ArticlePDF Available

‘Let’s Move It’ – a school-based multilevel intervention to increase physical activity and reduce sedentary behaviour among older adolescents in vocational secondary schools: a study protocol for a cluster-randomised trial

Authors:

Abstract and Figures

Background Physical activity (PA) has been shown to decline during adolescence, and those with lower education have lower levels of activity already at this age, calling for targeted efforts for them. No previous study has demonstrated lasting effects of school-based PA interventions among older adolescents. Furthermore, these interventions have rarely targeted sedentary behaviour (SB) despite its relevance to health. The Let’s Move It trial aims to evaluate the effectiveness and the cost-effectiveness of a school-based, multi-level intervention, on PA and SB, among vocational school students. We hypothesise that the intervention is effective in increasing moderate-to-vigorous-intensity physical activity (MVPA), particularly among those with low or moderate baseline levels, and decreasing SB among all students. Methods The design is a cluster-randomised parallel group trial with an internal pilot study. The trial is conducted in six vocational schools in the Helsinki Metropolitan area, Finland. The intervention is carried out in 30 intervention classes, and 27 control classes retain the standard curriculum. The randomisation occurs at school-level to avoid contamination and to aid delivery.Three of the six schools, randomly allocated, receive the ‘Let’s Move It’ intervention which consists of 1) group sessions and poster campaign targeting students’ autonomous PA motivation and self-regulation skills, 2) sitting reduction in classrooms via alterations in choice architecture and teacher behaviour, and 3) enhancement of PA opportunities in school, home and community environments. At baseline, student participants are blind to group allocation. The trial is carried out in six batches in 2015–2017, with main measurements at pre-intervention baseline, and 2-month and 14-month follow-ups. Primary outcomes are for PA, MVPA measured by accelerometry and self-report, and for SB, sedentary time and breaks in sedentary time (accelerometry).Key secondary outcomes include measured body composition, self-reported well-being, and psychological variables. Process variables include measures of psychosocial determinants of PA (e.g. autonomous motivation) and use of behaviour change techniques. Process evaluation also includes qualitative interviews. Intervention fidelity is monitored. DiscussionThe study will establish whether the Let’s Move It intervention is effective in increasing PA and reducing SB in vocational school students, and identify key processes explaining the results. Trial registrationISRCTN10979479. Registered: 31.12.2015
Content may be subject to copyright.
S T U D Y P R O T O C O L Open Access
Lets Move It’–a school-based multilevel
intervention to increase physical activity
and reduce sedentary behaviour among
older adolescents in vocational secondary
schools: a study protocol for a cluster-
randomised trial
Nelli Hankonen
1,2*
, Matti T. J. Heino
2
, Vera Araujo-Soares
3
, Falko F. Sniehotta
3
, Reijo Sund
2
, Tommi Vasankari
4
,
Pilvikki Absetz
5
, Katja Borodulin
6
, Antti Uutela
6
, Taru Lintunen
7
and Ari Haukkala
2
Abstract
Background: Physical activity (PA) has been shown to decline during adolescence, and those with lower education
have lower levels of activity already at this age, calling for targeted efforts for them. No previous study has demonstrated
lasting effects of school-based PA interventions among older adolescents. Furthermore, these interventions have rarely
targeted sedentary behaviour (SB) despite its relevance to health. The Lets Move It trial aims to evaluate the effectiveness
and the cost-effectiveness of a school-based, multi-level intervention, on PA and SB, among vocational school students.
We hypothesise that the intervention is effective in increasing moderate-to-vigorous-intensity physical activity (MVPA),
particularly among those with low or moderate baseline levels, and decreasing SB among all students.
Methods: The design is a cluster-randomised parallel group trial with an internal pilot study. The trial is conducted in six
vocational schools in the Helsinki Metropolitan area, Finland. The intervention is carried out in 30 intervention classes, and
27 control classes retain the standard curriculum. The randomisation occurs at school-level to avoid contamination and to
aid delivery.
Three of the six schools, randomly allocated, receive the LetsMoveItintervention which consists of 1) group sessions
and poster campaign targeting studentsautonomous PA motivation and self-regulation skills, 2) sitting reduction in
classrooms via alterations in choice architecture and teacher behaviour, and 3) enhancement of PA opportunities in
school, home and community environments. At baseline, student participants are blind to group allocation. The trial is
carried out in six batches in 20152017, with main measurements at pre-intervention baseline, and 2-month and
14-month follow-ups. Primary outcomes are for PA, MVPA measured by accelerometry and self-report, and for SB,
sedentary time and breaks in sedentary time (accelerometry).
Key secondary outcomes include measured body composition, self-reported well-being, and psychological variables.
Process variables include measures of psychosocial determinants of PA (e.g. autonomous motivation) and use of
behaviour change techniques. Process evaluation also includes qualitative interviews. Intervention fidelity is monitored.
(Continued on next page)
* Correspondence: nelli.hankonen@uta.fi
1
School of Social Sciences and Humanities, University of Tampere,
Kalevankatu 4, 33014 Tampere, Finland
2
Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
Full list of author information is available at the end of the article
© 2016 Hankonen et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Hankonen et al. BMC Public Health (2016) 16:451
DOI 10.1186/s12889-016-3094-x
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
(Continued from previous page)
Discussion: The study will establish whether the Lets Move It intervention is effective in increasing PA and reducing SB
in vocational school students, and identify key processes explaining the results.
Trial registration: ISRCTN10979479. Registered: 31.12.2015
Keywords: Physical activity, Sedentary behavior, Adolescents, School-based intervention, Vocational school,
Accelerometer, Behaviour change, Complex intervention
Background
Despite widely acknowledged benefits of physical activity
(PA), adolescents worldwide engage in far less PA than
is recommended [1]. In adolescence, PA tends to decline
with age and vary by gender, with boys reporting higher
PA levels than girls [2]. Increasing evidence points to
detrimental effects of excessive sedentary behaviour (SB)
even among those with sufficient levels of PA [3]. Socio-
economic status (SES) is one of the central correlates of
life expectancy, health and health behaviour, and is also
related to PA and SB in adolescents, with lower SES
youth engaging in less PA and in more SB [4].
Schools are a favourable setting for interventions aimed
at adolescents: they reach a majority of potential partici-
pants, who also spend a major part of their time there.
Although schools are a very promising setting for PA pro-
motion [5], variance in PA intervention effect sizes, so far,
is high [6], and interventions tend to have mainly short-
term effects [7] and change PA especially among girls [8].
With prior studies focusing on children, school-based
PA interventions among older adolescents or in voca-
tional schools are rare [5]: Our systematic review [9]
showed that only 10 RCTs of school-based interventions
to improve PA or SB among 1519 year-olds have thus
far been reported, and none of the trials had high meth-
odological quality. Only a few of existing trials have
assessed long-term effects, and of those who have, none
were effective [9]. An analysis of the behaviour change
techniques (BCT) and other intervention features char-
acterising effective and ineffective trials suggested the
potential of including a larger number of BCTs and cer-
tain BCTs (e.g. information about social and environ-
mental consequences, self-monitoring of PA) [9], in line
with other evidence (e.g., [10]).
Effective school-based PA and health promotion pro-
grams have been designed using behavioural theories and
intervene at several levels (e.g. not classroom-based educa-
tion only) (e.g. [1113]). The possible trade-off between
effectiveness and resources should be assessed with cost-
effectiveness analyses. Generally, school-based PA programs
have medium costs and medium-sized effects [14], but evi-
dence among older adolescents is scarce. With complex in-
terventions, comprehensive process evaluation has the
potential to identify causal mechanisms of change and
components critical to success [15]. However, theoretical
determinants identified as prospective predictors of youth
PA (e.g. [16, 17]) have rarely been studied as mediators in
school-based interventions in this age group.
Self-report assessments of PA and especially SB contain
some uncertainty as well as high variation in individual
reporting, and accelerometry is a state-of-the art method
to reliably assess activity [18]. As accelerometry does not
capture all types of PA (e.g., water sports), self-reported
PA could complement but not replace objective assess-
ment. In previous trials, objective assessment of outcomes
beyond self-report has been used in only three small trials
(sample sizes of 94 or lower), using individual-level ana-
lyses only despite nestedness in classes [9].
Thus, large gaps exist in the evidence concerning effect-
iveness of interventions to improve activity behaviours
among lower educated youth. Answering to the need for
high-quality school-based PA intervention studies for
older adolescents, this study aims to fill gaps in current
evidence by including objective measures of behaviour
and body composition, avoiding an underpowered study
design, taking into account clustering in classes, and fol-
lowing participants up to 12 months after the end of the
intensive intervention (14-month follow-up).
The Lets Move It(Fig. 1) is a complex theory- and
evidence-based intervention for vocational schools that
includes elements aiming at increasing individuals
autonomous motivation for PA, self-regulation skills for
initiating and maintaining regular PA, and at enhancing
environmental opportunities for reducing SB and in-
creasing PA. The intervention components targeting PA
were designed especially for and with adolescents with
low or moderate levels of PA [19]. Our randomised con-
trolled feasibility study [20] in 2014 demonstrated the
acceptability of the Lets Move It curriculum for both
teachers and students, and identified further improve-
ment needs, which led to an optimised version of the
intervention to be tested in the current cluster-
randomised trial.
The objective of this paper is to describe the study
protocol for a cluster RCT designed to evaluate the
effectiveness and cost-effectiveness as well as pro-
cesses of the Lets Move It programme compared with
usual curriculum for students in vocational schools. It
builds on the study protocol developed in our feasi-
bility trial [20].
Hankonen et al. BMC Public Health (2016) 16:451 Page 2 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Methods/Design
Aims of the study
The primary aim of the trial is to determine the effect-
iveness of the Lets Move It intervention on changes in
studentsphysical activity and sedentary behaviour over
two months (post-intervention, T3) and 14 months
(long-term follow-up, T4), specifically in the following
primary outcome measures:
1. Moderate-to-vigorous intensity PA (MVPA), as
measured by accelerometry and self-report
2. Sedentary behaviour: a) Sedentary time, and b)
Breaks in sedentary time (accelerometry)
We hypothesise that the intervention is effective in in-
creasing or maintaining PA and reducing SB, compared
to control group, among girls and boys, both immedi-
ately and one year after the intensive intervention (i.e., 2
and 14 months from baseline).
As the trial is designed especially for adolescents with
low PA at baseline, we expect to detect a significant dif-
ference in change in MVPA among students with low or
moderate levels of MVPA at baseline. We also aim to
examine the cost-effectiveness of the intervention, in
terms of determining cost of incremental activity.
Additionally, we will evaluate changes in secondary out-
comes among students (e. g. other indicators of activity,
body composition, physical and mental well-being, as
well as psychosocial variables) and teachers. Process
evaluation will be conducted to examine mechanisms of
change, implementation fidelity and key components of
the intervention, as well as responses and effectiveness
in subgroups.
Trial design
The design is a pragmatic, cluster randomised controlled
parallel group trial with one intervention arm (Lets
Move It programme) compared with control arm (stand-
ard curriculum). The trial is a superiority trial. The first
and second batches of the trial serve as an internal pilot
study. The internal pilot data was subject to interim ana-
lysis in line with the analysis plan to investigate previous
assumptions and to make adjustments to the data collec-
tion plan.
Control and intervention arms include altogether 57
classes (intervention k= 30, control k= 27). The school
is the unit of cluster randomisation, but classes are the
units of cluster analysis. A cluster randomisation based
on school was chosen for practical reasons and to pre-
vent contamination. The level of class (student group)
will be the cluster unit of analysis, as the essential part
of the intervention is delivered in the group setting, and
the nestedness of individuals in the classes may influ-
ence the individual outcomes due to e. g. group dynam-
ics and emerging norms. Matching schools by type of
educational tracks they offer (e.g. business, nursing) [21]
results in the same educational tracks being allocated to
both intervention and controls. Paired units were ran-
domly assigned to intervention or control. The interven-
tion is provided as normal part of the school. The details
of the trial have been planned to avoid the typical
sources of bias in health behaviour RCTs [22], including
Fig. 1 Simplified logic model linking intervention components to hypothesized mediating processes and primary outcomes
Hankonen et al. BMC Public Health (2016) 16:451 Page 3 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
using a strict protocol for participant contact (perform-
ance bias), cluster randomization (contamination bias),
and objective outcome measurement.
Study setting
Vocational schools. The study will be conducted in the
Helsinki Metropolitan area, Finland. The list of study
sites can be obtained from the first author.
Participants and eligibility criteria
Participants are vocational students in study year 1 and 2
(typically aged 1517). All students will be invited to take
part. Of educational tracks, those that meet the following
criteria were selected for the study: Those educational
tracks whose 1) students, compared to other educational
tracks in the Finnish National School Survey, report on
average higher levels of SBs and 2) report lower levels of
PA on their leisure-time, 3) student intake in the national
system is high to meet sample size requirements, and 4)
future occupations that are either sedentary or require ad-
equate/good physical condition. These educational tracks
were selected based on evidence (Finnish National School
Health Promotion survey, THL) and active consultation
with the study scientific steering committee and with
stakeholder expert group meetings, and the educational
tracks were ranked as follows: 1. Business and administra-
tion, 2. Business information technology, 3. Nursing, 4.
Hotel, restaurant and catering studies, 5. Tourism, 6. Car
mechanics. The final selected combination of tracks (1.-4.)
allowed for an even proportion of boys and girls in the
trial. Next, the eligibility criteria are explained for schools,
classes, individual students, and individual teachers.
(1) Vocational schools. Of the vocational schools
within the study region, we decided to select schools
that have the highest number of starting students in se-
lected educational tracks (to meet sample size require-
ments). Six school units were recruited. In these schools,
the trial aims to include the maximum number of classes
in years 1 and 2 in the selected educational track present
in the school during the study period (and not in voca-
tional work practice outside school).
Schools had to agree to randomisation, allow teachers to
participate in the Lets Move It workshop training, schedul-
ing the Lets Move It student program in their curriculum
and be representative of Finnish vocational schools.
(2) Classes. Inclusion criteria include 1) classes of voca-
tional students in the study year 1 or 2; and 2) possibility
to integrate 6 sessions of Lets Move It into the standard
curriculum (e.g. either within the Health Education course
or another alternative course catered in the first study
period after baseline measurement). The exclusion criteria
are 1) classes catering for students with severe physical
and mental disabilities, 2) classes for students with insuffi-
cient knowledge of the Finnish language to take part in
group interventions and use written materials, e.g., pre-
paratory classes for immigrants, and 3) classes that attend
lessons in vocational schools only 1 day per week or less
(due to partial on-the-job learning or high school
teaching).
(3) Students. Inclusion criteria for students are being
listed as students in the class and/or attending the classs
lessons. Exclusion criteria include physical condition
hindering taking part in bioimpedance measurement (e.
g. heart device).
(4) Teachers. Inclusion criteria for teachers include be-
ing core class or vocational class teachers whose teaching
involves a large amount of sitting or static/burdening work
positions and who teach the included classes in the study
period.
Recruitment
Recruitment of schools, classes and students occurs
through several phases.
(1) Six vocational schools or school units were recruited
in autumn 2014. The schools in the Helsinki Metropolitan
area that cater for the selected educational tracks were
ranked in the order of size of intake of students in that
educational track. The suitability according to selection
criteria determined the order in which the eligible upper
secondary schools were approached to participate. Once
randomised, schools either deliver LetsMoveItaspartof
their curriculum (intervention) or continue to offer PE
and health education as part of their usual curriculum
(control).
A letter was sent to directors of the selected schools
(summer/autumn 2014), informing about the study and
inviting participation, including a letter of support from
the Finnish Board of Education recommending partici-
pation in the Lets Move It trial. Then, the principal was
contacted by phone by a member of the research team,
following by a face-to-face meeting to outline the re-
quirements of the study. Invitations to participate were
sent to schools, and if a selected school declined, a letter
was sent to the next eligible school on the list that
matches the matched-pair school according to the criteria.
School principals gave consent prior to randomization
and thus were blind to randomisation. Out of all school
units (8) contacted, two schools did not accept the request
for the research team to present the project more in detail,
due to heavy workload or other similar interventions go-
ing on already at the school. Six schools consented.
(2) Following randomisation of schools, eligible classes
of first and second year students were enrolled, typically
with final confirmation a few weeks before the baseline
measurement. The trial was commenced in January
2015, and data are collected in six batches, with the
same educational tracks measured in parallel in both
intervention and control arms: business/IT (Batches 1
Hankonen et al. BMC Public Health (2016) 16:451 Page 4 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
and 2, spring 2015), nursing (Batches 3 and 4, autumn
2015), and hotel, restaurant and catering (Batches 5 and
6, spring 2016, ongoing) (Fig. 3).
(3) For each of the included classes, researchers give
an oral presentation about the study and provide written
study information and consent forms. All students are
asked to assent to data collection, but they are also in-
formed about the voluntary nature of the study. The stu-
dents in the participating classes are provided a letter
outlining the study and a consent form. According to
Finnish law, in research on 15-year-old youth and older,
their own consent to participate in the study data collec-
tion is sufficient, and guardians only need to be informed
about the study. The research assistants collect the signed
consent forms. The Lets Move It intervention is offered
as part of the normal school curriculum, so all students
normally participate in the intervention activities, regard-
less of whether they have given consent for study
measurements.
(4) In the staff meeting, teachers are given a short oral
presentation about the study and the teacher workshops
(intervention arm). They are then sent an online ques-
tionnaire. Part of the agreement with the participating
schools means that teachers are permitted to fill in the
assessment questionnaires and attend the training work-
shops during work time. Participation is voluntary.
Interventions
Active arm: intervention overview
The intervention objective is to increase total PA, more
specifically: 1) increase moderate-to-vigorous intensity
PA (MVPA), especially among those with low levels of
PA, 2) decrease time spent in SBs, and 3) increase the
number of breaks in SB. The intervention design was
preceded by a comprehensive needs assessment and pre-
liminary research among the target group [19] as well as
by synthesis of prior evidence [9] and a randomised ac-
ceptability and feasibility (rehearsal) trial [20]. The pro-
gram was designed specifically for those with low or
moderate baseline PA levels: The student panel for the
initial development of programme purposefully con-
sisted of youth reporting low levels of PA, and after the
feasibility trial, the feedback for optimization was col-
lected among participants excluding those with already
high levels of PA. Nevertheless, Lets Move It interven-
tion is delivered as a universal intervention for all stu-
dents, in order to minimise the risks of inequalities in
accessing the intervention and any potential for stigma
in case the intervention would only be targeting a sub-
group within the school. The design process of the Lets
Move It intervention made sure that this intervention could
fit into the school curriculum. The intervention is based on
theoretical and empirical insights from behavioural science:
e.g. self-determination theory [23], especially its goal
content and organismic integration theories, self-regulation
and planning theories [24, 25], and habit formation [26],
taking into account group motivational interviewing princi-
ples for the delivery of the actual intervention activities and
active ingredients [2729].
The intervention logic model for changing student PA is
differentfromthatofchangingstudent SB (Fig. 1), partially
due to the differing nature of and perceived familiarity with
the behaviours. In this intervention study, PA behaviours
are hypothesised to change via a set of conscious motiv-
ational and self-regulation processes. These are targeted in
group sessions using pair and group discussions. In this
group setting, graded, step-wise self-guided experimenta-
tion and prompting practice with PA is used, encouraging
students to select their own leisure time PA/sports type
and setting. This approach is used to increase behaviour
maintenance: Regularly incorporating PA in daily life may
be more likely to result in maintenance across time, even
outside of school terms, compared to an intervention
providing PA within the sessions in schools.
Changes in SB were designed to, primarily, be intro-
duced by environment: changes in the physical choice
architecture in classrooms (e.g. gym balls as chairs) and
teacher-led changes (e.g. increasing breaks in sitting in
class). In the Lets Move It student sessions, consequences
of excessive SB and tips for reducing SB in ones daily life
are briefly introduced. The parallel poster campaign aims
at reinforcing these cognitive and attitudinal changes. All
this goes in tandem with personal experiences of less sit-
ting in the classrooms. The latter is hypothesised to
mainly lead to changes in intentions and attitudes, sup-
ported by the educational elements of sessions and post-
ers. The intervention encourages the students to
generalise the newly adopted SB restriction behaviour in
the leisure (e.g. home) and workplace contexts. Finally,
the intervention designers acknowledge the overlapping
and intertwining nature of these behaviours: The activities
encouraged in the student group sessions include not only
MVPA but also light PA, substituting sedentary activities
(encouraging even small improvements).
Basic intervention components
The program contains 1) six intracurricular group sessions,
and a later booster session, as well as supporting online and
poster materials throughout the study, 2) teacher-led activ-
ity breaks and other SB reduction practices in classrooms,
and 3) increase of other environmental opportunities for
PA (e. g., lower-cost participation in neighbourhood sports
centres) (Fig. 1). More specific description of each compo-
nent follows:
(1)The PA group intervention consists of six interactive
face-to-face group sessions, ranging from 45-minutes
to 60 min each, which have been designed to target
Hankonen et al. BMC Public Health (2016) 16:451 Page 5 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
student PA motivation and self-regulation skills.
Trained facilitators (part of the research team) deliver
these group sessions as part of health education or a
similar course included in the school curriculum.
BCTs support improvement of both the amount and
the quality of motivation, and the progress from
motivation to goal setting and further self-regulation.
The intervention also aimed to target dysfunctional
beliefs regarding PA by e.g. emphasising well-being
motive over weight loss motive, and benefits of even
small increases in activity. Table 1lists key interaction
principles and Table 2the key BCTs as defined by the
BCT Taxonomy v1 [30]. The website and workbook
contain additional materials for students. To support
acquisitions during the sessions as well as retention,
the key messages of the intervention are portrayed
in a sequentially proceeding poster campaign in
school. The posters were designed together with an
advertisement agency and are based on the results
obtained during the needs assessment phase and
aligned with behavioural science and BCTs (targeting
specific theory-based mechanisms). In addition to wall
posters, school canteens are provided with table tri-
angle stands reiterating the most important messages,
and providing examples and guidance for self-enacting
the BCTs taught and used in the intervention sessions
and the workbook.
(2)The classroom SB reduction program, delivered by
teachers, involves decreasing studentssedentary
time and introducing breaks in sedentary time in the
classroom by altering choice architecture providing
equipment for light-intensity activity, gym balls to
replace part of the classroom chairs and standing desks
to replace part of the classroom tables, and by the use
of active teaching methods and the introduction of
activity breaks during class. The teachers are trained in
three 90-minute workshops, and the training aims at
creating sustained habitual behaviours in providing SB
reduction for students. Support materials for teachers
include: a) a 62-page booklet demonstrating a range of
strategies to reduce student sitting, with BCTs to
support the incorporation of sitting reduction as a
regular routine (habit formation); b) online materials
providing strategies and BCTs as well as video-led
sitting reduction or activity breaks for classrooms, and
useful external links, and c) posters demonstrating
various forms of activity breaks with explicit links to
subsequent benefits (e.g., vigour, increased muscle
strength, relaxation).
(3)Enhanced access to PA opportunities include a)
maximising access to existing school PA facilities,b)
establishing partnerships with community sporting
groups and/or organisations to provide salient
opportunities for students as well as reduced price
deals (for leisure-time PA), and c) providing students
with online exercise videos to guide home-based
workout. These videos were tailored to youth with little
experience in PA and low fitness (e.g., typical length
10 min), and required no gear. There are six videos that
include workout sessions targeting muscle strength,
flexibility, and aerobic fitness, ranging between 9 and
20 min in length. These videos were designed by a
certified personal trainer.Ayoungmaleprofessional
personal trainer demonstrates the workout, with a
female voice guiding through the activities (prompt
practice, provide instruction on how to perform the
behaviour, demonstration of the behaviour) using a
positive, encouraging approach in line with the ethos of
the Lets Move It. Students were encouraged to
combine multiple videos to construct their own session
based on their own preference and to use their own
music, in order to promote experience of autonomy.
Maintenance/boosters across the three components
Specific elements were designed to support maintenance
of the changed behaviours, listed below under each of
the components. For each intervention school, a Lets
Move It school team is founded, composed of voluntary
teachers and the Lets Move It project coordinator as
their contact person. It function is to cover all these ele-
ments and aim at increasing generalisability, sustainabil-
ity, and maintenance of the Lets Move It intervention.
(1)One booster session is delivered over the following
3-6 months to support maintenance of the changes.
Students are invited to follow Lets Move It social
media channels with regular boosters(e.g., pictures
of Lets Move It posters, suggestions for seasonal PA
in the area). Posters and table triangle stands are still
visible in schools after the intensive intervention
until the end of the trial.
(2)The third workshop for the teachers is scheduled
after the intensive 2-month intervention period.
Table 1 Interaction principles for intervention providers
(adapted based on Deci & Ryan, [23]; Miller & Rollnick, [29])
1. Show empathy for students
2. Ask open questions
3. Roll with studentsresistance
4. Evoke change talk
5. Show interest in studentsexperience and perspectives
6. Provide students with options and choices
7. Provide students with structure and agenda
8. Use reflective listening
9. Validate studentsconcerns
10. Provide positive feedback
Hankonen et al. BMC Public Health (2016) 16:451 Page 6 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Two quarterly email newsletters are sent to
teachers to remind of the importance of and
strategies for sitting reduction. Additionally, school
heads/educational track directors are requested to
discuss the Lets Move It activities in teacher
meetings as part of the agenda (slideshow materials
and discussion questions are provided to them). A
teacher tailored year-long calendar poster is placed at
the wall of the teachersstaff office to remind of the
various sitting reduction activities teachers selected in
the workshops to use throughout the year. Enthusiastic
teachers and other staff members are invited to affiliate
with the school team that enhances maintenance of
intervention activities in schools after the 2-month
intensive intervention (e.g., recycling posters, raising
the question of sitting reduction in staff meetings).
(3)The school team is requested to ensure continued
high access to sports facilities. The use of online
videos is promoted in the face-to-face booster
session and posters.
A central element across all intervention is autonomy
supportive interaction designed to foster self-determined
motivation in both students and teachers, aiming for
sustained motivation and behaviour (Table 1). Active
learning techniques and gradual, step-wise progress, with
a celebration of even small changes is emphasised. Sample
posters and other materials are shown in the Additional
file 1. Intervention components and their development
are described more fully elsewhere [19].
It should be noted that the intervention pertains to
both the class cluster level (e.g. Lets Move It student
sessions, teacher-led activity breaks in classes) and indi-
vidual level (e.g. tailored goals and action plans), as well
as school cluster level (poster campaign, teacherswork-
shop & PA equipment, school team). All students of the
included classes participate in the Lets Move It sessions
as part of their normal curriculum, i.e., the voluntariness
involves participation in the research measurements.
Control condition
Control group students receive teaching as usual, i.e.,
standard curriculum. Whereas the feasibility trial control
group received leaflets informing of consequences of PA
and SB, the main trial uses standard school curriculum
as the comparison, because 1) comparison to standard
only provides more relevant information and 2) the leaf-
lets were perceived unfeasible [20].
Table 2 Some of the most important behaviour change techniques delivered in the Lets Move It student group interventionscore
sessions. Full list of BCTs is reported by session and by exercise in a separate manuscript. Based on BCT Taxonomy v1 [30]
Key behaviour change techniques 123456
2.3 Self-monitoring of behaviour xxxxxx
5.1 Information about health consequences xxxxxx
5.6 Information about emotional consequences x x x x x
5.3 Information about social and environmental consequences xxxxxx
5.2 Salience of consequences x x x
5.4 Monitoring of emotional consequences xxxx
13.5 Identity associated with changed behaviour x x x x
1.1 Goal setting (behaviour) xxxxx
8.7 Graded tasks x x x x
1.4 Action planning xxxxx
4.4 Behavioral experiments x x
3.1 Social support x x x
2.2 Feedback on behavior xxxxx
1.2 Problem solving (coping planning) xxxxx
7.1, 12.1 Prompts/cues, Restructuring the physical environment x x
1.6 Discrepancy between current behaviour and goals xxxx
1.5 Review behavior goals xxxx
8.1 Behavioural practice x x
4.1 Instruction on how to perform a behaviour x x
6.1 Demonstration of behaviour x x
4.2 Information about antecedents of behaviour x x x
Hankonen et al. BMC Public Health (2016) 16:451 Page 7 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Strategies for enhancing and monitoring intervention
fidelity
The intervention sessions are carefully manualised. All
intervention facilitators are carefully trained, with role-
play exercises and ongoing revisions. Intervention facili-
tators keep track of components delivered, as well as the
quality of delivery (e.g., interaction elements), by filling
in a self-assessment form after each session, to assess
whether the intervention was delivered as intended and
to ensure high fidelity. We evaluate the extent to which
opportunities to access community and school PA facil-
ities were enhanced, and the fidelity of poster campaign
uptake and maintenance. We assess receipt and use of
intervention materials (e.g., use of workout and activity
break videos) and enactment of the BCTs taught in
intervention classes [31].
Primary outcomes
In line with intervention targets, primary outcomes are,
for PA, changes in MVPA and for SB, changes in overall
sedentary time and breaks in sedentary time. These are
designed to capture key aspects of the behaviours. The
objectively measured PA and SB outcomes are based on
accelerometry [32]. Self-reported MVPA outcome is
needed to measure types of PA that accelerometry does
not (e.g., water sports, contact sports not allowing for
any attachments to body).
Secondary outcomes and process evaluation
Secondary outcomes among students include objectively
measured body composition (muscle and fat mass),
other indicators of activity (e.g. self-reported SB), phys-
ical and mental well-being, and psychosocial variables
(e.g. behavioural automaticity). Key secondary outcomes
among teacher participants include self-reported sitting
reduction activities and observed student behaviour.
In order to examine mechanisms of change and imple-
mentation fidelity, processes will be evaluated using both
quantitative and qualitative methods. Evaluated process
variables include hypothesised mediators, including psy-
chological theoretical determinants, BCT use, observed
teacher sitting reduction behaviours. Intervention fidelity,
responses to intervention and effectiveness in subgroups
will also be investigated.
Sample size
The internal pilot study data (the first and second batches)
were subject to interim analysis in line with the analysis
plan to investigate whether the assumptions for the initial
power calculations were correct (e. g., intra-cluster correl-
ation and standard deviations for changes in outcomes).
This was done in order to make adjustments to the data
collection plan, to avoid collecting too much or too few
data. Additionally, accumulation of accelerometry data was
investigated. Altogether 502 participants (96 % of total
potential) consented to the measurements. Three
hundred seventy six participants were delivered the ac-
celerometer, and of these, 267 (71 %) wore the acceler-
ometer device over 10 h of data on at least four days.
Descriptive data from the internal pilot study is pre-
sented in Additional file 2: Table S1.
We conducted power analyses for all primary outcome
measures. For individual-level design, a sufficient num-
ber is 176 persons per arm to determine a change of ef-
fect size d = 0.30 (e.g. a mean of 8.24 min difference in
daily MVPA or 33.44 min difference in daily sedentary
time) with 80 % power and an alpha of 5 %, translating
to a post-dropout sample size of 352.
Individuals in this trial are nested within clusters (classes)
when the intervention is delivered, which may affect the re-
sults. Therefore we also calculated the effect of clustering
on the power, with a method [33] that took into account
the intracluster correlation coefficient (ICC), varying cluster
sizesandtheexpectedeffect.Datafromtheinternalpilot
was used to estimate the ICC and assess the likely mean
and SD of cluster sizes. The ICC for MVPA in the internal
pilot study varied from 0.033 (self-report measure) to 0.059
(objective measure) and we used a mean cluster size of 17
(SD = 3.83). This resulted in design effects of 1.56 and 2.00,
giving us 80 % power to detect d = 0.3 with a sample sizes
of 549 and 703, for self-report and objective MVPA mea-
sures, respectively. Using the same cluster parameters for
the SB measures, with ICC of 0.012 for interruptions to sit-
ting and 0.057 for sedentary time, design effects of 1.21 and
1.96 point to requirements of 425 and 691 students,
respectively.
Drop-out rates in previous similar trials [9] with sam-
ple totalling more than 100 and containing both genders
have varied widely, from 3.1 to 54.1 %. Our internal
pilot study showed a dropout of ~25 % from T1 to T3.
Due to improvements in follow-up data collection pro-
cedures, dropout rates are expected to diminish in
batches 36. In conclusion, with an expected sample
size of ca. 1100 students, and with a dropout of 20 %
from T1 to T3 and a further 20 % from T3 to T4, we
would be well-equipped to account for clustering in all
primary outcome measures with the post-dropout sam-
ple size of 704. Assuming 20 % of participants are classi-
fied as high-active and therefore excluded from the
MVPA analysis, we expect to achieve 93 % power to de-
tect d = 0.3 with individual-level analyses. Due to the
drop in SD, this effect translates to an absolute differ-
ence of 7.25 min for the target group, instead of
8.24 min for the whole sample. The ICC estimated from
the internal pilot study for the low- to moderate-active
studentsMVPA change was 0.038, leading to a design
effect of 1.65 and subsequently a post-dropout sample
size of 580 to reach 80 % power.
Hankonen et al. BMC Public Health (2016) 16:451 Page 8 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Randomisation procedure and blinding
Prior to starting the trial in 2014, participating schools
were randomly allocated to intervention and control
arms, using computer-generated random numbers, by a
statistician (RS) who was not involved in contacting
schools, design of the intervention program, or carrying
out the intervention. Because schools differed in educa-
tional track and size (large/small), the trial arms were
first balanced by matching consenting school units as
pairs so that large enough sample size could be ensured
for each arm. This was possible as all school clusters
were recruited prior to allocation and prevents the prob-
lem that heavily uneven-sized trial arms are known to
cause [33]. Randomisation was then conducted at the
school level and the matched school units (and educa-
tional tracks) conveniently fell in intervention or control
schools in a balanced way.
On receiving invitation to the study, student partici-
pants are blind to randomisation to avoid participation
bias. Research staff are not blind to allocation due to im-
practicalities identified in the feasibility study [20], how-
ever, the research procedures and scripts are highly
standardised and research staff are carefully trained in
order to treat all student participants similarly in both
arms. Also, researchers collecting follow-up data are not
blind to allocation: as there are major changes present in
the intervention schools (e.g., standing desks, poster
campaign) and removing these prior to follow-up mea-
surements for the sake of securing outcome assessment
blinding would not be justified or feasible. Also, school
is the most optimal location to contact the students, so
moving measurements to other locations would also not
be feasible. However, the contacts and interactions with
the participants are carefully scripted in order to provide
identical contacts with control and intervention partici-
pants and hence not to bias the results. The research
assistants are trained over several occasions to adhere to
these procedures, and those collecting follow-up mea-
surements were not delivering the intervention to avoid
any social desirability effect.
The school principal was contacted by the study team to
inform of random allocation. This is necessary as the prin-
cipal and other staff have to negotiate placing of interven-
tion materials, changes in physical environment, etc. The
staff are informed about whether they are intervention or
control schools but they are requested not to inform the
students prior to baseline, but instead leave all communi-
cation regarding the study to the research group.
Materials and procedures
Through the conduct of our acceptability and feasibility
trial [20], we developed and tested many of the instruments
and data collection methods that are used in the trial de-
scribed in this protocol. Data is collected from students at
four time points: pre-intervention baseline (Time 1, T1),
during intervention after the 3rd intervention session (T2,
intervention arm only), post-intervention at 2 months (T3),
and at 14 months (T4), i.e., 12 months after the intensive
intervention to investigate maintenance of the changes im-
mediately post-intervention (T3) (see Fig. 2). In vocational
schools, 14 months is the most feasible follow-up period to
optimise retention of students (before graduating or chan-
ging schools): a longer time-horizon would lead to higher
drop-out rates due to difficulty in reaching the students.
Measurements are conducted over six batches, correspond-
ing to 6 study cohorts (Fig. 3), to even out burden of the re-
search team. Thus, final follow-up data will be complete in
May 2017. The trial employs methods to enhance quality of
measurement (e.g., careful and repeated training of asses-
sors including simulations of student contacts, exchanging
assessors between schools in the same batches).
Fig. 2 Schedule of interventions and assessments. Students: sQ1-SQ4 = Questionnaires, A1-A3 = Accelerometry measurements, G1-G6 = Group intervention
sessions, B = Booster session, B1-B2 = Bioimpedance measurement, I = Interviews. Teachers: tQ1-tQ3 = Questionnaires, WS1-WS3 = Workshops for teachers
Hankonen et al. BMC Public Health (2016) 16:451 Page 9 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
School staff usually estimate the number of students to
be higher than it actually will be on the day of recruitment,
meaning that not all students enlisted attend school. This is
due to students being transferred to other classes, dropping
out of school, or classes being scheduled for on-the-job
learning period out of school, etc. Thus, if the students that
are reachable have not attended the information session,
the research group tries to reach them at school at least
three times after this session. Despite this, not all students
may be reached for information and consent forms.
Primary outcome measures
Objectively measured outcomes (MVPA, sedentary time,
breaks in sedentary time) are based on accelerometry [32].
The 3-axial accelerometer (Hookie AM 20, Traxmeet Ltd,
Espoo, Finland) has been shown to be a valid measurement
tool both among adults [32] and young people [34]. The ac-
celerometer is fixed to an elastic belt and participants are
instructed to wear the belt on their hip for seven consecu-
tive days during waking hours, except during shower and
other water activities, starting from the delivery day. The
accelerometers collected and stored the tri-axial data in raw
mode in actual acceleration (g-units). The data is analysed
in 6 secondsepoch length. PA was categorised into three
intensity categories based on metabolic equivalents (MET):
light, moderate and vigorous. Light PA is defined as activity
corresponding 1.52.9 MET, moderate activity as 3.05.9
MET and vigorous activity more than 6 MET [35]. Accord-
ing to the definition of SB [36], time spent in sitting and re-
clining positions are combined to indicate SB, time
standing still is analysed separately. It is possible to accur-
ately determine whether the participant is standing, sitting
or lying by applying the information from the raw data of
the three measurement axes of the accelerometer. While
the body position during walking is upright and the
direction of Earths gravity vector is constant, the verti-
cal position (angle) of the accelerometer can be identi-
fied during normal walking. This known position can
then be used to recognise different body postures. In
standardised conditions, standing can be separated
from sitting or lying with 100 % accuracy [37]. Breaks
in sedentary time are calculated on the basis of the
number of lying/sitting periods ending-up with a clear
vertical acceleration.
Research assistants deliver the accelerometers to the
participants in schools, and they collect them the subse-
quent week at the school. All participants are instructed
not to change their usual or intended patterns of activity
when wearing the accelerometer. Self-reported PA dur-
ing leisure time will be assessed using the validated
NordPAQ measure [38] in the questionnaire, concerning
MVPA over the previous seven days. The assessments
take place concurrently in both intervention and control
arms to control for the effect of weather conditions on
activity. The assessors are not involved in intervening on
students.
Other measures and materials
Table 3 shows an overview of measures among student par-
ticipants with literature references. Secondary outcomes in-
clude self-reported SB, body composition, self-reported
well-being, psychological variables (e. g. intention to restrict
ones SB), as well as health behaviours. Process measures in-
clude indicators of the direct behavioural predictors, i.e.,
the hypothesised mediators, such as PA intention, motiv-
ational regulations (self-determination theory), self-efficacy,
and the use of BCTs (adapted based on an earlier study
[39] and the Lets Move It feasibility trial [20]). At T1 and
T4, body composition is measured using Tanita MC-
780MA bioimpedance measurement device. The question-
naire data is collected online (SurveyMonkey). Participating
students complete the questionnaires in the school during
aclasssessionatT1-T4.
Teacher participants fill in questionnaires at T1, T3
and T4 after studentsmeasurements. Questionnaires
measure behaviour (use of sitting reduction strategies),
psychosocial determinants and use of BCTs, perceived
social support from colleagues and supervisors, and
background factors. Intervention arm teachers addition-
ally fill in short feedback questionnaires after teacher
workshops.
Fig. 3 Timing of data collection and (expected) sample size in each batch (k= student groups, n= individual students)
Hankonen et al. BMC Public Health (2016) 16:451 Page 10 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 3 Summary of measures among student participants in the Lets Move It trial
T1 T2
a
T3 T4
Background information, covariates XXX
PA & SB behavior
Objectively measured PA & SB (Hookie accelerometry) XXX
Self-reported PA, SB, and interruptions in SB [38,4246]XXXX
Other health related outcomes/covariates
Objectively measured body composition (Tanita MC-780 MA) XX
Self-reported health & physical fitness [47]XXX
Somatic symptoms (e.g. support- and mobility organ symptoms),
stress, sleep [47] (e.g. [4850]), dietary habits [51,52]
XXX
Smoking XX
Psychosocial correlates of PA
Behavioural beliefs: PA outcome expectations, PA descriptive norms
(peers & parents), PA injunctive norm (parents),
PA intention, PA self-efficacy/perceived behavioural control [5355]
XX XX
PA autonomous and controlled motivation [56]; integrated regulation subscale [57]XXXX
Opportunities for PA (school, neighborhood, at home) X X X
PA automaticity [58]XX
PA action and coping planning [59]XXX
Big five personality traits, brief measure [60]X
Psychosocial correlates of restricting SB
c
Behavioural beliefs: SB restriction outcome expectations, descriptive (peers) & injunctive norms
(peers, teachers), self-efficacy/perceived behavioural control, intention [5355]
XX XX
Automaticity [58]XX
Autonomous and controlled motivation [56]XX
Perceived teacher behavior and group climate
Perceived teacher actions to reduce studentssitting, Perceived opportunities for SB reduction within school
b
XX XX
Teacher sitting reduction behavior (in school classes, perceived)
b
XX
Teacher motivational behavior for reducing student SB (e.g. discussions on SB at home/work practice)
b
XX
Student group climate (acceptance & safety) [61]XXXX
Behaviour Change Technique (BCT) use (enactment fidelity items)
PA related BCT use: Frequency-dependent BCTs, Other BCTs
b
XX XX
SB related BCT use
b
XX
Intervention receipt and evaluation of programme and materials
a
Recalled number of intervention sessions attended
a
X
Intervention satisfaction
a
X
Evaluation of intervention provider
a
(autonomy support) [62]XX
Evaluation and use of home workout videos, workbook & website
ab
X
Open-ended questions on intervention
ab
XX
Adverse events
Injuries or illnesses that prevent or limit PA X X X X
Perceived harmful effects from the intervention, open-ended
ab
X
Injuries X
T1 = Baseline, T2 = Mid-intervention (after 3
rd
intervention session), T3 = Post-intervention, T4 = Follow-up (14 months); PA = physical activity,
SB = sedentary behaviour
a
= measured only of the intervention arm participants
b
= Questionnaire measure developed for this study
c
= existing mea sures adapted for this target behaviour
Hankonen et al. BMC Public Health (2016) 16:451 Page 11 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Harms and adverse events
PA-related injury and other perceived unintended negative
consequences are self-reported by students at T3-T4.
Adverse events are also be monitored constantly by project
coordinators and intervention providers, and addressed in
qualitative evaluation. Prior to the start of the trial, possible
scenarios of adverse events were discussed (e.g., increased
incidence of sports-related injuries, body dissatisfaction
leading to eating disorders or steroid use for gaining muscle
mass), and the team resolved to address these potential
emerging effects promptly. However, the intervention
content itself aimed to prevent such harmful effects by pro-
viding exercises to improve motorskillsasameansforin-
jury prevention, and by several exercises and discussions to
prevent emergence of body dissatisfaction.
Economic evaluation
The economic evaluation will model the potential cost-
effectiveness of the intervention in increasing PA and SB.
Resources relating to intervention implementation will be
collected and then used to calculate the costs relating to
the added value of intervention with regard to primary
outcomes. As the target group is not a patient population,
health-related quality-of-life questionnaires are not used
nor the longer term impact on quality-adjusted life years.
Cost-effectiveness will be presented as the cost per added
PA minute and reduced SB minute.
Qualitative process evaluation
Thematic, semi-structured individual interviews are con-
ducted among a subsample of students, to evaluate e.g. re-
ceipt of the program and student interpretations of the
causal mechanisms of change. A subsample of students
from the control arm are interviewed to be able to make
accurate conclusions about the mechanisms and effects of
the intervention. Focus group interviews are conducted
among a subsample of teachers, to evaluate e.g. receipt of
the teacher workshops and identify needs for improve-
ments before possible nation-wide dissemination. All in-
terviews are recorded and transcribed. Additionally, field
notes are kept and recorded during project meetings with
teachers and during visits to schools.
Data management details can be acquired from the
first author.
Strategies to ensure maximum study participation
The standard operational procedures for research assis-
tants collecting the data explicitly advise and script
friendly and respectful treatment of the students. We
also offer coffee, tea, lemonade and biscuits during the
data collection. Questionnaire data: While the consent-
ing students fill in the electronic questionnaires, the
non-consenting students are offered an alternative task:
a written essay based on a dietary self-assessment test
(at T4, on PA). This essay is in line with the schools health
education curriculum and ensures these students are also
focused on a meaningful task during assessment in-class.
Accelerometry: Accelerometers are delivered to students
with instruction and motivation on in a carefully scripted
manner (at T1, one-on-one; at T3 & T4, in small groups).
Toavoidforgetfulnessandsupportparticipants'useofthe
accelerometer in the mornings and assure wear for as long
as possible, SMS reminders are sent early (6.30 7 a.m.,
during the internal pilot slightly later) to participants who
do not opt out from this offer. To ensure retention at T4
and adequate use of the accelerometer, a movie ticket vou-
cher is offered to all those returning the accelerometer
promptly. At T1, T3 and T4, we offer for those who are
willing to receive the print-out for their use of accelerom-
eter. Bioimpedance: Bioimpedance measurements are con-
ducted by a same-sex research assistant. Feedback is offered
for those interested. To guarantee correct comprehension of
the print-outs (and to avoid potential unintentional side
effects, e.g., body dissatisfaction), they are given to students
in a one-on-one personal consultation (25min)afterT1.
Feedback is given in an identical way in both arms.
Statistical analyses
Effectiveness analyses will be conducted according to the
intention-to-treat principle. Primary and secondary out-
comes will be analysed using generalised linear mixed
model (GLMM) that will allow to take into account cor-
relations between observations. These methods also
allow the incorporation of incomplete longitudinal data
into the analysis. Additional sensitivity analysis using the
as treatedapproach will be conducted in order to
gauge efficacy. Process analyses will include e.g. multiple
mediation models to test whether the impact of the
intervention is explained by its effect on the hypothe-
sised mediators. We will conduct the outcome analyses
separately for gender and different levels of baseline ac-
tivity. When allowed by time and funding resources, we
will also conduct the analyses by educational track, par-
ental SES, and baseline body composition. Quantitative
analyses will be conducted using the R, SPSS and the
Mplus statistical softwares.
Discussion
The study will address central gaps in the evidence base.
The RCT will test the effectiveness of a multi-level theory-
based intervention to increase activity among adolescents.
To date, only three RCTs in this domain have evaluated
effects on PA over the long-term, beyond one-month
post-intervention [9]. This trial will show whether adding
a carefully designed, evidence- and theory-based program
will add value to teaching as usual. The analysis of inter-
vention and BCT uptake and target groupsexperiences
provide both theoretically interesting insights and also
Hankonen et al. BMC Public Health (2016) 16:451 Page 12 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
practically useful ideas to optimise intervention activities
before wider dissemination. Investigations of fidelity and
its predictors will provide practical help in the later dis-
semination phase in targeting key determinants and activ-
ities critical for maintenance.
To our knowledge, this is the first school-based PA
intervention specifically targeted at vocational schools
and tested in a randomised trial. The intervention ad-
dresses both individual and environmental features and
provide evidence regarding the causal mechanisms and
implementation, and their relation to outcomes. This
matched pair design improves comparability of the arms
(balanced for the most important covariates, gender and
educational tracks) and thus improves power. Contrary
to prior RCTs in the area that used an individual-level
design, our class-level cluster design acknowledges the
potential effect of small group dynamics on receipt of
intervention activities delivered at class level.
The phased approach in development, combined with
participatory process with end-users, may minimise risks
such as infeasibility with the setting and target group, fail-
ure in recruitment, and inefficacy in producing or detecting
the desired changes in behaviour due to inappropriate
BCTs or poor statistical power. After the project ends, the
anonymised dataset will be made available to other
researchers.
The project also produces a practical program to be uti-
lised in the Finnish school context. In line with the MRC
recommendation [40, 41], we aim to promote dissemin-
ation and translation of the program into routine practice
after completion of the trial. Vocational school students
would benefit from increases in PA in terms of improved
work capacity and mental well-being [4]. Intervention pro-
tocols including comprehensive manuals will be made
available in the public domain, as well as the student work-
book and other materials. The program components have
the potential to be translated to be a part of the standard
curriculum: Vocational school teachers, following appropri-
ate training, can teach the student programme, the dose is
easily embeddable in the school practices, and the student
group program is compatible with the national curriculum
learning objectives for health education. Thus, this inter-
vention has high potential for dissemination. In order for a
successful implementation into practice, the adoption
should be supported by a training programme, consisting
of a train-the-trainers manual, pre-intervention training,
supervision and auditing organised by the research group,
peer support and feedback systems at the schools, and on-
line facilitator support materials.
Ethical board
The Hospital District of Helsinki and Uusimaa, The Ethics
Committee for gynaecology and obstetrics, pediatrics and
psychiatry (decision number 367/13/03/03/2014.
Trial status
Recruitment started in January 2015 and is ongoing.
Additional file
Additional file 1: A selection of Lets Move It posters, table triangle
stands, and video workouts (screenshots). (DOCX 1.74 mb)
Additional file 2: Accelerometer data by different cutoff criteria.
(DOCX 20.0 kb)
Abbreviations
BCT: behaviour change technique; BMI: body mass index;
MVPA: moderate-to-vigorous physical activity; PA: physical activity;
SB: sedentary behaviour; SES: socioeconomic status.
Acknowledgements
We would like to thank Sini-Tuuli Hynynen and Hanna Laine for their
contributions to intervention development and optimization, Elisa Kaaja, Katariina
Köykkä and Katri Kostamo for helping finalise research procedures, and Emilia
Kujala and Anna Aistrich for their input in the early phases of trial design.
Funding
The study and the preceding development phase was funded by the Ministry
of Education and Culture, funding number 34/626/2012 (years 201214), and
funding number OKM/81/626/2014, (years 201517), the Ministry of Social
Affairs and Health, funding number 201310238 (years 201315). Process
evaluation studies are funded by the Academy of Finland (as part of the
Academy Research Fellowship for the first author, years 20152020). The
funding bodies played no role in the writing of this protocol or the decision to
submit it for publication.
Availability of data and material
Finnish Social Science Data Archive, 2018.
Authorscontributions
NH is the principal investigator. NH and AH supervise the study. All steering
group members (FFS, TV, TL, AU) and co-investigators (PA, VAS, KB, AH) were
involved in writing the original grant proposal. All authors contributed to
concept development and design of the study. NH, PA, VAS, FFS, TV, TL, KB
and AU contributed to the development of the intervention. MH conducted the
power calculation and statistical analyses for the internal pilot study. RS was
responsible for statistical methods and randomization and advised on the power
calculation. TV and KB advised on the physical activity assessment procedure. All
authors participated in planning the data collection procedures and contributed
to the study design. NH and MH drafted the manuscript. VAS, FFS, RS, TV, PA, KB,
AU, TL, and AH performed the critical revision of the manuscript for important
intellectual content. All authors approved the final manuscript.
Competing interests
The authors declare that they have no competing interests. Study sites have
no competing interests.
Ethics approval and consent to participate
The research plan has been assessed by the Ethics Committee for Gynaecology
and Obstetrics, Pediatrics and Psychiatry of the Hospital District of Helsinki and
Uusimaa (decision number 367/13/03/03/2014). Both students and parents or
custodians are provided with study details, including an explanation of the
benefits and limitations of participation. Written informed consent is asked from
students. Participation in the research is voluntary, and participants may withdraw
any time during the study. According to the Finnish law regarding medical
research, participants aged 15 or older are allowed to consent themselves as long
as they inform their parents or custodians. Potential negative unintentional effects
of the intervention will be observed throughout the programme.
School teams are requested to monitor unintended consequences and harm
from the intervention during and after the intensive intervention, and students
are asked to report possible adverse events in the questionnaires, including PA-
related injuries. A data monitoring committee is not needed due to low risks of
the intervention. Data will be stored in a secure location and will require a pass-
word, and only specified researchers are allowed access. All the data is kept and
Hankonen et al. BMC Public Health (2016) 16:451 Page 13 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
handled confidentially, according to the instructions and requirements of good
scientific procedures by the University of Helsinki.
Author details
1
School of Social Sciences and Humanities, University of Tampere,
Kalevankatu 4, 33014 Tampere, Finland.
2
Faculty of Social Sciences, University
of Helsinki, Helsinki, Finland.
3
University of Newcastle Upon Tyne, Newcastle
Upon Tyne, UK.
4
UKK Institute, Tampere, Finland.
5
School of Health Sciences,
University of Tampere, Tampere, Finland.
6
National Institute for Health and
Welfare, Helsinki, Finland.
7
Faculty of Sport and Health Sciences, University of
Jyväskylä, Jyväskylä, Finland.
Received: 30 March 2016 Accepted: 10 May 2016
References
1. Hallal PC et al. Global physical activity levels: surveillance progress, pitfalls,
and prospects. Lancet. 2012;380(9838):24757.
2. Van Der Horst K et al. A Brief Review on Correlates of Physical Activity and
Sedentariness in Youth. Med Sci Sports Exerc. 2007;39(8):124150. doi:10.
1249/mss.0b013e318059bf35.
3. Koster A et al. Association of Sedentary Time with Mortality Independent of
Moderate to Vigorous Physical Activity. PLoS ONE. 2012;7(6):e37696.
4. Elgar FJ et al. Socioeconomic inequalities in adolescent health 20022010: a
time-series analysis of 34 countries participating in the Health Behaviour in
School-aged Children study. Lancet. 2015;385(9982):208895.
5. van Sluijs EMF, McMinn AM, Griffin SJ. Effectiveness of interventions to
promote physical activity in children and adolescents: systematic review of
controlled trials. BMJ. 2007;335(7622):703.
6. Crutzen R. Adding effect sizes to a systematic review on interventions for
promoting physical activity among European teenagers. Int J Behav Nutr
Phys Act. 2011;7:5.
7. Dobbins M, DeCorby K, Robeson P, Husson H, Tirilis D. School-based
physical activity programs for promoting physical activity and fitness in
children and adolescents aged 6-18. Cochrane Database of Systematic
Reviews. 2009;(1). http://www.ncbi.nlm.nih.gov/pubmed/19160341.
8. Yildirim M et al. For whom and under what circumstances do school-based
energy balance behavior interventions work? Systematic review on
moderators. Int J Pediatr Obes. 2011;6(2-2):e4657.
9. Hynynen ST et al. A systematic review of school-based interventions
targeting physical activity and sedentary behaviour among older
adolescents. Int Rev Sport Exerc Psychol. 2016;9(1):2244.
10. Michie S et al. Effective techniques in healthy eating and physical activity
interventions: A meta-regression. Health Psychol. 2009;28(6):690701.
11. Peters LW et al. Effective elements of school health promotion across
behavioral domains: a systematic review of reviews. BMC Public Health.
2009;9(1):114.
12. Dadaczynski K, de Vries N. Quality based prevention of overweight in the
school setting: the HEPS quality checklist. J Public Health. 2013;21(3):297305.
13. Kriemler S et al. Effect of school-based interventions on physical activity and
fitness in children and adolescents: A review of reviews and systematic
update. Br J Sports Med 2011; 45(11): 10.1136/bjsports-2011-090186.
14. Wu S et al. Economic Analysis of Physical Activity Interventions. Am J Prev
Med. 2011;40(2):14958.
15. Moore GF et al. Process evaluation of complex interventions: Medical
Research Council guidance. BMJ. 2015;350.
16. McEachan RRC et al. Prospective prediction of health-related behaviours
with the Theory of Planned Behaviour: a meta-analysis. Health Psychol Rev.
2011;5(2):97144.
17. Ng JYY et al. Self-Determination Theory Applied to Health Contexts: A Meta-
Analysis. Perspect Psychol Sci. 2012;7(4):32540.
18. Matthews CE et al. Best practices for using physical activity monitors in
population-based research. Med Sci Sports Exerc. 2012;44(1 Suppl 1):S6876.
19. Hankonen N, Heino MTJ, Araujo-Soares V, Absetz P, Sniehotta FF, Haukkala
A. Using theory and evidence to increase physical activity: Lets Move It
school-based multi-level intervention. European Health Psychologist. In
press.
20. Hankonen N, Heino MTJ, Hynynen S, Laine H, Araujo-Soares V, Sniehotta FF,
Vasankari, Absetz P, Lintunen T, Haukkala A. Use of behavior change
techniques in a school-based physical activity intervention: Feasibility study
results. European Health Psychologist. 2015;17(S1):411.
21. Imai K, King G, Nall C. The Essential Role of Pair Matching in
Cluster-Randomized Experiments, with Application to the Mexican Universal
Health Insurance Evaluation. Stat Sci. 2009;24(1):2953.
22. de Bruin M, McCambridge J, Prins JM. Reducing the risk of bias in health
behaviour change trials: improving trial design, reporting, or bias
assessment criteria? Psychol Health. 2014;30:143.
23. Ryan RM, Deci EL. Self-Determination Theory and the Facilitation of Intrinsic
Motivation, Social Development, and Well-Being. Am Psychol. 2000;55(1):6878.
24. Carver CS, Scheier MF. Control theory: A useful conceptual framework for
personalitysocial, clinical, and health psychology. Psychol Bull. 1982;92(1):11135.
25. Hagger MS et al. Implementation intention and planning interventions in
Health Psychology: Recommendations from the Synergy Expert Group for
research and practice. Psychol Health. 2016:126. [Epub ahead of print].
26. Lally P, Gardner B. Promoting habit formation. Health Psychol Rev. 2013;
7(sup1):S13758.
27. Naar-King S, Suarez M, editors. Motivational Interviewing With Adolescents
and Young Adults. New York: Guilford Press; 2011.
28. Wagner CC, Ingersoll KS, editors. Motivational Interviewing in Groups. New
York: Guilford Press; 2013.
29. Miller WR, Rollnick S. Motivational interviewing: Helping people change.
New York, NY: Guilford press. 2012.
30. Michie S et al. The Behavior Change Technique Taxonomy (v1) of 93
Hierarchically Clustered Techniques: Building an International Consensus for the
Reporting of Behavior Change Interventions. Ann Behav Med. 2013;46(1):8195.
31. Bellg AJ et al. Enhancing Treatment Fidelity in Health Behavior Change
Studies: Best Practices and Recommendations From the NIH Behavior
Change Consortium. Health Psychol. 2004;23(5):44351.
32. Vähä-Ypyä H et al. A universal, accurate intensity-based classification of
different physical activities using raw data of accelerometer. Clin Physiol
Funct Imaging. 2014;35(1):64-70. doi:10.1111/cpf.12127.
33. Eldridge S, Kerry S. A Practical Guide to Cluster Randomised Trials in Health
Services Research. Chichester, UK: Wiley-Blackwell. 2012.
34. Aittasalo M et al. Mean amplitude deviation calculated from raw
acceleration data: a novel method for classifying the intensity of
adolescentsphysical activity irrespective of accelerometer brand. BMC
Sports Sci Med Rehab. 2015;7(1):17.
35. Vähä-Ypyä H et al. Validation of Cut-Points for Evaluating the Intensity of
Physical Activity with Accelerometry-Based Mean Amplitude Deviation
(MAD). PLoS ONE. 2015;10(8):e0134813.
36. Sedentary Behaviour Research, N. Letter to the Editor: Standardized use of
the terms sedentaryand sedentary behaviours. Appl Physiol Nutr Metab.
2012;37(3):5402.
37. Sievänen H et al. A Universal Method For Accurate Classification Of Physical
Activity And Sedentary Behavior With Triaxial Accelerometry (abstract). Med
Sci Sports Exerc. 2014;46(5S):567.
38. Rasmussen LB. Nordic monitoring of diet, physical activity and
overweight: First collection of data in all Nordic Countries 2011.
Copenhagen: Nordic Council of Ministers. 2012.
39. Hankonen N et al. Which Behavior Change Techniques are Associated
with Changes in Physical Activity, Diet and Body Mass Index in
People with Recently Diagnosed Diabetes? Ann Behav Med.
2015;49(1):717.
40. Campbell M et al. Framework for design and evaluation of complex
interventions to improve health. BMJ. 2000;321(7262):6946.
41. Craig P et al. Developing and evaluating complex interventions: the new
Medical Research Council guidance. BMJ. 2008;337.
42. Fagt S et al. Nordic monitoring on diet, physical activity and overweight:
Validation of indicators. Copenhagen: Nordic Council of Ministers. 2011.
43. National Institute for Health and Welfare, F. The National FINRISK Study. 2016.
Available from: https://www.thl.fi/fi/tutkimus-ja-asiantuntijatyo/vaestotutkimukset/
finriski-tutkimus/the-national-finrisk-study. Accessed 11 February 2016.
44. Borodulin K et al. Forty-year trends in cardiovascular risk factors in Finland.
Eur J Public Health. 2015;25(3):53946.
45. Dunstan DW et al. The Australian diabetes, obesity and lifestyle study
(AusDiab)methods and response rates. Diabetes Res Clin Pract.
2002;57(2):11929.
46. Lynch BM et al. Development and testing of a past year measure of
sedentary behavior: the SIT-Q. BMC Public Health. 2014;14(1):1.
47. National Institute for Health and Welfare, F. School Health Promotion Study. 2016.
Available from: https://www.thl.fi/fi/web/thlfi-en/research-and-expertwork/
population-studies/school-health-promotion-study. Accessed 11 February 2016.
Hankonen et al. BMC Public Health (2016) 16:451 Page 14 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
48. Karvonen S, Vikat A, Rimpelä M. The role of school context in the increase
in young peoples health complaints in Finland. J Adolesc. 2005;28(1):116.
49. Merikanto I et al. Late bedtimes weaken school performance and
predispose adolescents to health hazards. Sleep Med. 2013;14(11):110511.
50. Ståhl MK, El-Metwally AAS, Rimpelä AH. Time trends in single versus
concomitant neck and back pain in finnish adolescents: results from
national cross-sectional surveys from 1991 to 2011. BMC Musculoskelet
Disord. 2014;15(1):17.
51. Hoppu U et al. Yläkoululaisten ravitsemus ja hyvinvointi. In:
Kansanterveyslaitoksen julkaisuja B30. Helsinki: National Public Health
Institute, Finland; 2008.
52. Hoppu U et al. The diet of adolescents can be improved by school
intervention. Public Health Nutr. 2010;13(6A):9739.
53. Francis J et al. Constructing questionnaires based on the theory of planned
behavior. A manual for health services researchers. United Kingdom:
University of Newcastle; 2004.
54. Hagger MS et al. The processes by which perceived autonomy support in
physical education promotes leisure-time physical activity intentions and
behavior: a trans-contextual model. J Educ Psychol. 2003;95(4):784.
55. Fishbein M, Ajzen I. Predicting and changing behavior: The reasoned action
approach. New York, NY: Taylor & Francis. 2011.
56. Markland D, Tobin V. A modification to the behavioural regulation in
exercise questionnaire to include an assessment of amotivation. J Sport
Exerc Psychol. 2004;26(2):1916.
57. Wilson PM et al. Its Who I Am Really!The Importance of Integrated
Regulation in Exercise Contexts1. J Appl Biobehav Res. 2006;11(2):79104.
58. Gardner B et al. Towards parsimony in habit measurement: Testing the
convergent and predictive validity of an automaticity subscale of the
Self-Report Habit Index. Int J Behav Nutr Phys Act. 2012;9:1022.
59. Sniehotta FF et al. Action planning and coping planning for longterm lifestyle
change: theory and assessment. Eur J Soc Psychol. 2005;35(4):56576.
60. Gosling SD, Rentfrow PJ, Swann Jr WB. A very brief measure of the Big-Five
personality domains. J Res Pers. 2003;37(6):50428.
61. Richer S, Vallerand R. Construction and validation of the Perceived Relatedness
Scale. Revue Européene de Psychologie Appliquée. 1998;48:12937.
62. Hagger MS et al. The perceived autonomy support scale for exercise
settings (PASSES): Development, validity, and cross-cultural invariance in
young people. Psychol Sport Exerc. 2007;8(5):63253.
We accept pre-submission inquiries
Our selector tool helps you to find the most relevant journal
We provide round the clock customer support
Convenient online submission
Thorough peer review
Inclusion in PubMed and all major indexing services
Maximum visibility for your research
Submit your manuscript at
www.biomedcentral.com/submit
Submit your next manuscript to BioMed Central
and we will help you at every step:
Hankonen et al. BMC Public Health (2016) 16:451 Page 15 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
... Tiedon pohjalta voidaan kehittää ammattiin opis kelevien nuorten tiedonsaannin ja terveyden edis tämisen menetelmiä niin alueellisesti kuin kan sallisestikin. Oikeaaikaisilla, tarveperustaisilla ja toiminnallisilla nuorten arkisiin ympäristöön sijoittuvilla interventioilla voidaan tutkitusti vai kuttaa nuorten terveyteen ja terveyskäyttäytymi seen (10,(25)(26). Tiedonhakuun käytettiin kotimaisista tieto kannoista Medic ja Julkaritietokantoja. Kan sainvälisistä tietokannoista käytettiin Cinahl Complete, Google Scholar ja PubMedtietokan toja. Haut toteutettiin kirjoittajan (JL) toimesta huhti ja toukokuun 2020 aikana. ...
... Ammattiin opiskelevien nuorten yleisimmät ter veyttä uhkaavat tekijät liittyvät elintapoihin, ku ten päihteiden käyttöön (29,3536), tupakointiin (26,30), vähäiseen liikuntaan (25,30,33) sekä ylipainoon ja aliravitsemukseen (30,34). Tervey teen liittyvien valintojen tekemisen ja terveyttä ylläpitävien elintapojen toteuttamisen haasteet koskettavat laajasti ammattiin opiskelevia nuoria (8,16,26,2830,33). ...
... Useiden tutkimusten mukaan liikkumatto muus aiheuttaa riskejä nuorten terveydelle (25,3031,33). Liikkumattomuudella on vaiku tuksia mielenterveyteen sekä työkykyyn (25), ja runsas istuminen on yhteydessä yleistyneeseen tuki ja liikuntaelinkipuiluun (31). Hankosen ym. ...
Article
Nuorten terveyserot ovat kytköksissä koulutusryhmään: terveysvajeet ja -riskit koskettavat erityisesti toisen asteen ammatillisessa koulutuksessa opiskelevia nuoria. Myös sosioekonomisella asemalla ja koulutustasolla on merkitystä. Terveys on selkeästi heikointa niillä nuorilla, jotka jäävät kokonaan toisen asteen koulutuksen ulkopuolelle. Nuoruuden terveys ja terveyskäyttäytyminen vaikuttavat terveyteen vielä aikuisuudessa. Tämän systemaattisen kirjallisuuskatsauksen tavoitteena oli kuvata ammattiin opiskelevien nuorten terveyttä ja terveyttä uhkaavia tekijöitä. Katsaus toteutettiin Finkin mallin mukaisesti. Tiedonhakuun käytettiin Medic-, Julkari-, Cinahl Complete-, Google Scholar- ja PubMed-tietokantoja. Haut rajattiin koko tekstin saatavuuteen, suomen- tai englanninkielisiin sekä enintään 10 vuotta vanhoihin julkaisuihin. Lopulliseen katsaukseen hyväksyttiin kaikkiaan 13 tutkimusta. Tulosten mukaan terveyden koulutusryhmittäisiä eroja ilmenee erityisesti elintavoissa, terveysosaamisessa ja arjenhallinnassa. Ympäristöllä, perheellä ja vertaisilla on selkeä vaikutus nuorten terveyskäyttäytymiseen. Vaikka nuoret harjoittelevat itsenäistymistä ja omien valintojen tekemistä, he ovat edelleen erityisen riippuvaisia kasvuympäristöstään usealla terveyden ulottuvuudella. Terveyteen liittyvät heikkoudet korostuvat ammattiin opiskelevien nuorten ryhmässä. Tutkimusten mukaan terveyden riskit myös siirtyvät herkästi sukupolvelta toiselle. Terveyttä edistävien toimien kohdentaminen ja pyrkiminen huono-osaisuuden ylisukupolvisen kierteen katkaisemiseen ovat perusteltuja erityisesti kansanterveydellisestä näkökulmasta. Oikea-aikaisilla, tarveperustaisilla ja toiminnallisilla, sekä nuorten arkiympäristöihin, kuten kouluun, sijoittuvilla interventioilla voidaan tutkitusti vaikuttaa nuorten terveyskäyttäytymiseen ja terveyteen. Tutkimustiedon pohjalta voidaan kehittää ammattiin opiskelevien nuorten tiedonsaannin ja terveyden edistämisen menetelmiä niin alueellisesti kuin kansallisestikin.
... Adolescence is a transitional phase of growth and development between childhood and adulthood [1][2][3]. The World Health Organization defined an adolescent as any individual between ages 10 and 24 years, and adolescence as a period of life in which adolescents have health and developmental needs [4][5][6]. Adolescence can be a time of both disorientation and discovery, a transitional period that can raise questions of independence and identity as adolescents cultivate their sense of self, during which they make choices about physical activity (PA) behavior [7,8]. It is a time to develop healthy behaviors, knowledge, and skills that will be important later in life. ...
... In doing so, they help to lay a foundation for life-long, health-promoting physical activity. This influence becomes especially decisive in adolescence since there is evidence that it is a key stage in the adoption of healthy habits [1][2][3][4] and the strengthening of positive PA behavior that contributes to the improvement of adolescents' current and future health [5][6][7]. These needs, which were identified and discussed in the finding's chapters, were shared with the participants in the agreement workshop [41,42]. ...
... Physical activity is considered an important determinant of health, quality of life, and well-being. World Health Organization [6] defines physical activity as any bodily movement produced by skeletal muscles that require energy expenditure. Physical activity can also be undertaken as a form of movement-transport or house cleaning duties and through play [14][15][16]. ...
Article
Full-text available
Background: Adolescents are influenced by external factors which may impact their level of physical activity. Parents require specific strategies to become involved and to increase physical activity participation in adolescence. Objective: Thus, the current study aimed to design recommendations to increase physical activity participation and parental involvement. Methods: The current study forms part of a broader mixed-method study in which the results of the phases and stages of the pre-studies informed the current study. Thus, the current study uses an agreement workshop to develop recommendations with stakeholder and expert input in two rounds. Participants were invited to participate in the current study n = 100, and n = 65 participated in round one. Round two consisted of n = 20 experts invited to an agreement workshop, with n = 11 attending and making an input on the final recommendations. Therefore, experts and parents in the field of parenting, physical activity, and physical education, were invited to participate in the study rounds. After each round, the responses from the panellists were collated, interpreted, and developed into a framework for recommendations using thematic analysis. Themes were generated and refined using an agreement format. Results: After results from the stages and phases were consolidated and refined, six themes and 51 sub-themes were identified in a framework for recommendations. The framework was further refined using expert input and the final recommendations were derived using an agreement or agreement. Thus, with input from experts input through the agreement workshop, the findings were discussed, refined, and drafted into recommendations. Agreement and agreement were achieved on six broad recommendations and fifty-one sub-themes. The final recommendations were presented in the current study to increase parental involvement and physical activity in adolescents. Discussion: Recommendations and physical activity resources were developed and are presented as a form of support to parents and adolescents. The recommendations are intended as a source of unbiased information for parents to become more involved and for adolescents to increase physical activity participation.
... Olena Yelizarova 1 Natalia Duiba 2 DOI: https://doi.org/10.30525/978-9934-26-050- [6][7][8][9][10][11][12][13][14][15] Increasing the prevalence of Noncommunicable Diseases and Mental Health Disorders (NMH) which increase the mortality and disability of adults in most countries of the world are challenging for the scientific community to look for new ways of prevention using innovative multidisciplinary methods [1][2]. Risk factors of NMH are personal behaviour or lifestyle, environmental exposure, hereditary characteristic, anxiety disorders, depression. ...
... The goal of the GLMC intervention is to increase the proportion of children who reach the 60-minute MVPA per day recommended by the World Health Organization by 15%. There is also a randomized cluster study using behavioural and physical activity change methods in Finland [12]. ...
... Process evaluation is important in explaining the reasons for the discrepancies between expected and observed outcomes and in designing and implementing more rational and rigorous intervention program for the future [39]. Throughout the intervention, we will identify the process evaluation elements and procedure based on the principles and steps described in the conceptual framework by Saunders et al. [40], including: (1) frequency and intensity of interventions actually delivered by teachers, volunteers, program team members (dose delivered); (2) student and primary caregivers class attendance will be recorded at the schools to establish exposure and participation in the intervention, logbooks will be recorded to understand how satisfied they are with the intervention (dose received); (3) classroom observations and surveys of teachers, volunteers and program team members to assess the extent to which the intervention is being implemented as intended (fidelity); (4) interviews with school principals, teachers, and volunteers to understand the level of support from schools for the program (context). ...
Article
Full-text available
Inadequate intake of fruits and vegetables (FV) and moderate-to-vigorous physical activity (MVPA) in children has become a global public health problem. Therefore, school-based gardening and cooking (SGC) and sports participation (SP) interventions may be effective in improving children’s FV intake and MVPA. The aim of this study is to develop and evaluate the effectiveness of SGC and SP interventions on FV intake and MVPA among Chinese children. In this cluster randomized controlled trial study, 237 children in grades 4–5 from six public primary schools from Changsha, Hunan Province, China will be randomly assigned to: (1) a SGC and SP combined intervention group; (2) a SP intervention group; (3) a regular practice group. The intervention clusters will be implemented for a period of 6 months and follow up will be carried out after 12 months. The outcome will be collected using a combination of self-reported and objective measures. Primary outcomes will include children’s FV intake and duration of MVPA per day, and secondary outcomes will included frequency and attitudes of FV intake and SP, in addition to other measures. Finally, a process evaluation will be used to analyze the facilitators and barriers to intervention implementation. Trial Registration: (Registration Number: ChiCTR2200064141).
... There were 30 intervention classes and 27 control classes (Hankonen, 2016). This interesting research model noted that the interventions had minimal impact on the students from lowsocioeconomic groups with poorly educated parents (Mora, 2015). ...
Research
Full-text available
This Health Research Dissertation explored the Influence of Sef-Efficacy, Physical Activity, and Health Education on Body Mass Index and Latinx Middle Student Overall Health
... Despite the widely acknowledged benefits of PA, adolescents engage in far less PA than is recommended (Hankonen et al., 2016). It is generally agreed that adolescents in both developed and developing countries do not meet the health-related guidelines for engaging in at least 60 minutes of moderate-tovigorous (MVPA) PA daily (Oyeyemi et al., 2014). ...
Article
Despite the known benefits of physically activity, adolescents worldwide do not engage in sufficient amount of physical activity. Limited empirical evidence exists regarding the role of contributing factors and the influence of parental involvement. Therefore, the importance of understanding adolescent health behaviour has become a global health concern. The aim of this study was to understand the factors contributing to physical activity participation, specifically the barriers and facilitators to adolescents’ participation. Three focus group discussions (45-90 minutes) were held with adolescents (n=35), purposevily sampled from Metro South education district in Mitchell’s Plain, Cape Town. The focus groups discussions explored adolescents’ perceptions on the factors that contributed towards physical activity participation, barriers and facilitators. Thematic analysis revealed eight themes. Theme 1: Parental involvement, Theme 2: Physical activity barriers, Theme 3: Physical activity preferences, Theme 4: Physical activity parental support, Theme 5: Physical activity facilitators, Theme 6: Physical activity encouragement, Theme 7: Parental directive behaviour, Theme 8: Increasing physical activity strategies. It was concluded that enjoyable activities that are age appropriate, fun and social in nature, appeal most to adolescents. The adolescents suggested that parental involvement is the key to increasing physical activity and to sustain positive physical activity behaviour. The study evidence revealed that collaboration between adolescents and their parents enables adolescents to sustain positive physical activity participation that may track into adulthood.
... Activity levels decline throughout adolescence, 13 particularly in girls, and those who are more socioeconomically disadvantaged, or living in inner-city areas. [14][15][16] Worryingly just 43.2% of adolescents in the UK now meet the current government activity guidelines, which suggest accumulating at least 60 min MVPA per day across the week. [17][18][19] Most young people in the UK have to attend school, and physical education (PE) lessons are compulsory until Year 11,13 suggesting that school PE offers a suitable setting to promote adolescent PA and fitness. ...
Article
Full-text available
Objectives To establish pupil fitness levels, and the relationship to global norms and physical education (PE) enjoyment. To measure and describe physical activity (PA) levels during secondary school PE lessons, in the context of recommended levels, and how levels vary with activity and lesson type. Methods A cross-sectional design; 10 697 pupils aged 12.5 (SD 0.30) years; pupils who completed a multistage fitness test and wore accelerometers to measure PA during PE lessons. Multilevel models estimated fitness and PE activity levels, accounting for school and class-level clustering. Results Cardiorespiratory fitness was higher in boys than girls (ß=−0.48; 95% CI −0.56 to −0.39, p<0.001), within absolute terms 51% of boys and 54% of girls above the 50th percentile of global norms. On average, pupils spent 23.8% of PE lessons in moderate-to-vigorous PA (MVPA), and 7.1% in vigorous PA (VPA). Fitness-focused lessons recorded most VPA in co-educational (ß=1.09; 95% CI 0.43 to 1.74) and boys-only lessons (ß=0.32; 95% CI −0.21 to 0.85). In girls-only lessons, track athletics recorded most VPA (ß=0.13; 95% CI −0.50 to 0.75) and net/wall/racket games (ß=0.97; 95% CI 0.12 to 1.82) the most MVPA. For all lesson types, field athletics was least active (ß=−0.85; 95% CI −1.33 to −0.36). There was a relationship of enjoyment of PE to fitness (ß=1.03; 95% CI 0.83 to 1.23), and this relationship did not vary with sex (ß=−0.14 to 0.23; 95% CI −0.16 to 0.60). Conclusions PE lessons were inactive compared with current guidelines. We propose that if we are to continue to develop a range of sporting skills in schools at the same time as increasing levels of fitness and PA, there is a need to introduce additional sessions of PE activity focused on increasing physical activity. Trial registration number NCT03286725 .
Article
Full-text available
Objectives: Planning is an effective self-regulation strategy. However, little is known why some people take up planning and some do not. Such understanding would help interventions to promote planning. We investigated how adolescents explain their (non) use of planning for physical activity after an intervention. Methods: Qualitative content analysis was employed to investigate follow-up interviews (a purposeful sampling; n = 19 low-to-moderately active, vocational school students) of Let's Move It trial participants twice post-intervention: 6-8 weeks and 14 months post-baseline. In the intervention, planning was one of the key techniques used to promote PA. Results: We identified seven categories linked to reasons for (not) using planning. Most were related to feelings anticipated to result from planning. Action- and identity-related concerns were also raised. The reasons for planning were that the plan (1) helps to clarify what to do and to get things done, (2) strengthens the feeling of autonomy, (3) promotes a sense of progress, ability and control over one's PA. The reasons for not planning were that (having) a plan may (1) feel forced and like an unpleasant duty, (2) take away life's spontaneity and freedom, (3) result in anticipated annoyance and bad mood if one fails to enact the plan, or (4) be an effective strategy for others but not for the interviewee. Conclusions: Planning may not only link to behavioural control but also the sense of autonomy, and thus subsequent motivation. We suggest various strategies to promote planning, including challenging non-planner identity and harnessing social dimension of planning.
Article
Background: Physical activity among children and adolescents is associated with lower adiposity, improved cardio-metabolic health, and improved fitness. Worldwide, fewer than 30% of children and adolescents meet global physical activity recommendations of at least 60 minutes of moderate to vigorous physical activity per day. Schools may be ideal sites for interventions given that children and adolescents in most parts of the world spend a substantial amount of time in transit to and from school or attending school. Objectives: The purpose of this review update is to summarise the evidence on effectiveness of school-based interventions in increasing moderate to vigorous physical activity and improving fitness among children and adolescents 6 to 18 years of age. Specific objectives are: • to evaluate the effects of school-based interventions on increasing physical activity and improving fitness among children and adolescents; • to evaluate the effects of school-based interventions on improving body composition; and • to determine whether certain combinations or components (or both) of school-based interventions are more effective than others in promoting physical activity and fitness in this target population. Search methods: We searched CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, BIOSIS, SPORTDiscus, and Sociological Abstracts to 1 June 2020, without language restrictions. We screened reference lists of included articles and relevant systematic reviews. We contacted primary authors of studies to ask for additional information. Selection criteria: Eligible interventions were relevant to public health practice (i.e. were not delivered by a clinician), were implemented in the school setting, and aimed to increase physical activity among all school-attending children and adolescents (aged 6 to 18) for at least 12 weeks. The review was limited to randomised controlled trials. For this update, we have added two new criteria: the primary aim of the study was to increase physical activity or fitness, and the study used an objective measure of physical activity or fitness. Primary outcomes included proportion of participants meeting physical activity guidelines and duration of moderate to vigorous physical activity and sedentary time (new to this update). Secondary outcomes included measured body mass index (BMI), physical fitness, health-related quality of life (new to this update), and adverse events (new to this update). Television viewing time, blood cholesterol, and blood pressure have been removed from this update. DATA COLLECTION AND ANALYSIS: Two independent review authors used standardised forms to assess each study for relevance, to extract data, and to assess risk of bias. When discrepancies existed, discussion occurred until consensus was reached. Certainty of evidence was assessed according to GRADE. A random-effects meta-analysis based on the inverse variance method was conducted with participants stratified by age (children versus adolescents) when sufficient data were reported. Subgroup analyses explored effects by intervention type. Main results: Based on the three new inclusion criteria, we excluded 16 of the 44 studies included in the previous version of this review. We screened an additional 9968 titles (search October 2011 to June 2020), of which 978 unique studies were potentially relevant and 61 met all criteria for this update. We included a total of 89 studies representing complete data for 66,752 study participants. Most studies included children only (n = 56), followed by adolescents only (n = 22), and both (n = 10); one study did not report student age. Multi-component interventions were most common (n = 40), followed by schooltime physical activity (n = 19), enhanced physical education (n = 15), and before and after school programmes (n = 14); one study explored both enhanced physical education and an after school programme. Lack of blinding of participants, personnel, and outcome assessors and loss to follow-up were the most common sources of bias. Results show that school-based physical activity interventions probably result in little to no increase in time engaged in moderate to vigorous physical activity (mean difference (MD) 0.73 minutes/d, 95% confidence interval (CI) 0.16 to 1.30; 33 studies; moderate-certainty evidence) and may lead to little to no decrease in sedentary time (MD -3.78 minutes/d, 95% CI -7.80 to 0.24; 16 studies; low-certainty evidence). School-based physical activity interventions may improve physical fitness reported as maximal oxygen uptake (VO₂max) (MD 1.19 mL/kg/min, 95% CI 0.57 to 1.82; 13 studies; low-certainty evidence). School-based physical activity interventions may result in a very small decrease in BMI z-scores (MD -0.06, 95% CI -0.09 to -0.02; 21 studies; low-certainty evidence) and may not impact BMI expressed as kg/m² (MD -0.07, 95% CI -0.15 to 0.01; 50 studies; low-certainty evidence). We are very uncertain whether school-based physical activity interventions impact health-related quality of life or adverse events. Authors' conclusions: Given the variability of results and the overall small effects, school staff and public health professionals must give the matter considerable thought before implementing school-based physical activity interventions. Given the heterogeneity of effects, the risk of bias, and findings that the magnitude of effect is generally small, results should be interpreted cautiously.
Chapter
Recently there has been recognition that interventions to improve health equity must conceptualize health disparities interventions at multiple levels. Multilevel interventions simultaneously address more than one aspect of the socioecological framework of health (i.e., the individual, the provider, the healthcare setting, healthcare system, and/or community) in order to address a variety of factors that influence health outcomes (e.g., discrimination, culture, education). Existing multilevel intervention studies show positive health outcomes in racial/ethnic minority populations for a wide range of conditions, including diabetes, cancer, and cardiovascular disease. However, the field of multilevel interventions has yet to reconcile how the diverse intervention elements of the various sectors are connected to individual health outcomes. In this chapter, we offer a comprehensive review of the current literature on multilevel interventions in order to evaluate their effectiveness in addressing health disparities. We then discuss methodological challenges to the design and statistical evaluation of multilevel interventions. Challenges arise during the evaluation process due to the complexity of intervention effects, with researchers having to decide whether to compare the combined effect of the multiple interventions together, to analyze separately the impact of each single level intervention, or to assess whether there are interactive effects between the interventions. We also consider challenges to the implementation and sustainability of interventions, such as engaging important community stakeholders and building community capacity before, during, and after the research project. Although more research is needed to determine whether multilevel interventions are more effective than single‐level interventions, we conclude the chapter by offering recommendations for addressing health disparities through multilevel research based on the promising evidence outlined throughout the chapter
Article
Full-text available
The current article details a position statement and recommendations for future research and practice on planning and implementation intentions in health contexts endorsed by the Synergy Expert Group. The group comprised world-leading researchers in health and social psychology and behavioural medicine who convened to discuss priority issues in planning interventions in health contexts and develop a set of recommendations for future research and practice. The expert group adopted a nominal groups approach and voting system to elicit and structure priority issues in planning interventions and implementation intentions research. Forty-two priority issues identified in initial discussions were further condensed to 18 key issues, including definitions of planning and implementation intentions and 17 priority research areas. Each issue was subjected to voting for consensus among group members and formed the basis of the position statement and recommendations. Specifically, the expert group endorsed statements and recommendations in the following areas: generic definition of planning and specific definition of implementation intentions, recommendations for better testing of mechanisms, guidance on testing the effects of moderators of planning interventions, recommendations on the social aspects of planning interventions, identification of the preconditions that moderate effectiveness of planning interventions and recommendations for research on how people use plans.
Article
Full-text available
The current article details a position statement and recommendations for future research and practice on planning and implementation intentions in health contexts endorsed by the Synergy Expert Group. The Group comprised world-leading researchers in health and social psychology and behavioural medicine who convened to discuss priority issues in planning interventions in health contexts and develop a set of recommendations for future research and practice. The Expert Group adopted a nominal groups approach and voting system to elicit and structure priority issues in planning interventions and implementation intentions research. Forty-two priority issues identified in initial discussions were further condensed to 18 key issues, including definitions of planning and implementation intentions and 17 priority research areas. Each issue was subjected to voting for consensus among group members and formed the basis of the position statement and recommendations. Specifically, the Expert Group endorsed statements and recommendations in the following areas: generic definition of planning and specific definition of implementation intentions, recommendations for better testing of mechanisms, guidance on testing the effects of moderators of planning interventions, recommendations on the social aspects of planning interventions, identification of the preconditions that moderate effectiveness of planning interventions, and recommendations for research on how people use plans.
Article
Full-text available
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.
Chapter
Factors affecting sample size for cluster randomised designsCalculating sample size using the intra-cluster correlation coefficientSample size calculations for ratesRestricted number of clustersTrials with a small number of clustersVariability in cluster sizeComparison of different measures of between-cluster variabilityMatched and stratifi ed designsSample size for other designsSummaryReferences