Study of the Motivation of Spanish Amateur Runners Based on Training Patterns and Gender

objectives of the present study are to analyze the di erent training patterns of the amateur runners, according to their gender, and to nd out a correlation between the training pattern and the motivation. The sample was composed of 457 amateur runners. For the collection of data, a two-part questionnaire was used. The rst part consisted of questions about sporting and healthy patterns and the second part consisted of the Perception of Success Questionnaire (POSQ), adapted to Spanish. The obtained results indicated that their motives for starting to practice running and to continue their involvement are health and fun. The training pattern is as follows: they practise one to three days per week, running from three to ve hours overall plus additional stretching and high intensity training. They participated in less than one running event per month. Most of them did not belong to an athletic club, did not have a coach, were not federated and have more than four years' experience of running. What concerns the gender di erences, the men trained more than the women, and they did it with relatives and friends; women preferred to do it with friends or by themselves with the assistance of a coach. Age and running hours per week were the best variables to predict the task goal orientation, especially for men. For women, training hours per week predicted the goal orientation but to the ego. This nding could be especially helpful for coaches. A high number of training hours for men was linked with a

themselves with the assistance of a coach. Age and running hours per week were the best variables to predict the task goal orientation, especially for men. For women, training hours per week predicted the goal orientation but to the ego. This nding could be especially helpful for coaches. A high number of training hours for men was linked with a task goal orientation, and on the other hand, for women it meant an ego goal orientation. The consequences of their behaviours were likely to be markedly di erent. Keywords:athletics; perception of success; sport events; motives; achievement goals 1. Introduction Over the last decades there has been a “boom” in athletic events at the international level, and it is increasingly common for the adult population to participate in amateur races [1]. This phenomenon can be seen in Spain [2]. It emerged in the 1990s and was in uenced by postmodernism and the celebration of the Barcelona 1992 Olympic Games [3]. The number of studies that have discussed the characteristics of amateur runners who participate at a local, national, or even international level has increased over the past few years. Some of the main themes have been related to physical health bene ts [4,5], psychological bene ts [6], tourism and leisure [7,8], and the motivational characteristics of amateur runners [9,10]. Int. J. Environ. Res. Public Health2020,17, 8185; doi:10.3390 /ijerph17218185 /journal/ijerph

Int. J. Environ. Res. Public Health2020,17, 8185 2 of 12 Psychological studies have focused on why people begin and continuing to practise athletics [11–13], and also why some take part in amateur races [14,15]. One of the most recent studies [16] identi ed health as the main reason for participation in long-distance races, followed by personal growth and greater self-esteem. Such factors accord with previous research, but not necessarily in that order of importance [14,15]. In another study [17], long-distance runners stated that they were driven by the desire to experience strong emotions, have fun, and to enjoy the atmosphere of the sporting event. The goal orientation of athletes helps towards an understanding of the reasons why amateur runners participate in races [18], and why it is so important for them to be involved [19]. Many of these can be explained using the achievement goal theory [20]. This states that ego goal orientation is related to the belief that success in sport is achieved by being more skilled than the opponent, even if this means using techniques of deception. In contrast, task orientation is related to the most adaptive motivational patterns, which consist in believing that success in sport is achieved through personal e ort. In this case, sport is about training and individual development. In this sense, the task-oriented athlete allows to feel satisfaction with the sport practise in both genders [21]. Previous studies have related goal orientation to sociodemographic variables, especially gender and age. They have indicated that the older the participant, the greater his or her task goal orientation, and conversely, the younger the participant, the greater his or her ego orientation [22–24]. On the other hand, for the gender variable, the results are somewhat contradictory, since despite the fact that there are studies showing that motives are more linked to a pro le focused on performance and competition for men tan for women [23,25,26], the studies that have analysed goal orientation have not found signi cant di erences between the genders [27–29]. Another important aspect to consider when studying the goal orientations of amateur athletes is

despite the fact that there are studies showing that motives are more linked to a pro le focused on performance and competition for men tan for women [23,25,26], the studies that have analysed goal orientation have not found signi cant di erences between the genders [27–29]. Another important aspect to consider when studying the goal orientations of amateur athletes is their training experience and patterns, advice from a coach, partners with whom they train, training time and days per week, and other variables [30]. Other aspects include variables age, level of studies, sports habits, and running addiction contributed to di erentiating the motives to practise running [31]. These di erences between genders justify the importance to create a pro le of the amateur runner [32]. Using the data provided, the aim of the present study is to discover the training patterns of long-distance runners in the Murcia region of Spain (races from 5 to 14 kilometres), to analyse the reasons why they begin and continue to participate in the sport, and to examine the relationship between their training patterns and goal orientation, based on gender di erence. 2. Materials and Methods 2.1. Design and Participants This is a descriptive, quantitative, cross-sectional study. The sample was chosen randomly from amongst participants in two amateur races in Murcia, both of which are part of the provincial road racing circuit of the region. Both races had two distances, 5 k and 10 k and 7 k and 14 k, respectively. In the rst race there were almost 200 runners in total and in the second almost 3000. Participants lled out the questionnaire before the race, speci cally when they picked up their numbers. All of them provided written informed consent to participation in the survey. After reviewing and entering the questionnaires into a database, 14 were eliminated because the respondents had lled them out incorrectly, had omitted essential data (such as age or gender), or both. Once these had been eliminated, 486 participants remained. However, 29 additional participants also had to be excluded after abnormal values were obtained in the data cleaning. This

the survey. After reviewing and entering the questionnaires into a database, 14 were eliminated because the respondents had lled them out incorrectly, had omitted essential data (such as age or gender), or both. Once these had been eliminated, 486 participants remained. However, 29 additional participants also had to be excluded after abnormal values were obtained in the data cleaning. This left 457 subjects. Then, the data exclusion criteria were applied. First, debugging was performed to detect atypical cases. This was followed by a reliability analysis using Cronbach's alpha. Finally, normality was calculated using the Kolmogorov Smirnov test. Of the participants, 350 were men and 107 were women. The age range was 18 to 63 years and the mean age was 37.84 9.139 years. The mean age for the men was 38.23 9.346 years and 36.56 8.34 years for the women.

Int. J. Environ. Res. Public Health2020,17, 8185 3 of 12 2.2. Measurement Instruments The questionnaire consisted of 34 items divided into two sections. The rst comprised a form designed to collect demographic and training information. Participants answered questions on the following variables: age, gender, athletic club, federation, sporting experience, reasons for starting and maintaining participation in amateur races, planning of training sessions, number of hours and days of training per week, days of high intensity training per week, the number of runners the participant typically associated with during a week, days of strength training per week, and best nish time in 5 k, 10 k, or half marathon races. Most of the questions were extracted from Ogles and Masters [20]. The second section comprised questions from the Spanish version of the Escart½, Cervellâand Guzm¡n Perception of Success Questionnaire [33]. These were extracted from the Perception of Success Questionnaire (POSQ) by Roberts and Balagu²[34]. This questionnaire is based on the achievement goals theory and consists of twelve items, six of which measure ego or performance orientation and the other six task or mastery orientation. The answers in this questionnaire are Likert-type, ranging from (1) totally disagree to (4) totally agree. The reliability of the instrument was veri ed through internal consistency analysis. Applying Cronbach's alpha, values of 0.770 were obtained on the ego orientation scale and 0.737 on the task orientation scale. Approval for the study was obtained from the Ethics Committee of Murcia University, Spain. The le number was 2266/2019. The study was consistent with the Helsinki declaration of 1975. The goodness of the t indices (RMSEA=0.023; CFI=0.997; TLI=0.995) of the scale in the study sample was checked by the con rmatory factor analysis (CFA) denoting a good t to the data. Two additional measurements were taken into account to evaluate the reliability of the scale: the composite reliability (CR) with a value of 0.783 and 0.743 for ego and task factor respectively, higher than the 0.70 value recommended by the literature [35], and the average variance extracted (AVE) with a value of 0.553 for ego and 0.496 for task,

the data. Two additional measurements were taken into account to evaluate the reliability of the scale: the composite reliability (CR) with a value of 0.783 and 0.743 for ego and task factor respectively, higher than the 0.70 value recommended by the literature [35], and the average variance extracted (AVE) with a value of 0.553 for ego and 0.496 for task, this second one very close to 0.50, value recommended [36]. Additionally, the convergent validity was veri ed through the values of the t test associated with the factorial loads of the items, which were higher than 1.96 (p<0.05). Furthermore, the discriminant validity, which has to do with seeing the clear distinction between any pair of constructs, was evaluated using the method suggested by Fornell and Larcker [37]. This method demonstrates discriminant validity if the square root of AVE value of a determined factor, in this case 0.305 for ego and 0.246 for task were greater than the correlation coe cients between the determined factor and any other factor in the proposed scale (0.208). 2.3. Procedure Before completing the questionnaire, the participants were given an information sheet and were asked to sign an informed consent form. Before the “Save the Children” race took place, the organisers were contacted to explain the objectives of the study, and a model of the questionnaire was delivered to them. For the race at the Air Base in Alcantarilla, we contacted the Murcian Athletics Federation, who then contacted the Military Academy (the organisers). After a short period of time, a favourable response was received. Data collection was carried out before the contest, the day before the races, and when the runners picked up their numbers. Participants were informed of the purpose of the research, and were told that it was voluntary and con dential. All subjects had to be of legal age. They were given the opportunity to raise any doubts they may have had with regard to the study. 2.4. Data Analysis Data analysis was carried out using the software package SPSS version 22.0 (SPSS Inc. Chicago, IL, USA) and Mplus version 8.4. First, the

told that it was voluntary and con dential. All subjects had to be of legal age. They were given the opportunity to raise any doubts they may have had with regard to the study. 2.4. Data Analysis Data analysis was carried out using the software package SPSS version 22.0 (SPSS Inc. Chicago, IL, USA) and Mplus version 8.4. First, the chi-square test for normality was performed for the categorical variables; a non-normal distribution (p<0.05) was obtained. Then, normality was performed for the continuous variables through the Kolmogorov-Smirnov test; a non-normal distribution (p<0.05) was obtained. For the analysis of the categorical variables, the chi-square statistic was used for contingency tables (analysing the di erences according to gender), and the contingency coe cient was performed

Int. J. Environ. Res. Public Health2020,17, 8185 4 of 12 to show the correlation between the variables. An analysis of continuous variables was carried out using the Mann Whitney U test to contrast them with gender, and a correlation analysis was carried out using Kendal's Tau b test to verify the relationship between variables related to training patterns with the age and motivational orientation within the 95% con dence interval was also carried out. Finally, three multivariate linear regression models were used to verify the prediction of the variables of training patterns on motivational orientation to ego and task, on the global sample, and as a function of gender. 3. Results 3.1. Descriptive Analysis of Reasons for Starting and Continuing Sports Practice The main reason for participating in the races selected for the study was to have fun (30.9%), followed by health and to have fun (17.7%). The main reason for continuing to participate in amateur races was to have fun (26.5%), followed by health and to have fun (19.3%), then health, relationships, and to have fun (12.3%). With regard to gender (Figures), we observed the same trend; men gave a greater number of reasons for why they started and continued to compete than women, who gave more combined reasons (health and to have fun or health, relationships, and to have fun). In both cases, the predominant motive was to have fun (31.1% and 29.9% initially and 26% and 28% thereafter).Int. J. Environ. Res. Public Health 2020, 17, x 4 of 12 used to verify the prediction of the variables of training patterns on motivational orientation to ego and task, on the global sample, and as a function of gender. 3. Results 3.1. Descriptive Analysis of Reasons for Starting and Continuing Sports Practice The main reason for participating in the races selected for the study was to have fun (30.9%), followed by health and to have fun (17.7%). The main reason for continuing to participate in amateur races was to have fun (26.5%), followed by health and to have fun (19.3%), then health, relationships, and to have fun (12.3%). With

Continuing Sports Practice The main reason for participating in the races selected for the study was to have fun (30.9%), followed by health and to have fun (17.7%). The main reason for continuing to participate in amateur races was to have fun (26.5%), followed by health and to have fun (19.3%), then health, relationships, and to have fun (12.3%). With regard to gender (Figures 1 and 2), we observed the same trend; men gave a greater number of reasons for why they started and continued to compete than women, who gave more combined reasons (health and to have fun or health, relationships, and to have fun). In both cases, the predominant motive was to have fun (31.1% and 29.9% initially and 26% and 28% thereafter). Figure 1. Reasons for starting sports according to the gender of the participants. 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00% Men Women Figure 1.Reasons for starting sports according to the gender of the participants. 3.2. Di erences in Training Patterns in the Total Sample and Their Relationship with the Gender of the Participants An analysis was carried out, taking into account the training patterns of the athletes and distinguishing them according to the gender of the participants (Table).

Int. J. Environ. Res. Public Health2020,17, 8185 5 of 12Int. J. Environ. Res. Public Health 2020, 17, x 5 of 12 Figure 2. Reasons for continuing sports according to the gender of the participants. 3.2. Differences in Training Patterns in the Total Sample and their Relationship with the Gender of the Participants An analysis was carried out, taking into account the training patterns of the athletes and distinguishing them according to the gender of the participants (Table 1). Table 1. Data analysis related to the variables of training patterns. Variable Men Women Total M % M % p/C M % p Federated Yes 98 28.0% 22 20.6% 0.134 120 26.3% No 252 72.0% 85 79.4% 0.071 337 73.7% <0.001 *** Belong to a club Yes 162 46.3% 38 35.5% 0.058 200 43.8% No 188 53.7% 69 64.5% 0.092 257 56.2% 0.008 ** Experience Less than 1 year 54 15.4% 28 26.2% 82 17.9% Between 1 and 2 years 39 11.1% 21 19.6% 60 13.1% Between 3 and 4 years 65 18.6% 18 16.8% 83 18.2% More than 4 years 192 54.9% 40 37.4% 0.002 ** 232 50.8% <0.001 *** 0.071 Training planning By myself 250 71.4% 66 61.7% 316 69.1% A coach 70 20.0% 29 27.1% 99 21.7% A friend 14 4.0% 8 7.5% 22 4.8% Other 1 0.3% 1 0.9% 2 0.4% By myself and with friends 15 4.3% 3 2.8% 0.175 18 3.9% <0.001 *** 0.117 Training days per week 1–3 days 164 46.9% 60 56.1% 224 49.0% 4–5 days 140 40.0% 35 32.7% 175 38.3% More than 5 days 46 13.1% 12 11.2% 0.247 58 12.7% <0.001 *** 0.078 High intensity training days per week 0 days 49 14.0% 20 18.7% 69 15.1% 1 days 117 33.4% 31 29.0% 148 32.4% 2 days 130 37.1% 41 38.3% 171 37.4% More than 2 days 54 15.4% 15 14.0% 0.617 69 15.1% <0.001 *** 0.063 Training partner Family and friends 138 39.4% 24 22.4% 162 35.4% With friends 79 22.6% 29 27.1% 108 23.6% 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% Men Women Figure 2.Reasons for continuing sports according

31 29.0% 148 32.4% 2 days 130 37.1% 41 38.3% 171 37.4% More than 2 days 54 15.4% 15 14.0% 0.617 69 15.1% <0.001 *** 0.063 Training partner Family and friends 138 39.4% 24 22.4% 162 35.4% With friends 79 22.6% 29 27.1% 108 23.6% 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% Men Women Figure 2.Reasons for continuing sports according to the gender of the participants. Table 1.Data analysis related to the variables of training patterns. Variable Men Women Total M % M % p/C M % p Federated Yes 98 28.0% 22 20.6% 0.134 120 26.3% No 252 72.0% 85 79.4% 0.071 337 73.7% <0.001 *** Belong to a club Yes 162 46.3% 38 35.5% 0.058 200 43.8% No 188 53.7% 69 64.5% 0.092 257 56.2% 0.008 ** Experience Less than 1 year 54 15.4% 28 26.2% 82 17.9% Between 1 and 2 years 39 11.1% 21 19.6% 60 13.1% Between 3 and 4 years 65 18.6% 18 16.8% 83 18.2% More than 4 years 192 54.9% 40 37.4% 0.002 ** 232 50.8% <0.001 *** 0.071 Training planning By myself 250 71.4% 66 61.7% 316 69.1% A coach 70 20.0% 29 27.1% 99 21.7% A friend 14 4.0% 8 7.5% 22 4.8% Other 1 0.3% 1 0.9% 2 0.4% By myself andwith friends 15 4.3% 3 2.8% 0.175 18 3.9% <0.001 *** 0.117 Training days per week 1–3 days 164 46.9% 60 56.1% 224 49.0% 4–5 days 140 40.0% 35 32.7% 175 38.3% More than 5 days 46 13.1% 12 11.2% 0.247 58 12.7% <0.001 *** 0.078 High intensity training days per week 0 days 49 14.0% 20 18.7% 69 15.1% 1 days 117 33.4% 31 29.0% 148 32.4% 2 days 130 37.1% 41 38.3% 171 37.4% More than 2 days 54 15.4% 15 14.0% 0.617 69 15.1% <0.001 *** 0.063 Training partner Family and friends 138 39.4% 24 22.4% 162 35.4% With friends 79 22.6% 29 27.1% 108 23.6% Clubmates 35 10.0% 10 9.3% 45 9.8% With family 15 4.3% 6 5.6% 21 4.6% Alone and with friends 48 13.7% 25 23.4% 73 16.0% Alone, with friends and

Analyzes training patterns and motivation of Spanish amateur runners based on gender.