Abstract
round:Advanced footwear technology (AFT) has gained popularity among non- elite runners due to its potential benefits in training and competition. This study investigated the training practices and reported outcomes in non-elite runners using AFT.Methods:A cross-sectional observational study was conducted with 61 non-elite runners competing in distances ranging from 5 km to marathons. The survey collected data on demographics, training parameters, footwear usage, perceived changes in running mechanics, and self-reported injuries.Results:The results revealed a significant positive correlation (R = 0.6,p< 0.0001) between years of AFT use and weekly training volume, indicating that more experienced runners are likely to incorporate AFT consistently into their routines. Conversely, a significant negative
from 5 km to marathons. The survey collected data on demographics, training parameters, footwear usage, perceived changes in running mechanics, and self-reported injuries.Results:The results revealed a significant positive correlation (R = 0.6,p< 0.0001) between years of AFT use and weekly training volume, indicating that more experienced runners are likely to incorporate AFT consistently into their routines. Conversely, a significant negative correlation (R =−0.5,p< 0.0001) was found between training volume and the number of weekly sessions using AFT, suggesting a selective approach to footwear use. Participants reported biomechanical changes, such as increased forefoot support (49%) and higher calf muscle activation (44%), alongside a 16% self-reported injury rate, predominantly affecting the calves.Conclusions:These findings highlight the importance of proper guidance and gradual adaptation to maximize the benefits of AFT while minimizing injury risks. Future research should explore the long-term impact of AFT on performance and injury prevention through longitudinal studies. Keywords:running; training; footwear technology; musculoskeletal; performance 1. Introduction Advanced footwear technology (AFT) shoes were first introduced by Nike in late 2016– early 2017, and they consisted of performance-enhancing shoes that combine lightweight, resilient midsole foams with rigid moderators and pronounced rocker profiles in the soles [1]. Unlike traditional racing flats, AFT shoes are designed to improve running economy and performance through innovations such as enhanced bending stiffness, high- energy return foam, and increased stack height [2]. A recent systematic review stated that most of the recent research focused on investigating the impact of running shoe midsoles, bending stiffness, and heel-to-toe drop on athletic performance [3]. Thanks to these features, elite athletes significantly improved their performances by 4–5% [4], and the progression of world records by males and females starting from 5 km to marathon Sports2024,12, 356.
Sports2024,12, 356 2 of 14 length was broken [5]. Supporting this, Willwacher et al. [6] analyzed the 100 best yearly performances globally between 2010 and 2022, finding that AFT shoes contributed to systematic improvements in running economy and performance across multiple events. Their findings highlight pronounced benefits in long-distance events, particularly among women, who showed performance gains of 2.2% to 3.5%, compared to 0.7% to 1.4% in men. These characteristics also enabled great achievements such as Eliud Kipchoge’s sub-2-h marathon, which would have been deemed unlikely without technological enhancements regarding AFT [7]. These improvements have been consistently supported by laboratory- based studies, which highlight that AFT reduces the energy cost of running by 2.7% to 4.4%, translating into enhanced performance for elite runners [2,8]. While AFT is now a standard choice for elite athletes during both training and competition, its adoption among non-elite runners is less understood. Bermon [9] observed similar performance in sub-elite and recreational runners, suggesting the broader accessibility of AFT benefits. The use of AFT shoes during training and competition has introduced novel biome- chanical demands of the foot and lower extremities [10]. The biomechanical differences between AFT shoes and standard running footwear were investigated by Hoogkamer et al. [11], who found that runners using AFT shoes had a decrease in cadence and cor- respondingly longer steps, as well as a longer flight time. The use of AFT has also been associated with higher peak vertical ground reaction forces, vertical impulse per step, differences in ankle and metatarsophalangeal joint mechanics, and reduced peak ankle dorsiflexion during stance, as well as increased peak ankle moments, all of which are biomechanical changes believed to enhance running economy and overall performance, particularly in elite runners [11]. However, the same changes impose additional demands on the foot and lower extremities, which may lead to injury risk if runners fail to adapt prop- erly. According to Tenforde et al. [10], the changes in foot and ankle mechanics introduced via AFT shoe footwear may contribute to the risk of injury. Biomechanical analyses suggest that these improvements come with shifts in running dynamics, such
impose additional demands on the foot and lower extremities, which may lead to injury risk if runners fail to adapt prop- erly. According to Tenforde et al. [10], the changes in foot and ankle mechanics introduced via AFT shoe footwear may contribute to the risk of injury. Biomechanical analyses suggest that these improvements come with shifts in running dynamics, such as increased forefoot loading and changes in stride mechanics, which could contribute to overuse injuries, par- ticularly in runners who are not accustomed to these demands [12,13]. Recent studies have begun to explore the impact of footwear technology on injury patterns in non-elite popu- lations, shedding light on its potential benefits and risks. For instance, Theisen et al. [14] highlighted that much of the presumed benefits of advanced footwear technology are based on biomechanical assumptions, rather than robust epidemiological evidence. Similarly, Malisoux et al. [15] emphasized the complexity of the relationship between footwear, train- ing loads, and injury risk, noting that perceived comfort and mechanical properties may not always align with strategies for injury prevention. Furthermore, systematic reviews, such as the review of Sun et al. [16], have shown that specific shoe features, such as midsole stiffness or heel–toe drop, may influence biomechanical variables but currently lack con- sistent evidence for reducing injury incidence. However, poor research and epidemiology articles on health concerns around using AFT shoes are available. Expressing their current opinion, Hoogkamer et al. [11] illustrated a series of navicular bone stress injuries in two cohorts, including a population of junior track and field athletes and two master athletes competing in endurance events. Despite the growing popularity of AFT, most existing research focuses on elite athletes, leaving a significant gap in understanding its implications for non-elite runners. The number of non-elite recreational runners steadily increases and represents a substantial portion of the global running community. These athletes are often driven by personal health and wellness goals, rather than competitive ambitions, like running closely to pursue a disciplined and virtuous lifestyle [17]. Non-elite runners differ from elite athletes in several biomechanical characteristics, including reduced cadence, increased ground contact time,
number of non-elite recreational runners steadily increases and represents a substantial portion of the global running community. These athletes are often driven by personal health and wellness goals, rather than competitive ambitions, like running closely to pursue a disciplined and virtuous lifestyle [17]. Non-elite runners differ from elite athletes in several biomechanical characteristics, including reduced cadence, increased ground contact time, and greater variability in stride mechanics. These factors, combined with differences in training practices and access to professional guidance, may contribute to their unique injury risks. Furthermore, non-elite runners face a significant prevalence of running- related injuries, which range from 37 to 79%, depending on the follow-up duration and
Sports2024,12, 356 3 of 14 the definition of the running-related injury used [18]. The most common injuries include patellofemoral pain, Achilles tendinopathy, iliotibial band syndrome, and plantar fasciitis, primarily affecting areas below the knee. While biomechanical factors, such as atypical lower limb alignment and altered mechanical function, have been proposed as potential contributors to RRI, the current evidence remains inconclusive, and it warrants further investigation [18]. Moreover, these non-elite athletes differ significantly from their elite counterparts in terms of physiological capacities, training volume, and performance goals. Unlike elite athletes, who often have access to professional coaching and biomechanical analyses, recreational runners are more likely to experiment with AFT independently. This autonomy could increase the risk of improper adaptation or overuse injuries, particularly if the shoes are used inappropriately or without consideration of individual biomechanics. Understanding how non-elite runners adapt to AFT, and the potential implications for injury risk and performance, is essential to developing targeted recommendations for this population. The current evidence on how AFT influences training practices, running mechanics, and injury risk in non-elite runners is limited, making it difficult to draw definitive conclu- sions about its benefits and challenges for this population. Recreational runners represent a significant portion of the global running community, and understanding their response to AFT is critical, given their unique susceptibility to musculoskeletal injuries. These include acute injuries, such as muscle strains, lower limb stress, fractures, and chronic conditions like tendinopathies or joint overuse syndromes. This study aimed to address these gaps by investigating the experiences of non-elite runners using AFT, defined in this study as commercially available running shoes incorporating carbon fiber plates and innovative midsole technologies designed to enhance energy return and improve running economy. The focus of this study was on their training practices, perceived benefits, and reported challenges. Insights into how recreational runners adapt to AFT can help identify strategies to mitigate injury risks and promote safe, sustained engagement in running. By analyzing real-world data from a diverse cohort of recreational runners, this research sought to pro- vide valuable insights into the integration of AFT into everyday training routines, offering
their training practices, perceived benefits, and reported challenges. Insights into how recreational runners adapt to AFT can help identify strategies to mitigate injury risks and promote safe, sustained engagement in running. By analyzing real-world data from a diverse cohort of recreational runners, this research sought to pro- vide valuable insights into the integration of AFT into everyday training routines, offering practical recommendations for optimizing its use while minimizing potential risks. 2. Materials and Methods 2.1. Study Design This prospective, cross-sectional, observational study was conducted following the STROBE guidelines [19]. Before completing the questionnaire, all participants provided informed consent outlining the study protocol. Data collection was carried out over six months, from 1 January to 30 June 2024. The study protocol received approval from the Institutional Ethics Review Committee of the Universitàdegli Studi di Milano (Protocol No. 52/20, Attachment 4, 14 May 2020), adhering to the Declaration of Helsinki and all relevant ethical regulations for research involving human participants. 2.2. Participants Non-elite runners training for or competing in distances ranging from 5 km to marathon length were recruited in person through running clubs located in Lombardy, Italy, and online via email and WhatsApp. The recruitment materials explicitly invited runners of varying experience levels and training practices to ensure diversity within the sample. The inclusion criteria required participants to be members of the Italian Athletic Federation (FIDAL) and to have used AFT in training or competition for distances between 5 km and a marathon. For the purposes of this study, AFT was defined as commercially available running shoes incorporating carbon fiber plates and innovative midsole technologies de- signed to enhance energy return and improve running economy. Participants were asked to confirm their use of AFT via a structured questionnaire, which also collected details about specific shoe models, contexts of use (e.g., training or competition), and any alternation with other footwear technologies. To minimize potential selection bias, no exclusion criteria
Sports2024,12, 356 4 of 14 were applied, and recruitment efforts targeted runners across different age groups and genders. Demographic and training characteristics were monitored during recruitment to avoid the overrepresentation of highly experienced or competitive runners. While the study relied on a convenience sample, this approach was designed to reflect the diversity of the recreational running population. 2.3. Survey Participants were explicitly instructed to reflect on their most recent training practices and experiences to minimize recall bias. The survey was developed on Google Forms based on a review of the existing literature and validated through expert consultation. Three experts in sports biomechanics and running injuries reviewed the survey to ensure content validity. A pilot test was conducted with 10 recreational runners to assess the clarity and comprehensiveness of the questions, as well as the time required for completion. Feedback from the pilot test was used to refine the survey. To ensure reliability, selected questions were rephrased and repeated within the survey, and consistency in the responses was ana- lyzed. Participants were provided with detailed instructions emphasizing the importance of accurate and truthful self-reporting. Anomalies or inconsistencies in responses were flagged and verified with participants when possible. Participants completed a survey comprising three main sections, designed to be completed in 10–15 min. The full survey contents, including the questions used to assess training practices, footwear usage, and perceived outcomes, are provided in Appendix. 2.4. Statistical Analysis Descriptive statistics were calculated for all outcome measures and reported as means ±standard deviations (SDs). The normality of data distribution for demographic variables (age, height, body mass, and BMI), running activity (competition type, years of practice, weekly sessions, and training volume), and AFT use (years of use and weekly sessions) was assessed using graphical methods and the D’Agostino–Pearson test. Since all variables showed normal distributions, parametric tests were applied. Continuous variables such as weekly training volume and weekly sessions were categorized into predefined ranges for visualization and comparison purposes. Weekly training volume was grouped into categories such as “0–30 km”, “30–60 km”, and “≥60 km”, while weekly sessions were cat- egorized as “1–2 sessions”, “3–4
and the D’Agostino–Pearson test. Since all variables showed normal distributions, parametric tests were applied. Continuous variables such as weekly training volume and weekly sessions were categorized into predefined ranges for visualization and comparison purposes. Weekly training volume was grouped into categories such as “0–30 km”, “30–60 km”, and “≥60 km”, while weekly sessions were cat- egorized as “1–2 sessions”, “3–4 sessions”, and “>4 sessions”. The correlation between AFT use and running activity metrics was analyzed using Pearson’s correlation coefficient. The coefficient of determination (R 2 ) calculated from Pearson’s correlation coefficient represents the proportion of variance in the dependent variable thatis explained by the independent variable in the model. Effect sizes were calculated to determine the proportion of variance explained by each correlation. To ensure the appropriateness of the linear models, a resid- ual analysis was performed. Residuals were found to be randomly distributed around zero, confirming the validity of the regression models and indicating no systematic pat- terns. Correlation strength was categorized as negligible (0.0–0.3), low positive or negative (0.3–0.5), moderate positive or negative (0.5–0.7), high positive or negative (0.7–0.9), or very high positive or negative (0.9–1.0). Correlations were considered statistically significant when the correlation coefficient (r) exceeded 0.3 andp-values were below 0.05 [20]. Injury patterns and distribution data were summarized using descriptive statistics, including frequencies and percentages to illustrate the distribution of injuries based on the number of sessions using AFT shoes and the duration of AFT shoe use. Confidence intervals (95% CIs) were calculated for all reported percentages to provide an estimate of the precision of the observed proportions. Additionally, odds ratios (ORs) were calculated to assess the relative risk of injuries between groups, using one group as the reference category. The association between running experience and changes in running technique was analyzed using a chi-square test to evaluate the relationship between categorical variables. All statistical analyses were conducted using Prism GraphPad Prism software, version 11, for Windows (GraphPad Software, Version 11, San Diego, CA, USA).
changes in running technique was analyzed using a chi-square test to evaluate the relationship between categorical variables. All statistical analyses were conducted using Prism GraphPad Prism software, version 11, for Windows (GraphPad Software, Version 11, San Diego, CA, USA).
Sports2024,12, 356 5 of 14 3. Results 3.1. Demographic Characteristics The survey was distributed to 84 non-elite runners who were members of local running clubs in Lombardy (Italy). The participants were recruited via in-person announcements during club meetings and through digital channels, including email and WhatsApp groups. Of the 84 runners invited, 61 participants (47 men, 77%; age: 38±11 years; height: 1.76±0.07 m ; body mass: 66±7 kg; BMI 21.4±1.7 kg/m²; and 14 women, 23%; age: 38±12 years; height: 1.63±0.05 m; body mass: 53±5 kg; BMI 19.2±1.3 kg/m²) completed the survey, resulting in a response rate of 72%. All participants reported having used AFT during training or competition, making their responses directly relevant to the study objectives. Demographic data, including age, height, body mass, and calculated BMI, were self-reported by the participants. 3.2. Running Activity The participants reported competing in various distances, including 5 km (67%), 10 km (67%), half-marathon distance (62%), and marathon distance (44%). These dis- tances represented the events for which participants were currently training at the time of completing the survey. Their average running history was 8±3 years, reflecting their cumulative experience in running. Weekly training data, including the number of sessions (7±3 sessions/week) and training volume (68±20 km), were based on participants’ activ- ities during the six months before the survey. Figure competing at each distance, including marathons, half marathons, 10 km races, and 5 km races. The percentages shown exceed 100% because many participants reported competing in multiple event types.Sports 2025, 13, x FOR PEER REVIEW 6 of 14 Figure 1. The proportion of runners reporting specific types of competition. Significant correlations were identified between weekly training volume and AFT use. A moderate positive correlation (R = 0.6, p < 0.0001) was found between training vol- ume and years of AFT use, with an r 2 of 0.4. Similarly, a moderate negative correlation (R = −0.5, p < 0.0001) was observed between training volume and the number of weekly train- ing sessions using AFT, with an r 2 of 0.3. These findings are shown in Figure 2. 0 20 40 60 80 100120 0
training vol- ume and years of AFT use, with an r 2 of 0.4. Similarly, a moderate negative correlation (R = −0.5, p < 0.0001) was observed between training volume and the number of weekly train- ing sessions using AFT, with an r 2 of 0.3. These findings are shown in Figure 2. 0 20 40 60 80 100120 0 1 2 3 4 5 6 7 Weekly training volume (km) Use of AFT (years) R = 0.6 - P<0.0001 Y = 0.4315*X -0.2554 A 0 20 40 60 80 100120 0 1 2 3 4 5 6 7 Weekly training volume (km) Weekly sessions with AFT (n) R = -0.5 - P<0.0001 Y = -0.0423*X + 4.796 B Figure 2. Correlation between weekly training volume and the use of advanced footwear technology (AFT) and weekly training volume (A) and the number of weekly training sessions (B). The weekly training volume was reported as continuous data and categorized into ranges (e.g., “0–30 km ,” “30– 60 km,” and “ ≥ 60 km”) for visualization purposes. Similarly, weekly training sessions were grouped into categories (e.g., “1–2 sessions” and “3–4 sessions”). The dashed lines represent the 95% confidence intervals for the regression lines. Additionally, a moderate positive correlation (R = 0.6, p < 0.001) was observed be- tween years of running experience and the duration of AFT use. A weak but statistically significant positive correlation (R = 0.4, p = 0.02) was found between running experience and the number of weekly sessions using AFT (R = 0.4, p = 0.02). To further support these correlations, a residual analysis was conducted. Residuals were found to be randomly Figure 1.The proportion of runners reporting specific types of competition. Significant correlations were identified between weekly training volume and AFT use. A moderate positive correlation (R = 0.6,p< 0.0001) was found between training volume and years of AFT use, with an r 2 of 0.4. Similarly, a moderate negative correlation (R =−0.5, p< 0.0001) was observed between training volume and the number of weekly training sessions using AFT, with an r 2 of 0.3. These findings
Description
The research explores the impact of advanced footwear technology on training and injury in non-elite runners.