Effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among UK adolescents: A cluster randomised controlled trial.

BACKGROUND: Less than 20% of adolescents globally meet recommended levels of physical activity, and not meeting these recommended levels is associated with social disadvantage and rising disease risk. The determinants of physical activity in adolescents are multilevel and poorly understood, but the school's social environment likely plays an important role. We conducted a cluster randomised controlled trial to assess the effectiveness of a school-based programme (GoActive) to increase moderate-to-vigorous physical activity (MVPA) among adolescents. METHODS AND
FINDINGS: Non-fee-paying, co-educational schools including Year 9 students in the UK counties of Cambridgeshire and Essex were eligible for inclusion. Within participating schools (n = 16), all Year 9 students were eligible and invited to participate. Participants were 2,862 13- to 14-year-olds (84% of eligible students). After baseline assessment, schools were computer-randomised, stratified by school-level pupil premium funding (below/above county-specific median) and county (control: 8 schools, 1,319 participants, mean [SD] participants per school n = 165 [62]; intervention: 8 schools, 1,543 participants, n = 193 [43]). Measurement staff were blinded to allocation. The iteratively developed, feasibility-tested 12-week intervention, aligned with self-determination theory, trained older adolescent mentors and in-class peer-leaders to encourage classes to conduct 2 new weekly activities. Students and classes gained points and rewards for engaging in any activity in or out of school. The primary outcome was average daily minutes of accelerometer-assessed MVPA at 10-month follow-up; a mixed-methods process evaluation evaluated implementation. Of 2,862 recruited participants (52.1% male), 2,167 (76%) attended 10-month follow-up measurements; we analysed the primary outcome for 1,874 participants (65.5%). At 10 months, there was a mean (SD) decrease in MVPA of 8.3 (19.3) minutes in the control group and 10.4 (22.7) minutes in the intervention group (baseline-adjusted difference [95% confidence interval] -1.91 minutes [-5.53 to 1.70], p = 0.316). The programme cost £13 per student compared with control; it was not cost-effective. Overall, 62.9% of students and 87.3% of mentors reported that GoActive was fun. Teachers and mentors commented that their roles in programme delivery were unclear. Implementation fidelity was low. The main methodological limitation of this study was the relatively affluent and ethnically homogeneous sample.
CONCLUSIONS: In this study, we observed that a rigorously developed school-based intervention was no more effective than standard school practice at preventing declines in adolescent physical activity. Interdisciplinary research is required to understand educational-setting-specific implementation challenges. School leaders and authorities should be realistic about expectations of the effect of school-based physical activity promotion strategies implemented at scale. TRIAL REGISTRATION: ISRCTN Registry ISRCTN31583496.

RCT Entities:   Population Interventions Outcomes

Introduction

Physical inactivity is the fourth largest cause of death worldwide and is thought to be the principal cause of 1 in 3 cases of heart disease [1]. In adolescence, physical activity levels are low. Recent data show that less than 20% of adolescents meet the WHO physical activity guidelines of 60 minutes of moderate-to-vigorous physical activity (MVPA) every day, with little change over time [2]. Not only is inactivity increasingly linked to poor health in childhood [3], it may have long-lasting negative implications for health and educational achievement in adulthood [4,5]. Compared to their inactive peers, active adolescents are more likely to become active and healthy adults [4,6-11], and as such, preventing a decline in activity during adolescence is a major public health priority [1]. The challenge for public health professionals is to identify effective and cost-effective strategies to achieve this.

Evidence suggests that the reduction in physical activity in adolescence predominantly occurs outside of school [12]. School settings offer a way of reaching large numbers of young people from a broad range of backgrounds, and it therefore remains pragmatic and attractive to utilise the school setting for recruitment and delivery of physical activity promotion targeting the whole week [13]. Despite this, physical activity promotion research in adolescent populations is scarce and challenging, with review-level evidence showing no effect on device-measured physical activity and few studies in children over 12 years of age [14,15]. This lack of effect is hypothesised to be due to low intervention fidelity and poor implementation. Studies of the cost-effectiveness of school-based physical activity promotion report mixed results (e.g., [16,17]). As school funders are faced with finite resources, there is a continued need for the identification of effective and affordable school-based activity promotion strategies among older adolescents to inform the best use of limited funds.

Best practice guidelines suggest intervention development should be based on behaviour change theory, existing evidence, and pre-trial qualitative work with the target group [18]. Following our review of existing school-based strategies [19] and novel analyses of existing data [20], we identified limitations of previous adolescent physical activity promotion strategies including a lack of whole-population approaches, limited adolescent involvement in intervention development, poor participant engagement, and lack of consideration of potential negative impacts [13]. We have previously reported on the development and pilot work of the GoActive (Get Others Active) intervention, in which we aimed to address these limitations [13,21]. GoActive employs a population approach, in that it targets a whole year group irrespective of personal characteristics, to overcome the potential stigma of solely targeting at-risk groups [22], such as adolescents with obesity, or girls. Although GoActive is broadly aligned with self-determination theory [23], our priority was to co-design the intervention with students and teachers. Therefore, we used theory flexibility to enable the incorporation of components strongly suggested in the development work, irrespective of whether they aligned with theory, such as rewards [13].

The objective of this paper is to report on the results of the GoActive cluster randomised controlled trial, which aimed to evaluate the effectiveness and cost-effectiveness of the GoActive intervention to increase whole-day MVPA among adolescents aged 13–14 years.

Methods

Study design and participants

The main trial methods have been described in the published protocol paper [24]. All state-run secondary schools in Cambridgeshire and Essex were eligible for inclusion (n = 103) and were invited into the study between April and July 2016. The region includes substantial socioeconomic diversity and includes both urban and rural areas. In participating schools, school-level written informed consent was obtained from a member of the school’s senior leadership team following a meeting between GoActive team members and senior school staff; all students within Year 9 in the 2016–2017 academic year were eligible for inclusion. Ethical approval was obtained from the University of Cambridge Psychology Ethics Committee (PRE.126.2016), and included approval to obtain passive parental consent and written student assent for study participation. The study was prospectively registered (ISRCTN31583496).

Baseline assessments took place early in Year 9 (September 2016–January 2017, with 76% of testing between November and January), the school year in which students become 14 years old. After baseline measurements, participating schools were randomised to the intervention or no-treatment control arm. Allocation used a randomisation list prepared in advance by the trial statistician independent from the measurement team using a random number generator in Stata; 1:1 randomisation was stratified by school-level percentage of students eligible for pupil premium school funding (below or above the county-specific median) and county (Cambridgeshire or Essex). Pupil premium funding, used as a proxy for school-level deprivation, is school funding that aims to reduce effects of deprivation [25].

GoActive intervention

The GoActive intervention was developed following an evidence-based iterative approach, underpinned by principles central to multiple guidelines and frameworks [26-28], where we incorporated existing evidence and qualitative work with adolescents and teachers [13]. GoActive aimed to increase physical activity through increased peer support, self-efficacy, self-esteem, and friendship quality, and was implemented in tutor groups using a student-led tiered-leadership system. Mentorship and peer-leadership addressed time pressures, which were stated by teachers in our development work as being a barrier to participation in activity promotion programmes, and between-class competition was incorporated as a strategy to encourage teacher enthusiasm [13].

The mapping of intervention components to published behaviour change techniques has been published in previous GoActive papers [24,29], and an overview of key intervention elements and delivery structure is available in S1 Text and S1 Fig. Briefly, each Year 9 tutor group (class or homeroom) chose 2 activities each week from a selection provided. GoActive targeted peer-led class-based activity, with participation also encouraged outside of school. Working with existing class tutors (members of teaching staff), older adolescent mentors encouraged Year 9 students to try at least 1 weekly GoActive session. Activity points were gained for activity participation in and outside of school irrespective of duration or intensity; students were encouraged to regularly log ‘activity points’ on the GoActive website to unlock rewards. The GoActive intervention was delivered over 12 weeks. During the first 6 weeks, delivery was facilitated by intervention facilitators (health trainers employed by local councils), who provided school staff and older adolescent mentors with training, support, and resources for intervention delivery. Facilitator support for the programme was reduced during the second 6 weeks to encourage school-led sustainability.

Irrespective of whether students participated in measurements, intervention delivery was at a school tutor group level to all eligible students in intervention schools; parents were encouraged to speak with the school if they wanted to opt their child out of the intervention participation, but no parents chose this option. Control schools received no intervention.

Outcome assessment

Identical assessment procedures were undertaken at baseline, post-intervention (14–16 weeks post-baseline), and the 10-month post-intervention follow-up in the school. Questionnaire-based measures were also assessed mid-intervention (6 weeks after intervention start). Trained measurement staff conducted measurements using standardised protocols and instruments as detailed in the protocol [24] and summarised in S1 Table. Measurement staff were blinded to allocation, and our dedicated process evaluation researcher independently verified the success of this blinding via email correspondence shortly after the 10-month follow-up measurements.

Accelerometer-assessed outcomes (including primary outcome)

The pre-specified primary outcome for effectiveness was average daily minutes of MVPA at 10-month follow-up. We measured MVPA at baseline, post-intervention, and 10-month follow-up using wrist-worn activity monitors (Axivity) assessing acceleration (continuous waveform data). Participants were asked to wear the monitors for 7 days continuously, for 24 hours a day, on their non-dominant wrist. These monitors have been validated to assess physical activity energy expenditure [30] and have better wear time adherence and acceptability than commonly used hip-worn monitors among adolescents [31]. Given the 24-hour wear time protocol of the Axivity monitors, a diurnal adjustment was used to reduce any bias caused by imbalances of protocol deviations regarding non-wear [32]. Each day of possible wear was divided into 4 time quadrants: morning (6 AM–12 PM), afternoon (12 PM–6 PM), evening (6 PM–midnight), and night (midnight–6 AM). For participants to be included in analyses, over 6 hours of wear time spread over at least 2 days was required from the possible 42 hours in each day time quadrant (i.e., ≥6 hours from 7 possible mornings, ≥6 hours from 7 possible afternoons, and ≥6 hours from 7 possible evenings). The ‘night’ quadrant (i.e., midnight–6 AM) was considered as sleep time and was included in the denominator when calculating daily averages of MVPA, for consistency across all participants. Where individuals did not wear the monitor for ≥6 hours at night time, despite the protocol requesting them to wear it continuously for 7 days, average night time values were imputed using population averages (n = 91 at baseline and n = 463 at follow-up), created from GoActive participants with 100% protocol compliance regarding monitor wear, to avoid inflation of MVPA estimates. This method was verified by running simulations excluding night data for a subsample of participants with 100% protocol compliance. For an individual hour to be included for analysis, at least 70% of possible wear time was required, with non-worn time within the hour considered as missing [32].

Monitor output was processed to provide minutes spent in MVPA equivalent to ≥2,000 ActiGraph counts per minute (cpm) [24]. Additional secondary accelerometry-derived outcomes were average daily minutes of sedentary time (equivalent to ≤100 ActiGraph cpm), average daily minutes of light physical activity (equivalent to 101–1,999 ActiGraph cpm), and average daily activity (represented by average acceleration). In addition to daily averages, all intensity outcomes (including MVPA) were also derived during school time (9 AM–3 PM), during weekday after school time (after 3 PM), and at weekends. Participants who met the inclusion criteria for average daily MVPA were included in any analyses for which they had sufficient data (≥2 days) [17]. As the criteria for deriving average daily MVPA did not require both weekend and weekdays of valid data [33], participant numbers varied by outcome.

Non-accelerometry secondary outcomes

Student questionnaires were administered at each measurement occasion (baseline, post-intervention, and 10-month follow-up) using measures validated for use in the population. All secondary outcomes were assessed as continuous scores: physical activity self-efficacy (possible score 1–6) [34], social support for activity (1–4) [35], friendship quality (1–5) [36], well-being (1–5) [37], self-esteem (1–4) [38], and self-reported physical activity (0–160) [39]. Anthropometry (height, weight, waist circumference, and bio-impedance to assess body fat percentage) was assessed at baseline and 10-month follow-up by trained staff; BMI standard deviation score (BMI SDS) was calculated from height, weight, age, and gender [40]. BMI SDS was also used to establish weight categories. S1 Table provides further details on assessment and scoring of secondary outcome measures. As a change to the published protocol, anthropometry was not assessed immediately post-intervention to reduce measurement burden on schools and participants and because no meaningful impact on anthropometry was expected short-term.

Process evaluation measures

The implementation of the programme in each school was assessed through a mixed-methods process evaluation. Full details are available in the published process evaluation protocol [41]. The qualitative component included focus groups with students and mentors; individual interviews with students, facilitators, and contact teachers; and observations of GoActive sessions. Process evaluation questions were embedded into the outcome questionnaires, and were completed by students, mentors, teachers, and facilitators at all follow-up time points. Initial findings from student perspectives were published prior to analysing intervention efficacy to avoid interpretation bias [29], and full triangulation results will be published separately. For the purposes of the current paper, process evaluation questionnaire data were used to assess programme satisfaction (see S2 Table for details). Logging of activity points was tracked using website analytics from the GoActive website.

Demographic characteristics

Participant descriptive characteristics, including pre-specified effect modifiers (gender, individual socioeconomic position, and ethnicity) were self-reported. Ethnicity was self-reported by participants, who were given 20 response options and additional free text completion options. For descriptive purposes, the reported values were recoded to 5 categories according to recommendations [42] as ‘white’, ‘mixed ethnicity’ (identifying with multiple ethnicities), ‘Asian’ (including South-Asian and Chinese), ‘African and/or Caribbean’, and ‘other’. Ethnicity was subsequently dichotomised for pre-specified moderation analyses (‘white’ versus remaining categories). Participants completed 6 items from the Family Affluence Scale (FAS) relating to family car ownership, holidays, computers, availability of bathrooms, dishwasher ownership, and having their own bedroom, which were used as a proxy of individual socioeconomic position by summing answers (possible range 0–13), and dividing into predefined affluence groups (low = 0–6, medium = 7–9, high = 10–13) [43,44].

Economic evaluation

A within-trial cost-effectiveness analysis comparing the GoActive intervention with control was conducted from the perspective of the school funder (i.e., school or local authority budget). The reported costs therefore represent the likely costs to a local authority were it to implement the GoActive intervention.

Cost per school and per participant was calculated for intervention group participants and comprised facilitator time input and travel expenses, materials (Quick Cards, sports equipment, and rewards and prizes), and teacher time. Staff time inputs were based on the study protocol. Unit costs were based on the mid-point of national pay scales (facilitator and teacher time input), and study financial returns (expenditure on materials and expenses). All costs are reported in 2019 British pounds. There were £0 costs associated with the control arm.

Quality-adjusted life years (QALYs) were assessed using the UK Child Health Utility 9D (CHU-9D), which has been validated for use in adolescents [45] and was included in the participant questionnaire at baseline, post-intervention, and 10-month follow-up. Total time from baseline to 10-month follow-up, and hence the time horizon for the study, was approximately 2 academic years.

Sample size

We estimated that 1,310 Year 9 participants would be required to have 85% power to detect a 5-minute difference in change in MVPA between baseline and 10-month follow-up as significant at the 5% level [24], assuming a standard deviation of MVPA of 17.8 minutes and a correlation of 0.59 between baseline and follow-up [21]. Assuming a within-school (intraclass) correlation of 0.034 [46] and 30%–40% loss to follow-up [15,47], we aimed to recruit 16 schools with 150 participants per school.

Statistical analysis

The statistical analysis plan was approved by the trial steering committee prior to analyses being performed (http://www.mrc-epid.cam.ac.uk/research/studies/goactive/for-researchers/). All analyses were performed using Stata version 15.1 [48]. For MVPA at 10-month follow-up (the primary outcome), the intervention effect, representing the baseline-adjusted difference in change from baseline between the intervention and control groups, was estimated from a linear regression model including randomisation group, baseline value of the outcome (i.e., analysis of covariance [ANCOVA]), and the randomisation stratifiers (pupil premium funding and county). Robust standard errors were calculated to allow for the non-independence of individuals within schools, and the missing indicator method [49] was used to ensure inclusion of participants with a missing baseline value of the outcome variable. All secondary outcome variables were analysed using the same method.

For the primary outcome, effect modification by (1) gender, (2) socioeconomic status (medium or low versus high, according to FAS score), (3) ethnicity (white versus any other ethnic background), (4) baseline physical activity (≥60 minutes MVPA/day versus <60 minutes), and (5) weight status (with underweight or normal weight versus with overweight or obesity) was tested with an F-test of the relevant multiplicative interaction parameter in the ANCOVA model. Effect modifiers were selected based on previous evidence of potential differential effects [14,15]. Subgroup analyses were performed within all categories defined by these variables.

We conducted a complete-case analysis in which participants and schools were included in the group to which they were randomised, although participants with a missing value of an outcome at follow-up were excluded from the analysis of that particular variable. This is a complete-case analysis that is valid under the assumption that the outcome is missing at random, conditional on randomised group and the baseline value of the outcome [50]. A further analysis of the primary outcome was performed in a per-protocol population, defined as intervention group participants reporting “being active during tutor times at least twice during the last 2 weeks” (i.e., self-reported intervention engagement mid-intervention [week 6 of the intensely facilitated phase of the intervention]) and logging activity points on the study website at least once during the whole intervention period. This definition was based on a review of quantitative process evaluation data prior to the main analyses, and reflects the group with highest intervention engagement as opposed to delivery of the protocol with fidelity.

Post hoc sensitivity analyses recommended by the trial steering committee were performed in which the primary outcome was calculated (1) excluding time between midnight and 6 AM and (2) using a stricter inclusion criterion for wear time of 12 hours of wear per quadrant.

Economic analyses comprised calculation of within-trial additional cost per additional daily minute spent in MVPA and additional cost per additional QALY gained over the time horizon. An adjusted analysis included baseline CHU-9D score as a covariate as well as missing data imputed using multiple imputation.

Results

Fig 1 shows the study flow chart. The team approached 103 schools; most did not respond despite multiple re-contacts. Sixteen schools were initially recruited, 2 dropped out before baseline measurements due to changes in the senior leadership team (1 from Essex and 1 from Cambridgeshire), and replacements were recruited. Of 3,405 Year 9 students eligible for inclusion across all participating schools, 2,862 (84.1%) consented: 1,319 participants at 8 control schools (mean ± SD participants per school: n = 165 ± 62), and 1,543 participants at 8 intervention schools (n = 193 ± 43). A total of 2,828 (98.8% of those consenting) completed baseline questionnaires, and 2,638 (92.2% of those consenting) had a valid assessment of the primary outcome at baseline. At 10-month follow-up, 2,167 (75.7%) participants attended, and we obtained a valid measure of primary outcome for 1,874 of 2,862 (65.5%) randomised participants. More females and participants with high socioeconomic background, from Cambridgeshire, and with underweight or normal weight provided primary outcome data (S3 Table). Blinding of measurement staff was largely successful (S4 Table); a few cases of unblinding occurred due to student and teacher interaction during measurement sessions.

Fig 1

GoActive study flow chart.

Baseline characteristics were similar between randomised groups (Table 1). Overall, mean age was 13.2 (SD 0.2) years, 52.1% were male, and 84.7% self-reported as white.

Table 1

Baseline characteristics by randomised group: GoActive trial.

Characteristic	Controln = 1,319			Interventionn = 1,543
	Percent missing	Mean or percent	SD or n	Percent missing	Mean or percent	SD or n
Age (years)	0.0	13.2	0.4	0.0	13.2	0.4
BMI SDS	0.0	0.2	1.6	0.0	0.1	1.9
Body fat (%)	3.9	20.7	10.0	5.4	20.9	9.9
Waist circumference (cm)	0.5	70.0	9.6	0.6	70.4	9.7
Gender	0.0			0.0
Male		53.4%	704		51.1%	788
Female		46.6%	615		48.9%	755
Ethnicity	1.1			1.3
White		86.1%	1,135		83.5%	1,288
Mixed (identifying with multiple ethnicities)		6.2	82		6.3%	97
Asian (including South-Asian and Chinese)		3.2%	42		4.3%	66
African and/or Caribbean		2.2%	29		2.7%	41
Other		1.3%	17		2.0%	31
Family socioeconomic status	0.8			1.0
Low		11.0%	145		16.3%	252
Medium		40.6%	536		43.4%	669
High		47.6%	628		39.3%	606
Weight status	1.4			2.7
With underweight		2.6%	34		2.1%	33
With normal weight		68.5%	903		66.4%	1,025
With overweight		19.2%	253		18.5%	285
With obesity		8.3%	110		10.2%	158
County	0.0			0.0
Cambridgeshire		58.8%	775		42.4%	654
Essex		41.2%	544		57.6%	889
Pupil premium funding	0.0			0.0
Low		47.6%	628		49.2%	759
High		52.4%	691		50.8%	784

BMI SDS, BMI standard deviation score.

Primary outcome

Mean accelerometer-assessed MVPA decreased in both randomised groups between baseline and 10-month follow-up. The reduction was slightly larger in the intervention group, although the confidence interval around the intervention effect was wide and inconclusive (Table 2; Fig 2).

Table 2

Results for primary outcome of the GoActive trial: Average daily moderate-to-vigorous physical activity (MVPA, in minutes/day) at 10-month follow-up.

Measure	Control			Intervention			Intervention versus control between-group difference, B (95% CI)
	Baseline	10 months	Change from baseline	Baseline	10 months	Change from baseline
n	1,224	871		1,414	1,003
Mean (SD)	35.6 (18.9)	27.6 (20.6)	−8.3 (19.3)	35.6 (18.3)	25.6 (21.5)	−10.4 (22.7)	−1.91 (−5.53, 1.70)

Between-group difference (intervention effect) is the baseline-adjusted difference in mean change (baseline to 10-month follow-up) in average daily minutes of MVPA between the intervention and control group. Change from baseline calculated based on those with follow-up data (28.8% of control participants and 29.1% of intervention participants had missing data at follow-up). Difference is estimated from a linear regression model including parameters for randomised group (control, intervention), baseline value of the outcome (i.e., analysis of covariance), pupil premium funding (low, high), and county (Cambridgeshire, Essex). Robust standard errors were calculated to allow for non-independence of individuals within schools. Missing indicator method is used to enable participants with a missing baseline value of the outcome to be included in the analysis. Participants with a missing value of the outcome at 10-month follow-up are excluded from this analysis.

Fig 2

Intervention effect on continuous secondary physical activity outcomes in minutes per day (acceleration in milli-g).

Light, light-intensity activity; MVPA, moderate-to-vigorous physical activity; Sed, sedentary.

Secondary outcomes

In the whole population, over the duration of the study, overall time spent sedentary increased, and light physical activity decreased (S5 Table). There was no evidence of an intervention effect on average daily accelerometer-based outcome measures post-intervention or at 10-month follow-up (S6 Table; S7 Table). Time-specific accelerometry-based outcomes showed that on schooldays (weekdays) changes over time were more favourable in the control group (both during school and after school), while at weekends more favourable changes were observed in the intervention group, particularly at 10-month follow-up (Fig 2; see S2 Fig for post-intervention effects and S6 Table and S7 Table for full details).

Self-reported physical activity declined over the duration of the study, whereas little change over time was observed for self-efficacy, social support, friendship quality, well-being, and self-esteem (S5 Table). Overall, the intervention did not affect self-reported outcomes (including assessment of harm assessed using well-being) or anthropometry (Fig 3), with the exception of higher self-efficacy among intervention participants post-intervention (see S8 Table for full analytical results).

Fig 3

Intervention effect on secondary psychosocial and anthropometric outcomes presented as baseline-adjusted differences and 95% confidence intervals.

BMI SDS, BMI standard deviation score.

Effect modification

Tests for effect modification indicated differences in the effect of the intervention between subgroups, in particular between boys and girls, and between high and medium/low socioeconomic status (S9 Table). The results of the subgroup analyses suggested a negative intervention effect among boys and a positive intervention effect for those with low and medium socioeconomic status. However, the subgroup results are inconclusive as confidence intervals included 0 (Fig 4).

Fig 4

Intervention effect on primary outcome—overall and within subgroups.

MVPA, moderate-to-vigorous physical activity; SES, socioeconomic status.

Per-protocol and sensitivity analyses

Only 382 intervention group participants (24.8% of those recruited at baseline and randomised to intervention) met the criteria for inclusion in the per-protocol analysis. The results of the per-protocol analysis did not differ from those of the complete-case analysis (S10 Table). Post hoc sensitivity analyses indicated that results were unaffected by participants with missing data (S2 Text) or different approaches to data processing decisions (S11 Table).

Process evaluation outcomes

Fidelity of the intervention was mixed both within and between schools; 37.9% of students reported attending a GoActive session in the last fortnight post-intervention (ranging from 11.6% to 64.2% between schools). Of students attending baseline assessment and randomised to the intervention group, 46.5% entered activity points using the website. Quantitative data indicated that 7 of 8 intervention schools had mentors, and students at all schools reported having in-class peer-leaders. With regards to satisfaction, 62.9% of students reported that GoActive was fun, 70% of teachers reported that they enjoyed facilitating it, and 87.3% of mentors said it was fun. Session observations and interview data contradicted the effective incorporation of mentors and peer-leaders reported by schools and students. In interviews and focus groups, teachers and mentors discussed that their roles in programme delivery were sometimes unclear. Qualitative data also revealed that the GoActive programme was not consistently implemented within and across schools.

Adverse events

One participant (in the intervention group) reported an unrelated hospital admission during the baseline measurement period.

The cost of delivering the intervention was estimated to be £2,520 per school compared with control schools; the average cost per student was £13.06 (S12 Table; S13 Table). The mean (SE) QALYs accrued was 1.242 (0.005) in the intervention group versus 1.244 (0.005) in the control group (difference adjusted for baseline data −0.006 [95% CI −0.017 to 0.005]) (S14 Table).

Discussion

The results of the GoActive trial show that all adolescents became less physically active over time, with no difference between those exposed to the GoActive intervention and those who attended normal school activities. There were inconclusive indications of a more negative effect among boys and a more favourable effect for adolescents with low and medium socioeconomic status. Secondary physical activity outcomes showed differential impact across weekdays and weekends, with small between-group differences favouring the control group on weekdays for light physical activity and sedentary time. The findings also indicate that the GoActive intervention is not cost-effective, and that intervention implementation was variable. There was no evidence that the intervention negatively impacted well-being.

Our findings are in line with results from recent reviews suggesting limited effectiveness of research-driven physical activity promotion interventions on whole-day MVPA [14,15]. The absence of intervention effect on time spent in MVPA could be partly due to inadequate implementation; the per-protocol population was small, and our initial process evaluation findings indicate that some intervention components, such as mentorship, were not adequately implemented [29]. However, the per-protocol analysis produced similar results to the main analyses, indicating that if the intervention had been implemented with higher fidelity, it may still not have been effective at a whole-population level. The per-protocol definition focused on website use and reported activity sessions. Use of the website was low and contrasts with the high engagement observed in the pilot trial [21], which indicated preliminary effectiveness. This pattern is common in behavioural interventions, with 75% lower effectiveness seen for behavioural interventions across various health behaviours at the full trial stage compared to feasibility and pilot testing [51]. This is thought to be at least partly due to adaptations needed to implement programmes at scale. Since its inception, GoActive has been designed to be scalable by including a website and flexibility for use in multiple school structures. However, implementation difficulties may have arisen from the provision of implementation flexibility for schools—an issue also identified in the Girls Active study [17]—as well as a lack of clarity in the conceptualisation of the mentor and teacher roles. Additionally, the delivery agent of the intervention changed between the pilot (research staff) and full trial (local-authority-funded health trainer, supported by the research team), which may have contributed to the reduced effectiveness. This points to the challenge for researchers to design interventions that are scalable at the outset, which would minimise the need for major adaptions.

It has been suggested that for a school-based intervention to work, it needs to include a mechanism from at least 1 category outlined in the Theory of Expanded, Extended, and Enhanced Opportunities [52]; the GoActive intervention targeted 2 of these. The ‘expansion’ mechanism suggests providing new occasions to be active by replacing sedentary time with physical activity, such as adding activity to previously sedentary tutor times. Another suggested mechanism implemented in GoActive is ‘extension’, which suggests lengthening the time currently allocated to activity, such as by encouraging students to be active out of school and in tutor times [52]. Process evaluation revealed that the GoActive programme was not consistently implemented and therefore may not have led to sufficient expansion or extension of student activity provision. Low intervention fidelity has implications for the conclusions drawn. If the intervention was either not delivered or not engaged with by students as intended, then no matter how robust the trial design, methods, and analysis, they only give certainty to the findings pertaining to a low-fidelity intervention. As such, in concluding that the intervention was not effective, there is a caveat that it was not effectively delivered.

Secondary outcomes suggested a negative impact of the intervention on light physical activity and sedentary time on weekdays (both in school and out of school), with the opposite seen on weekends. Adolescent-focused process evaluation results indicate that, at times, the intervention may have fostered a climate that was not conducive to physical activity within school (e.g., the sessions appeared to have a lack of social cohesion and connection, and activity choice was often dominated by boys) [29]. However, this may not have extended to weekends. One of the main aims of GoActive was to use school time to encourage participation in activities with friends and family outside of school. On a population level, most of the decline in physical activity during adolescence happens on weekends [12,46]; therefore, it would be worthwhile teasing out what intervention components may be associated with weekend activity. The negative findings for light physical activity and sedentary time on weekdays were reversed for weekends; these opposing associations largely cancelled each other out, leading to no effect for daily averages, with the intervention not appearing to increase activity of higher intensity (i.e., MVPA).

The effect modification analyses suggest that the intervention differentially impacted population subgroups. The intervention appeared to have a more negative effect among boys, as well as those reporting high socioeconomic position. These findings contrast with results from a recent review, which showed no difference between subgroups for intervention effectiveness when assessing whole-day MVPA; however, this was mainly in primary-school-based studies [14]. Across subgroups, our results provide a tentative suggestion of a narrowing of inequalities in physical activity levels, as boys are often reported to have higher activity levels than girls [53], although differences in activity levels by socioeconomic position are less clear [54,55]. The unfavourable impact among boys for average daily MVPA contrasts with our insights from the mixed-methods process evaluation paper exploring satisfaction with the dose received. This evaluation reported higher intervention acceptability among boys, and found that activity choice appeared to be largely driven by boys [29]. These results indicate that gender differences in intervention delivery may not have manifested as expected regarding intervention effect. These contrasting results reinforce the importance of a thorough process evaluation, including observations of delivery, and highlight the complexity of psychosocial issues surrounding activity promotion.

The GoActive intervention appeared to be more effective among individuals with low socioeconomic position, in contrast to a recent meta-analysis showing no differential effectiveness by socioeconomic position [14]. Despite the fact that evidence regarding socioeconomic differences in activity levels is equivocal [55], individuals with lower socioeconomic position may do less vigorous-intensity activity [56] and may have less opportunity for a variety of structured activities [57]. This lack of equity contributes to health inequalities throughout the life course [58], and reducing health inequalities in behaviours and health is therefore a public health priority [59]. It is possible that individuals of low socioeconomic position may have particularly benefited from the chance to try a variety of activities in GoActive as the opportunities may not have been available to them otherwise. There appears to be some utility of comprehensive school physical activity interventions for increasing adolescents’ physical activity behaviour, particularly in disadvantaged neighbourhoods, and such interventions could be particularly relevant among certain population groups [60].

Physical activity across both groups decreased by 10 minutes/day over 2 school years, reflecting the population-level decline seen in physical activity over adolescence [13,61]. Even at baseline, the average activity level of participants was half of the recommended 60 minutes per day, potentially increasing the risk of poor health in the future. It is important to continue to try to increase, or at least prevent the decline of, physical activity among adolescents on a population level, and schools remain a convenient way to reach large numbers of adolescents in one place. However, given limitations in resources and time in school, there may be insurmountable barriers to this approach. UK schools now have very tight budgets, and, given statutory requirements, the additional curriculum time they can allocate to each subject or activity is constrained. Evidence suggests that the majority of the physical activity decline in adolescence occurs out of school, and it has been suggested that the structured nature of the school day may already be somewhat protective of maintaining activity levels [62]. Given the limited success of most school-based interventions in increasing objectively measured whole-day physical activity [14,15], higher level structural changes based on a more in-depth understanding of how physical activity is best integrated in the school, appears increasingly worthwhile.

Strengths and limitations

We recruited a population representative of the East of England, and our results are relevant to many schools across the UK and to many other high-income settings. Limitations include the adolescent-reported measure of socioeconomic status and the relative lack of participants of low socioeconomic status and non-white participants. However, the percentage of pupils eligible for pupil premium funding in the participating schools was similar to the East of England average (20.9% versus 22.7%) [63]. Moreover, the ethnic diversity of the participants was similar to that of England and Wales (86.1% versus 87.4% white) [64]. Device-measured MVPA as the primary outcome aligns with public health research recommendations for objective and comprehensive evaluation of health promotion programmes [65]. Our recruitment to measurement sessions was high, with 84% of eligible pupils measured at baseline. Although retention on the primary outcome at 10-month follow-up could be perceived as a limitation, we achieved our intended sample size, and the proportion of participants with valid data at follow-up is comparable to that of similar trials [15,47]. To our knowledge, this effectiveness trial was the largest with device-measured physical activity, and addressed many weaknesses of previous trials by including iterative development with the target group and school stakeholders, well-measured pre-specified outcomes, long-term follow-up, detailed process evaluation, and economic evaluation and by having sufficient statistical power to assess effectiveness. However, it is likely that an insufficient dose of the intervention was delivered to achieve the desired effect, and it therefore remains unclear whether the GoActive intervention, if delivered as intended, is effective in changing adolescents’ overall MVPA.

Implications for research

Taken together with recent reviews highlighting the lack of effectiveness of research-driven school-based physical activity promotion strategies [14,15], the current evidence suggests that school-based approaches on the whole do not work to increase adolescent physical activity. However, schools have massive potential to positively impact the health of young people. An overhaul of our approach to secondary-school-based physical activity promotion is needed to encourage school-driven approaches with support from the wider school system, through the use of frameworks such the Comprehensive School Physical Activity Program [66], the World Health Organization’s Health Promoting Schools [67], or the Creating Active Schools Framework [68]. It should be noted, however, that the utility and effectiveness of these frameworks has yet to be established comprehensively. A common feature of these frameworks is the importance of senior leadership buy-in. The GoActive intervention was not initiated by senior leaders, and in most cases their involvement was only for consent sign-off. This may indicate limited buy-in, which may have affected GoActive’s potential for effect.

Each school is a unique system with its own culture, and during this research the team experienced barriers to intervention implementation that varied on a school level due to what we often perceived as differences in school culture, ethos, or attitudes [29]. This led us to consider that a randomised controlled trial expecting the same intervention to be replicable, let alone effective, across multiple schools may be an unrealistic expectation and that perhaps aiming for success at a school-by-school level may be more realistic. Although schools are unique microenvironments, standardisation in approaches to every aspect of the curriculum is increasingly becoming normal practice, and appears welcome in schools. There is a need to pursue real and interdisciplinary understanding and collaboration that is likely to deviate from the path of subject-specific research agendas. This should lead to a deeper understanding of the educational system and culture, and may require a shift in the field’s ideological principles on physical activity interventions and their delivery in the educational system. Interdisciplinary techniques and disciplines such as ethnography, education, anthropology, sociology, and social networks could progress further understanding of the cultural context of physical activity behaviour in the educational setting.

Implications for practice

Physical activity promotion initiatives are proliferating throughout schools worldwide without evidence adequately assessing effect or potential harms [69,70]. However, the simplicity of such initiatives has achieved what many designers of complex school-based physical activity interventions aspire to in terms of scale-up, reach, and adoption, and there is also a lot to be learnt from them. Our results from this rigorous and honest evaluation may be uncomfortable, but they highlight the importance of thorough testing of outcomes and unexpected negative consequences and could serve as a warning to those wishing to implement interventions without a candid evaluation. Current research-led approaches to school physical activity promotion do not appear to be effective in their current forms and are unlikely to lead to population-level changes in adolescents’ behaviour [14]. The GoActive intervention was rigorously designed with students and teachers and iteratively tested and refined, but despite this rigorous and costly process, when implemented at scale it was no better than the normal school curriculum at preventing declines in adolescent physical activity. We recommend that authorities are cautious about commissioning and rolling out school-based health promotion strategies, that potential unintended negative consequences are considered, and that they are realistic about the scale of behaviour change that can be achieved at a population level and the challenges of implementing a programme as intended.

Conclusion

The GoActive school-based intervention was not effective in countering the age-related decline in adolescent physical activity. Together with other recent evidence, this suggests that current research-driven approaches to school-based adolescent physical activity promotion are not effective, with implementation challenges likely playing an important role in the lack of effect. Interdisciplinary research should seek to further understanding of the cultural context of physical activity behaviour in the educational setting. Funders, researchers, and local authorities should be realistic about expectations of the effect of school-based adolescent physical activity promotion strategies implemented at scale.

(DOC)

Click here for additional data file.

GoActive tiered delivery system.

(DOCX)

Click here for additional data file.

Intervention effect on continuous secondary physical activity outcomes at post-intervention.

(DOCX)

Click here for additional data file.

GoActive study outcomes.

(DOCX)

Click here for additional data file.

Reported items of GoActive process evaluation (post-intervention questionnaires).

(DOCX)

Click here for additional data file.

Pattern of missing data in the primary outcome (accelerometer-assessed MVPA at 10-month follow-up).

(DOCX)

Click here for additional data file.

GoActive blinding summary.

(DOCX)

Click here for additional data file.

GoActive trial primary and secondary outcomes at baseline, post-intervention, and 10-month follow-up.

(DOCX)

Click here for additional data file.

Secondary outcome results for the GoActive trial: Average daily physical activity (minutes/day) at post-intervention.

(DOCX)

Click here for additional data file.

Secondary outcome results for the GoActive trial: Average daily physical activity (minutes/day) at 10-month follow-up.

(DOCX)

Click here for additional data file.

Secondary outcome results for the GoActive trial: Psychosocial and anthropometric outcomes.

(DOCX)

Click here for additional data file.

Effect modification of the primary outcome, average minutes of MVPA/day.

(DOCX)

Click here for additional data file.

Primary outcome of the GoActive trial, average minutes of MVPA/day in per-protocol population.

(DOCX)

Click here for additional data file.

Post hoc sensitivity analyses with different pre-processing decisions regarding primary outcome data.

(DOCX)

Click here for additional data file.

Protocol-based costing per school per year.

(DOCX)

Click here for additional data file.

Conversion from cost per school to cost per student.

(DOCX)

Click here for additional data file.

Quality of life (assessed with CHU-9D): QALYs gained.

(DOCX)

Click here for additional data file.

Key elements of GoActive intervention.

(DOCX)

Click here for additional data file.

Impact of deviations from the missing at random assumption on the results for the primary outcome.

(DOCX)

Click here for additional data file.

11 Feb 2020

Dear Dr Corder,

Thank you for submitting your manuscript entitled "Effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among adolescents: a cluster randomised controlled trial" for consideration by PLOS Medicine.

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14 Apr 2020

Dear Dr. Corder,

Thank you very much for submitting your manuscript "Effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among adolescents: a cluster randomised controlled trial" (PMEDICINE-D-20-00312R1) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

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Requests from the editors:

* Please structure your abstract using the PLOS Medicine headings (Background, Methods and Findings, Conclusions).

* Please combine the Methods and Findings sections into one section, “Methods and findings”.

Background- please briefly mention reasons for low physical activity in adolescents

Methods

Please clarify 84% eligible students?

Please provide additional demographics- like gender?

Please clarify if both Cambridgeshire and Essex schools participated and consider revising the sentence for clarity.

In the last sentence of the Abstract Methods and Findings section, please describe the main limitation(s) of the study's methodology.

Please replace the interpretation section with conclusions

Abstract Conclusions:

* Please address the study implications without overreaching what can be concluded from the data; the phrase "In this study, we observed ..." may be useful.

* Please interpret the study based on the results presented in the abstract, emphasizing what is new without overstating your conclusions.

* Please avoid vague statements such as "these results have major implications for policy/clinical care". Mention only specific implications substantiated by the results.

* Please avoid assertions of primacy ("We report for the first time....")

Funding information should be moved to the funding section of the article meta-data

The Data Availability Statement (DAS) requires revision. For each data source used in your study:

a) If the data are freely or publicly available, note this and state the location of the data: within the paper, in Supporting Information files, or in a public repository (include the DOI or accession number).

b) If the data are owned by a third party but freely available upon request, please note this and state the owner of the data set and contact information for data requests (web or email address). Note that a study author cannot be the contact person for the data.

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At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

Introduction

References- please use square brackets throughout

“Compared to their inactive peers, active adolescents are more likely to

become active, healthy and successful adults”- I would recommend removing the word successful here. Your previous work is related to education so please rephrase.

Please include this information in the results section “Although the feasibility and pilot studies were not powered to determine effectiveness, preliminary effectiveness for our

intervention was suggested, with between-arm differences in objectively measured

physical activity at follow-up (difference in means 5.1 min/day (95% CI 1.1 to 9.2)(20).”

This information ought to be in the methods and/or discussion sections “The trial reported here overcame the limitations of much previous research(15) including

iterative development with the target group and school stakeholders, a sample size large

enough to detect a 5-minute difference in the primary outcome between intervention

and control groups, and assessment of long term effects of device-measured physical

activity”

Methods

Could you please mention if the passive mode of parental l consent was approved by the ethics committee?

Role of the funding source- please move this information to the financial disclosure section

Please ensure all questionnaires are cited or provided as SI files

Discussion

Please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion.

Please begin this section with “our results show..” or similar, especially at the start of the sentence “The GoActive intervention is not cost-effective”

You mention focus group interviews here but these are not fully articulated in earlier sections. This may not be the focus of the current manuscript but please do mention this briefly in the methods section.

Reflections and implications sections should be reduced or removed, since much of this is quite speculative.

Please complete the CONSORT checklist and ensure that all components of CONSORT are present in the manuscript, including how randomization was performed, allocation concealment, blinding of intervention, definition of lost to follow-up, power statement.

Comments from the reviewers:

Reviewer #1: General comments

The manuscript describes findings from the GoActive physical activity intervention for adolescents. Physical activity declines dramatically during adolescence and innovative strategies are needed to engage adolescents in health enhancing physical activity. The GoActive intervention was carefully designed and based on a successful pilot study. Study strengths include the rigorous study design, high quality outcomes, large sample size and high consent rates, inclusion of longer-term follow-up assessments and assessment of cost effectiveness. Despite these strengths, the intervention had no effect on reducing the decline in physical activity typically observed in adolescent populations. The authors provide an honest account of their findings and some useful suggestions for moving the field forwards. I provide a list of minor suggestions for improving the manuscript.

Specific comments

INTRODUCTION

In general, the authors have provided a strong rationale for their study. Physical activity declines dramatically during adolescence and schools represent an ideal opportunity for intervention.

METHODS

Study design and participants

The study design and methods are rigorous and appropriate for the study aims.

Excellent consent rate for students.

From the 103 schools that were invited, 16 were successfully recruited. Did the research team track reasons for schools' non-participation? Could this information be included in the CONSORT flow diagram (this is mentioned on page 25 of the protocol)?

Were schools match paired according to the four variables before randomisation? See Murray text below:

Murray, D. M. (1998). Design and analysis of group-randomized trials. New York, NY: Oxford University Press.

Procedures

Self-determination theory (SDT) has emerged as a useful theory for explaining and promoting physical activity in adolescent populations. However, the use of external rewards for participating in physical activity is not consistent with the tenets of SDT for promoting self-determined motivation. Such an approach may have a short-term positive effect, but is unlikely to promote sustained behaviour change. Please comment.

Statistical analyses

Did the research team conduct two types of analyses (i.e., complete case and intention to treat)? The following sentence appears contradictory- "We conducted a complete-case analysis based on the Intention to Treat principle, in which participants and schools were included in the group to which they randomised, although participants with a missing value of an outcome at follow-up were excluded from the analysis of that particular variable.". From my understanding of ITT, participants should be included in the analysis regardless of whether or not they completed follow-up assessments. Please elaborate.

Did the authors test for clustering of effects at the class level? Although participants were randomised at the school level, it appears as though aspects of the intervention were delivered during class-time.

RESULTS

If possible, please report the adjusted difference between groups for the psychosocial and anthropometric outcomes in a table (not in a supplementary table).

DISCUSSION

The discussion provides an honest account of the findings. The authors provide a useful summary of the challenges faced by researchers as they scale-up successful pilot studies.

The lack of alignment between reward provision and SDT should be addressed in the discussion.

Reviewer #2: See attachment

Michael Dewey

Reviewer #3: This paper reports on the evaluation of impact of the GoActive program on adolescent's total daily MVPA across 10 months, noting that the intervention was the most intensive during the initial 12-week period. The study was conducted in the UK, with a somewhat diverse population but does not necessarily include a large sample of racially/ethnically diverse children, low-income children, nor a high percentage of overweight/obese children, who might generally benefit more from school-based interventions. This was a randomized and blinded study in a large population of children and the authors are to be commended for that. However, throughout the manuscript I found that the writing was not necessarily compelling nor specific. I also think that based on their findings that there is the abrupt and somewhat overstated conclusion that we should give up on school-based PA interventions and that they are not cost-effective. That was not the primary goal of their study and it is indeed unfortunate that the results were not more positive. However, there are questions with regard to some of the analyses, the dose delivered, etc. which might resulted in the inability to find a positive effect on PA. We need to remember that we are working to prevent a natural decline in activity over the childhood years and it indeed may become ever more complex during the adolescent years when academics become more competitive and there more of a loss of light activity and a general increase in sedentary time. Fueling self-efficacy around PA might be indeed very important and maintaining the access to PA. In this study, given the focus on total daily activity it would have also been nice to hear more about the out-of-school time activities of these children - the % engaged in sport, etc. Even data on those who walked to school, vs. other means.

Title: "effectiveness" and "cost-effectiveness" seems a bit redundant/wordy in the title - consider rewording.

Abstract:

Introduction: "and social disadvantage" seems a bit misplaced - social disadvantage from chronic disease risk or just from alone not being active?

Methods:

Should "Year 9" be capitalized? - if so, your second mention is not.

It is not clear what N=165(62) and n=193(43) refers to

Introduction

Overall, the introduction is somewhat disjointed and does not read smoothly. It seems a bit thrown together and does not exactly prepare the reader for where the authors are at in terms of presenting the current work.

First paragraph

First sentence - do these data represent in a decline in adolescent physical activity from when to present? Or are you simply implying that globally adolescent PA is low - I would clarify be very precise with this compelling data.

Please clarify what "life chances" are

Note that the drop in 5min/day from adolescence to adulthood may not seem that compelling when it is known that children are already dropping on average two minutes per day throughout each progressing year of elementary school….such that levels are already so low. And please just clarify - is this comparing a 17 year old to an 18 year old? Again, some specifics might be more compelling for the reader.

Paragraph 2

Please cite the reference demonstrating that most PA declines throughout adolescence occur outside of school. This may vary substantially on the socio-demographics.

The thought-stream of this paragraph is not fluid. It is difficult to follow the points that are attempting to be made through discussing all of the reviews - are you attempting to highlight the lack of interventions in adolescence? Or are you high-lighting that school-based interventions are ineffective in increasing total daily activity…or other?

Paragraph 3

Needs a transition to this paragraph shifting the reader to the focus of the current intervention (that is not clearly stated). There are too many ideas/concepts in this paragraph - theory development, prior pilot work, the aim of this study, and why it overcame limitations. Some of that information could even be put in the discussion. Finally, the concept of cost-effectiveness feels a bit thrown in and does not have any background or rationale (although understood) in the text.

Also, please spell out moderate-to-vigorous PA the first time it is used (MVPA) and also be precise that the main outcome is total daily MVPA and not school-time

Methods

Baseline assessments Sept - Jan?

Accelerometry

Why did the criteria for accelerometry data inclusion not include both weekend and weekdays?

Inclusion criteria for 6 hours of wear time over at least two days seems very sparse. Would like to see references to support methodology chosen. The protocol, as written, is difficult to follow.

Reported outcomes

How can individual socio-economic position be self-reported by this group of children?

Anthropometry - understand the subject burden of assessing this measure, however I think it is an unfair statement to say that it was not important to assess at 10 months. There would not be an expectation of weight change, however, the differential impact of programming between weight status categories would be an important outcome to assess and understand.

Economic analysis - more explanation of the measures and costs incurred during the program implementation are needed here.

Process evaluation

Please briefly describe the levels of dose/measures survey/inquired about here and what your main process measures are that are utilized in the present study/analysis.

Analyses

More information is needed on the physical activity survey and how the variables of relative to never active were determined.

Please define what "active during tutor times at least twice during the last two weeks" means. How active? For how long? Is this only during the school day or could it be other? Etc.

Also be more specific about what activity points are and how often children were instructed to log - is this a daily, weekly, or monthly calendar, etc?

Results

In general, the results described are very vague and do not include much data. It is hard to understand the findings/results in the current written form.

Please describe the population in general terms in written results - age, % female, % overweight, % obese, % non-white.

Primary outcome - results "appearing to favor" seems like very vague language for the results section and should be presented more precisely and with or without significance.

Tests for interaction - similarly the language used is very vague…"suggest"…and results are inconclusive.

There is general concern that the per-protocol analyses only included 382 children and that the inclusion criteria for following the protocol did not seem to necessitate a very large dose of activity delivered.

Process evaluation

A better understanding of what it means for students to have a peer-leader vs. a tutor, etc. is needed.

Figures.

Legends need to describe what is being shown in more detail. They currently do not stand alone. What is acceleration?

Is self-efficacy - general or PA self-efficacy?

Discussion

Why does the first paragraph end with the notion that the intervention could have negatively impacted well-being?

If baseline was Sept-Jan then 10month follow-up occurred between the months of? July-November? That doesn't really make sense given the academic year. The discussion also mentions across "two academic years". There was also no mention of accounting for the time of year of measure at baseline vs. followup. (or weather for that matter)

What was the children's average school-time physical activity? How much did this decline over the time-frame? Vs. total daily? And did you indeed see more of a decrease out of school time? I think that the discussion is too focused on weekend days and out of school time, when the intervention was school-based.

Limitations

Failure to acknowledge some of the variables that could have been assessed such as longer wear-time inclusion criteria for accelerometry, weather, time of year of the different visits, child measure of SES, specified dose of delivery for children to achieve in school, and somewhat of a lack of lower-SES and racial/ethnic diversity. Final there appeared to be a disregard in understanding the dose received and uptake by important sub-groups such as girls and those who are overweight/obese. Discussion of the prevention of decline in minutes of MVPA in girls vs. boys might be very illustrative.

Given the apparent lack of dose delivered and received by the adolescents in this study, this reviewer believes that it may be somewhat of a premature assumption and editorial by the authors to state that we should divert our resources elsewhere beyond the promotion of physical activity in schools. Multiple modalities are warranted and indeed continue to be very difficult to assess in a natural way, but in a robust clinical trial design with adequate statistical rigor.

Reviewer #4: This paper reports of the effectiveness and cost effectiveness of a large cluster RCT in the UK. Like a number of other well-designed UK school-based trials the intervention aims to use peer leaders to influence younger pupils to become or stay active with the hope of reducing the age-related decline seen. A number of papers related to this study have already been published, including the protocol paper. Despite the preparation for this definitive RCT being linear with clearly related outputs (i.e. development work, feasibility study, protocol paper) the presentation in this paper is not wholly clear. The paper could do with a rework in how the work leading up this this RCT is presented, the clarity with which the actual intervention is presented and the rationale for including process evaluation peppered around the paper. Well done on the whole study and getting it down on paper here, they are a lot of work!

Critical comments:

Process evaluation section is a bit lost in there and doesn't add anything especially if more traiangulation work or reporting is planned in a separate paper. I would suggest removing and just sticking to primary outcomes and the costs.

The authors state the programme was not cost-effective. Firstly, the programme was not effective at changing the primary outcome so cost effective analysis is inappropriate. Should this be a cost consequence analysis? This would describe what the cost consequences of delivering the intervention were?

Economic analyses of trials like this are in their infancy in the UK. But now we have a number of large NIHR trials including ones from this PHRP call that have used economic analysis (also WAVES) that is building up since methods, tools and data in this area. Have you considered a separate paper on this? One that includes methods, reflections etc.

Major comments:

1. The authors stated the feasibility was promising. What was the difference between the feasibility and this RCT? The authors state that the engagement with online and was low and "contrasts high engagement in the pilot trial" but was there anything related to the delivery that was different? I think this is a key piece of the puzzle of how promising feasibility/pilot does not always translate into effective main trials. Consider (even in a separate short report) a table of differences between feasibility and the main trial in terms of, for example, delivery (type, amount, staff, training), support provided by the research team, the "buy in" from the delivery staff (vs. delivery from vested researchers) etc etc.

2. Paper goes very quickly from the lit into the background on the trial (top of page 13). A clear opening sentence introducing the programme would be useful there. The section starting with the following blends a little too much with the background/intro to the intervention. "Previous research suggests that activity promotion strategies should be based on behaviour change theory, existing evidence and pre-trial qualitative work with the target group(13, 17). Although the intervention was broadly aligned with self-determination theory(18), our priority was to co-design the intervention with students and teachers. Therefore we used theory flexibility to enable the incorporation of components strongly suggested in the development work, such as rewards." Suggest the whole section be split. Deal feasibility data separately as it is all mixed into one.

3. In relation to the delivery staff from Active Essex and Everyone Health. How sure are you that the delivery was as robust and fidelity compared to the feasibility? In outsourcing our intervention delivery to suit the funding call/stream (which is a positive to promote sustainability!) are we underserving the original intervention? What did the delivery staff say? What do Active Essex and EH think of the programme, will they keep it on their books?

4. Sentence on "Prior to April 2018, schools received money for every child whose families received income support and had an annual gross income of £16,190 or less(22)." Seems lost and I would say not needed as you have given the reference in the previous statement.

5. Reference number 13 has been used quite a bit and is the reference for the intervention development work. This is not stated anywhere in the paper. I think you need a clearer section about the development of the intervention, the feasibility trial and the feasibility results. This can go in the intro and will help "set the scene" for this definitive cluster RCT. As it stands I am not sure what background info has come from the literature and what has come from the team's own development work. I feel the intro to the development work is undersold!! State that reference 21 is the protocol.

6. The methods state that in the recruitment areas "substantial socioeconomic diversity and includes both urban and rural areas" existed. Consider whether this is enough to account for the context that schools exist in. "Each school is a unique system" very true. The context is key. Will this be explored in the process evaluation?

7. Results table: I have not seen a %missing column within the table, usually in the footnote. If it has to go in I suggest at the third column. Optional.

8. Costs collection were supplemented by study records, Give examples of what these study records were. Who were responsible for keeping these updated?

9. When describing the primary outcome of PA at 10 months. Be clear that that is the accelerometer measure of PA because the next section talks about self-report.

10. SES of the ppt was used in the sub-group analysis. Please add a justification. Would that mean that if an SES effect was seen that interventions would be tailored depending on a ppt SES?

11. Economic analysis - where do those costs lie with in the current delivery i.e. how much of that cost was bourne by the school (printing, cost of teacher time prepping or delivering), bourne by the research team but presumably would have to be paid for by a commissioner in the future?

12. "There was no evidence that the intervention negatively impacted wellbeing" but this is only based on the measures that were included in Table S1. Restate with caveat.

13. The paper states that "teachers and mentors found the programme too complicated and we perhaps afforded schools too much flexibility." Does this come out in the PE teacher interviews? This is an interesting point. This tallies with the finding in the Girls Active trial process evaluation whereby "The flexibility created by having choice in activities and timing of delivery on occasion created uncertainty. Without milestones or deadlines teachers found other priorities took over and the programme drifted, potentially explaining why schools did not achieve everything they set themselves in their action plans." Gorely, et al. "Process evaluation of the school-based Girls Active programme." BMC public Health 19.1 (2019). It is a fine balance between them all!

14. The intervention is based on SDT in relation to the adolescent ppts. What about the teachers? Is there an opportunity to explore how this flexibility relates to their need for using their expertise, getting appropriate social support…anything in teacher interviews about this and mapping teacher responses onto a theory.

15. There is a lot on the PE in the discussion but little in the results. I think this is an error because that process evaluation paper will be standalone and will be good. However, I know it is hard because you want to give readers some context on why the outcomes are the way they are. Perhaps reconsider what and how much of the PE is included herein.

16. I found the results largely hard to follow. The terms "effect modification" and "subgroups" are included the stats section. "Sub-group" and "test for interaction" are in the results. While meditation and interaction analyses are included in the discussion. There needs to be some consistency in how the terms are used and some description up front as to what both are looking to explore in practice.

17. The authors state "the intervention may have fostered a climate that was not conducive to physical activity within school" (ref 23) Vague, what does this actually mean?

18. The authors state "our results are relevant to many schools across the UK and to many other high income settings" but what are these results? What is that take home message from this that is relevant?

19. In the reflections section the authors state "the lack of effectiveness of school based physical activity promotion strategies" but these are all the ones that have been in research which are either research-driven. But the PHRP interventions are not always researcher driven. They are often a programme running and then adding research on. There are likely plenty of examples of good practice out there that are school specific and are held by teachers or principals and are part of a whole school-approach to health. Was there any evidence of the buy in from the wider school, other teachers, school senior leadership team?

20. The Daily Mile papers are mentioned and how simplicity of that programme is key. But it is also the cost. The fact that it is free is attractive in times of austerity.

21. The authors state that "Our findings suggest that current research driven approaches to school physical activity promotion are unlikely to be effective" is a sweeping statement. I think taken with the other non-effective trials (even just the others funded through the same NIHR themed call) there is an issue.

22. Again the statement in the conclusion "Authorities should be cautious about commissioning and proliferating school-based physical activity promotion strategies and be realistic about expectations of effect." Is not representative of this work.

23. The whole discussion needs tightening up but the comments above may help with that.

24. Is "procedures" the best heading for the section about the intervention? Again, that section needs to be tidied up for clarity. I feel there could be a better use of headings within the methods section to guide readers.

Minor/Typos

1. Is this sentence missing a word "Total accrued time from baseline to 10-month follow-up and hence the time horizon for the study is approximately two academic years."

2. Results. Opening line Figure is misspelled. Called "trial profile"

3. Table 2 title is missing a word

4. S12. What is T4?

5. Figure 4. Medium/low and high. State what subgroup this relates to.

6. Underweight is included in S7 but no mention of that anywhere else. What were the numbers in each category? Add to baseline characteristics.

Any attachments provided with reviews can be seen via the following link:

[LINK]

Submitted filename: corder.pdf

Click here for additional data file.

6 May 2020

Submitted filename: Corder_PlosMed_R2_response.docx

Click here for additional data file.

1 Jun 2020

Dear Dr. Corder,

Thank you very much for re-submitting your manuscript "Effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among adolescents: a cluster randomised controlled trial" (PMEDICINE-D-20-00312R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by xxx reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

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------------------------------------------------------------

Requests from Editors:

This is a bit unquantified in abstract “Adolescent physical activity levels are low” (also in the AS) please add more specific language

Please add the trial number at the end of the abstract

Abstract –please add inclusion criteria briefly

Table 1- please can you change the weight category names to avoid stigmatising labels like overweight, underweight etc and use people first language?

I think there is a simpler way of writing this “The results of the GoActive trial show that adolescents who participated in an evidence based school-level physical activity promotion intervention did not experience less of a decline in accelerometer-assessed physical activity than those who attended normal school activities.”

We don’t require the funding section within the main text. Please provide this information in the financial disclosure section. The same goes for conflicts of interest

Please remove page numbers from the CONSORT checklist and use paragraphs/sections instead.

Comments from Reviewers:

Reviewer #1: I am satisfied with the authors' revisions.

Reviewer #2: The authors have addressed all my points. Can we just clear up the point I made about per protocol? On what is now page 20 perhaps after the phrase 'similar results' insert what it is similar to. I thought it meant similar to the last analysis mentioned before which was the per protocol one.

Michael Dewey

Reviewer #4: Thank you to the team for addressing a large amount of review comments so well. I have a few more based on the changes but also a few I may not have caught the first time around.

Introduction

Thanks to the team for reworking the introduction. I find the intro vague. I have a number of comments based on this.

Line 103. What is "academic achievement in adulthood"?

Line 117. The authors state that "Moreover, evaluation of cost-effectiveness remains rare". Do they mean in school-based trials? In PA research? The reference used to back this up is from 2016. Since then, a number of trials in the UK and wider have included health economics. Suggest this statement is restated or a stronger justification for included health economics is included. E.g. the literature is limited, since a notable paper in 2016 there are more emerging, it is critical to included HE in these studies to understand costs/help decision makers etc etc.

Line 129. "GoActive employs a whole population approach to overcome the stigma of targeting at risk groups" Whole population? Do you mean the whole of school population? All pupils? Teachers? Population of a town/city? At risk for what?

Methods

"In participating schools, school-level written informed consent was obtained following a meeting between members of the GoActive team and senior school staff;" Who signed off on the consent? Was it the principal/ head teacher or some other school leader? This is important as I cannot see any other formal involvement of senior school staff in GoActive (but you say that will be looked at in the Process Eval).

At the first mention of Family Affluence Score please include (FAS) after it as you do use FAS subsequently.

The authors state in a response to Reviewer 3 that "Schools were all randomised at a similar time of year" and that "we do not consider accounting for weather and time of year of visits appropriate in the analyses of a randomised controlled trial." Even though schools might be randomised at a similar time that doesn't mean that their baseline assessments were all scheduled at random times between Sept to Jan. Scheduling was likely based on dates outside of the control of the research team but also not at random. There could be a situation where the majority of intervention schools were baseline tested in Sept/Oct and the majority of control schools baseline testing happened Dec/Jan. Unlikely but possible! Then weather and time of year of visits would be an issue.

Line 166. Please include a reference for the approach that was followed ("following an evidence-based iterative approach"). Was it the MRC guidelines?

Line 178. "tutor group (class or home room class)" will not make sense to non-UK readers.

I take the authors response comment that they are following CONSORT by abandoning ITT and instead giving a clear description of who was included in this main analysis. The authors also state "This is a complete-case analysis that is valid under the assumption that the outcome is missing at random, conditional on randomised group and the baseline value of the outcome" Can the authors include a reference for this statement of validity of this approach? Is it possible that the missing data are not at random in this type of trial? Have they looked for any differences in key baseline characteristics in those that did provide follow-up data and those that didn't? This also relates to the statement on the loss to follow-up being a limitation. If certain groups (e.g. those OW) provided less data at 10 months then this loss could indeed be a limitation.

Results

Line 367. "despite multiple follow-ups" Suggest using a different word for multiple contacts as follow-up appears elsewhere

The sentences in first paragraph of the Results that presents the ppt numbers needs reworking. What is the 193 referring to? What is n-165 referring to?

I.e. please relook at this section as it need multiple reads to understand that the values in parenthesis are SDs and not references. Perhaps add SD within then parenthesis for each: "2862 (84.1%) consented 371 (8 control, 1319 participants, mean (SD) participants per school: n-165 (62); 8 372 intervention, 1414 participants, n=193 (43)); 2828 (98.8% of those consenting) 373 completed baseline questionnaires, and 2638 (92.2% of those consenting)"

Discussion

Line 580. "However, given resource limitations and time in school limitations, there may be insurmountable barriers to this approach". Can the authors clarify what this means? Where are the resource limitations coming from?

Is it premature to suggest that "through the use of frameworks such as the Creating Active Schools Framework" is the answer to how we overhaul this research area? As the authors point out in the comments section this framework's effectiveness has not been established. I believe it is risky to give one specific example that is new and unproven that could be the panacea to the problem stemming from a number of non-effective trials. Also, this framework is very UK-centric. There are a number of established frameworks out there that have global relevance e,g. WHO https://www.who.int/healthpromotion/publications/health-promotion-school/en/

Is the only level of "school senior buy-in" the fact they sign a consent form. However, in the conclusion the authors state that "School leaders and authorities should be realistic about expectations of effect of school-based physical activity promotion strategies implemented at scale." What does this mean in relation to this study? School leaders were not on board from what I could see so why do the authors think that school leaders have unrealistic expectations (or any expectations) of the effect of these interventions. Same can be said for authorities. Who are these authorities, local authorities? Could the same be said for funders?

Line 654. Is commissioning a PA promotion strategy to schools trying to achieve change at a population level? Is it not a setting level? A population based approach would be something wider and larger like a promo campaign? "realistic about the scale of behaviour change that can be achieved at a population level". The authors may wish to reconsider the use of "population" within this paper.

In the conclusion the authors state that "that research driven approaches to school-based adolescent physical activity promotion are not effective" yet then go on to call for more research that is interdisciplinary. Consider changing to "the current research driven approaches"

Any attachments provided with reviews can be seen via the following link:

[LINK]

1 Jul 2020

Submitted filename: R5 response_Corder.docx

Click here for additional data file.

1 Jul 2020

Dear Dr Corder,

On behalf of my colleagues and the academic editor, Dr. Sanjay Basu, I am delighted to inform you that your manuscript entitled "Effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among UK adolescents: a cluster randomised controlled trial" (PMEDICINE-D-20-00312R3) has been accepted for publication in PLOS Medicine.

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Best wishes,

Adya Misra, PhD

Senior Editor

PLOS Medicine

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