Associations of physical activity and screen-time on health related quality of life in adults

Background: Associations between the combined effect of physical activity and screen based activities on health related quality of life remain largely undetermined. Methods: During 2008–2010, cross-sectional data for self-reported health related quality of life, physical activity, and screen-time were collected for 3796 Australian adults. Logistic regression was conducted to examine associations for six combinations of physical activity (none, insufficient, and sufficient), and screen-time (low and high) on health related quality of life

Associations of overall sitting time and sitting time in different contexts with depression, anxiety, and stress symptoms

Spending a lot of time sitting has been linked to more depressive symptoms and spending a lot of time engaged in screen-based sitting has been linked to greater likelihood of having mental disorders and poorer psychological distress. The purpose of this study was to examine whether overall sitting time and time spent sitting in different contexts was associated with depression, anxiety, or stress symptoms

Understanding occupational sitting : prevalence, correlates and moderating effects in Australian employees

Objective. To (1) compare occupational sitting between different socio-demographic, health-related, workrelated and psychosocial categories, (2) identity socio-demographic, health-related, work-related and psychosocial correlates of occupational sitting, and (3) examine the moderating effect of work-related factors in the relation between correlates and occupational sitting.Methods. Randomly-selected Australian adults completed a web-based survey assessing socio-demographic (country of birth, gender, age, education, income), health-related (general health, weight, physical activity), work-related (employment status, occupational task, occupational classification) and sedentary-specific psychosocial (social norm, social support, self-efficacy, control, advantages, disadvantage, intention) factors, and occupational sitting-time. t-tests, ANOVAs and multiple linear regression analyses were conducted (in 2013) on a sample of employees (n= 993). Results. Respondents sat on average for 3.75 (SD = 2.45) h/day during work. Investigated correlates explained 41% of the variance in occupational sitting. More occupational sitting was associated with being male, being younger, higher education and income, part-time and full-time employment, sedentary job tasks, white-collar/professional occupations, higher BMI, and perceiving more advantages of sitting less at work. Employment status and occupational classification moderated the association between control to sit less and occupational sitting. A lack of control to sit less was associated with higher occupational sitting in part-time andfull-time workers, but not in casual workers; and in white-collar and professional workers, but not in bluecollar workers. Conclusions. Most important contributors to occupational sitting were work-related and socio-demographic correlates. More research is needed to confirm present results

Engagement, acceptability, usability and satisfaction with Active for Life, a computer-tailored web-based physical activity intervention using Fitbits in older adults

Background: Preliminary evidence suggests that web-based physical activity interventions with tailored advice and Fitbit integration are effective and may be well suited to older adults. Therefore, this study aimed to examine the engagement, acceptability, usability, and satisfaction with ‘Active for Life,’ a web-based physical activity intervention providing computer-tailored physical activity advice to older adults. Methods: Inactive older adults (n = 243) were randomly assigned into 3 groups: 1) tailoring + Fitbit, 2) tailoring only, or 3) a wait-list control. The tailoring + Fitbit group and the tailoring-only group received 6 modules of computer-tailored physical activity advice over 12 weeks. The advice was informed by objective Fitbit data in the tailoring + Fitbit group and self-reported physical activity in the tailoring-only group. This study examined the engagement, acceptability, usability, and satisfaction of Active for Life in intervention participants (tailoring + Fitbit n = 78, tailoring only n = 96). Wait-list participants were not included. Engagement (Module completion, time on site) were objectively recorded through the intervention website. Acceptability (7-point Likert scale), usability (System Usability Scale), and satisfaction (open-ended questions) were assessed using an online survey at post intervention. ANOVA and Chi square analyses were conducted to compare outcomes between intervention groups and content analysis was used to analyse program satisfaction. Results: At post-intervention (week 12), study attrition was 28% (22/78) in the Fitbit + tailoring group and 39% (37/96) in the tailoring-only group. Engagement and acceptability were good in both groups, however there were no group differences (module completions: tailoring + Fitbit: 4.72 ± 2.04, Tailoring-only: 4.23 ± 2.25 out of 6 modules, p =.14, time on site: tailoring + Fitbit: 103.46 ± 70.63, Tailoring-only: 96.90 ± 76.37 min in total, p =.56, and acceptability of the advice: tailoring + Fitbit: 5.62 ± 0.89, Tailoring-only: 5.75 ± 0.75 out of 7, p =.41). Intervention usability was modest but significantly higher in the tailoring + Fitbit group (tailoring + Fitbit: 64.55 ± 13.59, Tailoring-only: 57.04 ± 2.58 out of 100, p =.003). Participants reported that Active for Life helped motivate them, held them accountable, improved their awareness of how active they were and helped them to become more active. Conversely, many participants felt as though they would prefer personal contact, more detailed tailoring and more survey response options. Conclusions: This study supports web-based physical activity interventions with computer-tailored advice and Fitbit integration as engaging and acceptable in older adults. Trial registration: Australian and New Zealand Clinical Trials Registry: ACTRN12618000646246. Registered April 23 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374901</p

Physical activity recommendations from general practitioners in Australia. Results from a national survey

Objective: To identify subgroups of Australian adults likely to receive physical activity advicefrom their general practitioner and to evaluate the content of the advice provided. Methods: Participants (n=1,799), recruited from the Australian Health and Social Science panel, completed an online survey. Signal Detection Analysis was used to identify subgroups that were more/less likely to have received physical activity recommendations. Results: Overall, 18% of participants received a physical activity recommendation from their general practitioner in the past 12 months and eight unique subgroups were identified. The subgroup with the highest proportion (54%) of participants reporting that they received a physical activity recommendation was those with poor physical and mental health-related quality of life and an average daily sitting time of <11 hours. Other subgroups with high proportions of individuals receiving recommendations were characterised by higher weight and/or the presence of co-morbidities. The most commonly prescribed physical activity type was aerobic activity. Few participants received specific physical activity advice. Conclusions: General practitioners are incorporating physical activity promotion into their practice, but primarily as a disease management tool and with limited specificity. Implications: Strategies to assist Australian general practitioners to effectively promote physical activity are needed.</p