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Background Sedentary behaviour (SB) is a risk factor for chronic disease and premature mortality. While many individual studies have examined the reliability and validity of various self-report measures for assessing SB, it is not clear, in general, how self-reported SB (e.g., questionnaires, logs, ecological momentary assessments (EMAs)) compares to device measures (e.g., accelerometers, inclinometers). Objective The primary objective of this systematic review was to compare self-report versus device measures of SB in adults. Methods Six bibliographic databases were searched to identify all studies which included a comparable self-report and device measure of SB in adults. Risk of bias within and across studies was assessed. Results were synthesized using meta-analyses. Results The review included 185 unique studies. A total of 123 studies comprising 173 comparisons and data from 55,199 participants were used to examine general criterion validity. The average mean difference was -105.19 minutes/day (95% CI: -127.21, -83.17); self-report underestimated sedentary time by ~1.74 hours/day compared to device measures. Self-reported time spent sedentary at work was ~40 minutes higher than when assessed by devices. Single item measures performed more poorly than multi-item questionnaires, EMAs and logs/diaries. On average, when compared to inclinometers, multi-item questionnaires, EMAs and logs/diaries were not significantly different, but had substantial amount of variability (up to 6 hours/day within individual studies) with approximately half over-reporting and half under-reporting. A total of 54 studies provided an assessment of reliability of a self-report measure, on average the reliability was good (ICC = 0.66). Conclusions Evidence from this review suggests that single-item self-report measures generally underestimate sedentary time when compared to device measures. For accuracy, multi-item questionnaires, EMAs and logs/diaries with a shorter recall period should be encouraged above single item questions and longer recall periods if sedentary time is a primary outcome of study. Users should also be aware of the high degree of variability between and within tools. Studies should exert caution when comparing associations between different self-report and device measures with health outcomes. Systematic review registration PROSPERO CRD42019118755

Background Progress in mobile health (mHealth) technology has enabled the design of just-in-time adaptive interventions (JITAIs). We define JITAIs as having three features: behavioural support that directly corresponds to a need in real-time; content or timing of support is adapted or tailored according to input collected by the system since support was initiated; support is system-triggered. We conducted a systematic review of JITAIs for physical activity to identify their features, feasibility, acceptability and effectiveness. Methods We searched Scopus, Medline, Embase, PsycINFO, Web of Science, DBLP, ACM Digital Library, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov and the ISRCTN register using terms related to physical activity, mHealth interventions and JITAIs. We included primary studies of any design reporting data about JITAIs, irrespective of population, age and setting. Outcomes included physical activity, engagement, uptake, feasibility and acceptability. Paper screening and data extraction were independently validated. Synthesis was narrative. We used the mHealth Evidence Reporting and Assessment checklist to assess quality of intervention descriptions. Results We screened 2200 titles, 840 abstracts, 169 full-text papers, and included 19 papers reporting 14 unique JITAIs, including six randomised studies . Five JITAIs targeted both physical activity and sedentary behaviour, five sedentary behaviour only, and four physical activity only. JITAIs prompted breaks following sedentary periods and/or suggested physical activities during opportunistic moments, typically over three to four weeks. Feasibility challenges related to the technology, sensor reliability and timeliness of just-in-time messages. Overall, participants found JITAIs acceptable. We found mixed evidence for intervention effects on behaviour, but no study was sufficiently powered to detect any effects. Common behaviour change techniques were goal setting (behaviour), prompts/cues, feedback on behaviour and action planning. Five studies reported a theory-base. We found lack of evidence about cost-effectiveness, uptake, reach, impact on health inequalities, and sustained engagement. Conclusions Research into JITAIs to increase physical activity and reduce sedentary behaviour is in its early stages. Consistent use and a shared definition of the term ‘JITAI’ will aid evidence synthesis. We recommend robust evaluation of theory and evidence-based JITAIs in representative populations. Decision makers and health professionals need to be cautious in signposting patients to JITAIs until such evidence is available, although they are unlikely to cause health-related harm. Reference PROSPERO 2017 CRD42017070849.

Sedentary behaviour can be associated with poor mental health, but it remains unclear whether all types of sedentary behaviour have equivalent detrimental effects. To model the potential impact on depression of replacing passive with mentally active sedentary behaviours and with light and moderate-to-vigorous physical activity. An additional aim was to explore these relationships by self-report data and clinician diagnoses of depression. In 1997, 43 863 Swedish adults were initially surveyed and their responses linked to patient registers until 2010. The isotemporal substitution method was used to model the potential impact on depression of replacing 30 min of passive sedentary behaviour with equivalent durations of mentally active sedentary behaviour, light physical activity or moderate-to-vigorous physical activity. Outcomes were self-reported depression symptoms (cross-sectional analyses) and clinician-diagnosed incident major depressive disorder (MDD) (prospective analyses). Of 24 060 participants with complete data (mean age 49.2 years, s.d. 15.8, 66% female), 1526 (6.3%) reported depression symptoms at baseline. There were 416 (1.7%) incident cases of MDD during the 13-year follow-up. Modelled cross-sectionally, replacing 30 min/day of passive sedentary behaviour with 30 min/day of mentally active sedentary behaviour, light physical activity and moderate-to-vigorous activity reduced the odds of depression symptoms by 5% (odds ratio 0.95, 95% CI 0.94-0.97), 13% (odds ratio 0.87, 95% CI 0.76-1.00) and 19% (odds ratio 0.81, 95% CI 0.93-0.90), respectively. Modelled prospectively, substituting 30 min/day of passive with 30 min/day of mentally active sedentary behaviour reduced MDD risk by 5% (hazard ratio 0.95, 95% CI 0.91-0.99); no other prospective associations were statistically significant. Substituting passive with mentally active sedentary behaviours, light activity or moderate-to-vigorous activity may reduce depression risk in adults.

ObjectivesTo understand how device-measured sedentary behaviour and physical activity are related to all-cause mortality in older men, an age group with high levels of inactivity and sedentary behaviour.MethodsProspective population-based cohort study of men recruited from 24 UK General Practices in 1978–1980. In 2010–2012, 3137 surviving men were invited to a follow-up, 1655 (aged 71–92 years) agreed. Nurses measured height and weight, men completed health and demographic questionnaires and wore an ActiGraph GT3x accelerometer. All-cause mortality was collected through National Health Service central registers up to 1 June 2016.ResultsAfter median 5.0 years’ follow-up, 194 deaths occurred in 1181 men without pre-existing cardiovascular disease. For each additional 30 min in sedentary behaviour, or light physical activity (LIPA), or 10 min in moderate to vigorous physical activity (MVPA), HRs for mortality were 1.17 (95% CI 1.10 to 1.25), 0.83 (95% CI 0.77 to 0.90) and 0.90 (95% CI 0.84 to 0.96), respectively. Adjustments for confounders did not meaningfully change estimates. Only LIPA remained significant on mutual adjustment for all intensities. The HR for accumulating 150 min MVPA/week in sporadic minutes (achieved by 66% of men) was 0.59 (95% CI 0.43 to 0.81) and 0.58 (95% CI 0.33 to 1.00) for accumulating 150 min MVPA/week in bouts lasting ≥10 min (achieved by 16% of men). Sedentary breaks were not associated with mortality.ConclusionsIn older men, all activities (of light intensity upwards) were beneficial and accumulation of activity in bouts ≥10 min did not appear important beyond total volume of activity. Findings can inform physical activity guidelines for older adults.

Background There is increasing concern about the time people spend in sedentary behaviour, including screen time, leisure and occupational sitting. The number of both primary research studies (published trials) and reviews has been growing rapidly in this research area. A summary of the highest level of evidence that provides a broader quantitative synthesis of diverse types of interventions is needed. This research is to articulate the evidence of efficacy of sedentary behaviour interventions to inform interventions to reduce sitting time. The umbrella review, therefore, synthesised systematic reviews that conducted meta-analyses of interventions aiming at reducing sedentary behaviour outcomes across all age group and settings. Method A systematic search was conducted on six databases (MEDLINE Complete, PsycINFO, CINAHL, Global Health via EBSCOhost platform, EMBASE, and Cochrane Central Register of Systematic Reviews). Included articles were systematic reviews with meta-analysis of interventions aiming at reducing sedentary behaviour (screen time, sitting time or sedentary time) in the general population across all age group. Results Seventeen reviews met the inclusion criteria (7 in children and adolescent, 10 in adults). All reviews of sedentary behaviour interventions in children and adolescents investigated intervention effectiveness in reducing screen time. Six out of 11 meta-analyses (reported in 7 reviews) showed small but significant changes in viewing time. All reviews of sedentary behaviour interventions in office workplaces indicated substantial reduction in occupational sitting time (range: 39.6 to 100 min per 8-h workday). Sub-group analyses reported a trend favouring environmental change components such as sit-stand desks, active permissive workstations etc. Meta-analyses indicated that sedentary behaviour interventions were superior to physical activity alone interventions or combined physical activity and sedentary behaviour interventions in reducing sitting time. Conclusion The current systematic reviews and meta-analyses supported sedentary behaviour interventions for reducing occupational sitting time in particular, with small changes seen in screen time in children and adolescents. Future research should explore approaches to maintaining behaviour change beyond the intervention period and investigate the potential of sedentary behaviour reduction interventions in older age groups in non-occupational settings.

Background Globally, many children fail to meet the World Health Organization’s physical activity and sedentary behaviour guidelines. Schools are an ideal setting to intervene, yet despite many interventions in this setting, success when delivered under real-world conditions or at scale is limited. This systematic review aims to i) identify which implementation models are used in school-based physical activity effectiveness, dissemination, and/or implementation trials, and ii) identify factors associated with the adoption, implementation and sustainability of school-based physical activity interventions in real-world settings. Methods The review followed PRISMA guidelines and included a systematic search of seven databases from January 1st, 2000 to July 31st, 2018: MEDLINE, EMBASE, CINAHL, SPORTDiscus, PsycINFO, CENTRAL, and ERIC. A forward citation search of included studies using Google Scholar was performed on the 21st of January 2019 including articles published until the end of 2018. Study inclusion criteria: (i) a primary outcome to increase physical activity and/or decrease sedentary behaviour among school-aged children and/or adolescents; (ii) intervention delivery within school settings, (iii) use of implementation models to plan or interpret study results; and (iv) interventions delivered under real-world conditions. Exclusion criteria: (i) efficacy trials; (ii) studies applying or testing school-based physical activity policies, and; (iii) studies targeting special schools or pre-school and/or kindergarten aged children. Results 27 papers comprising 17 unique interventions were included. Fourteen implementation models (e.g., RE-AIM, Rogers’ Diffusion of Innovations, Precede Proceed model), were applied across 27 papers. Implementation models were mostly used to interpret results ( n  = 9), for planning evaluation and interpreting results ( n  = 8), for planning evaluation ( n  = 6), for intervention design ( n  = 4), or for a combination of designing the intervention and interpreting results ( n  = 3). We identified 269 factors related to barriers ( n  = 93) and facilitators ( n  = 176) for the adoption ( n  = 7 studies), implementation ( n  = 14 studies) and sustainability ( n  = 7 studies) of interventions. Conclusions Implementation model use was predominately centered on the interpretation of results and analyses, with few examples of use across all study phases as a planning tool and to understand results. This lack of implementation models applied may explain the limited success of interventions when delivered under real-world conditions or at scale. Trial registration PROSPERO ( CRD42018099836 ).

Regular physical activity is related to many factors in a university student’s environment. The coronavirus pandemic and the resulting lockdown have restricted many elements of our environment. The aim of this study was to evaluate students’ physical activity and sedentary behaviour at two points in time: before and during the coronavirus lockdown. As a secondary aim, we also wanted to look at changes resulting from other factors (alcohol, tobacco, diet, stages of change, symptoms of anxiety/depression and sociodemographic characteristics). We conducted an observational, cross-sectional, pre-post study with two cut-off points. Two hundred and thirteen students took part in the study. The main dependent variables were physical activity and sitting time, measured using the International Physical Activity Questionnaire—Short Form (IPAQ-SF). Parametric and non-parametric tests were used for paired and unpaired data, as well as group-stratified analysis. During lockdown, both weekly physical activity (MD: −159.87; CI: −100.44, −219.31) and weekly sitting time increased (MD: −106.76; CI: −71.85, −141.67). In the group analysis, differences were observed in relation to gender, year of study, BMI, alcohol consumption, tobacco use, symptoms of anxiety/depression, Mediterranean diet, living situation and stage of change. The results showed an increase in both physical activity and sitting time globally and by group.

Background Sedentary behaviour (SB; time spent sitting) is associated with musculoskeletal pain (MSP) conditions; however, no prior systematic review has examined these associations according to SB domains. We synthesised evidence on occupational and non-occupational SB and MSP conditions. Methods Guided by a PRISMA protocol, eight databases (MEDLINE, CINAHL, PsycINFO, Web of Science, Scopus, Cochrane Library, SPORTDiscus, and AMED) and three grey literature sources (Google Scholar, WorldChat, and Trove) were searched (January 1, 2000, to March 17, 2021) for original quantitative studies of adults ≥ 18 years. Clinical-condition studies were excluded. Studies’ risk of bias was assessed using the QualSyst checklist. For meta-analyses, random effect inverse-variance pooled effect size was estimated; otherwise, best-evidence synthesis was used for narrative review. Results Of 178 potentially-eligible studies, 79 were included [24 general population; 55 occupational (incuding15 experimental/intervention)]; 56 studies were of high quality, with scores > 0.75. Data for 26 were meta-synthesised. For cross-sectional studies of non-occupational SB, meta-analysis showed full-day SB to be associated with low back pain [LBP – OR = 1.19(1.03 – 1.38)]. Narrative synthesis found full-day SB associations with knee pain, arthritis, and general MSP, but the evidence was insufficient on associations with neck/shoulder pain, hip pain, and upper extremities pain. Evidence of prospective associations of full-day SB with MSP conditions was insufficient. Also, there was insufficient evidence on both cross-sectional and prospective associations between leisure-time SB and MSP conditions. For occupational SB, cross-sectional studies meta-analysed indicated associations of self-reported workplace sitting with LBP [OR = 1.47(1.12 – 1.92)] and neck/shoulder pain [OR = 1.73(1.46 – 2.03)], but not with extremities pain [OR = 1.17(0.65 – 2.11)]. Best-evidence synthesis identified inconsistent findings on cross-sectional association and a probable negative prospective association of device-measured workplace sitting with LBP-intensity in tradespeople. There was cross-sectional evidence on the association of computer time with neck/shoulder pain, but insufficient evidence for LBP and general MSP. Experimental/intervention evidence indicated reduced LBP, neck/shoulder pain, and general MSP with reducing workplace sitting. Conclusions We found cross-sectional associations of occupational and non-occupational SB with MSP conditions, with occupational SB associations being occupation dependent, however, reverse causality bias cannot be ruled out. While prospective evidence was inconclusive, reducing workplace sitting was associated with reduced MSP conditions. Future studies should emphasise prospective analyses and examining potential interactions with chronic diseases. Protocol registration PROSPERO ID # CRD42020166412 (Amended to limit the scope)

Physical activity (PA) and sedentary behaviour (SB) of pre-school aged children are associated with important health and developmental outcomes. Accurate measurement of these behaviours in young children is critical for research and practice in this area. The aim of this review was to examine the validity, reliability, and feasibility of measurement tools used to assess PA and SB of pre-school aged children. Searches of electronic databases, and manual searching, were conducted to identify articles that examined the measurement properties (validity, reliability or feasibility) of measurement tools used to examine PA and/or SB of pre-school aged children (3–7 years old). Following screening, data were extracted and risk of bias assessment completed on all included articles. A total of 69 articles, describing 75 individual studies were included. Studies assessed measurement tools for PA ( n  = 27), SB ( n  = 5), and both PA and SB ( n  = 43). Outcome measures of PA and SB differed between studies (e.g. moderate to vigorous activity, step count, posture allocation). Most studies examined the measurement properties of one measurement tool only ( n  = 65). Measurement tools examined included: calorimetry, direct observation, combined heart rate and accelerometry, heart rate monitors, accelerometers, pedometers, and proxy report (parent, carer or teacher reported) measures (questionnaires or diaries). Studies most frequently assessed the validity (criterion and convergent) ( n  = 65), face and content validity ( n  = 2), test-retest reliability ( n  = 10) and intra-instrument reliability ( n  = 1) of the measurement tools. Feasibility data was abstracted from 41 studies. Multiple measurement tools used to measure PA and SB in pre-school aged children showed some degree of validity, reliability and feasibility, but often for different purposes. Accelerometers, including the Actigraph (in particular GT3X versions), Actical, ActivPAL and Fitbit (Flex and Zip), and proxy reported measurement tools used in combination may be useful for a range of outcome measures, to measure intensity alongside contextual information.

Background E- and m-health interventions are promising to change health behaviour. Many of these interventions use a large variety of behaviour change techniques (BCTs), but it’s not known which BCTs or which combination of BCTs contribute to their efficacy. Therefore, this experimental study investigated the efficacy of three BCTs (i.e. action planning, coping planning and self-monitoring) and their combinations on physical activity (PA) and sedentary behaviour (SB) against a background set of other BCTs. Methods In a 2 (action planning: present vs absent) × 2 (coping planning: present vs absent) × 2 (self-monitoring: present vs absent) factorial trial, 473 adults from the general population used the self-regulation based e- and m-health intervention ‘MyPlan2.0’ for five weeks. All combinations of BCTs were considered, resulting in eight groups. Participants selected their preferred target behaviour, either PA ( n  = 335, age = 35.8, 28.1% men) or SB ( n  = 138, age = 37.8, 37.7% men), and were then randomly allocated to the experimental groups. Levels of PA (MVPA in minutes/week) or SB (total sedentary time in hours/day) were assessed at baseline and post-intervention using self-reported questionnaires. Linear mixed-effect models were fitted to assess the impact of the different combinations of the BCTs on PA and SB. Results First, overall efficacy of each BCT was examined. The delivery of self-monitoring increased PA (t = 2.735,  p  = 0.007) and reduced SB (t = − 2.573,  p  = 0.012) compared with no delivery of self-monitoring. Also, the delivery of coping planning increased PA (t = 2.302,  p  = 0.022) compared with no delivery of coping planning. Second, we investigated to what extent adding BCTs increased efficacy . Using the combination of the three BCTs was most effective to increase PA (x 2  = 8849,  p  = 0.003) whereas the combination of action planning and self-monitoring was most effective to decrease SB (x 2  = 3.918,  p  = 0.048). To increase PA, action planning was always more effective in combination with coping planning (x 2  = 5.590,  p  = 0.014; x 2  = 17.722,  p  < 0.001; x 2  = 4.552,  p  = 0.033) compared with using action planning without coping planning. Of note, the use of action planning alone reduced PA compared with using coping planning alone (x 2  = 4.389,  p  = 0.031) and self-monitoring alone (x 2  = 8.858,  p  = 003), respectively. Conclusions This study provides indications that different (combinations of) BCTs may be effective to promote PA and reduce SB. More experimental research to investigate the effectiveness of BCTs is needed, which can contribute to improved design and more effective e- and m-health interventions in the future. Trial registration This study was preregistered as a clinical trial (ID number: NCT03274271 ). Release date: 20 October 2017.