The timing is significant. The article estimates that more than 740 million smartwatch users could have access to daily health tracking by 2029, without counting smart rings, wrist bands, portable electroencephalography devices or sensor-equipped mattresses. Once confined largely to hospitals, sleep laboratories and exercise physiology facilities, physiological monitoring has become part of everyday life and the wider “quantified-self” movement. Consumer devices can estimate sleep duration, sleep stages, heart rate, heart-rate variability and activity patterns, allowing users to observe biological signals continuously. In high-performance sport, wearables can collect information during travel, competition and recovery, including environments where conventional laboratory equipment would be impractical. Professional cyclists, for example, have been monitored during major stage races to examine sleep and autonomic activity. Yet the expanding availability of data has outpaced sport-specific guidance on how athletes should interpret it, who should control it and when it should influence decisions.

The technology itself is scientifically ingenious but not equivalent to a clinical instrument. Many wrist-worn devices use photoplethysmography, or PPG, a technique in which green or infrared light-emitting diodes illuminate the skin while photodiodes detect changes in reflected light caused by blood-volume fluctuations. From those optical signals, algorithms estimate pulse rate and, under suitable conditions, beat-to-beat variation. Motion, sweat, loose contact and device placement can introduce artifacts, while sleep stages and recovery scores are often inferred through proprietary models combining several indirect measurements. Some commercial devices have been compared with reference methods such as polysomnography and have shown useful performance for particular metrics. That does not mean every output is equally accurate, or that a device’s interpretation should be treated as a direct reading of physiology. Accuracy can also vary across users and exercise intensities. Evidence concerning skin pigmentation and PPG remains mixed, but studies cited by the authors indicate that heart-rate error may increase during intense exercise for people with darker skin tones and that missing or lower-quality data may be disproportionately common.

The greatest interpretive leap occurs when raw or relatively transparent measurements are converted into composite scores. A platform might combine sleep duration, resting heart rate, heart-rate variability, recent activity and other inputs into a single “readiness,” “recovery” or “training status” number displayed on a scale from zero to 100 or as a traffic-light warning. Such scores are attractive because they turn complicated time series into an apparently simple instruction. But their proprietary inputs and algorithms can make them difficult to validate independently. Two devices may process similar signals differently and produce different conclusions about the same night of sleep. A low score may reflect a real change, ordinary biological variation, sensor noise or an algorithm’s assumptions. The authors therefore emphasize that digital health metrics are most useful as longitudinal signals rather than daily judgments. Average sleep duration may be estimated from roughly three to seven nights, they note, while understanding night-to-night variability may require six to ten weeks of continuous monitoring.

That distinction is especially important for athletes, who often work in environments where perfectionism is rewarded. The perspective cites evidence that as many as 39 percent of some athlete groups display unproductive perfectionism, a pattern that can turn a useful training aid into a source of pressure. A competitor who feels rested but sees a poor recovery score may worry unnecessarily, reduce training or begin repeatedly checking the device. Another athlete may feel exhausted despite an apparently excellent sleep score and conclude that their own perceptions are wrong. The proposed construct differs from “orthosomnia,” a term used for excessive pursuit of ideal sleep data, because orthometria encompasses any physiological metric gathered by consumer digital health technology. It also differs from the broader quantified-self movement: tracking is not inherently harmful, and orthometria refers specifically to situations in which engagement with the data produces a negative outcome. The authors are careful not to claim that this behavioral pattern has yet been established through prevalence studies or validated psychological measurement.

To reduce the risk, the researchers outline a five-stage implementation framework based on David Kolb’s experiential learning theory, which treats learning as an iterative cycle of experience, reflection and application. The process begins with preparatory education before data collection starts. Athletes should be told which metrics will be recorded, how often collection will occur, who will have access to the information, who owns it and how it may affect training decisions. Education should address not only what a metric represents but also how often it should be viewed and how much weight it deserves. Athletes and support staff should be prepared for disagreements between subjective experience and device outputs, because such discrepancies are normal when indirect estimates are compared with the complex combination of physical and psychological information represented by a person’s own perception. Staff should also understand the warning signs of counterproductive preoccupation and know when referral is appropriate.

The second stage involves a supervised period of direct experience with the device. Athletes begin collecting and viewing their own information, ideally for at least one to two weeks, but are encouraged to observe rather than immediately act on early readings. This delay allows an individual baseline to develop. In the third stage, an expert such as a sport scientist, physiologist, psychologist or medical professional helps the athlete examine trends across weeks rather than reacting to isolated daily values. The fourth stage shifts the emphasis toward athlete-led interpretation. In one-on-one sessions, the expert facilitates reflection, helping the athlete integrate digital signals with perceived fatigue, mood, training demands, travel and performance context. The framework even proposes periodic metric-minimized training blocks, during which athletes make decisions using subjective experience and coach feedback rather than live scores, then review the data afterward to calibrate their perceptions. Finally, the fifth stage moves toward independent use: athletes retain agency over whether and how they review their information, while coaches and specialists use agreed-upon data alongside the athlete’s observations to inform training and recovery.

The framework also identifies a social risk that could be more powerful than personal perfectionism. If athletes believe wearable data influences selection, playing time, contracts, training opportunities or staff judgments, monitoring can begin to feel like surveillance. Anxiety may then arise not because an athlete is fascinated by a score, but because a low number appears to threaten their career. For that reason, responsible implementation requires explicit rules governing data ownership, privacy, access, downstream sharing and use in performance evaluations. The authors say the approach should apply to organization-issued devices and personally owned wearables alike, provided that multidisciplinary experts are available to interpret the information. It should also begin only after an organization has selected metrics and devices with evidence of adequate validity and relevance. Without that groundwork, a carefully staged education program could lend undeserved authority to unreliable measurements.

The researchers present orthometria as a starting point rather than a final diagnosis. They call for interviews and other qualitative research with athletes to determine which metrics most strongly influence behavior, what fixation looks like in practice and which organizational conditions increase risk. They also propose developing and validating an orthometria-specific questionnaire, similar in spirit to existing measures of anxiety and preoccupation about sleep. Intervention studies could test whether education, reduced device exposure and feedback based on longer-term trends actually protect well-being without sacrificing useful information. The broader message is not that athletes should abandon wearable technology. These devices can provide valuable physiological signals beyond the laboratory, and their data may complement expert observation and athletes’ own experiences. But a number is still an estimate, a score is still an interpretation and neither should become the sole authority over a living body. As personal health technology spreads, learning when not to measure may become as important as learning how measurement works.

The phenomenon of RED-S is characterized by an insufficient energy availability, which is rooted in the imbalance between dietary energy intake and the energy expended during physical activity. For ultra-endurance athletes who frequently train at high intensities for prolonged periods, the risk of entering a state of energy deficiency is heightened. This complex issue can lead to serious physiological disruptions, including hormonal imbalances and impaired metabolic function, which ultimately compromise athletic performance and overall well-being.

One of the striking findings reported in the review is the relationship between RED-S and mental health issues, particularly among athletes in the ultra-endurance community. It has been demonstrated that energy deficiency can contribute to anxiety, depression, and increased stress levels, creating a vicious cycle that can severely hamper an athlete’s performance. This relationship underscores the importance of a holistic approach when addressing the health of ultra-endurance athletes, where both physical and psychological aspects are considered in tandem.

The review also highlights the significant variations in the presentation of RED-S symptoms among male and female athletes. While both genders experience similar physiological consequences, the manifestation of symptoms may differ due to hormonal factors and societal pressures. Female athletes, in particular, may face greater scrutiny regarding their body image, which can exacerbate the risk of energy deficiency. Addressing these gender-specific issues is crucial for creating effective prevention and treatment strategies tailored to the unique needs of ultra-endurance athletes.

Nutritional strategies play a critical role in preventing and managing RED-S among ultra-endurance athletes. Maintaining a sufficiently high caloric intake, alongside a well-balanced diet rich in essential nutrients, is paramount for sustaining performance and health. The review emphasizes the need for athletes to work with registered dietitians or nutritionists who specialize in sports nutrition, ensuring they receive personalized advice that accounts for their unique training regimens and energy expenditure demands.

Moreover, the role of education and awareness cannot be overstated. Athletes, coaches, and support personnel must be well-versed in the warning signs of RED-S and understand the implications of energy deficiency on both performance and health. Training programs should incorporate educational components that inform athletes about the importance of energy balance, proper nutrition, and self-care strategies, fostering a culture that prioritizes physical and mental well-being.

In recent years, there has been a significant shift towards a more supportive and empathetic approach in the athletic community concerning mental health. This shift is paramount for addressing issues related to RED-S, as athletes may feel pressured to conform to certain body standards or performance expectations. Creating an open dialogue around mental health within the realm of ultra-endurance sports is essential for breaking the stigma associated with seeking help and fostering an environment where athletes feel comfortable discussing their challenges.

In addition to mental health considerations, the review points to the role of technology in monitoring athletes’ health and performance. Wearable devices and apps can aid in tracking energy expenditure, nutrient intake, and physiological responses, providing valuable insights that can inform nutrition and training regimens. Coaches and athletes alike can harness this technology to create more data-driven, personalized approaches to training that prioritize energy balance and overall health.

The review by Colangelo et al. also presents a call to action for organizations governing ultra-endurance sports, urging them to develop comprehensive guidelines and policies that address issues related to RED-S. These measures could include mandatory nutrition education for athletes and coaches, as well as protocols for identifying and managing energy deficiency in competitive settings. A proactive stance from governing bodies would contribute significantly to raising awareness and reducing the incidence of RED-S among athletes.

Cross-disciplinary collaborations are essential for tackling the multifaceted nature of RED-S in ultra-endurance sports. An alliance between sports scientists, nutritionists, psychologists, and trainers can generate a wealth of knowledge and strategies that address the variables contributing to energy deficiency. By integrating expertise from diverse fields, the sports community can develop more robust frameworks for preventing and managing RED-S, ultimately enhancing athlete health and performance.

Furthermore, examining cultural and societal influences on the perception of body image within the context of ultra-endurance sports is critical. Athletes, especially emerging talents, are often subjected to unrealistic ideals propagated by media and social platforms, leading to unhealthy behaviors in their pursuit of success. Addressing these influences through advocacy and positive representation can help empower athletes to embrace diverse body shapes and sizes as they strive for excellence in their respective sports.

As the conversation surrounding RED-S continues to evolve, the importance of community support cannot be overstated. Peer support networks can play a vital role in helping athletes navigate the challenges they face, providing a platform for sharing experiences and coping strategies. Fostering an inclusive environment that encourages athletes to connect and support one another can be a powerful determinant in promoting health and performance standards.

The rich tapestry of ultra-endurance sports presents unique challenges that demand attention and action, particularly concerning RED-S. The insights derived from the review by Colangelo et al. shed light on the various dimensions of this condition, offering a comprehensive understanding of its implications. By prioritizing education, open dialogue, personalized nutrition, and mental health advocacy, the sports community can pave the way for healthier, more resilient athletes.

In summary, the exploration of RED-S within ultra-endurance sports reveals a landscape fraught with complexities that require a concerted effort from all stakeholders involved. Through collective awareness and a commitment to athlete well-being, the potential for a healthier future in ultra-endurance sports is within reach.

Subject of Research: The presentation of Relative Energy Deficiency in Sport (RED-S) in ultra-endurance sports.

Article Title: Exploring the presentation of REDs in ultra endurance sport: a review.

Article References:

Colangelo, J., Smith, A., Henninger, K. et al. Exploring the presentation of REDs in ultra endurance sport: a review.
J Eat Disord 13, 210 (2025). https://doi.org/10.1186/s40337-025-01381-0

Image Credits: AI Generated

DOI: 10.1186/s40337-025-01381-0

Keywords: Relative Energy Deficiency in Sport (RED-S), ultra-endurance sports, nutrition, mental health, energy balance.