The Regulate your Sitting Time (RESIT) intervention for reducing sitting time in individuals with type 2 diabetes: findings from a randomised-controlled feasibility trial

BACKGROUND

Reducing and breaking up sitting is recommended for optimal management of Type 2 diabetes mellitus (T2DM). Yet, there is limited evidence of interventions targeting these outcomes in individuals with this condition. The primary aim of this study was to assess the feasibility and acceptability of delivering and evaluating a tailored online intervention to reduce and break up sitting in adults with T2DM.

METHODS

A mixed-methods two-arm randomised controlled feasibility trial was conducted in ambulatory adults with T2DM who were randomised 1:1 to the REgulate your SItting Time (RESIT) intervention or usual care control group. The intervention included online education, self-monitoring and prompt tools (wearable devices, smartphone apps, computer apps) and health coaching. Feasibility outcomes were recruitment, attrition, data completion rates and intervention acceptability. Measurements of device-assessed sitting (intended primary outcome for definitive trial), standing and stepping, and physical function, psychosocial health and wellbeing were taken at baseline, 3 months and 6 months. Individual semi-structured interviews were conducted at six-months (post intervention) to explore acceptability, feasibility and experiences of the trial and intervention using the Framework Method.

RESULTS

Seventy participants aged 55 ± 11 years were recruited. Recruitment rate (proportion of eligible participants enrolled into the study) was 67% and participant retention rate at 6 months was 93% (n = 5 withdrawals). Data completion rates for daily sitting were 100% at baseline and ranged from 83 to 91% at 3 months and 6 months. Descriptive analysis demonstrated potential for the intervention to reduce device-measured sitting, which was 30.9 ± 87.2 and 22.2 ± 82.5 min/day lower in the intervention group at 3 and 6 months, respectively, compared with baseline. In the control group, sitting was 4.4 ± 99.5 and 23.7 ± 85.2 min/day lower at 3 and 6 months, respectively. Qualitative analysis identified three themes: reasons for participating in the trial, acceptability of study procedures, and the delivery and experience of taking part in the RESIT intervention. Overall, the measurement visits and intervention were acceptable to participants.

CONCLUSIONS

This study demonstrated the feasibility and acceptability of the RESIT intervention and evaluation methods, supporting a future definitive trial. If RESIT is found to be clinically effective, this could lead to changes in diabetes healthcare with a focus on reducing sitting.

TRIAL REGISTRATION

The trial was registered with ISRCTN (number ISRCTN14832389).

Smartphone-based educational and counseling interventions for women with high body mass index at Urmia's health centers

BACKGROUND AND PURPOSE

Overweight and obesity in women of reproductive age not only contribute to chronic diseases but also lead to fertility issues, adverse pregnancy outcomes, and psychological challenges. Among the detrimental behaviors associated with obesity, the consumption of fast foods and sedentary lifestyles have the most significant impact on weight gain and require effective interventions. This study aims to examine the effectiveness of an educational and counseling smartphone intervention in raising awareness and modifying behaviors related to sedentary behavior and fast food consumption in women with high body mass index.

MATERIALS AND METHODS

This randomized controlled trial was conducted with two parallel groups comprising 106 women of reproductive age who sought assistance at Urmia health centers in 2022. Participants with diverse social and economic backgrounds were included. They were randomly assigned to either a control group or an intervention group. Valid and reliable questionnaires were administered to assess awareness regarding sedentary behaviors and fast foods consumption, as well as engagement in sedentary behaviors and consumption of fast foods. In addition to standard care, the intervention group received educational and counseling sessions through a dedicated smartphone application. Data analysis was performed using SPSS 20 software at a significance level of P < 0.05.

FINDINGS

The results of a statistical t-test indicated a noteworthy disparity between the control and intervention groups concerning the average awareness scores related to fast foods consumption (P < 0.001) and sedentary behaviors (P < 0.001) before and 3 months after the intervention. Additionally, a substantial statistical difference was observed in the mean consumption of fast foods (P < 0.001) and hours of sedentary behaviors (P < 0.001) before and 3 months after the intervention when comparing the two groups.

CONCLUSION

Educational and counseling programs, when applied effectively, can serve the dual purpose of enhancing awareness concerning sedentary behaviors and fast foods consumption while concurrently fostering a reduction in the prevalence of these behaviors. The study was registered in the Iranian Registry of Clinical Trials (IRCT Id: IRCT20210722051953N1) at 04/08/2021.

Effects on sedentary behaviour of an approach to reduce sedentary behaviour in patients with minor ischaemic stroke: A randomised controlled trial

OBJECTIVES

To determine the effects on sedentary behaviour of an approach that promotes reduction in sedentary behaviour in patients with minor ischaemic stroke after intervention and at follow-up.

DESIGN

A randomised controlled trial.

SETTING

During hospitalisation and after hospital discharge.

SUBJECTS

In total, 86 patients with minor ischaemic stroke admitted to an acute care hospital were assigned to the intervention (n = 43) and control (n = 43) groups.

INTERVENTION

An intervention group that received an approach to reduce sedentary behaviour upon hospital admission until 3 months after discharge (education, self-monitoring, phone calls, etc.) and a control group that received the usual care during hospitalisation. From 3 to 6 months after discharge, no group received any intervention.

MAIN OUTCOME

The primary outcome was the change (%) in sedentary behaviour from baseline to post-intervention (3 months after discharge) and follow-up (6 months after discharge). Sedentary behaviour was measured at baseline (upon hospital admission), post-intervention, and at follow-up using accelerometers.

RESULTS

At the post-intervention stage, the intervention group showed a significantly greater change in sedentary behaviour from baseline than that shown by the control group (sedentary behaviour: intervention group, -22.7%; control group, -14.9%; P = 0.013; effect size = 0.58). At follow-up too, the intervention group showed a significantly greater change in sedentary behaviour from baseline than that shown by the control group (sedentary behaviour: intervention group, -20.4%; control group, -13.6%; P = 0.025; effect size = 0.54).

CONCLUSIONS

An approach to reduce sedentary behaviour in patients with minor ischaemic stroke effectively reduces sedentary behaviour, which is sustained up to follow-up.

TRIAL REGISTRATION

This study is registered at www.umin.ac.jp/ctr/index/htm UMIN000038616.

Effects of Attitudes towards Exercise Behaviour, Use of Sports Apps and COVID-19 on Intentions to Exercise

The sudden outbreak of the novel coronavirus pandemic in 2019 disrupted the normal order of life and work, and the virus is still a major threat prevailing the globe. Confronted with the unknown virus, citizens have been following government policies of COVID-19 treatment and containment, and actively improving their immunity through physical activity (PA). This paper is concerned with ways to guide or promote people’s willingness to exercise, one of the most effective means to boost immunity. Based on the “attitude–intention” correlation defined in the theory of planned behaviour (TPB), this study, by synchronizing online data about workouts, explores the influence of people’s attitudes towards PA behaviour in promoting their intentions to engage in such behaviours as a means to fight the pandemic. In addition, the attitudes towards the use of sports apps and the epidemic are also reckoned with to investigate influencing factors promoting physical activity during the lockdown. The results of the study have been derived from the data of 1223 valid questionnaires, which are subjected to hierarchical regression analysis. Attitudes towards exercise and the use of sports apps are proven to have a significant impact on PA intentions, and the two variables are in direct proportion, with more positive attitudes leading to higher intentions; in contrast, attitudes towards the epidemic do not exhibit an obvious effect. In this light, it is advisable that when clinicians treat COVID-19 patients and medical departments respond to the epidemic, they actively make affirmative influences on peoples’ attitudes towards exercise and formulate appropriate exercise plans based on indicators detected and recorded by sports apps such as vital capacity, heart rate, respiratory index and self-perceived intensity to help them face the risk of the epidemic with more confidence.

Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach

The ubiquitous nature of smartphone ownership, its broad application and usage, along with its interactive delivery of timely feedback are appealing for health-related behavior change interventions via mobile apps. However, users' perspectives about such apps are vital in better bridging the gap between their design intention and effective practical usage. In this vein, a modified technology acceptance model (mTAM) is proposed here, to explain the relationship between users' perspectives when using an AI-based smartphone app for personalized nutrition and healthy living, namely, PROTEIN, and the mTAM constructs toward behavior change in their nutrition and physical activity habits. In particular, online survey data from 85 users of the PROTEIN app within a period of 2 months were subjected to confirmatory factor analysis (CFA) and regression analysis (RA) to reveal the relationship of the mTAM constructs, i.e., perceived usefulness (PU), perceived ease of use (PEoU), perceived novelty (PN), perceived personalization (PP), usage attitude (UA), and usage intention (UI) with the users' behavior change (BC), as expressed via the acceptance/rejection of six related hypotheses (H1-H6), respectively. The resulted CFA-related parameters, i.e., factor loading (FL) with the related p-value, average variance extracted (AVE), and composite reliability (CR), along with the RA results, have shown that all hypotheses H1-H6 can be accepted (p < 0.001). In particular, it was found that, in all cases, FL > 0.5, CR > 0.7, AVE > 0.5, indicating that the items/constructs within the mTAM framework have good convergent validity. Moreover, the adjusted coefficient of determination (R 2) was found within the range of 0.224-0.732, justifying the positive effect of PU, PEoU, PN, and PP on the UA, that in turn positively affects the UI, leading to the BC. Additionally, using a hierarchical RA, a significant change in the prediction of BC from UA when the UI is used as a mediating variable was identified. The explored mTAM framework provides the means for explaining the role of each construct in the functionality of the PROTEIN app as a supportive tool for the users to improve their healthy living by adopting behavior change in their dietary and physical activity habits. The findings herein offer insights and references for formulating new strategies and policies to improve the collaboration among app designers, developers, behavior scientists, nutritionists, physical activity/exercise physiology experts, and marketing experts for app design/development toward behavior change.

Where Does the Time Go? Displacement of Device-Measured Sedentary Time in Effective Sedentary Behaviour Interventions: Systematic Review and Meta-Analysis

BACKGROUND

Research has shown the effectiveness of sedentary behaviour interventions on reducing sedentary time. However, no systematic review has studied where the reduced sedentary time after such interventions is displaced to.

OBJECTIVE

Our objective was to synthesize the evidence from interventions that have reduced sedentary behaviour and test the displacement of sedentary time into physical activity (light physical activity [LPA], moderate-to-vigorous physical activity [MVPA], standing, and stepping).

METHODS

Two independent researchers performed a systematic search of the EBSCOhost, PubMed, Scopus, and Web of Science electronic databases. Meta-analyses were performed to examine the time reallocated from sedentary behaviour to physical activity during working time and the whole day in intervention trials (randomized/non-randomized controlled/non-controlled).

RESULTS

A total of 36 studies met all the eligibility criteria and were included in the systematic review, with 26 studies included in the meta-analysis. Interventions showed a significant overall increase in worksite LPA (effect size [ES] 0.24; 95% confidence interval [CI] 0.05 to 0.43; P < 0.013) and daily LPA (ES 0.62; 95% CI 0.34 to 0.91; P = 0.001). A statistically significant increase in daily MVPA was observed (ES 0.47; 95% CI 0.26 to 0.67; P < 0.001). There was a significant overall increase in worksite standing time (ES 0.76; 95% CI 0.56 to 0.95; P < 0.001), daily standing time (ES 0.52; 95% CI 0.38 to 0.65; P < 0.001), and worksite stepping time (ES 0.12; 95% CI 0.04 to 0.20; P = 0.002).

CONCLUSIONS

Effective interventions aimed at reducing sedentary behaviour result in a consistent displacement of sedentary time to LPA and standing time, both at worksites and across the whole day, whereas changes in stepping time or MVPA are dependent on the intervention setting. Strategies to reduce sedentary behaviour should not be limited to worksite settings, and further efforts may be required to promote daily MVPA.

TRIAL REGISTRATION

PROSPERO registration number CRD42020153958.

mHealth-Supported Interventions With Potential to Address Sedentary Behavior in Older Adults: A Scoping Review

Sedentary behavior (SB) is an independent risk for negative health outcomes in older adults. Mobile health (mHealth) technology has potential to address SB in this population. This scoping review aimed to describe, synthesize, and identify gaps in literature on mHealth-supported interventions with potential to reduce sedentariness in older people. Following an iterative search of five major databases, 13 studies were included in the final review. Only three papers described SB-related factors as the primary target of intervention. mHealth-Driven components were frequently paired with nonmobile approaches and aided self-regulation of physical activity as opposed to SB. Most SB-related outcomes were not statistically significant or were inconclusive. This scoping review revealed a paucity of research applying mHealth-supported approaches to directly overcome sedentariness in older people. Protocol studies included in the review provide evidence that efforts to address this research gap continue to be made, but the need for additional high-quality research remains.

Effectiveness of physical activity monitors in adults: systematic review and meta-analysis

OBJECTIVE

To estimate the effectiveness of physical activity monitor (PAM) based interventions among adults and explore reasons for the heterogeneity.

DESIGN

Systematic review and meta-analysis.

STUDY SELECTION

The electronic databases MEDLINE, Embase, SPORTDiscus, CINAHL, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched on 4 June 2021. Eligible randomised controlled trials compared interventions in which adults received feedback from PAMs with control interventions in which no feedback was provided. No restrictions on type of outcome measurement, publication date, or language were applied.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently extracted data and assessed risk of bias. Random effects meta-analyses were used to synthesise the results. The certainty of evidence was rated by the Grading of Recommendations Assessment and Evaluation (GRADE) approach.

MAIN OUTCOME MEASURES

The three primary outcomes of interest were physical activity, moderate to vigorous physical activity, and sedentary time.

RESULTS

121 randomised controlled trials with 141 study comparisons, including 16 743 participants, were included. The PAM based interventions showed a moderate effect (standardised mean difference 0.42, 95% confidence interval 0.28 to 0.55) on physical activity, equivalent to 1235 daily steps; a small effect (0.23, 0.16 to 0.30) on moderate to vigorous physical activity, equivalent to 48.5 weekly minutes; and a small insignificant effect (-0.12, -0.25 to 0.01) on sedentary time, equal to 9.9 daily minutes. All outcomes favoured the PAM interventions.

CONCLUSIONS

The certainty of evidence was low for the effect of PAM based interventions on physical activity and moderate for moderate to vigorous physical activity and sedentary time. PAM based interventions are safe and effectively increase physical activity and moderate to vigorous physical activity. The effect on physical activity and moderate to vigorous physical activity is well established but might be overestimated owing to publication bias.

STUDY REGISTRATION

PROSPERO CRD42018102719.

Approaches to Promote Reduction in Sedentary Behavior in Patients With Minor Ischemic Stroke: A Randomized Controlled Trial

OBJECTIVE

The purpose of this study was to determine whether an approach that promotes reduction in sedentary behavior (SB) during hospitalization and after hospital discharge reduces SB in patients with minor ischemic stroke (MIS) compared with an approach that promotes an increase in physical activity levels.

DESIGN

Randomized controlled trial design.

SETTING

During hospitalization and after hospital discharge.

PARTICIPANTS

We randomly assigned patients (N=61) with MIS (average age, 71.3±8.3y; 65.6% men) admitted to an acute hospital to either the intervention group (reduced SB, n=31) or the control group (increased physical activity levels, n=30).

INTERVENTIONS

During hospitalization, the intervention group received education on reducing SB, goal setting for SB after hospital discharge, and self-monitoring of SB and step count. In contrast, the control group received education on increasing physical activity levels and self-monitoring of step count. Patients in both groups wore an accelerometer during hospitalization until 3 months after hospital discharge. The intervention group received self-monitoring of SB and step count, stickers including information about reducing their SB, and phone calls once every 2 weeks for encouragement and feedback. The control group only wore the accelerometer.

MAIN OUTCOME MEASURES

The primary outcome was SB (in percentage) at 3 months after hospital discharge.

RESULTS

There was an interaction between the 2 groups for SB. Compared with the control group, the intervention group showed a significantly reduced SB (intervention group: baseline, 70.5%; 3 months after hospital discharge, 48.6%; control group: baseline, 71.5%; 3 months after hospital discharge, 57.5%; F value=5.981; P=.018).

CONCLUSIONS

The results suggested that an approach that promotes SB reduction during hospitalization and after hospital discharge is effective in reducing SB in patients with MIS 3 months after hospital discharge.

Efficacy, characteristics, behavioural models and behaviour change strategies, of non-workplace interventions specifically targeting sedentary behaviour; a systematic review and meta-analysis of randomised control trials in healthy ambulatory adults

BACKGROUND

Sedentary behaviour (SB) research has grown exponentially but efficacy for interventions to reduce sedentary behaviour is often contaminated by interventions primarily or co-targeting other behaviours and outcomes. The primary aim of this research therefore, was to systematically review the efficacy of interventions specifically targeting sedentary behaviour reduction, as a sole primary outcome, from randomised control trials in healthy ambulatory adults. This research also sought to identify the successful interventions characteristics, behaviour change techniques (BCT's) and underlying theories, and their relation to intervention effectiveness.

METHODS

We followed PRISMA reporting guidelines for this systematic review. Six electronic databases were searched and a grey literature review conducted. Only randomised or cluster randomised controlled trials, from 2000 to 2020, in adult populations with a sole primary outcome of change in sedentary behaviour were included. Data codebooks were developed, data were extracted, and a narrative synthesis and meta-analysis was conducted using mixed methods random effects models.

RESULTS

Of 5589 studies identified, 7 studies met the inclusion criteria. Six studies reported activPAL3 measures of mean daily sitting time, and four reported mean daily standing time, stepping time and number of sedentary breaks. Pooled analysis of weighted mean differences revealed a reduction in mean daily sitting time of -32.4mins CI (-50.3, -14.4), an increase in mean daily standing time of 31.75mins CI (13.7, 49.8), and mean daily stepping time of 9.5mins CI (2.8, 16.3), and an increase in rate of sedentary breaks per day of 3.6 (CI 1.6, 5.6). BCTs used exclusively in two of the three most effective interventions are 'feedback on behaviour' and 'goal setting behaviour' whilst all three most effective interventions included 'instruction on how to perform the behaviour' and 'adding objects to the environment', BCTs which were also used in less effective interventions.

CONCLUSIONS

Although limited by small sample sizes and short follow up periods, this review suggests that interventions specifically designed to change sedentary behaviour, reduce overall daily sitting time by half an hour, with an equivalent increase in standing time, in the short to medium term. Effective characteristics and behaviour change strategies are identified for future development of high quality interventions targeting change in sedentary behaviour.

PROSPERO REGISTRATION

PROSPERO 2020 CRD42020172457 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020172457.

SMART STEP - SMARTphone-driven exercise and pedometer-based STEP intervention to promote physical activity among desk-based employees: Study protocol for a three-arm cluster randomized controlled trial

BACKGROUND

Prolonged sitting in desk-based office workers is found to be associated with increased cardiometabolic risk and poor cognitive performance. Technology-based physical activity (PA) interventions using smartphone applications (SmPh app) to promote PA levels might be effective in reducing cardiometabolic risk among sedentary population but the evidence remains inconclusive.

OBJECTIVE

The objective is to investigate the effects of a technology-based PA intervention compared to PA education with a worksite manual or no intervention on PA levels, cardiometabolic risk, cognitive performance, and work productivity among desk-based employees.

METHOD

A three-arm clustered randomized trial will be conducted. The study will be conducted among various administrative offices of a multifaceted university in India. Desk-based employees aged between 30 and 50 years (n = 159; 53 in each arm) will be recruited. Employees from various constituent institutions (clusters) of the university will be randomized into one of the three following groups - SMART: SmPh app-driven break reminders (visual exercise prompts) plus pedometer-based step intervention, TRADE: worksite PA education with a manual plus American College of Sports Medicine guided PA prescription, or CONTROL: usual work group. At baseline and after the 1st, 3rd and 6th month of the trial period, accelerometer-measured sitting time and PA levels, cardiometabolic risk (fasting blood glucose, triglycerides, insulin, blood pressure, heart rate variability, functional capacity, and subcutaneous fat), cognitive performance (executive function), sickness absenteeism and work limitations will be assessed by a blinded assessor. Therapist delivering interventions will not be blinded.

CONCLUSION

This trial will determine whether a combined SmPh-app and pedometer-based intervention is more effective than education or no intervention in altering PA levels, cardiometabolic risk and cognitive performance among desk-based employees in India. This study has the potential to foster institutional recommendations for using SmPh-based technology and pedometers to promote PA and reduce sedentary behavior at work.

Mobile health apps to reduce sedentary behavior: a scoping review

Given the continued increase in mobile health applications (apps) aimed at healthcare and the recognition of sedentary behavior (SB) as a public health problem, the goal of this scoping review study was to summarize the effects of interventions based on mobile health apps designed to reduce SB in adults, with a specific focus on SB. The electronic databases PubMed, PsycINFO, SportDISCUS, Web of Science, and manual searches in reference lists were conducted on papers published up to September 2020. Nine out of the 897 studies researched were included and composed the descriptive synthesis. The investigations found in the present study showed a decrease in time spent on television viewing and in total time spent sitting, as well as an increase in the number of SB breaks after interventions based on mobile health apps. In conclusion, despite the growing interest in intervention programs in SB, only nine studies have used smartphone apps as a strategy to reduce SB in adults. Mobile health apps were proved to be effective in SB reduction, as assessed by different parameters, and should be encouraged. However, further studies are needed to verify the long-term effects of the utilization of such applications.

Interventions for reducing sedentary behaviour in community-dwelling older adults

BACKGROUND

Older adults are the most sedentary segment of society, often spending in excess of 8.5 hours a day sitting. Large amounts of time spent sedentary, defined as time spend sitting or in a reclining posture without spending energy, has been linked to an increased risk of chronic diseases, frailty, loss of function, disablement, social isolation, and premature death.

OBJECTIVES

To evaluate the effectiveness of interventions aimed at reducing sedentary behaviour amongst older adults living independently in the community compared to control conditions involving either no intervention or interventions that do not target sedentary behaviour.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, PsycINFO, PEDro, EPPI-Centre databases (Trials Register of Promoting Health Interventions (TRoPHI) and the Obesity and Sedentary behaviour Database), WHO ICTRP, and ClinicalTrials.gov up to 18 January 2021. We also screened the reference lists of included articles and contacted authors to identify additional studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and cluster-RCTs. We included interventions purposefully designed to reduce sedentary time in older adults (aged 60 or over) living independently in the community. We included studies if some of the participants had multiple comorbidities, but excluded interventions that recruited clinical populations specifically (e.g. stroke survivors).

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles and abstracts and full-text articles to determine study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted authors for additional data where required. Any disagreements in study screening or data extraction were settled by a third review author.

MAIN RESULTS

We included seven studies in the review, six RCTs and one cluster-RCT, with a total of 397 participants. The majority of participants were female (n = 284), white, and highly educated. All trials were conducted in high-income countries. All studies evaluated individually based behaviour change interventions using a combination of behaviour change techniques such as goal setting, education, and behaviour monitoring or feedback. Four of the seven studies also measured secondary outcomes. The main sources of bias were related to selection bias (N = 2), performance bias (N = 6), blinding of outcome assessment (N = 2), and incomplete outcome data (N = 2) and selective reporting (N=1). The overall risk of bias was judged as unclear. Primary outcomes The evidence suggests that interventions to change sedentary behaviour in community-dwelling older adults may reduce sedentary time (mean difference (MD) -44.91 min/day, 95% confidence interval (CI) -93.13 to 3.32; 397 participants; 7 studies; I² = 73%; low-certainty evidence). We could not pool evidence on the effect of interventions on breaks in sedentary behaviour or time spent in specific domains such as TV time, as data from only one study were available for these outcomes. Secondary outcomes We are uncertain whether interventions to reduce sedentary behaviour have any impact on the physical or mental health outcomes of community-dwelling older adults. We were able to pool change data for the following outcomes. • Physical function (MD 0.14 Short Physical Performance Battery (SPPB) score, 95% CI -0.38 to 0.66; higher score is favourable; 98 participants; 2 studies; I² = 26%; low-certainty evidence). • Waist circumference (MD 1.14 cm, 95% CI -1.64 to 3.93; 100 participants; 2 studies; I² = 0%; low-certainty evidence). • Fitness (MD -5.16 m in the 6-minute walk test, 95% CI -36.49 to 26.17; higher score is favourable; 80 participants; 2 studies; I² = 29%; low-certainty evidence). • Blood pressure: systolic (MD -3.91 mmHg, 95% CI -10.95 to 3.13; 138 participants; 3 studies; I² = 73%; very low-certainty evidence) and diastolic (MD -0.06 mmHg, 95% CI -5.72 to 5.60; 138 participants; 3 studies; I² = 97%; very low-certainty evidence). • Glucose blood levels (MD 2.20 mg/dL, 95% CI -6.46 to 10.86; 100 participants; 2 studies; I² = 0%; low-certainty evidence). No data were available on cognitive function, cost-effectiveness or adverse effects.

AUTHORS' CONCLUSIONS

It is not clear whether interventions to reduce sedentary behaviour are effective at reducing sedentary time in community-dwelling older adults. We are uncertain if these interventions have any impact on the physical or mental health of community-dwelling older adults. There were few studies, and the certainty of the evidence is very low to low, mainly due to inconsistency in findings and imprecision. Future studies should consider interventions aimed at modifying the environment, policy, and social and cultural norms. Future studies should also use device-based measures of sedentary time, recruit larger samples, and gather information about quality of life, cost-effectiveness, and adverse event data.

Are free workplace health promotion apps adequately mapped with behavior change theories, techniques and desired features? A content analysis

Free smartphone applications that aim to promote physical activity or reduce sedentary behavior at workplaces were questioned for its content such as technical features, behavior change techniques (BCT) and security concerns. To evaluate systematically whether smartphone apps are mapped adequately with BCTs and security concerns. Free apps in Google Play store were searched and coded for BCTs systematically in July 2020. Two reviewers independently coded apps that aimed to promote physical activity (n = 18) and reduce sedentary behavior (n = 16) using a taxonomy of 26 BCTs. BCTs, features and security concerns among apps promoting physical activity and reducing sedentary behavior were analyzed. While the features (social support, gamification, or rewards) help increase physical activity and decrease sedentary behavior, the apps do not typically include the above features. Further, the apps were based on an average of 13 (4-21) BCTs. The BCTs coded most frequently were "self-monitoring" (100%), "general encouragement" (97%), and "goal setting" (n = 94%). No significant relation between user rating and BCTs was found in the apps. Majority of the free apps that aimed to increase physical activity or reduce sedentary behavior at workplaces were not adequately based on BCTs and lacked essential features facilitating long term behavior compliance at workplaces. Hence, there is a need to develop newer applications mapped adequately with BCTs, involving the collaborative work of behavioral scientists, app developers and policymakers. Clinical Trial Registry of India CTRI/2020/03/024138.

Exploring the Views of Desk-Based Office Workers and Their Employers' Beliefs Regarding Strategies to Reduce Occupational Sitting Time, With an Emphasis on Technology-Supported Approaches

OBJECTIVE

Employee and employer views regarding how technology-supported strategies can best meet their needs to reduce occupational sitting are not well known. This study explored target user and key stakeholder beliefs regarding strategies to reduce occupational sitting focusing on technology-supported approaches.

METHODS

Nine focus groups and two interviews (employees, n = 27; employers, n = 19; board members, n = 2) were conducted, transcribed, and analyzed thematically.

RESULTS

The main barrier to reducing sitting was job-related tasks taking primary priority. Intervention designers should consider individual preferences, environmental factors, judgmental culture, productivity concerns, and staff knowledge. Technology-supported strategies such as smartphone applications, computer software, wearables, and emails were deemed to be useful tools to provide prompts and allow behavioral self-monitoring in an easily individualized manner.

CONCLUSIONS

Technology-supported strategies were seen to be valuable approaches and might fruitfully be incorporated into future interventions to reduce sitting time.

Interventions outside the workplace for reducing sedentary behaviour in adults under 60 years of age

BACKGROUND

Adults spend a majority of their time outside the workplace being sedentary. Large amounts of sedentary behaviour increase the risk of type 2 diabetes, cardiovascular disease, and both all-cause and cardiovascular disease mortality.

OBJECTIVES

Primary • To assess effects on sedentary time of non-occupational interventions for reducing sedentary behaviour in adults under 60 years of age Secondary • To describe other health effects and adverse events or unintended consequences of these interventions • To determine whether specific components of interventions are associated with changes in sedentary behaviour • To identify if there are any differential effects of interventions based on health inequalities (e.g. age, sex, income, employment) SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, Cochrane Database of Systematic Reviews, CINAHL, PsycINFO, SportDiscus, and ClinicalTrials.gov on 14 April 2020. We checked references of included studies, conducted forward citation searching, and contacted authors in the field to identify additional studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and cluster RCTs of interventions outside the workplace for community-dwelling adults aged 18 to 59 years. We included studies only when the intervention had a specific aim or component to change sedentary behaviour.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles/abstracts and full-text articles for study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted trial authors for additional information or data when required. We examined the following primary outcomes: device-measured sedentary time, self-report sitting time, self-report TV viewing time, and breaks in sedentary time.

MAIN RESULTS

We included 13 trials involving 1770 participants, all undertaken in high-income countries. Ten were RCTs and three were cluster RCTs. The mean age of study participants ranged from 20 to 41 years. A majority of participants were female. All interventions were delivered at the individual level. Intervention components included personal monitoring devices, information or education, counselling, and prompts to reduce sedentary behaviour. We judged no study to be at low risk of bias across all domains. Seven studies were at high risk of bias for blinding of outcome assessment due to use of self-report outcomes measures. Primary outcomes Interventions outside the workplace probably show little or no difference in device-measured sedentary time in the short term (mean difference (MD) -8.36 min/d, 95% confidence interval (CI) -27.12 to 10.40; 4 studies; I² = 0%; moderate-certainty evidence). We are uncertain whether interventions reduce device-measured sedentary time in the medium term (MD -51.37 min/d, 95% CI -126.34 to 23.59; 3 studies; I² = 84%; very low-certainty evidence) We are uncertain whether interventions outside the workplace reduce self-report sitting time in the short term (MD -64.12 min/d, 95% CI -260.91 to 132.67; I² = 86%; very low-certainty evidence). Interventions outside the workplace may show little or no difference in self-report TV viewing time in the medium term (MD -12.45 min/d, 95% CI -50.40 to 25.49; 2 studies; I² = 86%; low-certainty evidence) or in the long term (MD 0.30 min/d, 95% CI -0.63 to 1.23; 2 studies; I² = 0%; low-certainty evidence). It was not possible to pool the five studies that reported breaks in sedentary time given the variation in definitions used. Secondary outcomes Interventions outside the workplace probably have little or no difference on body mass index in the medium term (MD -0.25 kg/m², 95% CI -0.48 to -0.01; 3 studies; I² = 0%; moderate-certainty evidence). Interventions may have little or no difference in waist circumference in the medium term (MD -2.04 cm, 95% CI -9.06 to 4.98; 2 studies; I² = 65%; low-certainty evidence). Interventions probably have little or no difference on glucose in the short term (MD -0.18 mmol/L, 95% CI -0.30 to -0.06; 2 studies; I² = 0%; moderate-certainty evidence) and medium term (MD -0.08 mmol/L, 95% CI -0.21 to 0.05; 2 studies, I² = 0%; moderate-certainty evidence) Interventions outside the workplace may have little or no difference in device-measured MVPA in the short term (MD 1.99 min/d, 95% CI -4.27 to 8.25; 4 studies; I² = 23%; low-certainty evidence). We are uncertain whether interventions improve device-measured MVPA in the medium term (MD 6.59 min/d, 95% CI -7.35 to 20.53; 3 studies; I² = 70%; very low-certainty evidence). We are uncertain whether interventions outside the workplace improve self-reported light-intensity PA in the short-term (MD 156.32 min/d, 95% CI 34.34 to 278.31; 2 studies; I² = 79%; very low-certainty evidence). Interventions may have little or no difference on step count in the short-term (MD 226.90 steps/day, 95% CI -519.78 to 973.59; 3 studies; I² = 0%; low-certainty evidence) No data on adverse events or symptoms were reported in the included studies.

AUTHORS' CONCLUSIONS

Interventions outside the workplace to reduce sedentary behaviour probably lead to little or no difference in device-measured sedentary time in the short term, and we are uncertain if they reduce device-measured sedentary time in the medium term. We are uncertain whether interventions outside the workplace reduce self-reported sitting time in the short term. Interventions outside the workplace may result in little or no difference in self-report TV viewing time in the medium or long term. The certainty of evidence is moderate to very low, mainly due to concerns about risk of bias, inconsistent findings, and imprecise results. Future studies should be of longer duration; should recruit participants from varying age, socioeconomic, or ethnic groups; and should gather quality of life, cost-effectiveness, and adverse event data. We strongly recommend that standard methods of data preparation and analysis are adopted to allow comparison of the effects of interventions to reduce sedentary behaviour.

Randomised Controlled Feasibility Study of the MyHealthAvatar-Diabetes Smartphone App for Reducing Prolonged Sitting Time in Type 2 Diabetes Mellitus

This study evaluated the feasibility and acceptability of a self-regulation smartphone app for reducing prolonged sitting in people with Type 2 diabetes mellitus (T2DM). This was a two-arm, randomised, controlled feasibility trial. The intervention group used the MyHealthAvatar-Diabetes smartphone app for 8 weeks. The app uses a number of behaviour change techniques aimed at reducing and breaking up sitting time. Eligibility, recruitment, retention, and completion rates for the outcomes (sitting, standing, stepping, and health-related measures) assessed trial feasibility. Interviews with participants explored intervention acceptability. Participants with T2DM were randomised to the control (n = 10) and intervention groups (n = 10). Recruitment and retention rates were 71% and 90%, respectively. The remaining participants provided 100% of data for the study measures. The MyHealthAvatar-Diabetes app was viewed as acceptable for reducing and breaking up sitting time. There were preliminary improvements in the number of breaks in sitting per day, body fat %, glucose tolerance, attitude, intention, planning, wellbeing, and positive and negative affect in favour of the intervention group. In conclusion, the findings indicate that it would be feasible to deliver and evaluate the efficacy of the MyHealthAvatar-Diabetes app for breaking up sitting time and improving health outcomes in a full trial.

The effectiveness and complexity of interventions targeting sedentary behaviour across the lifespan: a systematic review and meta-analysis

BACKGROUND

Evidence suggests that sedentary behaviour (SB) is associated with poor health outcomes. SB at any age may have significant consequences for health and well-being and interventions targeting SB are accumulating. Therefore, the need to review the effects of multicomponent, complex interventions that incorporate effective strategies to reduce SB are essential.

METHODS

A systematic review and meta-analysis were conducted investigating the impact of interventions targeting SB across the lifespan. Six databases were searched and two review authors independently screened studies for eligibility, completed data extraction and assessed the risk of bias and complexity of each of the included studies.

RESULTS

A total of 77 adult studies (n=62, RCTs) and 84 studies (n=62, RCTs) in children were included. The findings demonstrated that interventions in adults when compared to active controls resulted in non-significant reductions in SB, although when compared to inactive controls significant reductions were found in both the short (MD -56.86; 95%CI -74.10, -39.63; n=4632; I2 83%) and medium-to-long term (MD -20.14; 95%CI -34.13, -6.16; n=4537; I2 65%). The findings demonstrated that interventions in children when compared to active controls may lead to relevant reductions in daily sedentary time in the short-term (MD -59.90; 95%CI -102.16, -17.65; n=267; I2 86%), while interventions in children when compared to inactive controls may lead to relevant reductions in the short-term (MD -25.86; 95%CI -40.77, -10.96; n=9480; I2 98%) and medium-to-long term (MD -14.02; 95%CI -19.49, -8.55; n=41,138; I2 98%). The assessment of complexity suggested that interventions may need to be suitably complex to address the challenges of a complex behaviour such as SB, but demonstrated that a higher complexity score is not necessarily associated with better outcomes in terms of sustained long-term changes.

CONCLUSIONS

Interventions targeting reductions in SB have been shown to be successful, especially environmental interventions in both children and adults. More needs to be known about how best to optimise intervention effects. Future intervention studies should apply more rigorous methods to improve research quality, considering larger sample sizes, randomised controlled designs and valid and reliable measures of SB.

Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review

Background

With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioral health interventions. The large variation in these mobile health apps—their target patient group, health behavior, and behavioral change strategies—has resulted in a large but incohesive body of literature.

Objective

This systematic review aimed to assess the effectiveness of mobile apps in improving health behaviors and outcomes and to examine the inclusion and effectiveness of behavior change techniques (BCTs) in mobile health apps.

Methods

PubMed, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behavior change. Two authors independently screened and selected studies according to the eligibility criteria. Data were extracted and the risk of bias was assessed by one reviewer and validated by a second reviewer.

Results

A total of 52 randomized controlled trials met the inclusion criteria and were included in the analysis—37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive—only one app was rated as less helpful and satisfactory than the control—and the studies that measured engagement and usability found relatively high study completion rates (mean 83%; n=18, N=39) and ease-of-use ratings (3 significantly better than control, 9/15 rated >70%). However, there was little evidence of changed behavior or health outcomes.

Conclusions

There was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the BCTs that are most effective at promoting behavior change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias.

A Scoping Review of Digital Tools to Reduce Sedentary Behavior or Increase Physical Activity in Knowledge Workers

Background: There is increasing interest in the role that technology can play in improving the vitality of knowledge workers. A promising and widely adopted strategy to attain this goal is to reduce sedentary behavior (SB) and increase physical activity (PA). In this paper, we review the state-of-the-art SB and PA interventions using technology in the office environment. By scoping the existing landscape, we identified current gaps and underexplored possibilities. We discuss opportunities for future development and research on SB and PA interventions using technology. Methods: A systematic search was conducted in the Association for Computing Machinery digital library, the interdisciplinary library Scopus, and the Institute of Electrical and Electronics Engineers Xplore Digital Library to locate peer-reviewed scientific articles detailing SB and PA technology interventions in office environments between 2009 and 2019. Results: The initial search identified 1130 articles, of which 45 studies were included in the analysis. Our scoping review focused on the technologies supporting the interventions, which were coded using a grounded approach. Conclusion: Our findings showed that current SB and PA interventions using technology provide limited possibilities for physically active ways of working as opposed to the common strategy of prompting breaks. Interventions are also often offered as additional systems or services, rather than integrated into existing office infrastructures. With this work, we have mapped different types of interventions and provide an increased understanding of the opportunities for future multidisciplinary development and research of technologies to address sedentary behavior and physical activity in the office context.

Can self-monitoring mobile health apps reduce sedentary behavior? A randomized controlled trial

OBJECTIVE

To examine whether the self-monitoring interventions of a mobile health app reduce sedentary behavior in the short and long terms.

METHOD

We designed a double-blind randomized control trial. Participants were selected from among the staff of a medical institution and registrants of an online research firm. Forty-nine participants were randomly assigned to either a control group (n = 25) or an intervention group (n = 24). The control group was given only the latest information about sedentary behavior, and the intervention was provided real-time feedback for self-monitoring in addition to the information. These interventions provided for 5 weeks (to measure the short-term effect) and 13 weeks (to measure the long-term effect) via the smartphone app. Measurements were as follows: subjective total sedentary time (SST), objective total sedentary time (OST), mean sedentary bout duration (MSB), and the number of sedentary breaks (SB). Only SST was measured by self-report based on the standardized International Physical Activity Questionnaire and others were measured with the smartphone.

RESULTS

No significant results were observed in the short term. In the long term, while no significant results were also observed in objective sedentary behavior (OST, MSB, SB), the significant differences were observed in subjective sedentary behavior (SST, βint  - βctrl between baseline and 9/13 weeks; 1.73 and 1.50 h/d, respectively).

CONCLUSIONS

Real-time feedback for self-monitoring with smartphone did not significantly affect objective sedentary behavior. However, providing only information about sedentary behavior to users with smartphones may make misperception on the amount of their subjective sedentary behavior.

Identifying characteristics of indicators of sedentary behavior using objective measurements

Objective

Recent attention has been focused on sedentary behavior (SB) affecting health outcomes, but the characteristics of indicators reflecting SB remain to be identified. This cross‐sectional study aims to identify the characteristics of indicators of SB, focusing on the examination of correlations, reliability, and validity of sedentary variables assessed by the smartphone app.

Method

Objectively measured data of SB of eligible 46 Japanese workers obtained from smartphones were used. We assessed the characteristics of current indicators being used with a 10‐minute or 30‐minute thresholds, in addition to the conventional indicators of total sedentary time, mean sedentary bout duration, and total number of sedentary bouts. They were evaluated from three perspectives: (a) association among the indicators, (b) reliability of the indicators, and (c) criterion validity.

Results

Total sedentary time under 10 minutes (U10) and U30 had negative associations with Total sedentary time (r = −.47 and −.21 respectively). The correlation between Mean sedentary bout duration and Total number of sedentary bouts was −.84, whereas between Mean sedentary bout duration 10, 30 and Total number of sedentary bouts were −.54 and −.21, respectively. The intraclass correlation coefficients of almost all indicators were around .80. Mean sedentary bout duration, Mean sedentary bout duration 10, Total number of sedentary bouts, Total sedentary time 30, U30 and U10 have significant differences between three BMI groups.

Conclusion

This study comprehensively revealed the rationale of advantage in the current indicator being used with a 10‐minute or 30‐minute threshold, rather than the conventional total amount of SB.

A Comparison of Physical Activity Mobile Apps With and Without Existing Web-Based Social Networking Platforms: Systematic Review

BACKGROUND

Physical activity mobile apps present a unique medium to disseminate scalable interventions to increase levels of physical activity. However, the effectiveness of mobile apps has previously been limited by low levels of engagement. Existing Web-based social networking platforms (eg, Facebook and Twitter) afford high levels of popularity, reach, and sustain engagement and, thus, may present an innovative strategy to enhance the engagement, and ultimately the effectiveness of mobile apps.

OBJECTIVE

This study aimed to comparatively examine the effectiveness of, and engagement with, interventions that incorporate physical activity mobile apps in conjunction with and without existing Web-based social networking platforms (eg, Facebook and Twitter).

METHODS

A systematic review was conducted by following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Guidelines. A systematic search of the following databases was conducted: Medline, PsycINFO, Web of Science, Scopus, CINAHL, ProQuest, SPORTDiscus, EMBASE, and Cochrane. According to the comparative objective of this review, 2 independent literature searches were conducted. The first incorporated terms related to apps and physical activity; the second also incorporated terms related to Web-based social networking. The results of the two searches were synthesized and compared narratively.

RESULTS

A total of 15 studies were identified, 10 incorporated a physical activity app alone and 5 incorporated an app in conjunction with an existing Web-based social networking platform. Overall, 10 of the 15 interventions were effective in improving one or more physical activity behaviors. Specifically, improvements in physical activity behaviors were reported in 7 of the 10 interventions incorporating physical activity apps alone and in 3 of the 5 interventions incorporating physical activity apps in conjunction with existing Web-based social networking platforms. Interventions incorporating physical activity apps alone demonstrated a decline in app engagement. In contrast, the physical activity apps in conjunction with existing Web-based social networking platforms showed increased and sustained intervention engagement.

CONCLUSIONS

The interventions incorporating physical activity apps in conjunction with and without existing Web-based social networking platforms demonstrated effectiveness in improving physical activity behaviors. Notably, however, the interventions that incorporated existing Web-based social networking platforms achieved higher levels of engagement than those that did not. This review provides preliminary evidence that existing Web-based social networking platforms may be fundamental to increase engagement with physical activity interventions.

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.

Electronic supplementary material

The online version of this article (10.1186/s12966-019-0824-3) contains supplementary material, which is available to authorized users.

Validation of a smart chair and corresponding smartphone app as an objective measure of desk-based sitting

Objectives

This study evaluated the validity of a smart chair and corresponding smartphone app (chair&app) to measure sitting time and sitting interruptions against camera‐derived observation and activPAL.

Methods

Belgian deskbound university employees (n = 28, 17 women, mean age 30 ± 7.5 years, mean BMI 22.1 ± 2.0 kg/m²) were provided with the chair&app in three conditions: a controlled condition (following a prescribed protocol), a free‐living condition (conducting usual office work for 2 hours), and an extended free‐living condition (conducting usual office work for three consecutive days). Total sitting time and the number of sitting interruptions were compared between the chair&app and criterion measures (camera observation and activPAL). Criterion validity was assessed using mean differences (95% CI) and intra‐class correlation coefficients (ICC; 95% CI).

Results

In the controlled condition, mean sitting time and number of sitting interruptions differed between chair&app and camera observation by 2.7 (−2.4, 7.9) minutes and −8.0 (−10.4, −5.6) interruptions, respectively. For the free‐living condition, there was good agreement between chair&app and camera observation for both sitting time (ICC: 0.74; 0.28, 0.93) and sitting interruptions (ICC: 0.68; 0.10, 0.91). For the extended free‐living condition, there was excellent agreement between chair&app and activPAL for sitting time (ICC: 0.89; 0.49, 0.97). Meanwhile, there was poor agreement between chair&app and activPAL for sitting interruptions (ICC: 0.38; −0.04, 0.70).

Conclusions

Chair&app generally provided reliable measures of desk‐based sitting. Consequently, chair&app might be useful as a self‐monitoring tool in the workplace context. Further research is needed to explore its usefulness in reducing adults’ desk‐based sitting.