The aim of this study was to analyse the influence of the pacing strategy adopted by elite marathon runners when setting every marathon world record in the last 50 years. We divided former marathon record holders into two groups:classic athletes(record holders between 1967 and 1988) andcontemporaneous athletes(record holders between 1988 and 2018). The total distance of the marathon was divided into 8 sections of 5 km and 1 last section of 2.195 km, and the relative average speed of each section was calculated individually. On average athletes were slightly faster in the first half‐marathon than in the second one, where they slowed down progressively (ES = 0.28, small effect). However, when comparing classic vs. contemporaneous athletes, we observed that classic athletes started significantly faster (p< .05, ES = 1.16, moderate effect), although after 25 km, their speed dropped dramatically and was significantly slower than in their contemporaneous counterparts (ES = 2.41, very large effect). This study shows that the pacing strategies of the best marathon runners in the world have changed over the last 50 years. Although a negative pace distribution has been proposed as the most efficient option, a pacing strategy characterised by very little speed changes across the whole race may be the way to go in the future.

Sleep problems in university students are important and have implications for health, quality of life, and academic performance. Using an ex post facto design, a total sample of 855 students (55.7% women) participated in the study. Sleep assessment was conducted using the Pittsburgh Sleep Quality Index, the Nightmare Frequency Scale, the Nightmare Proneness Scale, and the Composite Morningness Scale. Women show a higher risk [OR = 2.61] of presenting poor sleep quality (> 5 points on the PSQI) compared with men (p < 0.001). Similarly, women reported a greater frequency of nightmares (p < 0.001, d = 0.60), greater propensity for nightmares (p < 0.001, d = 0.70) and a higher score on Item-5h of the PSQI regarding nightmares (p < 0.001, d = 0.59). Women, compared with men, show higher risk [OR = 2.84] for a sleep disorder related to nightmares (p = 0.012). Women need more time to reach a state of alertness after getting up (p = 0.022), and there was an interaction between sex and the alertness factor when evaluating the subjective quality of sleep (p = 0.030). Women show worse sleep quality and a higher frequency and propensity for suffering nightmares. When considering the relationship between sleep quality and academic performance, it is observed that students with poor sleep quality obtain lower academic scores (M = 7.21, SD = 0.805) than those with good sleep quality (M = 7.32, SD = 0.685), an effect that reaches significance (t = 2.116, p = 0.035). Regarding the relationship between the categorized chronotype and academic performance, students with a morning chronotype achieve better academic results (M = 7.41, SD = 0.89) than their evening counterparts (M = 7.15, SD = 0.76), although these differences have a small effect size (d = 0.31).

This study examined the relationship between extracurricular physical activity (PA) levels and students’ motivational and emotional experience during physical education (PE) classes and how this psychological experience can predict the intention to be physically active. The sample consisted of 811 Spanish secondary education students (371 boys and 440 girls) aged between 11 and 17 years (M = 13.15, SD = 1.16). Students completed questionnaires about their PA levels, their intention to be physically active, and their motivational and emotional experience during PE classes. A cluster analysis was used to classify the students according to their level of extracurricular PA. Based on a regression analysis, the variables enjoyment, pride, hopelessness, competence, satisfaction, and autonomous motivation played the highest role, predicting the intention to be physically active in the future. Statistical differences were found among the different PA profiles in these variables during the PE classes (MANCOVA). In conclusion, hours of PA outside school have a high relationship with the students’ emotional and motivational experience in their PE classes, which is related with the intention to practise PA in the future. A series of strategies have been proposed at both the institutional level and the teacher level to improve the PE psychological experience of those students who practise less extracurricular PA.

The aim of this study was to analyse the pacing strategies adopted by elite male and female marathon runners when setting every world record since 1998. For data analysis, the total distance of the marathon was divided into eight sections of 5 km and a final section of 2.195 km, and the relative average speed of each section was calculated individually. Female athletes maintained similar speeds in the first and second half of the marathon (ES = 0.22, small effect, p = 0.705), whereas male athletes increased their speed as the marathon progressed (ES = 1.18, moderate effect, p = 0.011). However, no differences were observed between men and women in either the first (ES = 0.56, small effect, p = 0.290), or in the second half of the marathon (ES = 0.60, moderate effect, p = 0.266). When comparing the women's world records (1998–2003) vs. men's records (1998–2018) by sections, we observed differences at the beginning of the race (second section, ES = 0.89, moderate effect) and at the end (last section, ES = 0.87, moderate effect). The pace variations during the race were similar between male athletes and that of women with male pacemakers (1.53% ± 0.60 vs. 1.68% ± 0.84, respectively). However, a trend towards higher pace variations during the race in the female records with female pacemakers was observed (2.28% ± 0.95). This study shows how male and female marathon records in the last 20 years have been set using different pacing strategies. While men used a negative strategy (faster finishing), women used a less uniform pacing strategy.

The main goal of this study was to analyse the pacing strategies displayed by the winners of the six World Marathon Majors in order to determine which race offers the greatest potential for future world record attempts. For data analysis, the total distance of the marathon was divided into eight sections of 5 km and a final section of 2.195 km, and time needed to complete each section was calculated in seconds. When we analyzed the mean winning time in the last 13 editions of each of the World Marathon Majors, we observed differences between New York and London (ES = 1.46, moderate effect, p = 0.0030), New York and Berlin (ES = 0.95, small effect, p = 0.0001), London and Boston (ES = 0.08, small effect, p = 0.0001), Boston and Berlin (ES = 0.10, small effect, p = 0.0001), Boston and Chicago (ES = 0.16, small effect, p = 0.0361), Berlin and Tokyo (ES = 0.20, small effect, p = 0.0034), Berlin and Chicago (ES = 0.27, small effect, p = 0.0162). This study shows that Berlin and London are likely candidates for future world record attempts, whilst such a performance is unlikely in New York or Boston.