The aim of this systematic review was to identify and evaluate current literature which investigated the effects of ST exercise on the physiological determinants of middle- and long-distance running performance. The addition of new research published in this area, and the application of more liberal criteria provided results for 50% more participants (n = 469) compared to a recent review on RE [10]. Based upon the data presented herein, it appears that ST activities can positively affect performance directly and provide benefits to several physiological parameters that are important for distance running. However, inconsistencies exist within the literature, that can be attributed to differences in methodologies and characteristics of study participants, thus practitioners should be cautious when applying generalized recommendations to their athletes. Despite the moderate PEDro scores (4, 5, or 6), the quality of the works reviewed in this paper are generally considered acceptable when the unavoidable constraints imposed by a training intervention study (related to blinding) are taken into account.
Running Economy
Running economy, defined as the oxygen or energy cost to run at a given sub-maximal velocity, is influenced by a variety of factors, including force-related and stretch–shortening cycle qualities, which can be improved with ST activities. In general, an ST intervention, lasting 6–20 weeks, added to the training program of a distance runner appears to enhance RE by 2–8%. This finding is in agreement with previous meta-analytical reviews in this area that show concurrent training has a beneficial effect (~ 4%) on RE [10, 26]. In real terms, an improvement in RE of this magnitude should theoretically allow a runner to operate at a lower relative intensity and thus improve training and/or race performance. No studies attempted to demonstrate this link directly, although inferences were made in studies, which noted improvements in RE and performance separately [73, 80, 88]. Other works provide evidence that small alterations in RE (~ 1.1%) directly translate to changes (~ 0.8%) in sub-maximal [94] and maximal running performance [95]. The typical error of measurement of RE has been reported to be 1–2% [96,97,98,99] and the smallest worthwhile change ~ 2% [94, 98, 100], which is thought to represent a “real” improvement and not simply a change due to variability of the measure. Taken together, it is therefore likely that the improvements seen in RE following a period of concurrent training would represent a meaningful change in performance.
Improvements were observed in moderately-trained [72, 76, 84, 86], well-trained [33, 36, 73, 75, 79, 80, 88] and highly-trained participants [74, 77], suggesting runners of any training status can benefit from ST. Different modes of ST were utilized in the studies, with RT or HRT [72, 78, 79, 84, 86], ERT [80], PT [75, 76, 80], and a combination of these activities [33, 36, 77], all augmenting RE to a similar extent. Single-joint isometric RT may also provide a benefit if performed at a high frequency (4 day week−1) [84]. Several studies adopted a periodized approach to the types of ST prioritized during each 3- to 6-week cycle [33, 36, 77, 88], which is likely to provide the best strategy to optimize gains long-term [101].
Six studies [32, 81,82,83, 89, 91] failed to show any improvement in RE and a further six [36, 73, 76,77,78, 86] observed both improvements and an absence of change at various velocities. This implies benefits are more likely to occur under specific conditions relating to the choice of exercises, participant characteristics, and velocity used to measure RE. In most studies that observed a benefit, exercises with free weights were utilized [33, 36, 72, 74, 86, 88]. Multi-joint exercises using free weights are likely to provide a superior neuromuscular stimulus compared to machine-based or single-joint exercises as they demand greater levels of co-ordination, multi-planar control, activation of synergistic muscle groups [102, 103] and usually require force to be produced from closed-kinetic chain positions. These types of exercise also have a greater biomechanical similarity to the running action so are therefore likely to provide a greater level of specificity and hence transfer of training effect [104]. An insufficient overload or a lack of movement pattern specificity may therefore be the reason for the absence of an effect in studies that used only resistance machines [32, 81] or a single-joint exercise [82]. These studies were also characterized by a lower frequency of sessions compared to studies that used similar RT exercises but did observe an improvement in RE [78, 84].
Moderately-trained runners were used in three of the six studies showing an absence of effect [81, 83, 91] and one used triathletes who performed a relatively low volume of running (34.8 km week−1) as part of their training [83]. However, a similar number of studies who used recreational athletes did show a positive effect [72, 76, 84, 86], suggesting that training level is unlikely to be the reason for the lack of response in these studies. This is also confirmed by recent observations that showed improvement in RE following a period of concurrent training was similar across individuals irrespective of training status and the number of sessions per week ST was performed [10].
The velocity used to assess RE may also explain the discrepancies in results across studies. It has been suggested that runners are most economical at the speeds they practice at most [98], and for investigations that utilized PT, stretch–shortening cycle improvements are likely to manifest at high running speeds where elastic mechanisms have greatest contribution [83, 105]. Therefore a velocity-specific measurement of RE may be the most valid strategy to establish whether an improvement has occurred. For example, Saunders and associates [77] observed an improvement (p = 0.02, ES: 0.35) at 18 km h−1 in elite runners, but an absence of change at slower speeds. Similarly, Millet and colleagues [74] noted large (ES: > 1.1) improvements at speeds faster than 75% v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) (~ 15 km h−1) in highly-trained triathletes, and Paavolainen et al. [73] detected changes at 15 km h−1 but not slower speeds in well-trained runners. Furthermore, Piacentini and co-workers [86] found improvement at race-pace in recreational marathon runners but not at a slower and a faster velocity. Improvements observed at faster compared to slower speeds may also reflect improvements in motor unit recruitment as a consequence of ST. As running speed increases there is a requirement for greater peak vertical forces due to shorter ground contact times, which elevates metabolic cost [25]. To produce higher forces, yet overcome a reduction in force per motor unit as a consequence of a faster shortening velocity, more motor unit recruitment is required [106]. Thus, an increase in absolute motor unit recruitment following a period of ST would result in a lower relative intensity reducing the necessity to recruit higher threshold motor units during running [25]. Several studies that failed to show any response used a single velocity to assess RE [32, 83, 89], perhaps indicating that the velocity selected was unsuitable to capture an improvement. Furthermore, only a small number of studies used relative speeds [33, 74, 79, 81, 82], with most choosing to assess participants at the same absolute intensity. A given speed for one runner may represent a high relative intensity, whereas for another runner it may be a relatively low intensity. Therefore selecting the same absolute speed in a group heterogeneous with respect to \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\), may not provide a true reflection of any changes which take place following an intervention. Moreover, this may also confound any potential improvements observed in fractional utilization of \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\).
Several common procedural issues exist in the studies reviewed, which may influence the interpretation of results and therefore conclusions drawn. The majority of studies quantified RE and \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) as a ratio to body mass; however, oxygen uptake does not show a linear relationship with increasing body size [107]. It is also known that the relationship between body size and metabolic response varies across intensities, with a trend for an increasing size exponent as individuals move from low-intensity towards maximal exercise [108, 109]. Moreover, allometric scaling is likely to decrease interindividual variability [110], potentially improving the reliability of observations [99]. Ratio-scaling RE for all velocities to body mass is therefore theoretically and statistically inappropriate [111]. Just two studies [79, 80] used an appropriate allometric scaling exponent (0.75) to account for the non-linearity associated with oxygen uptake response to differences in body mass, both establishing a large ES in their results. The unsuitability of ratio-scaling as a normalization technique when processing physiological data is likely to have influenced the statistical outcomes of some studies and thus inaccurate conclusions may have been generated.
Running economy was expressed as oxygen cost in all but three studies [82, 84, 91], which quantified RE using the energy cost method. As the energy yield from the oxidation of carbohydrates and lipids differs, subtle alterations in substrate utilization during exercise can confound measurement of RE when expressed simply as an oxygen uptake value. Energy cost is therefore the more valid [112, 113] and reliable [99] metric for expressing economy, compared to traditional oxygen cost, as metabolic energy expenditure can be calculated using the respiratory exchange ratio, thus accounting for differences in substrate utilization. Despite attempts to control for confounding variables such as diet and lifestyle in most studies, equivalence in inter-trial substrate utilization cannot be guaranteed, which may have impacted upon the measurement of RE.
Maximal Oxygen Uptake
Maximal oxygen uptake is widely regarded as one of the most important factors in distance running success [114], therefore the objective for any distance runner is to maximize their aerobic power [9]. An individual’s \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) is limited by their ability to uptake, transport and utilize oxygen in the mitochondria of working muscles. Endurance training involving prolonged continuous bouts of exercise or high intensity interval training induces adaptations primarily within the cardiovascular and metabolic systems that results in improvements in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) [9, 115]. Conversely, ST is associated with a hypertrophy response that increases body mass and has been reported to decrease capillary density, oxidative enzymes and mitochondrial density [116,117,118], which would adversely impact aerobic performance. Theoretically there is therefore little basis for ST as a strategy to enhance aerobic power. However it is important to address whether in fact \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) is negatively affected when distance running is performed concurrently with ST.
Thirteen works in this review found no change in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) following the intervention period, demonstrating that although ST does not appear to positively influence \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\), it also does not hinder aerobic power. Although ST in most studies was supplementary to running training, it appears that the additional physiological stimulus provided by ST was insufficient to elicit changes in cardiovascular-related parameters [119]. Three studies did observe significant increases in aerobic power that did not differ to the change observed in the control group [33, 81, 91], and one further study found an improvement in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) in the control group only [78]. It is perhaps surprising that more studies did not find an increase in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) (in any group) given that participants continued their normal running training through the study period. Improvements in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) of 5–10% have been shown following relatively short periods (< 6 weeks) of endurance training [9]; however, the magnitude of changes is dependent upon a variety of factors including the initial fitness level of individuals and the duration and nature of the training program [120]. Maximal oxygen uptake is known to have an innate upper limit for each individual, therefore in highly-trained and elite runners, long-term performance improvement is likely to result from enhancement of other physiological determinants, such as RE, fractional utilization and v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) [4, 121, 122]. A number of studies used moderately-trained participants [23, 72, 76, 81, 91], who would be the most likely to show an improvement in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) following a 6- to 14-week period of running, with two investigations demonstrating improvements for both groups [81, 91]. The absence of \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) improvement in other papers suggests that the duration of the study and/or the training stimulus, was insufficient to generate an improvement [120]. Indeed, one study of 40 weeks’ duration in Collegiate level runners observed similar improvements (ES: 0.5–0.6) in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) in both groups [33], suggesting a longer time period may be required to detect changes in runners with a higher training status. High-intensity aerobic training (> 80% \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\)) is a potent stimulus for driving changes in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\)[123]; however, some studies reported runners predominantly utilized low-intensity (< 70% \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\)) continuous running [74, 78, 89], which may also explain the lack of changes observed.
Velocity Associated with \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\)
An individual’s v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) is influenced by their \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\), RE and anaerobic factors including neuromuscular capacity [4, 124]. The amalgamation of several physiological qualities into this single determinant appears to more accurately differentiate performance, particularly in well-trained runners [3, 98, 125, 126], therefore v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) has been labelled as an important endurance-specific measure of muscular power [127].
Improvements for v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) (3–4%, ES: 0.42–0.49) were found in two investigations [80, 89], with a further two studies observing improvements (2.6–4.0%, ES: 0.57–0.9) that could not be ascribed to the training differences between the groups [33, 74]. A number of studies also found little change in v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) following an intervention [31, 32, 36, 78, 85]. As v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) is the product of the interaction between aerobic and anaerobic variables, a small improvement in one area of physiology may not necessarily result in an increase in v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\). Damasceno et al. [89] found an improvement in v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) (2.9%, p < 0.05, ES: 0.42) despite detecting no change in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\), RE or Wingate performance, therefore attributed the change to the large improvements (23%, ES: 1.41) in the force-producing ability they observed in participants. Conversely, Berryman and associates [80] found changes in v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) (4.2%, ES: 0.43–0.49) alongside improvements in RE (4–7%, ES: 1.01), moderate increases in power output, and no change in \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) scores. Beattie and co-workers [33] credited the change in v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) they observed (20-weeks: 3.5%, ES: 0.7) to the accumulation of improvements in RE, \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) and anaerobic factors; however, these were not sufficiently large enough to provide a significant group × time interaction. Millet and colleagues [74] found notable improvements in RE (7.4%, ES: 1.14); however, changes in RE could not explain the changes observed in v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) (r = − 0.46, p = 0.09). It may also be the case that longer periods of ST are required before an improvement in v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) is detected, as studies showing an improvement (2.6–4.0%, ES: 0.57–0.9) from baseline lasted 14 weeks or more [33, 74], and studies showing little change tended to be 6–8 weeks in duration [31, 78, 85].
The conflicting results could also be explained by the inconsistency in methods used to define v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\). A number of different protocols and predictive methods have been suggested to assess v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) [4], including determination from the \(\dot{V}{\text{O}}_{2}\)-velocity relationship [128] and the peak running speed attained during a maximal test using speed increments to achieve exhaustion [21, 127]. All studies that measured v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) in this review did so via an incremental run to exhaustion progressed using velocity. Velocity at \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) was taken as the highest speed that could be maintained for a full 60-s stage [78, 80, 85], an average of the final 30-s [31, 36], the mean velocity in the final 120-s [32], or the minimum velocity that elicited \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) [33, 74]. Although a direct approach to the measurement of v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) has been recommended [4], due to the velocity increments (0.5–1.0 km h−1) used in these investigations, this may not provide sufficient sensitivity to detect a change following a short- to medium-term intervention. Damasceno and associates [89] calculated v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) using a more precise method based upon the fractional time participants reached through the final stage of the test multiplied by the increment rate. This perhaps provided a greater level of accuracy which allowed the authors to identify the differences in changes which existed between the groups. Taken together, there is weak evidence that v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) can be improved following an ST intervention, despite constituent physiological qualities often exhibiting change. Differences in the protocols used to determine v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) makes comparison problematic; however, a more precise measurement of v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) that accounts for partial completion of a final stage is likely to provide the sensitivity to identify subtle changes that may occur.
The critical velocity model, which represents exercise tolerance in the severe intensity domain, potentially offers an alternative to measurement of v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) that is currently uninvestigated in runners [35, 129]. Two main parameters can be assessed using the critical velocity model; critical velocity itself, which is defined as the lower boundary of the severe intensity domain which when maintained to exhaustion leads to attainment of \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\), and the curvature constant of the velocity–time hyperbola above critical velocity, which is represented by the total distance that can be covered prior to exhaustion at a constant velocity [130]. Middle-distance running performance (800 m) is strongly related to critical velocity models (r = 0.83–0.94) in trained runners [131], and may be more important than RE in well-trained runners [35]. Evidence from studies using untrained participants has demonstrated that the total amount of work that can be performed above critical power during high-intensity cycling exercise is improved (35–60%) following 6–8 weeks of RT [132, 133]. Future investigations should therefore address the dearth in literature around how ST might positively influence parameters related to the critical velocity model [35].
Blood Lactate Markers
A runner’s velocity at a reference point on the lactate-velocity curve (e.g., LT) or BL for a given running speed are important predictors of distance running performance [134,135,136]. A runners LT also corresponds to the fractional utilization of \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) that can be sustained for a given distance [114], therefore an increase in LT also allows a greater proportion of aerobic capacity to be accessed.
In contrast to RE, ST appears to have little impact upon BL markers. This is quite surprising as an improvement in RE should theoretically result in an enhancement in speed for a fixed BL concentration. This suggests that adaptations to RE can occur independently to changes in metabolic markers of performance. An absence of change in BL also implies that ST does not alter anaerobic energy contribution during running, thus assuming aerobic energy cost of running is reduced following ST, it can be inferred that total energy cost (aerobic plus anaerobic energy) is also likely to be reduced. Previous studies have shown as little as 6 weeks of endurance training can improve BL levels or the velocity corresponding to an arbitrary BL value in runners [137,138,139]. The intensity of training is important to elicit improvement in BL parameters [140], therefore it appears that the running training prescription may have been insufficient to stimulate improvements, or the training status of participants meant a longer period was required to realize a meaningful change. In addition, the inter-session reliability of BL measurement between 2–4 mmol L−1 is ~ 0.2 mmol L−1 [99], therefore over a short study duration this metric may not provide sufficient sensitivity to detect change.
Training at an intensity above the LT is likely to result in a reduction in the rate of BL production (and therefore accumulation), or an improved lactate clearance ability from the blood [9]. Short duration high-intensity bouts of activity generate high levels of BL so drive metabolic adaptations which can result in an improvement in performance [141,142,143]. Studies that have utilized high-repetition, low-load RT in endurance athletes therefore have the potential to produce high BL concentrations so may provide an additional stimulus to improve performance via BL parameters. This theory is supported by works that have demonstrated improvements in BL-related variables in endurance athletes following an intervention that uses a strength-endurance style of conditioning with limited rest between sets [54, 62, 144]. The ST prescription in the studies reviewed was predominantly low-repetition, high-intensity RT or PT, which is unlikely to have provided a metabolic environment sufficient to directly enhance adaptations related to BL markers.
Time-Trial Performance
Physiological parameters such as \(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\), v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\), RE and LT are clearly important determinants that can be quantified in a laboratory; however, for a runner, TT performance possesses a far higher degree of external validity. Similar improvements in TT performance were observed for middle-distance events (3–5%, ES: 0.4–1.0) and long-distance events up to 10 km (2–4%, ES: 1.06–1.5). In the majority of these studies, time trials took place in a similar environment and under comparable conditions to a race, therefore these findings have genuine applicability to “real-life” scenarios. These improvements are likely to be a consequence of significant enhancements in one or more determinants of performance. Interestingly, Damasceno and co-authors [89] found an improvement in 10 km TT performance due to the attainment of higher speeds in the final 3 km, despite observing no change in RE during a separate assessment. This suggests that greater levels of muscular strength may result in lower levels of relative force production per stride, thereby delaying recruitment of higher threshold muscle fibers and thus providing a fatigue resistant effect [145]. This subsequently manifests in a superior performance during the latter stages of long-distance events [89].
Four studies observed no difference in performance change compared to a control group [38, 75, 80, 90, 92]. Vikmoen and colleagues [38] attributed a lack of effect in their 40 min TT to the slow running velocity caused by the 5.3% treadmill inclination used in the test. This was also the only study to use a treadmill set to a pre-determined velocity which participants could control once the test had commenced. The absence of natural self-pacing may therefore have prevented participants achieving their true potential on the test. Spurrs et al. [75] and Berryman et al. [80] both found improvements in 3 km performance compared to a pre-training measure of a comparable magnitude to other studies (2.7–4.8%, ES: 0.13–0.46); however, changes were not significantly different to a control group, suggesting ST provided no additional benefit or there was a practice effect associated with the test.
It could be possible that enhancement of physiological qualities in some studies could be attributed to RT being positioned immediately after low-intensity, non-depleting running sessions [146]. This arrangement of activities in concurrent training programs has been shown to provide a superior stimulus for endurance adaptation compared to performing separate sessions, and without compromising the signaling response regulating strength gains [147, 148]. This, however, appears not to be the case, as most studies reported ST activities took place on different days to running sessions [85, 88, 89] or were at least performed as separate sessions within the same day [33, 36, 38, 72, 75, 78]. Only three studies performed ST and running immediately after one another, with one positioning PT before running [87] and one lacking clarity on sequencing [76]. Schumann and colleagues [90, 92] observed no additional benefit to both strength and endurance outcomes compared to a running only group, when ST was performed immediately following an incremental running session (65–85% maximal heart rate), citing residual fatigue which compromised quality of ST sessions as the reason.
Anaerobic Running Performance
The contribution of anaerobic factors to distance running performance is well established [127, 149]. In particular, anaerobic capacity and neuromuscular capabilities are thought to play a large role in discriminating performance in runners who are closely matched from an aerobic perspective [124, 150]. An individual’s v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) perhaps provides the most functional representation of neuromuscular power in distance runners; however, measures of maximal running velocity and anaerobic capacity are also potentially important [127].
Tests for pure maximal sprinting velocity (20–30 m) were used in three studies [73, 78, 87] and showed improvements (1.1–3.4%) following ST in every case. This confirms results from previous studies that have shown sprinting performance can be positively affected by an ST intervention in shorter-distance specialists [151,152,153]. This finding has important implications for distance runners, as competitive events often involve mid-race surges and outcomes are frequently determined in sprint-finishes, particularly at an elite level [154,155,156,157]. Middle-distance runners also benefit from an ability to produce fast running speeds at the start of races [158], therefore improving maximum speed allows for a greater “anaerobic speed reserve” [159], resulting in a lower relative work-rate, and thus decreasing anaerobic energy contribution [41]. Interestingly, endurance training in cyclists has been shown to improve critical power [160] but reduce work capacity for short duration exercise [161, 162]. It is unknown whether long-term aerobic training has a similar effect on anaerobic running qualities; however, ST offers a strategy to avoid this potential negative consequence.
The velocity attained during a maximal anaerobic running test provides an indirect measure of anaerobic and neuromuscular performance, and has a strong relationship (r = 0.85) to v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) [19]. The vMART is particularly relevant to middle-distance runners because it requires athletes to produce fast running speeds under high-levels of fatigue caused by the acidosis and metabolites derived from glycolysis [163]. Both studies that included this test observed significant improvements in vMART (1.1–3.4%), which can be attributed to changes observed in neuromuscular power as a result of the ST intervention [73, 78]. One study showed no alteration in the predicted distance achieved on an anaerobic running test following 6 weeks of HRT; however, the validity and reliability of the test was questioned by the authors [31]. Performance on a 30 s Wingate test was also unchanged following 8 weeks of running training combined with HRT in recreational participants [89]. This finding perhaps underlines the importance of selecting tests which are specific to the training which has been performed in the investigation.
Strength Outcomes
Changes in strength outcomes were evident in most studies despite all but one [78] observing no change in body mass. Since strength changes can be ascribed to both neurological and morphological adaptations [164], it is therefore likely that improvements are primarily underpinned by alterations in intra- and inter-muscular co-ordination. It is also known that initial gains in strength in non-strength trained individuals are the consequence of neural adaptations rather than structural changes [118]. An improvement in force producing capability is perhaps expected in individuals who have little or no strength-training experience [165]; however, concurrent regimens of training have consistently been shown to attenuate strength-related adaptation [30].
The seminal paper published by Hickson et al. [48] was the first to identify the potential for endurance exercise to mitigate strength gains, when both training modalities were performed concurrently within the same program. Follow-up investigations have since shown mixed results [166,167,168,169,170,171], but evidence from this review clearly demonstrates that, for the distance runner at least, strength-related improvements are certainly possible following a concurrent period of training. Nevertheless, the study designs adopted by the works under review did not include a strength-only training group, thus it is not possible to determine whether strength adaptation was in fact negated under a concurrent regimen. One study using well-trained endurance cyclists with no ST experience, observed a blunted strength response in a group who added ST to their endurance training compared to a group who only performed ST [170]. Based upon this finding and other similar observations [167, 172, 173] it seems likely that although distance runners can significantly improve their strength using a concurrent approach to training, strength outcomes are unlikely to be maximized. Moreover, the degree of interference with strength-adaptation also appears to be exacerbated when volumes of endurance training are increased and the duration of concurrent training programs is longer [30, 146].
Body Composition
Resistance training performed 2–3 times per week is associated with increases in muscle cross-sectional area as a principal adaptation [174]. Although gains in gross body mass may appear to be an unfavorable outcome for distance runners, the addition of muscle mass to proximal regions of the lower limb (i.e., gluteal muscles) should theoretically provide an advantage, via increases in hip extension forces, minimizing moment of inertia of the swinging limb, and reducing absolute energy usage [25]. It is somewhat surprising that virtually all studies demonstrated an absence of change in body mass, fat-free mass, lean muscle mass, and limb girths. Other than one investigation [33], the duration of the studies that observed no effect on measures of body composition was < 14 weeks, suggesting this may not have been sufficiently long to demonstrate a clear hypertrophic response. There is also a possibility that small increases in muscle mass within specific muscle groups (e.g., gluteals) were present, and contributed to the improvements observed in RE, but these may not have been detectable using a gross measure of mass. Evidence for this may have occurred in the Schumann et al. study [90, 92], who observed increases in total lean mass (3%) despite noting no significant change in body mass or cross-sectional area of the vastus lateralis compared to baseline measures.
The interference effect observed during concomitant integration of endurance and ST as part of the same program may also provide an explanation for the lack of change in measures of mass. Following a bout of exercise, a number of primary and secondary signaling messengers are up regulated for 3–12 h [175], which initiate a series of molecular events that serve to activate or suppress specific genes. The signaling messengers which are activated, relate to the specific stress which is imposed on the physiological systems involved in an exercise bout. Strength training causes mechanical perturbation to the muscle cell, which elicits a multitude of signaling pathways that lead to a hypertrophic response [176]. In particular, the secretion of insulin-like growth factor-1 as a result of intense muscular contraction is likely to cause a cascade of signaling events which increase activity of phosphoinositide-3-dependent kinase (Pl-3 k) and the mammalian target of Rapamycin (mTOR) [177,178,179]. There is strong evidence that mTOR is responsible for mediating skeletal muscle hypertrophy via activation of ribosome proteins which up regulate protein synthesis [180]. Prolonged exercise bouts, such as those associated with endurance training, activate metabolic signals related to energy depletion, uptake and release of calcium ions from the sarcoplasmic reticulum and oxidative stress in cells [181]. Adenosine monophosphate activated kinase (AMPK) is a potent secondary messenger which functions to monitor energy homeostasis [182] and when activated, modulates the release of peroxisome proliferator co-activator-1α, which along with calcium-calmodulin-dependent kinases increase mitochondrial function to enhance aerobic function [181, 183, 184]. Crucially though, AMPK also acts to inhibit the Pl-3 k/mTOR stage of the pathway via activation of the tuberous sclerosis complex thereby suppressing the ST induced up regulation of protein synthesis [185, 186]. This conflict arising at a molecular signaling level therefore appears to impair the muscle fiber hypertrophy response to ST and attenuate increases in body mass [186].
Muscle–Tendon Interaction Mechanisms
The potential mechanisms for the positive changes observed in physiological parameters underpinning running performance were directly investigated in three studies [82, 84, 91], and were inferred from gait measures [36, 73,74,75, 77] and strength outcomes in others. It is well documented that muscle–tendon unit stiffness correlates well with RE [187,188,189]. Tendons are also highly adaptable to mechanical loading and have been shown to increase in stiffness in response to HRT and PT [84, 190, 191]. Despite observing no statistical effect for HRT on RE, Fletcher and colleagues [82] also found a relationship between the change in RE and the changes observed in Achilles tendon stiffness. Despite these associations, it is likely that improvements in RE are a consequence of the interaction between adaptations to tendon properties and improvements in motor unit activation which influence behavior of force–length-velocity properties of muscles [25]. It tends to be assumed that improved tendon stiffness allows the body to store and return elastic energy more effectively, which results in a reduction in muscle energy cost due to a greater contribution from the elastic recoil properties of tendons [192]. Indeed, authors of studies in the present review have argued that the improvements observed in RE following a period of ST are due to an enhanced utilization of elastic energy during running [36, 73,74,75]. An alternative proposal, based upon more recent evidence, suggests the Achilles tendon provides a very small contribution to the total energy cost of running therefore improvements in stiffness provide a negligible reduction in energy cost [193, 194]. Instead, a tendon with an optimal stiffness contributes to reducing RE by minimizing the magnitude and velocity of muscle shortening, thus allowing muscle fascicles to optimize their length and remain closer to an isometric state [25]. A reduction in the amount and velocity of fiber shortening therefore reduces the level of muscle activation required and hence the energy cost of running [193].
The improvements observed in maximal and explosive strength, which can be attributed to increases in motor unit recruitment and firing frequency, enable the lower limb to resist eccentric forces during the early part of ground contact [165] and thus contribute to the attainment of a near isometric state during stance. As the force required to sustain speed during distance running performance is submaximal, the level of motor unit activation needed can be minimized when fascicles contract isometrically [25]. This enables the Achilles tendon in particular to accommodate a greater proportion of the muscle–tendon unit length change during running thereby reducing metabolic cost [194]. Variables which provide an indirect measure of the neuromuscular systems ability to produce force rapidly and utilize tendon stiffness were found to improve in other studies that showed improvements in running performance and/or key determinants [73, 74, 78,79,80, 87]. However, some studies found improvements in running-related parameters despite observing no alterations in jump performance [33, 76,77,78, 91], rate of force development [36, 75, 77], or stiffness [33, 74, 89] illustrating that measures were insufficiently sensitive to detect change, or a combination of mechanisms is likely to be contributing towards the enhancements observed.
Heavy RT causes a shift in muscle fiber phenotype, from the less efficient myosin heavy chain (MHC) IIx to more oxidative MHC IIa, [195, 196]. A higher proportion of MHC IIa has been shown to relate to better running economy [91, 197, 198]; however, whether changes to MHC properties as a result of ST contribute to an improvement in RE and performance remains to be determined. One previous study provided evidence that 4 weeks of sprint running (30-s bouts) improve RE and also the percentage of MHC IIx [199]; however, the absence of endurance training may partly explain the shift in phenotype. Over a longer period (6 weeks), Pellegrino and co-workers [91] found no measurable changes in MHC isoforms following a PT intervention despite a significant improvement in 3 km TT performance, suggesting that a contribution from this mechanism is unlikely for distance running.
It could also be speculated that improvements in RE due to improved strength might have resulted in subtle changes to running kinematics, thus enabling participants to perform less work for a given submaximal speed [72]. There is currently little direct support for this conjecture; however, previous work has shown that running technique is an important component of RE [200, 201], and improving hip strength can reduce undesirable frontal and transverse plane motion in the lower limb during running [202]. One study in this review did observe a reduction in EMG amplitude in the superficial musculature of the lower limb following ST; however, this wasn’t accompanied by an improvement in RE [83]. This suggests that favorable adaptations in neuromuscular control do not necessarily translate to reducing the metabolic cost of running. Additionally, two studies showed significant increases (3.0–4.4%) in ground contact time during submaximal running after an ST intervention [36, 81]; however, only Giovanelli and colleagues [36] found a corresponding improvement in RE. Several papers have demonstrated an inverse relationship between RE and ground contact times [201, 203, 204], since a lower peak vertical force is required to generate the same amount of impulse during longer compared to short ground contacts [25]. Although there is currently minimal evidence to suggest an ST intervention increases ground contact time during sub-maximal running, this mechanism may in part explain the improvements in RE.
Strength-Training Prescription
Modality and Exercise Selection
The works included in this review used a variety of ST modalities; however, the most effective type of training is currently difficult to discern. Adaptations are specific to the demands placed upon the body, therefore it would be expected that HRT, ERT and PT produce somewhat different outcomes [205]. This can be observed in the study by Berryman and co-workers [80], who observed larger improvements in explosive concentric power in a group following an ERT program compared to a group who used PT. The opposite result occurred for the counter-movement jump, which places a greater reliance on a plyometric action; the PT group displayed greater improvements than the ERT group [80]. Heavy RT, which is characterized by slow velocities of movement, is likely to improve agonist muscle activation via enhanced recruitment of the motor neuron pool, whereas ERT, which involves lighter loads being moved rapidly, tends to enhance firing frequency and hence improve rate of force development [164, 165]. Plyometric training develops properties related to the stretch–shortening cycle function [206], and uses movements patterns which closely mimic the running action (e.g., hopping and skipping). It is therefore likely that although a variety of ST methods are capable of improving physiological parameters relating to distance running performance, the mechanisms underpinning the response may differ.
In less strength-trained individuals, such as those used in the studies reviewed, any novel ST stimulus is likely to provide a sufficient overload to the neuromuscular system to induce an adaptation in the short term [207]. This is perhaps why ST is effective even in highly-trained distance runners [74, 77, 87]. Studies that have attempted to compare ST techniques in distance runners have generally shown HRT to be superior to ERT or a mixed methods approach at improving aerobic parameters [57, 63] and maximal anaerobic running speed [62]. Plyometric training has also shown superiority to ERT for improvement of RE in moderately trained runners [80]. Other investigations have found no differences in the physiological changes between groups using HRT, ERT or a mixture of modalities [62, 65]. A number of studies have also shown HRT and/or ERT to be more beneficial to a muscular endurance style of ST [59, 64, 65, 67, 86]. The addition of whole body vibration to RT also provides no extra benefit [85]. Although ERT and PT may have more appeal compared to HRT due to their higher-level of biomechanical similarity to running, an initial period of HRT is likely to provide an advantage long-term in terms of reducing injury risk [208] and eliciting a more pronounced training effect [209]. Taken together, it seems that long-term, a mixed modality approach to ST is most effective, as this provides the variety and continual overload required to ensure the neuromuscular system is constantly challenged. One study that used a longer intervention period lends support to this notion, as significant improvements were observed in strength and physiological measures after 20 and 40 weeks with a periodized methodology that used several types of ST [33]. Further research is required to ascertain the long-term benefits of various ST modalities and the relative merits of different approaches to sequencing and progressing these modalities.
As discussed in Sect. 4.1, the exercises selected in an ST program can potentially influence the magnitude of neuromuscular adaptation and thus the impact on physiological determinants of performance. Exercises using free weights, which require force to be generated from the leg extensor muscles in a close-kinetic chain position, are the most likely to positively transfer to running performance [210]. Examples of RT exercises commonly used include: barbell squat, deadlifts, step-ups and lunging movement patterns [31, 33, 36, 72, 79, 85, 88]. Isometric HRT may also have value for the plantarflexors [84]. Explosive RT, by its very nature, should avoid a deceleration phase, therefore exercises such as squat jumps and Olympic weightlifting derivatives should be utilized [33, 80]. To maximize transfer to distance running performance, particularly at faster speeds, PT exercises should exhibit short ground contact times (< 0.2 s) [36, 72], which approximates the contact times observed in competitive middle- [211] and long-distance running [212], and encourages a rapid excitation–contraction coupling sequence and improved musculotendinous stiffness [36, 73,74,75]. Exercises which possess a low to moderate eccentric demand such as depth jumps (from a 20–30 cm box), skipping, hopping, speed bounding appear most suitable [33, 73, 75, 77, 80, 83].
Intra-Session Variables
For non-strength trained individuals, exercise prescription and gradual progression is important to avoid injury and overtraining [213]. Most studies initially used 1–2 sets and progressed to 3–6 sets over the course of the intervention period for HRT, ERT and PT, which appears appropriate to circumvent these risks. Several studies utilized a low (3–5) repetition range in every HRT session [31, 79, 81, 86] at loads which approached maximum (≥ 80% 1RM or repetition failure), but did not observe superior benefits compared to investigations that prescribed RT at moderate loads (60–80% 1RM) and higher repetition ranges (5–15 repetitions). Sets were performed to RM in a number of studies [32, 38, 72, 79, 81, 88, 89], which was likely employed as a means of standardizing the intensity of each set in the absence of 1RM data for participants. Performing sets which leads to repetition failure induces a high level of metabolic and neuromuscular fatigue, which may delay recovery [214]. Although training to repetition failure may be more important than the load lifted for inducing a hypertrophy response [215], this is both unfavorable and unnecessary to optimize gains in strength compared to a non-repetition failure strategy [216]. Not working to repetition failure also appears to become a more important feature of RT as ST status increases [216]. Participants were often instructed to move the weights as rapidly as possible when performing the concentric phase of RT exercises, which increases the likelihood of maximizing neuromuscular adaptations [217]. Plyometric training is characterized by high eccentric forces compared to running and RT, therefore repetitions per set were typically low (4–10 repetitions). Total foot contacts progressed from 30 to 60 repetitions in the first week of an intervention up to 110–228 repetitions after 6–9 weeks [73, 75, 76, 91]. Plyometric exercises were all performed without additional external resistance in all but one study [73] and in many cases a short ground contact time [76, 77, 83] and maximal height [80, 83] were cued to amplify the intensity. An inter-set recovery period of 2–3 min was typical for HRT, ERT and PT, which is in line with recommendations for these training techniques [213]. Where SpT was incorporated into ST programs, repetition distances were short (20–150 m) and performed at or close to maximal running speed [73, 74, 88].
Inter-Session Variables
The majority of studies that demonstrated improvements in running physiology scheduled ST 2–3 times per week, which is in line with the guidelines for non-strength trained individuals [213]. One study used just one session per week (ERT or PT) and achieved moderate improvements in strength outcomes and RE after 8 weeks of training [80]. Beattie and associates [33] observed small improvements (ES: 0.3) in RE using a single ST session (mixed activities) each week for 20 weeks; however, the participants had already experienced moderate improvement (ES: 1.0) in this parameter using a twice weekly program in the 20 weeks prior. For well-trained runners who complete 8–13 running sessions per week [73, 77], it would be useful to establish the minimal ST dosage required to elicit a beneficial effect to reduce the risk of overtraining. Equally, for the recreational runner, ST may take up valuable leisure time that could be spent running, therefore identifying the optimal volume and frequency of ST to achieve an improvement in performance would be desirable. A previous meta-analysis indicated that two or three sessions per week provides a large effect on strength, but for the non-strength trained individual, three sessions is superior to two sessions per week [218]. More recently, a weak relationship was established between improvement in RE and weekly frequency of ST sessions in 311 endurance runners [10]. This suggests that higher weekly volumes of ST would not necessarily provide greater RE improvements, therefore two sessions per week is likely to be sufficient [10].
Given the volume of endurance training participants were exposed to and the duration of each study, it seems likely that an attenuation of strength-related adaptation would have occurred. To minimize this interference phenomenon, it is therefore recommended that a recovery period of > 3 h is provided following high-intensity running training before ST takes place [146]. In many studies running training and ST took place on different days [33, 36, 85, 88, 89], and several papers noted a gap of > 3 h between running and ST on the same day [32, 38, 72, 78, 79]. This feature of concurrent training prescription therefore appears important in ensuring sufficient strength-adaptations are realized but without compromising running training. Although there is very little evidence that the dosage of ST prescribed impaired any endurance-related adaptations, recent work has highlighted that acute bouts of RT may cause fatigue sufficient to impair subsequent running performance, which long term may result in sub-optimal adaptation [219]. It is therefore recommended that this potential fatigue is accounted for by allowing at least 24 h recovery between an ST session and an intensive running session [33, 85, 88, 89].
The results provide compelling evidence that a relatively short period (6 weeks) of ST can enhance physiological qualities related to distance running performance. Improvements in RE [57] and 10 km TT performance [88] have also been shown in as little as 4 weeks. A relationship between intervention duration and improvement in RE has previously been reported [10], suggesting that longer periods of ST provide a larger benefit. The same may be true for v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\); however, more research using longer periods of ST is required to establish if this is indeed the case. The benefits to performance also seem to be dependent on study duration as most short interventions (6 weeks) tended to produce small TT improvements (2.4–2.7%, ES: 0.13–0.4) [75, 87, 91], whereas longer programs (8–11 weeks) resulted in moderate or large performance effects (3.1–5.5%, ES: 0.67–1.50) [32, 73, 88]. It would seem reasonable to assume that highly-trained distance runners would require a higher volume of ST to achieve the same benefit as less experienced runners; however, this does not appear to be the case. Relatively short (6–9 weeks) periods of ST improved RE and TT performance to a similar extent in highly-trained individuals [77, 87] and recreational runners [76, 86, 91]. It is therefore recommended that future investigations use periods of 10 weeks or longer to provide further insight into how ST modalities may impact physiological parameters long-term in different types of distance runner.
The time of year or phase of training when the research was conducted was not reported in the majority of studies. Several papers indicated that the intervention formed part of an off-season preparation period [73, 74, 78, 82, 86], but others scheduled the intervention within the competition period [32, 38, 87]. Based upon the literature reviewed, it is currently not possible to provide specific recommendations for ST in different phases of a runners training macrocycle, as most studies found at least some physiological or performance benefits to concurrent training. Importantly though, evidence suggests that choosing to exclude ST following a successful intervention period results in a detraining effect which causes improvements to return to baseline levels within 6 weeks [31]. The 40-week intervention conducted by Beattie and colleagues [33] provides evidence that reducing ST volume from two sessions per week (both with a lower limb HRT emphasis) during the preparatory phase to one weekly session (ERT and PT emphasis) during the in-season racing period is sufficient to at least maintain previous strength and physiological gains. This finding corroborates with a maintenance effect observed in cyclists [220, 221] and soccer players [222] showing one ST session per week is sufficient to preserve the strength qualities developed during a preceding phase of training. Therefore, runners can decrease ST volume from 2–3 sessions per week (each with a lower limb focus) in preparatory phases of training to a single session each week during the competitive season without fearing a loss of adaptation as a consequence of the reduction in training density.
It is currently uncertain what volume and intensity of running and ST are most likely to avoid the interference effect associated with concurrent training practices. One option to minimize attenuation of strength development is to organize activities into periods that concentrate on developing either strength or endurance adaptation [223]. This polarized approach to planning seems unnecessary and counterintuitive for distance runners who generally possess little ST experience, therefore require a minimal stimulus to create an adaptation. Indeed, studies that replaced running training with ST [73, 78, 88] found no greater benefit than those which included ST in a supplementary manner.
Training Supervision
In most studies, the ST routine was supervised and tightly monitored; however, similar controls were often absent for the running training participants performed. It seems reasonable to assume that any errors in participants training logbooks would be similar across intervention and control groups; however, validity of findings would be improved if the running component of training had been more tightly defined. Where supervision of the ST exercises was not included [76] or only included for the first 2 weeks [36], strength measures did not improve following the intervention period. This indicates that a suitably qualified coach is an important feature of an ST programme for a distance runner who lacks ST experience.
Limitations
In addition to the limitations already highlighted in this review, there are other weaknesses that should be acknowledged. For many of the studies reviewed, calculation of an ES was possible for the variables measured, which provides insight into the meaningfulness and substantiveness of results. However, despite the qualitative nature of this review, interpretation of findings was predominantly based upon reported probability values, which can be misleading due to low sample sizes and the heterogeneity in the pool of participants studied. A relatively large number of studies have been included in this review; however, several parameters (e.g., v\(\dot{V}{\text{O}}_{{2{ \hbox{max} }}}\) and BL) were measured in only a small number of studies, which increases the possibility that false conclusions may be drawn.
There was also a lack of detail concerning several important confounding variables in studies, such as the nature of running training prescription and participant’s previous experience in ST. All but seven studies [31, 73, 74, 76, 84, 86, 90, 92] identified that participants had not been engaged in a program of ST for at least 3 months prior to the study commencing. Although it is perhaps unlikely that participants in these seven studies were strength-trained, this cannot be discounted and may therefore have influenced findings in these investigations.