Evidence map›Paper›PMID 37585404›Full record

ArticlePLOS global public health2023

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

Andre S Gilburn

Abstract read
In one paragraph

Article in PLOS global public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Andre S GilburnHealthy Environments: Sustainable Societies Research Group, Biological and Environmental Sciences, University of Stirling, Stirling, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID37585404
PMCPMC10431652

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.