person-specific, data-driven) and nomothetic (generalizable, theory-driven) approaches to build models that may predict within-subject variation in the likelihood of behavior {"}episodes{"} (eg, ≥10 minutes of physical activity, ≥120 minutes of sedentary time, ≥7 hours sleep) and {"}lapses{"} (ie, not attaining recommended levels for ≥7 days) as a function of reflective and reactive factors.RESULTS: The study recruited young adults across the United States (N=246). Rolling recruitment began in March 2020 and ended August 2021. Data collection will continue until August 2022.CONCLUSIONS: Results from the TIME study will be used to build more predictive health behavior theories, and inform personalized behavior interventions to reduce obesity and improve public health.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36666.",

keywords = "EMA, behavior change, chronic disease, ecological momentary assessment, emerging adulthood, longitudinal data collection, physical activity, sensing, theory, weight gain, young adult",

author = "Shirlene Wang and Stephen Intille and Aditya Ponnada and Bridgette Do and Alexander Rothman and Genevieve Dunton",

note = "Funding Information: This work is supported by the National Institutes of Health (NIH/NHLBI U01HL146327). Amy Ngyuen, Jon Kaslander, and Micaela Hewus assisted with participant recruitment, data collection, and the conduct of exit interviews. Krit Goyal, Adeeb M Arif, Binod Thapa Chhetry, Jixin Li, and Qu Tang contributed to the development of the TIME app and compliance monitoring scripts. We thank our participants of the study for their time. Publisher Copyright: {\textcopyright} Shirlene Wang, Stephen Intille, Aditya Ponnada, Bridgette Do, Alexander Rothman, Genevieve Dunton",

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doi = "10.2196/36666",

language = "English (US)",

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T1 - Investigating Microtemporal Processes Underlying Health Behavior Adoption and Maintenance

T2 - Protocol for an Intensive Longitudinal Observational Study

AU - Wang, Shirlene

AU - Intille, Stephen

AU - Ponnada, Aditya

AU - Do, Bridgette

AU - Rothman, Alexander

AU - Dunton, Genevieve

N1 - Funding Information: This work is supported by the National Institutes of Health (NIH/NHLBI U01HL146327). Amy Ngyuen, Jon Kaslander, and Micaela Hewus assisted with participant recruitment, data collection, and the conduct of exit interviews. Krit Goyal, Adeeb M Arif, Binod Thapa Chhetry, Jixin Li, and Qu Tang contributed to the development of the TIME app and compliance monitoring scripts. We thank our participants of the study for their time. Publisher Copyright: © Shirlene Wang, Stephen Intille, Aditya Ponnada, Bridgette Do, Alexander Rothman, Genevieve Dunton

PY - 2022/7/1

Y1 - 2022/7/1

N2 - BACKGROUND: Young adulthood (ages 18-29 years) is marked by substantial weight gain, leading to increased lifetime risks of chronic diseases. Engaging in sufficient levels of physical activity and sleep, and limiting sedentary time are important contributors to the prevention of weight gain. Dual-process models of decision-making and behavior that delineate reflective (ie, deliberative, slow) and reactive (ie, automatic, fast) processes shed light on different mechanisms underlying the adoption versus maintenance of these energy-balance behaviors. However, reflective and reactive processes may unfold at different time scales and vary across people.OBJECTIVE: This paper describes the study design, recruitment, and data collection procedures for the Temporal Influences on Movement and Exercise (TIME) study, a 12-month intensive longitudinal data collection study to examine real-time microtemporal influences underlying the adoption and maintenance of physical activity, sedentary behavior, and sleep.METHODS: Intermittent ecological momentary assessment (eg, intentions, self-control) and continuous, sensor-based passive monitoring (eg, location, phone/app use, activity levels) occur using smartwatches and smartphones. Data analyses will combine idiographic (person-specific, data-driven) and nomothetic (generalizable, theory-driven) approaches to build models that may predict within-subject variation in the likelihood of behavior "episodes" (eg, ≥10 minutes of physical activity, ≥120 minutes of sedentary time, ≥7 hours sleep) and "lapses" (ie, not attaining recommended levels for ≥7 days) as a function of reflective and reactive factors.RESULTS: The study recruited young adults across the United States (N=246). Rolling recruitment began in March 2020 and ended August 2021. Data collection will continue until August 2022.CONCLUSIONS: Results from the TIME study will be used to build more predictive health behavior theories, and inform personalized behavior interventions to reduce obesity and improve public health.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36666.

AB - BACKGROUND: Young adulthood (ages 18-29 years) is marked by substantial weight gain, leading to increased lifetime risks of chronic diseases. Engaging in sufficient levels of physical activity and sleep, and limiting sedentary time are important contributors to the prevention of weight gain. Dual-process models of decision-making and behavior that delineate reflective (ie, deliberative, slow) and reactive (ie, automatic, fast) processes shed light on different mechanisms underlying the adoption versus maintenance of these energy-balance behaviors. However, reflective and reactive processes may unfold at different time scales and vary across people.OBJECTIVE: This paper describes the study design, recruitment, and data collection procedures for the Temporal Influences on Movement and Exercise (TIME) study, a 12-month intensive longitudinal data collection study to examine real-time microtemporal influences underlying the adoption and maintenance of physical activity, sedentary behavior, and sleep.METHODS: Intermittent ecological momentary assessment (eg, intentions, self-control) and continuous, sensor-based passive monitoring (eg, location, phone/app use, activity levels) occur using smartwatches and smartphones. Data analyses will combine idiographic (person-specific, data-driven) and nomothetic (generalizable, theory-driven) approaches to build models that may predict within-subject variation in the likelihood of behavior "episodes" (eg, ≥10 minutes of physical activity, ≥120 minutes of sedentary time, ≥7 hours sleep) and "lapses" (ie, not attaining recommended levels for ≥7 days) as a function of reflective and reactive factors.RESULTS: The study recruited young adults across the United States (N=246). Rolling recruitment began in March 2020 and ended August 2021. Data collection will continue until August 2022.CONCLUSIONS: Results from the TIME study will be used to build more predictive health behavior theories, and inform personalized behavior interventions to reduce obesity and improve public health.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36666.

KW - EMA

KW - behavior change

KW - chronic disease

KW - ecological momentary assessment

KW - emerging adulthood

KW - longitudinal data collection

KW - physical activity

KW - sensing

KW - theory

KW - weight gain

KW - young adult

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M3 - Article

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JO - JMIR research protocols

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ER -

Investigating Microtemporal Processes Underlying Health Behavior Adoption and Maintenance: Protocol for an Intensive Longitudinal Observational Study

Abstract

Bibliographical note

UN SDGs

Keywords

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