Intention has been an extremely important concept in physical activity theory and research but is complicated by a double-barreled definition of a decision to perform physical activity and the ...commitment to enact that decision. We put forth the hypothesis that these separate meanings have different measurement requirements, are situated in distinctly different intention-based models, and show discrete findings when explaining physical activity motives.
Physical activity theories have almost exclusively focused on conscious regulatory processes such as plans, beliefs, and expected value. The aim of this review was to aggregate the burgeoning ...evidence showing that physical activity is also partially determined by non-conscious processes (e.g., habits, automatic associations, priming effects). A systematic search was conducted and study characteristics, design, measures, effect size of the principle summary measures, and main conclusions of 52 studies were extracted by two independent coders. The findings support that habitual regulatory processes measured via self-report are directly associated with physical activity beyond conscious processes, and that there is likely interdependency between habit strength and intentions. Response latency measures of automatic associations with physical activity were widely disparate, precluding conclusions about specific effects. A small body of evidence demonstrated a variety of priming effects on physical activity. Overall, it is evident that physical activity is partially regulated by non-conscious processes, but there remain many unanswered questions for this area of research. Future research should refine the conceptualisation and measurement of non-conscious regulatory processes and determine how to harness them to promote physical activity.
Objective
Farmers are prone to poor well‐being and are at higher risks of suicide than the general population. The aim of this study was to understand whether the negative impact of daily stressors ...on Australian farmers' well‐being could be buffered through a strong internal locus of control – a strong sense of control over what happens in life.
Methods
Australian farmers self‐reported their well‐being, daily stress, and locus of control.
Design
Cross‐sectional via pen‐and‐paper survey.
Setting
Participants completed the surveys at the beginning of agricultural management training courses.
Participants
Australian farmers (N = 129, M age = 39 ± 12 years, 54.7% male).
Main Outcome Measures
Internal and external locus of control, daily stress, and subjective well‐being.
Results
More daily stressors were associated to poorer well‐being, regardless of external locus of control; however, farmers with a stronger internal locus of control were buffered from the negative impacts of daily stressors. That is, daily stressors were not significantly associated with well‐being for farmers with a strong internal locus of control.
Conclusions
Internal locus of control may be a significant factor in supporting good well‐being for farmers. Further research should investigate how to enhance internal locus of control amongst this population. It may be that interventions to enhance internal locus of control in farmers could improve their well‐being and productivity, good outcomes for the individual farmers, and global society overall.
To compare the frequency of and trends in healthy lifestyle factors between singles and couples.
Cross-sectional data from annual surveys conducted from 2005-2014 were used. The pooled sample ...included 15,001 Australian adults (mean age: 52.9 years, 50% male, 74% couples) who participated in the annual Queensland Social Survey via computer-assisted telephone interviews. Relationship status was dichotomised into single and couple. Binary logistic regression was used to assess associations between relationship status, and the frequency of and trends in healthy lifestyle factors.
Compared to singles, couples were significantly more likely to be a non-smoker (OR = 1.82), and meet recommendations for limited fast food (OR = 1.12), alcohol consumption (OR = 1.27) and fruit and vegetable intake (OR = 1.24). Fruit and vegetable intake was not significantly associated with relationship status after adjusting for the other healthy lifestyle factors. Conversely, couples were significantly less likely to be within a normal weight range (OR = 0.81). In both singles and couples, the trend data revealed significant declines in the rates of normal weight (singles: OR = 0.97, couples: OR = 0.97) and viewing TV for less than 14 hours per week (singles: OR = 0.85, couples: OR = 0.84), whilst non-smoking rates significantly increased (singles: OR = 1.12, couples: OR = 1.03). The BMI trend was no longer significant when adjusting for health behaviours. Further, in couples, rates of meeting recommendations for physical activity and fruit/vegetable consumption significantly decreased (OR = 0.97 and OR = 0.95, respectively), as did rates of eating no fast food (OR = 0.96). These trends were not significant when adjusting for the other healthy lifestyle factors. In singles, rates of meeting alcohol recommendations significantly increased (OR = 1.08).
Health behaviour interventions are needed in both singles and couples, but relationship status needs to be considered in interventions targeting alcohol, fast food, smoking and BMI. Further research is needed to understand why health behaviours differ by relationship status in order to further improve interventions.
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.
•Poor neighborhood conditions explain less frequent engagement in physical activity.•Poor neighborhood conditions explain a steeper decline in physical activity across aging.•Cognitive resources reduce the adverse influence of poor neighborhood conditions.•Both individual and contextual factors influence the pandemic of physical inactivity.
Lifestyle behaviours significantly contribute to high levels of chronic disease in older adults. The aims of the study were to compare the prevalence and the prevalence trends of health behaviours ...(physical activity, fruit and vegetable consumption, fast food consumption, TV viewing, smoking and alcohol consumption), BMI and a summary health behaviour indicator score in older (65+ years) versus younger adults (18-65 years). The self-report outcomes were assessed through the Queensland Social Survey annually between 2007-2014 (n = 12,552). Regression analyses were conducted to compare the proportion of older versus younger adults engaging in health behaviours and of healthy weight in all years combined and examine trends in the proportion of younger and older adults engaging in health behaviours and of healthy weight over time. Older adults were more likely to meet recommended intakes of fruit and vegetable (OR = 1.43, 95%CI = 1.23-1.67), not consume fast food (OR = 2.54, 95%CI = 2.25-2.86) and be non-smokers (OR = 3.02, 95%CI = 2.53-3.60) in comparison to younger adults. Conversely, older adults were less likely to meet the physical activity recommendations (OR = 0.86, 95%CI = 0.78-0.95) and watch less than 14 hours of TV per week (OR = 0.65, 95%CI = 0.58-0.74). Overall, older adults were more likely to report engaging in 3, or at least 4 out of 5 healthy behaviours. The proportion of both older and younger adults meeting the physical activity recommendations (OR = 0.97, 95%CI = 0.95-0.98 and OR = 0.94, 95%CI = 0.91-0.97 respectively), watching less than 14 hours of TV per week (OR = 0.96, 95%CI = 0.94-0.99 and OR = 0.94, 95%CI = 0.90-0.99 respectively) and who were a healthy weight (OR = 0.95, 95%CI = 0.92-0.99 and OR = 0.96, 95%CI = 0.94-0.98 respectively) decreased over time. The proportion of older adults meeting the fruit and vegetable recommendations (OR = 0.90, 95%CI = 0.84-0.96) and not consuming fast food (OR = 0.94, 95%CI = 0.88-0.99) decreased over time. Although older adults meet more health behaviours than younger adults, the decreasing prevalence of healthy nutrition behaviours in this age group needs to be addressed.
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.
Bedtime procrastination is defined as the volitional delay of going to bed, without any external circumstances causing the delay, and is associated with inadequate sleep. Alleviating bedtime ...procrastination is an important target for interventions promoting adequate sleep, yet the correlates of bedtime procrastination are poorly understood. This study examined (1) correlates of bedtime procrastination, and (2) strength and direction of the association between bedtime procrastination and sleep outcomes. Six databases (CINAHL, EMBASE, PsychINFO, PubMed, Scopus, Web of Science) were searched from inception to September 2021 against pre-determined eligibility criteria. Forty-three studies were included (GRADE = low). Meta-analysis revealed that bedtime procrastination had a moderate negative association with self-control (z = −0.39; CI: −0.45, −0.29) and a moderate positive association with evening chronotype (z = 0.43; CI: 0.32, 0.48). Furthermore, bedtime procrastination was moderately negatively associated with sleep duration (z = −0.31; CI: −0.37, −0.24), sleep quality (z = −0.35; CI: −0.42, −0.27) and moderately positively associated with daytime fatigue (z = 0.32; CI: 0.25, 0.38). Further high-quality studies are needed to identify causal relationships between bedtime procrastination and correlates, as well as bedtime procrastination and sleep. Future work will guide the development of interventions targeting bedtime procrastination for improved sleep outcomes.
PROSPERO registration number CRD42021248891.
Skin cancer is highly burdensome, but preventable with regular engagement in sun protective behaviors. Despite modest effectiveness of sun-protective behavior promotional efforts thus far, rates of ...engagement in sun-protective behaviors remain low. More is needed to understand motivation for using sunscreen, wearing sun-protective clothing, and seeking shade. This study tested whether the links of intention and habit strength with behavior differed between sun-protective behaviors. It was hypothesized that sun protective behaviors would be predicted by both habit and intention and that intention-behavior associations would be weaker for people with stronger habits. Participants residing in Queensland, Australia (N = 203; 75.96% female; M age = 37.16 years, SD = 14.67) self-reported their intentions and habit strength about sun-protective behavior for the next 7 days. Participants were followed-up 7 days later to self-report their sun-protective behavior. Multilevel modeling, accounting for nesting of multiple behaviors within-person, revealed that habit moderated the intention strength - behavior association and this moderation effect did not differ as a function of which behavior was being predicted. People with strong or moderate habit strength tended to act in line with their intentions; however, for people with very weak habits (2 SD < M), there was less alignment between their intention and behavior. These findings suggest that habit plays a facilitative role in the implementation of strong sun protective behavior intentions. Interventions should consider how to encourage intention and habit to enhance sun-protective behaviors and reduce the burden of skin cancer from sun exposure.
Supplemental data for this article is available online at https://doi.org/10.1080/08964289.2021.1903380 .
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