A systematic review of school-based interventions targeting physical activity and sedentary behaviour among older adolescents

A systematic review of school-based interventions targeting physical activity and sedentary behaviour among older adolescents S-T. Hynynen a , M. M. van Stralen b , F. F. Sniehotta c , V. Araújo-Soares c , W. Hardeman d , M. J. M. Chinapaw e , T. Vasankari f and N. Hankonen a * a Department of Social Research, University of Helsinki, Helsinki, Finland; b Department of Health Sciences, Faculty of Earth and Life Sciences and the EMGO Institute for Health and Care Research, VU University Amsterdam, Amsterdam, The Netherlands; c Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK; d Behavioural Science Group, Primary Care Unit, University of Cambridge, Cambridge, UK; e Department of Public and Occupational Health and the EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands; f UKK Institute for Health Promotion Research, Tampere, Finland ABSTRACT Lack of physical activity (PA) and high levels of sedentary behaviour (SB) have been associated with health problems. This systematic review evaluates the effectiveness of school-based interventions to increase PA and decrease SB among 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’sdranged 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. ARTICLE HISTORY Received 22 November 2014 Accepted 10 July 2015 KEYWORDS physical activity; sedentary behaviour; adolescents; school-based intervention; behaviour change techniques Introduction Ample evidence exists of the profound benefits of leading a physically active life. Regular physical activity (PA) has been associated with a decreased risk of physical and mental health problems, such as obesity, cardiovascular disease, type II diabetes and depression © 2015 The Author(s). Published by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/Licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. CONTACT S-T Hynynen sini.hynynen@kuulas.fi *Present address: School of Social Sciences and Humanities, University of Tampere, Finland. INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY, 2015 VOL. 9, NO. 1, 22–44 http://dx.doi.org/10.1080/1750984X.2015.1081706 Downloaded by [Tampere University] at 22:47 08 June 2016 among children and adolescents (Biddle, Gorely, & Stensel, 2004; Janssen & LeBlanc, 2010; Penedo & Dahn, 2005). The evidence on the adverse health effects of excessive sedentary behaviour (SB) in youth is inconsistent to date (Chinapaw, Altenburg, & Brug, 2015; Chinapaw, Proper, Brug, van Mechelen, & Singh, 2011). Yet there is an indication that excessive SB is associated with both physical and psychological health problems such as unfavourable body composition, decreased fitness, lowered self-esteem and pro-social behaviour and decreased academic achievement in school-aged children and youths (Tremblay et al., 2011a). If non-sedentary lifestyle habits can be initiated in adolescence, this may have beneficial preventive value, as the effects on mortality and morbidity among adults have already been established (Thorp, Owen, Neuhaus, & Dunstan, 2011; Wilmot et al., 2012). To achieve and maintain good health, children and adolescents are recommended to engage in at least 60 minutes of moderateto vigorousintensity physical activity (MVPA) each day (Janssen & LeBlanc, 2010; Strong et al., 2005). However, according to the Health Behaviour in School-aged Children study 2009–2010, only 15% of 15-year-old adolescents met this recommendation globally (Currie et al., 2012). There are also recommendations for sedentary time –although not as widely agreed upon as for PA. For example, the guidelines of the Canadian Society for Exercise Physiology (CSEP) for decreasing SB in youth state that the goal of minimising the time spent sedentary can be achieved by several means: in addition to limiting recreational screen time, also limiting sedentary transport, extended sitting time and time spent indoors throughout the day which also may involve time spent in classrooms (Tremblay et al., 2011b). In Finland recent national recommendations on the reduction of sedentary time explicitly identify schools as one of the key settings (Ministry of Social and Health Affairs, 2015). As PA even decreases during adolescence (Dumith, Gigante, Domingues, & Kohl, 2011) and youths spend a lot of their time both at home and in school being sedentary (van Stralen et al., 2014; Verloigne et al., 2012), interventions that aim to promote PA and to reduce SB among adolescents are urgently needed. Schools are a promising setting for health promotion interventions aimed at adolescents, since they reach a majority of the target population. In previous studies, schoolbased interventions have been found to have significant effects on adolescents’PA and SB. However, the effects have been small, short-term and have largely differed between interventions (Biddle, O’Connell, & Braithwaite, 2011; De Meester, van Lenthe, Spittaels, Lien, & De Bourdaedhuij, 2009; Demetriou & Höner, 2012; Dobbins, De Corby, Robeson, Husson, & Tirilis, 2009; Lonsdale et al., 2013; Metcalf, Henley, & Wilkin, 2012; van Sluijs, McMinn, & Griffin, 2007). Also, effects are mostly seen in school-related PA while effects outside of this context in leisure time and commuting PA are often not observed or assessed (Kriemler et al., 2011). Furthermore, age might moderate the effectiveness of school-based interventions. Earlier reviews have tended to either include a broad age range (e.g., 6–18-year-olds) or focus on younger age categories (Safron, Cislak, Gaspar, & Luszczynska, 2011; van Sluijs et al., 2007). To our knowledge, no recent review has focused solely on interventions targeting older adolescents, and evidence in this age group is lacking. These previous studies have disregarded the possibility that age groups differ in developmental stages and thus require different intervention strategies. Since older adolescents have been a less studied target group, this review focuses on them exclusively. INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 23 Downloaded by [Tampere University] at 22:47 08 June 2016 The heterogeneity in effectiveness of school-based PA interventions (see, e.g., Kriemler et al., 2011; van Sluijs et al., 2007) may be explained by differences in factors such as length of the intervention, mode of delivery, provider or content of the intervention. Yet no studies so far have systematically sought to explain this variability by analysing intervention content (see Abraham & Michie, 2008; Michie et al., 2013). Taxonomies of behaviour change techniques (BCTs) allow more in-depth analyses of interventions and intervention strategies (Abraham & Michie, 2008; Michie et al., 2013). Three previous reviews have identified the BCTs used in interventions targeting obesityand weight-related behaviours among children and adolescents (Golley, Hendrie, Slater, & Corsini, 2011; Hendrie et al., 2012; Martin, Chater, & Lorencatto, 2013). In communityand school-based interventions to target obesity-related behaviours in 1–18-year-old children, three BCTs were associated with effectiveness: Providing general information on behaviour –health links,Prompting practice, and Planning for social support/social changes (Hendrie et al., 2012). In their review on interventions that target parents to improve children’s weight-related nutrition intake and activity patterns, Golley et al. (2011) found that effective interventions included: Prompting barrier identification,Restructuring the home environment,Prompting self-monitoring and Prompting specific goal setting. In childhood obesity prevention interventions, only Prompting generalisation of target behaviour was shown to be related to intervention effectiveness (Martin et al., 2013). None of the existing reviews has conducted a BCT analysis of school-based PA or SB interventions among adolescents aged over 15 years old (e.g., Biddle et al., 2011; Dobbins et al., 2009; van Sluijs et al., 2007). More studies have investigated effective BCTs to increase PA among adult populations (see, e.g., Abraham & Graham-Rowe, 2009; Bird et al., 2013; Michie, Abraham, Whittington, McAteer, & Gupta, 2009; Williams & French, 2011). These systematic reviews show that effective PA interventions have usually included BCTs linked with self-regulation, such as self-monitoring, goal setting and action planning. There is a lack of evidence about whether the number of BCTs reported as being present in interventions is related to intervention effectiveness. However, a review of interventions targeting obesity and weight-related nutrition and PA behaviours in children both in the home and school/community setting (Hendrie et al., 2012) suggested that interventions including a higher number of BCTs were associated with better outcomes. In addition to characterising interventions in terms of component BCTs, existing reviews of school-based PA interventions fall short of analysing whether intervention outcomes are influenced by intervention length, mode of delivery (e.g., oral communication, written material, video, interactive computer program, self-help, individual face-to-face, group face-to-face, telephone) or provider of delivery. A systematic review of systematic reviews and meta-analyses on effects of school-based interventions targeting obesityrelated behaviours showed that more effective interventions generally lasted at least three months, i.e. a longer duration was reported to be more effective compared to shorter interventions (Safron et al., 2011). A better understanding of whether the abovementioned characteristics are related to intervention effectiveness would enable evidence-based decisions during intervention development. Our review provides anup-to-date systematic analysis ofthe effectiveness ofschool-based interventions targeting PA and/or SB among older adolescents (aged 15–19 years), using an exploratory narrative review with an analysis of intervention components including BCTs. 24 S-T. HYNYNEN ET AL. Downloaded by [Tampere University] at 22:47 08 June 2016 Review questions (1) Are school-based interventions to increase PA and/or reduce SB among 15to 19-yearolds effective? (2) Does effectiveness of the interventions vary according to a) the length of the intervention, b) the mode of delivery (e.g., oral communication, written material, video, interactive computer program, self-help, individual face-to-face, group face-to-face, telephone), and c) the provider of the intervention (e.g., teacher, peer, researcher)? (3) Which BCTs have been used in the interventions and how is intervention content related to effectiveness? Methods The protocol for this systematic review was published in PROSPERO –International prospective register of systematic reviews (Hynynen et al., 2013). Study selection and search strategy A systematic search was conducted using the following electronic databases of peerreviewed journal articles and online research registers: Medline, Cinahl, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Cochrane Methodology Register. The search spanned from the year of the database’s inception up to and including February 2013. During the search we imposed no language restrictions but only articles written in English were included in the review. Individualised search strategies for the different databases included combinations of key words related to PA and SB, school, intervention and adolescence (see supplemental data). We used a modified version of the Cochrane highly sensitive search strategy for identifying randomised trials, where the sections on complementary therapies were removed. The reference lists of studies that met the inclusion criteria as well as other relevant reviews were scanned. The researchers also sent inquiries about ongoing intervention studies via relevant networks, such as scientific societies. However, no additional studies were identified through this approach. Inclusion criteria specified randomised or cluster randomised studies on school-based interventions that targeted PA and/or SB among 15to 19-year-old adolescents who are apparently healthy (for a more detailed description, see Hynynen et al., 2013). Included studies could also address other health behaviours, but data on these behaviours were not extracted. Inclusion criteria specified that interventions had to be primarily based in schools but they might also include homeor community-based components. The included studies reported either self-reported or objectively measured (e.g., accelerometer) PA or SB or both, presenting a baseline and a post-intervention measurement. Studies that only targeted individuals at increased health risk (e.g., obese youths) were excluded. We also excluded studies that measured students’PA during physical education (PE) classes only. This strategy identified 8470 references that were imported into the RefWorks database (see Figure 1). After excluding duplicates, 5482 references remained. The screening of the remaining references was conducted in three phases by two researchers (STH and MVS) INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 25 Downloaded by [Tampere University] at 22:47 08 June 2016 working independently. Publications were included if eligibility was unclear. In the first phase of screening, titles of all references were reviewed. During this phase 4456 references were excluded. In the second phase, abstracts of the remaining 1026 articles were screened and 667 articles excluded. In the third phase, full text papers were obtained for 359 articles and eligibility reviewed in detail. Any disagreements were resolved by discussion between the two researchers. We created a standardised form to extract all relevant details of the trial characteristics (study design, number of participants, method of randomisation, study setting and Figure 1. Identification of the included studies. 26 S-T. HYNYNEN ET AL. Downloaded by [Tampere University] at 22:47 08 June 2016 country), sample characteristics (inclusion and exclusion criteria for participants, co-morbidities), details of interventions (mode of delivery, provider, setting, recipient, intensity, length), participant characteristics, participant attrition, physical activity and sedentary behaviour outcome measures and possible secondary outcomes. The data extraction was carried out by one researcher (STH) and verified by a second (MVS or another researcher). Assessing risk of bias The Cochrane risk of bias tool (Higgins et al., 2011) was used for assessing risk of bias in the included articles, covering the allocation procedures, outcome analyses, reporting and other possible sources of bias. Two researchers (STH and MC) independently assessed the quality of all studies that met the inclusion criteria. The following domains were considered: sequence generation, allocation concealment, blinding of study personnel and participants, incomplete outcome data, selective outcome reporting, other possible sources of bias, and when relevant cluster recruitment bias and baseline imbalance bias. Each paper was carefully assessed for each domain and judgements were made regarding potential bias, according to three categories: low risk, high risk, or risk unclear. Inter-rater reliability was calculated (average percentage agreement 74%). Coding the behaviour change techniques The BCT coding was conducted by two researchers (STH and MVS) using Michie et al.’s (2013) behaviour change technique taxonomy (BCTT v1). Prior to coding, STH had attended a BCT training workshop and MVS completed a group tutorial training programme guided by phone. BCTs were coded separately for increasing PA and reducing SB. Both intervention arms and control arms were coded for BCTs. All published materials (e.g., intervention protocols) of the included trials were used to characterise intervention content. Prior to extracting BCTs from included intervention studies, the two coders piloted consistency in their BCT coding by coding three intervention reports that were not included in the review as they targeted a different age group. All included interventions were then coded independently. Inter-rater reliability was assessed and percent agreement on BCTs present in the descriptions was high (83.3%). Discrepancies between both primary coders were discussed and resolved with a third researcher (WH) who is a member of the BCTT v1 team. Assessing intervention and BCT effectiveness For each study, intervention effects (Cohen’sd) for PA and SB were calculated at the first follow-up post-intervention. This was the only outcome measurement point after baseline that was reported in all included studies. Therefore, we selected this point in time to compare the effects across studies. For the purpose of calculating effect sizes, we contacted four authors for further numerical data needed. Three responded and provided the requested data. Half of the studies reported moderate to vigorous physical activity (MVPA) outcome measures, which were used for the effect size calculations when available. If the study presented objective measurement of PA, those were used for the INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 27 Downloaded by [Tampere University] at 22:47 08 June 2016 Table 1. Study characteristics. Study Country Study design Intervention and control groups Number of participants Total attrition Sex of participants Mean age of participants (SD) PA outcomes SB outcomes Assessment Bayne-Smith et al. (2004) US CRT 1 IV 1 CON 442 Not reported Only female - Self-reported PA no. of sessions per week Not targeted or reported Baseline, Post-IV Gomes de Barros et al. (2009) Brazil CRT 1 IV 1 CON 2155 54.1% 55.7% female 18.4 (SD = 2.3) Self-reported no. of days per week accumulating 60 min of MVPA Not reported Baseline, Post-IV Hill, Abraham, and Wright (2007) UK CRT 3 IV 1 CON 620 18.9% 51% female 16.97 (SD 1.4) Self-reported ‘On average over the last three weeks, I have exercised energetically for at least 30 minutes ____ times per week.’ Not targeted or reported Baseline, Post-IV Lee, Kuo, Fanaw, Perng, and Juang (2012) Taiwan CRT 1 IV 1 CON 94 3.2% Only female 16.2 (SD 0.4) Objectively measured PA (pedometer) Change in aerobic walking (steps/day) Not reported Baseline, Post-IV Lubans and Sylva (2006) UK RCT 1 IV 1 CON 78 Post-IV 0% Follow-up 2.6% 61.5% female 16.7 (SD 0.5) Self-reported MVPA min/week Not reported Baseline, Post-, 3month follow-up Mauriello et al. (2010) US CRT 1 IV 1 CON 1800 Post-IV 20.6% Follow-up 34.3% 50.8% female - Self-reported PA ‘In a typical week, how many days do you do 60 min or more of physical activity?’ Self-reported limited TV viewing Baseline, Post-IV,6month follow-up, 12-month followup Neumark-Sztainer et al. (2010) US CRT 1 IV 1 CON 356 Post-IV 3.1% Follow-up 5.6% Only female - Self-reported MVPA (30-min blocks/day) Self-reported sedentary activity (30-minute blocks/ day) Baseline, Post-IV, 9-month follow-up Schofield, Mummery, and Schofield (2005) Australia CRT 2 IV 1 CON 85 Post-IV 20% Only female 15.8 (SD 0.8) Objectively measured PA (pedometer) 4-d step count Not targeted or reported Baseline, Mid-IV, Post-IV Singhal, Misra, Shah, and Gulati (2010) India CRT 1 IV 1 CON 209 Post-IV 3.8% 40.2% female IV 16.04 (SD 0.41) CON 16.0 (SD 0.5) Self-reported PA > 4 days in a week Self-reported watching TV (4–5 h/day) Baseline, Post-IV Slootmaker, Chinapaw, Seidell, van Mechelen, and Schuit (2010) The Netherlands RCT 1 IV 1 CON 87 Post-IV 21.8% Follow-up 9.2% 63.2% female 15.1 (SD not reported) Objectively measured MVPA (accelerometer) Objectively measured sedentary time Baseline, Post-IV, 8-month follow-up IV: Short for intervention. CON: Short for control. 28 S-T. HYNYNEN ET AL. Downloaded by [Tampere University] at 22:47 08 June 2016 effect size calculations; in other cases self-reported outcomes were addressed. When there was no MVPA outcome reported, we used the closest outcome available (see Table 1). We classified the interventions into effective vs. non-effective based on the same PA outcome data that were used in the effect size calculations. Effective trials were defined as those that reported a significant difference (p< .05) between intervention and control groups’ PA at first follow-up post-intervention. We identified which BCTs were present in the effective trials and which BCTs were present in the non-effective trials. We analysed BCT effectiveness using a method modified from one used in Martin et al.’s(2013) systematic review on childhood obesity prevention and management interventions. Effective BCTs were defined as those that were present in a majority (> 50%) of the effective trials but not at all present or present in only one of the non-effective trials. We also attempted to identify the BCTs unique to interventions that did not change PA or SB. We illustrated BCT effectiveness by calculating ‘effectiveness ratios’of the relative weight of BCTs appearing in two or more trials. The effectiveness ratio was calculated as the ratio of the number of times a BCT was present in an effective intervention divided by the number of times it was present as a component of all interventions, including the ineffective interventions. Results The search provided 5482 records (see Figure 1) out of which 13 articles reporting 10 unique intervention studies were identified for inclusion in the review (Bayne-Smith et al., 2004; Gomes de Barros et al., 2009; Hill et al., 2007; Lee et al., 2012; Lubans & Sylva, 2006; Mauriello et al., 2006; Mauriello et al., 2010; Nahas et al., 2009; Neumark-Sztainer et al., 2010; Neumark-Sztainer, Story, Hannan, & Rex, 2003; Schofield et al., 2005; Singhal et al., 2010; Slootmaker et al., 2010). Study characteristics and participants Two of the included studies were individually randomised controlled trials (Lubans & Sylva, 2006; Slootmaker et al., 2010) and eight were cluster randomised trials (Bayne-Smith et al., 2004; Gomes de Barros et al., 2009; Hill et al., 2007; Lee et al., 2012; Mauriello et al., 2010; Neumark-Sztainer et al., 2010; Schofield et al., 2005; Singhal et al., 2010). The average sample size was 593 (SD = 757), ranging from 78 to 2155 older adolescents. The nonweighed mean attrition percentage (where reported) at first follow-up post intervention was 16.2% (SD = 16.8%) ranging from 0% to 54.1%. Four interventions were only aimed at female adolescents (Bayne-Smith et al., 2004; Lee et al., 2012; Neumark-Sztainer et al., 2010; Schofield et al., 2005) and six were aimed at both sexes (Gomes de Barros et al., 2009; Hill et al., 2007; Mauriello et al., 2010; Singhal et al., 2010; Slootmaker et al., 2010). (For more detail on study characteristics, see Table 1.) Intervention and comparison arms The 10 studies compared a total of 13 different intervention groups against 10 control groups. Eight studies compared one intervention group against one control group (Bayne-Smith et al., 2004; Gomes de Barros et al., 2009; Lee et al., 2012; Lubans & Sylva, INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 29 Downloaded by [Tampere University] at 22:47 08 June 2016 2006; Mauriello et al., 2010; Neumark-Sztainer et al., 2010; Singhal et al., 2010; Slootmaker et al., 2010). These interventions included a web-based intervention offering personalised feedback on readiness to change (Mauriello et al., 2010), a web-based intervention coupled with the use of accelerometers (Slootmaker et al., 2010), an intervention using pedometers to encourage walking (Lee et al., 2012), an intervention targeting the school environment and offering students PA opportunities (Gomes de Barros et al., 2009), health and exercise programmes (Lubans & Sylva, 2006), a heart health programme focusing on vigorous exercise and other health behaviours such as diet, smoking and stress (Bayne-Smith et al., 2004), and an all-girls PE course targeting self-empowerment, nutrition and including one-on-one motivational interviewing sessions (Neumark-Sztainer et al., 2010) (for further information see Table 2). One study compared two intervention groups against a control group (Schofield et al., 2005). In this study both intervention groups were offered a 12-week PA self-monitoring and educative programme. One intervention group was provided with pedometers and set daily step count targets whereas the other group set daily time-based goals for PA involvement (Schofield et al., 2005). A final study compared three types of theory-based persuasive leaflets to increase PA (leaflet alone, leaflet plus a motivational quiz, and leaflet plus implementation intention prompt) against a no-leaflet control group (Hill et al., 2007). Control group treatment differed widely in the 10 trials. Whereas some control groups received a cognitive word search task (Hill et al., 2007), or a brief leaflet with general PA recommendations (Slootmaker et al., 2010), others received the school’s standard PE programme (Gomes de Barros et al., 2009). Neumark-Sztainer et al. (2010) described also providing the control group with an all-girls PE class. Overall, control group interventions were insufficiently described in the studies to enable coding of BCTs. Risk of bias All studies except for one (Slootmaker et al., 2010) were judged to be at high risk of bias in at least one domain (see Table 3). However, the study by Slootmaker et al. (2010) also had domains of unclear risk of bias. Sequence generation was inadequately described in eight out of 10 study reports. None of the studies reported proper blinding of participants to study group allocation. Outcomes Five studies targeted only PA or PA and SB outcomes (Hill et al., 2007; Lee et al., 2012; Lubans & Sylva, 2006; Schofield et al., 2005; Slootmaker et al., 2010). The five other studies targeted other outcomes as well, such as heart health knowledge and dietary behaviours (Bayne-Smith et al., 2004; Gomes de Barros et al., 2009; Mauriello et al., 2010; Neumark-Sztainer et al., 2010; Singhal et al., 2010). Five studies assessed outcome measures only at baseline and at the end of the intervention period (Bayne-Smith et al., 2004; Gomes de Barros et al., 2009; Lee et al., 2012; Schofield et al., 2005; Singhal et al., 2010). Hill et al. (2007) assessed outcomes three weeks post-intervention. Three studies assessed outcomes both post-intervention and a few months post-intervention (Lubans & Sylva, 2006; Neumark-Sztainer et al., 2010; Slootmaker et al., 2010). Mauriello et al. 30 S-T. HYNYNEN ET AL. Downloaded by [Tampere University] at 22:47 08 June 2016 large, reported using more BCTs than the non-effective interventions, and specifically eight BCTs: Information about social and environmental consequences,Graded tasks,Selfmonitoring of behaviour,Feedback on behaviour,Problem solving,Goal setting (behaviour), Action planning and Social support. Out of the four studies that measured SB, only two had significant effects on the behaviour. No studies were found that focused solely on SB. Due to this lack of evidence, it is difficult to draw conclusions on what intervention elements or BCTs were related to effectiveness in regards to SB. Our review suggests that interventions targeting multiple health behaviours are less effective in promoting PA among older adolescents than ones focusing solely on PA or PA and SB, which is also supported by earlier evidence (Crutzen et al., 2010). Previous reviews have suggested that when appropriately trained, a wide range of providers can deliver effective health behaviour interventions (Greaves et al., 2011; Peters, Kok, Ten Dam, Buijs, & Paulussen, 2009). On the contrary, we found that interventions delivered by research staff were more effective than those delivered by school staff or other providers. This finding resembles the basic difference between efficacy and effectiveness trials, and may be more a matter of fidelity of delivery –or training –rather than a matter of the person providing the intervention. While other reviews have shown that longer duration of school-based PA interventions was associated with effectiveness (Dobbins et al., 2009; Safron et al., 2011), we did not find a relationship between intervention length and short-term effectiveness. It is possible that the relationship between intervention length and PA outcomes was influenced by other intervention characteristics not analysed in our review such as intervention intensity: short but very intensive interventions may be more effective than longer interventions with less contact. Finally, in line with previous evidence (Greaves et al., 2011), there was no clear association between mode of intervention delivery and effectiveness. In line with some (Avery, Flynn, van Wersch, Sniehotta, & Trenell, 2012; Hendrie et al., 2012) and in contrast to other reviews (Abraham & Graham Rowe, 2009; Dombrowski et al., 2013), we found that effective PA interventions included more BCTs than non-effective interventions. This may be either a matter of non-effective interventions actually using fewer techniques to change behaviour, or of not reporting what was done, indicating less precision in both planning and reporting the intervention. The specific BCTs identified to be related with intervention effectiveness resonate with the findings of previous reviews with adult populations (Avery et al., 2012; Michie et al., 2009; Williams & French, 2011), where BCTs related to self-regulation have been shown to be effective in changing PA. Based on our review, this applies also among older adolescents: Goal setting and Action planning were techniques emphasised in effective trials, and complementing BCTs such as Self-monitoring of behaviour,Feedback on behaviour and Problem solving were unique to effective trials. In their review on obesity prevention interventions for children, Hendrie et al. (2012) found that providing information on behaviour–health links was related to intervention effectiveness. Quite similarly, we found Information about social and environmental consequences to be a technique uniquely present in the effective trials. What should be noted is that this BCT is coded whenever the information provided is unspecified in the intervention description (Michie et al., 2013). Therefore it is possible that the information provided in the interventions was not actually about social and environmental consequences, but rather about health consequences or emotional consequences, or a combination of these. INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 37 Downloaded by [Tampere University] at 22:47 08 June 2016 Interestingly, Behavioural practice/rehearsal was a technique present mainly in noneffective interventions. In a previous review of PA interventions among obese adults (Olander et al., 2013), quite to the contrary, Prompting practice 1 was related to largest effects for PA. It is possible that prompting behavioural practice outside of intervention sessions is related to effectiveness whereas practice within the sessions is a typical element of non-effective interventions. This is supported by our finding that setting Graded tasks was a BCT present uniquely in effective interventions. We found little evidence of intervention techniques focusing on the environment level of behaviour change, such as Restructuring the physical environment. Neither have previous reviews on PA interventions (see, e.g., Greaves et al., 2011; Michie et al., 2009) shown these techniques to be related to effectiveness. Restructuring the physical environment was present in only three interventions, two of which were effective and one non-effective. The lack of environment-level techniques may be a matter of financial resources. Initiating major changes in the school’s physical environment without previous evidence of it actually being effective in supporting and increasing students’PA might be too risky and costly. Several distinct environmental changes, such as providing opportunities for PA by direct monetary investments in schools’PA equipment, offering students free opportunities for structured PA and organising collective supervised PA events, were heavily emphasised in the intervention by Gomes de Barros et al. (2009). However, in the BCT Taxonomy v1 all of these different actions are coded under one technique: Restructuring the physical environment. We recommend that this technique is unpacked in more detail in future developments of the taxonomy, so that studies can investigate the relative effectiveness of the above approaches. Out of the four studies that measured sedentary behaviour, only two significantly decreased SB. Based on only two studies it is difficult to draw reliable conclusions on what elements were related to effectiveness. Notably, none of the trials measuring SB treated it as a separate behaviour, but rather as an indicator of insufficient PA levels. SB was measured objectively in only one of the studies (Slootmaker et al., 2010). The others relied on self-reported SB often indicated by time spent on the computer, viewing television or playing board games. The studies provided no descriptions of intervention strategies aimed specifically at changing SB, which made it impossible to identify the BCTs effective in reducing SB, and make a distinction with PA. The BCTs and alterations in the school context that may need to occur in order to decrease adolescents’SB may be quite different from the strategies needed to enhance PA. Ultimately, an intervention focusing on PA may not affect SB (e.g., if the focus of the intervention is on increasing the intensity of the PA). Conversely, an SB intervention may not affect health-enhancing MVPA if adolescents are encouraged to substitute sitting with standing or light-intensity PA. It is evident that more studies are needed that target intervention strategies to specifically decrease SB. Furthermore, in order to reliably identify the BCTs associated with PA and SB intervention effectiveness, the BCTs used in control groups, i.e. standard care, should be described in intervention reports and coded. Especially when the intervention is delivered during the PE class, it is difficult to draw conclusions on effective BCTs without knowing which BCTs are also part of standard care. Control group treatment differed widely in the 10 trials and was altogether insufficiently described in the studies. Neumark-Sztainer et al. (2010) described providing the control group with an all-girls PE class with mostly inactive participants. It is possible that this alone is quite a powerful intervention, deviating from 38 S-T. HYNYNEN ET AL. Downloaded by [Tampere University] at 22:47 08 June 2016 the standard mixed-gender PE, and may explain the lack of statistically significant differences in PA between intervention and control groups post-intervention. We recommend that future studies report BCTs used in both intervention and control groups. It is notable that four out of 10 interventions targeted females exclusively. Girls are indeed more in need of PA-promoting interventions, as they engage on average in less MVPA than boys (Sallis, Prochaska, & Taylor, 2000). However, boys generally spend more time on screen-based behaviours. Previous studies have shown that school-based PA interventions work better for girls than boys (Yildirim et al., 2011), which may be in part due to girls’low baseline MVPA levels. The limitations of our review are influenced by the number and quality of the studies included. In general, the methodological quality of the included studies was weak, with relatively small sample sizes and a high risk of bias. Only three studies reported objective measurement of PA (accelerometry, pedometers) and one study (Slootmaker et al., 2010) objectively assessed SB, posing a major reliability problem. Out of the seven studies that we classified as effective in increasing PA, four relied solely on self-report measures. Since self-report can be influenced by recall bias and social desirability bias, these findings need to be confirmed by objective measures. Another major limitation in this area, as noted in earlier systematic reviews as well (e.g., van Sluijs et al., 2007), is the lack of longterm follow-ups and, consequently, a lack of evidence regarding long-term effectiveness. Thirdly, delivering interventions only to volunteer participants expressing heightened interest in the programme (Lubans & Sylva, 2006; Mauriello et al., 2010) versus, for example, recruiting all students from a given classroom possesses a threat of positively biased results. It is quite evident that individuals who seek to participate in a PA intervention are more motivated to increase their level of PA than their age cohort in general. Also, because self-reported PA was the main outcome measure in most studies, it is possible that failure to blind participants to allocation might have resulted in differential effects of social desirability bias between intervention and control group participants. There was an apparent lack of quality in reporting the studies. Some of the studies were so superficially described that it was difficult to draw conclusions on intervention elements related to effectiveness; from some it was difficult to even tell who delivered the intervention. However, the inter-rater reliability of the coders was adequate. Finally, due to the small number of included studies and the heterogeneity of the outcome measures, we were not able to conduct a meta-analysis. Hence, it should be taken into account that the conclusions on associations and relationships between intervention components and intervention effectiveness presented in this review are based on a small number of studies and descriptive rather than quantitative analysis. The scarcity of reported studies in this age group and the fact that only three non-effective studies were found in the literature search also raises a serious question of possible risk of publication bias in this research field. Due to these factors, the conclusions drawn from this review regarding BCT effectiveness are tentative. This study has several implications for future research and practice. We recommend that future intervention studies use objective measures of PA and SB alongside self-report measures and use large enough sample sizes to allow for multi-level analyses to account for clustering within classes and schools. Furthermore, future trials should include longterm follow-ups and more precise descriptions of intervention content in terms of BCTs. The advantages of school-based PA and SB interventions include a captive audience and wide reach of the target group. As there is a marked drop in PA levels during INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 39 Downloaded by [Tampere University] at 22:47 08 June 2016 adolescence, and a high level of SB, this age group is an especially important target for public health efforts. Our review may help efforts to develop more effective interventions in this under-researched age group, having identified factors associated with effectiveness and crucial gaps in research that merit attention in future studies. First, for future intervention developers, we would point out the major lack of school-based intervention studies to decrease SB in this age group. Future studies ought to acknowledge that PA and SB are different target behaviours that require different intervention strategies. In our review, we identified promising BCTs that seem to be effective at least in the short term in school-based interventions to promote PA among older adolescents. It should be noted that interventions should not be deemed effective based on statistical significance only, but one should also examine whether the changes have public health or clinical significance. Few of the original studies made an explicit judgement, or assessed cost-effectiveness. Since our review found that interventions delivered via research staff were more effective than those delivered by school staff or other providers, we suggest that in future research careful process evaluation (Moore et al., 2015) is conducted to examine acceptability and fidelity of the intervention and to understand whether public health interventions can be rolled out successfully without researcher delivery. In addition, intervention developers should carefully select BCTs and other elements that would increase maintenance of PA over the long term, as so far no study has been able to demonstrate that their school-based intervention have long-lasting effects on older adolescents’PA. Since our review shows a lack of evidence in this target audience and behaviour, we suggest that developers look into other areas of behavioural science research where BCTs aimed at maintaining behaviour are being tested. In conclusion, this review found that there is limited evidence on how to best promote PA and reduce SB among older adolescents in school-based interventions in the long term. The method we used to analyse the content of interventions was helpful in identifying effective elements, which will benefit future intervention development work, ultimately improving adolescent activity behaviours. Disclosure statement No potential conflict of interest was reported by the authors. Funding The first author S-T. Hynynen was supported by the Ministry of Education and Culture [grant number 34/626/2012], and the Ministry of Social Affairs and Health [grant number: 201310238]; Finland. F. F. Sniehotta is funded by Fuse, the UK Clinical Research Collaboration Centre of Excellence for Translational Research in Public Health. 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