Synergizing the Behavior Change Wheel and a Cocreative Approach to Design a Physical Activity Intervention for Adolescents and Young Adults With Intellectual Disabilities: Development Study.

BACKGROUND: There is a need for physical activity promotion interventions in adolescents and young adults with intellectual disabilities. Current interventions have shown limited effectiveness, which may be attributed to the absence of theory and a population-specific development. Combining a planning model (including theory) and cocreation with the target audience during intervention development could potentially address this gap. OBJECTIVE: This study aimed to report the systematic development of the Move it, Move ID! intervention by describing how the 8 different steps of the Behavior Change Wheel (BCW) were applied and present the results that emerged from those steps. In doing so, the (theoretical) content of the intervention is described in detail. METHODS: A total of 23 adolescents and young adults (aged 14-22 years) with mild to moderate intellectual disabilities were designated as cocreators of the intervention. Across 2 groups, 6 similar cocreation sessions were organized in each. The content and sequence of the sessions were structured to align with the 8 steps of the BCW. All sessions were recorded and transcribed verbatim. Both a deductive (ie, steps of the BCW) and inductive (ie, resonating the voice of the participants) analysis approach were applied specifically focusing on identifying and describing the findings within each of the BCW steps. RESULTS: After behavioral analysis (steps 1-4), 10 intervention goals were chosen and linked to Capability, Opportunity, and Motivation-Behavior components (theory within the BCW) that needed to be addressed. Psychological capability, social opportunity, and reflective motivation were emphasized as the first targets to focus on. A key finding was the urge for real-life social connectedness and social integration, which makes the social component as part of physical activity a central theme to focus on within intervention development. Judgments on the most suitable intervention functions (step 5) and behavior change techniques (step 7) were explained. When discussing the mode of delivery of the intervention (step 8), it was underscored that solely relying on a mobile health app would not fulfill participants' social needs. Hence, the chosen intervention adopts a dyadic approach in which young individuals with intellectual disabilities are matched with peers without intellectual disabilities to engage in physical activities together, with a mobile app playing a supportive role in this partnership. CONCLUSIONS: The transparent description of the development process highlights why certain intervention components and behavior change techniques were chosen and how they are intertwined by means of the selected intervention design. This paper provides a detailed blueprint for practitioners wanting to integrate the BCW and its associated behavior change techniques, in combination with actively involving the target group, into their intervention development for people with intellectual disabilities.

Older Adults' User Engagement With Mobile Health: A Systematic Review of Qualitative and Mixed-Methods Studies.

Background and Objectives: The aging population places increasing demands on our healthcare system. Mobile health offers the potential to reduce this burden. The aim of this systematic review is to thematically synthesize qualitative evidence of older adults' user engagement toward mobile health, and to generate relevant recommendations for intervention developers. Research Design and Methods: A systematic literature search was performed in Medline, Embase, and Web of Science electronic databases from inception until February 2021. Papers on qualitative and mixed-methods studies that investigated older adults' user engagement with a mobile health intervention were included. Relevant data were extracted and analyzed using thematic analysis. The Critical Appraisal Skills Program Qualitative Checklist was used to assess the quality of the included studies. Results: Thirty-two articles were deemed eligible for inclusion in the review. Three overarching analytical themes emerged from the 25 descriptive themes generated by the line-by-line coding: the limited capabilities, the prerequisite of motivation, and the importance of social support. Discussion and Implications: Successful development and implementation of future mobile health intervention for older adults will be challenging given the physical and psychological limitations and motivational barriers that older adults experience. Design adaptations and well-thought-out blended alternatives (i.e., combining mobile health with face-to-face support) might be potential solutions to improve older adults' user engagement with mobile health interventions.

Co-creating an intervention to promote physical activity in adolescents with intellectual disabilities: lessons learned within the Move it, Move ID!-project.

BACKGROUND: Co-creation is a method to develop acceptable, contextually appropriate and potentially more effective interventions. Adolescents with intellectual disabilities (ID) seldomly participate in research and program development due to the assumption that they lack the capacity to understand and discuss the related topics. OBJECTIVE: This study describes reflections on a co-creation process with adolescents with ID from the point of view of the researchers in developing an intervention to increase physical activity. It was the aim to highlight elements that must be considered when implementing co-creation and consequently formulate important lessons learned. METHODS: Twenty-three adolescents (14-22 y) with mild to moderate ID participated in six co-creation sessions at their school. The objectives and working methods in each session are described. Inductive thematic analysis was conducted on the researchers' reflection forms, which were completed after each session. RESULTS: Seven main themes could be distinguished from the data: experiences related to assistance (i.e., teacher presence) during sessions, the importance of building rapport, co-decision making power, the impact of different group dynamics, the relevance of adapted questioning, the influence of co-creative working methods and required characteristics of a co-creation researcher. CONCLUSION: Seven lessons learned were formulated when preparing and conducting co-creation with adolescents with ID. Innovative, concrete (non-abstract) and creative working methods are highly needed. Describing the entire process transparently could be a first step to turn co-creative research into an evidence-based methodology.

Studies show that people with intellectual disabilities are less physically active than the general population. This is a problem, since people with intellectual disabilities experience more health problems, and physical activity might be an important angle to reduce these health problems. However, current interventions to promote physical activity in this target group do not appear to work because they do not match their needs and preferences. Therefore, it is important to develop interventions together with them, in collaboration, what is called "co-creation". This has not happened much in research with people with intellectual disabilities before (and especially not with adolescents having intellectual disabilities), because researchers often have the perception that they do not have the capabilities to understand and discuss research related topics. This study elaborates on the researchers' experiences in conducting co-creative research with adolescents and young adults with mild to moderate intellectual disabilities, and formulates 'lessons learned' so that future researchers can start from these findings when they themselves want to engage in a co-creation process with this target group. The results showed that co-creation is feasible with this target group, if co-creation methods are selected that fit the target group (e.g. making use of visuals, asking concrete (non-abstract) questions and providing clear but short instructions). We suggest that (standardized) innovative and creative working methods are needed when conducting co-creation with this target group. Moreover, to be better armed against the enormous flexibility expected of a co-creative researcher, it might be helpful to make an assessment of the group dynamics before conducting co-creation. The presence and contribution of the physical education teacher in these co-creation sessions was seen as an added value for several reasons. By describing this entire process transparently and in detail, this could be a first step in making co-creation an evidence-based methodology, also for vulnerable populations.

The role of socio-demographic factors and physical functioning in the intra- and interpersonal variability of older adults' sedentary time: an observational two-country study.

BACKGROUND: Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability. METHODS: Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability. RESULTS: Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time. CONCLUSIONS: The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults' sedentary time.

Nonusage Attrition of Adolescents in an mHealth Promotion Intervention and the Role of Socioeconomic Status: Secondary Analysis of a 2-Arm Cluster-Controlled Trial.

BACKGROUND: Mobile health (mHealth) interventions may help adolescents adopt healthy lifestyles. However, attrition in these interventions is high. Overall, there is a lack of research on nonusage attrition in adolescents, particularly regarding the role of socioeconomic status (SES). OBJECTIVE: The aim of this study was to focus on the role of SES in the following three research questions (RQs): When do adolescents stop using an mHealth intervention (RQ1)? Why do they report nonusage attrition (RQ2)? Which intervention components (ie, self-regulation component, narrative, and chatbot) prevent nonusage attrition among adolescents (RQ3)? METHODS: A total of 186 Flemish adolescents (aged 12-15 years) participated in a 12-week mHealth program. Log data were monitored to measure nonusage attrition and usage duration for the 3 intervention components. A web-based questionnaire was administered to assess reasons for attrition. A survival analysis was conducted to estimate the time to attrition and determine whether this differed according to SES (RQ1). Descriptive statistics were performed to map the attrition reasons, and Fisher exact tests were used to determine if these reasons differed depending on the educational track (RQ2). Mixed effects Cox proportional hazard regression models were used to estimate the associations between the use duration of the 3 components during the first week and attrition. An interaction term was added to the regression models to determine whether associations differed by the educational track (RQ3). RESULTS: After 12 weeks, 95.7% (178/186) of the participants stopped using the app. 30.1% (56/186) of the adolescents only opened the app on the installation day, and 44.1% (82/186) stopped using the app in the first week. Attrition at any given time during the intervention period was higher for adolescents from the nonacademic educational track compared with those from the academic track. The other SES indicators (family affluence and perceived financial situation) did not explain attrition. The most common reasons for nonusage attrition among participants were perceiving that the app did not lead to behavior change, not liking the app, thinking that they already had a sufficiently healthy lifestyle, using other apps, and not being motivated by the environment. Attrition reasons did not differ depending on the educational track. More time spent in the self-regulation and narrative components during the first week was associated with lower attrition, whereas chatbot use duration was not associated with attrition rates. No moderating effects of SES were observed in the latter association. CONCLUSIONS: Nonusage attrition was high, especially among adolescents in the nonacademic educational track. The reported reasons for attrition were diverse, with no statistical differences according to the educational level. The duration of the use of the self-regulation and narrative components during the first week may prevent attrition for both educational tracks. TRIAL REGISTRATION: ClinicalTrials.gov NCT04719858; http://clinicaltrials.gov/ct2/show/NCT04719858.

The association between Geographic Information System-based neighborhood built environmental factors and accelerometer-derived light-intensity physical activity across the lifespan: a cross-sectional study.

Background: Evidence on associations between environmental factors and accelerometer-derived light-intensity physical activity (LPA) is scarce. The aim of this study was to examine associations between Geographic Information System (GIS)-based neighborhood built environmental factors and accelerometer-derived LPA, and to investigate the moderating effect of age group (adolescents, adults, older adults) on these associations. Methods: Objective data were used from three similar observational studies conducted in Ghent (Belgium) between 2007 and 2015. Accelerometer data were collected from 1,652 participants during seven consecutive days, and GIS-based neighborhood built environmental factors (residential density, intersection density, park density, public transport density, entropy index) were calculated using sausage buffers of 500 m and 1,000 m around the home addresses of all participants. Linear mixed models were performed to estimate the associations. Results: A small but significant negative association was observed between residential density (500 m buffer) and LPA in the total sample (B = -0.002; SE = 0.0001; p = 0.04), demonstrating that every increase of 1,000 dwellings per surface buffer was associated with a two minute decrease in LPA. Intersection density, park density, public transport density and entropy index were not related to LPA, and moderating effects of age group were absent. Conclusions: The small association, in combination with other non-significant associations suggests that the neighborhood built environment, as classically measured in moderate-to-vigorous intensity physical activity research, is of limited importance for LPA. More research is needed to unravel how accelerometer-derived LPA is accumulated, and to gain insight into its determinants.

Identifying conducive contexts and working mechanisms of sedentary behaviour interventions in older adults: a realist review protocol as part of the 'Stand UP Seniors' project.

INTRODUCTION: Lifestyle behaviours, including sedentary behaviour, have been listed as key modifiable factors to promote healthy ageing. Sedentary behaviour is ubiquitous in older adults and has a strong link with age-related functional declines and chronic health conditions. Although several interventions have been developed aimed at the reduction of sedentary behaviour in older adults, little in-depth information is available on how these complex interventions work in different contexts. Therefore, the aim of our study was to unpack the mechanisms of how existing interventions aimed at the reduction of older adults' sedentary behaviour work or fail to work in particular contexts in order to optimise the development and implementation of future sedentary behaviour interventions. METHODS AND ANALYSIS: A realist review will be conducted as a first part of the Stand UP Seniors (SUPS) project and will be structured as follows: (1) defining the scope of the review, (2) searching and appraising the evidence, (3) extracting data and synthesising the results, and (4) drawing conclusions and formulating recommendations. The result of this iterative process will be a final programme theory that can be used to identify which context triggers which mechanism, and in turn might elicit which outcome. The final programme theory will be used to inform the second and the third parts of the SUPS project, which are, respectively, the development and evaluation of a sedentary behaviour intervention in older adults. ETHICS AND DISSEMINATION: Ethical approval is not required for the review. Dissemination of the realist review results, including the final programme theory, will occur through peer-reviewed publications and presentations at relevant conferences. The peer-reviewed realist review will be prepared according to the Realist and Meta-narrative Evidence Synthesis: Evolving Standards publication standards for realist syntheses. PROSPERO REGISTRATION NUMBER: CRD42021248795.

Participatory Development and Pilot Testing of an Adolescent Health Promotion Chatbot.

Background: The use of chatbots may increase engagement with digital behavior change interventions in youth by providing human-like interaction. Following a Person-Based Approach (PBA), integrating user preferences in digital tool development is crucial for engagement, whereas information on youth preferences for health chatbots is currently limited. Objective: The aim of this study was to gain an in-depth understanding of adolescents' expectations and preferences for health chatbots and describe the systematic development of a health promotion chatbot. Methods: Three studies in three different stages of PBA were conducted: (1) a qualitative focus group study (n = 36), (2) log data analysis during pretesting (n = 6), and (3) a mixed-method pilot testing (n = 73). Results: Confidentiality, connection to youth culture, and preferences when referring to other sources were important aspects for youth in chatbots. Youth also wanted a chatbot to provide small talk and broader support (e.g., technical support with the tool) rather than specifically in relation to health behaviors. Despite the meticulous approach of PBA, user engagement with the developed chatbot was modest. Conclusion: This study highlights that conducting formative research at different stages is an added value and that adolescents have different chatbot preferences than adults. Further improvement to build an engaging chatbot for youth may stem from using living databases.

Exploring Breaks in Sedentary Behavior of Older Adults Immediately After Receiving Personalized Haptic Feedback: Intervention Study.

BACKGROUND: "Push" components of mobile health interventions may be promising to create conscious awareness of habitual sedentary behavior; however, the effect of these components on the near-time, proximal outcome, being breaks in sedentary behavior immediately after receiving a push notification, is still unknown, especially in older adults. OBJECTIVE: The aims of this study are to examine if older adults break their sedentary behavior immediately after receiving personalized haptic feedback on prolonged sedentary behavior and if the percentage of breaks differs depending on the time of the day when the feedback is provided. METHODS: A total of 26 Flemish older adults (mean age 64.4 years, SD 3.8) wore a triaxial accelerometer (Activator, PAL Technologies Ltd) for 3 weeks. The accelerometer generated personalized haptic feedback by means of vibrations each time a participant sat for 30 uninterrupted minutes. Accelerometer data on sedentary behavior were used to estimate the proximal outcome, which was sedentary behavior breaks immediately (within 1, 3, and 5 minutes) after receiving personalized haptic feedback. Generalized estimating equations were used to investigate whether or not participants broke up their sedentary behavior immediately after receiving haptic feedback. A time-related variable was added to the model to investigate if the sedentary behavior breaks differed depending on the time of day. RESULTS: A total of 2628 vibrations were provided to the participants during the 3-week intervention period. Of these 2628 vibrations, 379 (14.4%), 570 (21.7%), and 798 (30.4%) resulted in a sedentary behavior break within 1, 3 and 5 minutes, respectively. Although the 1-minute interval did not reveal significant differences in the percentage of breaks depending on the time at which the haptic feedback was provided, the 3- and 5-minute intervals did show significant differences in the percentage of breaks depending on the time at which the haptic feedback was provided. Concretely, the percentage of sedentary behavior breaks was significantly higher if personalized haptic feedback was provided between noon and 3 PM compared to if the feedback was provided between 6 and 9 AM (odds ratio 1.58, 95% CI 1.01-2.47, within 3 minutes; odds ratio 1.78, 95% CI 1.11-2.84, within 5 minutes). CONCLUSIONS: The majority of haptic vibrations, especially those in the morning, did not result in a break in the sedentary behavior of older adults. As such, simply bringing habitual sedentary behavior into conscious awareness seems to be insufficient to target sedentary behavior. More research is needed to optimize push components in interventions aimed at the reduction of the sedentary behavior of older adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT04003324; https://clinicaltrials.gov/ct2/show/NCT04003324.

Sex-specific typologies of older adults' sedentary behaviors and their associations with health-related and socio-demographic factors: a latent profile analysis.

BACKGROUND: Some types of sedentary behaviors tend to cluster in individuals or groups of older adults. Insight into how these different types of sedentary behavior cluster is needed, as recent research suggests that not all types of sedentary behavior may have the same negative effects on physical and mental health. Therefore, the aim of this study was to identify sex-specific typologies of older adults' sedentary behavior, and to examine their associations with health-related and socio-demographic factors. METHODS: Cross-sectional data were collected as part of the BEPAS Seniors, and the Busschaert study among 696 Flemish older adults (60+). Typologies of self-reported sedentary behavior were identified using latent profile analysis, and associations with health-related and sociodemographic factors were examined using analyses of variances. RESULTS: Five distinct typologies were identified from seven sedentary behaviors (television time, computer time, transport-related sitting time, sitting for reading, sitting for hobbies, sitting for socializing and sitting for meals) in men, and three typologies were identified from six sedentary behaviors (television time, transport-related sitting time, sitting for reading, sitting for hobbies, sitting for socializing and sitting for meals) in women. Typologies that are characterized by high television time seem to be related to more negative health outcomes, like a higher BMI, less grip strength, and a lower physical and mental health-related quality-of-life. Typologies that are represented by high computer time and motorized transport seem to be related to more positive health outcomes, such as a lower body mass index, more grip strength and a higher physical and mental health-related quality-of-life. CONCLUSIONS: Although causal direction between identified typologies and health outcomes remains uncertain, our results suggests that future interventions should better focus on specific types of sedentary behavior (e.g. television time), or patterns of sedentary behavior, rather than on total sedentary behavior.

Engagement, Acceptability, Usability, and Preliminary Efficacy of a Self-Monitoring Mobile Health Intervention to Reduce Sedentary Behavior in Belgian Older Adults: Mixed Methods Study.

BACKGROUND: Although healthy aging can be stimulated by the reduction of sedentary behavior, few interventions are available for older adults. Previous studies suggest that self-monitoring might be a promising behavior change technique to reduce older adults' sedentary behavior. However, little is known about older adults' experiences with a self-monitoring-based intervention aimed at the reduction of sedentary behavior. OBJECTIVE: The aim of this study is to evaluate engagement, acceptability, usability, and preliminary efficacy of a self-monitoring-based mHealth intervention developed to reduce older adults' sedentary behavior. METHODS: A mixed methods study was performed among 28 community-dwelling older adults living in Flanders, Belgium. The 3-week intervention consisted of general sedentary behavior information as well as visual and tactile feedback on participants' sedentary behavior. Semistructured interviews were conducted to explore engagement with, and acceptability and usability of, the intervention. Sitting time was measured using the thigh-worn activPAL (PAL Technologies) accelerometer before and after the intervention. System usage data of the app were recorded. Quantitative data were analyzed using descriptive statistics and paired-samples t tests; qualitative data were thematically analyzed and presented using pen profiles. RESULTS: Participants mainly reported positive feelings regarding the intervention, referring to it as motivating, surprising, and interesting. They commonly reported that the intervention changed their thinking (ie, they became more aware of their sedentary behavior) but not their actual behavior. There were mixed opinions on the kind of feedback (ie, tactile vs visual) that they preferred. The intervention was considered easy to use, and the design was described as clear. Some problems were noticed regarding attaching and wearing the self-monitoring device. System usage data showed that the median frequency of consulting the app widely differed among participants, ranging from 0 to 20 times a day. No significant reductions were found in objectively measured sitting time. CONCLUSIONS: Although the intervention was well perceived by the majority of older adults, no reductions in sitting time were found. Possible explanations for the lack of reductions might be the short intervention duration or the fact that only bringing the habitual sedentary behavior into conscious awareness might not be sufficient to achieve behavior change. TRIAL REGISTRATION: ClinicalTrials.gov NCT04003324; https://tinyurl.com/y2p4g8hx.

Neighbourhood drivability: environmental and individual characteristics associated with car use across Europe.

BACKGROUND: Car driving is a form of passive transportation associated with higher sedentary behaviour, which is associated with morbidity. The decision to drive a car is likely to be influenced by the 'drivability' of the built environment, but there is lack of scientific evidence regarding the relative contribution of environmental characteristics of car driving in Europe, compared to individual characteristics. This study aimed to determine which neighbourhood- and individual-level characteristics were associated with car driving in adults of five urban areas across Europe. Second, the study aimed to determine the percentage of variance in car driving explained by individual- and neighbourhood-level characteristics. METHODS: Neighbourhood environment characteristics potentially related to car use were identified from the literature. These characteristics were subsequently assessed using a Google Street View audit and available GIS databases, in 59 administrative residential neighbourhoods in five European urban areas. Car driving (min/week) and individual level characteristics were self-reported by study participants (analytic sample n = 4258). We used linear multilevel regression analyses to assess cross-sectional associations of individual and neighbourhood-level characteristics with weekly minutes of car driving, and assessed explained variance at each level and for the total model. RESULTS: Higher residential density (ß:-2.61, 95%CI: - 4.99; -0.22) and higher land-use mix (ß:-3.73, 95%CI: - 5.61; -1.86) were significantly associated with fewer weekly minutes of car driving. At the individual level, higher age (ß: 1.47, 95%CI: 0.60; 2.33), male sex (ß: 43.2, 95%CI:24.7; 61.7), being employed (ß:80.1, 95%CI: 53.6; 106.5) and ≥ 3 person household composition (ß: 47.4, 95%CI: 20.6; 74.2) were associated with higher weekly minutes of car driving. Individual and neighbourhood characteristics contributed about equally to explained variance in minutes of weekly car driving, with 2 and 3% respectively, but total explained variance remained low. CONCLUSIONS: Residential density and land-use mix were neighbourhood characteristics consistently associated with minutes of weekly car driving, besides age, sex, employment and household composition. Although total explained variance was low, both individual- and neighbourhood-level characteristics were similarly important in their associations with car use in five European urban areas. This study suggests that more, higher quality, and longitudinal data are needed to increase our understanding of car use and its effects on determinants of health.

Older Adults' Perceptions of Sedentary Behavior: A Systematic Review and Thematic Synthesis of Qualitative Studies.

BACKGROUND AND OBJECTIVES: Reducing sedentary behavior contributes to healthy aging. In order to develop sedentary behavior interventions, insight is needed into older adults' perceptions of (reducing) sedentary behavior. Therefore, this systematic review aims to synthesize qualitative evidence of older adults' perceptions towards (a) the concept of sedentary behavior, (b) barriers and facilitators of sedentary behavior, and (c) solutions and strategies to reduce sedentary behavior. RESEARCH DESIGN AND METHODS: A systematic search was conducted in four electronic databases. Inclusion criteria comprised qualitative and mixed-methods studies investigating the perceptions of older adults (mean age: ≥60 years) towards (reducing) sedentary behavior. Quality of the included studies was rated using the Critical Appraisal Skills Programme (CASP) Qualitative Checklist. Relevant data on older adults' perceptions were extracted and imported into NVivo. Two independent reviewers analyzed the data by means of thematic synthesis (line-by-line coding, constructing descriptive (sub)themes, developing analytical themes). RESULTS: Fifteen studies were included. Four analytical themes were developed to be considered when aiming to reduce sedentary behavior in older adults: the lack of knowledge on/awareness of sedentary behavior, the habitual nature of sedentary behavior, the importance of enjoyment and convenience, and the key role of aging. DISCUSSION AND IMPLICATIONS: The reduction of older adults' sedentary behavior will likely be challenging as sedentary behavior seems to be firmly incorporated into older adults' daily routines, and strongly linked with positive reinforcement. Both aspects deserve thoughtful attention by intervention developers and health care professionals who aim to promote healthy aging by reducing sedentary behavior.

Effectiveness of interventions using self-monitoring to reduce sedentary behavior in adults: a systematic review and meta-analysis.

BACKGROUND: Sedentary behavior occurs largely subconsciously, and thus specific behavior change techniques are needed to increase conscious awareness of sedentary behavior. Chief amongst these behavior change techniques is self-monitoring of sedentary behavior. The aim of this systematic review and meta-analysis was to evaluate the short-term effectiveness of existing interventions using self-monitoring to reduce sedentary behavior in adults. METHODS: Four electronic databases (PubMed, Embase, Web of Science, and The Cochrane Library) and grey literature (Google Scholar and the International Clinical Trials Registry Platform) were searched to identify appropriate intervention studies. Only (cluster-)randomized controlled trials that 1) assessed the short-term effectiveness of an intervention aimed at the reduction of sedentary behavior, 2) used self-monitoring as a behavior change technique, and 3) were conducted in a sample of adults with an average age ≥ 18 years, were eligible for inclusion. Relevant data were extracted, and Hedge's g was used as the measure of effect sizes. Random effects models were performed to conduct the meta-analysis. RESULTS: Nineteen intervention studies with a total of 2800 participants met the inclusion criteria. Results of the meta-analyses showed that interventions using self-monitoring significantly reduced total sedentary time (Hedges g = 0,32; 95% CI = 0,14 - 0,50; p = 0,001) and occupational sedentary time (Hedge's g = 0,56; 95% CI = 0,07 - 0,90; p = 0,02) on the short term. Subgroup analyses showed that significant intervention effects were only found if objective self-monitoring tools were used (g = 0,40; 95% CI = 0,19 - 0,60; p < 0,001), and if the intervention only targeted sedentary behavior (g = 0,45; 95% CI = 0,15-0,75; p = 0,004). No significant intervention effects were found on the number of breaks in sedentary behavior. CONCLUSIONS: Despite the small sample sizes, and the large heterogeneity, results of the current meta-analysis suggested that interventions using self-monitoring as a behavior change technique have the potential to reduce sedentary behavior in adults. If future - preferably large-scale studies - can prove that the reductions in sedentary behavior are attributable to self-monitoring and can confirm the sustainability of this behavior change, multi-level interventions including self-monitoring may impact public health by reducing sedentary behavior.

Efficacy of a Self-Regulation-Based Electronic and Mobile Health Intervention Targeting an Active Lifestyle in Adults Having Type 2 Diabetes and in Adults Aged 50 Years or Older: Two Randomized Controlled Trials.

BACKGROUND: Adopting an active lifestyle plays a key role in the prevention and management of chronic diseases such as type 2 diabetes mellitus (T2DM). Web-based interventions are able to alter health behaviors and show stronger effects when they are informed by a behavior change theory. MyPlan 2.0 is a fully automated electronic health (eHealth) and mobile health (mHealth) intervention targeting physical activity (PA) and sedentary behavior (SB) based on the Health Action Process Approach (HAPA). OBJECTIVE: This study aimed to test the short-term effect of MyPlan 2.0 in altering levels of PA and SB and in changing personal determinants of behavior in adults with T2DM and in adults aged ≥50 years. METHODS: The study comprised two randomized controlled trials (RCTs) with an identical design. RCT 1 was conducted with adults with T2DM. RCT 2 was performed in adults aged ≥50 years. Data were collected via face-to-face assessments. The participants decided either to increase their level of PA or to decrease their level of SB. The participants were randomly allocated with a 2:1 ratio to the intervention group or the waiting-list control group. They were not blinded for their group allocation. The participants in the intervention group were instructed to go through MyPlan 2.0, comprising 5 sessions with an interval of 1 week between each session. The primary outcomes were objectively measured and self-reported PA (ie, light PA, moderate-to-vigorous PA, total PA, number of steps, and domain-specific [eg, transport-related] PA) and SB (ie, sitting time, number of breaks from sitting time, and length of sitting bouts). Secondary outcomes were self-reported behavioral determinants for PA and SB (eg, self-efficacy). Separate linear mixed models were performed to analyze the effects of MyPlan 2.0 in the two samples. RESULTS: In RCT 1 (n=54), the PA intervention group showed, in contrast to the control group, a decrease in self-reported time spent sitting (P=.09) and an increase in accelerometer-measured moderate (P=.05) and moderate-to-vigorous PA (P=.049). The SB intervention group displayed an increase in accelerometer-assessed breaks from sedentary time in comparison with the control group (P=.005). A total of 14 participants of RCT 1 dropped out. In RCT 2 (n=63), the PA intervention group showed an increase for self-reported total PA in comparison with the control group (P=.003). Furthermore, in contrast to the control group, the SB intervention group decreased their self-reported time spent sitting (P=.08) and increased their accelerometer-assessed moderate (P=.06) and moderate-to-vigorous PA (P=.07). A total of 8 participants of RCT 2 dropped out. CONCLUSIONS: For both the samples, the HAPA-based eHealth and mHealth intervention, MyPlan 2.0, was able to improve only some of the primary outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT03291171; http://clinicaltrials.gov/ct2/show/NCT03291171. ClinicalTrials.gov NCT03799146; http://clinicaltrials.gov/ct2/show/NCT03799146. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/12413.

The Moderating Role of Social Neighbourhood Factors in the Association between Features of the Physical Neighbourhood Environment and Weight Status.

BACKGROUND: This paper investigated the independent and joint associations between aspects of the physical neighbourhood environment and social neighbourhood factors with BMI and overweight status in European adults. METHODS: Data from 5,199 participants in the SPOTLIGHT survey were analysed. Participants reported on their height, weight and perceptions of the neighbourhood. Objectively measured aspects of the physical neighbourhood environment included: presence of recreational facilities, features of the active transportation environment, neighbourhood aesthetics and presence of different types of food outlets. Social factors included the self-reported variables social network, social cohesion, social trust and perceived crime and the census variable neighbourhood socioeconomic status. Outcome measures were BMI and overweight status. Main associations between physical and social factors and BMI/overweight status were analysed using multilevel regression analyses adjusted for confounders. Moderation analysis was conducted by adding the interaction terms between physical and social neighbourhood factors one by one to the multivariable models. Significant interaction terms were then stratified. RESULTS: Significant associations with BMI/overweight status were found for features of the active transportation environment and all social factors, except perceived crime. Several significant interaction terms were detected, but no significant associations between the physical neighbourhood environment and BMI/overweight status were found after stratification. CONCLUSION: We did not find consistent interactions between physical and social neighbourhood factors to explain BMI and overweight status.

What factors explain socioeconomic inequalities in adults' television-related sitting time?

BACKGROUND: There are considerable socioeconomic inequalities in television-related sitting time, but there is little evidence for the explanatory mechanisms. We used a cohort of Belgian adults (25-60 years) and older adults (≥65 years) to examine the social cognitive, home environmental and health-related factors contributing to socioeconomic differences in television-related sitting. METHODS: We included 301 adults and 258 older adults (total n = 559). Linear regression analyses were used to examine the associations of education and occupational status with television-related sitting time, adjusted for age and gender. We assessed the explanatory power of social cognitive, home environmental and health-related factors using the traditional 'change-in-estimation method'. RESULTS: Those with low and medium education, respectively, engaged in 54 and 28 minutes per day more television-related sitting time than those with high education. We found no association between occupational status and television-related sitting time. Social cognitive factors explained 54% of the difference in television-related sitting time between those with low and high education, while home environmental factors only explained 6%, and health-related variables explained 10% of these differences. CONCLUSION: We found no occupational inequalities in television-related sitting time. Social cognitive variables such as attitude and modelling of the partner explained a large part of the educational inequalities in television-related sitting time. If confirmed by future studies, a focus on social cognition may help reduce sedentary behaviours in low-educated adults and diminish inequalities in sedentary behaviours.

Differences in Context-Specific Sedentary Behaviors According to Weight Status in Adolescents, Adults and Seniors: A Compositional Data Analysis.

To develop effective sedentary behavior interventions aimed at people who are overweight/obese, detailed insight is needed into the contexts of sedentary behavior of these people. Therefore, the aims of this study were to describe the composition of sedentary behavior and to compare context-specific sedentary behaviors between different weight groups. Cross-sectional data were used from a study conducted in 2013⁻2014 among a Flemish sample of adolescents (n = 513), adults (n = 301), and seniors (n = 258). Sixteen context-specific sedentary behaviors were assessed using a validated questionnaire during the week and weekend. Compositional descriptive statistics were performed to determine the relative contribution of context-specific sedentary behaviors in the three age groups. Compositional multivariate analysis of covariance and pairwise comparisons were conducted to examine weight group differences in context-specific sedentary behaviors. The compositional means indicated that the highest proportion of sedentary time was spent at school, at work, and while watching television. Statistically significant differences were found in the composition of sedentary behaviors between healthy weight and overweight/obese participants. In all age groups, socially engaging sedentary behaviors were more prevalent in healthy weight people, whereas socially disengaging behaviors were more prevalent in overweight/obese people. Consequently, the findings of this study suggest that future overweight/obesity interventions should no longer focus on total sedentary time, as not all context-specific sedentary behaviors are associated with overweight/obesity. Instead, it might be better to target specific contexts of sedentary behaviors-preferably those less socially engaging-when aiming to reduce overweight/obesity.

Exploring the cross-sectional association between outdoor recreational facilities and leisure-time physical activity: the role of usage and residential self-selection.

BACKGROUND: The availability of outdoor recreational facilities is associated with increased leisure-time physical activity (PA). We investigated how much of this association is attributable to selection effects, and explored whether usage of recreational facilities was an explanatory mechanism. METHODS: We analysed data from 5199 participants in the SPOTLIGHT survey residing in five European urban regions. Adults completed a survey and a Google Street View-based virtual audit was conducted to objectively measure the availability of outdoor recreational facilities in the residential neighbourhood. We used negative binomial GEE models to examine the association between objective and subjective availability of outdoor recreational facilities and leisure-time PA, and explored whether this association was attenuated after adjustment for socioeconomic status and preference for neighbourhoods with recreational facilities (as indicators of self-selection). We examined whether reported use of recreational facilities was associated with leisure-time PA (as explanatory mechanism), and summarized the most important motivations for (not) using recreational facilities. RESULTS: Subjective - but not objective - availability of outdoor recreational facilities was associated with higher levels of total leisure-time PA. After adjustment for self-selection (which attenuated the association by 25%), we found a 25% difference in weekly minutes of total leisure-time PA between individuals with and without self-reported availability of outdoor recreational facilities. For our study population, this translates to about 28 min per week. Participants who reported outdoor recreational facilities to be present but indicated not to use them (RR = 1.19, 95% CI = 1.03;1.22), and those reporting outdoor recreational facilities to be present and to use them (RR = 1.33, 95% CI = 1.22, 1.45) had higher levels of total leisure-time PA than those who reported outdoor recreational facilities not to be present. Proximity to outdoor recreational facilities was the most important motivation for use. CONCLUSION: The modest attenuation in the association between availability of outdoor recreational facilities and self-reported leisure-time PA suggests that individuals' higher activity levels may be due more to the perceived availability of outdoor recreational facilities than to self-selection. The use of these facilities seemed to be an important underlying mechanism, and proximity was the main motivator for using recreational facilities.

Lack of interest in physical activity - individual and environmental attributes in adults across Europe: The SPOTLIGHT project.

A considerable proportion of European adults report little or no interest in physical activity. Identifying individual-level and environmental-level characteristics of these individuals can help designing effective interventions and policies to promote physical activity. This cross-sectional study additionally explored associations between level of interest and physical activity, after controlling for other individual and environmental variables. Measures of objective and perceived features of the physical environment of residence, self-reported physical activity and other lifestyle behaviors, barriers towards physical activity, general health, and demographics were obtained from 5205 European adults participating in the 2014 online SPOTLIGHT survey. t-Tests, chi-square tests, and generalized estimating equations with negative binomial log-link function were conducted. Adults not interested in physical activity reported a higher BMI and a lower self-rated health, were less educated, and to a smaller extent female and less frequently employed. They were more prone to have less healthy eating habits, and to perceive more barriers towards physical activity. Only minor differences were observed in environmental attributes: the non-interested were slightly more likely to live in neighborhoods objectively characterized as less aesthetic and containing more destinations, and perceived as less functional, safe, and aesthetic. Even after controlling for other individual and environmental factors, interest in physical activity remained a significant correlate of physical activity, supporting the importance of this association. This study is among the first to describe characteristics of individuals with reduced interest in physical activity, suggesting that (lack of) interest is a robust correlate of physical activity in several personal and environmental conditions.