Novel Statistical Models for EMA Studies of Physical Activity

身体活动 EMA 研究的新统计模型

• 批准号: 9268804
• 负责人: Genevieve Fridlund Dunton
• 金额: $ 53.16万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-01 至 2019-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9268804
• 关键词: Address; Adult; Affective; Area; Asthma; Attenuated; Behavior; Belief; Child; Chronic Disease; Cognition; Cognitive; Complex; Computer software; Coupling; Data; Data Analyses; Data Set; Development; Diabetes Mellitus; Diet; Disease; Ecological momentary assessment; Emotional Stability; Event; Exercise; Fatigue; Feeling; Foundations; Gender; Health; Heart Diseases; High School Student; Hour; Individual; Life Cycle Stages; Linear Models; Malignant Neoplasms; Measures; Mediating; Memory; Mental Depression; Meta-Analysis; Methodology; Methods; Modeling; Moods; Nature; Neighborhoods; Outcome; Parents; Participant; Persons; Physical activity; Public Health; Research; Research Activity; Risk; Safety; Sample Size; Secondary to; Self Efficacy; Smoking; Statistical Methods; Statistical Models; Stress; Stroke; Testing; Time; Work; base; cost; improved; insight; medication compliance; middle age; multilevel analysis; negative affect; novel; physical inactivity; programs; psychologic; public health relevance; response; secondary analysis; sedentary; sedentary activity; simulation; social; walkability

DESCRIPTION (provided by applicant): This proposal responds to PAR-12-198 ("Improving Diet and Physical Activity Assessment"). It will develop and test novel multilevel statistical methods to examine the effects of subject-level parameters (variance and slope) of time-varying variables in ecological momentary assessment (EMA) studies of physical activity. Low level of physical activity heightens the risk of numerous deadly diseases (e.g., heart disease, stroke, cancer, diabetes) throughout the life course. The use of EMA in physical activity research is growing rapidly because real-time data capture methods supply novel insights into determinants of this behavior. In EMA studies, it is common to have up to thirty or forty observations per subject, and this allows us to model subject-level parameters such as variances (e.g., how erratic is a subject's mood?) and slopes (e.g., how much does a subject's mood change across contexts?) of time-varying variables. For example, in our recent EMA work, we have found that more physically active children have greater positive and negative emotional stability than children who are less physically active. However, current multilevel modeling strategies are restricted to treating subject-level variances and slopes as outcomes. As a consequence, statistical models do not have the ability to test whether subject-level variance and slope parameters have predictive, mediating, and moderating effects on physical and sedentary activity. For example, we are unable to ask important research questions such as whether erratic mood mediates the effects of depression on physical activity, or whether the effects of living in a highly walkable neighborhood on physical activity are attenuated for individuals with unstable self- efficacy beliefs. This modeling restriction severely limits our ability to capitaliz on the full potential of the time- varying nature of EMA data to enhance physical activity research. To address this critical methodological gap, we propose to develop multilevel models, software, and strategies to test for the effects of these parameters in EMA studies. We will apply these modeling strategies to secondary analyses of pooled data from five federally- and foundation-supported EMA studies of physical activity with a combined sample size of N = 553 participants (including children and adults). The primary aims are (1) to develop novel multilevel modeling strategies and software to test whether subject-level variance and slope parameters have predictive, mediating, and moderating effects on subject-level physical and sedentary activity outcomes and (2) to apply these novel modeling strategies and software in secondary analyses of existing EMA datasets to examine the effects of subject-level variance and slopes of time-varying variables such as safety, stress, fatigue, and self-efficacy on physical and sedentary activity. This study has the potential to make novel methodological and substantive contributions for analysis of EMA data in physical activity research. The methods to be developed can easily generalize to a variety of chronic disease-relevant research areas.

描述（由申请人提供）：该提案响应 PAR-12-198（“改善饮食和身体活动评估”）。它将开发和测试新颖的多级统计方法，以检查体力活动生态瞬时评估（EMA）研究中时变变量的受试者级参数（方差和斜率）的影响。身体活动水平低会增加整个生命过程中多种致命疾病（例如心脏病、中风、癌症、糖尿病）的风险。 EMA 在身体活动研究中的使用正在迅速增长，因为实时数据捕获方法为这种行为的决定因素提供了新颖的见解。在 EMA 研究中，每个受试者通常有多达三十或四十个观察值，这使我们能够对受试者级别的参数进行建模，例如时变变量的方差（例如，受试者的情绪有多不稳定？）和斜率（例如，受试者的情绪在不同背景下变化有多大？）。例如，在我们最近的 EMA 工作中，我们发现体力活动较多的孩子比体力活动较少的孩子具有更大的积极和消极情绪稳定性。然而，当前的多级建模策略仅限于将主题级方差和斜率视为结果。因此，统计模型无法测试受试者水平方差和斜率参数是否对身体和久坐活动具有预测、中介和调节作用。例如，我们无法提出重要的研究问题，例如不稳定的情绪是否会介导抑郁对身体活动的影响，或者对于自我效能信念不稳定的个体来说，居住在高度步行的社区对身体活动的影响是否会减弱。这种建模限制严重限制了我们充分利用 EMA 数据时变性质的潜力来加强身体活动研究的能力。为了解决这一关键的方法论差距，我们建议开发多层次模型、软件和策略来测试这些参数在 EMA 研究中的影响。我们将应用这些建模策略对五项联邦和基金会支持的 EMA 身体活动研究的汇总数据进行二次分析，合并样本量为 N = 553 名参与者（包括儿童和成人）。主要目标是（1）开发新颖的多级建模策略和软件，以测试受试者水平方差和斜率参数是否对受试者水平身体和久坐活动结果具有预测、中介和调节作用；（2）将这些新颖的建模策略和软件应用于现有 EMA 数据集的二次分析，以检查受试者水平方差和时变变量（例如安全性、 身体和久坐活动的压力、疲劳和自我效能。这项研究有可能为身体活动研究中的 EMA 数据分析做出新的方法论和实质性贡献。待开发的方法可以很容易地推广到各种慢性病相关的研究领域。

项目成果

Do fluctuations in positive affective and physical feeling states predict physical activity and sedentary time?

• DOI: 10.1016/j.psychsport.2018.01.011
• 发表时间: 2019-03-01
• 期刊: PSYCHOLOGY OF SPORT AND EXERCISE
• 影响因子: 3.4
• 作者: Maher, Jaclyn P.;Dzubur, Eldin;Dunton, Genevieve F.
• 通讯作者: Dunton, Genevieve F.

An empirical example of analysis using a two-stage modeling approach: within-subject association of outdoor context and physical activity predicts future daily physical activity levels.

使用两阶段建模方法进行分析的实证示例：户外环境和身体活动的受试者内关联可以预测未来的日常身体活动水平。

• DOI: 10.1093/tbm/ibaa107
• 发表时间: 2021
• 期刊: Translational behavioral medicine
• 影响因子: 3.6
• 作者: Yang,Chih-Hsiang;Maher,JaclynP;Ponnada,Aditya;Dzubur,Eldin;Nordgren,Rachel;Intille,Stephen;Hedeker,Donald;Dunton,GenevieveF
• 通讯作者: Dunton,GenevieveF

Associations of Mothers' and Children's Stress With Children's Device-Measured Physical Activity and Sedentary Behavior Trajectories Across 3 Years.

三年来母亲和儿童的压力与儿童设备测量的体力活动和久坐行为轨迹之间的关联。

• DOI: 10.1123/jpah.2020-0558
• 发表时间: 2021
• 期刊: Journal of physical activity & health
• 影响因子: 3.1
• 作者: Dunton,GenevieveF;Chu,Daniel;Naya,ChristineH;Belcher,BritniR;Mason,TylerB
• 通讯作者: Mason,TylerB

How acute affect dynamics impact longitudinal changes in physical activity among children.

影响动态对儿童体力活动纵向变化的影响有多严重。

• DOI: 10.1007/s10865-022-00282-w
• 发表时间: 2022
• 期刊: Journal of behavioral medicine
• 影响因子: 3.1
• 作者: Dunton,GenevieveF;Wang,Wei-Lin;Intille,StephenS;Dzubur,Eldin;Ponnada,Aditya;Hedeker,Donald
• 通讯作者: Hedeker,Donald

Mean level of positive affect moderates associations between volatility in positive affect, mental health, and alcohol consumption among mothers.

积极情绪的平均水平调节了母亲积极情绪的波动性、心理健康和饮酒之间的关联。

• DOI: 10.1037/abn0000374
• 发表时间: 2018
• 期刊: Journal of abnormal psychology
• 影响因子: 4.6
• 作者: Maher,JaclynP;Ra,ChaelinK;Leventhal,AdamM;Hedeker,Donald;Huh,Jimi;Chou,Chih-Ping;Dunton,GenevieveF
• 通讯作者: Dunton,GenevieveF