What Encourages Physically Inactive People to Start Running? An Analysis of Motivations to Participate in Parkrun and City Trail in Poland

Personality of marathon runners: a narrative review of recent findings

Participation in marathons has dramatically increased over the last few years. Marathon running has many proven beneficial effects, especially on cardiovascular health and fitness. Most research has focused on physiologic and pathophysiologic adaptations in connection with endurance exercise. Nevertheless, marathon running also has a major impact on psychological aspects and positively influences mental health, which has only recently attracted research interest. The present narrative review aimed to review the personality traits of marathon runners with an emphasis on recent literature. Marathon runners show a distinct personality and highly characteristic personality traits needed to successfully finish such a demanding race, i.e., a strong sense of vigor, self-sufficiency, and intelligence as well as low scores in anger, fatigue, tension, and depression. Furthermore, personality differences are detectable between runners of different sexes, ages, and performance level groups. This has significant clinical implications for athletes, coaches and competition organizers, as these groups show different patterns of personality traits. Future studies should focus on changes in cognition and mood states pre-, during, and post-endurance events, as well as during training periods. Large-scale studies comparing personality differences by sex, age, and performance are also important for better clinical guidance. See also the graphical abstract(Fig. 1).

Differences in training characteristics of recreational endurance runners by race distance - results from the NURMI Study (Step 2)

Background

Although runner's profiles were previously investigated, information on the training frequency and training distance for short (5 km, 10 km) and long-distance (>21 km) running is absent. The present study aimed to investigate the associations between training routines and exercise habits of recreational endurance runners considering self-reported preferred race distance [10 km, half-marathon (HM), and marathon/ultra-marathon (M/UM)] subgroups.

Methods

This is a cross-sectional study, sampling 154 recreational runners of both sexes. A web survey was used for data collection regarding age, sex, preferred distance (10-km, HM, M/UM), training routines, exercise habits, and periodized training routines. The Chi-square test (Cramer's V) and Kruskal-Wallis test (Eta-Squared η2) with effect sizes were used for comparisons between race distances.

Results

Significant differences were shown for anthropometric, training, and periodization characteristics. Highly significant differences were found between subgroups for the number of sessions, running kilometers, and training hours at all periods and within all four preparation conditions. M/UM runners were training more frequently, for longer durations, and ran greater distances each week.

Conclusion

This finding supports the notion that training habits and periodization characteristics are different for different race distances (10-km, half marathon, marathon, and ultramarathon).

Differences in race history by distance of recreational endurance runners from The NURMI Study (Step 2)

Few studies were developed to understand the relationship between running characteristics and motivation. The purpose of this study was to assess the relationship between running event history, running experience, and best race performances in recreational distance runners. We used a web survey to obtain information regarding running experience, racing history, and periodization training routines/exercise habits, including weekly volumes and daily mileage and duration across periods and conditions. Associations between variables were conducted with the Chi-square test (χ2; nominal scale) and Wilcoxon test. Multiple linear regression analysis and multivariate linear regression were performed. Concerning the participants' motive for exercising, a significant difference was identified between the race distance subgroups (p < 0.001), where 58% of M/UM runners exercised for performance (n = 38) and 64% of HM runners (n = 57) and 57% of 10 km runners (n = 52) exercised for recreational purposes. A significant difference was found in the number of years of running completed without taking a break (p = 0.004), with marathoners/ultramarathoners reporting the most years. Runners competing in different race distances such as 10 km, half-marathon, marathon, and ultra-marathon presented differences in training background and habits according to the distance of preference.

The Relative Importance of Training and Social Support for Runners' Performance: A Cross-Sectional Study

BACKGROUND

Running participation/performance is a complex system. Understanding the variables associated with these behaviors may help to increase population physical activity and improve performance. This study aimed to investigate social and training variables important for running performance using a network approach.

METHODS

This cross-sectional study sampled 1151 non-professional Brazilian runners of both sexes (women, 38.2%; men, 61.7%). A questionnaire was available for eligible participants using an online platform, and information regarding training (volume and running pace) and social variables (participation in a running event, participation in a running group, influence on running, runners in the family, and childhood sport) related to runners' performance was obtained. The Chi-square test and network model were estimated by sex.

RESULTS

Training characteristics tend to be clustered. For both sexes, the training volume node presented the highest expected influence in the network (1.69 for women and 2.16 for men). Centrality indicators of social variables show that sports childhood participation and the presence of runners in the family were the most important nodes of network connection for women and men, respectively.

CONCLUSION

Based on these findings, it was concluded that sports participation during childhood and the practice of running by other family members were important factors to connect variables in the network. These findings have practical applications for health policymakers, highlighting the need to develop educational programs to increase sports participation during childhood and within families.

Motivation and Eco-Attitudes among Night Runners during the COVID-19 Pandemic

Running surrounded by nature at night, often with limited contact with other people, is one of the safest physical activities during the COVID-19 pandemic. The aim of this article is to determine what motivates night recreational runners and to analyse the differences between men and women according to age, and also to see whether the fact of having had COVID-19 or not matters when it comes to athletes’ motivation behind participating in runs. Runners were also asked about participating in cities or out-of-town events in terms of verifying the cleanliness of the air before running, using masks or running in green areas. 233 individuals in total participated in this descriptive, quantitative, cross-sectional study. The questionnaire uses the division of motives used in the Marathon Motivation Scale (MOMS) and a number of additional questions on environmental factors. Overall, the main motivation that drives night-time runners is health orientation, weight concern, personal goal achievement, psychological coping, life meaning and self-esteem. The research also showed higher scores for health orientation, recognition, psychological coping, life meaning and self-esteem among runners who had had COVID-19 than runners who had not had the virus. In addition, respondents clearly indicated that night running makes it easier to fall asleep and improves the quality of sleep. Most runners rated their mental health as being good, did not run in the morning despite better air levels, did not choose running events outside the urban area and did not check the air quality index before running. Therefore, it will be important for coaches, event organisers and other professionals to consider athletes’ age, gender, whether they have had COVID-19 and runners’ approaches to eco-attitudes when trying to understand their reasons for participating in different sports or leisure events, especially those that focus on a priority in shaping environmental attitudes.

Motivation behind running among older adult runners

Background

Recreational running has greatly increased over the last decade, and different research has tried to understand the motivation that leads these amateur athletes to run. However, most research has focused on adult athletes, while the motivation behind older adult athletes has been overlooked.

Methods

The aim of this research was to analyse the motivational aspects of amateur runners aged over 50 years, and to consider the influence that years of practice, type of participation and some socio-demographical variables have on these older adults’ motivation behind running. 244 older adult amateur athletes in total completed an online survey with the 56 items contained in the motivation of marathoners scales (MOMS), 108 of whom were female (44%), and 136 were male runners (56%). Athletes were asked about their years’ running experience (< 1 year, 1–5 years, 6–10 years, > 10 years), their participation in running events (recreationally, half marathon, marathon, ultramarathon) and age (ranges 50–60, more than 60 years), gender (male, female), family life (whether in a relationship or not), and whether they had children (yes, no).

Results

The results showed statistical differences in the nine MOMS dimensions in terms of years’ running experience and participation in different running events. Moreover, older adult runners’ gender and age subsequently showed statistical differences with five and six motivational factors respectively, while athletes that did not have children were more likely to run regarding competition and showing recognition. Family life did not show any statistical association with any of the dimensions on the scale in this population, while regression analyses showed that, mainly, years’ running experience and participation were positively predicted, together with most motivational dimensions, while having children was negatively predicted in some of them.

Conclusions

This study showed that older adult runners’ reasons for participating differ from those obtained in previous studies, especially regarding training experience and participation in events. Therefore, the older adult population should be specifically addressed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-021-00366-1.

Use of monitoring technology and injury incidence among recreational runners: a cross-sectional study

Background

Monitoring technology is increasingly accessible to recreational runners. Our aim was to examine patterns of technology use in recreational runners, and its potential association with injury.

Methods

We conducted a cross-sectional questionnaire study in a sample of adult runners. Recruitment took place at three different 5 km parkrun event across Northern Ireland. Demographics, technology use, running behaviour and running-related injury (RRI) history were examined. Regression analyses were performed to determine relationships between variables.

Results

Responses were obtained from 192 of 483 eligible finishers (39.8% response rate). Average age was 45.9 years (SD 10.3), with males (47.1 years SD 9.7) slightly older than females (44.8 years SD 10.8). On average, participants ran 3.0 days per week (SD 1.3), with an average weekly distance of 22.6 km (SD 19.7). Males typically ran further (MD 6.2 km/week; 95% CI 0.4 to 12.0) than females. Monitoring technology was used by 87.4% (153/175); with GPS watches the most common device (87.6% (134/153)). Runners using monitoring technology ran further (MD 14.4 km/week; 95% CI 10.3 to 18.5) and more frequently (MD 1.3 days/week; 95% CI 0.7 to 1.9) than those who did not use monitoring technology. There was no significant difference in average age between runners who used monitoring technology and those who did not (MD 4.0 years; 95% CI −0.7 to 8.7). RRI was reported by 40.6% (71/175) of participants in the previous 12 months. In a univariate analysis, none of the selected predictors (age, number of days run per week, distance run per week, or usage of technology to modify training pattern) (p > 0.1) were associated with RRI.

Conclusions

This study found a high prevalence of monitoring technology usage among recreational runners. While the incidence of RRI remains high, it is not associated with the usage of monitoring technology. Further prospective research should examine if monitoring technology can reduce RRI incidence among recreational runners in future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-021-00347-4.

Individual and Economic Characteristics as Determinants of Brazilian Runners’ Motivation

Due to differences in runners’ profiles, which can be related to sociodemographic characteristics, motivations for running can vary. This study aimed to identify Brazilian runners’ motivations for their practice, and the factors associated among runners who point to look for performance improvement as their main motivation. The sample comprised 1097 non-professional road runners. The questionnaire “Profile characterization and associated factors for runner’s performance” was used. The results showed that the oldest athletes and those with the highest income levels presented lower likelihood of reporting performance improvement as their main motivation for taking part in running. In terms of income level, results showed that as this increased, there was a lower chance of getting involved in practice with a focus on incremental improvements in performance. Differences between sexes were also observed, with men more likely to indicate performance improvement as their motivation for running. In Brazil, most runners reported “health” as their main motivation for running. Women, older runners, and those with higher income levels were less likely to point to performance improvements as their main motivation for taking up running.

Development and Validation of Prediction Equation of "Athens Authentic Marathon" Men's Race Speed

Aim

Despite the increasing popularity of outdoor endurance running races of different distances, little information exists about the role of training and physiological characteristics of recreational runners. The aim of the present study was (a) to examine the role of training and physiological characteristics on the performance of recreational marathon runners and (b) to develop a prediction equation of men’s race time in the “Athens Authentic Marathon.”

Methods

Recreational male marathon runners (n = 130, age 44.1 ± 8.6 years)—who finished the “Athens Authentic Marathon” 2017—performed a series of anthropometry and physical fitness tests including body mass index (BMI), body fat percentage (BF), maximal oxygen uptake (VO₂max), anaerobic power, squat, and countermovement jump. The variation of these characteristics was examined by quintiles (i.e., five groups consisting of 26 participants in each) of the race speed. An experimental group (EXP, n = 65) was used to develop a prediction equation of the race time, which was verified in a control group (CON, n = 65).

Results

In the overall sample, a one-way ANOVA showed a main effect of quintiles on race speed on weekly training days and distance, age, body weight, BMI, BF, and VO₂max (p ≤ 0.003, η² ≥ 0.121), where the faster groups outscored the slower groups. Running speed during the race correlated moderately with age (r = −0.36, p < 0.001) and largely with the number of weekly training days (r = 0.52, p < 0.001) and weekly running distance (r = 0.58, p < 0.001), but not with the number of previously finished marathons (r = 0.08, p = 0.369). With regard to physiological characteristics, running speed correlated largely with body mass (r = −0.52, p < 0.001), BMI (r = −0.60, p < 0.001), BF (r = −0.65, p < 0.001), VO₂max (r = 0.67, p < 0.001), moderately with isometric muscle strength (r = 0.42, p < 0.001), and small with anaerobic muscle power (r = 0.20, p = 0.021). In EXP, race speed could be predicted (R² = 0.61, standard error of the estimate = 1.19) using the formula “8.804 + 0.111 × VO₂max + 0.029 × weekly training distance in km −0.218 × BMI.” Applying this equation in CON, no bias was observed (difference between observed and predicted value 0.12 ± 1.09 km/h, 95% confidence intervals −0.15, 0.40, p = 0.122).

Conclusion

These findings highlighted the role of aerobic capacity, training, and body mass status for the performance of recreational male runners in a marathon race. The findings would be of great practical importance for coaches and trainers to predict the average marathon race time in a specific group of runners.

Motivational Differences between 5K Runners, Marathoners and Ultramarathoners in Poland

The aim of the study was to determine the reasons for practicing different running distances (5K run, marathon, and ultramarathon), and to analyze the differences in each type according to gender, age, and marital status. An empirical study was conducted during the 2020 Karkonosze Winter Ultramarathon, 20th PKO Poznan Marathon, and 5K run—Parkrun Poznan and City Trail, over the course of which we interviewed 925 runners. A total of 267 ultramarathoners, 493 marathon runners, and 165 Parkrun and City Trail participants took part in the cross-sectional study, which used the diagnostic survey method. The questionnaire employed the division of motives used by the Motivation of Marathoners Scale (MOMS) by Masters et al., adapted to the Polish language by Dybała. No significant differences were found in any of the disciplines based on gender or marital status, although the results showed that weight concern increased with increasing age range in all the running distances analyzed. In addition, in 5K run and marathon runners, weight concern decreased in the 36 to 50 age range, but subsequently increased in those over 51 years of age. Therefore, it will be important for coaches and other professionals to consider athletes’ age when trying to understand their motives to participate in different disciplines.

The Impact of Water Sporting Events on Attitudes Toward Physical Activity: Motivational Profiles of Participants in Modern and Traditional Water Events

The aim of this paper was to analyze the relationship between attitudes toward physical activity and participation in water sports events and to recognize the main motives for involvement in these kinds of events. A written paper-pencil diagnostic survey was conducted among 394 participants in two traditional and two modern sports events on water held in Poland to ascertain whether innovative (modern) events are needed in society, and whether they cause an increase in interest in physical activity (more than traditional events). The research results showed that modern sports events on water did not have any more power to attract physically inactive people than traditional water events, did not produce a greater desire to lead an active lifestyle, and did not encourage people to more regularly practice water sports. Moreover, modern events, compared to traditional events, were only a one-time experience and the people who completed survey often wanted to return to traditional sports events which provided participants with greater positive emotions than a modern event. In the case of socio-demographical variables, there was no statistically significant relationship between gender and choice of modern or traditional event, but older people were more likely to choose a traditional event than younger people; modern water events were an attractive option primarily for young people under 30 years of age, furthermore, modern events more often attracted people who had completed higher education. However, it turned out that a modern event on water often attracted more people who had had no experience in this sport discipline rather than people who chose traditional water events. In a sense, modern events are therefore effective in promoting water sports in Polish society. We also distinguished five main groups of participants: healthy lifestyle managers, lovers of sports emotions, water sports malcontents, water sports enthusiasts, and neutrals to water sports. Additionally, we looked into gender-related motives for participation in modern and traditional water events: social and health-related motives proved to be more important for women and men who participated in modern water events. The research results presented in the article expand on the current state of knowledge about mass participation in sport, the impact of sporting events on the promotion of physical activity, and show the motivation behind participation in modern and traditional water sporting events.