A process evaluation of the Walking In ScHools (WISH) Study using the RE-AIM framework

doi:10.21203/rs.3.rs-4692920/v1

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Research Article

A process evaluation of the Walking In ScHools (WISH) Study using the RE-AIM framework

https://doi.org/10.21203/rs.3.rs-4692920/v1

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Background

Physical inactivity in adolescents is a major public health issue. Schools are important settings for physical activity interventions. The WISH Study was a peer-led, school-based walking intervention that aimed to increase physical activity levels of adolescent girls. This study uses the RE-AIM Framework to present the process evaluation of the WISH Study with a focus on factors that affected participation, motivation, and enjoyment of the intervention.

Methods

Pupils (n589 12–14 years) were recruited from 18 schools in the border region of Ireland and Northern Ireland. In intervention schools (n9), older pupils (15–18 years) were trained as walk leaders and led pupils (12–14 years) in brisk walks (10–15 minutes) during the school day, across the school year (2021-22). Questionnaires were administered throughout the intervention, and at the end of the intervention focus groups were held with pupils, and interviews conducted with teachers and walk leaders. Attendance at walks was monitored by walk leaders. Quantitative data were analysed descriptively, and qualitative analysis was undertaken using thematic analysis. Themes were reported under RE-AIM indicators (reach, effectiveness, adoption, implementation, and maintenance).

Results

Participating pupils (n286) were representative of adolescent girls in Northern Ireland and Ireland, with 15% of pupils, achieving recommended physical activity guidelines (60 mins moderate-vigorous physical activity per day) at baseline. The total number of walks reported per school ranged from 2-104 across intervention schools. One quarter of pupils (n74, 26%) never attended a walk and 15% (n23) of walk leaders did not lead a walk. Pupils and walk leaders self-reported improvements in their physical health, mental well-being, and social relationships, and walk leaders reported gaining transferrable skills. Implementation was aided by school support in some schools, although barriers such as COVID-19, lack of time, harsh weather, inadequate facilities for indoor walks, and walk leader availability, were identified. Staff engagement was a key driver for the maintenance of walks.

Conclusions

Despite a promising feasibility study and a comprehensive walk leader training programme, the extent to which the intervention was adopted and implemented varied, suggesting future school-based physical activity interventions need to consider individual school contexts to ensure intervention fidelity.

Trial registration

: ISRCTN 12847782

Process evaluation

RE-AIM Framework

Physical activity

Walking

Adolescents

School-based intervention

Adolescents’ physical and mental health has been shown to benefit from regular physical activity (PA). Positive outcomes have been reported for bone health [1, 2], cognitive function [3], cardiovascular fitness [4], muscle strength [5], depression [6] and the maintenance of body mass status in adolescents, through biological, psychosocial, and behavioural mechanisms [7, 8]. Literature reports a link between moderate-to-vigorous PA (MVPA) and improved academic performance and self-esteem, which can improve social connectedness in children and adolescents [9]. Public health guidance states children and adolescents should accumulate, on average, at least 60 minutes of MVPA daily [8], yet many do not achieve this. Data from the Global School-based Student Health Survey suggests that 84% of adolescents are inactive [10]. Similarly, 84% and 88% of adolescents in Northern Ireland (NI) and Ireland respectively, are not meeting recommended PA guidelines [11]. Insufficient PA levels have been reported in children as young as 5 years [12] and longitudinal data from the UK suggest time spent in MVPA decreases (an average of 10.9 min/day less during weekdays and 15.5 min/day less during weekends) between the age of 6 and 11 years [13]. This is a major public health concern, considering the decrease in adolescent PA, which has been linked with declining well-being since the onset of the COVID-19 pandemic [14].

School-based PA interventions have the potential to improve the PA levels of adolescents, particularly during recess breaks [15]. Walking as a form of PA incorporated in school-based interventions could help address barriers to PA identified by adolescent girls [16], while equipping them with the knowledge, skills, and confidence, to remain adequately active throughout their lifespan [17]. However, evidence from systematic reviews and meta-analyses have suggested small, pooled effects or non-significant effects of school-based interventions at improving MVPA and reducing sedentary behaviour [18–21].

The Walking In ScHools (WISH) study design was informed by a feasibility pilot study [22] and used the Medical Research Council (MRC) Framework [23] to develop a school-based, peer-led walking intervention [24]. In the pilot study, a significant interaction effect was observed for changes in light-intensity PA across the school day [22]. Albeit, when the pilot study was ‘scaled up’ to the fully powered WISH Study, post-intervention total PA did not statistically differ between groups when adjusted for age, body mass index (BMI) z-scores, and baseline PA [25].

To address elements other than efficacy and effectiveness and to investigate conceptual issues with the implementation of complex interventions such as the WISH Study, the MRC suggests a variety of approaches, including process evaluations [26]. Embedding process evaluation in research study designs is essential to determine whether interventions are implemented as intended and to identify gaps between the development of interventions that show promising results at pilot, and their subsequent ‘scale-up’ and adoption in educational settings [27, 28]. As a result, an in-depth process evaluation was embedded within the WISH Study. The RE-AIM (Reach, Effectiveness, Adoption, Maintenance) Framework was conceptualised to address problems and delays in the translation of research into practice and goes beyond just measuring outcomes and considers factors that influence the success of interventions. The Framework is widely used in public health research to systematically evaluate the external validity and generalisability of interventions [29] and consists of 5 dimensions, reach, effectiveness, adoption, implementation, and maintenance [30]. This process evaluation aimed to identify factors that affected participation, motivation, and enjoyment of the WISH intervention, investigate barriers to walking, and explore the experiences of pupils, walk leaders, and teachers.

Study design

A mixed-methods process evaluation of the WISH Study was undertaken using the RE-AIM framework [29]. The full trial protocol has been published elsewhere [24] and the CONSORT flow chart has been included (see Additional file 1). Ethical approval was obtained from the Ulster University Research Ethics Committee (REC/19/0020) and the study was prospectively registered with ISRCTN (ISRCTN 12847782). All pupils provided written assent and parents/guardians provided written informed consent. Walk leaders and teachers provided written informed consent.

Patient and Public Involvement Statement

A Youth Advisory Group (YAG) was established, and Patient and Public Involvement (PPI) informed the delivery, implementation, and dissemination of the WISH Study. Schools invited pupils aged 12-14 years and 15-18 years to YAG meetings (n3 from 2019-2023) [31].

The WISH intervention

The WISH Study was a two-arm cluster randomised controlled trial (cRCT) that has been described in detail elsewhere [24]. Briefly, post-primary schools in the border region of Ireland and NI were invited to participate. Participants aged 12-14 years, for whom walking was not contraindicated were deemed eligible. Between September and November 2021, 18 schools were recruited and after baseline data collection, were randomly assigned to receive either the intervention (peer-led, brisk walking programme) (n9) or function as a control (usual PA) (n9). In intervention schools, a key teacher contact (Physical Education [PE] teacher/department head) nominated older pupils (aged 15-18 years) as walk leaders. The walk leader training programme was developed in consultation with a PA co-ordinator (Western Health and Social Care Trust) and was based on the Walking for Health Training (Public Health Agency & NI Health and Social Care Trusts). Walk leaders were asked to lead the younger pupils in 10–15-minute brisk walks, before school, at break and lunch recess. Walk leaders were provided with a wrist-worn heart rate monitor (Mi Band 3, Xiaomi, China) to assist in maintaining a brisk pace during the walk and asked to complete a checklist (see Additional file 2) each time they led a walk to monitor intervention fidelity. A booster session was held in each intervention school 2-6 weeks (mean 4.1 ± 1.4 weeks) before the end of intervention data collection, to improve pupil and walk leader engagement after the Easter holidays. During this session, pupils had the opportunity to nominate a Walk Leader Champion to be the main contact for the research team. Throughout the study, walk leaders were supported by the research team via bi-weekly visits to schools, private social media groups (Facebook and Instagram), and regular email contact from the Trial Manager. Data collection appointments took place in school, at baseline (T0: October-November 2021), mid-intervention (T1: February-March 2022; accelerometry only), end of intervention (T2: May-June 2022), and follow-up (T3: October-December 2022).

Impact of COVID on WISH intervention

The WISH Study was originally to be implemented across two academic years (phase 1: 2019/2020; phase 2: 2020/2021), with nine schools recruited each year. However, the COVID-19 pandemic and resulting school closures for face-to-face teaching, meant that both phases 1 and 2 were disrupted and the intervention could not run as intended, across the full academic year. Funding for the WISH Study was extended to allow for a third phase and the eighteen schools were recruited to this phase (phase 3: 2021/2022). Only data collected during phase 3 will be reported here. During Phase 3, Public Health guidance varied between jurisdictions (NI and Ireland) and each school had individual Health and Safety policies and procedures in place to minimise the risk of exposure to COVID-19. Schools remained open for face-to-face teaching during phase 3 and face coverings were mandatory in schools until 20^th January and 28^th February 2022 in NI and Ireland respectively. A school environment questionnaire was developed by the research team and completed by teachers at each data collection visit (see Additional file 3), to monitor individual school variations in social distancing procedures.

Mapping data to RE-AIM Framework

This process evaluation triangulated quantitative and qualitative data and the findings were mapped to the RE-AIM Framework to facilitate the interpretation of the results (Table 1).

Table 1. WISH data mapped to the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework indicators

Framework section[29]	Definition of assessment criteria	Source, timepoint, and number of survey items
Reach	The proportion of the target population involved with the intervention How pupils reflect the general population	Pupil recruitment Walk leader recruitment and training Participant PA levels at T0
Effectiveness	Effect of intervention on pupils and walk leaders Unintended intervention consequences	Intervention effect on pupils PA, HRQoL, PA self-efficacy, walking self-efficacy, amotivation, external regulation, introjected regulation, identified regulation, integrated regulation, and intrinsic motivation (T0, T2, T3)^† Walk leader’s participation in sport, PA self-efficacy and enjoyment and leadership (T0 n149, T2 n133) Participant focus groups (T0 n9, T2 n9) Walk leader interviews (T2 n18) Teacher interviews (n9)
Adoption	The number of pupils willing to initiate and continue with the intervention Setting level adoption Participants and walk leaders' reasons for participating	Recruitment data and attrition rate Walk leader checklists Participant focus groups (T2 n9) Walk leader interviews (T2 n18)
Implementation	Implementation adherence, exposure, and adaptations Barriers and facilitators to intervention implementation Intervention costs incurred	Walk leader checklists Observations from school visits School environment questionnaire (T0 n9, T1 n9, T2 n9 & T3 n9) Social media interactions Participant focus groups (T2 n9) Walk leader interviews (T2 n18) Teacher interviews (T2 n9)
Maintenance	Views on whether walks could be maintained Suggested improvements	Participant focus groups (T2 n9) Walk leader interviews (T2 n18) Teacher interviews (T2 n9)

Abbreviations: WISH; Walking In Schools, T0; baseline, T1: mid intervention, T2; end intervention, T3; follow-up, PA; physical activity, HRQoL; health-related quality of life. ^†Sample size for each questionnaire at each timepoint is presented in additional file 5.

Reach

School, pupil, and walk leader recruitment data was used to determine the reach. To assess whether recruited pupils had PA levels representative of the general population, T0 PA data were used to report the proportion of pupils who met PA guidelines (60 mins MVPA per day) [8].

Effectiveness

Quantitative and qualitative measures were used to address the effectiveness of the intervention on participant and walk leader outcomes. Quantitative measures were completed by pupils on electronic devices (Apple iPad) using Qualtrics (Provo, Utah, USA) at T0, T2, and T3. Tools included the validated Self-efficacy for PA questionnaire [32] that was adapted to also assess self-efficacy for walking (see Additional file 4). The validated Kidscreen-10 index to assess health-related quality of life on a 5-point Likert scale, from which a total score was calculated [33]. The Behavioural Regulation in Exercise Questionnaire (BREQ-3), a 24-item tool to assess reasons for engaging in PA [34, 35], was completed on a 5-point Likert-type scale. The BREQ-3 measures a continuum of exercise behavioural regulation, and six domains of regulation are reported (amotivation, external regulation, introjection, identification, integration, and intrinsic regulation) [35]. For questionnaire data (see Additional file 5), responses from all pupils (intervention and control) are reported, with all other process evaluation measures (focus groups, interviews, walk leader checklists, school environment questionnaire), relating only to the intervention schools.

Walk leaders completed a series of paper questionnaires before walk leader training and at the end of the intervention. Walk leaders who were absent at the end of the intervention due to study leave, were sent an electronic link to complete the questionnaires (Qualtrics, Provo, Utah, USA). Walk leaders completed a questionnaire to assess their self-perception of PA and fitness [36]. Participation in sport activities (excluding school PE) was assessed using a single question that included the frequency of participation [36]. Responses were used to identify walk leaders who participated in sport activities (‘2-3 times/month’; ‘once/week’; and ‘≥2 times/week’) and those who did not. Self-perceived PA was assessed, and responses were recoded to identify walk leaders who self-perceived themselves to have sufficient PA (‘satisfactorily physically active’ and ‘very physically active’) or not sufficiently physically active (‘not sufficiently active’ and ‘some physically active’) [36]. Self-perceived physical fitness was assessed by asking walk leaders to evaluate their fitness level compared to others [36]. Responses were recoded as having good physical fitness (‘very fit,’ ‘fit enough’ or ‘average fitness’) or poor physical fitness (‘a little unfit’ or ‘very unfit’). Walk leaders completed the 8-item PA Self-Efficacy Scale [37], with items scored on a 3-point Likert-type scale, and a mean score was calculated. The 18-item PA enjoyment scale [38] was modified for use in adolescents and included 16 items measured on a 5-point Likert-type scale [39]. Reverse scoring was applied to seven negatively worded items and a total score was calculated. Walk leaders were asked to indicate their degree of agreement or disagreement on a 5-point Likert scale for questions relating to being a walk leader, including ‘I can work well as part of a team’, ‘I can lead younger pupils on health walks’, and ‘I can support younger pupils to improve their health through regular PA’.

Qualitative data was collected to contextualise and further explain the observed outcomes in relation to the effectiveness of the intervention for pupils and walk leaders and whether there were any unintended negative consequences. At the end of the intervention, face-to-face, semi-structured focus groups (n9) were conducted in schools. Purposive sampling was used to recruit pupils (n66) who were either low or high attenders at walks. Quantification of low and high attenders varied between schools, albeit, within each school, efforts were made to select a representative sample of low and high attenders at walks. Each focus group comprised of 5-8 pupils, and focus group duration ranged from 9-19 minutes. A semi-structured topic guide (see Additional file 6) was used to inform discussions, which aimed to explore pupils’ experience of the WISH intervention.

One-to-one online interviews, using a topic guide (see Additional file 7) were conducted with walk leaders, to assess how the school environment affected the delivery of the intervention. Two walk leaders (n18) from each school (n9), one Walk Leader Champion, and one other walk leader per school, subjectively assessed to be high attenders at walks using walk leader checklists, were invited to participate. The duration of interview discussions ranged from 13-24 minutes. The teacher contact in each intervention school (n9) was invited to take part in an online (Zoom Video Communications, Inc.), one-to-one interview. Using a semi-structured topic guide (see Additional file 8) to inform discussion, the interview aimed to identify key elements that affected intervention implementation. The duration of interviews ranged from 9-19 minutes.

Adoption

Recruitment data was used to determine the number of pupils willing to initiate the intervention and attrition data was used to document those who did not want to continue the intervention. Intervention adoption at an individual and setting level was measured by walk leaders, who were asked to complete a checklist each time they led a walk (paper and online (Qualtrics) checklists available). The reasons pupils and walk leaders enrolled in the intervention were evaluated, using focus group and interview data.

Implementation

Factors associated with implementation were examined from observations documented by the research team and monitored by the Trial Manager after each bi-weekly visit to the schools, walk leader checklists, and school environment questionnaires. Support and encouragement were provided by the Trial Manager to walk leaders, via social media platforms (Facebook and Instagram). The number of interactions walk leaders had with social media content (such as polls, stories, and posts) was measured and used to assess the support walk leaders received with intervention implementation. Adherence was defined as whether the intervention was delivered as intended. Data from checklists, focus groups and interviews were used to assess adherence and highlight any adaptations to the protocol which may have occurred at a setting-level. Exposure refers to the amount of intervention received by pupils (i.e., the number of walks attended) [40] and this was captured from the checklists. The Trial Manager collated data on the resources used and staff time to implement the intervention. This included preparation time, travel to schools for walk leader training, visits to join walks and booster sessions, training materials and resources for walk leader training, time spent developing content for social media as well as actual staff time. This was used to estimate the cost of intervention per school and participant.

Maintenance

At a settings level, insights into the extent to which the WISH intervention could be maintained, and any suggested improvements were collected from teachers and walk leaders during interviews, and pupils’ opinions were documented from focus groups.

Data analysis

Quantitative analysis of control and intervention pupil’s questionnaire outcomes (Kidscreen-10, exercise and walking self-efficacy, and BREQ-3) were conducted using R and RStudio [41] version 2023.6.1.524 (release Mountain Hydrangea) and the median and interquartile range (IQR) is presented for the data. Univariate descriptive statistics were performed for all other data (walk leader checklists, school environment questionnaire, walk leader questionnaires, social media interactions, and indicative intervention implementation costs) using IBM SPSS for Windows (Version 28, SPSS Inc, Chicago, IL, USA). Data is presented as frequency and percentage or median and IQR. All outcomes presented were secondary outcomes [24], and given no power calculation was performed for these, no p-value was presented.

Focus groups (pupils) and one-to-one interviews (teachers and walk leaders) were undertaken by a female researcher, independent of the research team (GH). Each focus group was preceded by an icebreaker to establish a relationship between pupils and the researcher (GH). Focus groups and Interviews were audio recorded and transcribed verbatim by a member of the research team and then verified against the recording by another researcher. Transcripts were imported into NVivo (release 1.7.1) for data management, and an inductive approach was undertaken using thematic analysis [42], to identify content relevant to the process evaluation outcomes. Analysis was led by a trained researcher (LCD) and following familiarisation of the data through reading the transcripts, initial codes were identified and assigned under the RE-AIM indicators (reach, effectiveness, adoption, implementation, and maintenance). Two researchers (LCD and AC) coded two focus group transcripts independently and then discussed initial codes before LCD continued with coding. Following this, each code was verified (AC) then codes and themes were discussed and refined to ensure rigor and reliability, while adhering to the Consolidated Criteria for Reporting Qualitative (COREQ) guidelines [43]. Anonymised quotes were reported and identified as coming from either a walk leader, teacher, or pupil.

Reach

School enrolment data was used to identify eligible schools (n158) and an invitation was sent to the school principal. Eighteen schools were recruited, and one school withdrew before baseline data collection due to a COVID-19 outbreak within the school. A school from the waiting list (n11) was subsequently contacted and recruited. Reasons for not taking part included no response from the school (n113) and stating they were unable to participate (n14). Within the 18 schools, girls (n1368) were invited to participate. Some 589 girls were recruited and reasons for exclusion included parental consent not provided (n704), declining to participate in baseline data collection (n7), being absent at baseline data collection (n67), and being outside of the inclusion age range (n1). After T0 data collection, schools were randomly assigned to the intervention or control arm.

589 pupils from 18 schools were recruited and 286 (48.6%) were allocated to the intervention group. Walk leader training was conducted between 22^nd November and 9^th December 2021, and the walking programme commenced in all schools by 9^th December 2021. Each school was required to have one walk leader training session, while two schools required a second training session to train additional walk leaders. Training was provided to 149 walk leaders and the mean (SD) number of walk leaders per school was 17 (6.6) with a minimum of 10 and a maximum of 31 walk leaders. At baseline, 12% (n66), of pupils (12-14 years) achieved the recommended PA guidelines (≥60 mins MVPA per day) [8] (15% [n37] of intervention pupils, and 10% [n29] of control pupils respectively).

Effectiveness

Effect of intervention on pupils

Post-intervention total PA did not differ between groups when adjusted for age, BMI z-scores, and baseline PA (mean difference, -33.5, 95% CI= -21.2 to 88.1; p=0.213 [25]. Based on the estimated marginal means and corresponding 95% CIs, there was a between-group difference in pupils’ PA self-efficacy at T3, identified regulation at T2 and T3, introjected regulation at T3, intrinsic motivation at T2 and T3, and integrated regulation at T2 (see Additional file 5).

Effect of intervention on walk leaders

Some 61% (n91) walk leaders reported participating in sport before walk leader training, and after the intervention 69% (n92) were participating in sport. Before the training, 61% (n91) self-perceived their PA as sufficient, and 20% (n29) reported their physical fitness as good. At T2, 59% (n78) and 14% (n19) self-perceived their PA as sufficient and physical fitness as good, respectively. Before the walk leader training, 98% (n146) of walk leaders agreed or strongly agreed that they could work well as part of a team, 97% (n144) agreed or strongly agreed that they could lead younger pupils on health walks, and 95% (n142) agreed or strongly agreed that they could support younger pupils to improve their health through regular PA. At the end of the intervention, 96% (n128) agreed or strongly agreed that they could work well as part of a team, 95% (n126) agreed or strongly agreed that they could lead younger pupils on health walks and 90% (n120) agreed or strongly agreed that they could support younger pupils to improve their health through regular PA. Results for PA self-efficacy, PA enjoyment, and youth leadership skills were similar before the walk leader training and at T2 (see Additional file 9).

Based on the qualitative data, the intervention showed effects on three main domains for pupils and walk leaders: (1) physical health (2) mental well-being, and (3) social connections, with an additional effect for walk leaders being the (4) development of transferable skills (Table 2).

Table 2. Experiences of pupils, walk leaders, and teachers mapped to effectiveness and adoption framework section and themes

Framework section[29]	Theme	Verbatim Quotes
Effectiveness	Physical health	‘It is a good thing to do, to be more active and just those ten, fifteen-minutes a couple times a day or per week it does sort of build-up, on the habits of being more active, and like it gets your steps in for the day and sort of resets as well, like you have a wee break outside in the fresh air and it sort of puts you in the right place to then go back into classes.’ WL 301_01
		‘I started walking at lunch and when I would have just sat talking with my friends instead, I guess.’ FG 301
		‘A lot of the girls have gone away and taking it up themselves to go and participate in other things or go on walks with friends.’ WL 306_09
	Mental wellbeing	‘And it also benefited like my mental health and obviously like my health as well like it was great, school’s stressful this year so heading out for the walk each day definitely benefited me that way’ WL 319_10
	Mental wellbeing	‘But then when they tell you to get up and go for a walk then you feel like happier for it like you did that.’ FG 307
	Social connections	‘And then because of the support then between and like the bond that was created between the two-year groups, as well the support and guidance that it brought everyone together.’ WL 306_09
	Social connections	‘A good thing for year nines causes they get to know the year fourteens, there is a bit of mentoring goes on too subconsciously in terms of they get to talk to the younger girls.’ Teacher 307
	Walk leader skills development	‘I think I just I definitely got like better teamwork skills and better team leader skills in general am I found it easier just to communicate and get on with the younger ones as well like a lot of them actually got to know me by my name and always would say hello to me on the corridor as well.’ WL 307_09
Adoption Walk Leaders	Promote PA	I know how good, how good exercise made me feel and I wanted to kind of you know let others almost like experience that like you know to make them feel good, make them feel happy you know because it definitely does boost your mood.' WL 306_09
	Promote PA	I love being active in the first place anyways and I believe that walking any physical activity was good for mental health.' WL 307_09
	To be more knowledgeable about PA	I thought it was quite interesting like you know when I heard about the like all the background information about it, I thought it would be like, help me you know getting to more depth about like my sports studies and stuff.' WL 306_02
	Develop transferable skills	I think the main reason was to gain just more confidence because whenever am I was usually a very quiet person so that I would try and just apply for anything I could do at school just to get the confidence up.' WL 303_02
Adoption Pupils	More active	Just to get more active.' FG 307
	Walking during class	Walks during class.' FG 310
	Socialise	Like going with your friends.' FG 303

Verbatim quotes are presented in the table and details are provided regarding the data source and the school or participants’ unique identification number (i.e., FG 303 indicates focus group data collected from school 303 and WL 303_02 represents walk leader_school code_participant code)

Abbreviations: WL; Walk leader, FG; focus group, PA; physical activity

Positive outcomes

During focus groups and interviews, pupils and walk leaders reported that participation in the WISH Study had a positive effect on their PA or fitness. Some described replacing sedentary behaviour with walking, especially during recess and lunch, and starting other types of PA.

“… they [pupils] had started going walking in the evenings after doing their homework or if they had, like a class test, they had started walking. Some of them had started playing football and things so I thought that was good” (walk leader 319_10).

Walk leaders in particular, reported improvements in their mental well-being and linked this with walking outdoors. Most pupils and walk leaders enjoyed being able to walk with their friends, and most stayed within established friendship groups, albeit some enjoyed the opportunity to meet new people. Establishing and reinforcing peer relationships and building relationships between pupils and walk leaders, was a benefit of the intervention, and teachers reflected that the school community was more connected.

“First-year girls got to know our fourth-year girls better so it’s actually good for relations within school em and the walk leaders have to be accountable to their walk leaders so that’s, that was good” (teacher 301).

Walk leaders reported developing transferable skills, including leadership, communication, and collaboration, because of their role as walk leaders, and having the responsibility for planning walks, and interacting with staff and pupils improved their confidence.

Unintended negative outcomes

No adverse events were reported to the research team, albeit pupils and walk leaders both reported feeling frustrated when walks did not occur, due to either pupils not attending, or walk leaders not being available to lead the walks.

Adoption

Most walk leaders reported a desire to be more active or promote PA to adolescent girls, and a desire to improve their knowledge around PA or sport whilst developing transferable skills, as reasons for participating.

Between T0 and T2, 4 walk leaders and 34 pupils withdrew from the study, and a further 17 pupils after T2 and before T3. Walk leaders did not provide a reason for withdrawing and pupils’ reasons included that they wanted to discontinue involvement (n35), had moved school (n9), or did not want to wear the accelerometer (for data collection) (n2). For a further two pupils, their school requested they withdraw due to behavioural issues (n2) and for two pupils no reason was given.

Across the intervention period (mean19.9 [SD 0.97] weeks), the total number of walks recorded for all schools was 371. The number of walks reported per school ranged from 2-104 walks (median = 35, Table 3). The walk leader timetable was developed jointly by the Trial Manager and the walk leaders during walk leader training and schools were asked to schedule up to 3 walks per day (before school, at break, and lunch recess). If it was not possible to schedule 3 walks per day, at a minimum, schools were requested to schedule 2 walks per day. This was considered feasible and each participating school scheduled 2 walks per day (10 walks per week). As summarised in Table 3, according to walk leader checklists, the mean (SD) number of walks that occurred per school across the intervention period, was 41.2 (34.4), suggesting per week the average number of walks was 2.1 walks. The actual number of walks that occurred per school varied, and there were some months when no walks were recorded by some schools (Table 3). The month with the greatest number of walks was January, with a total of ninety-six walks recorded, followed by March, December February and April with May being the month with the least number of walks documented (Table 3). The total number of pupils who did not engage with the intervention, as indicated by attendance monitoring from walk leader checklists, was n74 (25.9%). Furthermore, there were 23 (15.4%) walk leaders who completed the training and signed up to be a walk leader but did not lead any of the walks they were scheduled to lead, as agreed when the walk leader rota was devised.

Table 3. Number of walks reported from walk leader checklists in intervention schools

	Number of walks recorded
Intervention school	November 2021	December 2021	January 2022	February 2022	March 2022	April 2022	May 2022	Date not recorded	Total walks per school
School 301	0	5	15	5	3	4	1	0	33
School 303	0	11	10	5	6	4	0	0	36
School 306	0	1	1	0	1	0	0	0	3
School 307	0	10	16	4	1	0	0	6	37
School 308	0	4	9	5	12	0	0	5	35
School 310	0	1	0	0	0	0	0	1	2
School 313	0	11	18	11	13	3	2	31	89
School 317	1	17	21	14	22	12	14	3	104
School 319	0	0	6	7	13	5	0	1	32
Total walks per month	1	60	96	51	71	28	17	47	371

Implementation

Triangulated data from walk leader checklists, researcher observations, interviews with teachers and walk leaders, and focus groups with pupils were used to evaluate the implementation of the WISH Study in this section (Table 4).

Table 4. Experiences of pupils, walk leaders, and teachers mapped to implementation framework section and themes

Framework section	Theme	Verbatim Quotes
Implementation: facilitators	School support for WISH	‘...every school is different whereas in our school like obviously it was a slow burner but did end up very good but like I think every school is different and it’s all about how the school promotes it and I think our school did do a good job or promoting it at the start and even near the end they did do a good job of promoting it, I think it’s all to do with the school like ...’ WL 319_09
	WLs supported getting walks established	‘[Teacher] started a Google classroom and that was with all the walk leaders and all the people that attended the walks, and she was in it too,’ WL 317_02
	Engaged WLs to maintain attendance at walks	‘…we were able to say to the year eight and year nine am year heads could we come in you know just to ask the girls, so we were able to come in during the year eight and nine assemblies and you would reassure the girls, we were like you know come along [to the walks], bring your friends…’ WL 306_09
	Engaged WLs to maintain attendance at walks	‘The way we done it is, we would of just went around the form classes in the morning.’ WL 307_09
Implementation: barriers	WL availability	‘The walkers initially [did not show up] and then the walk leaders stopped turning up to be leaders because there was nobody turning up for them.’ Teacher 310
		‘Just if they were off on study leave, we wouldn’t have got a walk.’ FG 319
		‘I’d say probably like some of the girls not showing up would probably be a challenge and trying to get them out.’ WL 310_11
	Lack of time	‘You lost your break time.’ FG 310
	Lack of appropriate facilities	‘I think it went pretty good, you know because for like the lack of facilities we have for those like say rainy days, I think it went pretty well.’ WL 301_07
	Social distancing restrictions because of COVID-19	‘... just that a of the few girls didn’t show up due to the lunch time, lunch times were split between year 9 and 10’ WL 319_10

Verbatim quotes are presented in the table and details are provided regarding the data source and the school or participants’ unique identification number (i.e., FG 310 indicates focus group data from school 310 and WL 319_10 represents walk leader_school code_participant code)

Abbreviations: WISH; Walking In Schools, WL; walk leader, FG ; focus group, COVID-19; Coronavirus disease

Adherence, exposure, and adaptations

According to teachers and walk leaders, the intervention was set up as intended, with a timetable developed including two walk leaders per scheduled walk and two walks scheduled per day. The peer-led aspect of WISH was achieved in each school with walk leaders coordinating and implementing the programme, albeit in one school the teacher accompanied the pupils on walks and on two occasions arranged a walk outside of the school grounds. Walks lasted on average 14.8 minutes. Most walks occurred at lunch (48%, n178) with a similar number occurring before school (22%, n80) and during recess (27%, n101), and a small number (3%, n2) outside of the school premises. As summarised in Table 5, in 6 schools some pupils did not engage with the intervention at all. There were 3 schools in which pupils attended more than twenty walks across the intervention period and in all other schools (n6) the total number of walks pupils attended ranged from 0 to twenty walks across the intervention period (Table 5). Social distancing procedures due to the COVID-19 pandemic were introduced within educational settings and the concept of class and year group ‘bubbles’ was adopted as a measure to reduce social interactions and reduce the spread of COVID-19, which impacted intervention implementation.

“… if they have similar experience to us with timetables to sort that out as soon as you possibly can because obviously it hindered our experience a lot at the start” (walk leader 306_09).

At baseline, most intervention schools (n6) implemented a form of social distancing procedure, with two schools reporting class bubbles and five opting for year group bubbles. However, by T3, none of the intervention schools had class or year group 'bubbles'."

Table 5. The number of pupils recruited to the WISH Study and the total number of walks pupils engaged in across the intervention period

Intervention school	Participants recruited (n)	Participants who attended 0 walks n (%)	Participants who attended 1-5 walks n (%)	Participants who attended 6-10 walks n (%)	Participants who attended 11-15 walks n (%)	Participants who attended 16-20 walks n (%)	Participants who attended > 20 walks n (%)
School 1	26	4 (15)	11 (42)	4 (15)	3 (13)	4 (15)	0 (0)
School 2	25	0 (0)	11 (44)	12 (48)	2 (8)	0 (0)	0 (0)
School 3	32	25 (78)	7 (22)	0 (0)	0 (0)	0 (0)	0 (0)
School 4	39	5 (13)	14 (36)	12 (31)	8 (20)	0 (0)	0 (0)
School 5	32	17 (53)	10 (31)	2 (6)	3 (10)	0 (0)	0 (0)
School 6	30	6 (20)	24 (80)	0 (0)	0 (0)	0 (0)	0 (0)
School 7	35	0 (0)	4 (11)	3 (9)	6 (17)	9 (26)	13 (37)
School 8	29	0 (0)	0 (0)	9 (31)	7 (24)	1 (4)	12 (41)
School 9	38	17 (45)	18 (47)	0 (0)	0 (0)	1 (3)	2 (5)

Abbreviation: WISH; Walking In ScHools

Walk leader check lists were used to determine the number of walks each participant attended at each school.

Resources/Intervention costs

The indicative costs (Table 6) show that the total cost to implement the WISH Study was £12,050.94. The cost per school was £1,338.99, and the cost per intervention pupil was £44.30 across the school year.

Table 6. Summary of indicative implementation costs of the WISH study based on 2022/23 prices

Description of resources incurred	Total incurred (£)
Walk leader training
Trial Manager and Student Intern time	1,175.00
Trial Manager and Student Intern travel costs	363.60
Training materials	651.22
Resources	6,991.16
Total	9,180.98
Per school	1,020.11
Intervention implementation
Student Intern time and travel to school	1,310.40
Time for social media content development	94.67
Resources	241.00
Total	1,646.07
Per school	182.90
Booster session
Trial Manager and Student Intern time	1,175.36
Trial Manager and Student Intern travel costs	363.60
Resources	282.55
Total	1,821.51
Per school	202.39
Research Incentives
Water bottle	671.46
Earphones	789.26
Boost power bank	2,344.22
Hoody	8,246.00
Total	12, 050.94
Per school	1, 338.99

Per school costs were calculated by dividing the total cost by the number of schools; therefore, it is an approximate cost since participant numbers varied across schools. The Abbreviation: WISH; Walking In Schools. Walk leader training resources included stationery, MiBand wrist-worn heart rate monitor, walk leader badges, and hoody. Intervention resources included stationary incentives, posters, and certificates. Booster session resources included top walk leader prizes, teacher incentives, and stationery. Research incentives were provided to each participant upon return of the accelerometer after each data collection session.

Facilitators and barriers to intervention implementation

Factors associated with the successful implementation of WISH included: (1) school support for WISH, (2) walk leaders supported to get walks established, and (3) engaged walk leaders to maintain attendance at walks (Table 4).

School support for WISH

Although WISH was a peer-led intervention, the results indicate that teacher participation contributed to the success of establishing walks. Teachers collectively noted that the school calendar is busy and described supporting this research study as an additional task in an already full schedule.

“I am extremely busy but eh, maybe this, some aspects of this could be delegated to other members of staff I didn’t find eh I didn’t find it kind of an awful lot of work but on top of what I ready have I did find it was quite a bit” (teacher 301).

Walk leaders supported getting walks established

Walk leaders unanimously agreed the walk leader training and resources provided, prepared them for their role. As reported previously, walk leaders felt positive about the training programme [31] and they actively engaged with social media content (n120) posted by the Trial Manager.

Engaged walk leaders to maintain attendance at walks

Teachers discussed the selection of walk leaders as crucial for the success of establishing and implementing walks. Some walk leaders displayed initiative by creating a ‘Google Classroom’ for communication. Additionally, some leaders engaged with teachers and pupils, providing regular reminders about the walks and making announcements at assemblies and over the school intercom.

“So, we had to like go to every classroom and made sure the form, everyone’s form teacher knew, reminded them and stuff and that like you know we reminded them and all to come but once we got that sorted it was like a routine, everyone kept coming” (walk leader 306_02).

Barriers to implementation

Pupil engagement with the intervention was poor given the sub-optimal attendance at walks. The barriers which affected implementation included: (1) walk leader availability, (2) lack of time, (3) lack of appropriate facilities, and (4) social distancing restrictions because of the COVID-19 pandemic (Table 4).

There were occasions when walk leaders were not available to lead walks, particularly during exam periods.

“You see we started it off at break time but then you see our studies kinda and things, things would kinda our subjects were getting more stressful, we were doing like over like so more extra revision classes and things like that” (walk leader 319_09).

This is supported by the quantitative data indicating that the number of walks scheduled in schools was lower during school exam periods (February, May, and June) (Table 3).

A lack of time during morning recess and lunch affected attendance at walks, as well as adverse weather, and not having the appropriate facilities to accommodate an indoor walk. During the COVID-19 pandemic, “split breaks” were introduced, whereby breaks (recess or lunch or both) were staggered into separate times for different year groups, to reduce social interactions. As a result, pupils and walk leaders were not always allocated the same break, and in some instances, pupils within a school were not always on the same breaks as their peers or walk leaders.

Maintenance

Although the continuation of walks in schools was not assessed after the intervention, pupils, walk leaders, and teachers provided feedback on the viability of the WISH intervention and offered recommendations for improvement. Walk leaders acknowledged that a lack of participant engagement could hinder the maintenance of walks, yet some pupils and walk leaders believed that walks could be sustained. All teachers agreed that the program could continue at school, but they identified key factors to support its maintenance, such as staff engagement, promotion within the school, and improved communication between pupils and walk leaders.

“I mean the basic principle was like a short fifteen-minute walk you know ehm I think it’s just getting it organised and having the staff and having people to drive it you know to keep it going” (teacher 317)

Pupils and walk leaders also agreed that improved communication was necessary if the WISH programme was to be maintained, and platforms such as Google Classroom were proposed as a potential communication tool, to facilitate daily reminders for pupils.

“We had a Google Classroom and we just communicated that way.” (walk leader 317_06).

There is a need for school-based interventions to move beyond a focus on effectiveness and consider the contextual factors within schools that affect intervention implementation [44]. This in-depth process evaluation, using the RE-AIM Framework [29], provides a school setting context, discusses barriers and facilitators to implementation, and highlights the experiences of pupils, walk leaders, and teachers.

Given that the percentage of students who did not meet the recommended PA guidelines is consistent with the literature, the cohort of students recruited for the WISH Study was representative of the overall adolescent population in the UK and Ireland [45]. Pupils and walk leaders self-reported that the intervention positively affected their physical and mental health, as well as their social relationships and connections in the school. The walk leaders also benefited from the chance to gain valuable, transferable skills, including collaboration, leadership, and communication.

Despite the lack of effect of the intervention on device-measured PA [25], pupils and walk leaders acknowledged that the WISH intervention provided them with an opportunity to increase their PA and fitness. Additionally, some participants mentioned that they started engaging in other forms of PA as a result of the WISH Study. To understand why an improvement in device-measured PA was not found [25], it is necessary to consider the context in which the intervention was implemented, as the literature suggests [44]. The current study was impacted by inadequate participant involvement, which is consistent with previous research [46, 47], as the adoption of walking varied within and between schools. The feasibility study [22] that led to the development of the WISH Study did not detail intervention exposure, making it plausible that changes in activity were identified due to greater engagement with walks in the pilot study (pre-pandemic) compared to the full trial. Pupils and walk leaders cited harsh weather as a barrier to walking, and despite efforts by both school staff and the research team to facilitate an indoor walking route, a lack of acceptable facilities was an issue for some schools. This is consistent with other research that identified the need for adequate facilities and flexible timetables as critical factors for successful implementation [48, 49].

Several barriers affected intervention implementation. Like other school-based interventions [47, 50, 51], pupils in the current study consistently reported a lack of time, particularly at recess, as a barrier to attending walks. Additionally, the number of walks recorded in schools decreased during months when walk leaders were due to take examinations. Despite this, promoting active recess breaks remains a target component of school-based interventions [17]. This suggests a need to collaborate with schools to discuss ways in which students can be supported to be physically active during school breaks if active recess breaks are to be a successful component of future school-based PA interventions.

The research team supported walk leaders in developing a walking timetable to ensure consistent PA opportunities and scheduled at least two walks per day across the week. The introduction of staggered year-group recess and lunch breaks made it difficult to create a walking timetable in two schools. This was only identified during walk leader training; therefore, additional walk leaders and more training were required in these schools, delaying the adoption of walks for some pupils. A series of barriers have been highlighted here that affected intervention implementation; some were previously reported in the literature, while others emerged due to changes in the school environment caused by the COVID-19 pandemic, which were not anticipated during the intervention design.

The results of the current study indicate older pupils in the school context may be trained to serve as peer role models. This can create a more active, engaged, and cohesive school environment while fostering leadership skills and promoting long-term health benefits for both the pupils and walk leaders. Walk leaders reported feeling prepared for their role following the training and felt they knew to recognise walking at a brisk pace. Consistent with previous research [52], the concept of a peer-led school-based intervention was effective at encouraging younger pupils to be more physically active. The autonomous supportive style identified within the WISH Study also had a positive impact on walk leaders' well-being and provided them with the opportunity to develop many skills, as evidenced by the qualitative data obtained.

Central to the successful implementation of the WISH Study was a sense of 'whole school support,' whereby walk leaders felt supported to get walks established and remained actively involved with leading walks. This aligns with findings from the ‘Physical Activity 4 Everyone’ study that highlights a lack of whole school engagement negatively impacted intervention reach and implementation [53]. Greater input from school staff to make adaptations, such as adjusting walk schedules, could be a determining factor in the adoption, implementation, and maintenance of walks. School-based interventions often report challenges with engagement from school staff, given the nature of the busy environment they work in [27, 46, 47]. Schools having the autonomy to appoint additional staff and/or students as walk leaders could address some of the barriers identified in the current study. Consultation with senior leadership at the research development stage could help researchers better understand how PA could be best integrated and maintained within the school setting by providing insights into resource allocation.

Strengths and limitations of the study

The WISH Study was a fully powered cRCT with a robust methodology that incorporated PPI, which was central to the design, conduct, and dissemination of the study [31]. This paper uses process evaluation data embedded within the WISH Study design, and the use of the RE-AIM Framework is a strength of the research process that corresponds with existing MRC guidelines [26]. However, randomisation and walk leader training could only occur after baseline data collection was completed; therefore, the intervention was not introduced to schools until the end of November or the start of December. This inhibited the opportunity for schools to fully establish the walking program before the Christmas holidays. Future school-based interventions should carefully consider the timing of intervention commencement to maximize implementation, ensuring that sufficient time is allowed for schools to establish and integrate the intervention effectively.

When interventions are ‘scaled up’ from pilot studies to fully powered trials, their effects are frequently shown to be diminished [52], emphasising the significance of embedded process evaluation in the study design of interventions such as the WISH Study. The process evaluation aided in determining the individual and system-level factors in the educational environment that affected the implementation of the WISH Study. Poor implementation and adherence to scheduled walks were key limitations of the study, resulting in reduced participant exposure to walking during the school day.

RE-AIM: Reach, Effectiveness, Adoption, Implementation, and Maintenance; PA: Physical activity; MVPA: Moderate to vigorous physical activity; NI: Northern Ireland; COVID-19: Coronavirus Disease; MRC: Medical Research Council; WISH: Walking In ScHools Study; YAG: Youth Advisory Group; PPI: Patient and Public Involvement; cRCT: Cluster randomised controlled trial; PE: Physical Education; PP: Person parameter; SD: Standard deviation; BREQ-3: The Behavioral Regulation in Exercise Questionnaire; SPSS: Statistical Package for the Social Sciences; COREQ: Consolidated criteria for reporting qualitative research; BMI: Body mass index.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

The study received ethical approval from the Ulster Ethics Committee (REC/19/0020) on June 20^th, 2019. All pupils provided assent and parents/guardians provided informed written consent before data collection. Walk leaders completed an agreement form which indicated their consent to take part in the research and take on the role of a peer walk leader.

CONSENT FOR PUBLICATION

As part of the informed consent process, parents/guardians provided written consent for their child’s data to be used for this research study which includes publication of findings in scientific journals.

AVAILABILITY OF DATA AND MATERIALS

A de-identified dataset can be made available for non-commercial purposes from the corresponding author on reasonable request and permits use, distribution, and reproduction in any medium, provided the original work is properly cited.

COMPETING INTERESTS

All authors have completed the ICMJE uniform disclosure form at http://www.icmje.org/coi_disclosure.pdf

FUNDING

The WISH study was funded from INTERREG VA funding of €10.601,181.20 (incl. 15% contribution from the Department of Health in Northern Ireland and the Department of Health in Ireland) that had been awarded to the Health and Social Care Research and Development Division (HSC R&D) of the Public Health Agency, Northern Ireland and the Health Research Board in Ireland for the Cross-border Healthcare Intervention Trials in Ireland Network (CHITIN) Project.

DISCLAIMER

The views and opinions expressed in this article do not necessarily reflect those of the European Commission or the Special EU Programmes Body (SEUPB).

AUTHORS’ CONTRIBUTIONS

MHM, AMG, AC, RJ, IML, and MF contributed to the conception and design of the WISH Study and SMOK assisted with the design of the process evaluation. LCD and SMOK were Trial Managers and LCD, SMOK, and GMcD were responsible for data acquisition. IL, LCD, and SMOK conducted the quantitative analysis. LCD conducted the qualitative analysis and prepared the first draft of the manuscript. AC assisted with the qualitative analysis and interpretation of the results. All authors revised the manuscript, agreed to be fully accountable for ensuring the integrity and accuracy of the study, and read and approved the definitive version of the manuscript. All authors meet the criteria for authorship and are included as co-authors on the title page.

ACKNOWLEDGEMENTS

The authors would like to thank all participating schools, including the reception staff, key teachers, and the senior leadership teams of participating schools. We are extremely grateful to all the pupils and walk leaders. Thanks to the undergraduate placement students who supported the research (Naomi Bell, Jordan Fleming, Tessa Campbell, Caitlin Fallis, Clare Conway, Samantha McCombe, Elisha McBride, and Layla Alvey), and post-graduate students (Sinead Martin, Jordan Kavanagh, Sofia Marini and Daniel Fernández Argüelles). We thank Yolande Butcher, WISH Support Assistant, for her continued support throughout the study and Dr Geraldine Horigan for conducting the qualitative data collection.

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No competing interests reported.

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A process evaluation of the Walking In ScHools (WISH) Study using the RE-AIM framework

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