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PLOS Global Public Health logoLink to PLOS Global Public Health
. 2023 Aug 16;3(8):e0001786. doi: 10.1371/journal.pgph.0001786

Predictors of successful return to parkrun for first-time adult participants in Scotland

Andre S Gilburn 1,*
Editor: Nnodimele Onuigbo Atulomah2
PMCID: PMC10431652  PMID: 37585404

Abstract

Physical activity is essential for promoting good health and reducing burdens on healthcare systems. parkrun organise free weekly events where participants complete a 5km route. Studies have identified characteristics of participants associated with lower levels of participation. The aim of the study was to identify predictors of the likelihood of returning to parkrun for first-time adult participants. The return rate of adult first-time participants was determined for all 5km parkrun events in Scotland over a 1-year period from February 2019. The dataset consisted of 20,191 adult participants made up of 11,459 females and 8,732 males across 58 venues. A General Linear Mixed Model was used to identify factors associated with return rate. Return rates were negatively correlated with event size and positively correlated with the proportion of first-time adult participants at the event. Age was positively correlated with return rate and males were more likely to return. New participants that finished in a relatively slow time were disproportionately less likely to return. Return rates were positively correlated with the amount of freshwater and woodland on the route. These findings provide potential opportunities to manage events to enhance their efficacy. Specific events could be promoted as first-timer days to encourage new participants to attend together. New events could be prioritised in proximity to events that currently experience high attendances to reduce attendances locally. As the presence of freshwater and woodland are associated with higher return these habitats could play a role in generating the benefits of green exercise. If so the creation of more routes running through or alongside these habitats could be beneficial. The findings are likely to be widely applicable to other mass participation events and those interesting in understanding the mechanism by which green exercise provides its benefits.

Introduction

Global patterns in physical activity

Estimates suggest there are 1.4 billion adults partaking in insufficient levels of physical activity globally [1]. This can lead to a range of diseases and place additional burdens upon healthcare systems [2]. Consequently, promotion of wider participation in physical activity has become a global priority [3]. The environmental context within which people exist can play an important role in driving levels of physical activity and defining patterns of inactivity [4]. These upstream factors can have both negative and positive influences and their management could influence their impacts. Upstream factors can include provision of more positive influences such as safe and pleasant physical spaces in which to exercise [4] and mass participation events that make use of these spaces to encourage group exercise and the additional social benefits that this generates [5].

parkrun

One example of a positive upstream factor is parkrun who organise approximately 2000 free weekly 5km events across 22 countries [6]. These events often occur in public parks but also make use of other suitable public areas. Events also occur on private property such as estates, university campuses, nature reserves and forestry. Events are designed to promote inclusivity with participants allowed to use wheelchairs, run with young children, use walking frames, push buggies and run with a dog. There is no also requirement to complete the route within a time limit with walking now being actively promoted through the parkwalk at parkrun initiative [7].

parkrun have a mission to create a healthier and happier planet [8]. Studies into the impacts of parkrun have revealed that it does indeed provide both a physical and mental health benefit to its participants [913]. A combination of initiatives and the inclusive regulations means that some traditional barriers to partaking in sport and exercise are not present within parkrun [5]. Studies have also shown there are more barriers to participating in physical activity for women than men [14, 15] and that the context in which women will engage in physical activity can differ from that of men [16, 17]. Motivations for taking part in physical activity also differ between the genders [18, 19]. Understanding how the genders respond to the provision of positive upstream factors, such as parkrun, is likely to be crucial to their management and effectiveness [20].

In addition to physical health benefits, both participants and volunteers gain social network rewards from being part of the parkrun community [5, 2128]. Engagement with parkrun has also been found to promote a more positive sense-of-self [29]. Testament to the success of parkrun is highlighted by the important role it is now playing in social prescription, with many medical practices in the UK being linked to specific parkrun locations, with parkrun being prescribed to patients as part of their treatment [3033]. So, the benefits of engaging with parkrun are truly multifaceted.

Green exercise and parkrun

As all parkrun events occur outdoors they encourage engagement with the natural environment with studies identifying additional benefits of green exercise [5, 3437] compared to exercising indoors in a gym. Studies have also found that exercising in more natural environments seems to have more benefits compared to exercising in urban green spaces [36]. parkrun routes utilise both urban green spaces and other more natural environments. The setting could influence the benefits gained from attending a parkrun. For example, completing a parkrun event that runs alongside water might also provide additional mental health benefits as exposure to blue spaces has been found to be associated with better mental health [38].

Using data science to further our understanding of parkrun

The majority of studies of participation in parkrun have used qualitative methodologies particularly in the form of surveys. Quantitative approaches such as data science can also be applied to identify predictors of engagement with parkrun by through large-scale statistical modelling of the parkrun results dataset. Data science can be used to address specific questions about participation in parkrun and also to identify previously unknown patterns and associations between various factors and participation levels [10, 22, 39, 40]. One key advantage of data science studies is the samples will not be affected by survey bias [41]. When participants register with parkrun they are allocated a unique identification number [39]. They use this number after completing a parkrun to get their finishing time and be included in the results. The results of each event are published on the parkrun website generating a dataset on the finishing time, gender and age group for millions of participants and many millions of participations. The dataset could contain considerable amounts of novel information about associations between levels of participation and various characteristics of both participants and events. There have been relatively few quantitative studies utilising the results of parkrun events to further our understanding of its impacts and benefits [10, 22, 39, 40]. This relative lack of studies utilising the parkrun results database is surprising as one of the studies that pioneered research into parkrun used finishing times as a proxy for fitness [10].

Three studies have used the parkrun dataset to understand patterns of participation [22, 39, 40]. The first study was conducted in Tasmania and found that those with lower levels of education are more likely to regularly participate in parkrun showing evidence of how inclusive it can be [22]. A study in Scotland found that the performance of the parkrun population was falling even though it was on average increasing for individual participants showing that parkrun was becoming increasingly inclusive by attracting more inactive participants [39]. A recent study in the UK, Ireland and Australia has identified that 43% of people who register for parkrun never take part in an event and a further 22% only participate once [40]. This study questioned those that registered for parkrun to identify barriers to participation and returning. This identified that women, younger adults and the inactive were least likely to participate or return. The main barriers identified were the inconvenient start time and the feeling of being too unfit to participate. The latter was more commonly reported by women than men.

Aim of the study

There remain many unanswered questions with respect to what motivates people to engage with parkrun. The overarching aim of this study is to use quantitative analyses of the behaviour of new parkrun participants to address some of these key knowledge gaps and to identify previously unknown associations with returning to participate in parkrun for a second time. The questions addressed by the study can be separated into two broad groups.

  1. What characteristics of new participants predict their likelihood of returning to parkrun? Previous studies have investigated associations between age and gender with return rates. This study includes an additional new characteristic of participants, their finishing time, and investigates previously unexamined interactions between these factors.

  2. What characteristics of parkrun events predict the likelihood of new participants returning to parkrun? The following characteristics of events were considered: field size; proportion of new participants; gender ratio of participants, the proportion of land cover types the routes proceed through; distance to the next nearest event; elevation gain; surface type. No previous studies have investigated if any of these characteristics are associated with levels of participation in parkrun, however, one previous study has shown that distance to the next nearest event, elevation gain and surface type are all associated with performance [39] which another has shown to be associated with levels of participation [10].

These overarching research questions will enable the following key specific hypotheses to be tested for the first time.

  1. Is the proportion of other new participants at a parkrun event associated with the likelihood of new participants returning to parkrun?

  2. Is the proportion of other new participants at a parkrun event associated with the likelihood of new participants returning to parkrun?

  3. Is the finishing time of new participants at a parkrun event associated with likelihood of them returning to parkrun?

  4. Is the land cover type that a parkrun route passes through associated with likelihood of new participants returning to parkrun?

  5. How do the gender and age of participants interact with any new associations identified when answering the specific questions above?

Methods

Ethics statement

This was an analytical study of aggregated secondary data and as such had no active participants. Ethical approval was obtained from the Stirling University General University Ethics Committee (EC 2022 10861 8035).

parkrun data

The study included data from all 58 5km parkrun course locations that held a parkrun event in Scotland over a year long period from February 2019 to January 2020. The course locations comprised a range of event location types including 33 in public parks, eight coastal events using esplanades and the areas surrounding them, eight events used traffic-free paths, three occurred on private estates, three on university campuses, one in a forestry, one on a Local Nature Reserve and one on public roads.

The results page for all events were accessed and processed using an Excel macro which extracted information about each participant including their age category, parkrun ID number, gender, age group, finishing time, number of participations, date and whether the participant was a new parkrunner [42]. An example results page is available here [43]. Any unknown participants (participants who completed the event without presenting an identification number) and participants under 18 years of age were removed from the dataset. Adults participating in their first parkrun were identified amongst the remaining participants. All other records were removed resulting in a dataset of new parkrun participants who attended an event in Scotland over that one-year period. The dataset consisted of 20,191 adult participants made up of 11,459 females and 8,732 males across 58 different event venues.

Age for adult participants is provided in the parkrun results as a 5-year cohort except for 18–19 year olds. Age was converted to a continuous variable by assigning participants the mid-point for their cohort group for all new parkrun participants. The parkrun identification number of all new participants was used to access their parkrun participation history to determine whether they had subsequently returned to parkrun. These were accessed in November and December 2022. Consequently, new participants had a period of at least 33 months up to a maximum of 46 months after their first participation to return to parkrun. It should be noted that Scottish parkrun events were suspended for a period of 17 months between March 2020 and July 2021 so the return time was in effect a shorter period of 16 to 29 months where active events were occurring in Scotland.

Additional characteristics were collected for the first event each of the participants attended. These were the number of participants, the number of new adult participants and the gender ratio of the participants. The following additional event characteristics were used: elevation gain in m; surface type (scored 0 for soft surfaces such as trail, 1 for mixed soft and hard surfaces and 2 for hard surfaces such as tarmac); the shortest travelling time in minutes by car from the recommended parking of an event to the recommended parking of another parkrun events as determined from Google Maps. This was used as a measure of the remoteness of an event from other parkruns [39].

Land cover data

Each parkrun event location provides a map of its route. An example is available here [44]. The course routes for all 58 Scottish event venues that hosted a parkrun during the study period were downloaded in Keyhole Markup Language format and imported into the GIS software package Digimap Edina [45]. Measuring tools within the aerial roam feature were used to mark out a 30m distance from the route and the total area within the zone determined and recorded. The land cover types within the zones were classified using satellite imagery on Digimap and the proportion of each type within each zone determined. Land cover was classified into the following types: woodland, grassland, freshwater, saltwater, shore, urban and other. Other included anything that could not be classified into the other six land cover types and only comprised on average just 2.3% of the total area surrounding events.

Statistical methodology

The data were analysed using R x64 4.1.1 [46]. A generalized linear mixed model (GLMM) with a binomial error distribution was used to model participants returning to parkrun. This was generated using the glmer function in the lme4 package [47]. Quadratic terms were included in the model of returning to parkrun for finishing time, number of participants, proportion of first-time participants and date. Event venue was included as a random effect. All continuous explanatory variables were scaled to have a mean of zero and a standard deviation of one including quadratic terms. Minimum Akaike Information Criterion was used to select the optimal model.

Results

Factors determining the return rate of first-time parkrun participants

The overall return rate of first-time participants to parkrun was 64.18% (12,959 of 20,191). A GLMM identified several significant associations with return rate (Table 1). There was a significant increase in return rate with age (Table 1, Fig 1). Date was strongly negatively associated with return rate. A significant quadratic term shows that the association with date weakens over time. Male participants (66.5%, 5,805 of 8,732) were highly significantly more likely to return (Fig 1) than female participants (62.4%, 7,154 of 11,459). The finishing time at a participants first parkrun was also an important determinant of return rate. The non-significant linear term and significant quadratic term suggests little effect of time on return amongst the faster runners but a disproportionately negative impact of the slowest times on return rates (Fig 2). There was a highly significant quadratic association between the proportion of new participants at an event and return rate, with participants disproportionately more likely to return after attending events with the highest proportion of new participants (Fig 3). There was also a highly significant association between event size and return rate with first-time participants more likely to return when attending smaller events. The travelling time to the next nearest parkrun also was negatively correlated with return rate. The mean travelling time to the next nearest event was 30 mins for those that returned and 33 mins for those that did not return.

Table 1. A GLMM with binomial error distribution of return rate to parkrun of adult first-time participants.

All continuous explanatory variables were scaled. Three interaction terms and three quadratic terms were retained in the model.

Parameter Z20,174 Estimate Standard Error P
Intercept 15.09 0.556 0.036 <0.001
Age 9.97 0.159 0.016 <0.001
Date 3.99 -0.058 0.015 <0.001
Date2 3.98 0.058 0.015 <0.001
Gender(male) 2.40 0.083 0.034 0.016
Proportion of first-timers 1.81 -0.075 0.042 0.070
Proportion of first-timers2 3.59 0.155 0.043 <0.001
Number of participants 3.39 -0.103 0.030 0.001
Finishing time 1.26 0.117 0.093 0.207
Finishing time2 2.95 -0.266 0.090 0.003
Travelling time to next parkrun 2.69 -0.067 0.027 0.012
Surface type 1.77 0.058 0.033 0.077
Woodland 2.34 0.090 0.038 0.019
Freshwater 2.31 0.092 0.040 0.021
Woodland*Freshwater 1.51 0.078 0.052 0.131
Gender(Male)*Freshwater 2.54 -0.076 0.030 0.011
Age*Freshwater 1.92 0.029 0.015 0.055

Fig 1. The return rate of adult first-time participants to parkrun events in Scotland against their age.

Fig 1

Standard error bars are provided for the mean return rate for each age cohort for both sexes.

Fig 2. The return rate of adult first-time participants to parkrun against their finishing time.

Fig 2

Standard error bars are provided for cohorts based upon finishing time. N.B. Finishing time was treated as a continuous variable in the analyses. Cohorts have simply been created to aid illustration of the data.

Fig 3. The proportion of first-time adult participants to Scottish events that returned to parkrun against the proportion of new adult participants at the event venues they attended.

Fig 3

Standard error bars are provided for cohorts based upon the proportion of adult participants attending events. N.B. Proportion of new adult participants was treated as a continuous variable in the analyses. Cohorts have simply been created to aid illustration of the data.

Return rates were also positively associated with the amount of woodland and freshwater at an event. In the case of freshwater, a significant interaction term with gender reveals a stronger association between return rate and the amount of freshwater on a route in female than male participants. Gender ratio of the field and elevation gain were not retained in the model.

Discussion

What characteristics of new participants are associated with their likelihood of returning to parkrun?

The overall return rate of 64.18% is higher than the 61.95% reported in an earlier study [40]. In the current study participants had a longer period of time within which to return (33–46 months compared to 2 years). However, Scottish parkruns were suspended for 17 months during the pandemic meaning that the possible return period was effectively 16–29 months which is on average slightly shorter than the previous study. This suggests that Scottish parkruns might have a relatively high proportion of new participants that return to parkrun. As this study included data from both sides of lockdown an additional study of the impact of lockdown on the return rates of new parkrun participants would be needed to fully understand if Scotland does on average have higher return rates than the rest of the UK, Ireland and Australia. Furthermore, another study identified that parkrun participants in Scotland are increasing in age [39], so this could simply be a consequence of an older population of parkrun participants being considered here compared the previous study, as older new participants are known to be more likely to return.

Age and gender were both found to affect likelihood of returning to parkrun for first-time participants in Scotland. This is consistent with the finding of the larger scale study covering the UK, Ireland and Australia [40]. The gap in return rate between the genders was slightly wider in Scotland (66.5% for males, 62.4% for females) compared to the broader geographic study that found return rates of 63.7% for men and 60.4% in women [40]. The wider gap in Scotland might be indicative of a larger gender gap in activity in Scotland compared to other regions. A gender gap in activity has been previously reported among school children in Scotland [48]. Extending the current study design to include other regions would allow determination of whether Scotland does have a relatively wider gender gap compared to some other parkrun nations.

The broader geographic study found from surveying participants that those that engaged more readily in physical activity were more likely to return. The current study found that first-time participants with finishing times of over 40 minutes (Fig 2) had disproportionately low return rates. Those that exercise more regularly are likely to be fitter, and therefore run faster times [10] so this finding is also consistent with the previous study suggesting that the least active, and those most likely to benefit from parkrun, are those that are least likely to return [40].

A key barrier to participation has been identified in a previous study as the psychological fear of not being fit enough to participate [40]. The current study found that finishing with a particularly slow time was associated with lower return rates which adds additional evidence that being relatively unfit is a barrier to continued participation. The parkwalk at parkrun initiative was introduced in September 2022 with the aim of encouraging and promoting walking. This could really help make slower new participants feel more welcome. A study looking at return rate of relatively slow new participants before and after parkwalk at parkrun was launched could determine if it is contributing to making slower new participants feel more welcome by increasing the proportion of them that return.

What characteristics of parkrun events are associated with the likelihood of new participants returning?

This study was the first to investigate what characteristics of parkrun events are associated with the return rate of first-time parkrun participants. Those who attended events with a higher proportion of other adult first-time parkrun participants were more likely to return. First-time parkrun participants were also more likely to return after attending events with smaller field sizes. These two findings, together with the finding discussed earlier that new participants recording particularly slow finishing times were particularly unlikely to return, could relate to how much a new parkrun participant feels a part of the parkrun community. The social rewards gained from feeling part of the parkrun community have been identified as being important in a range of studies [2527, 35, 49, 50]. Attending events with friends and family has been found to be an important motivator for participating in parkrun [35]. This shared experience of completing their first run with others could be contributing to them feeling part of the parkrun community. The higher return rate of those attending with other new participants could be partly driven by new participants who are known to each other attending their first event together. Future studies investigating whether it is individuals attending their first events in groups or unknown individuals sharing the experience of their first participation that drive this association would be useful for understanding the management implications of this finding.

First-time participants who attended an event where the travelling time to the next nearest event was shorter were also more likely to return. This suggests that density of parkrun event locations within an area could be influencing return rates with individuals more likely to return to parkrun in areas with a higher density of event venues.

This study was only the second to try to relate geospatial features of parkrun routes to a measure of the outcome of the experience, in this case likelihood of returning to parkrun. Both the amount of freshwater and woodland that new parkrun participants were exposed to were positively associated with their likelihood of returning. Studies have revealed additional benefits to green exercise in more wild landscapes than urban green spaces [36]. Assuming return rates of new participants to parkrun are related to level of positivity of the experience then the current study suggests in the context of parkrun that woodland and freshwater could be encouraging people to return by enhancing the quality of green exercise. This would mean there is potential to manage the influence of parkrun as a positive upstream factor by prioritising the creation of new routes alongside freshwater and woodland.

Studies investigating what aspects of exercising in woodland and alongside freshwater might enhance the green exercise experience would be valuable. For example, what is the nature of the stimuli enhancing the benefits of exercising in green spaces. Is it visual stimuli from for example seeing trees and water. Is it olfactory stimuli, for example smelling plants such as wild garlic in woodlands, or it is auditory stimuli such as the sounds of bird calls. The fact that parkrun have numerous events all taking place at the same time and on the same time of the week but in varying locations means that parkrun provides a potentially unrivalled opportunity for understanding how the benefits of green exercise are gained.

Another notable finding from the study was that freshwater was positively associated with return rates but saltwater was not. This could suggest that freshwater has a more positive impact upon parkrun participants but alternatively it could be caused by another correlated factor. For example, coastal areas will experience higher wind speeds, which might have a negative impact on return rates and possibly negate the positive benefits gained from running alongside water. Further study is required to establish why the experiences of running alongside freshwater and saltwater has different impacts on return rates of new parkrun participants and what relevance this might have to the benefits of green exercise.

Implications for parkrun

One of the key findings of this study is that in terms of encouraging continued engagement with parkrun not all parkrun venues are equal. Variation in size, distance from other events, proportion of new participants and the amount of woodland and freshwater on the route are all associated with return rates. Therefore, it might be possible to enhance the role of parkrun as a positive upstream factor by increasing the attractiveness of parkrun venues to new participants. As route design could influence whether first-timers return, parkrun might want to consider the mechanism by which new events are created and whether they can add more flexibility to these processes to encourage the introduction of more parkruns with characteristics associated with higher return rates. For example, parkrun have prioritised the creation of events on socio-economic grounds after inequalities were identified in the distribution of parkrun events in England [51]. After receiving funding to create 200 new events a study identified the ideal locations to reduce these inequalities [52]. In addition to more managed event creation, the fact that this study identified that return rates were higher at smaller events and at events where the travelling time to other events was lower, both support the continued creation of more parkrun venues through more traditional routes, assuming that local communities can sustain additional events by providing enough volunteers willing to contribute to organising them.

The discovery that new participants are more likely to return after attending an event with a higher proportion of other first-time participants suggests that parkrun might want to consider introducing specific event days to which new participants are particularly encouraged to attend, so increasing the proportion of new attendees present at those events.

Another implication of the findings of this study relates to the parkrun practice initiative [3033]. Practitioners utilising the parkrun practice might want to consider prescribing specific local event parkrun events that could particularly increase the patient’s likelihood of returning, for example, by recommending smaller events or where the route goes through woodland and alongside freshwater. Furthermore, patients could be encouraged to attend their first parkrun as a group, or with friends and family.

Limitations of the study

Data science studies are excellent for identifying previously unknown associations between variables but limited in their ability to determine cause and effect as the data are not primarily collected in order to test predictions of hypotheses. This means that all the findings of the study are correlational. Consequently, data science studies of this type are particularly useful for generating new hypotheses that can be tested in other studies but are more limited in providing tests of those hypotheses.

The study was also limited to a year-long period due to the considerable time needed to generate the dataset. It is known that the gender gap in participation has been narrowing and this could be partly driven by changes in the return rate of the different genders over time [39]. Therefore, it would be useful to compare this study to other time periods to determine how general the findings are. It is notable in this study that although return rates were lower for female first-time participants there were still more returning female than male first-time participants because the difference in return rate was more than compensated by the higher proportion of female first-time participants. Therefore, the study period was associated with a clear narrowing of the gender gap and shows that, at least in Scotland, the majority of new participants that return to parkrun are actually female. This suggests that parkrun is successfully overcoming traditional barriers to female participation in physical activity.

The restriction of the study to Scotland is another limitation. It would be useful to conduct similar analyses of parkrun return rates in other areas to determine the generality of the findings.

The COVID-19 pandemic resulted in parkrun being suspended in Scotland for a period of 17 months. This could have impacted the return rates of participants as lockdown is known to have substantially impacted the levels of physical activity with reductions in activity particularly amongst the less fit, the young and women [53]. The sample duration for first-time participants was specifically chosen to cover the full one-year period before news of the potential pandemic hit the media to reduce the impact of the pandemic influencing the sample but while still making the study reasonably current. Therefore, all participants included in this study attended their first event without knowledge of the pandemic, but many will have not returned by the point that news of the emerging pandemic was hitting the media. The higher return rates found in this study which straddles the covid suspension compared to the one previous study [40] which was conducted prior to the pandemic suggests that it may not have substantially negatively impacted return rates. It would be interesting to investigate the impacts of the pandemic on return rates further by investigating them for first-time participants from February 2020 onwards when they would have known about the pandemic when they first attended parkrun.

Conclusion

This study has identified various novel features of parkrun events that are associated with the likelihood of first-time participants returning to parkrun. Identification of these features provides parkrun with additional information that could be potentially used to manage their events to increase their efficacy. The results also have potentially important wider implications for other organisers of mass participation events as the same characteristics associated with return rates at parkrun events are likely to be more widely applicable. The findings of the study also extend our understanding of green exercise by suggesting that exercising in woodland and alongside freshwater could be important components of the benefits gained by exercising outdoors in a green space.

Acknowledgments

The author would like to thank Euan McDiarmid for generating the landcover data. The author would also like to thank Kate Black and an anonymous referee for providing constructive comments on an earlier version of the manuscript. The author acknowledges the use of data owned by parkrun Global. The data have been accessed as a permitted act for independent non-commercial research purposes through fair dealing legislation allowing access to publicly available databases. Only a tiny proportion of the parkrun results database was accessed (data from just 58 of more than 2000 events). The author has no official connection to parkrun but is a regular participant and volunteer.

Data Availability

The full dataset is available in the University of Stirling datastorre http://hdl.handle.net/11667/210.

Funding Statement

The author received no specific funding for this work.

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001786.r001

Decision Letter 0

Joseph Donlan

25 Apr 2023

PGPH-D-23-00368

Characteristics of parkrun That Encourage New Participants to Return

PLOS Global Public Health

Dear Dr. Gilburn,

Thank you for submitting your manuscript to PLOS Global Public Health. After careful consideration, we feel that it has merit but does not fully meet PLOS Global Public Health’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Your manuscript has been assessed by two expert reviewers, whose comments are appended below. The reviewers have highlighted concerns about several aspects of the methodology and the clarity of the rationale for the specific study design you used. Please ensure you respond to each point carefully in your response to reviewers document, and modify your manuscript accordingly.

Please submit your revised manuscript by Jun 09 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at globalpubhealth@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pgph/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Dr Joseph Donlan

Senior Editor

PLOS Global Public Health

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1. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I don't know

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Reviewer #1: No

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS Global Public Health does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you very much indeed for the opportunity to review your article on the characteristics of parkrun that encourage new participants to return. Your article has used linear modelling and associated statistics on pre-existing data (parkrun results database) to assert that return was more likely for older males, faster runners, smaller events, and where there were a greater number of other first timers.

As also holding the identity of a Run Director for parkrun in an area of high obesity and a very broad socio-economic status (but a large event without water on the route itself!), I found this especially interesting. Your use of pre-existing data from across parkrun events is a very suitable and objective dataset which reduces potential issues around for example perceptions of returning. I do though have concerns that if this paper was read by someone outside of the community that they might struggle to understand what parkrun is, how it operates and what this data you are using is.

I do also have concerns about the data used and the decisions that you have made at the outset, without an extensive review of the literature, notably, that only certain characteristics will encourage return. In consequence, it is risky asserting that you are identifying “characteristics” of parkrun that encourage return. You are actually identifying a subset of characteristics from a very bounded set of characteristics.

Overall, I think this paper has potential to contribute to the field, but does need significant reconsideration from the current format.

Consequent of these overall concerns, I do have significant reservations about the paper. My major concerns are as follows:

• The structure of the Introduction is unclear. For example, it is unclear what parkrun is and why it is important. At present, the structure of the paper assumes insider knowledge. For example, where are these events located (e.g. line 65 needs context!). I think that the paper needs to start with an introduction to the growth in physical activity before moving to the barriers that individuals might face. You should also provide some explanation or evidence as to why you are indicating a connection between women and morbid obesity. I actually don’t think that you are suggesting this but the construction of the first paragraph indicates that this is the case!

• No clear aim of the paper and/or research question is stated. You merely assert that you are applying a generalized linear model to the data – but why is this necessary?

• You have not really examined the literature to document what previous studies both within parkrun but also relating to exercise more broadly, have shown / told us. You assert that previous studies of parkrun have used descriptive statistics. This omits to recognise that qualitative studies have also been undertaken, for example, Warhurst & Black (2022) “Lost and found: parkrun, work and identity”, Qualitative Research in Sport, Exercise and Health https://doi.org/10.1080/2159676X.2021.1924244

• As indicated above, you have discerned only a very limited number of characteristics that you consider will encourage return without justification for the selection of these specifically. An extensive literature within health, psychology and sport/exercise has examined multiple other factors that have been shown to influence likelihood of exercise (and of parkrunning). For example, why have you collected data re water without considering other terrain that have been shown to enhance wellbeing such as open space generally within large urban environments (e.g Birch, J., Rishbeth, C., & Payne, S. R. (2020). Nature doesn't judge you–how urban nature supports young people's mental health and wellbeing in a diverse UK city. Health & Place, 62, 102296; also Martin, L., White, M. P., Hunt, A., Richardson, M., Pahl, S., & Burt, J. (2020). Nature contact, nature connectedness and associations with health, wellbeing and pro-environmental behaviours. Journal of Environmental Psychology, 68, 101389). There are a number of systematic reviews of this literature. In the case of parkrun itself you have also not taken account of what has been shown to be a key factor in sustaining the parkrun community – that of the social aspects that surround the run such as the availability of a café or refreshments and/or post-run community gathering/s – see for example, Hindley, D. (2022). “More than just a run in the park”: an exploration of parkrun as a shared leisure space. Leisure Sciences, 42(1), 85-105; also Morris, P., & Scott, H. (2019). Not just a run in the park: a qualitative exploration of parkrun and mental health. Advances in mental health, 17(2), 110-123

• Methods: It is not clear from where you sourced the data that you analysed? You indicate that it is the parkrun results but someone without knowledge of parkrun won’t know what/where. Why only 56 events that data was extracted from? Why those 56? Were these just UK? Have you taken account of location more broadly?

• Within the findings, a number of assertions are made that are unclear:

o (line 183/184) that “those that engaged more readily in physical activity were more likely to return” but what is meant by this as you do not have data on exercise readiness?

o (lines 198-200) “Individuals who enjoyed the general experience of parkrun but maybe not the specific course at the venue they attended could be more likely to try a different parkrun if they have another local alternative”. What is your evidence for this assertion?

o (lines 203-204) “first-time participants with the slowest finishing times were more likely to attend smaller and more remote events”. Do you know this, or is it that smaller events typically have slower participants? – and perhaps there is a reason for this, for example, are they new events, remote events, specific terrain etc. etc.?

• You do not interpret the data/findings is made. As one example, the first para suggests, that returning to Scottish parkruns had a higher likelihood than shown in the wider data but it isn’t clear why (needs explanation) and the implications of this – especially given the health data for Scotland as a whole (although whether the hard-to-get-to are actually ever parkrunning …??)

• The implications asserted from the findings indicate that the author does not fully understand the context of parkrun and how/when new parkruns are established! The establishment of a parkrun depends upon the availability of an open space that facilitates a safe 5k route, the availability of a team of volunteers (typically relates to the socio-economic status of the area / social capital of the lead), the willingness of a landowner. New concepts / practices are asserted at this stage. For example, social prescribing is potentially really important for the whole paper.

In addition to the more major concerns that I have, I feel that greater clarity is needed as follows:

• p.3 It needs to be clear that parkrun is a running event as the preceding sentence refers to cycle routes.

• Further explanation of parkrun is also needed as the current description assumes insider knowledge of the events and the datasets. For example, do you mean that by 2020 over 30m runs had been completed? (and is the COVID pandemic actually a necessary statement?).

• Ensure that all assertions are evidenced – for example, line 68, previous studies – what previous studies?

• Take care using the term “primary data source” (line 82) as this might lead the reader to think you are generating primary data (ie an empirical study)

I look forward to seeing a revised version of the paper.

Reviewer #2: Review

This paper presents secondary data analysis from the parkrun database. It focuses on adult parkrun participants in Scotland between 2019-2020 – looking particularly at new participants who return. The authors have presented a generalised linear mixed modelling analysis and found important factors that influence whether participants return. These factors are important considerations for parkrun in encouraging new participants to return and when planning new events. This is a well-written manuscript; the text is clear and easy to read. It is also relevant to the journal and would interest the reader. My main concern with the paper is in level of detail. A stronger rationale is needed for why the paper focuses on parkrun, more detail is needed in the methods to explain how “remoteness” and travelling time were determined and the wider implications of the findings (beyond direct implications for parkrun) could be considered as this will interest a wider readership.

Major issues with this paper:

1. I would like to see a stronger rationale/justification for why parkrun is being used as an example of a “positive upstream factor” in this paper. What role could parkrun play in the global obesity epidemic? – perhaps here draw upon the potential for parkrun as a social prescription offer by health practitioners. Is it just the obesity epidemic that parkrun is potential useful for? Why is it important to understand patterns of participation, what could we do with this information? Perhaps the authors could use the existing parkrun research evidence base more to support this justification.

2. The methods section would benefit from detail around:

a. How remoteness of parkrun venues was determined

b. How travelling time to parkrun venues was determined

3. Parkrun is used here as an example of a ‘positive upstream’ initiative that can have an important role in the obesity epidemic.

Minor issues

Please see below for issues related to each manuscript section.

Title

I think the title would benefit from extra detail about the methods and/or location, also that the focus is on adults - if title word limit allows. A suggestion below – just a suggestion!

Characteristics of parkrun That Encourage New Adult Participants to Return: Generalised linear mixed modelling of parkrun data from Scotland

Abstract

Abstract provides a succinct summary of the research. More detail of the methods would be beneficial. For example – how many parkrun events were analysed

Line 16: GLMM is used in the abstract – should be written in full.

Introduction

General comments about Introduction: The introduction mentions the obesity epidemic, and parkrun’s role as a ‘positive upstream factor’ in this. Doing so might be reducing parkrun to a physical activity intervention only, when the research suggests it could be more than that (e.g., community initiative, social capital, wellbeing, volunteering). Is the obesity epidemic the only public health concern that parkrun could address?

Line 31-37: The first paragraph mentions physical activity and sport – with terms seemingly being used interchangeably. Is this intentional? It could be clear – perhaps with a definition of physical activity that encompasses sport and exercise.

Line 35: 1.4 billion – is that globally?

Line 45-46: could add that the 2,000 events are across 22 countries.

Line 49: “covid-19 pandemic” is later referred to as “SARS-cov2 pandemic” (line 94) – consistency needed.

Lines 45-55: Readers who are unfamiliar with parkrun will benefit from a much broader explanation of the “5km event”. For example, it’s a free event, hosted in public open spaces. It is important to explain that people can run, walk, jog or participate as volunteers. Given the focus on new participants, it might be good to explain how people register and what they do (e.g. with their personal barcode/ID number) to get a record of their completion time, and how this feeds into the parkrun dataset.

Lines 59-62: Where was this study based?

Lines 63-65: More detail needed here to help justify the focus on parkrun. What does the previous research into parkrun say? How does parkrun improve mental health and wellbeing? You might want to consider citing the scoping review by Grunseit et al. here (cited later on in the manuscript).

Line 71: mention of health practitioners prescribing parkrun could be expanded upon- perhaps helping to justify why this research is focussing on parkrun as a public health offer.

Line 67: a rationale is provided for why the analysis looks at parkrun venues with blue space, but there is no rationale for why the analysis segregates by freshwater and saltwater. Could this make a difference?

Methods

General comments about Methods: The methods section would benefit from more detail in places. It needs an explanation of how “remoteness” was calculated and also how travel time to the parkrun was determined. Why was travel time preferred over distance? (see point below).

Line 87: adults - is this 18 years and over – please specify.

Line 94-95: the additional characteristics of parkrun venues – where was this information collected from? By who?

Line 103: I admit to being no expert in this analysis method. Is generalised linear mixed modelling the same as generalised linear modelling? If so, consistency needed throughout.

Line 110: how was “remoteness” of the event determined? This detail is needed in the methods. You may want to refer to previous studies by Robert Smith and Paul Schneider that have looked specifically at parkrun locations in the England.

Smith, R. A., Schneider, P. P., Cosulich, R., Quirk, H., Bullas, A. M., Haake, S. J., &; Goyder, E. (2021). Socioeconomic inequalities in distance to and participation in a community-based running and walking activity: A longitudinal ecological study of parkrun 2010 to 2019. Health & place, 71, 102626-102626. doi:10.1016/j.healthplace.2021.102626

Schneider, P., Smith, R. A., Bullas, A. M., Quirk, H., Bayley, T., Haake, S. J., . . . Goyder, E. (2020). Multiple deprivation and geographic distance to community physical activity events — achieving equitable access to parkrun in England. Public health (London), 189, 48-53. doi:10.1016/j.puhe.2020.09.002

Results

Lines 129-130: “The mean travelling time to the next nearest event was 30 mins for those that returned and 33 for those that did not return.” How was travelling time calculated? This detail is needed in the methods.

Line 158: Is this study only looking at “runners” or might some completion times be from those who walked (e.g., over 50-55mins might be consider walkers)? Be careful with terminology.

Line 168: “reasonable comparable to” 1) do you mean reasonably 2) it seems a bit vague to say “reasonably comparable” – is it comparable or not? Is this a meaningful comparison to make?

Discussion

General comments about Discussion: In the introduction, parkrun is used here as an example of a ‘positive upstream’ initiative that can have an important role in the obesity epidemic. I would like to see the Discussion come back to this point – how do the findings support this claim and what are the wider implications?

Line 181-182: “The wider gap in Scotland might be indicative of a larger gender gap in activity in Scotland”. Can you support this proposition with evidence/a citation?

Line 196: “lower” (travelling time) – might ‘shorter’ be a more appropriate word? I also want to know if this travelling time is by car, foot, as the crow flies or taking roads etc. Much more detail needed in Methods.

Implications for parkrun

There is a focus on parkrun (understandably, given the data), but I wonder if the authors could demonstrate any wider implications of the findings for other community initiatives like parkrun? This is important for readers from countries that do not have parkrun events, and would increase the relevance/impact of the findings.

Line 227: the paper would benefit from introducing the parkrun practice in the Introduction – this could be part of the rationale for focussing on parkrun as a public health initiative.

Limitations of the study

Line 236: “It is known that the gender gap in participation has been narrowing” – please specify, is this in the parkrun population? If so, provide a citation/reference.

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Reviewer #1: Yes: Kate Black

Reviewer #2: No

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001786.r003

Decision Letter 1

Lucinda Shen

4 Jun 2023

PGPH-D-23-00368R1

Identification of novel characteristics that encourage first-time adult participants to return to parkrun in Scotland

PLOS Global Public Health

Dear Dr. Gilburn,

Thank you for submitting your manuscript to PLOS Global Public Health. After careful consideration, we feel that it has merit but does not fully meet PLOS Global Public Health’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The revised manuscript has undergone evaluation by the two previous reviewers, and their comments are provided below. The reviewers expressed satisfaction with the manuscript's revision, which incorporated their suggestions, and acknowledged that the study's implications are now communicated more clearly.

However, the reviewers still have a few remaining concerns that would benefit from further attention.

Please submit your revised manuscript by Jul 02 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at globalpubhealth@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pgph/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Lucinda Shen, MSc

Staff Editor

PLOS Global Public Health

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I don't know

Reviewer #2: I don't know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS Global Public Health does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you very much indeed for the opportunity to re-review your manuscript. It is evident that you have taken the majority of the reviewers’ comments on board in this revised manuscript. The methods that you have used to extract and analyse the data are now much clearer, as is the analysis itself (although I have only a relatively limited knowledge of quants analysis). Your findings are also much clearer as are the implications of your findings for parkrun’s future activity. Importantly, you have addressed one of my key concerns that was that in the initial manuscript you have seemingly identified only characteristics of parkruns that encourage return, from an unsubstantiated bounded set. That this is not the case is now far clearer. Thank you.

My main concerns remain as follows:

1. There is no overarching RQ but a series of RQs that while related necessitate the reader to make those connections. I would encourage you to consider identifying one over-arching RQ and then a series of sub-Qs (or perhaps even objectives?). I do wonder if a single focus upon geospatial features would make for a better paper?

2. You draw upon gender differences and barriers to exercise explicitly at the outset but then gender isn’t actually one of your questions / the focus of your paper (although it does then reappear so perhaps it does need to be included within the RQs?). I would encourage you to reconsider what you foreground in the introduction (see point 3)

3. I would encourage you to reconsider the structuring of the “Introduction” as at present there is no clear narrative through it that relates to and informs the overall purpose of your study. While I do recognise and appreciate that you have attempted to respond to the previous comments of the need to further recognise the extant literature, this has resulted in a somewhat amorphous section that is highly descriptive and needs greater synthesis. I do think all that you mention is relevant, it is just how it is structured and what is foregrounded / backgrounded that needs further reworking

4. Would not the pandemic have affected return rates by changing behaviours, and would this potentially not be more important than the variables observed? For example, new runners may have, in that intervening time period moved up from being a new/novice runner and have moved onto longer runs / additional activities?

5. Discussion: I would encourage you to stick to what you have found out and try to explain these findings rather than trying to make unsubstantiated ‘perhaps’ assertions. Ensure that you focus upon your RQs in this section

Minor points that you should also consider are:

1. Line 48 it is not clear why you are referring to “cycle routes” (as only an insider might recognise that parkruns are sometimes on cycle routes). Perhaps “traffic free routes” would be a better explanation at this point in the paper?

2. Line 64 “This is currently being promoted through the parkwalk” – what is? And walking what? – the route

3. Line 78 “In addition to the health benefits …” I think you mean physical health benefits as community, enhanced sense of self etc all relate to mental health – and therefore arguably are also ‘health benefits’ rather than ‘in addition to ..’

4. Line 319 you refer to “moving water” but surely coastal parkruns would have far more moving water than the other water-based locations? This (among some other assertion within) brings me to question your assertions re freshwater throughout the paper as the characteristics of it that you assert are very similar, if not more pertinent, for coastal locations as well. I think you need greater clarity here therefore in distinguishing these.

5. Lines 363-364, you suggest that more returners are female but I didn’t see this within the data that you presented

I look forward to reading your revised manuscript

Reviewer #2: All my comments have been addressed comprehensively. The revised manuscript is much improved. The description of parkrun provides much more detail for readers who are unfamiliar.

Given that much of the manuscript has been revised, I have some additional comments to make. These are just minor:

Line 75: should run be 'runs'

Line 98/99: 'performance of the parkrun population was falling' didn't quite sit right with me. Consider rephrasing. "the average finish time is getting longer" (again, I'm careful not to use the word slower, as I think that's a bit degrading!)

Line 105: is there scope to briefly add what some of the major barriers to participation were here?

Line 179: KML format- does this need writing in full?

Line 290-292: repetition of 'relatively slow' in this sentence. Is there any evidence/citation to support this claim of slower participants feeling like they're holding up the event? (I'm wondering if any of the barriers to parkrun research has this evidence?)

line 343: check consistency of using hyphen in 'first-time' throughout manuscript

I've enjoyed reading this paper and hope the readers do too.

Please note, the reason I have selected "I don't know" about the appropriateness and rigour of statistical analysis is because I have no experience with the analysis used in this paper.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Helen Quirk

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001786.r005

Decision Letter 2

Nnodimele Onuigbo Atulomah

10 Jul 2023

PGPH-D-23-00368R2

Identification of novel characteristics associated with first-time adult participants returning to parkrun in Scotland

PLOS Global Public Health

Dear Dr. Gilburn,

Thank you for submitting your manuscript to PLOS Global Public Health. After careful consideration, we feel that it has merit but does not fully meet PLOS Global Public Health’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

EDITOR'S COMMENT: 

  • An observation is made regarding the benefit of minor revision to the title of the manuscript is suggested.  Kindly consider this.

Please submit your revised manuscript by 14 July 2023. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at globalpubhealth@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pgph/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Nnodimele Onuigbo Atulomah, PhD

Academic Editor

PLOS Global Public Health

Journal Requirements:

1. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

Having reviewed the outcomes of the rounds of reviews submitted, it is believed that the manuscript would greatly benefit from a title modification from what it is currently to "Predictors of successful return to Parkrun among first-time adults in Scotland" considering that the short title is "Factors Associated With Return Rates to parkrun" and harmonizes appropriately with the suggested revised title and the data analysis in the manuscript and findings. With this revision the manuscript is well poised to communicate adequately with potential readers. If this suggestion is accepted, kindly replace "novel characteristics" and modify the statement of the aim to align appropriately with the revised title.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I don't know

Reviewer #2: I don't know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS Global Public Health does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you very much indeed for the opportunity to further re-review your manuscript. I appreciate you responding to many of the comments in this revised manuscript. In particular, thank you for ensuring that the study aim, and associated questions, are now clearly stated and that the narrative through the paper is much more apparent. Thank you.

My suggestions are as follows:

1. Your work would have greater initial impact, and understanding, if you direct the reader towards parkrun earlier in your initial statements around exercise, by drawing upon parkrun-relevant examples – for example that exercising with others can be really important … rather than e.g. provision of off road routeways!

2. That many other quants studies have taken place isn’t in itself a reason to undertake the work! Are you better able to justify the study?

3. Some of the variables that you state within the RQs aren’t entirely evident in your preceding literature review

4. As previously, research has shown that the pandemic has significantly changed individuals’ behaviours, and especially towards exercise. Therefore, I would encourage you to consider would not the pandemic have affected return rates by changing behaviours, and would this potentially not be more important than the variables observed? For example, new runners may have, in that intervening time period moved up from being a new/novice runner and have moved onto longer runs / additional activities? You acknowledge this in your comments but I would have expect to see some recognition of this in the “limitations”

Reviewer #2: All comments have been addressed.

I have no further comments.

Please note, the reason I have selected "I don't know" about the appropriateness and rigour of statistical analysis is because I have no experience with the analysis used in this paper.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001786.r007

Decision Letter 3

Nnodimele Onuigbo Atulomah

21 Jul 2023

Predictors of successful return to parkrun for first-time adult participants in Scotland

PGPH-D-23-00368R3

Dear Mr. Gilburn,

We are pleased to inform you that your manuscript 'Predictors of successful return to parkrun for first-time adult participants in Scotland' has been provisionally accepted for publication in PLOS Global Public Health.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they'll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact globalpubhealth@plos.org.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Global Public Health.

Best regards,

Nnodimele Onuigbo Atulomah, PhD

Academic Editor

PLOS Global Public Health

Congratulations for having completed the rounds of reviews and revisions successfully.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Response to Reviewers.docx

    Attachment

    Submitted filename: Response to reviewers 2.docx

    Attachment

    Submitted filename: Third response to reviewers.docx

    Data Availability Statement

    The full dataset is available in the University of Stirling datastorre http://hdl.handle.net/11667/210.


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