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Momentary assessment of physical activity intention-behavior coupling in adults.

ABSTRACT: Research attempting to elucidate physical activity (PA) intention-behavior relations has focused on differences in long-term behavior forecasting between people. However, regular PA requires a repeated performance on a daily or within-daily basis. An empirical case study application is presented using intensive longitudinal data from a study of PA in adults to (a) describe the extent to which short-term intention-behavior coupling occurs and (b) explore time-varying predictors of intention formation and short-term intention-behavior coupling. Adults (n = 116) participated in three 4-day waves of ecological momentary assessment (EMA). Each day, participants received EMA questionnaires assessing short-term PA intentions and wore accelerometers to assess whether they engaged in ?10 min of moderate-to-vigorous physical activity (MVPA) in the 3-hour period after each EMA prompt. Concurrent affective states and contexts were also assessed through EMA. Participants reported having short-term intentions to engage in PA in 41% of EMA prompts. However, participants only engaged in ?10 min of MVPA following 16% of the prompts that short-term PA intentions were reported indicating an intention-behavior gap of 84%. Odds of intentions followed by PA were greater on occasions when individuals reported higher levels of positive affect than was typical for them. This study is the first to take an EMA approach to describe short-term intention-behavior coupling in adults. Results suggest that adults have difficulty translating intentions into behavior at the momentary level, more so than over longer timescales, and that positive affect may be a key to successfully translating intentions into behavior.

SUBMITTER: Maher JP

PROVIDER: S-EPMC5684065 | biostudies-other | 2017 Dec

REPOSITORIES: biostudies-other

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Momentary assessment of physical activity intention-behavior coupling in adults.

Maher Jaclyn P JP Rhodes Ryan E RE Dzubur Eldin E Huh Jimi J Intille Stephen S Dunton Genevieve F GF

Translational behavioral medicine 20171201 4

Research attempting to elucidate physical activity (PA) intention-behavior relations has focused on differences in long-term behavior forecasting between people. However, regular PA requires a repeated performance on a daily or within-daily basis. An empirical case study application is presented using intensive longitudinal data from a study of PA in adults to (a) describe the extent to which short-term intention-behavior coupling occurs and (b) explore time-varying predictors of intention forma ...[more]

PMID: 28155108

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Project description:BackgroundStrategies to promote physical activity (PA) focus mainly on changing or fostering explicit cognitions and are only modestly effective. Contemporary studies suggest that, as well as explicit cognitions, implicit cognitions influence health behavior, such as PA, and that implicit processes interact with the intention to be active. Relatively little is known about whether implicit processes interact with other explicit cognitions which determine PA intention and behavior, i.e. self-efficacy. The aim of the current study was to investigate the direct effects of explicit cognitions and implicit attitudes on PA behavior as well as interactions between them regarding intention and behavior prediction.MethodsIn a longitudinal study, participants (N = 340) completed self-report measures of explicit cognitions (perceived pros, perceived cons, social norms, social modeling, self-efficacy, intention) and activity levels, as well as a Single-Category Implicit Association Task to measure implicit attitudes towards PA at baseline (T0), and at one (T1) and 3 months thereafter (T2).ResultsHierarchical multiple regressions revealed that T0-positive implicit attitudes moderated the relationship between T0 self-efficacy and T1 PA. Similarly, T0-neutral implicit attitudes were associated with the relationship between T0 intention and T1 PA. Negative implicit attitudes strengthened the negative relationship between perceived cons and intention at baseline; neutral or positive implicit attitudes strengthened the positive relationship between self-efficacy and intention. At the follow-ups, the relationship between social modeling and intention was strengthened by negative implicit attitudes.ConclusionThis study revealed important insights into how implicit attitudes and explicit cognitions synergistically predict PA intention and behavior. As well as targeting explicit cognitions, steering a person's implicit attitude towards a more positive one, i.e. by implicit cognitive trainings, could help to increase both PA intention and behavior.

Project description:INTRODUCTION:The purpose of this study was to examine the association between sedentary behavior (SB), cardiometabolic risk factors, and self-reported physical function by level of moderate-vigorous physical activity (MVPA). METHODS:Cross-sectional analysis was completed on 1914 older adults age ? 65 yr from the 2003-2006 U.S. National Health and Nutrition Examination Survey. MVPA and SB were derived from ActiGraph accelerometers worn for 1 wk. MVPA was categorized as sufficient to meet the current U.S. guidelines (? 150 min · wk(-1)) or not; SB was split into quartiles. Various biomarkers were examined in laboratory analyses and physical exams, and the number of functional limitations was self-reported. Statistical interaction between SB and MVPA on the biomarker associations was the primary analysis, followed by an examination of their independent associations with relevant covariate adjustment. RESULTS:Average SB was 9.4 ± 2.3 h · d(-1) (mean ± SD), and approximately 35% were classified as sufficiently active. Overall, no significant meaningful statistical interactions were found between SB and MVPA for any of the outcomes; however, strong independent positive associations were found between SB and weight (P < 0.01), body mass index (P < 0.01), waist circumference (P < 0.01), C-reactive protein (P < 0.01), plasma glucose (P = 0.04), and number of functional limitations (P < 0.01) after adjustment for MVPA. Similarly, MVPA was negatively associated with weight (P = 0.01), body mass index (P < 0.01), waist circumference (P < 0.01), diastolic blood pressure (P = 0.04), C-reactive protein (P < 0.01), and number of functional limitations (P < 0.01) after adjustment for SB. CONCLUSIONS:The results suggest that sufficient MVPA did not ameliorate the negative associations between SB and cardiometabolic risk factors or functional limitations in the current sample and that there was independence on a multiplicative scale in their associations with the outcomes examined. Thus, older adults may benefit from the joint prescription to accumulate adequate MVPA and avoid prolonged sitting.

Project description:PurposeA data mining approach was applied to establish a multilevel hierarchy predicting physical activity (PA) behavior, and to methodologically identify the correlates of PA behavior.MethodsCross-sectional data from the population-based Northern Finland Birth Cohort 1966 study, collected in the most recent follow-up at age 46, were used to create a hierarchy using the chi-square automatic interaction detection (CHAID) decision tree technique for predicting PA behavior. PA behavior is defined as active or inactive based on machine-learned activity profiles, which were previously created through a multidimensional (clustering) approach on continuous accelerometer-measured activity intensities in one week. The input variables (predictors) used for decision tree fitting consisted of individual, demographical, psychological, behavioral, environmental, and physical factors. Using generalized linear mixed models, we also analyzed how factors emerging from the model were associated with three PA metrics, including daily time (minutes per day) in sedentary (SED), light PA (LPA), and moderate-to-vigorous PA (MVPA), to assure the relative importance of methodologically identified factors.ResultsOf the 4582 participants with valid accelerometer data at the latest follow-up, 2701 and 1881 had active and inactive profiles, respectively. We used a total of 168 factors as input variables to classify these two PA behaviors. Out of these 168 factors, the decision tree selected 36 factors of different domains from which 54 subgroups of participants were formed. The emerging factors from the model explained minutes per day in SED, LPA, and/or MVPA, including body fat percentage (SED: B = 26.5, LPA: B = - 16.1, and MVPA: B = - 11.7), normalized heart rate recovery 60 s after exercise (SED: B = -16.1, LPA: B = 9.9, and MVPA: B = 9.6), average weekday total sitting time (SED: B = 34.1, LPA: B = -25.3, and MVPA: B = -5.8), and extravagance score (SED: B = 6.3 and LPA: B = - 3.7).ConclusionsUsing data mining, we established a data-driven model composed of 36 different factors of relative importance from empirical data. This model may be used to identify subgroups for multilevel intervention allocation and design. Additionally, this study methodologically discovered an extensive set of factors that can be a basis for additional hypothesis testing in PA correlates research.

Project description:BackgroundMany theoretical frameworks have been used in order to understand health behaviors such as physical activity, sufficient sleep, healthy eating habits, etc. In most research studies, determinants within these frameworks are assessed only once and thus are considered as stable over time, which leads to rather 'static' health behavior change interventions. However, in real-life, individual-level determinants probably vary over time (within days and from day to day), but currently, not much is known about these time-dependent fluctuations in determinants. In order to personalize health behavior change interventions in a more dynamic manner, such information is urgently needed.ObjectiveThe purpose of this study was to explore the time-dependent variability of emotions, physical complaints, intention, and self-efficacy in older adults (65+) using Ecological Momentary Assessment (EMA).MethodsObservational data were collected in 64 healthy older adults (56.3% men; mean age 72.1 ± 5.6 years) using EMA. Participants answered questions regarding emotions (i.e., cheerfulness, relaxation, enthusiasm, satisfaction, insecurity, anxiousness, irritation, feeling down), physical complaints (i.e., fatigue, pain, dizziness, stiffness, shortness of breath), intention, and self-efficacy six times a day for seven consecutive days using a smartphone-based questionnaire. Generalized linear mixed models were used to assess the fluctuations of individual determinants within subjects and over days.ResultsA low variability is present for the negative emotions (i.e., insecurity, anxiousness, irritation, feeling down) and physical complaints of dizziness and shortness of breath. The majority of the variance for relaxation, satisfaction, insecurity, anxiousness, irritation, feeling down, fatigue, dizziness, intention, and self-efficacy is explained by the within subjects and within days variance (42.9% to 65.8%). Hence, these determinants mainly differed within the same subject and within the same day. The between subjects variance explained the majority of the variance for cheerfulness, enthusiasm, pain, stiffness, and shortness of breath (50.2% to 67.3%). Hence, these determinants mainly differed between different subjects.ConclusionsThis study reveals that multiple individual-level determinants are time-dependent, and are better considered as 'dynamic' or unstable behavior determinants. This study provides us with important insights concerning the development of dynamic health behavior change interventions, anticipating real-time dynamics of determinants instead of considering determinants as stable within individuals.

Project description:BACKGROUND:Choice architecture interventions, which subtly change the environment in which individuals make decisions, can be used to promote behavior change. This systematic review aimed to summarize studies on micro-environmental choice architecture interventions that encouraged physical activity or discouraged sedentary behavior in adults, and to describe the effectiveness of those interventions on these behaviors - and on related intentions or health outcomes - in presence of the intervention and after removal of the intervention (i.e. post-intervention, regardless of the time elapsed). METHODS:We systematically searched PubMed, Embase, PsycINFO and the Cochrane Library for (quasi) experimental studies published up to December 2019 that evaluated the effect of choice architecture interventions on physical activity and sedentary behavior, as well as on intentions and health outcomes related to physical activity/sedentary behavior. Studies that combined choice architecture techniques with other behavior change techniques were excluded. All studies were screened for eligibility, relevant data was extracted and two independent reviewers assessed the methodological quality using the QualSyst tool. RESULTS:Of the 9609 records initially identified, 88 studies met our eligibility criteria. Most studies (n = 70) were of high methodologic quality. Eighty-six studies targeted physical activity, predominantly stair use, whereas two studies targeted sedentary behavior, and one targeted both behaviors. Intervention techniques identified were prompting (n = 53), message framing (n = 24), social comparison (n = 12), feedback (n = 8), default change (n = 1) and anchoring (n = 1). In presence of the intervention, 68% of the studies reported an effect of choice architecture on behavior, whereas after removal of the intervention only 47% of the studies reported a significant effect. For all choice architecture techniques identified, except for message framing, the majority of studies reported a significant effect on behavioral intentions or behavior in presence of the intervention. CONCLUSIONS:The results suggest that prompting can effectively encourage stair use in adults, especially in presence of a prompt. The effectiveness of the choice architecture techniques social influence, feedback, default change and anchoring cannot be assessed based on this review. More (controlled) studies are needed to assess the (sustained) effectiveness of choice architecture interventions on sedentary behavior and other types of physical activity than stair use.

Project description:BackgroundPhysical inactivity and sedentary behavior are major concerns for public health. Although global initiatives have been successful in monitoring physical activity (PA) worldwide, there is no systematic action for the monitoring of correlates of these behaviors, especially in low- and middle-income countries. Here we describe the prevalence and distribution of PA domains and sitting time in population sub-groups of six south American countries.MethodsData from the South American Physical Activity and Sedentary Behavior Network (SAPASEN) were used, which includes representative data from Argentina (n = 26,932), Brazil (n = 52,490), Chile (n = 3719), Ecuador (n = 19,851), Peru (n = 8820), and Suriname (n = 5170). Self-reported leisure time (≥150 min/week), (≥150 min/week), transport (≥10 min/week), and occupational PA total (≥10 min/week), as well as sitting time (≥4 h/day) were captured in each national survey. Sex, age, income, and educational status were exposures. Descriptive statistics and harmonized random effect meta-analyses were conducted.ResultsThe prevalence of PA during leisure (Argentina: 29.2% to Peru: 8.6%), transport (Peru: 69.7% to Ecuador: 8.8%), and occupation (Chile: 60.4 to Brazil 18.3%), and ≥4 h/day of sitting time (Peru: 78.8% to Brazil: 14.8%) differed widely between countries. Moreover, total PA ranged between 60.4% (Brazil) and 82.9% (Chile) among men, and between 49.4% (Ecuador) and 74.9% (Chile) among women. Women (low leisure and occupational PA) and those with a higher educational level (low transportation and occupational PA as well as high sitting time) were less active. Concerning total PA, men, young and middle-aged adults of high educational status (college or more) were, respectively, 47% [OR = 0.53 (95% CI = 0.36-0.78), I2 = 76.6%], 25% [OR = 0.75 (95% CI = 0.61-0.93), I2 = 30.4%] and 32% [OR = 0.68 (95% CI = 0.47-1.00), I2 = 80.3%] less likely to be active.ConclusionsPA and sitting time present great ranges and tend to vary across sex and educational status in South American countries. Country-specific exploration of trends and population-specific interventions may be warranted.

Project description:BackgroundDespite physical activity (PA) being recognized as a critically important factor for good physical and mental health already early in life and throughout the life course, prospective data on activity behavior during the preschool years remains scarce. This study examined trajectories and determinants of levels and change in total PA (TPA), moderate-to-vigorous PA (MVPA) and sedentary behavior (SB) in a representative sample of Swiss preschoolers.MethodsData were drawn from the Swiss Preschoolers' Health Study (SPLASHY), a multi-site prospective cohort study including 555 children (53% boys) aged 2-to-6 years at baseline. A follow-up was conducted after 12 months. Activity behavior was measured using accelerometers. Information on 35 potential determinants from different socio-ecological domains was either directly measured or parent-reported. Trajectories of TPA, MVPA and SB over time were described for boys and girls. Linear mixed models were used to investigate factors that predicted levels and change in TPA, MVPA and SB.ResultsAll children were sufficiently physically active according to published recommendations for preschoolers. Trajectory profiles revealed a marked increase in TPA and MVPA in boys and girls whereas SB remained fairly stable over time. Mixed modeling demonstrated that variables most relevant to determining PA levels were sex, age and activity temperament (all positively associated). Together with gross motor skills, birth weight, family structure (only for TPA) and season (only for MVPA), these factors accounted for 26 and 32% of total variance explained in TPA and MVPA, respectively. Activity temperament emerged as the strongest determinant of SB (negative association) and explained with sex, season and family structure 20% of total variance in SB. The presence of older siblings was the only factor that predicted change in PA over time.ConclusionsIn this healthy physically active cohort of preschoolers, non-modifiable individual-level factors had the greatest influence on PA. The limited success of this and previous studies to identify modifiable determinants and the finding that most preschoolers were sufficiently active suggest that future attempts should provide insights into how preschoolers' activity levels can be maintained and fostered to prevent subsequent harmful declines attributable, amongst others, to educational transitions. Thus, good-quality longitudinal studies are needed.Trial registrationCurrent Controlled Trials ISRCTN41045021 (date of registration: 21.03.14).

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Momentary assessment of physical activity intention-behavior coupling in adults.

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Momentary assessment of physical activity intention-behavior coupling in adults.

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