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Lack of physical activity (PA) and high levels of sedentary behaviour (SB) have been associated with health problems. This systematic review evaluates the effectiveness of school-based interventions to increase PA and decrease SB among 15–19-year-old adolescents, and examines whether intervention characteristics (intervention length, delivery mode and intervention provider) and intervention content (i.e. behaviour change techniques, BCTs) are related to intervention effectiveness. A systematic search of randomised or cluster randomised controlled trials with outcome measures of PA and/or SB rendered 10 results. Risk of bias was assessed using the Cochrane risk of bias tool. Intervention content was coded using Behaviour Change Technique Taxonomy v1. Seven out of 10 studies reported significant increases in PA. Effects were generally small and short-term (Cohen's d ranged from 0.132 to 0.659). Two out of four studies that measured SB reported significant reductions in SB. Interventions that increased PA included a higher number of BCTs, specific BCTs (e.g., goal setting, action planning and self-monitoring), and were delivered by research staff. Intervention length and mode of delivery were unrelated to effectiveness. More studies are needed that evaluate long-term intervention effectiveness and target SBs among older adolescents.
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International Review of Sport and Exercise Psychology
ISSN: 1750-984X (Print) 1750-9858 (Online) Journal homepage: http://www.tandfonline.com/loi/rirs20
A systematic review of school-based interventions
targeting physical activity and sedentary
behaviour among older adolescents
S-T. Hynynen, M. M. van Stralen, F. F. Sniehotta, V. Araújo-Soares, W.
Hardeman, M. J. M. Chinapaw, T. Vasankari & N. Hankonen
To cite this article: S-T. Hynynen, M. M. van Stralen, F. F. Sniehotta, V. Araújo-Soares, W.
Hardeman, M. J. M. Chinapaw, T. Vasankari & N. Hankonen (2016) A systematic review of
school-based interventions targeting physical activity and sedentary behaviour among
older adolescents, International Review of Sport and Exercise Psychology, 9:1, 22-44, DOI:
10.1080/1750984X.2015.1081706
To link to this article: http://dx.doi.org/10.1080/1750984X.2015.1081706
© 2015 The Author(s). Published by Taylor &
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A systematic review of school-based interventions targeting
physical activity and sedentary behaviour among older
adolescents
S-T. Hynynen
a
, M. M. van Stralen
b
, F. F. Sniehotta
c
, V. Araújo-Soares
c
, W. Hardeman
d
,
M. J. M. Chinapaw
e
, T. Vasankari
f
and N. Hankonen
a
*
a
Department of Social Research, University of Helsinki, Helsinki, Finland;
b
Department of Health Sciences,
Faculty of Earth and Life Sciences and the EMGO Institute for Health and Care Research, VU University
Amsterdam, Amsterdam, The Netherlands;
c
Institute of Health & Society, Newcastle University, Newcastle
upon Tyne, UK;
d
Behavioural Science Group, Primary Care Unit, University of Cambridge, Cambridge, UK;
e
Department of Public and Occupational Health and the EMGO Institute for Health and Care Research, VU
University Medical Center, Amsterdam, The Netherlands;
f
UKK Institute for Health Promotion Research,
Tampere, Finland
ABSTRACT
Lack of physical activity (PA) and high levels of sedentary behaviour
(SB) have been associated with health problems. This systematic
review evaluates the effectiveness of school-based interventions to
increase PA and decrease SB among 1519-year-old adolescents,
and examines whether intervention characteristics (intervention
length, delivery mode and intervention provider) and intervention
content (i.e. behaviour change techniques, BCTs) are related to
intervention effectiveness. A systematic search of randomised or
cluster randomised controlled trials with outcome measures of PA
and/or SB rendered 10 results. Risk of bias was assessed using the
Cochrane risk of bias tool. Intervention content was coded using
Behaviour Change Technique Taxonomy v1. Seven out of 10
studies reported signicant increases in PA. Effects were generally
small and short-term (Cohensdranged from 0.132 to 0.659). Two
out of four studies that measured SB reported signicant
reductions in SB. Interventions that increased PA included a higher
number of BCTs, specic BCTs (e.g., goal setting, action planning
and self-monitoring), and were delivered by research staff.
Intervention length and mode of delivery were unrelated to
effectiveness. More studies are needed that evaluate long-term
intervention effectiveness and target SBs among older adolescents.
ARTICLE HISTORY
Received 22 November 2014
Accepted 10 July 2015
KEYWORDS
physical activity; sedentary
behaviour; adolescents;
school-based intervention;
behaviour change techniques
Introduction
Ample evidence exists of the profound benets of leading a physically active life. Regular
physical activity (PA) has been associated with a decreased risk of physical and mental
health problems, such as obesity, cardiovascular disease, type II diabetes and depression
© 2015 The Author(s). Published by Taylor & Francis.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License
(http://creativecommons.org/Licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any
medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
CONTACT S-T Hynynen sini.hynynen@kuulas.
*Present address: School of Social Sciences and Humanities, University of Tampere, Finland.
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY, 2015
VOL. 9, NO. 1, 2244
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among children and adolescents (Biddle, Gorely, & Stensel, 2004; Janssen & LeBlanc, 2010;
Penedo & Dahn, 2005). The evidence on the adverse health effects of excessive sedentary
behaviour (SB) in youth is inconsistent to date (Chinapaw, Altenburg, & Brug, 2015; Chi-
napaw, Proper, Brug, van Mechelen, & Singh, 2011). Yet there is an indication that exces-
sive SB is associated with both physical and psychological health problems such as
unfavourable body composition, decreased tness, lowered self-esteem and pro-social
behaviour and decreased academic achievement in school-aged children and youths
(Tremblay et al., 2011a). If non-sedentary lifestyle habits can be initiated in adolescence,
this may have benecial preventive value, as the effects on mortality and morbidity
among adults have already been established (Thorp, Owen, Neuhaus, & Dunstan,
2011; Wilmot et al., 2012). To achieve and maintain good health, children and adoles-
cents are recommended to engage in at least 60 minutes of moderate- to vigorous-
intensity physical activity (MVPA) each day (Janssen & LeBlanc, 2010; Strong et al.,
2005). However, according to the Health Behaviour in School-aged Children study
20092010, only 15% of 15-year-old adolescents met this recommendation globally
(Currie et al., 2012). There are also recommendations for sedentary time although
not as widely agreed upon as for PA. For example, the guidelines of the Canadian
Society for Exercise Physiology (CSEP) for decreasing SB in youth state that the goal
of minimising the time spent sedentary can be achieved by several means: in addition
to limiting recreational screen time, also limiting sedentary transport, extended sitting
time and time spent indoors throughout the day which also may involve time spent
in classrooms (Tremblay et al., 2011b). In Finland recent national recommendations on
the reduction of sedentary time explicitly identify schools as one of the key settings
(Ministry of Social and Health Affairs, 2015). As PA even decreases during adolescence
(Dumith, Gigante, Domingues, & Kohl, 2011) and youths spend a lot of their time
both at home and in school being sedentary (van Stralen et al., 2014; Verloigne et al.,
2012), interventions that aim to promote PA and to reduce SB among adolescents are
urgently needed.
Schools are a promising setting for health promotion interventions aimed at adoles-
cents, since they reach a majority of the target population. In previous studies, school-
based interventions have been found to have signicant effects on adolescentsPA and
SB. However, the effects have been small, short-term and have largely differed between
interventions (Biddle, OConnell, & Braithwaite, 2011; De Meester, van Lenthe, Spittaels,
Lien, & De Bourdaedhuij, 2009; Demetriou & Höner, 2012; Dobbins, De Corby, Robeson,
Husson, & Tirilis, 2009; Lonsdale et al., 2013; Metcalf, Henley, & Wilkin, 2012; van Sluijs,
McMinn, & Grifn, 2007). Also, effects are mostly seen in school-related PA while effects
outside of this context in leisure time and commuting PA are often not observed or
assessed (Kriemler et al., 2011). Furthermore, age might moderate the effectiveness of
school-based interventions. Earlier reviews have tended to either include a broad age
range (e.g., 618-year-olds) or focus on younger age categories (Safron, Cislak, Gaspar, &
Luszczynska, 2011; van Sluijs et al., 2007). To our knowledge, no recent review has
focused solely on interventions targeting older adolescents, and evidence in this age
group is lacking. These previous studies have disregarded the possibility that age
groups differ in developmental stages and thus require different intervention strategies.
Since older adolescents have been a less studied target group, this review focuses on
them exclusively.
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 23
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The heterogeneity in effectiveness of school-based PA interventions (see, e.g., Kriemler
et al., 2011; van Sluijs et al., 2007) may be explained by differences in factors such as length
of the intervention, mode of delivery, provider or content of the intervention. Yet no
studies so far have systematically sought to explain this variability by analysing interven-
tion content (see Abraham & Michie, 2008; Michie et al., 2013). Taxonomies of behaviour
change techniques (BCTs) allow more in-depth analyses of interventions and intervention
strategies (Abraham & Michie, 2008; Michie et al., 2013).
Three previous reviews have identied the BCTs used in interventions targeting
obesity- and weight-related behaviours among children and adolescents (Golley,
Hendrie, Slater, & Corsini, 2011; Hendrie et al., 2012; Martin, Chater, & Lorencatto, 2013).
In community- and school-based interventions to target obesity-related behaviours in
118-year-old children, three BCTs were associated with effectiveness: Providing general
information on behaviour health links,Prompting practice, and Planning for social
support/social changes (Hendrie et al., 2012). In their review on interventions that target
parents to improve childrens weight-related nutrition intake and activity patterns,
Golley et al. (2011) found that effective interventions included: Prompting barrier identi-
cation,Restructuring the home environment,Prompting self-monitoring and Prompting
specic goal setting. In childhood obesity prevention interventions, only Prompting gener-
alisation of target behaviour was shown to be related to intervention effectiveness (Martin
et al., 2013). None of the existing reviews has conducted a BCT analysis of school-based PA
or SB interventions among adolescents aged over 15 years old (e.g., Biddle et al., 2011;
Dobbins et al., 2009; van Sluijs et al., 2007).
More studies have investigated effective BCTs to increase PA among adult populations
(see, e.g., Abraham & Graham-Rowe, 2009; Bird et al., 2013; Michie, Abraham, Whittington,
McAteer, & Gupta, 2009; Williams & French, 2011). These systematic reviews show that
effective PA interventions have usually included BCTs linked with self-regulation, such
as self-monitoring, goal setting and action planning.
There is a lack of evidence about whether the number of BCTs reported as being
present in interventions is related to intervention effectiveness. However, a review of inter-
ventions targeting obesity and weight-related nutrition and PA behaviours in children
both in the home and school/community setting (Hendrie et al., 2012) suggested that
interventions including a higher number of BCTs were associated with better outcomes.
In addition to characterising interventions in terms of component BCTs, existing
reviews of school-based PA interventions fall short of analysing whether intervention out-
comes are inuenced by intervention length, mode of delivery (e.g., oral communication,
written material, video, interactive computer program, self-help, individual face-to-face,
group face-to-face, telephone) or provider of delivery. A systematic review of systematic
reviews and meta-analyses on effects of school-based interventions targeting obesity-
related behaviours showed that more effective interventions generally lasted at least
three months, i.e. a longer duration was reported to be more effective compared to
shorter interventions (Safron et al., 2011). A better understanding of whether the above-
mentioned characteristics are related to intervention effectiveness would enable evi-
dence-based decisions during intervention development.
Our review provides an up-to-date systematic analysis of the effectiveness of school-based
interventions targeting PA and/or SB among older adolescents (aged 1519 years), using an
exploratory narrative review with an analysis of intervention components including BCTs.
24 S-T. HYNYNEN ET AL.
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Review questions
(1) Are school-based interventions to increase PA and/or reduce SB among 15- to 19-year-
olds effective?
(2) Does effectiveness of the interventions vary according to a) the length of the interven-
tion, b) the mode of delivery (e.g., oral communication, written material, video, inter-
active computer program, self-help, individual face-to-face, group face-to-face,
telephone), and c) the provider of the intervention (e.g., teacher, peer, researcher)?
(3) Which BCTs have been used in the interventions and how is intervention content
related to effectiveness?
Methods
The protocol for this systematic review was published in PROSPERO International pro-
spective register of systematic reviews (Hynynen et al., 2013).
Study selection and search strategy
A systematic search was conducted using the following electronic databases of peer-
reviewed journal articles and online research registers: Medline, Cinahl, Embase, PsycINFO,
Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews,
and Cochrane Methodology Register. The search spanned from the year of the databases
inception up to and including February 2013. During the search we imposed no language
restrictions but only articles written in English were included in the review. Individualised
search strategies for the different databases included combinations of key words related
to PA and SB, school, intervention and adolescence (see supplemental data). We used a
modied version of the Cochrane highly sensitive search strategy for identifying random-
ised trials, where the sections on complementary therapies were removed. The reference
lists of studies that met the inclusion criteria as well as other relevant reviews were
scanned. The researchers also sent inquiries about ongoing intervention studies via rel-
evant networks, such as scientic societies. However, no additional studies were identied
through this approach.
Inclusion criteria specied randomised or cluster randomised studies on school-based
interventions that targeted PA and/or SB among 15- to 19-year-old adolescents who are
apparently healthy (for a more detailed description, see Hynynen et al., 2013). Included
studies could also address other health behaviours, but data on these behaviours were
not extracted. Inclusion criteria specied that interventions had to be primarily based in
schools but they might also include home- or community-based components. The
included studies reported either self-reported or objectively measured (e.g., acceler-
ometer) PA or SB or both, presenting a baseline and a post-intervention measurement.
Studies that only targeted individuals at increased health risk (e.g., obese youths) were
excluded. We also excluded studies that measured studentsPA during physical education
(PE) classes only.
This strategy identied 8470 references that were imported into the RefWorks database
(see Figure 1). After excluding duplicates, 5482 references remained. The screening of the
remaining references was conducted in three phases by two researchers (STH and MVS)
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 25
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working independently. Publications were included if eligibility was unclear. In the rst
phase of screening, titles of all references were reviewed. During this phase 4456 refer-
ences were excluded. In the second phase, abstracts of the remaining 1026 articles
were screened and 667 articles excluded. In the third phase, full text papers were obtained
for 359 articles and eligibility reviewed in detail. Any disagreements were resolved by dis-
cussion between the two researchers.
We created a standardised form to extract all relevant details of the trial characteristics
(study design, number of participants, method of randomisation, study setting and
Figure 1. Identication of the included studies.
26 S-T. HYNYNEN ET AL.
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country), sample characteristics (inclusion and exclusion criteria for participants, co-mor-
bidities), details of interventions (mode of delivery, provider, setting, recipient, intensity,
length), participant characteristics, participant attrition, physical activity and sedentary
behaviour outcome measures and possible secondary outcomes. The data extraction
was carried out by one researcher (STH) and veried by a second (MVS or another
researcher).
Assessing risk of bias
The Cochrane risk of bias tool (Higgins et al., 2011) was used for assessing risk of bias in the
included articles, covering the allocation procedures, outcome analyses, reporting and
other possible sources of bias. Two researchers (STH and MC) independently assessed
the quality of all studies that met the inclusion criteria. The following domains were con-
sidered: sequence generation, allocation concealment, blinding of study personnel and
participants, incomplete outcome data, selective outcome reporting, other possible
sources of bias, and when relevant cluster recruitment bias and baseline imbalance
bias. Each paper was carefully assessed for each domain and judgements were made
regarding potential bias, according to three categories: low risk, high risk, or risk
unclear. Inter-rater reliability was calculated (average percentage agreement 74%).
Coding the behaviour change techniques
The BCT coding was conducted by two researchers (STH and MVS) using Michie et al.s
(2013) behaviour change technique taxonomy (BCTT v1). Prior to coding, STH had
attended a BCT training workshop and MVS completed a group tutorial training pro-
gramme guided by phone. BCTs were coded separately for increasing PA and reducing
SB. Both intervention arms and control arms were coded for BCTs. All published materials
(e.g., intervention protocols) of the included trials were used to characterise intervention
content. Prior to extracting BCTs from included intervention studies, the two coders
piloted consistency in their BCT coding by coding three intervention reports that were
not included in the review as they targeted a different age group. All included interven-
tions were then coded independently. Inter-rater reliability was assessed and percent
agreement on BCTs present in the descriptions was high (83.3%). Discrepancies
between both primary coders were discussed and resolved with a third researcher (WH)
who is a member of the BCTT v1 team.
Assessing intervention and BCT effectiveness
For each study, intervention effects (Cohensd) for PA and SB were calculated at the rst
follow-up post-intervention. This was the only outcome measurement point after baseline
that was reported in all included studies. Therefore, we selected this point in time to
compare the effects across studies. For the purpose of calculating effect sizes, we con-
tacted four authors for further numerical data needed. Three responded and provided
the requested data. Half of the studies reported moderate to vigorous physical activity
(MVPA) outcome measures, which were used for the effect size calculations when avail-
able. If the study presented objective measurement of PA, those were used for the
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Table 1. Study characteristics.
Study Country
Study
design
Intervention
and control
groups
Number of
participants
Total
attrition
Sex of
participants
Mean age of
participants
(SD) PA outcomes SB outcomes Assessment
Bayne-Smith et al.
(2004)
US CRT 1 IV
1 CON
442 Not
reported
Only female - Self-reported
PA no. of sessions per week
Not targeted or
reported
Baseline, Post-IV
Gomes de Barros
et al. (2009)
Brazil CRT 1 IV
1 CON
2155 54.1% 55.7%
female
18.4
(SD = 2.3)
Self-reported
no. of days per week
accumulating 60 min of MVPA
Not reported Baseline, Post-IV
Hill, Abraham, and
Wright (2007)
UK CRT 3 IV
1 CON
620 18.9% 51% female 16.97
(SD 1.4)
Self-reported
On average over the last three
weeks, I have exercised
energetically for at least 30
minutes ____ times per week.
Not targeted or
reported
Baseline, Post-IV
Lee, Kuo, Fanaw,
Perng, and Juang
(2012)
Taiwan CRT 1 IV
1 CON
94 3.2% Only female 16.2
(SD 0.4)
Objectively measured PA
(pedometer)
Change in aerobic walking
(steps/day)
Not reported Baseline, Post-IV
Lubans and Sylva
(2006)
UK RCT 1 IV
1 CON
78 Post-IV 0%
Follow-up
2.6%
61.5%
female
16.7
(SD 0.5)
Self-reported
MVPA min/week
Not reported Baseline, Post-, 3-
month follow-up
Mauriello et al.
(2010)
US CRT 1 IV
1 CON
1800 Post-IV
20.6%
Follow-up
34.3%
50.8%
female
- Self-reported PA
In a typical week, how many
days do you do 60 min or more
of physical activity?
Self-reported
limited TV viewing
Baseline, Post-IV,6-
month follow-up,
12-month follow-
up
Neumark-Sztainer
et al. (2010)
US CRT 1 IV
1 CON
356 Post-IV
3.1%
Follow-up
5.6%
Only female - Self-reported MVPA (30-min
blocks/day)
Self-reported
sedentary activity
(30-minute blocks/
day)
Baseline, Post-IV,
9-month follow-up
Schoeld,
Mummery, and
Schoeld (2005)
Australia CRT 2 IV
1 CON
85 Post-IV
20%
Only female 15.8
(SD 0.8)
Objectively measured PA
(pedometer)
4-d step count
Not targeted or
reported
Baseline, Mid-IV,
Post-IV
Singhal, Misra, Shah,
and Gulati (2010)
India CRT 1 IV
1 CON
209 Post-IV
3.8%
40.2%
female
IV 16.04 (SD
0.41)
CON 16.0
(SD 0.5)
Self-reported
PA > 4 days in a week
Self-reported
watching TV (45
h/day)
Baseline, Post-IV
Slootmaker,
Chinapaw, Seidell,
van Mechelen, and
Schuit (2010)
The
Nether-
lands
RCT 1 IV
1 CON
87 Post-IV
21.8%
Follow-up
9.2%
63.2%
female
15.1
(SD not
reported)
Objectively measured MVPA
(accelerometer)
Objectively
measured
sedentary time
Baseline, Post-IV,
8-month follow-up
IV: Short for intervention.
CON: Short for control.
28 S-T. HYNYNEN ET AL.
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effect size calculations; in other cases self-reported outcomes were addressed. When there
was no MVPA outcome reported, we used the closest outcome available (see Table 1). We
classied the interventions into effective vs. non-effective based on the same PA outcome
data that were used in the effect size calculations. Effective trials were dened as those
that reported a signicant difference (p< .05) between intervention and control groups
PA at rst follow-up post-intervention.
We identied which BCTs were present in the effective trials and which BCTs were
present in the non-effective trials. We analysed BCT effectiveness using a method modied
from one used in Martin et al.s(2013) systematic review on childhood obesity prevention
and management interventions. Effective BCTs were dened as those that were present in
a majority (> 50%) of the effective trials but not at all present or present in only one of the
non-effective trials. We also attempted to identify the BCTs unique to interventions that
did not change PA or SB. We illustrated BCT effectiveness by calculating effectiveness
ratiosof the relative weight of BCTs appearing in two or more trials. The effectiveness
ratio was calculated as the ratio of the number of times a BCT was present in an effective
intervention divided by the number of times it was present as a component of all interven-
tions, including the ineffective interventions.
Results
The search provided 5482 records (see Figure 1) out of which 13 articles reporting 10
unique intervention studies were identied for inclusion in the review (Bayne-Smith
et al., 2004; Gomes de Barros et al., 2009; Hill et al., 2007; Lee et al., 2012; Lubans &
Sylva, 2006; Mauriello et al., 2006; Mauriello et al., 2010; Nahas et al., 2009; Neumark-Sztai-
ner et al., 2010; Neumark-Sztainer, Story, Hannan, & Rex, 2003; Schoeld et al., 2005;
Singhal et al., 2010; Slootmaker et al., 2010).
Study characteristics and participants
Two of the included studies were individually randomised controlled trials (Lubans & Sylva,
2006; Slootmaker et al., 2010) and eight were cluster randomised trials (Bayne-Smith et al.,
2004; Gomes de Barros et al., 2009; Hill et al., 2007; Lee et al., 2012; Mauriello et al., 2010;
Neumark-Sztainer et al., 2010; Schoeld et al., 2005; Singhal et al., 2010). The average
sample size was 593 (SD = 757), ranging from 78 to 2155 older adolescents. The non-
weighed mean attrition percentage (where reported) at rst follow-up post intervention
was 16.2% (SD = 16.8%) ranging from 0% to 54.1%. Four interventions were only aimed
at female adolescents (Bayne-Smith et al., 2004; Lee et al., 2012; Neumark-Sztainer et al.,
2010; Schoeld et al., 2005) and six were aimed at both sexes (Gomes de Barros et al.,
2009; Hill et al., 2007; Mauriello et al., 2010; Singhal et al., 2010; Slootmaker et al., 2010).
(For more detail on study characteristics, see Table 1.)
Intervention and comparison arms
The 10 studies compared a total of 13 different intervention groups against 10 control
groups. Eight studies compared one intervention group against one control group
(Bayne-Smith et al., 2004; Gomes de Barros et al., 2009; Lee et al., 2012; Lubans & Sylva,
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2006; Mauriello et al., 2010; Neumark-Sztainer et al., 2010; Singhal et al., 2010; Slootmaker
et al., 2010). These interventions included a web-based intervention offering personalised
feedback on readiness to change (Mauriello et al., 2010), a web-based intervention
coupled with the use of accelerometers (Slootmaker et al., 2010), an intervention using
pedometers to encourage walking (Lee et al., 2012), an intervention targeting the
school environment and offering students PA opportunities (Gomes de Barros et al.,
2009), health and exercise programmes (Lubans & Sylva, 2006), a heart health programme
focusing on vigorous exercise and other health behaviours such as diet, smoking and
stress (Bayne-Smith et al., 2004), and an all-girls PE course targeting self-empowerment,
nutrition and including one-on-one motivational interviewing sessions (Neumark-Sztainer
et al., 2010) (for further information see Table 2). One study compared two intervention
groups against a control group (Schoeld et al., 2005). In this study both intervention
groups were offered a 12-week PA self-monitoring and educative programme. One inter-
vention group was provided with pedometers and set daily step count targets whereas the
other group set daily time-based goals for PA involvement (Schoeld et al., 2005). A nal
study compared three types of theory-based persuasive leaets to increase PA
(leaet alone, leaet plus a motivational quiz, and leaet plus implementation intention
prompt) against a no-leaet control group (Hill et al., 2007). Control group treatment dif-
fered widely in the 10 trials. Whereas some control groups received a cognitive word
search task (Hill et al., 2007), or a brief leaet with general PA recommendations (Sloot-
maker et al., 2010), others received the schools standard PE programme (Gomes de
Barros et al., 2009). Neumark-Sztainer et al. (2010) described also providing the control
group with an all-girls PE class. Overall, control group interventions were insufciently
described in the studies to enable coding of BCTs.
Risk of bias
All studies except for one (Slootmaker et al., 2010) were judged to be at high risk of bias in
at least one domain (see Table 3). However, the study by Slootmaker et al. (2010) also had
domains of unclear risk of bias. Sequence generation was inadequately described in eight
out of 10 study reports. None of the studies reported proper blinding of participants to
study group allocation.
Outcomes
Five studies targeted only PA or PA and SB outcomes (Hill et al., 2007; Lee et al., 2012;
Lubans & Sylva, 2006; Schoeld et al., 2005; Slootmaker et al., 2010). The ve other
studies targeted other outcomes as well, such as heart health knowledge and dietary
behaviours (Bayne-Smith et al., 2004; Gomes de Barros et al., 2009; Mauriello et al.,
2010; Neumark-Sztainer et al., 2010; Singhal et al., 2010). Five studies assessed outcome
measures only at baseline and at the end of the intervention period (Bayne-Smith et al.,
2004; Gomes de Barros et al., 2009; Lee et al., 2012; Schoeld et al., 2005; Singhal et al.,
2010). Hill et al. (2007) assessed outcomes three weeks post-intervention. Three studies
assessed outcomes both post-intervention and a few months post-intervention (Lubans
& Sylva, 2006; Neumark-Sztainer et al., 2010; Slootmaker et al., 2010). Mauriello et al.
30 S-T. HYNYNEN ET AL.
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(2010) reported post-intervention measurements and further follow-ups at 6 and 12
months post-intervention.
All 10 studies reported PA outcomes and four studies reported SB outcomes as well
(Mauriello et al., 2010; Neumark-Sztainer et al., 2010; Singhal et al., 2010; Slootmaker
et al., 2010). Three other studies mentioned the assessment of SB-related outcomes, but
did not report any data (Gomes de Barros et al., 2009; Lee et al., 2012; Lubans & Sylva,
2006). Out of the 10 studies only three used objective PA measurement: two used ped-
ometers (Lee et al., 2012; Schoeld et al., 2005) and one used accelerometers (Slootmaker
et al., 2010). Seven out of 10 studies relied exclusively on self-report methods to measure
PA. Only one out of four studies that measured SB used accelerometry (Slootmaker et al.,
2010). The remaining studies used proxy measures of TV viewing (Mauriello et al., 2010); TV
viewing, playing board games and attending tuition classes (Singhal et al., 2010); and
blocks of sedentary activity using the Self-reported Total Physical Activity (3-DPAR) ques-
tionnaire (Neumark-Sztainer et al., 2010).
Intervention effects on physical activity and sedentary behaviours
Seven studies showed signicant differences in PA between intervention and control
groups post-intervention (Gomes de Barros et al., 2009; Hill et al., 2007; Lee et al., 2012;
Lubans & Sylva, 2006; Mauriello et al., 2010; Schoeld et al., 2005; Slootmaker et al.,
2010). The effect sizes (Cohensd) post-intervention ranged from small to medium
(0.1320.659). Three studies did not nd signicant between-group differences (Bayne-
Smith et al., 2004; Neumark-Sztainer et al., 2010; Singhal et al., 2010). None of the four
studies (Lubans & Sylva, 2006; Mauriello et al., 2010; Neumark-Sztainer et al., 2010; Sloot-
maker et al., 2010) with follow-ups beyond one month post-intervention reported signi-
cant differences between groups, although three of the four studies (Lubans & Sylva, 2006;
Mauriello et al., 2010; Slootmaker et al., 2010) observed signicant effects post-
intervention.
Out of the four studies that measured SB, one found signicant differences between
intervention and control groups in self-reported sedentary activity over a nine-month
post-baseline follow-up (Neumark-Sztainer et al., 2010). Slootmaker et al. (2010) reported
a signicant difference between intervention and control groups in objectively measured
sedentary time at eight months follow-up. The other two studies showed no signicant
differences between groups in SB measured by time spent viewing television (Mauriello
et al., 2010; Singhal et al., 2010). Because of the lack of studies that focused solely on
SB, analysis of intervention characteristics and BCTs related to effectiveness in this
review will focus on PA only.
Intervention characteristics
Table 2 describes intervention characteristics. Five of seven interventions that increased
PA targeted PA or PA and SB only (Hill et al., 2007; Lee et al., 2012; Lubans & Sylva,
2006; Schoeld et al., 2005; Slootmaker et al., 2010), whereas two targeted multiple beha-
viours related to energy balance, including dietary behaviour (Gomes de Barros et al., 2009;
Mauriello et al., 2010). All three interventions that did not increase PA targeted multiple
behaviours: two targeted obesity-related behaviours (Neumark-Sztainer et al., 2010;
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 31
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Table 2. Intervention characteristics.
Study
Cohens
d
Mean values (SD) on which Cohens
dwas calculated
Risk of bias
(number of
items)
Intervention
targets
Intervention
length Intervention delivery mode Intervention provider
Lubans and Sylva
(2006)
0.659 MVPA min/week
IV: 250.5 (113.4)
CON: 172.5 (123.3)
High risk: 3
Unclear risk: 2
Low risk: 1
N/A: 2
Physical
activity
10 weeks Face-to-face groups, self-led exercise 1 member of the research team
Hill et al. (2007) LII:0.586*
L: 0.484
LQ:0.384
Exercise times/wk:
LII: 3.17 (2.0)
L: 2.96 (1.9)
LQ: 3.46 (2.3)
CON: 2.52 (1.80)
High risk: 2
Unclear risk: 0
Low risk: 6
Physical
activity
1 session Leaets, written material Research assistant
Schoeld et al.
(2005)
S:
0.502**
T: 0.241
High risk: 3
Unclear risk: 2
Low risk: 1
Physical
activity
12 weeks Face-to-face small groups, written
materials e.g. log- & textbooks,
pedometers
Research staff (principal
researcher or assistant)
Lee et al. (2012) 0.454 Aerobic steps/day
IV: 836 (832.03)
CON: 515 (554.19)
High risk: 1
Unclear risk: 3
Low risk: 4
Physical
activity
12 weeks Face-to-face group and individual
discussions, pedometers
1 researcher with public health
nursing background
Gomes de Barros
et al. (2009)
0.333 No. of days/week accumulating 60
min of MVPA IV: 3.3 (2.1) CON: 2.6
(2.1)
High risk: 1
Unclear risk: 3
Low risk: 4
Multiple
behaviours
9 months Face-to-face groups, written materials Trained school staff
Slootmaker et al.
(2010)
0.174 High risk: 0
Unclear risk: 2
Low risk: 4
N/A: 0
Physical
activity
12 weeks IIndividualised Internet-based
programme, accelerometers
Intervention research group
Mauriello et al.
(2010)
0.132 High risk: 5
Unclear risk: 1
Low risk: 2
Multiple
behaviours
8 weeks Interactive computer program Research assistant
Neumark-Sztainer
et al. (2010)
Not sign. High risk: 2
Unclear risk: 4
Low risk: 2
Multiple
behaviours
16 weeks Face-to-face groups & individual
meetings, textbooks and postcards
Trained PE teachers,
Community guest instructors,
Research staff
Singhal et al.
(2010)
Not sign. High risk: 4
Unclear risk: 2
Low risk: 2
Multiple
behaviours
24 weeks Face-to-face groups & individual
meetings
Trained nutritionist, unclear
Bayne-Smith et al.
(2004)
Not sign. High risk: 5
Unclear risk: 3
Low risk: 0
Multiple
behaviours
12 weeks Face-to-face groups, written materials,
homework assignments
Trained PE teachers
*LII: Leaet & implementation intention prompt, L: Leaet alone, LQ: Leaet & a motivational quiz.
**S: Step-based goals condition, T: Time-based goals condition.
IV: Short for Intervention Group.
CON: Short for Control Group.
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Table 3. Risk of bias summary.
Risk of bias
summary
Adequate
sequence
generation
Allocation
concealment
Blinding
(Subjective
outcomes)
Incomplete outcome
data addressed
Free of selective
outcome reporting
Free of other
sources of bias
Free of cluster
recruitment bias
Free of baseline
imbalance bias
Lubans and Sylva
(2006)
unclear unclear high low high high N/A N/A
Hill et al. (2007) low low high low low high low low
Schoeld et al.
(2005)
unclear unclear high high low high N/A N/A
Lee et al. (2012) unclear unclear high low low unclear low low
Gomes de Barros
et al. (2009)
unclear unclear high low unclear high low low
Slootmaker et al.
(2010)
low low unclear low low unclear N/A N/A
Mauriello et al.
(2010)
unclear high high low low high high high
Neumark-Sztainer
et al. (2010)
unclear unclear high unclear low high unclear low
Singhal et al.
(2010)
unclear unclear high low low high high high
Bayne-Smith et al.
(2004)
unclear high high unclear unclear high high high
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Singhal et al., 2010) and one targeted heart health knowledge and behaviours (Bayne-
Smith et al., 2004). To summarise, it appears that effective interventions focus on PA or
PA and SB only.
Length of intervention
Intervention length ranged from one intervention session (Hill et al., 2007) to nine months
(Gomes de Barros et al., 2009). The median length of intervention was 12 weeks. Interven-
tion length appeared unrelated to intervention effectiveness.
Mode of intervention delivery
Two interventions were delivered via an interactive, individualised computer program
(Mauriello et al., 2010; Slootmaker et al., 2010), and one solely via leaets (Hill et al.,
2007). The remaining seven interventions were delivered face-to-face in groups (Bayne-
Smith et al., 2004; Gomes de Barros et al., 2009; Lee et al., 2012; Lubans & Sylva, 2006;
Neumark-Sztainer et al., 2010; Schoeld et al., 2005; Singhal et al., 2010), some including
individual meetings with adolescents (Lee et al., 2012; Neumark-Sztainer et al., 2010;
Singhal et al., 2010). All of the interventions delivered face-to-face also included written
materials, such as textbooks, logbooks, postcards and homework assignments. Two inter-
ventions used pedometers (Lee et al., 2012; Schoeld et al., 2005) and one study used
accelerometers (Slootmaker et al., 2010) as an intervention strategy. There appeared to
be no systematic differences in delivery mode between effective versus non-effective
interventions.
Intervention provider
Two out of 10 interventions were delivered by trained school staff and PE teachers (Bayne-
Smith et al., 2004; Gomes de Barros et al., 2009) and seven by researchers (Hill et al., 2007;
Lee et al., 2012; Lubans & Sylva, 2006; Mauriello et al., 2010; Schoeld et al., 2005; Singhal
et al., 2010; Slootmaker et al., 2010). One study utilised trained PE teachers, community
guests and intervention staff for programme delivery (Neumark-Sztainer et al., 2010). Six
of the seven effective interventions were delivered by researchers (Hill et al., 2007; Lee
et al., 2012; Lubans & Sylva, 2006; Mauriello et al., 2010; Schoeld et al., 2005; Slootmaker
et al., 2010). Of the three ineffective interventions, one was delivered by school staff only
(Bayne-Smith et al., 2004), the second by trained school staff, community guest instructors
and research staff (Neumark-Sztainer et al., 2010) and the third was delivered by a trained
nutritionist, but details were lacking about potential other providers (Singhal et al., 2010).
To summarise, most of the effective interventions were delivered by researchers rather
than school staff.
Intervention content: BCTs
Table 4 presents BCTs identied in more than one of the included studies. Full details on all
of the identied BCTs are available from the authors. Both coders agreed that 57 out of the
93 BCTs in the BCTT v1 were not present in any intervention description. For the remaining
36 BCTs inter-rater reliability was good for 28 BCTs (percentage agreement ranging from
75% to 100%) and sub-optimal (< 75%) for the remaining eight, due to their infrequent
inclusion in the descriptions. The coders were unable to conduct proper analysis of the
BCTs used in control groups due to insufcient reporting in the research articles.
34 S-T. HYNYNEN ET AL.
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Table 4. Behaviour Change Techniques present in interventions.
Lubans and
Sylva (2006)
Hill et al.
(2007)
Schoeld
et al. (2005)
Lee et al.
(2012)
Gomes de
Barros et al.
(2009)
Slootmaker
et al. (2010)
Mauriello
et al. (2010)
Singhal
et al.
(2010)
Neumark-
Sztainer et al.
(2010)
Bayne-
Smith et al.
(2004)
BCT
frequency
Cohensd0.659 LII:0.586
L: 0.484
LQ:0.384
S:0.502
T: 0.241
0.454 0.333 0.174 0.132 non.sign. non.sign. non.sign.
Instruction on how to
perform a behaviour
XX XXX X X X X9
Goal setting (behaviour) X X X X X X 6
Demonstration of the
behaviour
XX XX X X6
Action planning X X X X X 5
Behavioural practice/
rehearsal
XXXXX5
Social support
(unspecied)
XXX XX 5
Information about social
and environmental
consequences
XX XX X 5
Graded tasks X X X X 4
Feedback on behaviour X X X X 4
Self-monitoring of
behaviour
XXX X 4
Problem solving X X X X 4
Social comparison X X X 3
Review behaviour goals X X X 3
Discrepancy between
current behaviour and
goal
XX X 3
Restructuring the physical
environment
XX X3
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An average of 10.5 (range = 520) BCTs were included in effective interventions, and an
average of four BCTs (range = 36) in ineffective interventions. BCTs unique to effective
interventions were Information about social and environmental consequences, Graded
tasks,Self-monitoring of behaviour,Feedback on behaviour,Problem solving,Goal setting
(behaviour),Action planning and Social support (unspecied).Behavioural practice was
present in all three ineffective trials but only in two out of seven effective interventions.
Instruction on how to perform a behaviour and Demonstration of the behaviour were fre-
quently present in both effective and non-effective interventions. Figure 2 describes the
ratio of effectiveness for BCTs identied two or more times in studies included in this
review.
Discussion
To our knowledge, this is the rst systematic review to investigate school-based interven-
tions targeting PA and SB among 1519-year-old adolescents, characterising intervention
content using the BCT Taxonomy v1, and linking intervention characteristics to interven-
tion effectiveness. In total, 10 trials met the inclusion criteria and seven of these increased
PA in the short term, but effects were not sustained at longer follow-ups. The trials with
signicant effects on PA focused on PA or PA and SB only and tended to use researchers
as providers. Effectiveness was unrelated to length of intervention or mode of delivery.
Effective interventions, and especially those with an effect size ranging from medium to
Figure 2. The ratio of effectiveness for Behaviour Change Techniques identied in two or more trials
(the BCTs are ordered by frequency in the trials, with the most frequently identied BCTs on the left).
36 S-T. HYNYNEN ET AL.
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large, reported using more BCTs than the non-effective interventions, and specically
eight BCTs: Information about social and environmental consequences,Graded tasks,Self-
monitoring of behaviour,Feedback on behaviour,Problem solving,Goal setting (behaviour),
Action planning and Social support. Out of the four studies that measured SB, only two had
signicant effects on the behaviour. No studies were found that focused solely on SB. Due
to this lack of evidence, it is difcult to draw conclusions on what intervention elements or
BCTs were related to effectiveness in regards to SB.
Our review suggests that interventions targeting multiple health behaviours are less
effective in promoting PA among older adolescents than ones focusing solely on PA or
PA and SB, which is also supported by earlier evidence (Crutzen et al., 2010). Previous
reviews have suggested that when appropriately trained, a wide range of providers can
deliver effective health behaviour interventions (Greaves et al., 2011; Peters, Kok, Ten
Dam, Buijs, & Paulussen, 2009). On the contrary, we found that interventions delivered
by research staff were more effective than those delivered by school staff or other provi-
ders. This nding resembles the basic difference between efcacy and effectiveness trials,
and may be more a matter of delity of delivery or training rather than a matter of the
person providing the intervention. While other reviews have shown that longer duration of
school-based PA interventions was associated with effectiveness (Dobbins et al., 2009;
Safron et al., 2011), we did not nd a relationship between intervention length and
short-term effectiveness. It is possible that the relationship between intervention length
and PA outcomes was inuenced by other intervention characteristics not analysed in
our review such as intervention intensity: short but very intensive interventions may be
more effective than longer interventions with less contact. Finally, in line with previous evi-
dence (Greaves et al., 2011), there was no clear association between mode of intervention
delivery and effectiveness.
In line with some (Avery, Flynn, van Wersch, Sniehotta, & Trenell, 2012; Hendrie et al.,
2012) and in contrast to other reviews (Abraham & Graham Rowe, 2009; Dombrowski
et al., 2013), we found that effective PA interventions included more BCTs than non-effec-
tive interventions. This may be either a matter of non-effective interventions actually using
fewer techniques to change behaviour, or of not reporting what was done, indicating less
precision in both planning and reporting the intervention. The specic BCTs identied to
be related with intervention effectiveness resonate with the ndings of previous reviews
with adult populations (Avery et al., 2012; Michie et al., 2009; Williams & French, 2011),
where BCTs related to self-regulation have been shown to be effective in changing PA.
Based on our review, this applies also among older adolescents: Goal setting and Action
planning were techniques emphasised in effective trials, and complementing BCTs such
as Self-monitoring of behaviour,Feedback on behaviour and Problem solving were unique
to effective trials.
In their review on obesity prevention interventions for children, Hendrie et al. (2012)
found that providing information on behaviourhealth links was related to intervention
effectiveness. Quite similarly, we found Information about social and environmental conse-
quences to be a technique uniquely present in the effective trials. What should be noted is
that this BCT is coded whenever the information provided is unspecied in the interven-
tion description (Michie et al., 2013). Therefore it is possible that the information provided
in the interventions was not actually about social and environmental consequences, but
rather about health consequences or emotional consequences, or a combination of these.
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Interestingly, Behavioural practice/rehearsal was a technique present mainly in non-
effective interventions. In a previous review of PA interventions among obese adults
(Olander et al., 2013), quite to the contrary, Prompting practice
1
was related to largest
effects for PA. It is possible that prompting behavioural practice outside of intervention
sessions is related to effectiveness whereas practice within the sessions is a typical
element of non-effective interventions. This is supported by our nding that setting
Graded tasks was a BCT present uniquely in effective interventions.
We found little evidence of intervention techniques focusing on the environment level
of behaviour change, such as Restructuring the physical environment. Neither have previous
reviews on PA interventions (see, e.g., Greaves et al., 2011; Michie et al., 2009) shown these
techniques to be related to effectiveness. Restructuring the physical environment was
present in only three interventions, two of which were effective and one non-effective.
The lack of environment-level techniques may be a matter of nancial resources. Initiating
major changes in the schools physical environment without previous evidence of it actu-
ally being effective in supporting and increasing studentsPA might be too risky and
costly. Several distinct environmental changes, such as providing opportunities for PA
by direct monetary investments in schoolsPA equipment, offering students free opportu-
nities for structured PA and organising collective supervised PA events, were heavily
emphasised in the intervention by Gomes de Barros et al. (2009). However, in the BCT Tax-
onomy v1 all of these different actions are coded under one technique: Restructuring the
physical environment. We recommend that this technique is unpacked in more detail in
future developments of the taxonomy, so that studies can investigate the relative effec-
tiveness of the above approaches.
Out of the four studies that measured sedentary behaviour, only two signicantly
decreased SB. Based on only two studies it is difcult to draw reliable conclusions on
what elements were related to effectiveness. Notably, none of the trials measuring SB
treated it as a separate behaviour, but rather as an indicator of insufcient PA levels. SB
was measured objectively in only one of the studies (Slootmaker et al., 2010). The others
relied on self-reported SB often indicated by time spent on the computer, viewing television
or playing board games. The studies provided no descriptions of intervention strategies
aimed specically at changing SB, which made it impossible to identify the BCTs effective
in reducing SB, and make a distinction with PA. The BCTs and alterations in the school
context that may need to occur in order to decrease adolescentsSB may be quite different
from the strategies needed to enhance PA. Ultimately, an intervention focusing on PA may
not affect SB (e.g., if the focus of the intervention is on increasing the intensity of the PA).
Conversely, an SB intervention may not affect health-enhancing MVPA if adolescents are
encouraged to substitute sitting with standing or light-intensity PA. It is evident that
more studies are needed that target intervention strategies to specically decrease SB.
Furthermore, in order to reliably identify the BCTs associated with PA and SB interven-
tion effectiveness, the BCTs used in control groups, i.e. standard care, should be described
in intervention reports and coded. Especially when the intervention is delivered during the
PE class, it is difcult to draw conclusions on effective BCTs without knowing which BCTs
are also part of standard care. Control group treatment differed widely in the 10 trials and
was altogether insufciently described in the studies. Neumark-Sztainer et al. (2010)
described providing the control group with an all-girls PE class with mostly inactive par-
ticipants. It is possible that this alone is quite a powerful intervention, deviating from
38 S-T. HYNYNEN ET AL.
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the standard mixed-gender PE, and may explain the lack of statistically signicant differ-
ences in PA between intervention and control groups post-intervention. We recommend
that future studies report BCTs used in both intervention and control groups.
It is notable that four out of 10 interventions targeted females exclusively. Girls are
indeed more in need of PA-promoting interventions, as they engage on average in less
MVPA than boys (Sallis, Prochaska, & Taylor, 2000). However, boys generally spend more
time on screen-based behaviours. Previous studies have shown that school-based PA
interventions work better for girls than boys (Yildirim et al., 2011), which may be in part
due to girlslow baseline MVPA levels.
The limitations of our review are inuenced by the number and quality of the studies
included. In general, the methodological quality of the included studies was weak, with rela-
tively small sample sizes and a high risk of bias. Only three studies reported objective
measurement of PA (accelerometry, pedometers) and one study (Slootmaker et al., 2010)
objectively assessed SB, posing a major reliability problem. Out of the seven studies that
we classied as effective in increasing PA, four relied solely on self-report measures. Since
self-report can be inuenced by recall bias and social desirability bias, these ndings
need to be conrmed by objective measures. Another major limitation in this area, as
noted in earlier systematic reviews as well (e.g., van Sluijs et al., 2007), is the lack of long-
term follow-ups and, consequently, a lack of evidence regarding long-term effectiveness.
Thirdly, delivering interventions only to volunteer participants expressing heightened inter-
est in the programme (Lubans & Sylva, 2006; Mauriello et al., 2010) versus, for example,
recruiting all students from a given classroom possesses a threat of positively biased
results. It is quite evident that individuals who seek to participate in a PA intervention are
more motivated to increase their level of PA than their age cohort in general. Also,
because self-reported PA was the main outcome measure in most studies, it is possible
that failure to blind participants to allocation might have resulted in differential effects of
social desirability bias between intervention and control group participants. There was an
apparent lack of quality in reporting the studies. Some of the studies were so supercially
described that it was difcult to draw conclusions on intervention elements related to effec-
tiveness; from some it was difcult to even tell who delivered the intervention. However, the
inter-rater reliability of the coders was adequate. Finally, due to the small number of
included studies and the heterogeneity of the outcome measures, we were not able to
conduct a meta-analysis. Hence, it should be taken into account that the conclusions on
associations and relationships between intervention components and intervention effective-
ness presented in this review are based on a small number of studies and descriptive rather
than quantitative analysis. The scarcity of reported studies in this age group and the fact that
only three non-effective studies were found in the literature search also raises a serious ques-
tion of possible risk of publication bias in this research eld. Due to these factors, the con-
clusions drawn from this review regarding BCT effectiveness are tentative.
This study has several implications for future research and practice. We recommend that
future intervention studies use objective measures of PA and SB alongside self-report
measures and use large enough sample sizes to allow for multi-level analyses to account
for clustering within classes and schools. Furthermore, future trials should include long-
term follow-ups and more precise descriptions of intervention content in terms of BCTs.
The advantages of school-based PA and SB interventions include a captive audience
and wide reach of the target group. As there is a marked drop in PA levels during
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adolescence, and a high level of SB, this age group is an especially important target for
public health efforts. Our review may help efforts to develop more effective interventions
in this under-researched age group, having identied factors associated with effectiveness
and crucial gaps in research that merit attention in future studies. First, for future interven-
tion developers, we would point out the major lack of school-based intervention studies to
decrease SB in this age group. Future studies ought to acknowledge that PA and SB are
different target behaviours that require different intervention strategies. In our review,
we identied promising BCTs that seem to be effective at least in the short term in
school-based interventions to promote PA among older adolescents. It should be noted
that interventions should not be deemed effective based on statistical signicance only,
but one should also examine whether the changes have public health or clinical signi-
cance. Few of the original studies made an explicit judgement, or assessed cost-effective-
ness. Since our review found that interventions delivered via research staff were more
effective than those delivered by school staff or other providers, we suggest that in
future research careful process evaluation (Moore et al., 2015) is conducted to examine
acceptability and delity of the intervention and to understand whether public health
interventions can be rolled out successfully without researcher delivery. In addition, inter-
vention developers should carefully select BCTs and other elements that would increase
maintenance of PA over the long term, as so far no study has been able to demonstrate
that their school-based intervention have long-lasting effects on older adolescentsPA.
Since our review shows a lack of evidence in this target audience and behaviour, we
suggest that developers look into other areas of behavioural science research where
BCTs aimed at maintaining behaviour are being tested.
In conclusion, this review found that there is limited evidence on how to best promote
PA and reduce SB among older adolescents in school-based interventions in the long term.
The method we used to analyse the content of interventions was helpful in identifying
effective elements, which will benet future intervention development work, ultimately
improving adolescent activity behaviours.
Disclosure statement
No potential conict of interest was reported by the authors.
Funding
The rst author S-T. Hynynen was supported by the Ministry of Education and Culture
[grant number 34/626/2012], and the Ministry of Social Affairs and Health [grant
number: 201310238]; Finland. F. F. Sniehotta is funded by Fuse, the UK Clinical Research
Collaboration Centre of Excellence for Translational Research in Public Health. Funding
for Fuse from the British Heart Foundation, Cancer Research UK, Economic and Social
Research Council, Medical Research Council, and the National Institute for Health Research,
under the auspices of the UK Clinical Research Collaboration.
Supplemental data
Supplemental data for this article can be accessed 10.1080/1750984X.2015.1081706.
40 S-T. HYNYNEN ET AL.
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Note
1. Prompting practice is a BCT in the CALO-RE taxonomy; a rened taxonomy of behaviour change
techniques to help people change their physical activity and healthy eating behaviour (see
Michie et al. 2011)
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... Of the nine identified reviews, three focused on adolescents only (110,112,113), and the remaining six included both adolescents and younger children (105)(106)(107)(108)(109)111). Of the nine reviews, seven concluded that school physical activity interventions have a small positive effect on physical activity (105,106,(108)(109)(110)113). ...
... Of the nine identified reviews, three focused on adolescents only (110,112,113), and the remaining six included both adolescents and younger children (105)(106)(107)(108)(109)111). Of the nine reviews, seven concluded that school physical activity interventions have a small positive effect on physical activity (105,106,(108)(109)(110)113). The remaining two reviews found null effects for physical activity programs (111,112). ...
... The remaining three reviews focused on adolescents only (110,112,113). Adolescents may respond differently to younger children in school physical activity programs, as adolescents are more independent and mature, and are typically less active than younger children (84)(85)(86)(87)(88). Physical activity interventions in secondary schools (110)(111)(112)(113) have typically been less effective than those in primary schools (105)(106)(107)(108)(109). Of the three reviews involving adolescent-focused interventions only, two reviews suggested that there may be a beneficial effect of school-based physical activity promotion programs based on narrative synthesis and vote counting (110,113), with the third review reporting null effects based on meta-analyses (112). ...
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... Otros estudios han revelado que las pequeñas mejoras provocadas por algunos programas de actividad física escolares disminuyen o se diluyen con el tiempo, lo que sugiere que no resultan tampoco eficaces a largo plazo (Nguyen et at., 2016;Sims, Scarborough, y Foster, 2015). Por tanto, parece necesario identificar algunas de las causas que pueden justificar la falta de eficacia de los programas de actividad física, para poder aportar sugerencias y/o soluciones (Hynynen et al., 2016;Love et al., 2019;Sevil-Serrano, García-González, Abós, Aibar, y Simón-Montañés, 2020). ...
... Por otro lado, en la revisión de diferentes estudios realizada por Hynynen et al. (2016), se apreció que las intervenciones realizadas por los equipos de investigación son más efectivas que las realizadas por el propio profesorado. Este hecho puede deberse a que el equipo investigador, a pesar de no poder contar con una formación didáctica más ligada al ámbito educativo, posee un mayor conocimiento sobre la actividad física (beneficios, riesgo, intensidad, etc.) y la manera de promoverla desde el ámbito escolar. ...
... Por otro lado, varios estudios de investigación señalaron que la falta de eficacia de los programas de intervención escolares de promoción de actividad física puede deberse a que están integrados por pocas áreas de actuación (ej., únicamente la Educación Física), tienen poca duración y/o intensidad (se intervienen durante periodos cortos de tiempo o se realizan pocas acciones), no se involucran todos los agentes de la comunidad educativa y social (ej., profesores, tutores, familias, equipo directivo, etc.) y no tienen un marco teórico de referencia para abordar la intervención (ej., modelo socioecológico) (Hynynen et al., 2016;Sims et al., 2015). ...
... However, the effects were minor, transient, and most varied among interventions. Furthermore, effects of PA, SA, and diet together are not often observed 16,17 . To our knowledge, no contemporary review has focussed exclusively on PA, SA, and nutrition intervention and follow-up at two levels 3 months to 1 year and 12 months to 24 months effect on BMI. ...
... Several reviews reported multiple interventions, various study designs, socio-economic backgrounds, and various outcome measures which also showed similar result 28,29 . The effectiveness of school-based PA interventions was, however, shown to be correlated with longer intervention durations in previous reviews 17,30 . The review bias score was found very strong on the randomization process, negative effects on the absence of allocation of concealment /blinding and low withdrawal and dropout rates, and a moderate effect on intervention integrity. ...
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Background: High body mass index is a common well-known issue among adolescents, its related morbid-ity track to adulthood life and decrease life expectancy. The review aims to derive a consensus on school-based intervention on body mass index. Objective: This review evaluates the effect of school-based inter-ventions in reducing or preventing high body mass index for adolescents. Method: A literature search was performed in six electronic databases: Pubmed, Science Direct index, Sci-Hub, HINARI, and Google Scholar to identify published studies between January 2010 and December 2020. Only randomized controlled studies evaluated the effect of physical activity and/or physical education and nutritional education and/or dietary behavior, sedentary behavior outcome reporting on body mass index among adolescents were included. The Standard Cochrane tool was used to assess the risk of bias for indi-vidual studies. An evaluation of the effects of included interventions on body mass index was done using a random effects model. Results: There were 6 trials included. 2503 adolescent partakers met the inclusion criteria. Meta-analysis showed there is a significant difference between length of intervention between 3 to 12 months were MD -0.44 kg [95% CI: 1.06, 0.18], p-value = 0.04, with evidence of substantial study between heterogeneity (I2 = 61%). Discussion: Intervention less than three to twelve months more effective with multiple school-based inter-ventions among adolescents. Numerous studies are needed for evaluation to determine long-term interven-tion effectiveness targeted on adolescents.
... In our study, these two strategies were both related to physical activity, thereby highlighting their independent predictive value. Further, we consider that developing a "selfregulation toolbox" among adolescents may represent an important target for future interventions aiming to promote physical activity among youth (Hynynen et al., 2016). Smartphone apps appear as a promising tool (Petersen et al., 2020), assuming that adolescents are taught on how to use these technological devices in order to convert their intention to be active into action. ...
... The effectiveness of school-based PA interventions are largely mixed [5], however there is some evidence that school-based interventions incorporating goal setting, action planning, feedback and self-monitoring can increase children's/adolescent's PA [6]. Wearable activity trackers (wearables) include features that correspond with these behaviour change techniques [7]. ...
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Background: The school environment is an ideal setting for promoting physical activity (PA). Wearable activity trackers (wearables) have previously been implemented, in research, as intervention tools within the school-environment. However, the large-scale use and acceptance of wearables, in schools, is unknown. Methods: This study distributed a cross-sectional survey to school staff to investigate the prevalence of child and adolescent wearable use in schools, including when and how they are used, and school staff's willingness to use them in the future (as implemented by school staff). This survey consisted of between 13 and 22 items, including closed-ended and open-ended questions. Closed-ended responses were displayed descriptively (wearable prevalence and characteristics), and open-ended qualitative responses were categorised using descriptive content analysis (how wearables are used). Results: 1087 school staff provided valid responses. Of those, 896 (82.4%) had never used a wearable as a teaching or support tool for their students, and 120 (11%) currently used- and 71 (6.5%) had previously used- a wearable as a teaching or support tool for their students. When wearables were used, school staff implemented their use regularly and during physical education lessons or throughout the entire school day. Wearables were used to monitor or increase student's PA levels, or for student and staff educational purposes (e.g., academic learning, movement breaks). Most school staff were willing to use a wearable as a teaching or support tool to promote student's PA, and/or learning about PA, in the future. Conclusions: This study is the first study to explore the widescale use and acceptance of children and adolescents using wearables in the school-setting. Findings may inform the development of future school-based interventions and public health initiatives for physical activity promotion, using wearables.
... Unfortunately, few findings have been reported specifically about school-based exercise programs in the last two decades promoting MF, to the authors' knowledge and as of the time this review is written. On the other hand, some studies concluded that no significant development is observed when the variables are obesity, sedentary behavior, and physical activity [14,15]. Moreover, most studies have mainly focused on older children, and thus there is limited research investigating schoolbased exercise programs in children aged 6 to 10. ...
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Musculoskeletal fitness (MF) is a multidimensional construct that combines muscle strength, endurance, and power to allow for the performance of tasks against one’s own body weight or an external resistance. The aim of this study was to determine the effects of school-based programs on promoting MF in children aged 6 to 10. PubMed and Web of Science databases were used as searching tools. A total of 16 studies were included in a systematic review with primary school-based program interventions measuring at least one variable related to musculoskeletal fitness. Parameters for measuring explosive power, especially standing broad jump (SBJ), have a large potential for development throughout school-based programs. Long-lasting interventions did not necessarily improve MF; however, there were shorter interventions that caused the improvement in a larger number of parameters. Our findings imply that increased physical activity during a school week, together with improved lesson content, is crucial for MF development in this age group.
... The studies corroborated the increasing prevalence of cardiovascular risk factors, burden among adolescents [8, [20][21][22], and increase subclinical atherosclerosis in young adulthood [23]. Recent studies reported a marked reduction in physical exercise, poor dietary habits, and increased SB among adolescents, and the need for different intervention strategies [8, 24,25]. Health-related education is reported to be an effective means of curbing the burden of cardiovascular diseases (CVDs) among adolescence and it is the most vital part for the prevention of atherosclerosis [26]. ...
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Background Atherosclerotic risk starts at an early stage in adolescents and interventions on adolescents’ lifestyles are most important. The pandemic of obesity-related morbidities like atherosclerosis among young adults and atherosclerotic risk factors for middle-aged adolescents in India is known. Yet, there is a lack of cost-effective and integrated intervention programs to treat this important health problem. Objective The main objective of this study is to evaluate the effect of a 12-week structured interventional strategy program, containing integrated education and supervised physical activity interventions for middle-aged adolescents. Methods/design This will be a school-based pre-experimental one-group pre-post time-series research design. The sample size is estimated to include 154 adolescents of 10th to 12th grade; aged 15–17 years will be grouped as a single arm. Data will be collected from July 2021 to January 2022. The intervention duration will be 3 months. The following measures will be evaluated before, during, and after intervention: knowledge, body mass index, level of physical activity, dietary habits, and sedentary activity. Discussion We believe that the structured interventional strategy approach which includes education related to atherosclerosis, physical activity, dietary habits, and sedentary activity, and costeffective physical activity training will be more effective in preventing atherosclerotic-related changes among middle-aged adolescents. Further, this kind of approach may be applied in similar study areas elsewhere in India.
... Logically, the higher the duration of social occasions, the lower should be the opportunity ratio values, corroborating previous studies showing that school time tends to promote sedentary behaviors during the day [37,38]. Paradoxically, school has been considered as the most appropriate place to promote a PA lifestyle for adolescents [39][40][41]. Brooke et al. (2014) have shown that adolescents had a total PA level lower in school, than out of school, with the possibility of accumulating even more in it [42]. Weaver et al. (2021) have shown that MVPA has shown increases during school time since 2015 [38]. ...
Article
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Background Following an ecological framework, the aim of this study was to highlight the way adolescents invested their time in opportunities to engage in moderate to vigorous physical activity (MVPA) according to whether they were profiled as more or less active. This study’s innovation lies in the analysis of MVPA according to social occasions which are understood as opportunities to be active throughout the day (e.g. home, school, transport). Methods PA data measured by accelerometry (ActiGraph GT3X) for seven consecutive days were compiled, with adolescents’ social occasions during the week recorded in a daily digital diary ( n = 135). The opportunity ratio of MVPA at each social time is the ratio between time spent in MVPA and the duration of a corresponding social occasion. Following the literature, participants were categorised into three profiles according to their reported amount of MVPA: HEPA active, minimally active and inactive. Non-parametric Wilcoxon signed rank and Kruskal Wallis tests were performed to determine the relative intensity of PA performed at different social occasions, and to investigate whether intensities differed between adolescents with various activity profiles. Results Results showed that engagement in MVPA at different social occasions differed according to participant profiles. Mismatch was noticed between the opportunity ratio and the duration of the most and least favorable social occasions for MVPA. For all three profiles, the social occasion “physical education lesson” revealed an opportunity ratio of MVPA (23.6% vs 17.0% vs 13.8%) significantly higher than the overall opportunity ratio of the week (6.9% vs 2.9% vs 1.2%), but of lower duration. Conversely, “home” (5.3% vs 0.0% vs 0.0%) and “school” (outside of PE time) (2.4% vs 0.0% vs 0.0%) represented the two least opportune social occasions for PA in an adolescent’s week. Conclusions Rethinking engagement with MVPA in the context of temporal opportunities would allow potential ways to intervene within an educational supervised setting to help young people adopt a physically active lifestyle at the end of the key period of adolescence. These results reinforced the importance of context in interventions for PA promotion, opening for “time education” in people.
... Others who tried to enhance the overall sound development through gross motor skills [31][32][33] proved that school-based interventions can lead to an increase in PA, PF, and the prevention of obesity. However, there are also studies [34][35][36] that have reported a low or null effect of PA interventions on children in variables such as fitness, the PA levels, and sedentary behaviours, especially when delivering PE of quality was an issue. ...
Article
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We evaluated the effectiveness of a 15-week intervention that increased from three to five lessons of physical education (PE) a week on 7-year-old boys’ and girls’ physical fitness (PF), physical activity (PA) and sedentary behaviour on week and weekend days. A total of 212 first grade pupils (mean age 6.95 ± 0.43) from two urban schools in Poznań were randomly assigned to the experimental or control groups. The PF was measured with a battery of field tests, while health-related behaviours were assessed with the Healthy Children in Sound Communities questionnaire. There were some interaction effects noticed in the PF scores in the case of a 20-min run for boys (F2,196 = 5.29, p = 0.0058) and for girls (F2,220 = 3.31, p = 0.0382) and the sit-ups test for boys (F2,196 = 1.93, p = 0.1478) and for girls (F2,220 = 3.98, p = 0.0201) and for the sit and reach test in the case of girls (F2,220 = 3.98, p = 0.0201). In terms of outdoor PA levels, there were no major differences between any of the examined groups. Differences were found between girls from the experimental and control groups in the post-test (p = 0.0107) and follow-up (p = 0.0390) during the weekdays, with no differences between the groups of boys. Despite the moderate effects of the extended PE time programme right after the intervention, there were some indications of progress in the follow-up experiments.
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Attempts to tackle problems such as smoking and obesity increasingly use complex interventions. These are commonly defined as interventions that comprise multiple interacting components, although additional dimensions of complexity include the difficulty of their implementation and the number of organisational levels they target.1 Randomised controlled trials are regarded as the gold standard for establishing the effectiveness of interventions, when randomisation is feasible. However, effect sizes do not provide policy makers with information on how an intervention might be replicated in their specific context, or whether trial outcomes will be reproduced. Earlier MRC guidance for evaluating complex interventions focused on randomised trials, making no mention of process evaluation.2 Updated guidance recognised the value of process evaluation within trials, stating that it “can be used to assess fidelity and quality of implementation, clarify causal mechanisms and identify contextual factors associated with variation in outcomes.”3 However, it did not provide guidance for carrying out process evaluation
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Objectives To review the effectiveness of school-based interventions with a physical activity component by measuring changes in psychological determinants, physical activity, and health outcomes.DesignSystematic Review.Method We conducted a literature search of school-based controlled studies that involved a physical activity intervention targeting school students. Study design, methodological quality, and effectiveness of interventions on three target levels, ‘health and fitness’ (BMI and motor performance), ‘physical activity’, and ‘psychological determinants’ (knowledge of physical activity effects, self-concept, and attitudes towards physical activity), were analysed. Furthermore, we examined the influence of specific factors (e.g., age and gender) and mediator effects.ResultsThe literature search identified 129 studies. The majority of the studies examining motor performance, physical activity, and knowledge of physical activity achieved significant results (69.7%, 56.8% and 87.5%, respectively). Significant effects on self-concept and attitudes were also found but to a smaller extent (in 30% and 43.8% of the studies, respectively). Only a few studies examining BMI (2.7%), physical activity (6.8%), and attitudes towards physical activity (12.5%) revealed negative effects, with better results observed for the control group. Intervention effects were influenced by the students’ age, intervention type, and frequency of the interventions. Self-efficacy was found to mediate the relationship between the program and the students’ physical activity.Conclusions Numerous school-based physical activity interventions achieved positive effects on three target levels. Further research is needed to clarify the mediator effects of psychological variables on physical activity and health and to increase our knowledge about the mechanisms that underlie behavioural change.
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This study describes the development, implementation, and evaluation of a structured physical activity intervention designed for high school students (years 11 and 12). A sample of 78 students was randomly allocated to control or intervention conditions for a period of ten weeks. Students in the control group (n = 40) participated in unstructured physical activity in a health and fitness center. Students in the intervention group (n = 38) participated in a ten-week structured health and exercise program based on Bandura's social learning theories. At the initial posttest, a number of statistically significant group differences were found using analysis of covariance. The intervention group reported more physical activity and improved exercise self-efficacy in comparison to the control group. At the 3-month follow-up, no statistically significant differences in physical activity were found. Results from this study suggest that a well-organized exercise-based program can be effective in increasing physical activity behavior of adolescents on a short-term basis.
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This study describes the development, implementation, and evaluation of a structured physical activity intervention designed for high school students (years 11 and 12). A sample of 78 students was randomly allocated to control or intervention conditions for a period of ten weeks. Students in the control group (n = 40) participated in unstructured physical activity in a health and fitness center. Students in the intervention group (n = 38) participated in a ten-week structured health and exercise program based on Bandura's social learning theories. At the initial posttest, a number of statistically significant group differences were found using analysis of covariance. The intervention group reported more physical activity and improved exercise self-efficacy in comparison to the control group. At the 3-month follow-up, no statistically significant differences in physical activity were found. Results from this study suggest that a well-organized exercise-based program can be effective in increasing physical activity behavior of adolescents on a short-term basis.
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No convincing evidence exists on the association of SB and child health.•New high-quality studies are needed on health effects of sedentary patterns.•We have to remain critical in interpreting existing and future evidence on SB.