Citation: Liang Liu, Wen Chen, Lei Zhang, JiaYong Liu, Jian Qin. A type of block withholding delay attack and the countermeasure based on type-2 fuzzy inference[J]. Mathematical Biosciences and Engineering, 2020, 17(1): 309-327. doi: 10.3934/mbe.2020017
[1] | Adrienne R Hughes, David J Muggeridge, Ann-Marie Gibson, Avril Johnstone, Alison Kirk . Objectively Measured Sedentary Time in Children and Their Parents. AIMS Public Health, 2016, 3(4): 823-836. doi: 10.3934/publichealth.2016.4.823 |
[2] | Bronwyn Sudholz, Anna Timperio, Nicola D. Ridgers, David W. Dunstan, Rick Baldock, Bernie Holland, Jo Salmon . The Impact and Feasibility of Introducing Height-Adjustable Desks on Adolescents’ Sitting in a Secondary School Classroom. AIMS Public Health, 2016, 3(2): 274-287. doi: 10.3934/publichealth.2016.2.274 |
[3] | Naime Altay, Ebru Kılıcarslan Toruner, Ebru Akgun-CITAK . Determine the BMI levels, self-concept and healthy life behaviours of children during a school based obesity training programme. AIMS Public Health, 2020, 7(3): 535-547. doi: 10.3934/publichealth.2020043 |
[4] | P. Dean Cooley, Casey P. Mainsbridge, Vaughan Cruickshank, Hongwei Guan, Anjia Ye, Scott J. Pedersen . Peer champions responses to nudge-based strategies designed to reduce prolonged sitting behaviour: Lessons learnt and implications from lived experiences of non-compliant participants. AIMS Public Health, 2022, 9(3): 574-588. doi: 10.3934/publichealth.2022040 |
[5] | Le Thi Thanh Huong, Tran Khanh Long, Le Vu Anh, Margaret Cook, Mike Capra . Decreasing In-home Smoking of Adults—Results from a School-based Intervention Program in Viet Nam. AIMS Public Health, 2016, 3(4): 863-879. doi: 10.3934/publichealth.2016.4.863 |
[6] | Michael O Ogundele, Hani F Ayyash . ADHD in children and adolescents: Review of current practice of non-pharmacological and behavioural management. AIMS Public Health, 2023, 10(1): 35-51. doi: 10.3934/publichealth.2023004 |
[7] | Alison Kirk, Ann-Marie Gibson, Katie Laverty, David Muggeridge, Louise Kelly, Adrienne Hughes . Patterns of Sedentary Behaviour in Female Office Workers. AIMS Public Health, 2016, 3(3): 423-431. doi: 10.3934/publichealth.2016.3.423 |
[8] | Calum F Leask, Marlene Sandlund, Dawn A Skelton, Emmanuelle Tulle, Sebastien FM Chastin . Modifying Older Adults’ Daily Sedentary Behaviour Using an Asset-based Solution: Views from Older Adults. AIMS Public Health, 2016, 3(3): 542-554. doi: 10.3934/publichealth.2016.3.542 |
[9] | Linna Tam-Seto, Patricia Weir, Shilpa Dogra . Factors Influencing Sedentary Behaviour in Older Adults: An Ecological Approach. AIMS Public Health, 2016, 3(3): 555-572. doi: 10.3934/publichealth.2016.3.555 |
[10] |
Dorota Zarnowiecki, Meaghan S Christian, James Dollman, Natalie Parletta, Charlotte E.L Evans, Janet E Cade .
Comparison of school day eating behaviours of 8–11 year old children from Adelaide, South Australia, and London, England . AIMS Public Health, 2018, 5(4): 394-410. doi: 10.3934/publichealth.2018.4.394 |
“Sedentary behaviour refers to any waking activity characterised by an energy expenditure < 1.5 metabolic equivalents and a sitting or reclining posture” [1]. In recent decades, advances in modern technology, increases in passive transportation and shifts in leisure time activities have all contributed to the increasing amount of time both adults and children spend engaged in sedentary behaviours [2,3].
Uninterrupted sedentary time is increasingly recognised as a distinct health risk behaviour [4]. Spending much of the day sedentary may carry an increased risk to cardiometabolic health even if the minimum recommended levels of physical activity are achieved [5]. In children, sedentary time is positively associated with weight status [6] and obesity [7]. Specific sedentary behaviours such as TV viewing are associated with lower fitness, lower scores of self-esteem and pro-social behaviour, and decreased academic achievement [8].
In the UK children spend approximately 80% of their day sedentary [9] and this behaviour appears to be more prevalent in girls compared with boys [10]. Sedentary time is thought to track from childhood through to adulthood [11,12] suggesting that sedentary behaviour habits are established at a young age [11]. Colley et al [13] reported that children under the age of 11 years engaged in 1.3 hours less sedentary behaviour than those aged 11-14 years and approximately two hours less than those aged 15-19 years. A systematic review by Jones et al [12] reported moderate-to-large tracking of sedentary behaviour from early childhood up to middle childhood, with a minimum of one-year follow-up from baseline as the inclusion criteria. The tracking coefficients in these studies ranged from 0.35 to 0.60, with a mean of 0.49 and a median of 0.52 [12]. In contrast, Biddle et al [11] reported tracking coefficients ranging from -0.15 (boys over 2 years) to 0.48 (over 1 year) for total sedentary time. In general, children become more sedentary with increasing age [14]. These general increases in sedentary behaviour may be due in part to increased use of computers, smart phones and engagement in social media [15]. In particular, middle childhood and adolescence (9-15 years) has been identified as a life transition or key stage in maturation when parental influence begins to wane and the influence of peers becomes stronger [16]. Interventions aimed at children prior to this milestone, may help prevent further increases in sedentary time.
In addition to sedentary leisure pursuits, school is a key setting for sedentary behaviour [17]. Children spend 57% of their waking time at school [18]. Most primary school children spend approximately 6 hours per day at school [19] with most of this time (65%) being sedentary [20]. School-based interventions have been shown to be effective in reducing health inequalities [21,22], promoting healthy behaviours generally [23], increasing physical activity [12] and may also be helpful in preventing excessive sedentary behaviour in children [24]. However, there appears to be variability in how each of these studies measured sedentary time as an outcome, therefore leading to uncertainties in objective reliability in intervention efficacy. Nevertheless, the increased availability of portable electronic devices such as accelerometers and inclinometers has enabled the objective measurement of sedentary time [25,26]. These devices are easy to wear [27] and are more affordable than other objective methods of measurement; for example, direct observation [28] making them more feasible for the evaluation of interventions to reduce sedentary time.
The purpose of this study was to conduct a systematic review of classroom-based interventions designed to reduce objectively measured sedentary time in children.
Studies were assessed for eligibility for inclusion according to the following criteria: (1) reported an intervention aimed at reducing sedentary behaviour which involved the children’s classroom; (2) included participants attending primary education; (3) included an objective measure of sedentary time; (4) published in English up to and including August 2015. Interventions which solely or partly aimed to reduce sedentary time were included. Studies which defined sedentary behaviour as “failure to meet physical activity guidelines” were excluded. Studies were assessed by one author (LH) with uncertainties referred to a second author.
Five electronic databases were searched in August 2015 for full-text articles published in peer reviewed journals using a combination of keywords including sedentar*, sitting*, child, child*, teacher, teachers, school and schools. The databases included Medline (OvidSP), PsycINFO, Scopus, CINAHL and Cochrane Libraries. The key search terms included were (1) sedentary behaviour; (2) child; and (3) teacher or school. Table 1 provides the full search strategy which was used in Ovid® Medline which was modified for the remaining databases. The search was also repeated independently by a subject librarian. The reference lists of articles were also searched for suitable articles meeting the criteria.
Searches |
1. Sedentary Lifestyle/ |
2. sedentary.tw. |
3. sitting.tw. |
4. 1 or 2 or 3 |
5. "teacher*".tw. |
6. Schools/ |
7. (school or schools).mp. (mp = title, abstract, original title, name of substance word, subject heading word, keyword heading word, protocol supplementary concept word, rare disease supplementary concept word, unique identifier) |
8. 5 or 6 or 7 |
9. exp Child/ |
10. (child* or preschool* or pre school*).tw. |
11. 9 or 10 |
12. 4 and 8 and 11 |
Studies were selected by (1) screening the titles; (2) screening the abstracts; and (3) examining the entire paper if the title and abstract did not provide sufficient information to determine whether it met the inclusion criteria. Studies which did not meet all of the inclusion criteria were discarded.
For inclusion in this review, studies were required, at a minimum, to report a baseline and follow-up objective measurement of sedentary time. These data were required to analyse the effectiveness of the intervention for each study.
Data were extracted in accordance with PRISMA guidelines [29] onto an Excel sheet which was developed for the purposes of this review. This included information on the studies in relation to study characteristics, participant characteristics, intervention characteristics, outcome measurement and data analyses. The Cochrane Collaboration Risk of Bias Tool [30] was used to assess the risk of bias in the studies included in this review across six domains for sequence generation, allocation concealment, blinding, incomplete outcome data and selective reporting. Two authors (LH and EM) independently reviewed the studies and agreed on the risk of bias as low risk of bias, unclear risk of bias or high risk of bias [30]. Discrepancies between the two assessments were resolved by a third author (MM).
The study was registered with PROSPERO, an international database of prospectively registered systematic reviews [31].
The literature search yielded 1, 376 studies. Initially, studies were excluded based on title only, then title and abstract and then full-text using inclusion and exclusion criteria. Articles relating to the same study were grouped together. Eleven papers, reporting eight studies, met inclusion criteria (see Figure 1). The studies included controlled and non-controlled trials.
A summary of the included studies are shown in Table 2. Studies originated in the UK (n = 3) [32,33,34], Australia (n = 1) [35,36], New Zealand (n = 2) [37,38] and Belgium (n = 1) [39,40,41], whilst one study was based in both the UK and Australia (n = 1) [42]. In seven of the studies, reducing sitting/sedentary time was a main aim [32,34,35,36,37,38,39,40,41,42], whilst, in another study, reducing sedentary time formed part of an overall school-based intervention to promote health [33].
Studies | Participants | Details of Intervention | |||||||
Authors & Year | n | Location | Age (yrs) | Gender | Name of Intervention | Duration | Duration per Session | Frequency (days/week) | Accelerometer Used |
Aminian et al., (2015) [37] | 26 | New Zealand | 9-11 | m f | N/A | 9 weeks | Full school day | 5 | activPAL |
Breslin et al. (2012) [32] | 416 | UK | 8-9 | m f | Sport for LIFE | 12 weeks | 1 hour | 1 | Actigraph |
Carson et al. (2013) [35]; Yildirim (2014)[36] | 268 | Australia | 7-9 | m f | Transform Us! | 18 months | 30 mins | 5 | Actigraph |
Clemes et al. (2015) [42] | 74 | UK and Australia | 9-12 | m f | N/A | 9-10 weeks | UK group: minimum of 1 hour per day. Australian group: full school day | 5 | activPAL |
Fairclough et al. (2013) [33] | 318 | UK | 10-11 | m f | CHANGE! Project | 20 weeks | 60 mins | 1 | Actigraph |
Hinckson et al. (2013) [38] | 30 | New Zealand | 9-11 | m f | N/A | 4 weeks | Full school day | 5 | activPAL |
Kipping et al. (2014) [34] | 2221 | UK | 8-10 | m f | Active for Life Year 5 (AFLY5) | 1 school year | Varied | Varied | Actigraph |
Verloigne et al. (2012) [39]; Verloigne et al. (2015) [40]; Vik et al. (2015) [41] | 372 | Belgium1 | 9-11 | m f | UP4FUN | 6 weeks | Not specified | 1-2 | Actigraph |
1 Intervention implemented in Belgium, Germany, Greece, Hungary and Norway but activPAL data related to Belgian sample only. |
All schools in the studies were state-funded. The socioeconomic status (SES) of the participating schools varied: low SES [32,37,38]; a combination of low-, mid- and high SES [34,35,36]; and low and high [33]. One study did not provide the SES of the participating schools [39,40,41]. The study by Clemes et al [42] used a low SES school for the UK group but a mid-high SES school for the Australian group.
Participants in the eight studies ranged in age from 7-12 years. All studies involved both male and female participants. The number of participants in each study varied. Three studies had less than 100 participants [37,38,42]; four studies had 101-500 participants [32,33,35,36,39,40,41]; and one study had more than 2, 000 participants [34]. The samples comprised of multiple ethnicities including white, South Asian, Australian, and Maori.
A convenience sample was used by two studies [37,38]. One study discussed how sample size was calculated based on a previously published simulation study [35,36] and a sample size based on intra-cluster correlation coefficients for different outcomes and other information collected during the pilot study [34]. Four studies did not describe how sample size was calculated [32,33,39,40,41,42].
The majority of studies used random allocation to intervention or control groups [32,33,34,35,36,39,40,41,42]. Two studies did not describe how participants were allocated [37,38]. None of the studies were judged to have a low-risk of bias (Table 3).
Authors & Year | Adequate sequence generation? | Allocation concealment? | Blinding of participants and personnel? | Blinding of outcome assessors? | Incomplete outcome data addressed? | Free of selective reporting? | Free of other bias? | |
1 | Aminian et al. (2015) [37] | Unclear | Unclear | Unclear | Unclear | Low | Low | High |
2 | Breslin et al. (2012) [32] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | High |
3 | Clemes et al. (2015) [42] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear |
4 | Carson et al. (2013) [35] | Low | Unclear | High | Unclear | High | High | Low |
5 | Fairclough et al. (2013) [33] | Unclear | Unclear | Unclear | High | High | Unclear | Low |
6 | Hinckson et al. (2015) [38] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | High |
7 | Kipping et al. (2014) [22] | Unclear | Low | Low | Low | Low | Low | Low |
8 | Verloigne et al. (2012) [39] | Unclear | Unclear | Unclear | Unclear | High | Unclear | High |
9 | Verloigne et al. (2015) [40] | Unclear | Unclear | Unclear | Unclear | High | Unclear | High |
10 | Vik et al. (2015) [41] | Unclear | Unclear | Unclear | Unclear | Low | Unclear | High |
11 | Yildirim et al. (2014) [42] | Low | Unclear | Unclear | Unclear | High | Unclear | Low |
Five of the eight studies based the intervention on psychological theory. Social cognitive theory [43] was used by three studies [32,33,34]. One study was developed from the five steps of the Model of Planned Promotion for Population Health, which was based on a socioecological framework [39,40,41]. Another study [35,36] used a combination of elements of social cognitive theory, behaviour choice theory and the ecological systems theory. Three studies did not describe an underpinning psychological theory in relation to planning the intervention [37,38,42].
The studies included in this review varied in their duration from 4 weeks [38] to 18 months [35,36]. In one study, it was unclear exactly how many weeks the intervention took place for [34]; however, the corresponding author confirmed that the intervention was spread over a school year [44]. The time of year varied for interventions depending primarily on curriculum demands.
Four of the eight included studies consisted of single-component interventions whilst the remainder were multi-component. The multi-component interventions involved parents assisting their children with intervention activities at home [33,34,35,36,39,40,41].
Two studies replaced standardised desks and chairs within the classroom with adjustable sit-to-stand desks to reduce sedentary time [37,38]. Aminian et al [37] also incorporated exercise balls, beanbags and mat space into the classroom. Clemes et al [42] reported two different interventions. In the first study, based in the UK, the teacher rotated the children between standing desks and standard desks whilst, in the Australian-based intervention, all standard desks were replaced with sit-to-stand desks. The remaining five studies involved a combination of specific lessons and activities which focused on reducing sitting time. Sport for LIFE was a healthy lifestyle intervention intended to increase physical activity, decrease sedentary behaviour, reduce screen time behaviours, encourage healthy attitudes and behaviours to nutrition, and reduce body mass index [32]. This intervention involved weekly sessions which consisted of 5-10 minutes of education theory followed by 1 hour of physical activity [32]. The Transform-Us! Intervention aimed to increase physical activity, reduce sedentary behaviour and optimise healthy outcomes [35,36]. It involved the teacher delivering class lessons which had key learning messages and also included standing lessons, light intensity activity breaks and newsletters. Participants were allocated to one of three intervention groups which focused on (1) reducing sedentary behaviour; (2) increasing physical activity; or (3) reducing sedentary behaviour and increasing physical activity. The CHANGE! Project aimed to assess the effectiveness of the intervention on measures of body size, increasing physical activity, reducing sedentary time and food intake [33]. It consisted of a teacher-led curriculum, learning tasks and homework tasks [33]. The AFLY5 (Active for Life) intervention [34] aimed to increase time spent in moderate or vigorous physical activity, reduce sedentary behaviour, and increase fruit and vegetable consumption. It consisted of weekly lessons and child-parent interactive homework plans. The ENERGY Project aimed to assess the effectiveness of the intervention in reducing children’s total sedentary time [39,40,41]. It consisted of 1-2 lessons per week which focused on educating the participants on changing their behaviour in relation to total sitting time [39,40,41]. All studies included a control group that continued with current practice. The interventions were delivered in rural and urban areas.
Of the five studies which involved the delivery of specific lessons, four were teacher-delivered lessons and had a specific theme; for example, reducing sedentary time, breaking up sitting time and active transportation [33,34,35,36,39,40,41]. One study used specially trained undergraduate and graduate students in partnership with the teachers to deliver the lessons in school [32].
Intervention effects are shown in Table 4. The Actigraph accelerometer was the most commonly used device to measure sedentary time in five of the eight studies [32,33,34,35,36,39,40,41]. The remaining studies used the thigh-worn activPAL device, which quantifies sedentary, upright and ambulatory activities [37,38,42].
Authors & Year | Nature of Intervention | Intervention Effects |
Aminian et al. (2015) [37] | Standing workstations replaced traditional desks. Exercise balls, beanbags and mat space. | Overall mean sitting time (hours; mean ± SD): Intervention: pre, 9.56 ± 1.27; post, 7.64 ± 2.06. Control: pre, 9.34 ± 1.32; post, 8.08 ± 3.10. Mean sitting time during school (hours; mean ± SD): Intervention: pre, 3.88 ±0.36; post, 2.81 ± 0.36. Control: pre, 3.59 ± 0.45; post, 3.24 ± 0.81. Decrease in weekday sitting time: 45 minutes |
(CL ± 122). Moderate reduction by possibly 36 minutes in sitting time during school but results unclear. | ||
Breslin et al. (2012) [32] | Education theory and activities led by teacher. | Intervention group: lower levels of sedentary behaviour at follow-up compared to baseline. Significant main effects: F(1, 49) = 5.585; p < 0.022; ηp2 = 0.102. Increase in sedentary behaviour 15:00-18:00. Decrease in sedentary behaviour 18:00-bedtime. Significant multivariate effects: Intervention group, sedentary behaviour: F(4, 56) = 14.416; p < 0.001; ηp2 =0.507. Time period: 15:00-18:00, F(1, 59) = 4.906; p < 0.031, ηp2 = 0.077 and 18:00-bedtime, F(1, 59) = 38.821; p < 0.001; ηp2 = 0.397). |
Carson et al. (2013)[35]; Yildirim (2014)[36] | Combination of strategies using the curriculum, in-house activities, physical environment < home setting | 13.3 minute decrease in weekday sitting time in arm of intervention that aimed to increase PA and reduce SB (significant). Total effect on total weekday sedentary time was -13.28 (-24.37, 2.20) (95% CI). |
Clemes et al. (2015) [42] | UK study: participants were rotated around 6 sit-to-stand desks so that they stood for at least one hour per day. Australian study: sit-to-stand desks replaced all traditional desks and participants stood for a minimum of 30 mins per day. In both studies, teachers provided information on benefits of reducing sedentary behaviour and classroom sitting time. | Sitting during class (% of wear time): UK sample: Intervention: pre, 71.8 ± 10.6; post, 62 ± 15.8 (p = 0.03). Control: pre, 68.6 ± 20; post, 65.4 ± 20.1 (not significant). Australian sample: Intervention: pre, 67.9 ± 8.4; post, 58.5 ± 8.4 (p < 0.001). Control: pre, 70.8 ± 5.8; post, 64.8 ± 10.8 (p = 0.04). |
Weekday sitting time (minutes): UK sample (mean ±SD): Intervention: pre, 606.5 ± 66.4; post, 525.7 ± 103.7. Control: pre, 566.1 ± 92.6; post, 574 ± 180.6. Australian sample (mean ±SD): Intervention: pre, 498.2 ± 80.2; post, 429.8 ± 60.4. Control: pre, 489.7 ± 84.6; post, 435.5 ± 81.2. | ||
Fairclough et al. (2013) [33] | Teacher-led curriculum, learning resources, homework tasks, CD-ROM. Teacher received 4 hours of training in the delivery of the curriculum resource. | Compared with baseline data, 28 minutes more sedentary time in intervention group post-intervention but 8.5 minutes less at follow-up. Effect for sedentary time: β = -8.44 (95% CI = -53.23, 36.35) minutes (non-significant). |
Hinckson et al. (2015) [38] | Standing workstations replaced traditional desks. | Sitting Time (hours; mean ± SD): Intervention: pre, 9.26 ± 1.15; post, 8.27 ± 1.45. Control: pre, 9.30 ± 1.46; post, 9.00 ± 0.80. Effect size (90% CL): 0.49 (0.64). |
Kipping et al. (2014) [34] | Teachers trained to deliver 16 sessions — 10 of which had associated homework. Child-parent interactive homework tasks also. | Difference in means between intervention and control group of -0.11 (-9.71 to 9.49) minutes per day less sitting (non-significant). |
Verloigne et al. (2012) [39]; Verloigne et al. (2015) [40]; Vik et al. (2015) [41] | Teacher delivered 1-2 intervention lessons per week. Manual given to teachers who were trained by researcher. Each week had a specific theme. | Effects: Sedentary time (β = 2.18, SE = 0.59, d = 0.20); weekday sedentary time (β = 1.07, SE = 0.47, d = 0.12) (significant); weekend day sedentary time (β = 4.17, SE = 0.88, d = 0.25) (significant); school hours (β = 0.22, SE = 0.46) (non-significant); after school sedentary time (β = 3.32, SE = 0.67, d = 0.26) (significant). |
The majority of the included studies asked the participants to wear the accelerometer for seven consecutive days [32,33,37,38,42]. Eight consecutive days of wear was required by Carson et al [35,36] and Verloigne et al [39,40,41]. The shortest wear time was five days by Kipping et al [34]. With the exception of three studies [34,37,38], the majority of studies reported compliance issues in relation to adhering to the accelerometer wear time. Consequently, these studies reported valid data for approximately half or less than the number of participants who wore the accelerometer. For data to be deemed valid for statistical analyses, the number of days and the number of hours per day that the accelerometer had to be worn varied between the studies. These included three weekdays and one weekend day [32,37]; three days [33,34]; three weekdays [35,36]; two weekdays and one weekend day [39,40,41]; one weekday [42]; and no minimum wear time described [38]. The minimum number of hours per day included 8 hours [34,35,36,37,42]; 9 hours on weekdays and 8 hours on weekend days [33]; 9 hours on weekdays and 11 hours on weekend days [32]; 10 hours on weekdays and 8 hours on weekend days [39,40,41]; and no minimum wear time described [38]. All studies reported time spent sitting in minutes as means and standard deviations.
All of the studies included in this review evaluated outcomes pre- and immediately post-intervention but none adopted longitudinal follow-up designs. However, only two studies then collected follow-up data in the months following completion of the intervention. These included 10-weeks post-intervention [33] and 12-months [34]. One other study included a 12-month post-intervention booster [36].
The studies included in this review either did not offer, or did not disclose the use of incentives to reward the participants for taking part. However, as part of the methodologies, participants in some studies did receive resources. For example, to compensate for the standing desks having no drawers, the participants were provided with shoulder bags [37]. One study suggested that incentives should be used in future studies especially to increase adherence to the wearing of accelerometers [32].
Five of the eight studies reported decreases in sedentary time between baseline and post-intervention measurements [32,35,37,38,42]. Aminian et al [37] reported that, on weekdays, during waking hours, there was an overall decrease in sitting time by 45 minutes from baseline (9.56 ± 1.27 hours) to post-intervention (7.64 ± 2.06 hours) and an increase in standing time by 55 minutes in the experimental group from baseline (3.71 ± 0.92 hours) to post-intervention (3.71 ± 0.92 hours). During school hours, sitting time reduced by 36 minutes in the experimental group (3.88 ± 0.36 hours at baseline compared to 2.81 ± 0.36 hours post-intervention) [37]. However, the authors noted wide confidence limits and that the results were unclear. Further decreases in sitting time were observed during other segments of the day between pre- and post-intervention in the experimental group including before school (0.86 ± 0.42 v. 0.59 ± 0.37 hours per day) and after school (4.82±1.15 v. 4.15 ± 1.67 hours per day).
Breslin et al [32] reported an overall decrease in sedentary time for the intervention group of approximately 25.5 minutes per day (709.28 ± 41.32 minutes per day at baseline and 684.30 ± 72.17 minutes per day post-intervention). However, further analyses of sedentary time in the intervention group at specific intervals showed varying results. Sedentary time increased before school (+0.71 minutes per day), during school (+9.59 minutes per day) and after school whilst a decrease was observed in the time period between 6pm and bedtime (-40.24 minutes per day) [32]. Further analysis by Breslin et al [42] showed a significant multivariate effect for sedentary behaviour for the intervention group (F(4, 56) = 14.416; p < 0.001; ηp2 = 0.507). During particular segments of the day, the participants showed statistically significant differences for average time in sedentary behaviour at follow-up compared with baseline. Specifically, between 15:00 and 18:00 (F(1, 59) = 4.906; p < 0.031; ηp2 = 0.077) which represented an increase in sedentary behaviour and between 18:00 and bedtime (F(1, 59)=38.821; p < 0.001; ηp2 = 0.397) which represented a decrease in sedentary behaviour.
The mid-intervention results by Carson et al [35] at 5-9 months reported a statistically significant decrease of 13.3 minutes per day in weekday sedentary time in the arm of the intervention group which focused on reducing sedentary time and increasing physical activity in comparison to the control group. However, there were no statistically significant decreases observed during class time. The total effect on total weekday sedentary time was -13.28 (-24.37, 2.20) (95% CI) [35].
The results for the intervention by Clemes et al [42] reported that the proportion of time spent sitting in class decreased significantly at follow-up in both intervention groups. In the UK study which had some standing desks, classroom sitting time decreased by -52.4 ± 66.6 minutes per day in the intervention group and -6.9 ± 91 minutes per day in the control group [42]. The Australian study with all standing desks showed a decrease of -43.7 ± 29.9 minutes per day in the intervention group and -28.2 ± 28.3 in the control group [42]. Sitting time as a percentage of wear time decreased in both intervention groups by -9.8 ± 16.5% (UK sample) and -9.4 ± 10% (Australian sample). The results for both intervention groups showed statistical significance. Overall decreases in sitting time were also reported for both intervention groups (UK: -80.8 ± 103.4 minutes per day; Australia: -68.3 ± 97.2 minutes per day); however, these results were not statistically significant.
Fairclough et al [33] reported that participants recorded less sedentary time at follow-up; however, post-intervention, they did over 28 minutes more per day but these results were not statistically significant. Baseline sedentary time was also reported for the comparison and intervention groups but not post-intervention. Instead, multi-level analyses of the effectiveness of the intervention between baseline and post-intervention were conducted. Adjusted analyses showed no significant intervention between-group intervention effects for sedentary time.
Results by Hinckson et al [38] showed a decrease in sitting time of approximately 60 minutes (9.26 ± 1.15 hours per day in the experimental group at baseline compared to 8.27 ± 1.45 hours per day post-intervention). Mean sitting time decreased by 0.3 hours in the control group and by 0.99 hours in the experimental group. Hinckson et al (2013) reported this difference to have an effect size of -0.49 which was a likely small decrease.
Kipping et al [34] reported the difference in means as -0.11 (-9.71 to 9.49) minutes per day for sedentary time when comparing the intervention and control group but this was not statistically significant. Although the remaining UP4FUN study by Verloigne et al [39,40,41] reported no significant differences with regards to changes in sedentary time, it did observe increases in sedentary time which were statistically significant; the percentage of time spent sedentary from pre- to post-intervention in the intervention group for total time (63.3% v. 66.5%), weekday (64.1% v. 66.7%), weekend day (62.2% v. 66.4%); and after school (60.8% v. 65.8%) [39]. However, no statistically significant differences were reported for during school hours (62.4% v. 62.9%). Table 4 provides a summary of the intervention effects of the included summaries. Only two studies aimed to interrupt sitting time at regular intervals throughout the day [35,39].
The different findings of the included studies are likely to be attributable to variations in (1) the intervention strategies used; (2) the duration and frequency of the interventions; (3) the follow-up period; (4) the sample size; (5) the theoretical models used to plan the interventions; (6) minimum wear time required for data to be considered valid; (7) the definition of non-wear time; (8) the type of monitor used; and (9) how data were cleaned.
The intervention strategies included in this review ranged from single-component to multi-component interventions and it is unknown which is more effective for reducing sedentary time in children. This is mirrored in relation to increasing total daily physical activity as there is currently limited evidence on the effectiveness of multicomponent interventions [45]. In relation to obesity, which is a multi-factorial problem, approaches must target individual and environmental factors that promote healthy behaviours [46]. However, single-component studies have also been shown to positively affect adiposity outcomes in children [47].
The duration of studies included in this review ranged from 4 weeks to 18 months. Verloigne et al [39] discussed this issue suggesting that a shorter intervention period may make the intervention more feasible; however, they also refer to a meta-analysis by Biddle et al. [48] which concluded that interventions to reduce sedentary time of less than 4 months’ duration showed small treatment effects. The frequency of the interventions included in this review ranged from 1 hour per week to daily exposure and, because the literature has not adequately ascertained the dose-response effect of the number or duration of breaks in sedentary time [49], it is difficult to clearly provide guidelines on these aspects of future interventions.
A meta-analysis by Biddle et al [48] has highlighted the variation in follow-up periods in sedentary behaviour interventions in young people given that only five out of seventeen included studies had a follow-up assessment and those that did had a short follow-up period. Therefore, the meta-analysis recommended longer follow-up with large samples.
It is clear from this review that a huge variation in sample size existed in the included studies. Given the potential for too small or too large sample sizes to affect the power of the study, it is possible that some of the included studies may have been under-powered to clearly detect between-group differences of statistical significance [50,51].
Social cognitive theory [43] was the most commonly referred to model used to plan the interventions. However, some of the included studies which reported statistically significant reductions in sedentary time did not describe a model used at the planning stage of their interventions.
Minimum wear-time varied in the included studies in terms of the number of days that accelerometers had to be worn ranging from one day to four days, weekdays only to weekday and weekend days. Also, the minimum number of hours for which the data was deemed valid ranged from 8 hours to 10 hours.
Given the variation in the definitions of non-wear time used in the included studies, it is possible that sedentary time may have been under- or over-reported — an issue highlighted by Janssen et al [52]. Actigraph was the most commonly used accelerometer used in the included studies. Although it has a built-in inclinometer, the Actigraph cannot clearly distinguish between standing and sitting and, therefore, it is possible that sedentary time may have been under- or over-reported [53]. All included studies did not report specifically how data were cleaned and reduced; therefore, the potential exists for results to vary within studies depending on the methodology used.
In four of the five studies which used the Actigraph accelerometer, sedentary behaviour was defined as less than 100 counts per minute [33,34,35,36,39,40,41]. Non-wear time would have been applicable to all eight studies. However, not all studies discussed this aspect of their statistical analysis. Four studies defined non-wear time as 20 minutes or more of consecutive zeros [32,33,35,36,39,40,41,54]. Two studies used a definition of 60 minutes or more of consecutive zeros [34,42]. Aminian et al [37] provided participants with a log to record when the activPALs were removed. When the data were analysed, if there were non-wear times which did not correspond with the participant’s log, the non-wear times were classified as missing and the data were then excluded from the analyses. One study did not report on non-wear time [38].
This is the first systematic review to examine evidence on the effectiveness of sedentary behaviour interventions based in the classroom to reduce objectively measured sedentary time in children. Three of the eight studies included in this review observed differences in sedentary time [32,35,42]. These decreases were also observed in ethnically diverse and also low- [32,35,42], middle-high [42] and high-SES [35] groups. It should be noted that the largest decrease reported was in a study which mainly focused on replacing all classroom standardised desks and chairs with sit-to-stand desks [42].
Reasons for lack of effect on sedentary time in some of the remaining interventions may have included the time lapse between the feasibility study and intervention [34]; the lack of emphasis on educational messages on sedentary behaviour [33]; and the use of accelerometers which could not differentiate between sitting and standing [39]. Verloigne et al [39] hypothesised that sedentary time could have been replaced by low-intensity physical activity (LPA); however, no significant effect was found in their study whereas Fairclough et al [33] reported a statistically significant increase in LPA at follow-up. Kipping et al [34] reported the lowest decrease in overall sitting time; the difference in means between the intervention and control groups were -0.11 (-9.91 to 9.49) minutes per day. Clemes et al [42] reported the largest decrease in overall sitting time (80.8 ± 103.4 minutes per day and 68.3 ± 97.2 minutes per day) followed by 60 minutes less per day in the study by Hinckson et al [38] and 45 minutes less per day in the study by Aminian et al [37]. However, these results were not statistically significant. Only two of the included studies aimed to interrupt sitting time [35,39]. Given that uninterrupted sedentary time is increasingly recognised as the distinct health risk behaviour as opposed to just the total time spent sedentary [4], future studies examining the effects of interventions in interrupting sedentary time are warranted.
Although the evidence suggests that multi-component interventions using a combination of a teacher-led curriculum, specialist lessons, homework tasks (with or without the assistance of parents) and printed materials may be effective in reducing sedentary time in children, the inclusion of standing desks may be more effective. The evidence presented suggests that the approach of using standing desks removes the conscious effort of the users to engage in a healthy behaviour (standing) and decrease the negative behaviour (prolonged sitting). Therefore, the studies which used the standing desks consequently removed a competing alternative behaviour from the equation (i.e. sitting) by not having traditional desks available. This is supported by Koepp et al [55] who reported that standing desks may provide an attractive alternative to traditional seated desks as there is less potential for sitting. However, it should be noted that the standing desks used in the studies included sit-to-stand desks which could be adjusted for sitting or standing. These results may be relevant to policymakers, school management teams, teachers and health promotion departments.
It is evident from the included studies that a child’s physical environment, such as the school setting, can act as an important catalyst towards reducing sedentary time. The British Heart Foundation [56] has emphasised the need for policy makers to encourage schools to reduce extended periods of sitting for pupils. Of all the strategies included in this review, the use of adjustable standing desks produced the largest decrease in sitting time [37,38,42]. The World Health Organization (WHO) [57] states that interventions that are based on theory are more likely to be effective. Although the aforementioned studies did not explicitly discuss a theoretical model, it is proposed here that the Social Ecological Model [58], which focuses on the importance of the child’s environment (individual, physical, social and policy) could be applied to not only assist our understanding of these findings, but may assist in designing future interventions. This is important because, within the social ecological framework, a combination of individual, environmental and policy interventions are required to achieve sustainable and substantial positive health behaviour change [59]. A child’s family also falls under the ecological theory which would explain why a number of the interventions in the included studies also involved, for example, homework tasks for the children to complete with their parents. However, future research may want to explore the effectiveness of using parents to reduce the sedentary time of their children. If a child’s environment within the classroom can be structured to facilitate less sitting and more standing, then consideration must be given as to how the traditional classroom may be structured away from the use of traditional desks and chairs. This is important for policymakers, schools and teachers as each can play a role in mitigating the effects of prolonged sitting. However, notably, none of the included studies examined the economic costs of the interventions which is vital for policymakers.
Although the majority of studies used random allocation to intervention or control groups, most of them lacked detail as to how this was achieved. This could possibly have been a confounding variable in the studies. However, given the nature of the studies, it would be impossible to blind participants to intervention and control conditions. Having distinct arms of varying exposure may help reduce bias in future research. Randomisation may not always be possible in school-based clustered randomised trials [60]. However, these studies are still at a high risk of bias because participants in the intervention and the control groups would have been aware which condition they were assigned to. Concealment can be achieved, for example, by using sequentially numbered, opaque, sealed envelopes. Waters et al. [60] describes studies to be at low risk of bias if the investigators enrolling participants are blinded to group assignment. A recent Cochrane Review [61] investigating the effect of interventions to reduce sitting time at work did not assess blinding of participants or personnel for risk of bias as it is not possible to blind either in studies that are trying to modify activity behaviour. Shrestha et al [61] also judged studies to be at high risk of bias if they did not report concealing intervention versus control group allocation.
The main strength of this systematic review was that only studies which objectively measured sedentary time were included in comparison to less objective measures, for example, child- or parent-report, which are subject to either over- or under-reporting [62]. A limitation of this review is that the studies which were included were assessed by one author increasing the possibility that a study has been missed.
The evidence suggests that a multi-component intervention which includes the use of standing desks may have a small effect in reducing sedentary time in the school-setting. However, these conclusions are advanced on the basis of a small number of studies. There is no evidence currently on the longitudinal effects of sedentary behaviour interventions in a school setting and more research is needed on the long-term effectiveness of school-based interventions to reduce and interrupt sitting time in children. Furthermore, given the variation in the duration of included interventions, future research should examine the optimal length required to be effective. Considering the need to form healthy habits such as reducing sitting time, exposure on a daily basis may be preferred for use in an intervention compared to once weekly. Accelerometers which can clearly differentiate between time spent sitting/lying, standing and stepping should be the preferred choice for objectively measuring sedentary time. Also, consistent/strict criteria as to what constitutes valid accelerometer data should be developed and how participants can be encouraged to meet minimum wear criteria should be examined. Researchers should also provide a clear account as to how accelerometer data are filtered and cleaned. A standard definition of non-wear time which is appropriate to the age of the participants will help achieve consistency when comparing results across studies. Collectively, these recommendations may be achieved through more multi-component, cluster randomised controlled trials which consider these methodological aspects including adequate sample size with a power analysis which involve parents and school to reduce sedentary time in children.
All authors contributed to the rationale, design and the protocol relating to the search strategy. LH conducted the search. Two authors (LH and EM) independently assessed the risk of bias of the included studies. Any disagreements on the risk of bias were discussed and then reviewed by a third author (MM). LH led the writing of the paper whilst all authors reviewed and edited the manuscript.
All authors declare no conflict of interest with the paper.
[1] | S. Nakamoto, bitcoin: A peer-to-peer electronic cash systemTech, 2008(2008). Available from: https://bitcoin.org/bitcoin.pdf. |
[2] | M. K. M. Ly, Coining bitcoin's Legal-Bits: Examining the regulatory framework for bitcoin and virtual Currencies, Harv. J. L. Tech., 27 (2014), 587-608. |
[3] | A. Zohar, bitcoin: Under the Hood, Communicat. ACM, 58 (2015), 104-113. |
[4] | V. Savvas, P. Perikles, R. Maria, bitcoin value analysis based on cross-correlations, J. Int. Bank. Commerce, 22 (2017), 1-12. |
[5] | S. Higgins. $300 Billion: Bitcoin price boosts crypto market value to record high, 2018. Available from: https://www.coindesk.com/. |
[6] | M. A. Khan and K. Salah, IoT security: Review, blockchain solutions, and open challenges, Future Generat. Comput. Syst., 82 (2018), 395-411. |
[7] | A. Suliman, Z. Husain, M. Abououf, et al., Monetization of IoT Data using Smart Contracts, IET Networks, 8 (2019), 32-37. |
[8] | M. Conti, C. Lal and S. Ruj, A Survey on Security and Privacy Issues of bitcoin., 2017. Available from: https://arxiv.org/abs/1706.00916. |
[9] | Y. X. WANG and J. T. Gao, A Regulation Scheme Based on the CiphertextPolicy Hierarchical Attribute-Based Encryption in Bitcoin System, IEEE Access, 6 (2018), 16267-16278. |
[10] | A. Miller, A. Kosba, J. Katz, et al., Nonoutsourceable Scratch-Off Puzzles to Discourage bitcoin Mining Coalitions, Proc. 22nd ACM SIGSAC Conf. Comput. Comm. Secur. (CCS), Denver, Colorado, USA, October, 2015 (2015), 680-691. |
[11] | G. O. Karame, E. Androulaki, M. Roeschlin, et al., Misbehavior in bitcoin: A study of doublespending and accountability, ACM T. Ioform. Syst. SE., 18 (2015), 1-32. |
[12] | G. O. Karame, E. Androulaki, M. Roeschlin, et al., Misbehavior in Bitcoin: A Study of DoubleSpending and Accountability ACM Transact. Inform. Syst. Secur., 18 (2015), 1-32. |
[13] | Khaled Salah, M. H. U. Rehman, N. Nizamuddin, Blockchain for AI: Review and open research challenges, IEEE Access, 7 (2019), 10127-10148. |
[14] | I. Eyal and E. G. Sirer, Majority is not enough: Bitcoin mining is vulnerable, Proc. Int. Conf. Fina. Cryptol. Secur., Christ Church, Barbados, March, 2014 (2014), 436- 454. |
[15] | H. R. HASAN and K. Salah, Combating deepfake videos using blockchain and smart contracts, IEEE Access, 7 (2019), 41596-41606. |
[16] | B. Johnson, A. Laszka, J. Grossklags, et al., Game-Theoretic analysis of DDoS attacks against bitcoin mining pools, Proc. Int. Conf. Fina. Cryptol. Secur., Christ Church, Barbados, March, 2014 (2014), 72-86. |
[17] | E. Heilman, A. Kendler, A. Zohar, et al., Eclipse attacks on bitcoin's peer-to-peer network, Porc. 24th USENIX Symp. Secur., Washington, D.C., USA, 2015 (2015), 129-144. |
[18] | K. Nayak, S. Kumar, A. Miller, et al., Stubborn mining: Generalizing selfish mining and combining with an eclipse attack, Proc. IEEE Euro. Symp. Secur Privacy (Euro S&P), Saarbrucken, Germany, March, 2016 (2016), 1-16. |
[19] | N. T. Courtois and L. Bahack, On subversive miner strategies and block withholding attack in bitcoin digital currency, 2014. Available from: https://arxiv.org/abs/1402.1718. |
[20] | M. Rosenfeld, Analysis of bitcoin pooled mining reward systems. Accessed: Nov.30, 2018, 2011. Available from: https://arxiv.org/abs/1112.4980. |
[21] | D. Wu, X. D. Liu, X. B. Yan, et al., Equilibrium analysis of bitcoin block withholding attack: A generalized model, Reliabil. Eng. Syst. Safety, 5 (2019), 1-32. |
[22] | L. Luu, R. Saha, I. Parameshwaran, et al., On power splitting games in distributed computation: The case of bitcoin pooled mining, Proc. IEEE Symp. 28th Comput. Secur. Found (CSF), Verona, Italy, July, 2015 (2015), 1-18. |
[23] | I. Eyal, The miner's dilemma, Proc. IEEE Symp. Secur. Privacy (SP), San Jose, CA, USA, July, 2015 (2015), 89-103. |
[24] | S. Bag, S. Ruj and K. Sakurai, Bitcoin block withholding attack: Analysis and mitigation, IEEE Trans. Inf. Forensic Secur., 12 (2017), 1967-1978. |
[25] | N. T. Courtois and L. Bahack, On subversive miner strategies and block withholding attack in bitcoin digital currency, 2014. Available from: Available:https://arxiv.org/abs/1402.1718. |
[26] | A. Laszka, B. Johnson and J. Grossklags, When bitcoin mining pools run dry, Proc. Int. Conf. Fina. Cryptol Secur., San Juan, Puerto Rico, January, 2015 (2015), 63-77. |
[27] | S. Shen, H. Li, R. Han, et al., Differential game-based strategies for preventing malware propagation in wireless sensor networks, IEEE Trans. Inf. Forensic Secur., 9 (2014), 1962-1973. |
[28] | J. Tuwiner, Bitcoin Mining Pools, 2018. Available from: https://www.buybitcoinworldwide.com. |
[29] | O. Schrijvers, J. Bonneau, D. Boneh, et al., Incentive compatibility of bitcoin mining pool reward functions, Proc. Int. Conf. Fina. Cryptol.Secur., Christ Church, Barbados, 2016 (2016), 477- 498. |
[30] | S. Bag and K. Sakurai, Yet another note on block withholding attack on bitcoin mining pools, Proc. Int. Conf. Inf. Secur.(ISC), Honolulu, HI, USA, 2016 (2016), 167-180. |
[31] | J. S. R. Jangn and C. T. Sun, Neuro-fuzzy and soft computing: A computational approach to learning and machine intelligence, Prentice-Hall Inc., Upper Saddle River, NJ, 1996 (1996). |
[32] | M. Mizumoto and K. Tanaka, Some properties of fuzzy sets of type-2, Inform. Control, 31 (1976), 312-340. |
1. | Liane B. Azevedo, Esther M.F. Sluijs, Helen J. Moore, Kathryn Hesketh, Determinants of change in accelerometer‐assessed sedentary behaviour in children 0 to 6 years of age: A systematic review, 2019, 20, 1467-7881, 1441, 10.1111/obr.12882 | |
2. | Ana María Contardo Ayala, Bronwyn Sudholz, Jo Salmon, David W. Dunstan, Nicola D. Ridgers, Lauren Arundell, Anna Timperio, Hajo Zeeb, The impact of height-adjustable desks and prompts to break-up classroom sitting on adolescents' energy expenditure, adiposity markers and perceived musculoskeletal discomfort, 2018, 13, 1932-6203, e0203938, 10.1371/journal.pone.0203938 | |
3. | Lynda Hegarty, Marie H. Murphy, Karen Kirby, Elaine Murtagh, John Mallett, Jacqueline L. Mair, The Influence of Role Models on the Sedentary Behaviour Patterns of Primary School-Aged Children and Associations with Psychosocial Aspects of Health, 2020, 17, 1660-4601, 5345, 10.3390/ijerph17155345 | |
4. | Jennifer L. Copeland, Sedentary Time in Older Adults: Sitting Is Not the New Smoking, 2019, 8, 2163-0453, 70, 10.1123/kr.2018-0061 | |
5. | Anoek M. Adank, Dave H. H. Van Kann, Joris A. A. Hoeboer, Sanne I. de Vries, Stef P. J. Kremers, Steven B. Vos, Investigating Motor Competence in Association with Sedentary Behavior and Physical Activity in 7- to 11-Year-Old Children, 2018, 15, 1660-4601, 2470, 10.3390/ijerph15112470 | |
6. | Aleš Gába, Jan Dygrýn, Nikola Štefelová, Lukáš Rubín, Karel Hron, Lukáš Jakubec, Replacing school and out-of-school sedentary behaviors with physical activity and its associations with adiposity in children and adolescents: a compositional isotemporal substitution analysis, 2021, 26, 1342-078X, 10.1186/s12199-021-00932-6 | |
7. | Stuart J.H. Biddle, Jason Bennie, Editorial for Special Issue: Advances in Sedentary Behavior Research and Translation, 2017, 4, 2327-8994, 33, 10.3934/publichealth.2017.1.33 | |
8. | Danilo R. Silva, Cláudia S. Minderico, Fernando Pinto, Paul J. Collings, Edilson S. Cyrino, Luís B. Sardinha, Impact of a classroom standing desk intervention on daily objectively measured sedentary behavior and physical activity in youth, 2018, 21, 14402440, 919, 10.1016/j.jsams.2018.01.007 | |
9. | Heeseung Choi, Chanhee Kim, Heesung Ko, Chang Gi Park, Relationship Between Sedentary Time and Sleep Duration Among Korean Adolescents, 2020, 36, 1059-8405, 423, 10.1177/1059840519842230 | |
10. | Priscila Cristina dos Santos, Valter Cordeiro Barbosa Filho, Jaqueline Aragoni da Silva, Alexsandra da Silva Bandeira, Giseli Minatto, Kelly Samara da Silva, What Works in Sedentary Behavior Interventions for Youth: A Review of Reviews, 2019, 4, 2363-8346, 267, 10.1007/s40894-018-0105-4 | |
11. | Rhiannon Eleanor Day, Pinki Sahota, Meaghan Sarah Christian, Effective implementation of primary school-based healthy lifestyle programmes: a qualitative study of views of school staff, 2019, 19, 1471-2458, 10.1186/s12889-019-7550-2 | |
12. | Javier Rodrigo-Sanjoaquín, Julien E. Bois, Alberto Aibar Solana, Léna Lhuisset, Javier Zaragoza Casterad, Identifying Promising School-Based Intervention Programs to Promote 24-Hour Movement Guidelines among Children: Protocol for a Systematic Review, 2020, 12, 2071-1050, 9436, 10.3390/su12229436 | |
13. | H.Q. Chim, Pascal W.M. Van Gerven, Renate H.M. de Groot, Mirjam G.A. oude Egbrink, Roy H.J. Erkens, Hans H.C.M. Savelberg, The effects of standing tutorial meetings on physical activity behavior in undergraduates: A randomized controlled trial, 2021, 230, 00319384, 113294, 10.1016/j.physbeh.2020.113294 | |
14. | Aron P Sherry, Natalie Pearson, Nicola D Ridgers, Sally E Barber, Daniel D Bingham, Liana C Nagy, Stacy A Clemes, activPAL-measured sitting levels and patterns in 9–10 years old children from a UK city, 2019, 41, 1741-3842, 757, 10.1093/pubmed/fdy181 | |
15. | Jan-Erik Romar, Ida Enqvist, Janne Kulmala, Jouni Kallio, Tuija Tammelin, Physical activity and sedentary behaviour during outdoor learning and traditional indoor school days among Finnish primary school students, 2019, 19, 1472-9679, 28, 10.1080/14729679.2018.1488594 | |
16. | Associations between the Home Physical Environment and Children’s Home-Based Physical Activity and Sitting, 2019, 16, 1660-4601, 4178, 10.3390/ijerph16214178 | |
17. | Stacy A Clemes, Daniel D Bingham, Natalie Pearson, Yu-Ling Chen, Charlotte Edwardson, Rosemary McEachan, Keith Tolfrey, Lorraine Cale, Gerry Richardson, Mike Fray, James Altunkaya, Stephan Bandelow, Nishal Bhupendra Jaicim, Sally E Barber, Sit–stand desks to reduce sedentary behaviour in 9- to 10-year-olds: the Stand Out in Class pilot cluster RCT, 2020, 8, 2050-4381, 1, 10.3310/phr08080 | |
18. | Chih-Hsiang Yang, Jennifer Zink, Britni R Belcher, Martina Kanning, Genevieve F Dunton, Age-varying Bi-directional Associations Between Momentary Affect and Movement Behaviors in Children: Evidence From a Multi-wave Ecological Momentary Assessment Study, 2021, 0883-6612, 10.1093/abm/kaaa124 | |
19. | Nicole E. Blackburn, Jason J. Wilson, Ilona I. McMullan, Paolo Caserotti, Maria Giné-Garriga, Katharina Wirth, Laura Coll-Planas, Sergi Blancafort Alias, Marta Roqué, Manuela Deidda, Andrew T. Kunzmann, Dhayana Dallmeier, Mark A. Tully, The effectiveness and complexity of interventions targeting sedentary behaviour across the lifespan: a systematic review and meta-analysis, 2020, 17, 1479-5868, 10.1186/s12966-020-00957-0 | |
20. | Lauren McMichan, Ann-Marie Gibson, David A. Rowe, Classroom-Based Physical Activity and Sedentary Behavior Interventions in Adolescents: A Systematic Review and Meta-Analysis, 2018, 15, 1543-3080, 383, 10.1123/jpah.2017-0087 | |
21. | Nematullah Hayba, Chris Rissel, Margaret Allman Farinelli, Effectiveness of lifestyle interventions in preventing harmful weight gain among adolescents: A systematic review of systematic reviews, 2021, 22, 1467-7881, 10.1111/obr.13109 | |
22. | Aron P. Sherry, Natalie Pearson, Nicola D. Ridgers, William Johnson, Sally E. Barber, Daniel D. Bingham, Liana C. Nagy, Stacy A. Clemes, Impacts of a Standing Desk Intervention within an English Primary School Classroom: A Pilot Controlled Trial, 2020, 17, 1660-4601, 7048, 10.3390/ijerph17197048 | |
23. | Ellen Caroline M. Silva, Luciana L. S. Barboza, Larissa Gandarela, Julián Tejada, Heike Schmitz, Thayse Natacha Gomes, Roberto Jerônimo S. Silva, Luís B. Sardinha, Danilo R. Silva, Two-Year Effectiveness of a Controlled Trial With Physically Active Lessons on Behavioral Indicators of School Children, 2022, 0270-1367, 1, 10.1080/02701367.2021.2020707 | |
24. | Sanne te Meerman, Justin E. Freedman, Laura Batstra, ADHD and reification: Four ways a psychiatric construct is portrayed as a disease, 2022, 13, 1664-0640, 10.3389/fpsyt.2022.1055328 | |
25. | Jani Hartikainen, Eero A. Haapala, Anna-Maija Poikkeus, Eero Lapinkero, Arto J. Pesola, Timo Rantalainen, Arja Sääkslahti, Ying Gao, Taija Finni, Comparison of Classroom-Based Sedentary Time and Physical Activity in Conventional Classrooms and Open Learning Spaces Among Elementary School Students, 2021, 3, 2624-9367, 10.3389/fspor.2021.626282 | |
26. | José Francisco Jiménez-Parra, Noelia Belando-Pedreño, Alfonso Valero-Valenzuela, The Effects of the ACTIVE VALUES Program on Psychosocial Aspects and Executive Functions, 2022, 20, 1660-4601, 595, 10.3390/ijerph20010595 | |
27. | Jani Hartikainen, Eero A. Haapala, Arja Sääkslahti, Anna-Maija Poikkeus, Taija Finni, Sedentary Patterns and Sit-to-Stand Transitions in Open Learning Spaces and Conventional Classrooms among Primary School Students, 2022, 19, 1660-4601, 8185, 10.3390/ijerph19138185 | |
28. | Marta Amor-Barbosa, Anna Ortega-Martínez, Andoni Carrasco-Uribarren, Maria Caridad Bagur-Calafat, Active School-Based Interventions to Interrupt Prolonged Sitting Improve Daily Physical Activity: A Systematic Review and Meta-Analysis, 2022, 19, 1660-4601, 15409, 10.3390/ijerph192215409 | |
29. | J. Rodrigo-Sanjoaquín, A. Corral-Abós, A. Aibar Solana, J. Zaragoza Casterad, L. Lhuisset, J.E. Bois, Effectiveness of school-based interventions targeting physical activity and sedentary time among children: a systematic review and meta-analysis of accelerometer-assessed controlled trials, 2022, 213, 00333506, 147, 10.1016/j.puhe.2022.10.004 | |
30. | Danilo R. Silva, Daniel G. S. Machado, Fernando Pinto, Pedro B. Júdice, Cláudia S. Minderico, Paul J. Collings, Edilson S. Cyrino, Luís B. Sardinha, Effect of a 16-week multi-level classroom standing desk intervention on cognitive performance and academic achievement in adolescents, 2022, 12, 2045-2322, 10.1038/s41598-022-18248-y | |
31. | Jani Hartikainen, Eero A. Haapala, Anna-Maija Poikkeus, Arja Sääkslahti, Arto Laukkanen, Ying Gao, Taija Finni, Classroom-based physical activity and teachers’ instructions on students’ movement in conventional classrooms and open learning spaces, 2023, 26, 1387-1579, 177, 10.1007/s10984-022-09411-3 | |
32. | Piyawat Katewongsa, Panya Choolers, Pairoj Saonuam, Dyah Anantalia Widyastari, Effectiveness of a Whole-of-School Approach in Promoting Physical Activity for Children: Evidence From Cohort Study in Primary Schools in Thailand, 2022, 0273-5024, 1, 10.1123/jtpe.2021-0186 | |
33. | Bina Ram, Kimberley A Foley, Esther van Sluijs, Dougal S Hargreaves, Russell M Viner, Sonia Saxena, Developing a core outcome set for physical activity interventions in primary schools: a modified-Delphi study, 2022, 12, 2044-6055, e061335, 10.1136/bmjopen-2022-061335 | |
34. | Dominic Fisher, Quinette Louw, The Effect of Classroom-Based Interventions on Sedentary Behavior and Spinal Health in Schoolchildren: Systematic Review, 2022, 11, 1929-073X, e39006, 10.2196/39006 | |
35. | Mansoor Rahman A, Baskaran Chandrasekaran, Estimating the Impact of the Pandemic on Children's Physical Health: A Scoping Review, 2021, 91, 0022-4391, 936, 10.1111/josh.13079 | |
36. | Sarah Nally, Nicola D. Ridgers, Alison M. Gallagher, Marie H. Murphy, Jo Salmon, Angela Carlin, “When You Move You Have Fun”: Perceived Barriers, and Facilitators of Physical Activity From a Child's Perspective, 2022, 4, 2624-9367, 10.3389/fspor.2022.789259 | |
37. | Jonathan P. Wong, Jennifer Bachman, Suzanne Griggs, Jacob Hartz, Decreasing Sedentary Behaviors in Youth to Prevent and Manage Childhood Obesity: Is It Realistic?, 2023, 25, 1523-3804, 479, 10.1007/s11883-023-01121-2 | |
38. | Henner Hanssen, Trine Moholdt, Martin Bahls, Alessandro Biffi, Monika Siegrist, Adam J Lewandowski, Giuseppe Biondi-Zoccai, Elena Cavarretta, Ane Kokkvoll, Maja-Lisa Løchen, Viviana Maestrini, Rita Salvador Pinto, Stefano Palermi, David Thivel, Malgorzata Wojcik, Dominique Hansen, Emeline M Van Craenenbroeck, Daniel Weghuber, Nicolle Kraenkel, Monica Tiberi, Lifestyle interventions to change trajectories of obesity-related cardiovascular risk from childhood onset to manifestation in adulthood: a joint scientific statement of the task force for childhood health of the European Association of Preventive Cardiology and the European Childhood Obesity Group, 2023, 30, 2047-4873, 1462, 10.1093/eurjpc/zwad152 | |
39. | Marie Cholley-Gomez, Steven Laujac, Cyrille Delpierre, Marion Carayol, Effectiveness of multilevel interventions based on socio-ecological model to decrease sedentary time in children: a systematic review of controlled studies, 2023, 11, 2296-2565, 10.3389/fpubh.2023.1106206 | |
40. | Javier Rodrigo-Sanjoaquín, Julien E Bois, Alberto Aibar Solana, Léna Lhuisset, Ana Corral-Abós, Javier Zaragoza Casterad, Are school-based interventions promoting 24-hour movement guidelines among children? A scoping review, 2023, 82, 0017-8969, 444, 10.1177/00178969231165468 | |
41. | Hernawan Hernawan, Dena Widyawan, Mukhtar Mukhtar, Hartman Nugraha, Aridhotul Haqiyah, Physical Activities and sedentary time of Students Outdoor Education and Conventional Education in Primary Schools, 2024, 7, 2645-9094, 389, 10.33438/ijdshs.1403090 | |
42. | Flaminia Ronca, Paul W. Burgess, Peter Savage, Nipuna Senaratne, Evelyn Watson, Mike Loosemore, Decreasing Sedentary Time during Lessons Reduces Obesity in Primary School Children: The Active Movement Study, 2024, 17, 1662-4025, 243, 10.1159/000536665 | |
43. | Caroline Maité Marie Bernal, Léna Lhuisset, Nicolas Fabre, François Trudeau, Julien Bois, Objectively assessed school-based intervention to reduce children’s sedentary time: a systematic review, 2023, 38, 0957-4824, 10.1093/heapro/daad140 | |
44. | Dominic Fisher, Quinette Louw, Primary school learners’ movement during class time: perceptions of educators in the Western Cape, South Africa, 2023, 23, 1471-2458, 10.1186/s12889-023-17428-3 | |
45. | Caroline Bernal, Léna Lhuisset, Nicolas Fabre, Julien Bois, Promouvoir l’activité physique à l’école primaire pour les enfants de milieux défavorisés : enjeux, constats et propositions de leviers d’intervention efficaces, 2021, 1969-0622, 10.4000/rechercheseducations.11053 | |
46. | Y. El Miedany, Hala Lotfy, Laila A.G. Hegazy, Maha Elgaafary, Safaa Mahran, Susan Plummer, Walaa Elwakil, The Egyptian 24-h movement guidelines for children and adolescents: an integration of physical activity, sedentary behaviour, sleep and eating habits—by the Egyptian Academy of Bone and Muscle health, 2024, 51, 2090-3235, 10.1186/s43166-024-00279-0 | |
47. | Harriet Koorts, Anna Timperio, Chris Lonsdale, Nicola D Ridgers, David R Lubans, Jacqueline Della Gatta, Adrian Bauman, Amanda Telford, Lisa Barnett, Karen E Lamb, Natalie Lander, Samuel K Lai, Taren Sanders, Lauren Arundell, Helen Brown, Katrina Wilhite, Jo Salmon, Scaling up a school-based intervention to increase physical activity and reduce sedentary behaviour in children: protocol for theTransformUshybrid effectiveness–implementation trial, 2023, 13, 2044-6055, e078410, 10.1136/bmjopen-2023-078410 | |
48. | José Francisco López-Gil, 2024, Chapter 2, 978-3-031-65594-4, 41, 10.1007/978-3-031-65595-1_2 | |
49. | Mohammed Khudair, Anna Marcuzzi, Gavin Daniel Tempest, Kwok Ng, Ratko Peric, František Bartoš, Maximilian Maier, Mirko Brandes, Angela Carlin, Simone Ciaccioni, Cristina Cortis, Chiara Corvino, Andrea di Credico, Patrik Drid, Francesca Gallè, Pascal Izzicupo, Henriette Jahre, Athanasios Kolovelonis, Atle Kongsvold, Evangelia Kouidi, Paul Jarle Mork, Federico Palumbo, Penny Louise Sheena Rumbold, Petru Sandu, Mette Stavnsbo, Ioannis Syrmpas, Sofia Vilela, Catherine Woods, Kathrin Wunsch, Laura Capranica, Ciaran MacDonncha, Fiona Chun Man Ling, DE-PASS Best Evidence Statement (BESt): A Systematic Review and Meta-analysis on the Effectiveness of Trials on Device-Measured Physical Activity and Sedentary Behaviour and Their Determinants in Children Aged 5–12 Years, 2024, 0112-1642, 10.1007/s40279-024-02136-8 | |
50. | David Larose, Carole-Lynn Massie, Alix St-Aubin, Valérie Boulay-Pelletier, Elyse Boulanger, Marie Denise Lavoie, Jennifer Yessis, Angelo Tremblay, Vicky Drapeau, Effects of flexible learning spaces, active breaks, and active lessons on sedentary behaviors, physical activity, learning, and musculoskeletal health in school-aged children: a scoping review, 2024, 3, 2731-4391, 10.1186/s44167-024-00068-2 | |
51. | Apoorva Rathod, Jerry Olsson, Tim Schwanen, ‘Can You Please Sit Still?!’: Exploring the Dynamics of Children's Sedentary Behaviours at Home, 2024, 0951-0605, 10.1111/chso.12932 | |
52. | Ana Cikač, Kaja Teraž, Saša Pišot, Subjective assessment of sedentary behavior between theory and practice: Pilot study using the “Sedentary meter”, 2024, 16, 2406-1379, 25, 10.31382/eqol.241204 | |
53. | Anísio Luis da Silva Brito, Rafael Miranda Tassitano, Edilânea Nunes Mélo, Simone José dos Santos, Jorge Mota, Mauro Virgílio Gomes de Barros, Efeito de uma intervenção em aulas de educação física sobre a redução do comportamento sedentário em adolescentes, 2024, 40, 1678-4464, 10.1590/0102-311xpt211023 |
Searches |
1. Sedentary Lifestyle/ |
2. sedentary.tw. |
3. sitting.tw. |
4. 1 or 2 or 3 |
5. "teacher*".tw. |
6. Schools/ |
7. (school or schools).mp. (mp = title, abstract, original title, name of substance word, subject heading word, keyword heading word, protocol supplementary concept word, rare disease supplementary concept word, unique identifier) |
8. 5 or 6 or 7 |
9. exp Child/ |
10. (child* or preschool* or pre school*).tw. |
11. 9 or 10 |
12. 4 and 8 and 11 |
Studies | Participants | Details of Intervention | |||||||
Authors & Year | n | Location | Age (yrs) | Gender | Name of Intervention | Duration | Duration per Session | Frequency (days/week) | Accelerometer Used |
Aminian et al., (2015) [37] | 26 | New Zealand | 9-11 | m f | N/A | 9 weeks | Full school day | 5 | activPAL |
Breslin et al. (2012) [32] | 416 | UK | 8-9 | m f | Sport for LIFE | 12 weeks | 1 hour | 1 | Actigraph |
Carson et al. (2013) [35]; Yildirim (2014)[36] | 268 | Australia | 7-9 | m f | Transform Us! | 18 months | 30 mins | 5 | Actigraph |
Clemes et al. (2015) [42] | 74 | UK and Australia | 9-12 | m f | N/A | 9-10 weeks | UK group: minimum of 1 hour per day. Australian group: full school day | 5 | activPAL |
Fairclough et al. (2013) [33] | 318 | UK | 10-11 | m f | CHANGE! Project | 20 weeks | 60 mins | 1 | Actigraph |
Hinckson et al. (2013) [38] | 30 | New Zealand | 9-11 | m f | N/A | 4 weeks | Full school day | 5 | activPAL |
Kipping et al. (2014) [34] | 2221 | UK | 8-10 | m f | Active for Life Year 5 (AFLY5) | 1 school year | Varied | Varied | Actigraph |
Verloigne et al. (2012) [39]; Verloigne et al. (2015) [40]; Vik et al. (2015) [41] | 372 | Belgium1 | 9-11 | m f | UP4FUN | 6 weeks | Not specified | 1-2 | Actigraph |
1 Intervention implemented in Belgium, Germany, Greece, Hungary and Norway but activPAL data related to Belgian sample only. |
Authors & Year | Adequate sequence generation? | Allocation concealment? | Blinding of participants and personnel? | Blinding of outcome assessors? | Incomplete outcome data addressed? | Free of selective reporting? | Free of other bias? | |
1 | Aminian et al. (2015) [37] | Unclear | Unclear | Unclear | Unclear | Low | Low | High |
2 | Breslin et al. (2012) [32] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | High |
3 | Clemes et al. (2015) [42] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear |
4 | Carson et al. (2013) [35] | Low | Unclear | High | Unclear | High | High | Low |
5 | Fairclough et al. (2013) [33] | Unclear | Unclear | Unclear | High | High | Unclear | Low |
6 | Hinckson et al. (2015) [38] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | High |
7 | Kipping et al. (2014) [22] | Unclear | Low | Low | Low | Low | Low | Low |
8 | Verloigne et al. (2012) [39] | Unclear | Unclear | Unclear | Unclear | High | Unclear | High |
9 | Verloigne et al. (2015) [40] | Unclear | Unclear | Unclear | Unclear | High | Unclear | High |
10 | Vik et al. (2015) [41] | Unclear | Unclear | Unclear | Unclear | Low | Unclear | High |
11 | Yildirim et al. (2014) [42] | Low | Unclear | Unclear | Unclear | High | Unclear | Low |
Authors & Year | Nature of Intervention | Intervention Effects |
Aminian et al. (2015) [37] | Standing workstations replaced traditional desks. Exercise balls, beanbags and mat space. | Overall mean sitting time (hours; mean ± SD): Intervention: pre, 9.56 ± 1.27; post, 7.64 ± 2.06. Control: pre, 9.34 ± 1.32; post, 8.08 ± 3.10. Mean sitting time during school (hours; mean ± SD): Intervention: pre, 3.88 ±0.36; post, 2.81 ± 0.36. Control: pre, 3.59 ± 0.45; post, 3.24 ± 0.81. Decrease in weekday sitting time: 45 minutes |
(CL ± 122). Moderate reduction by possibly 36 minutes in sitting time during school but results unclear. | ||
Breslin et al. (2012) [32] | Education theory and activities led by teacher. | Intervention group: lower levels of sedentary behaviour at follow-up compared to baseline. Significant main effects: F(1, 49) = 5.585; p < 0.022; ηp2 = 0.102. Increase in sedentary behaviour 15:00-18:00. Decrease in sedentary behaviour 18:00-bedtime. Significant multivariate effects: Intervention group, sedentary behaviour: F(4, 56) = 14.416; p < 0.001; ηp2 =0.507. Time period: 15:00-18:00, F(1, 59) = 4.906; p < 0.031, ηp2 = 0.077 and 18:00-bedtime, F(1, 59) = 38.821; p < 0.001; ηp2 = 0.397). |
Carson et al. (2013)[35]; Yildirim (2014)[36] | Combination of strategies using the curriculum, in-house activities, physical environment < home setting | 13.3 minute decrease in weekday sitting time in arm of intervention that aimed to increase PA and reduce SB (significant). Total effect on total weekday sedentary time was -13.28 (-24.37, 2.20) (95% CI). |
Clemes et al. (2015) [42] | UK study: participants were rotated around 6 sit-to-stand desks so that they stood for at least one hour per day. Australian study: sit-to-stand desks replaced all traditional desks and participants stood for a minimum of 30 mins per day. In both studies, teachers provided information on benefits of reducing sedentary behaviour and classroom sitting time. | Sitting during class (% of wear time): UK sample: Intervention: pre, 71.8 ± 10.6; post, 62 ± 15.8 (p = 0.03). Control: pre, 68.6 ± 20; post, 65.4 ± 20.1 (not significant). Australian sample: Intervention: pre, 67.9 ± 8.4; post, 58.5 ± 8.4 (p < 0.001). Control: pre, 70.8 ± 5.8; post, 64.8 ± 10.8 (p = 0.04). |
Weekday sitting time (minutes): UK sample (mean ±SD): Intervention: pre, 606.5 ± 66.4; post, 525.7 ± 103.7. Control: pre, 566.1 ± 92.6; post, 574 ± 180.6. Australian sample (mean ±SD): Intervention: pre, 498.2 ± 80.2; post, 429.8 ± 60.4. Control: pre, 489.7 ± 84.6; post, 435.5 ± 81.2. | ||
Fairclough et al. (2013) [33] | Teacher-led curriculum, learning resources, homework tasks, CD-ROM. Teacher received 4 hours of training in the delivery of the curriculum resource. | Compared with baseline data, 28 minutes more sedentary time in intervention group post-intervention but 8.5 minutes less at follow-up. Effect for sedentary time: β = -8.44 (95% CI = -53.23, 36.35) minutes (non-significant). |
Hinckson et al. (2015) [38] | Standing workstations replaced traditional desks. | Sitting Time (hours; mean ± SD): Intervention: pre, 9.26 ± 1.15; post, 8.27 ± 1.45. Control: pre, 9.30 ± 1.46; post, 9.00 ± 0.80. Effect size (90% CL): 0.49 (0.64). |
Kipping et al. (2014) [34] | Teachers trained to deliver 16 sessions — 10 of which had associated homework. Child-parent interactive homework tasks also. | Difference in means between intervention and control group of -0.11 (-9.71 to 9.49) minutes per day less sitting (non-significant). |
Verloigne et al. (2012) [39]; Verloigne et al. (2015) [40]; Vik et al. (2015) [41] | Teacher delivered 1-2 intervention lessons per week. Manual given to teachers who were trained by researcher. Each week had a specific theme. | Effects: Sedentary time (β = 2.18, SE = 0.59, d = 0.20); weekday sedentary time (β = 1.07, SE = 0.47, d = 0.12) (significant); weekend day sedentary time (β = 4.17, SE = 0.88, d = 0.25) (significant); school hours (β = 0.22, SE = 0.46) (non-significant); after school sedentary time (β = 3.32, SE = 0.67, d = 0.26) (significant). |
Searches |
1. Sedentary Lifestyle/ |
2. sedentary.tw. |
3. sitting.tw. |
4. 1 or 2 or 3 |
5. "teacher*".tw. |
6. Schools/ |
7. (school or schools).mp. (mp = title, abstract, original title, name of substance word, subject heading word, keyword heading word, protocol supplementary concept word, rare disease supplementary concept word, unique identifier) |
8. 5 or 6 or 7 |
9. exp Child/ |
10. (child* or preschool* or pre school*).tw. |
11. 9 or 10 |
12. 4 and 8 and 11 |
Studies | Participants | Details of Intervention | |||||||
Authors & Year | n | Location | Age (yrs) | Gender | Name of Intervention | Duration | Duration per Session | Frequency (days/week) | Accelerometer Used |
Aminian et al., (2015) [37] | 26 | New Zealand | 9-11 | m f | N/A | 9 weeks | Full school day | 5 | activPAL |
Breslin et al. (2012) [32] | 416 | UK | 8-9 | m f | Sport for LIFE | 12 weeks | 1 hour | 1 | Actigraph |
Carson et al. (2013) [35]; Yildirim (2014)[36] | 268 | Australia | 7-9 | m f | Transform Us! | 18 months | 30 mins | 5 | Actigraph |
Clemes et al. (2015) [42] | 74 | UK and Australia | 9-12 | m f | N/A | 9-10 weeks | UK group: minimum of 1 hour per day. Australian group: full school day | 5 | activPAL |
Fairclough et al. (2013) [33] | 318 | UK | 10-11 | m f | CHANGE! Project | 20 weeks | 60 mins | 1 | Actigraph |
Hinckson et al. (2013) [38] | 30 | New Zealand | 9-11 | m f | N/A | 4 weeks | Full school day | 5 | activPAL |
Kipping et al. (2014) [34] | 2221 | UK | 8-10 | m f | Active for Life Year 5 (AFLY5) | 1 school year | Varied | Varied | Actigraph |
Verloigne et al. (2012) [39]; Verloigne et al. (2015) [40]; Vik et al. (2015) [41] | 372 | Belgium1 | 9-11 | m f | UP4FUN | 6 weeks | Not specified | 1-2 | Actigraph |
1 Intervention implemented in Belgium, Germany, Greece, Hungary and Norway but activPAL data related to Belgian sample only. |
Authors & Year | Adequate sequence generation? | Allocation concealment? | Blinding of participants and personnel? | Blinding of outcome assessors? | Incomplete outcome data addressed? | Free of selective reporting? | Free of other bias? | |
1 | Aminian et al. (2015) [37] | Unclear | Unclear | Unclear | Unclear | Low | Low | High |
2 | Breslin et al. (2012) [32] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | High |
3 | Clemes et al. (2015) [42] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear |
4 | Carson et al. (2013) [35] | Low | Unclear | High | Unclear | High | High | Low |
5 | Fairclough et al. (2013) [33] | Unclear | Unclear | Unclear | High | High | Unclear | Low |
6 | Hinckson et al. (2015) [38] | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | High |
7 | Kipping et al. (2014) [22] | Unclear | Low | Low | Low | Low | Low | Low |
8 | Verloigne et al. (2012) [39] | Unclear | Unclear | Unclear | Unclear | High | Unclear | High |
9 | Verloigne et al. (2015) [40] | Unclear | Unclear | Unclear | Unclear | High | Unclear | High |
10 | Vik et al. (2015) [41] | Unclear | Unclear | Unclear | Unclear | Low | Unclear | High |
11 | Yildirim et al. (2014) [42] | Low | Unclear | Unclear | Unclear | High | Unclear | Low |
Authors & Year | Nature of Intervention | Intervention Effects |
Aminian et al. (2015) [37] | Standing workstations replaced traditional desks. Exercise balls, beanbags and mat space. | Overall mean sitting time (hours; mean ± SD): Intervention: pre, 9.56 ± 1.27; post, 7.64 ± 2.06. Control: pre, 9.34 ± 1.32; post, 8.08 ± 3.10. Mean sitting time during school (hours; mean ± SD): Intervention: pre, 3.88 ±0.36; post, 2.81 ± 0.36. Control: pre, 3.59 ± 0.45; post, 3.24 ± 0.81. Decrease in weekday sitting time: 45 minutes |
(CL ± 122). Moderate reduction by possibly 36 minutes in sitting time during school but results unclear. | ||
Breslin et al. (2012) [32] | Education theory and activities led by teacher. | Intervention group: lower levels of sedentary behaviour at follow-up compared to baseline. Significant main effects: F(1, 49) = 5.585; p < 0.022; ηp2 = 0.102. Increase in sedentary behaviour 15:00-18:00. Decrease in sedentary behaviour 18:00-bedtime. Significant multivariate effects: Intervention group, sedentary behaviour: F(4, 56) = 14.416; p < 0.001; ηp2 =0.507. Time period: 15:00-18:00, F(1, 59) = 4.906; p < 0.031, ηp2 = 0.077 and 18:00-bedtime, F(1, 59) = 38.821; p < 0.001; ηp2 = 0.397). |
Carson et al. (2013)[35]; Yildirim (2014)[36] | Combination of strategies using the curriculum, in-house activities, physical environment < home setting | 13.3 minute decrease in weekday sitting time in arm of intervention that aimed to increase PA and reduce SB (significant). Total effect on total weekday sedentary time was -13.28 (-24.37, 2.20) (95% CI). |
Clemes et al. (2015) [42] | UK study: participants were rotated around 6 sit-to-stand desks so that they stood for at least one hour per day. Australian study: sit-to-stand desks replaced all traditional desks and participants stood for a minimum of 30 mins per day. In both studies, teachers provided information on benefits of reducing sedentary behaviour and classroom sitting time. | Sitting during class (% of wear time): UK sample: Intervention: pre, 71.8 ± 10.6; post, 62 ± 15.8 (p = 0.03). Control: pre, 68.6 ± 20; post, 65.4 ± 20.1 (not significant). Australian sample: Intervention: pre, 67.9 ± 8.4; post, 58.5 ± 8.4 (p < 0.001). Control: pre, 70.8 ± 5.8; post, 64.8 ± 10.8 (p = 0.04). |
Weekday sitting time (minutes): UK sample (mean ±SD): Intervention: pre, 606.5 ± 66.4; post, 525.7 ± 103.7. Control: pre, 566.1 ± 92.6; post, 574 ± 180.6. Australian sample (mean ±SD): Intervention: pre, 498.2 ± 80.2; post, 429.8 ± 60.4. Control: pre, 489.7 ± 84.6; post, 435.5 ± 81.2. | ||
Fairclough et al. (2013) [33] | Teacher-led curriculum, learning resources, homework tasks, CD-ROM. Teacher received 4 hours of training in the delivery of the curriculum resource. | Compared with baseline data, 28 minutes more sedentary time in intervention group post-intervention but 8.5 minutes less at follow-up. Effect for sedentary time: β = -8.44 (95% CI = -53.23, 36.35) minutes (non-significant). |
Hinckson et al. (2015) [38] | Standing workstations replaced traditional desks. | Sitting Time (hours; mean ± SD): Intervention: pre, 9.26 ± 1.15; post, 8.27 ± 1.45. Control: pre, 9.30 ± 1.46; post, 9.00 ± 0.80. Effect size (90% CL): 0.49 (0.64). |
Kipping et al. (2014) [34] | Teachers trained to deliver 16 sessions — 10 of which had associated homework. Child-parent interactive homework tasks also. | Difference in means between intervention and control group of -0.11 (-9.71 to 9.49) minutes per day less sitting (non-significant). |
Verloigne et al. (2012) [39]; Verloigne et al. (2015) [40]; Vik et al. (2015) [41] | Teacher delivered 1-2 intervention lessons per week. Manual given to teachers who were trained by researcher. Each week had a specific theme. | Effects: Sedentary time (β = 2.18, SE = 0.59, d = 0.20); weekday sedentary time (β = 1.07, SE = 0.47, d = 0.12) (significant); weekend day sedentary time (β = 4.17, SE = 0.88, d = 0.25) (significant); school hours (β = 0.22, SE = 0.46) (non-significant); after school sedentary time (β = 3.32, SE = 0.67, d = 0.26) (significant). |