The balance between recovery and stress and between training and rest is of high importance in the daily routine of competitive athletes, and is a substantial component for optimal competition preparation (Hausswirth & Mujika, 2013; Kellmann & Beckmann, 2018a). Fast and effective regeneration and recovery have become important due to the increased frequency of competition, which is related to social and media pressures and the constant pursuit for performance improvement. The greater demand on athletes is supported by literature findings of inadequate recovery phases and overload symptoms in athletes from different sport disciplines (Dupont et al., 2010; Ekstrand, Walden, & Hagglund, 2004; Main & Landers, 2012; Meyer, 2010). Increased training stimuli for a long period combined with insufficient recovery can lead to a performance stagnation or decrease and may even involve a chronic maladaptation. This is known as overtraining syndrome (Meeusen et al., 2013; Meeusen & De Pauw, 2018). Progressive fatigue and underperformance can be the result of a long-term underrecovery (Halson, 2014; Kellmann & Beck-mann, 2018a). However, the difficulty is to determine the exact point when conventional training turns from overreaching into non-functional overreaching.
Recovery and stress
Since the terms load and stress differ between scientific disciplines, it is necessary to define them.1 Load defines the objectively quantifiable variables or factors that externally affect a person. Load is reflected in the subjective results and in the person’s perception of stress (Rohmert & Rutenfranz, 1975). To give an example from sports, different individuals respond differently (subjective stress; e.g., dependent on the training condition or the current state on the day) to an external load of 100 kg in bench press (objective load). Also, the same individual may respond differently to the same external load because of changes in their current physiological, emotional, and mental states. Therefore, the assessment of the mediating psychological processes associated with various perceptions (e.g., perceptions of load/effort/discomfort) are of great importance (Jerusalem, 1990; Lazarus, 1991). Athletes with the same performance level may react in different ways to an identical stimulus and show different stress states (Raglin, 1993). The same external absolute training load could lead to the desired training adaptions in one athlete, but chronic maladaptations in another athlete (O’Toole, 1998), or even the same athlete under different stress and recovery states. Therefore, there is a need to assess the emotional and mental states of an athlete and potential regeneration/recovery strategies to help them adapt to stress.
Kellmann, Bertollo, et al. (2018) recently defined the terms that are related to recovery in a consensus statement.
Recovery is regarded as a multifaceted (e.g., physiological, psychological) restorative process relative to time. In case an individual’s recovery status (i.e., his or her biopsychosocial balance) is disturbed by external or internal factors, fatigue as a condition of augmented tiredness due to physical and mental effort develops. Fatigue can be compensated with recovery, that is, the organismic allostatic balance is regained by reestablishing the invested resources on a physiological and psychological level.
(Kellmann, Bertollo, et al., 2018, p. 240)
Physiologically, recovery is mainly referred to as regeneration in sport and exercise contexts (Kellmann, Bertollo, et al., 2018). Ideally, regeneration follows physical fatigue that has been induced by training or competition. Nédélec et al. (2012) mentioned cold water immersion (CWI), nutrition/diet, and sleep as frequently used and scientifically evaluated regeneration methods. On a psychological level, cognitive coping strategies, resource activation, and psychological relaxation techniques (e.g., breathing, progressive muscle relaxation, systematic application of napping) help to reduce mental fatigue (Kellmann & Beck-mann, 2018b; Kellmann, Pelka, & Beckmann, 2018; Pelka & Kellmann, 2017).
A continuous physiological or psychological imbalance due to inadequate recovery and excessive demands can be the result of insufficient systematic and individualized recovery, which can further lead to a cascade of deleterious conditions. The first precursor of an overtraining syndrome can be a state of continuous underrecovery which has been identified as underrecovery syndrome (Kellmann, Bertollo, et al., 2018). This underrecovery syndrome is the consequence of an imbalance between daily life demands and recovery, and depicts the reaction to general stress (e.g., family, media) as a broader condition of insufficient recovery. Meeusen et al. (2013), on the other hand, define non-functional overreaching (NFO) as a more training-specific concept that results in negative psychological and hormonal alterations and decreased performance. Continuous underrecovery and NFO often serve as precursors to overtraining syndrome. An accumulation of insufficient recovery from daily life demands, in combination with a long-term NFO in training and competition, will inevitably lead to the overtraining syndrome. Despite a considerable overlap in symptoms between underrecovery and overtraining (e.g., fatigue, exhaustion), physical symptoms of an overtrained state include continuous muscle soreness, pain sensations, or clinical and/or endocrinological disturbances. The earlier potential intervention strategies are applied, the shorter the recovery period from overtraining will be. Compensation for underrecovery can be the systematic application of recovery strategies and rest periods, while recovering from overtraining requires a continuous restoration. This can only be achieved through long rest periods that might last from weeks to months. Recovery serves as the umbrella term, which can then be further characterized by different forms of recovery, such as regeneration or psychological recovery strategies. These strategies should be applied in a structured manner and they should be tailored to the individual needs of the athlete.
It is certain that in sport and training science, the type of stimulus and the type of recovery interact with each other, depending on the respective activity (Kellmann, Bertollo, et al., 2018). A stimulus can, therefore, either lead to overload or, in combination with sufficient recovery, it can contribute to a training effect and an increased resilience to the training stimulus. Top athletic performance cannot only be accomplished through optimal training intensity and volume, but also through the compliance and facilitation of sufficient rest and recovery phases between training sessions (Hoffman, Epstein, Yarom, Zigel, & Ein-binder, 1999). Chronic negative consequences in the mental and physical domain, for example as an over-training syndrome, can be the result of neglected recovery (Kellmann, Bertollo, et al., 2018). Therefore, it is important to recognize an imbalance between the recovery-stress state as early as possible to avoid an unplanned reduction in performance (Brink, Visscher, Coutts, & Lemmink, 2012; Kellmann & Beckmann, 2018a). Standardized diagnostic methods can identify signs of overtraining with the help of the current biopsychosocial stress state to individually adapt the training regulation (Meeusen et al., 2013). Moreover, psychometric methods can support interdisciplinary cooperation between the coaches, medical team, and sport-psychological staff (Kellmann, Bertollo, et al., 2018). According to Hooper, Mackinnon, Howard, and Gordon (1995), the difficulty with physiological markers lies in distinguishing abnormal changes from normal reactions that result from intensive training stimuli. Often, overtraining syndromes are more effectively revealed with the help of psychological parameters than with objective tests (Kenttä & Hassmén, 1998; Raglin & Wilson, 2000; Saw, Main, & Gastin, 2016; Saw, Kellmann, Main, & Gastin, 2017).
Psychometric scales may well represent the most successful instrument in scientific studies to show recovery and stress (Heidari et al., 2019; Heidari, Kölling, Pelka, & Kellmann, 2018; Kellmann, Bertollo, et al., 2018; Meeusen et al., 2013; Nässi, Ferrauti, Meyer, Pfeiffer, & Kellmann, 2017b; Saw et al., 2016). One reason for this superiority could be assumed in the underlying global approach, as the gathered items assess several recovery and stress levels at the same time. The mental state, for instance, is constituted from different physical, mental, and emotional inputs that are processed by the central nervous system and hence influence the perception of the recovery-stress state, as well as the need for regeneration. By using psychometric methods, the individual biopsychosocial recovery-stress state can be measured economically and effectively and with as little impact as possible. In addition, performance control and training prescription can be supported (Meeusen et al., 2013). With regard to the monitoring of larger groups, using psychometric tools bears advantages due to the economy of implementation and the objectivity of evaluation (Kellmann & Beckmann, 2003). Furthermore, the recording of the athlete’s subjective perspective is crucial for an early identification of fatigue and stress signals (Meeusen et al., 2013; Meeusen & De Pauw, 2018). Constant monitoring is especially relevant, as athletes react differently and adapt individually to training stimuli (Coutts, Crowcroft, & Kempton, 2018; Hecksteden et al., 2017). It should be considered, though, that psychometric methods are generally transparent and are therefore easy to manipulate, as well. Hence, the use of the data and the benefit for an optimal training prescription must be explained to the athletes (Kellmann & Beckmann, 2003).
Assessing recovery and stress in sport
The following subjective measurements are mostly used in sport-scientific research and practice: Borg’s Rating of Perceived Exhaustion (Borg, 1998), Delayed-Onset Muscle Soreness (Ohnhaus & Adler, 1975), Profile of Mood States (McNair, Lorr, & Droppleman, 1992) and Recovery-Stress Questionnaire for Athletes (Kellmann & Kallus, 2001, 2016).
Borg’s Rating of Perceived Exhaustion (RPE; Borg, 1998) is a one-dimensional scale. The original version with a scale from 6 to 20 (very, very easy to very, very hard) measures the training intensity and the perceived exhaustion of an athlete at a certain time. Due to its shortness, the RPE has been used in many experimental studies (Noble & Robertson, 1996). Changes in the RPE scale in combination with blood lactate proved to be a reliable predictor for overtraining (Snyder, 1998; Snyder, Jeukendrup, Hesselink, Kuipers, & Foster, 1993). In a cohort study with more than 2,500 participants, the RPE turned out to be a convenient and valid instrument for emphasizing the training intensity independently from gender, age, and type of the implemented load (Scherr et al., 2013). Foster (1998) introduced a modification of the RPE (Session-RPE), which involves an athlete rating a whole training session with a global intensity. By multiplying the value (on a scale from 0 to 10) with the duration of the training session 30 minutes after completion, the individual training load can also be determined (Impellizzeri, Rampinini, Coutts, Sassi, & Marcora, 2004). However, a criticism of RPE scales is that the underlying reasons for changes in subjective effort across sessions for the same absolute training load remain unclear. Therefore, it is difficult to derive appropriate intervention measures based on the ratings alone (Mäetsu, Jürimäe, & Jürimäe, 2005). For example, athletes who were identified with overtraining syndrome showed only minor variation in RPE ratings (Urhausen & Kindermann, 2002). Kellmann (2002) has pointed out that by using a ‘one-item scale’, the multidimensional aspect of stress and recovery is neglected. Moreover, Kenttä and Hassmén (1998) argue that recovery, which they do not only characterize as the absence or reduction of stress, is completely disregarded.
In training and (sports-)medical or clinical settings, the visual analogue scale has been used to measure Delayed-Onset Muscle Soreness (DOMS; Ohnhaus & Adler, 1975). The athlete marks on a 10-cm line, ranging from no pain (left endpoint) to extreme pain (right endpoint), the appropriate position for his/her experienced pain intensity. The distance (in mm or cm) between the left endpoint and the respective mark represents the pain index. Consequently, the scale proves to be an economical and quickly implemented method, which is especially useful in experimental studies (Brown et al., 2017; Cleather & Guthrie, 2007; Nosaka, Newton, & Sacco, 2002; Page, Swan, & Patterson, 2017). Williamson and Hoggart (2005) observed a good sensitivity to...