Search

Background: Behavioral interventions targeted at managing Type 2 diabetes mellitus (T2DM) may have a positive effect on quality of life (QOL). Limited reviews have synthesized this effect in low- and middle-income countries (LMICs). This review and meta-analysis synthesised available evidence on the effect of behavioral interventions to manage T2DM on the QOL of people with T2DM in LMICs. Methods: Electronic databases PUBMED/MEDLINE, SCOPUS, CINAHL, Embase, Web of Science and PsycINFO were searched from May to June 2022. Studies published between January 2000 and May 2022, conducted in LMICs using randomized controlled trial design, using a health behavior intervention for T2DM management, and reporting QOL outcomes were included. Difference in QOL change scores between the intervention and control group was calculated as the standardized mean difference (SMD) of QOL scores observed between the intervention and control groups. Random-effects model was used for meta-analysis. Results: Of 6122 studies identified initially, 45 studies met the inclusion criteria (n = 8336). Of them, 31 involved diabetes self-management education and 14 included dietary and/or physical activity intervention. There was moderate quality evidence from the meta-analysis of mean QOL (n = 25) that health behavior intervention improved the QOL of people with T2DM (SMD = 1.62, 95%CI = 0.65–2.60 I2 = 0.96, p = 0.001). However, no significant improvements were found for studies (n = 7) separately assessing the physical component summary (SMD = 0.76, 95%CI = -0.03–1.56 I2 = 0.94, p = 0.060) and mental component summary (SMD = 0.43, 95%CI = -0.30–1.16 I2 = 0.94, p = 0.249) scores. High heterogeneity and imprecise results across studies resulted in low to moderate quality of evidence. Conclusion: The findings suggest that health behavior interventions to manage T2DM may substantially improve the QOL of individuals with T2DM over short term. However, due to low to moderate quality of evidence, further research is required to corroborate our findings. Results of this review may guide future research and have policy implications for T2DM management in LMICs. [ABSTRACT FROM AUTHOR]

Objective: This study examined adherence to dietary guidelines and symptoms of sleep problems (e.g. taking a long time to fall sleep or waking up early) and their associations in a sample of older Australian women (68–73 years of age). Design: This was a population-based cross-sectional study. Adherence to the dietary guidelines was measured using a validated FFQ and reported as a diet quality score. Symptoms of sleep problems were measured using five questions and a total score was derived. Multivariate linear regression was used to investigate the association between these outcomes, adjusted for the potential confounding influence of demographic (i.e. age and marital status) and lifestyle (i.e. physical activity, stress, alcohol intake, sleep medication use) variables. Setting: Respondents from the 1946–1951 cohort of the Australian Longitudinal Study on Women's Health who completed Survey 9 were included. Participants: Data from n 7956 older women (mean age ± sd: 70·8 ± 1·5) were included. Results: 70·2 % reported having at least one symptom and 20·5 % had between 3 and 5 symptoms of sleep problems (mean score ± sd: 1·4 ± 1·4, range 0–5). Adherence to dietary guidelines was poor with an average diet quality score of 56·9 ± 10·7 (range 0–100). Better adherence to dietary guidelines was associated with fewer sleep problem symptoms (β : –0·065, 95 % CI: –0·012, –0·005) and remained significant after adjusting for confounding influences. Conclusions: These findings support the evidence that adherence to dietary guidelines is associated with symptoms of sleep problems in older women. [ABSTRACT FROM AUTHOR]

Background: Physical activity is associated with depression. However, benefits of physical activity on depression may differ for specific domains of physical activity (i.e., leisure-time, work, and travel). Moreover, the relationship between physical activity and depression could also differ for people in different Body Mass Index (BMI) categories. This study investigated the relationship between domain-specific physical activity and BMI with depression, and the moderation effects of BMI on the relationship between domain physical activity and depression.Methods: Complex survey data from the NHANES 2011-2014 was used (N=10,047). Depression was measured using the Patient Health Questionnaire (PHQ-9). Participants reported physical activity minutes in each domain using the Global Physical Activity Questionnaire. Demographic characteristics were self-reported. Weight and height were objectively measured and used for calculating BMI. Survey procedures were used to account for complex survey design. As two survey cycles were used, sampling weights were re-calculated and used for analyses. Taylor series linearisation was chosen as a variance estimation method.Results: Participants who engaged in ≥150 minutes/week of total moderate-vigorous physical activity (MVPA) (adjusted B = 0.83, 95% CI [0.50, 1.16]) and leisure-time MVPA (adjusted B = 0.84, 95% CI [0.57, 1.11]) experienced lower levels of depression compared to those engaging in <150 MVPA minutes/week. Work and travel-related physical activity were not associated with depression. Overweight (adjusted B = -0.40, 95% CI [-0.76, -0.04]) and underweight/normal weight participants (adjusted B = -0.60, 95%CI [-0.96, -0.25]) experienced less depressive symptoms compared to obese participants. BMI did not moderate the relationship between domain-specific physical activity and depression.Conclusions: Interventions that focus on leisure-time physical activity appear to be best suited to improve depression, however, this needs to be confirmed in purposefully designed intervention studies. Future studies may also examine ways to improve the effectiveness of work and travel physical activity for reducing depression. [ABSTRACT FROM AUTHOR]

This study aimed to investigate awareness of having hypertension, diabetes and dyslipidaemia and their associated factors among US adults.Data from the National Health and Nutrition Examination Survey, including 21,399 adults aged ⩾20 years (pregnant women excluded) collected between 2011 and 2018, were used. Blood pressure was measured using a Baumanometer calibrated mercury true gravity wall model sphygmomanometer. Serum total cholesterol levels were measured using enzymatic assays. The percentage of haemoglobin A1C (HbA1c), which reflects long-term blood glucose levels, was measured and used to identify diabetes. Participants self-reported whether they were told by a doctor that they have hypertension, dyslipidaemia and diabetes. Awareness was defined as alignment between objective and self-reported measures for having the conditions. Sampling weights and the Taylor series linearisation variance estimation method were used in the analyses.The findings showed that 64.06% of people with hypertension, 54.71% of those with dyslipidaemia and 78.40% of those with diabetes were aware of having the respective condition. Age, sex and health insurance were associated with awareness of having all three conditions, but marital status was not associated with any outcome. Weight status was associated with awareness of having hypertension and dyslipidaemia, whereas ethnicity was associated with awareness of having hypertension and diabetes. Relative family income was only associated with awareness of having hypertension. Large proportions of US adults with hypertension, dyslipidaemia and diabetes are not aware of having the conditions. Interventions targeting groups at higher risk of being unaware of these conditions are needed. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has resulted in substantial global upheaval. Resilience is important in protecting wellbeing, however few studies have investigated changes in resilience over time, and associations between resilience with depression, anxiety, stress, and physical activity during the COVID-19 pandemic.Methods: Online surveys were conducted to collect both longitudinal and cross-sectional data at three time points during 2020. Australian adults aged 18 years and over were invited to complete the online surveys. Measures include the six-item Brief Resilience Scale, the 21-item Depression, Anxiety and Stress Scale, and the Active Australia Survey which have eight items identifying the duration and frequency of walking, and moderate and vigorous physical activities (MVPA), over the past 7 days. General linear mixed models and general linear models were used in the analysis.Results: In the longitudinal sample, adjusted differences (aDif) in resilience scores did not significantly change over time (time 2 vs. time 1 [aDif = - 0.02, 95% CI = - 0.08, 0.03], and time 3 vs. time 1 [aDif = < 0.01, 95% CI = - 0.07, 0.06]). On average, those engaging in at least 150 min of MVPA per week (aDif = 0.10, 95% CI = 0.04, 0.16), and having depression (aDif = 0.40, 95% CI = 0.33), anxiety (aDif = 0.34, 95% CI = 0.26, 0.41), and stress scores (aDif = 0.30, 95% CI = 0.23, 0.37) within the normal range had significantly higher resilience scores. The association between resilience and physical activity was independent of depression, anxiety, and stress levels. All results were similar for the cross-sectional sample.Conclusions: Resilience scores did not change significantly during the COVID-19 pandemic. However, there were significant associations between resilience with physical activity and psychological distress. This research helps inform future interventions to enhance or nurture resilience, particularly targeted at people identified as at risk of psychological distress. [ABSTRACT FROM AUTHOR]

Health‐related quality of life (HRQoL) is being increasingly studied as an indicator of wellbeing. This study evaluated the HRQoL of nursing students and relationships between lifestyle behaviors including smoking, diet, alcohol intake and physical activity. A cross‐sectional study was conducted in 2018 using the Short‐Form 12V2 to measure the HRQoL of 475 students from both regional and metropolitan universities in Queensland, Australia. z‐scores were aggregated into a Physical Composite Score (PCS) and a Mental Composite Score (MCS). Multivariate linear regression was used to explore the associations. Nursing students (94.5% female) had lower HRQoL scores relative to the general Australian population. Students enrolled at the regional university, with higher income; higher intakes of vitamin A, calcium, and iodine; and more physical activity had a higher Mental Composite Score, but those with health conditions and high intakes of meat, fat, carbohydrates, and sugar reported lower Physical Composite Score compared to their counterparts. Skipping breakfast, physical inactivity, and alcohol score were inversely associated with HRQoL. This study highlights the need for strategies to address the poor lifestyle and HRQoL in nursing students to support their physical and mental health. [ABSTRACT FROM AUTHOR]

Lack of time, financial issues, and stressful clinical and educational environments in nursing studies promote higher intakes of convenience and fast foods loaded with fat and sugar, which are linked to reduced mental and physical health. In this study, we examined the dietary patterns of nursing students and their associated sociodemographic factors to inform the development of future health‐promotion interventions. A total of 548 Bachelor of Nursing students were invited to complete a survey. Associations were explored using χ2 and logistic regression. Three dietary patterns were identified: healthy (fruit, vegetables, and legumes), Western (loaded with fat, sugar, and salt), and unbalanced. Only 21% of participants were classified as following a healthy dietary pattern, and more likely to be older (>35 years old) and have a personal annual income between $AUD20 000–$59 999 and $60 000–$99 999. Students with one to two and three or more children were more likely to follow a Western dietary pattern. There is a need to develop interventions to improve the dietary behaviors of nursing students by health‐promoting activities and the provision of online health resources. [ABSTRACT FROM AUTHOR]

This study used a bibliometric analysis through the Scopus database to examine papers that combined physical activity and sleep, published between 1979 and 2018. Bibliometric indicators of productivity included publication volume and citation distribution, top 10 authors, average authors per paper, single- and multicountry collaboration, collaborative index, top 10 countries, leading journals, highly cited papers and network visualization for coauthorship, international collaboration, and co-occurrence of author keywords. The initial search identified 1,509 papers, of which 607 passed through comprehensive screening and were included in the final analysis. Most of the papers were research articles (90.8%) and published in English (90.8%). Most papers (81.4%) were published within the past decade, 2009–2018. The mean number of papers published per year was 15.2, the mean number of citations per paper was 257.3, and the mean number of authors per paper was 5.5. International collaboration was evident for 21.6% of the papers, and 95.6% of papers were multiauthored. The most prolific publishing institutions and authors were from the United States, Canada, Australia, Switzerland, and Brazil. Keyword analysis suggested that almost all age groups and study designs were covered, but most papers focus on noncommunicable diseases. Although there has been a rise in scientific production on combined physical activity and sleep research in recent years, future work in this area should include researchers from developing countries. [ABSTRACT FROM AUTHOR]

Objectives: To compare the frequency of and trends in healthy lifestyle factors between singles and couples. Methods: 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. Results: 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). Conclusions: 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. [ABSTRACT FROM AUTHOR]

Background: Classroom-based physical activity interventions have demonstrated positive effects in reducing sedentary behaviour among school children. However, this is an understudied area, especially in low- and middle-income countries such as Sri Lanka. This study aims to explore teachers' opportunity, capability and motivation relating to the implementation of an in-classroom physical activity breaks programme. Methods: Twenty-seven teachers were recruited through snowball sampling and participated in semi-structured telephone interviews from early-January to the mid-June 2022. The Capability, Opportunity, and Motivation Behaviour (COM-B) model was used to guide and deductively thematic analyse the interviews. Results: 21 out of the recruited teachers responded to the full study. The mean age of respondents was 39.24 years old ranging from 27 years to 53 years. Teaching experience of the respondents ranged from three to 37 years, and 57% were female. Three teachers had a degree with a teacher training diploma, while others were having General Certificate of Education in Advanced Level with a teacher training diploma as the highest education qualification. Capability factors such as age, dress code, mask wearing, knowledge, skills and workload of the teachers were identified as important factors in implementing a physical activity breaks intervention in a Sri Lankan classroom setting. Classroom space, facilities, student backgrounds and safety were identified as opportunity factors. Obtaining policy level decisions to implement the activity breaks and managing the time of the activities to reduce time lost in education time were identified as motivational factors. Conclusion: During the intervention development phase, implementation facilitators and barriers must be considered carefully. Behaviour change techniques can be utilised to address the identified COM-B factors to ensure a good implementation of the intervention. [ABSTRACT FROM AUTHOR]

Background: Most people do not engage in sufficient physical activity to confer health benefits and to reduce risk of chronic disease. Healthcare professionals frequently provide guidance on physical activity, but often do not meet guideline levels of physical activity themselves. The main objective of this study is to develop and test the efficacy of a tailored intervention to increase healthcare professionals' physical activity participation and quality of life, and to reduce work-related stress and absenteeism. This is the first study to compare the additive effects of three forms of a tailored intervention using different techniques from behavioural theory, which differ according to their focus on motivational, self-regulatory and/or habitual processes.Methods/design: Healthcare professionals (N = 192) will be recruited from four hospitals in Perth, Western Australia, via email lists, leaflets, and posters to participate in the four group randomised controlled trial. Participants will be randomised to one of four conditions: (1) education only (non-tailored information only), (2) education plus intervention components to enhance motivation, (3) education plus components to enhance motivation and self-regulation, and (4) education plus components to enhance motivation, self-regulation and habit formation. All intervention groups will receive a computer-tailored intervention administered via a web-based platform and will receive supporting text-messages containing tailored information, prompts and feedback relevant to each condition. All outcomes will be assessed at baseline, and at 3-month follow-up. The primary outcome assessed in this study is physical activity measured using activity monitors. Secondary outcomes include: quality of life, stress, anxiety, sleep, and absenteeism. Website engagement, retention, preferences and intervention fidelity will also be evaluated as well as potential mediators and moderators of intervention effect.Discussion: This is the first study to examine a tailored, technology-supported intervention aiming to increase physical activity in healthcare professionals. The study will evaluate whether including additional theory-based behaviour change techniques aimed at promoting motivation, self-regulation and habit will lead to increased physical activity participation relative to information alone. The online platform developed in this study has potential to deliver efficient, scalable and personally-relevant intervention that can be translated to other occupational settings.Trial Registration: Australian New-Zealand Clinical Trial Registry: ACTRN12616000462482, submitted 29/03/2016, prospectively registered 8/04/2016. [ABSTRACT FROM AUTHOR]

Background: Parents play an important role in modelling healthy behaviours to their children. This study investigated associations between parent and child physical activity and screen time behaviours across specific domains, including moderating effects by parent and child gender. Method: The sample comprised 3300 school children and 2933 parents participating in the UP4FUN project (mean ages: child 11.2 ± 0.8 years, mother 40.0 ± 4.9 years, father 43.4 ± 5.8 years; 49% boys, 83% mothers). Data were collected in 2011 in Belgium, Greece, Hungary, Germany and Norway. Questionnaires assessed physical activity (sport, outdoor activities, walking and cycling for transport) and screen time (TV/DVD viewing, computer/games console use) in children and parents. Multilevel multivariate regression was applied to assess associations between parent and child physical activity and screen time. Results: Maternal, but not paternal, participation in sport, outdoor activities and walking for transport were associated with higher participation in these activities in children (P< 0.001). In contrast, both maternal and paternal TV/DVD viewing and computer/games console use were related to higher engagement in these screen-based activities in children (P<0.01). Furthermore, maternal modelling of outdoor activities was significantly associated with outdoor activities in girls (P<0.001). In contrast, paternal modelling of TV/DVD viewing and computer/games console were significantly associated with these screen-based behaviours in boys (P<0.001). Conclusions: Maternal modelling of healthy active behaviours may have a greater influence on children compared to paternal modelling, whereas unhealthy sedentary behaviours seem to be modelled by both parents equally. [ABSTRACT FROM AUTHOR]

Physical activity is partly regulated by automatic processes such as habits (ie, well-learned responses to cues), but it remains unclear what cues trigger these processes. This study examined the relations of physical activity automaticity and behavior with the consistency of people, activity, routine, location, time, and mood cues present upon initiation of physical activity behavior. Australian adults (N = 1,244, 627 female, M age = 55 years) reported their physical activity automaticity, behavior, and the degree of consistency of these cues each time they start a physical activity behavior. Multiple regression models, which accounted for gender and age, revealed that more consistent routine and mood cues were linked to more physical activity automaticity; whereas more consistent time and people cues were linked to more physical activity behavior. Interventions may more effectively translate into long-lasting physical activity habits if they draw people's attention to the salient cues of time, people, routine, and mood. [ABSTRACT FROM AUTHOR]

Background: Many adults are insufficiently physically active, have prolonged sedentary behaviour and report poor sleep. These behaviours can be improved by interventions that include education, goal setting, self-monitoring, and feedback strategies. Few interventions have explicitly targeted these behaviours simultaneously or examined the relative efficacy of different self-monitoring methods.Methods/design: This study aims to compare the efficacy of two self-monitoring methods in an app-based multi-behaviour intervention to improve objectively measured physical activity, sedentary, and sleep behaviours, in a 9 week 2-arm randomised trial. Participants will be adults (n = 64) who report being physically inactive, sitting >8 h/day and frequent insufficient sleep (≥14 days out of last 30). The "Balanced" intervention is delivered via a smartphone 'app', and includes education materials (guidelines, strategies to promote change in behaviour), goal setting, self-monitoring and feedback support. Participants will be randomly allocated to either a device-entered or user-entered self-monitoring method. The device-entered group will be provided with a activity tracker to self-monitor behaviours. The user-entered group will recall and manually record behaviours. Assessments will be conducted at 0, 3, 6, and 9 weeks. Physical activity, sedentary behaviour and sleep-wake behaviours will be measured using the wrist worn Geneactiv accelerometer. Linear mixed models will be used to examine differences between groups and over time using an alpha of 0.01.Discussion: This study will evaluate an app-based multi-behavioural intervention to improve physical activity, sedentary behaviour and sleep; and the relative efficacy of two different approaches to self-monitoring these behaviours. Outcomes will provide information to inform future interventions and self-monitoring targeting these behaviours.Trial Registration: ACTRN12615000182594 (Australian New Zealand Clinical Trials Registry. Registry URL: www.anzctr.org.au ; registered prospectively on 25 February 2015). [ABSTRACT FROM AUTHOR]

Background: The aim of this paper was to ascertain whether greater familiarity with a smartphone or tablet was associated with participants' preferred mobile delivery modality for eHealth interventions.Methods: Data from 1865 people who participated in the Australian Health and Social Science panel study were included into two multinomial logistic regression analyses in which preference for smartphone and tablet delivery for general or personalised eHealth interventions were regressed onto device familiarity and the covariates of sex, age and education.Results: People were more likely to prefer both general and personalised eHealth interventions presented on tablets if they reported high or moderate tablet familiarity (compared to low familiarity) and people were more likely to prefer both general and personalised eHealth interventions presented on smartphones if they reported high or moderate smartphone familiarity, were younger, and had university education (compared to completing high school or less).Conclusion: People prefer receiving eHealth interventions on the mobile devices they are most familiar with. These findings have important implications that should be considered when developing eHealth interventions, and demonstrates that eHealth interventions should be delivered using multiple platforms simultaneously to optimally cater for as many people as possible. [ABSTRACT FROM AUTHOR]

Objective: This study aims to examine the relationship of lifestyle behaviors (physical activity, work and non-work sitting time, sleep quality, and sleep duration) with presenteeism while controlling for sociodemographics, work- and health-related variables. Methods: Data were collected from 710 workers (aged 20 to 76 years; 47.9% women) from randomly selected Australian adults who completed an online survey. Linear regression was used to examine the relationship between lifestyle behaviors and presenteeism. Results: Poorer sleep quality (standardized regression coefficients [B] = 0.112; P < 0.05), suboptimal duration (B = 0.081; P < 0.05), and lower work sitting time (B = —0.086; P < 0.05) were significantly associated with higher presenteeism when controlling for all lifestyle behaviors. Engaging in three risky lifestyle behaviors was associated with higher presenteeism (B = 0.150; P < 0.01) compared with engaging in none or one. Conclusions: The results of this study highlight the importance of sleep behaviors for presenteeism and call for behavioral interventions that simultaneously address sleep in conjunction with other activity-related behaviors. [ABSTRACT FROM AUTHOR]

Website-delivered interventions are increasingly used to deliver physical activity interventions, yet problems with engagement and retention result in reduced effectiveness. Hence, alternative modes of online intervention delivery need to be explored. Therefore, this study aimed to evaluate the acceptability and effectiveness of a computer-tailored physical activity intervention delivered on the Internet in 3 delivery modes: video, text, or both. Australian adults (N = 803), recruited through e-mail, were randomized into the three delivery modes and received personal physical activity advice. Intervention content was identical across groups. Repeated measures analyses of variance were used to compare the three groups regarding acceptability, website usability, and physical activity. Participants in the video group accepted the content of the physical activity advice significantly better (F = 5.59;p < .01), and spent significantly more time on the website (F = 21.19;p < .001) compared with the text and combination groups. Total physical activity improved significantly over time in all groups (F = 3.95;p < .01). Although the combination group increased physical activity the most, few significant differences between groups were observed. Providing video-tailored feedback has advantages over the conventional text-tailored interventions; however, this study revealed few behavioral differences. More studies, examining alternative delivery modes, that can overcome the limitations of the present study, are needed. [ABSTRACT FROM PUBLISHER]

Background It has been shown that physical activity is more likely to increase if web-based interventions apply evidence-based components (e.g. self-monitoring) and incorporate interactive social media applications (e.g. social networking), but it is unclear to what extent these are being utilized in the publicly available web-based physical activity interventions. The purpose of this study was to evaluate whether freely accessible websites delivering physical activity interventions use evidence-based behavior change techniques and provide social media applications. Methods In 2013, a systematic search strategy examined 750 websites. Data was extracted on a wide range of variables (e.g. self-monitoring, goal setting, and social media applications). To evaluate website quality a new tool, comprising three sub-scores (Behavioral Components, Interactivity and User Generated Content), was developed to assess implementation of behavior change techniques and social media applications. An overall website quality scored was obtained by summing the three sub-scores. Results Forty-six publicly available websites were included in the study. The use of self-monitoring (54.3%), goal setting (41.3%) and provision of feedback (46%) was relatively low given the amount of evidence supporting these features. Whereas the presence of features allowing users to generate content (73.9%), and social media components (Facebook (65.2%), Twitter (47.8%), YouTube (48.7%), smartphone applications (34.8%)) was relatively high considering their innovative and untested nature. The average Behavioral Components score was 3.45 (±2.53) out of 10. The average Interactivity score was 3.57 (±2.16) out of 10. The average User Generated Content Score was 4.02 (±2.77) out of 10. The average overall website quality score was 11.04 (±6.92) out of 30. Four websites (8.7%) were classified as high quality, 12 websites (26.1%) were classified as moderate quality, and 30 websites (65.2%) were classified as low quality. Conclusions Despite large developments in Internet technology and growth in the knowledge of how to develop more effective web-based interventions, overall website quality was low and the majority of freely available physical activity websites lack the components associated with behavior change. However, the results show that website quality can be improved by taking a number of simple steps, and the presence of social media applications in most websites is encouraging. [ABSTRACT FROM AUTHOR]

Background People have different preferences on how health behaviour change interventions are delivered to them; intervention implementation, retention and effectiveness may be improved if preferences can be matched. Purpose This study aims to explore factors related to preference of face-to-face, and group-, print- or web-based physical activity intervention delivery modes among adults recruited from the general population. Methods A question relating to physical activity intervention preference was included in the telephone administered 2010 Queensland Social Survey. Multinomial regression models were used to explore socio-demographic (e.g., age, marital status, location), health (e.g., BMI, chronic disease status) and behavioral factors (e.g., internet use, physical activity, diet, social networking) related to intervention preferences, using 'a face-to-face intervention' as the reference category. Results 35.2% of those approached took part in the telephone interviews (n = 1,261). Preference for a web-based intervention was positively associated with being in the 35-44 age group (compared to the 18-34 age group; RR = 2.71), living in a rural area (RR = 2.01), and high internet use (RR = 1.03); and negatively associated with female gender (RR = 0.52), obesity (RR = 0.42), and higher physical activity participation (RR = 0.99). Preference for a print-based intervention was positively associated with older age (RR = 5.50); and negatively associated with female gender (RR = 0.48) and obesity (RR = 0.47). Preference for a groupbased program was positively associated with living in a regional town (RR = 1.48) and negatively associated with being separated (RR = 0.45) and obesity (RR =0.56). Conclusion Findings from this study help to delineate what physical activity intervention delivery modes are likely to be appealing for specific target groups, especially in relation to people of different weight status, age, gender and living environment. As such, this information will be useful in the development of interventions targeted at these groups. [ABSTRACT FROM AUTHOR]

OBJECTIVE: This study examined the effectiveness of a fully automated web-based programme to increase physical activity in adults with Type 2 diabetes. METHODS: Between May and July 2010, participants were randomly allocated into either a 12-week intervention (n=195) or a control (n=202) group. Participants were adults diagnosed with Type 2 diabetes, residing in Australia. Participants were assessed at baseline, 12 and 36weeks. The primary physical activity outcome was self-reported minutes of total physical activity. Secondary physical activity outcomes included minutes spent walking, and engaged in moderate, and vigorous physical activity. Additional measures included website satisfaction and website usage. The intervention consisted of a 12-week web-based physical activity intervention developed based on the Theory of Planned Behavior and self-management framework. Data were analysed from 2011 to 2012. RESULTS: There was a significant group-by-time interaction (X(2) (df=1)=6.37, p<.05) for total physical activity favouring the intervention group d=0.11, for those who completed the intervention, however this was not significant in the intention-to-treat analysis d=0.01. The intervention yielded high website satisfaction and usage. CONCLUSIONS: In general, there is some evidence for the effectiveness of web-based interventions for improving physical activity levels; however it is clear that maintaining improvements remains an issue. [ABSTRACT FROM AUTHOR]

Abstract: Objective: This study examined the effectiveness of a fully automated web-based programme to increase physical activity in adults with Type 2 diabetes. Methods: Between May and July 2010, participants were randomly allocated into either a 12-week intervention (n =195) or a control (n =202) group. Participants were adults diagnosed with Type 2 diabetes, residing in Australia. Participants were assessed at baseline, 12 and 36weeks. The primary physical activity outcome was self-reported minutes of total physical activity. Secondary physical activity outcomes included minutes spent walking, and engaged in moderate, and vigorous physical activity. Additional measures included website satisfaction and website usage. The intervention consisted of a 12-week web-based physical activity intervention developed based on the Theory of Planned Behavior and self-management framework. Data were analysed from 2011 to 2012. Results: There was a significant group-by-time interaction (X 2 (df =1)=6.37, p <.05) for total physical activity favouring the intervention group d =0.11, for those who completed the intervention, however this was not significant in the intention-to-treat analysis d =0.01. The intervention yielded high website satisfaction and usage. Conclusions: In general, there is some evidence for the effectiveness of web-based interventions for improving physical activity levels; however it is clear that maintaining improvements remains an issue. [Copyright &y& Elsevier]

Background A better understanding of how occupational indicators (e.g. job type, doing shift-work, hours worked, physical demand) influence sitting time will aid in the design of more effective health behaviour interventions. The aim of the study was to examine the associations between several occupational indicators and total, occupational and leisure-time sitting. Methods Cross-sectional self-report data was collected in November 2011 from 1194 participants through a telephone interview in regional Queensland, Australia (response rate was 51.9%). The Workforce Sitting Questionnaire was used to measure sitting time. Multiple logistic regression was applied to examine associations between sitting time and occupational indicators. Results Of all participants 77.9% were employed full-time, 72.7% had white-collar jobs, 35.7% were engaged in shift-work, 39.5% had physically demanding jobs, and 53.2% had high total sitting time (>8 hours a day). Those in physically demanding and blue-collar occupations were less likely to report high total (physically demanding: OR = 0.41,95%CI = 0.29-0.58; blue-collar: OR = 0.55,95%CI = 0.37-0.82) and occupational (physically demanding: OR = 0.26,95%CI = 0.14-0.24; blue-collar: OR = 0.32,95%CI = 0.21-0.49) sitting time compared to those in physically undemanding and white-collar occupations respectively. Working more than 8 hours per day was inversely associated with high leisure-time sitting (OR = 0.44,95%CI = 0.29-0.68). No evidence for 'compensation' effects, where lower occupational sitting is compensated with higher leisure-time sitting, was found. Conclusions Behaviour change interventions are needed to reduce sitting time as a means to prevent chronic disease. Workplace initiatives to reduce sitting time may be particularly important among individuals employed in white-collar and physical undemanding occupations, although other intervention strategies targeting leisure-time sitting are also required. [ABSTRACT FROM AUTHOR]

Within a health context, men in Western societies are a hard-to-reach population who experience higher rates of chronic disease compared with women. Innovative technology-based interventions that specifically target men are needed; however, little is known about how these should be developed for this group. This study aimed to examine opinions and perceptions regarding the use of Internet and mobile phones to improve physical activity and nutrition behaviors for middle-aged men. The authors conducted 6 focus groups (n = 30) in Queensland, Australia. Their analyses identified 6 themes: (a) Internet experience, (b) website characteristics, (c) Web 2.0 applications, (d) website features, (e) self-monitoring, and (f) mobile phones as delivery method. The outcomes indicate that men support the use of the Internet to improve and self-monitor physical activity and dietary behaviors on the condition that the website-delivered interventions are quick and easy to use, because commitment levels to engage in online tasks are low. Participants also indicated that they were reluctant to use normal mobile phones to change health behaviors, although smartphones were perceived to be more acceptable. This pilot study suggests that there are viable avenues to engage middle-aged men in Internet- or in mobile-delivered health interventions. This study also suggests that to be successful, these interventions need to be tailor-made especially for men, with an emphasis on usability and convenience. A wider quantitative study would bring further support to these findings. [ABSTRACT FROM PUBLISHER]

Abstract: Objective: The relationship between short sleep and obesity remains unclear, and a possible explanation is that many studies have not included sufficient control variables in the analyses. We examined the association between sleep and being overweight or obese after adjusting for the confounding contributions of 17 variables. Methods: A random sample of 1162 Australian adults from three regional cities in central Queensland, Australia, participated in a telephone survey. A series of increasingly complex multinomial logistic regression models were employed to assess the association between short sleep (⩽6h) being overweight (body mass index [BMI] 25–29.99kg/m2) and obesity (BMI, ⩾30kg/m2), while controlling for several demographic, lifestyle, work, and health-related variables. Results: The results suggested obesity was significantly associated with short sleep, age, male gender, lower education level, less physical activity, more sitting time, working longer hours, drinking more alcohol, having diabetes mellitus (DM), and having hypertension. Being overweight was significantly associated with age, male gender, smoking, and working more than 43hours per week. Conclusions: After adjustment of several confounding variables, a significant association between short sleep and obesity was obtained, but there was no association between short sleep and being overweight. Additional studies applying comprehensive analytic models and stronger research designs are needed to confirm our findings. [Copyright &y& Elsevier]

Abstract: 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. Results: In comparison to the reference category (sufficient physical activity and low screen-time) men and women who reported no physical activity and either high (OR=4.52, 95% CI 2.82–7.25) or low (OR=2.29, 95% CI 1.37–3.80) screen-time, were significantly more likely to report over 14 unhealthy days. Men reporting either; no physical activity and high (OR=3.15, 95% CI 1.92–5.15), or low (OR=2.17, 95% CI 1.30–3.63) screen-time; insufficient physical activity and high (OR=1.68, 95% CI 1.08–2.60), or low (OR=1.79, 95% CI 1.14–2.82) screen-time were more likely to rate their health as poor or fair. In women this was significant for those who reported no physical activity and high screen-time (OR=1.98, 95% CI, 1.19–3.31). Conclusions: Results suggest that the combination of no physical activity and high screen-time demonstrated the greatest negative impact on health related quality of life. [Copyright &y& Elsevier]

Background: The aims of this study were to examine temporal trends in the prevalence of sufficient moderate-to-vigorous intensity physical activity (MVPA), high levels of screen time, combined measures of these behaviors and overweight or obesity in Australian adults during the period 2002-2008. Trends over this time period in overweight or obesity within each behavior group (sufficient/insufficient MVPA, high/low screen time and combined behaviors) were also examined. Methods: Data were collected via annually conducted cross-sectional computer-assisted-telephone-interviews (CATI) of adults (n=7908) living in Central Queensland, Australia (2002-2008). Self-reported MVPA, screen time (TV viewing and computer use), and BMI were used to create dichotomous classifications of physical activity (Sufficient MVPA (S-MVPA), Insufficient Physical Activity (I-MVPA)), screen time (High Screen Time (HST), Low Screen Time (LST)), combined behavior categories (S-MVPA/LST, I-MVPA/LST, S-MVPA/HST, I-MVPA/HST) and BMI (Overweight or Obese, Healthy Weight) respectively. Results: The prevalence of S-MVPA, HST, and overweight or obesity increased at approximately the same rate over the study period in the overall sample and females (p?0.05). In the overall sample and in females, the prevalence of overweight and obesity increased over the study period in those individuals classified as I-MVPA/HST (p≤0.05). Conclusion: Results provide evidence that while the prevalence of S-MVPA appears to be modestly increasing, the proportion of the population engaging in HST and classified as overweight or obese are increasing at approximately the same rate. These observations highlight the need to increase levels of total physical activity (including light intensity physical activity) and decrease sedentary behavior including screen time. [ABSTRACT FROM AUTHOR]

Background: Compared to females, males experience higher rates of chronic disease and mortality, yet few health promotion initiatives are specifically aimed at men. Therefore, the aim of the ManUp Study is to examine the effectiveness of an IT-based intervention to increase the physical activity and nutrition behaviour and literacy in middle-aged males (aged 35-54 years). Method/Design: The study design was a two-arm randomised controlled trial, having an IT-based (applying website and mobile phones) and a print-based intervention arm, to deliver intervention materials and to promote self-monitoring of physical activity and nutrition behaviours. Participants (n = 317) were randomised on a 2:1 ratio in favour of the IT-based intervention arm. Both intervention arms completed assessments at baseline, 3, and 9 months. All participants completed self-report assessments of physical activity, sitting time, nutrition behaviours, physical activity and nutrition literacy, perceived health status and socio-demographic characteristics. A randomly selected sub-sample in the IT-based (n = 61) and print-based (n = 30) intervention arms completed objective measures of height, weight, waist circumference, and physical activity as measured by accelerometer (Actigraph GT3X). The average age of participants in the IT-based and print-based intervention arm was 44.2 and 43.8 years respectively. The majority of participants were employed in professional occupations (IT-based 57.6%, Print-based 54.2%) and were overweight or obese (IT-based 90.8%, Print-based 87.3%). At baseline a lower proportion of participants in the IT-based (70.2%) group agreed that 30 minutes of physical activity each day is enough to improve health compared to the print-based (82.3%) group (p = .026). The IT-based group consumed a significantly lower number of serves of red meat in the previous week, compared to the print-based group (p = .017). No other significant between-group differences were observed at baseline. Discussion: The ManUp Study will examine the effectiveness of an IT-based approach to improve physical activity and nutrition behaviour and literacy. Study outcomes will provide much needed information on the efficacy of this approach in middle aged males, which is important due to the large proportions of males at risk, and the potential reach of IT-based interventions. Trial registration: ACTRN12611000081910 [ABSTRACT FROM AUTHOR]

Background: The adoption and maintenance of healthy behaviours is essential in the primary prevention of chronic non-communicable diseases. This study evaluated the effectiveness of a minimal intervention on multiple lifestyle factors such as diet, physical activity, smoking and alcohol, delivered through general practice, using computer-tailored feedback. Methods: Adult patients visiting 21 general practitioners in Brisbane, Australia, were surveyed about ten health behaviours that are risk factors for chronic, non-communicable diseases. Those who completed the self-administered baseline questionnaire entered a randomised controlled trial, with the intervention group receiving computer-tailored printed advice, targeting those health behaviours for which respondents were not meeting current recommendations. The primary outcome was change in summary lifestyle score (Prudence Score) and individual health behaviours at three months. A repeated measures analysis compared change in these outcomes in intervention and control groups after adjusting for age and education. Results: 2306 patients were randomised into the trial. 1711 (76%) returned the follow-up questionnaire at 3 months. The Prudence Score (10 items) in the intervention group at baseline was 5.88, improving to 6.25 at 3 months (improvement = 0.37), compared with 5.84 to 5.96 (improvement = 0.12) in the control group (F = 13.3, p = 0.01). The intervention group showed improvement in meeting recommendations for all individual health behaviours compared with the control group. However, these differences were significant only for fish intake (OR 1.37, 95% CI 1.11-1.68), salt intake (OR 1.19, 95% CI 1.05-1.38), and type of spread used (OR 1.28, 95% CI 1.06-1.51). Conclusion: A minimal intervention using computer-tailored feedback to address multiple lifestyle behaviours can facilitate change and improve unhealthy behaviours. Although individual behaviour changes were modest, when implemented on a large scale through general practice, this intervention appears to be an effective and practical tool for population-wide primary prevention. Trial Registration: The Australian New Zealand Clinical Trials Registry: ACTRN12611001213932 [ABSTRACT FROM AUTHOR]

Background: Continued low adherence to physical activity recommendations illustrates the need to refine intervention strategies and increase their effectiveness. The purpose of this study was to conduct formative research related to the development of a next generation of computer-tailored interventions that use online tailored video-messages to increase physical activity. Methods: Five focus groups (n = 30), aimed at males and females, aged between 35 and 60 years, that do not meet the physical activity recommendation, were conducted to allow in-depth discussion of various elements related to the development of an online video-tailored intervention. In addition, a series of questions were delivered to a random sample (n = 1261) of Australians, using CATI survey technology, to gain more information and add a quantitative assessment of feasibility related to the development of the intervention. Focus group data was transcribed, and summarised using Nvivo software. Descriptive and frequency data of the survey was obtained using SPSS 18.0. Results: Nearly all of the focus group participants supported the concept of a video-tailored intervention and 35.8% of survey participants indicated that they would prefer a video-based over a text-based intervention. Participants with a slow internet-connection displayed a lower preference for video-based advice (31.9%); however less than 20% of the survey sample indicated that downloading videos would be slow. The majority of focus group and survey participants did not support the idea of using mobile phones to receive this kind of intervention and indicated that video-tailored messages should be shorter than 5 minutes. Video-delivery of content is very rich in information, which increases the challenge to appropriately tailor content to participant characteristics; focusgroup outcomes indicated a large diversity in participant preferences. 52.4% of survey participants indicated that the videos should be convincing and motivating. Conclusions: These results provide valuable information to develop an innovative video-tailored physical activity intervention. The results support the feasibility of such intervention, both in terms of users being ready to participate in it, as well as from a point of view whereby current internet infrastructure is able to cope with the demands of downloading videos. Though promising, a number of specific challenges in the development of these interventions were identified (e.g. the videos need to be short, made professionally, and tailor to a larger number of variables) and will need to be overcome in the development and evaluation of this new type of physical activity intervention. [ABSTRACT FROM AUTHOR]

Synopsis: Despite their popularity and potential to promote health in large populations, the effectiveness of online social networks (e.g., Facebook) to improve health behaviors has been somewhat disappointing. Most of the research examining the effectiveness of such interventions has used randomized controlled trials (RCTs). It is asserted that the modest outcomes may be due to characteristics specific to both online social networks and RCTs. The highly controlled nature of RCTs stifles the dynamic nature of online social networks. Alternative and ecologically valid research designs that evaluate online social networks in real-life conditions are needed to advance the science in this area. [ABSTRACT FROM AUTHOR]

Unlabelled: Screening physical activity levels is common in trials to increase physical activity in inactive populations. Commonly applied single-item screening tools might not always be effective in identifying those who are inactive. We applied the more extensive Active Australia Survey to identify inactive people among those who had initially been misclassified as too active using a single-item measure. Those enrolled after the Active Australia Survey screening had significantly higher physical activity levels at subsequent baseline assessment. Thus, more extensive screening measures might result in the inclusion of participants who would otherwise be excluded, possibly introducing unwanted bias.Trial Registration: Australian New Zealand Clinical Trials Registry, ACTRN12611000157976. [ABSTRACT FROM AUTHOR]

Abstract: Background: Major questions remain unanswered about how best to accomplish multiple behavior change. The purpose of this study was to evaluate whether there are differences in successfully changing multiple behaviors in computer-tailored sequential and simultaneous interventions for physical activity (PA) promotion and fat intake (FI) reduction. Methods: Participants (N =567) were randomly assigned to receive an intervention for PA and FI simultaneously; PA at baseline and FI at 3 months; or FI at baseline and PA at 3 months. Successful behavior change at 6 months was defined as: >60 min PA increase and/or 5% FI reduction. Using multinomial logistic regression the odds ratios of successful behaviors change (none, PA only, FI only, or both) were determined for intervention mode, gender, age, BMI and education. Results: Overall drop-out was 26%. There was no behavior change for 20.2% of participants; 30.5% successfully decreased FI; 15.8% successfully increased PA; 33.5% successfully changed both behaviors. Intervention mode, gender and age were not associated with successful behavior change. Compared to those that did not change any behaviors: participants that successfully changed FI were more likely to be overweight/obese (OR=1.85); and participants that successfully changed both behaviors were more likely to be overweight/obese (OR=2.13) and have lower education (OR=2.46). Conclusions: Success in changing multiple behaviors was not associated with intervention mode; both simultaneous and sequential interventions can be applied. Being overweight might be an extra motivator to change health behaviors. [Copyright &y& Elsevier]

Background: Evidence-based physical activity interventions that can be delivered to large numbers of adults at an acceptable cost are a public health priority; website-delivered programs have this potential. The purpose of this study was to systematically review the research findings and outcomes of website-delivered physical activity interventions and to identify relationships of intervention attributes with behavioral outcomes. Methods: A structured search of PubMed, Medline, PsycInfo, and Web of Science was conducted for intervention studies published up to July 2006. Studies included in the review were those that (1) used websites or e-mail, (2) had physical activity behavior as an outcome measure, (3) had randomized controlled or quasi-experimental designs, (4) targeted adults, and (5) were published in English. Results: Of the fifteen studies reviewed, improvement in physical activity was reported in eight. Better outcomes were identified when interventions had more than five contacts with participants and when the time to follow-up was short (≤3 months; 60% positive outcomes), compared to medium-term (3–6 months, 50%) and long-term (>6 months, 40%) follow-up. There were no clear associations of outcomes with other intervention attributes. Conclusions: A little over half of the controlled trials of website-delivered physical activity interventions have reported positive behavioral outcomes. However, intervention effects were short lived, and there was limited evidence of maintenance of physical activity changes. Research is needed to identify elements that can improve behavioral outcomes, the maintenance of change and the engagement and retention of participants; larger and more representative study samples are also needed. [Copyright &y& Elsevier]

Background: Limited evidence exists on long-term efficacy of interactive computer-tailored interventions for increasing physical activity and decreasing fat intake, and even more so when they are implemented simultaneously or sequentially. Purpose: This study aims to examine long-term efficacy of interactive computer-tailored physical activity and fat intake interventions, and evaluate their efficacy in a simultaneous or sequential implementation over 2 years. Methods: Participants (392) were randomly assigned to a simultaneous group receiving both interventions at baseline; a sequential group first receiving the physical activity intervention and 3 months later the fat intake intervention; and a sequential group first receiving the fat intake intervention and 3 months later the physical activity intervention. Results: Strong time effects were seen for total physical activity (F�=�38.7, p�<�.001) and fat intake (F�=�103.9, p�<�.001), indicating that intervention effects remained over 2 years for those participants that were still available for the 2-year follow-up. At 2-year follow-up the interventions resulted in a 10% and a 27% increase of participants that met public health recommendations for physical activity and fat intake, respectively. Overall the interventions were more effective for participants not meeting the public health recommendations at baseline. The sequential intervention mode was overall slightly more effective than the simultaneous mode in maintaining intervention effects. Conclusions: Both interventions showed efficacy in maintaining long-term health behavior changes. More research is needed on sequential and simultaneous intervening modes. [ABSTRACT FROM AUTHOR]

Background: Little evidence exists about the effectiveness of “interactive” computer-tailored interventions and about the combined effectiveness of tailored interventions on physical activity and diet. Furthermore, it is unknown whether they should be executed sequentially or simultaneously.Purpose: The purpose of this study was to examine (a) the effectiveness of interactive computer-tailored interventions for increasing physical activity and decreasing fat intake and (b) which intervening mode, sequential or simultaneous, is most effective in behavior change.Methods: Participants (N = 771) were randomly assigned to receive (a) the physical activity and fat intake interventions simultaneously at baseline, (b) the physical activity intervention at baseline and the fat intake intervention 3 months later, (c) the fat intake intervention at baseline and the physical activity intervention 3 months later, or (d) a place in the control group.Results: Six months postbaseline, the results showed that the tailored interventions produced significantly higher physical activity scores, F(2, 573) = 11.4, p <.001, and lower fat intake scores, F(2, 565) = 31.4, p <.001, in the experimental groups when compared to the control group.Conclusions: For both behaviors, the sequential and simultaneous intervening modes showed to be effective; however, for the fat intake intervention and for the participants who did not meet the recommendation in the physical activity intervention, the simultaneous mode appeared to work better than the sequential mode. [ABSTRACT FROM AUTHOR]

Background: Little evidence exists about the effectiveness of"interactive"computer-tailored interventions and about the combined effectiveness of tailored interventions on physical activity and diet. Furthermore, it is unknown whether they should be executed sequentially or simultaneously. Purpose: The purpose of this study was to examine (a) the effectiveness of interactive computer-tailored interventions for increasing physical activity and decreasing fat intake and (b) which intervening mode, sequential or simultaneous, is most effective in behavior change. Methods: Participants (N = 771) were randomly assigned to receive (a) the physical activity and fat intake interventions simultaneously at baseline, (b) the physical activity intervention at baseline and the fat intake intervention 3 months later, (c) the fat intake intervention at baseline and the physical activity intervention 3 months later, or (d) a place in the control group. Results: Six months postbaseline, the results showed that the tailored interventions produced significantly higher physical activity scores, F(2, 573) = 11.4, p<.001, and lower fat intake scores, F(2, 565) = 31.4, p<.001, in the experimental groups when compared to the control group. Conclusions: For both behaviors, the sequential and simultaneous intervening modes showed to be effective; however, for the fat intake intervention and for the participants who did not meet the recommendation in the physical activity intervention, the simultaneous mode appeared to work better than the sequential mode. [ABSTRACT FROM AUTHOR]

In order to reduce the risk of chronic diseases health authorities recommend restricting fat intake to 30% of the total energy uptake. However, fat intake in Belgium is much higher warranting interventions aimed at reducing fat intake. Tailored interventions have shown to be promising; however, studies on effectiveness of interactive computer-tailored systems are needed. We investigated the acceptability and feasibility of a recently developed interactive computer-tailored fat reduction intervention. Differences in the reported acceptability and feasibility according to demographic and stages of change were explored. Participants (n = 220) completed a computerized questionnaire, and received a personal fat intake advice, which was almost immediately displayed on screen. They also completed an evaluation questionnaire, during and after they ran the tailored program, with questions on the quality, user-friendliness and applicability of the program. Participants rated the program positively on all aspects. No significant differences in acceptability and feasibility scores were found according to sex, education levels and computer literacy. Although several significant differences were found between age groups and stages of change (oldest group, contemplators and preparators were more positive about the program), the importance of these differences is probably not great, since acceptability and feasibility scores for the different age groups and stages of change were always very high. These results suggest that the computer-tailored intervention is an acceptable and feasible tool for reducing fat intake in a general population in Belgium. [ABSTRACT FROM AUTHOR]

This study evaluated the reliability and validity of a Belgian computerized questionnaire to measure fat intake. A total of 86 adults completed a 48-item computerized fat intake questionnaire, subsequently kept a 7-day diet record, and finally completed the questionnaire again. For validity, a Pearson correlation of 0.67 for total fat intake and of 0.60 for percent energy from fat were found between the computerized questionnaire and the diet records. Gross misclassification between the two methods was 5.8% for total fat intake and for percent energy from fat. Cohen''s κ values were respectively 0.27 and 0.29. For reliability, intraclass correlation coefficients ranged from 0.70 to 0.87 between the two administrations of the computerized fat intake questionnaire. Gross misclassification between the administrations was 1.2% for total fat intake and for percent energy from fat, κ values were respectively 0.64 and 0.50. These results indicate that this fat intake questionnaire has an acceptable reliability and validity. [Copyright &y& Elsevier]

Issue Addressed: Interventions targeting health care professionals' behaviours are assumed to support them in learning how to give behavioural advice to patients, but such assumptions are rarely examined. This study investigated whether key assumptions were held regarding the design and delivery of physical activity interventions among health care professionals in applied health care settings. This study was part of the 'Physical Activity Tailored intervention in Hospital Staff' randomised controlled trial of three variants of a web‐based intervention. Methods: We used data‐prompted interviews to explore whether the interventions were delivered and operated as intended in health care professionals working in four hospitals in Western Australia (N = 25). Data were analysed using codebook thematic analysis. Results: Five themes were constructed: (1) health care professionals' perceived role in changing patients' health behaviours; (2) work‐related barriers to physical activity intervention adherence; (3) health care professionals' use of behaviour change techniques; (4) contamination between groups; and (5) perceptions of intervention tailoring. Conclusions: The intervention was not experienced by participants, nor did they implement the intervention guidance, in the way we expected. For example, not all health care professionals felt responsible for providing behaviour change advice, time and shift constraints were key barriers to intervention participation, and contamination effects were difficult to avoid. So What?: Our study challenges assumptions about how health care professionals respond to behaviour change advice and possible knock‐on benefits for patients. Applying our learnings may improve the implementation of health promotion interventions in health care settings. [ABSTRACT FROM AUTHOR]

Highlights: [•] We examine interdevice variability in ActivPAL3 accelerometers. [•] Interdevice variability exists in the magnitude of baseline acceleration signals. [•] Regular monitoring of interdevice variability is recommended. [ABSTRACT FROM AUTHOR]

Background: Online risk assessment tools for type 2 diabetes communicate risk information to motivate individuals to take actions and reduce their risk if needed. The impact of these tools on follow-up behaviours (e.g., General Practitioner (GP) visits, improvement in health behaviours) is unknown. This study examined effectiveness of a personalised video story and text-based message on GP and health professional visitations and health behaviours, of individuals assessed as 'high risk' following completion of the online Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK). Methods: A Randomised Controlled Trial (conducted between October 2018 and April 2019) included 477 participants with a high score (≥12). The control group received a text-based message (TM) and the intervention group received both the text-based message and a personalised video story (TM+VS) encouraging them to take follow-up action. Participants reported follow-up actions (one- and three months), and physical activity (PA), dietary behaviours and body weight (baseline, one and three months). Generalized Linear Mixed Models and chi-squared tests were used to test differences in outcomes between groups over time. Results: The intervention was not more effective for the TM+VS group compared to the TM only group (p-values>0.05 for all outcomes). More participants in the TM only group (49.8% compared to 40.0% in the VS+TM group) visited either a GP or health professional (p = 0.18). During the 3-month follow-up: 44.9% of all participants visited a GP (36.7%) and/or other health professional (31.0%). Significant improvements were found between baseline and three months, in both groups for weekly physical activity, daily fruit and vegetable intake and weight status. Conclusions: Messages provided with online diabetes risk assessment tools to those with high-risk, positively influence GP and health professional visitations and promote short-term improvements in health behaviours that may contribute to an overall reduction in the development of type 2 diabetes. Trial registration: Australia New Zealand Clinical Trials Registry; ACTRN12619000809134. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Few individuals with metastatic prostate cancer have access to prostate cancer-specific exercise support, despite demonstrated benefits. eHealth tools, such as websites, may be viable options for increasing access. To be effective and acceptable, future eHealth websites need to consider end-users' perspectives, capacity and needs. We aim to provide insight into these factors by exploring daily priorities, activities and health literacy of individuals with metastatic prostate cancer and their perspectives towards exercise and exercise-based web-based eHealth interventions. Methods: Semi-structured interviews explored participant's experiences and understanding of their disease, exercise levels, advice received from health care providers, as well as acceptability of and suggested content for an eHealth tool. A thematic analysis was undertaken. Results: Interviews were conducted with eighteen Australians (55–83 years; M = 71.5, SD = 8.9) living with metastatic prostate cancer. Needing to perform daily responsibilities was a key priority. Participants had limited understanding of the benefits of prostate cancer-specific exercise, and less than half discussed exercise with their health team. Fourteen men felt they could report metastases location, but only four could provide detailed information, which has clinical implications for exercise prescription. A potential web-based intervention was considered acceptable by seventeen men for reasons such as affordability, accessibility and convenience. User-friendly design and practitioner support were important. Conclusions: Results identified key aspects useful for person-centred design of exercise programs. Participants were positive towards the proposed web-based tool and expressed the need for individualised, user-friendly and reliable information with support from a professional embedded. Lastly, not all participants could accurately report metastasis locations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Chronic disease is the leading cause of death globally. Sleep, diet, and physical activity are modifiable health behaviours that are key for reducing the burden of chronic disease. These health behaviours are collectively termed 'The 3 Pillars of Health' and are critical for populations who are at risk of poor health. Shiftworkers are one such at-risk population. To target behavioural change it is critical to first understand which of these health behaviours Australians currently prioritise. Therefore, this study aimed to investigate how Australians (including shift workers) prioritise sleep, physical activity, and diet, and examine the associations with correlates of health behaviours. Methods: Two cohorts of Australian adults were sampled. A cohort of 1151 Australian adults (54% female, aged 18–65 years) including employed (in any work schedule), unemployed, studying, and retired completed a phone interview. A cohort of 533 Australian shiftwork-only adults (76% female, 18–72) completed an online survey. All participants were asked which health behaviour (sleep, physical activity, or diet) they prioritised in their own life. Behavioural correlates of sleep, diet, and physical activity (sleep duration, frequency of moderate to physical activity, healthy dietary behaviour), and years of shiftwork experience were also collected. Multinomial logistic regressions were used to investigate the association between the highest prioritised pillar of health and the behavioural correlates. Results: Diet was prioritised by the Australian adults (49%), whereas sleep was prioritised by the shiftwork-only sample (68%). Australian adults who prioritised diet were significantly more likely to report diets with less fast-food consumption (p < 0.002) and more fruit consumption (p < 0.002) compared to those that prioritised sleep. For the shiftwork-only sample, those with 16–30 years of shiftwork experience were significantly more likely to prioritise sleep compared to diet (p < 0.05). However, prioritising sleep was not associated with meeting the sleep duration recommendations in the shiftwork-only sample. Conclusions: Across two cohorts of Australians, prioritisation of health behaviour was only associated with actual behaviour for diet. This may reflect different motivations for prioritising different health behaviours, in addition to different capabilities to change different health behaviours. Future research should include longitudinal methodologies to understand how behaviour prioritisation changes over work- and life-span, and any associations with actual health behaviour. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the direct and indirect effects of sociodemographic/health factors on diet quality through practical nutrition knowledge (PNK) about how to compose a balanced meal.Design: A cross-sectional study using data from an online survey of the 10 000 Steps cohort (data collected November-December 2016).Setting: Australia.Participants: Adults (n = 8161). Response rate was 16.7%.Measures: Self-reported lifestyle, health, and sociodemographic characteristics, including diet quality and PNK.Analysis: The PROCESS macro for SPSS was used to conduct the mediation analyses.Results: Better diet quality was associated with being female, older, more highly educated, and having a lower body mass index. Mediation analysis showed that PNK significantly mediated the associations between sex (a*b = 0.54, 95% confidence interval [CI] = 0.39-0.70) and education (vocational education: a*b = 0.22, 95% CI = 0.12-0.35, university: a*b = 0.48, 95% CI = 0.35-0.64), and diet quality. Practical nutrition knowledge suppressed the association between age and diet quality (a*b = -0.03, 95% CI = -0.04 to -0.03).Conclusion: Variations in diet quality between sociodemographic groups were partially explained by differences in PNK, suggesting that focusing public health efforts on increasing this specific knowledge type might be promising. [ABSTRACT FROM AUTHOR]

This study aims to compare the effectiveness, engagement, usability, and acceptability of a web-based, computer-tailored physical activity intervention (provided as video or text) between participants who were matched or mismatched to their self-reported learning style (visual and auditory delivery through video or text-based information). Generalised linear mixed models were conducted to compare time (baseline, 3 months) by group (matched, mismatched) on ActiGraph-GT3X+measured moderate-to-vigorous physical activity (MVPA) and steps. Generalised linear models were used to compare group (matched and mismatched) on session completion, time-on-site, usability, and acceptability. MVPA and steps improved from baseline to 3-months, however this did not differ between participants whose learning styles were matched or mismatched to the intervention they received. Session completion, time-on-site, usability, and acceptability did not differ between matched and mismatched participants. Therefore, aligning intervention delivery format to learning style is unlikely to influence intervention effectiveness or engagement. [ABSTRACT FROM AUTHOR]

Abstract Objective Methods and Measures Results Conclusion Action planning is a common approach used in physical activity interventions. The aim of this study was to assess the association of frequency, consistency and content of action planning with physical activity behaviour, intention strength and habit strength.Within a 3-month web-based, computer-tailored physical activity intervention, participants (N = 115; 68.7% female, M age =43.9; range = 22–73 years) could create 6 rounds of action plans for 4 activities each (24 total).Consistency of action planning during the intervention was associated with change in physical activity at 9-months, and intention and habit strength at 3-months and 9-months. Frequency of action planning was negatively associated with intention at 3-months and 9-months. The effect of action planning consistency on physical activity behaviour was no longer significant when accounting for change in intention and habit strength.Consistency of how, where, when and with whom people plan their physical activity may translate into stronger physical activity habits. Interventions should avoid encouraging making many distinct action plans, but rather encourage stable contexts through consistent action planning. [ABSTRACT FROM AUTHOR]