The influence of context stability on physical activity and sedentary behaviour habit and behaviour: An ecological momentary assessment study

OBJECTIVES

This study used ecological momentary assessment (EMA) to empirically test the theoretical propositions that habit for and level of physical activity (PA) and sedentary behaviour (SB) should be associated with degree of context stability of those behaviours.

DESIGN

Older adults (N = 104) completed a 10-day EMA protocol and continuous accelerometer monitoring.

METHODS

As part of the EMA protocol older adults answered 6 EMA prompts per day to assess current behaviour as well as social and physical contexts of behaviour. Temporal context was determined via time stamps of EMA questionnaires. Context stability was calculated as the reversed entropy scores of the contexts (physical, social, temporal, behavioural [i.e., type]) of PA and SB weighted for total frequency of context prompts. Habit for PA and SB (operationalized as self-reported behavioural automaticity) was assessed via baseline questionnaire. An ActivPAL monitor was worn to assess average daily time spent in moderate-vigorous PA (MVPA), light PA, and SB, and number of sit-to-stand transitions.

RESULTS

More stable physical contexts for physical activity predicted more MVPA (β = 10.22) and more stable social contexts for sitting predicted more SB (β = 1.36). More variety of time people tended to report engaging in SB, the more SB engaged in (β = -13.76). No context stability scores predicted light PA, sit-to-stand transitions, or habit.

CONCLUSIONS

Although context stability was related to behaviour, this did not appear to be explained by habit, as habit did not differ by the degree of context stability surrounding bouts of PA or SB.

Music Listening Predicted Improved Life Satisfaction in University Students During Early Stages of the COVID-19 Pandemic

Quarantine and spatial distancing measures associated with COVID-19 resulted in substantial changes to individuals’ everyday lives. Prominent among these lifestyle changes was the way in which people interacted with media—including music listening. In this repeated assessment study, we assessed Australian university students’ media use (i.e., listening to music, playing video/computer games, watching TV/movies/streaming videos, and using social media) throughout early stages of the COVID-19 pandemic in Australia, and determined whether media use was related to changes in life satisfaction. Participants (N = 127) were asked to complete six online questionnaires, capturing pre- and during-pandemic experiences. The results indicated that media use varied substantially throughout the study period, and at the within-person level, life satisfaction was positively associated with music listening and negatively associated with watching TV/videos/movies. The findings highlight the potential benefits of music listening during COVID-19 and other periods of social isolation.

Perceived daily tension and food cravings and consumption: A within- and between-person investigation

Previous research examining the relationship between negative states such as tension/anxiety and food intake has typically overlooked the naturally occurring variability of day-to-day experiences and the subsequent consequences for eating behavior. In this study, the relationship of within- and between-person perceived daily tension with food cravings and consumption was assessed. One hundred and forty-two men and women (M_age=21.3, SD_age=5.3) completed a survey daily for 7 consecutive days. Levels of perceived daily tension, food cravings, and consumption were assessed. Linear and logistic mixed effect regression models were used to examine associations between tension and food cravings and consumption variables, respectively. Individuals reported greater cravings (for sweets, OR 95% CI 1.05-1.26; carbohydrates/starches, OR 95% CI 1.02-1.26; and fast foods, OR 95% CI 1.01-1.19) and consuming more carbohydrates/starches (b 95% CI 0.05-0.79) on days when they felt more tension. Individuals with higher tension had more cravings (total OR 95% CI 1.09-1.71; and specifically for sweets, OR 95% CI 1.04-1.42; and fast foods, OR 95% CI 1.15-1.54) and reported consuming more sweet (b 95% CI 0.21-1.10) and fast foods (b 95% CI 0.55-1.66). These findings suggest that greater perceived tension (both within and between individuals) is associated with increased food cravings and consumption.

Effects of an Activity Tracker and App Intervention to Increase Physical Activity in Whole Families-The Step It Up Family Feasibility Study

(1) Background: Interventions using activity trackers and smartphone apps have demonstrated their ability to increase physical activity in children and adults. However, they have not been tested in whole families. Further, few family-centered interventions have actively involved both parents and assessed physical activity effects separately for children, mothers and fathers. Objective: To examine the feasibility and short-term effects of an activity tracker and app intervention to increase physical activity in the whole family (children, mothers and fathers). (2) Methods: This was a single-arm feasibility study with pre-post intervention measures. Between 2017-2018, 40 families (58 children aged 6-10 years, 39 mothers, 33 fathers) participated in the 6-week Step it Up Family program in Queensland, Australia. Using commercial activity trackers combined with apps (Garmin Vivofit Jr for children, Vivofit 3 for adults; Garmin Australasia Pty Ltd., Sydney, Australia), the intervention included individual and family-level goal-setting, self-monitoring, performance feedback, family step challenges, family social support and modelling, weekly motivational text messages and an introductory session. Parent surveys were used to assess physical activity effects measured as pre-post intervention changes in moderate-to-vigorous physical activity (MVPA) in children, mothers and fathers. Objective Garmin activity tracker data was recorded to assess physical activity levels (steps, active minutes) during the intervention. (3) Results: Thirty-eight families completed the post intervention survey (95% retention). At post intervention, MVPA had increased in children by 58 min/day (boys: 54 min/day, girls: 62 min/day; all p < 0.001). In mothers, MVPA increased by 27 min/day (p < 0.001) and in fathers, it increased by 31 min/day (p < 0.001). The percentage of children meeting Australia's physical activity guidelines for children (≥60 MVPA min/day) increased from 34% to 89% (p < 0.001). The percentage of mothers and fathers meeting Australia's physical activity guidelines for adults (≥150 MVPA min/week) increased from 8% to 57% (p < 0.001) in mothers and from 21% to 68% (p < 0.001) in fathers. The percentage of families with 'at least one child and both parents' meeting the physical activity guidelines increased from 0% to 41% (p < 0.001). Objective activity tracker data recorded during the intervention showed that the mean (SD) number of active minutes per day in children was 82.1 (17.1). Further, the mean (SD) steps per day was 9590.7 (2425.3) in children, 7397.5 (1954.2) in mothers and 8161.7 (3370.3) in fathers. (4) Conclusions: Acknowledging the uncontrolled study design, the large pre-post changes in MVPA and rather high step counts recorded during the intervention suggest that an activity tracker and app intervention can increase physical activity in whole families. The Step it Up Family program warrants further efficacy testing in a larger, randomized controlled trial.

Methods and design for the ADAPT study: Application of integrateD Approaches to understanding Physical activity during the Transition to emerging adulthood

BACKGROUND

The overarching objective of the study is to obtain a comprehensive understanding of the salient factors predicting changes in physical activity (PA) during adolescents' transition into emerging adulthood. Using the Multi-Process Action Control model as our guiding framework, we will examine how implicit and explicit psychological processes along with regulatory practices impact PA change during this major life transition. Additionally, we will use a real-time data capture method called Ecological Momentary Assessment to further investigate how environmental and contextual factors, and momentary psychosocial influences effect PA patterns across this dynamic life stage.

METHODS

The ADAPT study is a 4-year project comprised of two interrelated studies. Study I is a large prospective cohort study that will invite all grade 11 students across one large school board (a total of seven secondary schools) to participate by completing an online questionnaire. Using a cluster randomization approach, a subset of students from each school will be invited to participate in Study II, whereby participants will wear an accelerometer and complete Ecological Momentary Assessments 5 times a day over a 7-day study period. For both studies, following baseline assessments, there will be three annual follow-up assessments approximately 12 months apart.

DISCUSSION

The current study represents one of the largest longitudinal cohort studies examining PA and its determinants and associated consequences among adolescents transitioning out of high school into emerging adulthood. Findings from this study will provide a much more in-depth understanding of how and why changes in PA behaviour occur across this first major life transition.

A focus group study of older adults' perceptions and preferences towards web-based physical activity interventions

OBJECTIVE

To explore older adults' perceptions and preferences for web-based physical activity interventions.

PARTICIPANTS

Adults 65+ years were recruited via telephoning randomly selected households in Central Queensland, Australia.

METHODS

Six focus groups were conducted with a total of 46 adults 65+ years. Data were analyzed by qualitative content analysis.

RESULTS

This group of older adults liked websites that have links to information and included instructional videos and disliked websites that were hard to navigate. Many participants did not express an initial interest in web-based physical activity programs. The most common reason was that they did not have a computer or adequate internet connection. Some participants said they would be interested if it included a structured exercise program. When asked about preferences for web-based physical activity programs, this group preferred them to be simple and not cluttered, to include personalized advice, to include reminder check-ins and the ability to review goals after illness or injury. The most common preference for personalized advice in web-based interventions was that the information needs to be tailored to their existing injuries and illnesses.

CONCLUSION

The findings from this study will inform the design of future web-based interventions specifically tailored to the needs of older people.

Is sitting invisible? Exploring how people mentally represent sitting

Background

Growing evidence suggests that prolonged uninterrupted sitting can be detrimental to health. Much sedentary behaviour research is reliant on self-reports of sitting time, and sitting-reduction interventions often focus on reducing motivation to sit. These approaches assume that people are consciously aware of their sitting time. Drawing on Action Identification Theory, this paper argues that people rarely identify the act of sitting as ‘sitting’ per se, and instead view it as an incidental component of more meaningful and purposeful typically-seated activities.

Methods

Studies 1 and 2 explored whether people mentioned sitting in written descriptions of actions. Studies 3–5 compared preferences for labelling a typically desk-based activity as ‘sitting’ versus alternative action identities. Studies 6 and 7 used card-sort tasks to indirectly assess the prioritisation of ‘sitting’ relative to other action descriptions when identifying similar actions.

Results

Participants rarely spontaneously mentioned sitting when describing actions (Studies 1–2), and when assigning action labels to a seated activity, tended to offer descriptions based on higher-order goals and consequences of action, rather than sitting or other procedural elements (Studies 3–5). Participants primarily identified similarities in actions based not on sitting, but on activities performed while seated (e.g. reading; Studies 6–7).

Conclusion

‘Sitting’ is a less accessible cognitive representation of seated activities than are representations based on the purpose and implications of seated action. Findings suggest that self-report measures should focus on time spent in seated activities, rather than attempting to measure sitting time via direct recall. From an intervention perspective, findings speak to the importance of targeting behaviours that entail sitting, and of raising awareness of sitting as a potential precursor to attempting to reduce sitting time.

Cognitive resources moderate the adverse impact of poor perceived neighborhood conditions on self-reported physical activity of older adults

Poor neighborhood conditions are associated with lower levels of physical activity for older adults but socio-ecological models posit that physical activity depends on both environmental and individual factors. Older adults' ability to overcome environmental barriers to physical activity may partially rely on cognitive resources. However, evidence on the moderating role of these cognitive resources in the associations between environmental barriers and physical activity is still lacking. We analyzed cross-national and longitudinal data on 28,393 adults aged 50 to 96 years as part of the SHARE. Lack of access to services and neighborhood nuisances were used as indicators of poor neighborhood conditions. Delayed recall and verbal fluency were used as indicators of cognitive resources. Confounder-adjusted generalized estimation equations were conducted to test associations between neighborhood conditions and self-reported moderate physical activity, as well as the moderating role of cognitive resources. Results showed that poor neighborhood conditions reduced the odds of engagement in physical activity. Cognitive resources robustly reduced the adverse influence of poor neighborhood conditions on physical activity. Participants with lower cognitive resource scores showed lower odds of engaging in physical activity when neighborhood conditions were poorer, whereas these conditions were not related to this engagement for participants with higher cognitive resource scores. These findings suggest that cognitive resources can temper the detrimental effect of poor neighborhood conditions on physical activity. Public policies should target both individual and environmental factors to tackle the current pandemic of physical inactivity more comprehensively.

How we are misinterpreting physical activity intention - behavior relations and what to do about it

Background

Studies of the physical activity intention-behavior gap, and factors that may moderate the gap (e.g., habit, perceived behavioral control), can inform physical activity promotion efforts. Yet, these studies typically apply linear modeling procedures, and so conclusions rely on linearity and homoscedasticity assumptions, which may not hold.

Methods

We modelled and plotted physical activity intention-behavior associations and the moderation effects of habit using simulated data based on (a) normal distributions with no shared variance, (b) correlated parameters with normal distribution, and (c) realistically correlated and non-normally distributed parameters.

Results

In the uncorrelated and correlated normal distribution datasets, no violations were unmet, and the moderation effects applied across the entire data range. However, because in the realistic dataset, few people who engaged in physical activity behavior had low intention scores, the intention-behavior association was non-linear, resulting in inflated linear moderation estimations of habit. This finding was replicated when tested with intention-behavior moderation of perceived behavioral control.

Conclusions

Comparisons of the three scenarios illustrated how an identical correlation coefficient may mask different types of intention-behavior association and moderation effects. These findings highlight the risk of misinterpreting tests of the intention-behavior gap and its moderators for physical activity due to unfounded statistical assumptions. The previously well-documented moderating effects of habit, whereby the impact of intention on behavior weakens as habit strength increases, may be based on statistical byproducts of unmet model assumptions.

Should I sit or stand: likelihood of adherence to messages about reducing sitting time

Background

High population levels of sitting is contributing to high rates of chronic health problems. Therefore, the aim of this study was to identify the sitting time messages with the greatest potential to reduce sitting behaviour, as well as identify how this may differ according to demographic, behavioural and psychosocial characteristics.

Methods

Australian adults (N = 1460) were asked to report the likelihood that they would adhere to seven messages promoting reduced sitting time and two messages promoting increased physical activity (from ‘not at all likely’ to ‘very likely’). Ordinal regression models were used to compare messages on the likelihood of adherence and whether likelihood of adherence differed as a function of demographic, psychosocial and behavioural characteristics.

Results

Likelihood of adherence was highest for the messages, ‘Stand and take a break from sitting as frequently as you can’ (83% respectively) and ‘Avoid sitting for more than 10 hours during the entire day’ (82%) and was significantly lower for the message, ‘Sit as little as possible on all days of the week’ (46%) compared to all other messages.

Conclusions

To increase likelihood of adherence messages should be specific, achievable and promote healthy alternatives to sitting (e.g. standing). Messages promoting standing as a healthy alternative to sitting may be more likely to engage people with high sitting behaviour and messages promoting physical activity may be more likely to engage males and retired adults.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7189-z) contains supplementary material, which is available to authorized users.

Validity and responsiveness to change of the Active Australia Survey according to gender, age, BMI, education, and physical activity level and awareness

BACKGROUND

This study aimed to investigate the validity of the Active Australia Survey across different subgroups and its responsiveness to change, as few previous studies have examined this.

METHODS

The Active Australia Survey was validated against the ActiGraph as an objective measure of physical activity. Participants (n = 465) wore the ActiGraph for 7 days and subsequently completed the Active Australia Survey. Moderate activity, vigorous activity and total moderate and vigorous physical activity were compared using Spearman rank-order correlations. Changes in physical activity between baseline and 3-month assessments were correlated to examine responsiveness to change. The data were stratified to assess outcomes according to different subgroups (e.g., gender, age, weight, activity levels).

RESULTS

With regards to the validity, a significant correlation of ρ = 0.19 was found for moderate physical activity, ρ = 0.33 for vigorous physical activity and ρ = 0.23 for moderate and vigorous physical activity combined. For vigorous physical activity correlations were higher than 0.3 for most subgroups, whereas they were only higher than 0.3 in those with a healthy weight for the other activity outcomes. With regards to responsiveness to change, a correlation of ρ = 0.32 was found for moderate physical activity, ρ = 0.19 for vigorous physical activity and ρ = 0.35 for moderate and vigorous physical activity combined. For moderate and vigorous activity combined correlations were higher than 0.4 for several subgroups, but never for vigorous physical activity.

CONCLUSIONS

Little evidence for the validity of Active Australia Survey was found, although the responsiveness to change was acceptable for several subgroups. Findings from studies using the Active Australia Survey should be interpreted with caution.

TRIAL REGISTRATION

World Health Organisation Universal Trial Number: U111-1119-1755. Australian New Zealand Clinical Trials Registry, ACTRN12611000157976 . Registration date: 8 March 2011.

Impact of increasing social media use on sitting time and body mass index

Issue addressed Sedentary behaviours, in particular sitting, increases the risk of cardiovascular disease, type 2 diabetes, obesity and poorer mental health status. In Australia, 70% of adults sit for more than 8h per day. The use of social media applications (e.g. Facebook, Twitter, and Instagram) is on the rise; however, no studies have explored the association of social media use with sitting time and body mass index (BMI). Methods Cross-sectional self-report data on demographics, BMI and sitting time were collected from 1140 participants in the 2013 Queensland Social Survey. Generalised linear models were used to estimate associations of a social media score calculated from social media use, perceived importance of social media, and number of social media contacts with sitting time and BMI. Results Participants with a high social media score had significantly greater sitting times while using a computer in leisure time and significantly greater total sitting time on non-workdays. However, no associations were found between social media score and sitting to view TV, use motorised transport, work or participate in other leisure activities; or total workday, total sitting time or BMI. Conclusions These results indicate that social media use is associated with increased sitting time while using a computer, and total sitting time on non-workdays. So what? The rise in social media use may have a negative impact on health by contributing to computer sitting and total sitting time on non-workdays. Future longitudinal research with a representative sample and objective sitting measures is needed to confirm findings.

A Test of How Australian Adults Allocate Time for Physical Activity

The most common reported barrier to physical activity is a lack of sufficient time. Just like most resources in economics are finite, so too is time within a day. We utilized a time-utility model to better understand how people are allocating time for physical activity. Additionally, we tested whether the allocation of physical activity time impacts people's perception of "lack of time" as a barrier for physical activity or their likelihood of being sufficiently physical active. Australian adults (N = 725 participants, 54% men) reported their time use throughout their day, perceived lack of time as a barrier to activity, and physical activity. Cluster analysis and χ²-tests were used to test the study research questions. People tended to either be entirely inactive (29%) or active while doing either leisure (18%), occupation (18%), transport (14%), or household (22%) activities. Those who were active during their leisure or transport time were most likely to be sufficiently active. There were no significant differences among clusters in how much people perceived that lack of time was a physical activity barrier. The commonly reported barrier of not having enough time to be active might be a fallacy. Although a lack of time is a commonly reported barrier of physical activity, these findings bring to light that increasing physical activity behavior is not as simple as adding more time to the day.

Health behaviours of Australian fly-in, fly-out workers and partners during on-shift and off-shift days: an ecological momentary assessment study

OBJECTIVES

Fly-in, fly-out (FIFO) work involves long commutes, living on-site for consecutive days and returning home between shifts. This unique type of work requires constant transitioning between the roles and routines of on-shift versus off-shift days. This study aims to examine health behaviour patterns of FIFO workers and FIFO partners during on-shift and off-shift time frames.

DESIGN

This study used ecological momentary assessment and multilevel modelling to examine daily health behaviours.

SETTING

FIFO workers and FIFO partners from across Australia responded to daily online surveys for up to 7 days of on-shift and up to 7 days of off-shift time frames.

PARTICIPANTS

Participants included 64 FIFO workers and 42 FIFO worker partners.

RESULTS

Workers and partners reported poorer sleep and nutrition quality for on-shift compared with off-shift days. Both workers and partners exercised less, smoked more cigarettes, took more physical health medication and drank less alcohol during on-shift compared with off-shift days.

CONCLUSIONS

FIFO organisations should consider infrastructure changes and support services to enhance opportunities for quality sleep and nutrition, sufficient exercise, moderate alcohol consumption and cigarette cessation for workers on-site and their partners at home.

The Effectiveness of a Web-Based Computer-Tailored Physical Activity Intervention Using Fitbit Activity Trackers: Randomized Trial

BACKGROUND

Web-based interventions that provide personalized physical activity advice have demonstrated good effectiveness but rely on self-reported measures of physical activity, which are prone to overreporting, potentially reducing the accuracy and effectiveness of the advice provided.

OBJECTIVE

This study aimed to examine whether the effectiveness of a Web-based computer-tailored intervention could be improved by integrating Fitbit activity trackers.

METHODS

Participants received the 3-month TaylorActive intervention, which included 8 modules of theory-based, personally tailored physical activity advice and action planning. Participants were randomized to receive the same intervention either with or without Fitbit tracker integration. All intervention materials were delivered on the Web, and there was no face-to-face contact at any time point. Changes in physical activity (Active Australia Survey), sitting time (Workforce Sitting Questionnaire), and body mass index (BMI) were assessed 1 and 3 months post baseline. Advice acceptability, website usability, and module completion were also assessed.

RESULTS

A total of 243 Australian adults participated. Linear mixed model analyses showed a significant increase in total weekly physical activity (adjusted mean increase=163.2; 95% CI 52.0-274.5; P=.004) and moderate-to-vigorous physical activity (adjusted mean increase=78.6; 95% CI 24.4-131.9; P=.004) in the Fitbit group compared with the non-Fitbit group at the 3-month follow-up. The sitting time and BMI decreased more in the Fitbit group, but no significant group × time interaction effects were found. The physical activity advice acceptability and the website usability were consistently rated higher by participants in the Fitbit group. Non-Fitbit group participants completed 2.9 (SD 2.5) modules, and Fitbit group participants completed 4.4 (SD 3.1) modules.

CONCLUSIONS

Integrating physical activity trackers into a Web-based computer-tailored intervention significantly increased intervention effectiveness.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12616001555448; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371793 (Archived by WebCite at http://www.webcitation.org/73ioTxQX2).

How are different levels of knowledge about physical activity associated with physical activity behaviour in Australian adults?

People with knowledge of the benefits of physical activity tend to be more active; however, such knowledge is typically operationalized as a basic understanding that physical activity is 'good' for health. Therefore, the aim of this study was to investigate whether there are differences in how detailed a person's knowledge is about the benefits of physical activity. Participants (N = 615) completed an online survey to measure their current physical activity behaviour, as well as their level of knowledge of the benefits and risks of physical (in)activity. The majority of participants (99.6%) strongly agreed that physical activity is good for health, however on average, participants only identified 13.8 out of 22 diseases associated with physical inactivity and over half of participants (55.6%) could not identify how much physical activity is recommended for health benefits. Furthermore, 45% of the participants overestimated, 9% underestimated and 27% did not know the increased risk of disease resulting from inactivity as indicated by the Australian Department of Health. Participants were significantly more active when they correctly identified more diseases associated with physical inactivity and when they overestimated the risks associated with inactivity. Therefore, health promotion initiatives should increase knowledge of the types of diseases associated with inactivity. Low knowledge of physical activity guidelines suggest they should be promoted more, as this knowledge provides guidance on frequency, types and duration of physical activity needed for health.

Can you elaborate on that? Addressing participants' need for cognition in computer-tailored health behavior interventions

Computer-tailored interventions, which deliver health messages adjusted based on characteristics of the message recipient, can effectively improve a range of health behaviours. Typically, the content of the message is tailored to user demographics, health behaviours and social cognitive factors (e.g., intentions, attitudes, self-efficacy, perceived social support) to increase message relevance, and thus the extent to which the message is read, considered and translated into attitude and behaviour change. Some researchers have suggested that the efficacy of computer-tailored interventions may be further enhanced by adapting messages to suit recipients' need for cognition (NFC) - a personality trait describing how individuals tend to process information. However, the likely impact of doing so, especially when tailored in conjunction with other variables, requires further consideration. It is possible that intervention effects may be reduced in some circumstances due to interactions with other variables (e.g., perceived relevance) that also influence information processing. From a practical point of view, it is also necessary to consider how to optimally operationalise and measure NFC if it is to be a useful tailoring variable. This paper aims to facilitate further research in this area by critically examining these issues based on relevant theories and existing evidence.