1. bookVolume 78 (2021): Issue 1 (March 2021)
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13 Jan 2009
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access type Open Access

Post-Activation Potentiation in Strength Training: A Systematic Review of the Scientific Literature

Published Online: 31 Mar 2021
Page range: 141 - 150
Journal Details
License
Format
Journal
First Published
13 Jan 2009
Publication timeframe
5 times per year
Languages
English
Abstract

This review aimed to determine the ideal combination of post activation potentiation (PAP) strategies for an improved strength performance. After analysing 202 articles, 15 studies met the inclusion criteria. The findings of this review suggest that a potentiation effect exists as long as a minimum intensity and enough rest are provided. Although intensities of 65% 1RM are sufficient to elicit a potentiation effect, higher effects can be achieved with 85 - 90% 1RM intensities. Similarly, we found that experienced athletes will benefit more from a higher volume bout (1-3 sets), as long as 7-8 minutes of rest are allowed to avoid fatigue.

Key words

Introduction

During the last few years post-activation potentiation (PAP) has been used to acutely improve power output and muscular function (Maloney et al., 2014). PAP is commonly used during the warm-up through complex training, which refers to a training method where heavy resistance exercises are used prior to a biomechanically similar ballistic movement (Poulos et al., 2018).

PAP acts through skeletal muscle contractile history, where the muscle is preactivated with a higher load using a conditioning activity before performing a training session or a competition. Two mechanisms have been suggested: (i) the phosphorylation of myosin regulatory light chains and (ii) improved -motoneuron excitability (Gołas et al., 2016). Additionally, according to the vector theory (Morin et al., 2010), biomechanical similarities between the conditioning and the effective activity (the competition, training bout or test) play a crucial role in potentiation. Four main variables are thought to act over the conditioning activity: (i) intensity to activate the working mechanisms (Gołas et al., 2016), (ii) volume, which is inversely proportional to intensity, (iii) resting time, which is directly conditioned by intensity and volume (Kilduff et al., 2008), and (iv) movement similarity (Dello Iacono et al., 2018).

To date, very different protocols have been used trying to achieve optimal potentiation with opposing results (Dello Iacono et al., 2018; Gołas et al., 2017; Kobal et al., 2019). Thus, the aim of this review was to compare different protocols and to clarify the importance of the aforementioned variables on the conditioning activity. We hypothesized that the volume load would be the main conditioning factor to achieve an optimal potentiation, followed by intensity.

Methods
Experimental Approach to the Problem

A literature search was conducted on October 23, 2020. The following databases were searched: PubMed and Scopus. The previously named databases were searched from inception to October 2020, with language limitations: only peer reviewed articles in English were selected. Citations from scientific conferences were excluded.

Literature Search

In the database, the title and abstracts were searched. The following MeSH terms and key words, combined with the Boolean operators (AND, OR), were used: “athletic performance”, “resistance training”, “post activation potentiation”, “PPA”, “PAP”, “post-activation potentiation”, “potentiation post activation”, “potentiation post-activation”, “performance”, “strength performance”, “strength training”, “strength” and “powerlifting”. No additional filters or search limitations were used.

Inclusion Criteria

Studies were eligible for further analysis if the following inclusion criteria were met; a) subjects´ age ranged between 18-30 years; b) studies analysed experienced lifters; c) postactivation potentiation was studied in sports with high requirements of the rate of force development; d) the potentiation protocol was conducted with barbell exercises; e) pre- and postevaluation was done with a resistance exercise, vertical jump or similar (i.e. squat jump, counter movement jump or drop jump). In the studies where volume was not directly reported, it was calculated as follows: volume = sets x repetitions x kilograms.

Quality assessment

Oxford’s level of evidence (OCEBM Levels of Evidence Working Group, 2011) and the Physiotherapy Evidence Database (PEDro) scale (Maher et al., 2003; de Morton, 2009) were used in order to assess the methodological quality of the studies included in the review. Oxford’s level of evidence ranges from 1a to 5, with 1a being systematic reviews of high-quality randomized controlled trials (RCT) and 5 being expert opinions. The PEDro scale consists of 11 different items related to the scientific rigor. Given that assessors are rarely blinded and that blinding participants is almost impossible, items 5-7 (which are specific to blinding) were removed from the scale (Baz-Valle et al., 2018). With the removal of these items, the maximum result on the modified PEDro scale was 7 (the first item is not included in the final score) and the lowest, 0. Zero points are awarded to a study that fails to satisfy any of the included items and 7 points to a study that satisfies all the included items.

Results
Studies Selected

The search strategy yielded 202 total citations as presented in Figure 1. From those 202 articles, 17 met the inclusion criteria. Excluded studies had at least one of the following characteristics: the potentiation protocol included strategies different from resistance training (e.g. electrostimulation or vibration), participants were not experienced lifters (had less than 2 years of resistance training experience or less than 2 x bodyweight squat 1-RM) or the evaluation protocol was done with sprinting bouts (Table 1).

Figure 1

Flow chart of search strategy and selection of articles.

Physiotherapy Evidence Database (PEDro) ratings and Oxford evidence levels of the included studies.

Study12345678TotalEvidence level
Andrews et al. (2016)Yes111111171b
Comyns et al. (2007)Yes111111171b
Dello Iacono et al. (2019)Yes111111171b
Do Carmo et al. (2018)Yes111111172b
Gilbert & Lees (2007)Yes111111171b
Golas et al. (2017)Yes111111152b
Kilduff et al. (2008)Yes001111152b
Kobal et al. (2019)Yes001111152b
Krzysztofik et al. (2020a)Yes111111171b
Krzysztofik et al. (2020b)Yes111111171b
Krzysztofik et al. (2020c)Yes111111171b
Krzysztofik and Wilk (2020)Yes111111171b
Lowery et al. (2012)Yes111111172b
Mina et al. (2019)Yes111011161b
Poulos et al. (2018)Yes111111171b
Reardon et al. (2014)Yes111111172b
Thomas et al. (2015)Yes100111152b

Items in the PEDro scale: 1 = eligibility criteria were specified; 2 = subjects were randomly allocated to groups; 3 = allocation was concealed; 4 = the groups were similar at baseline regarding the most important prognostic indicators; 5 = measures of 1 key outcome were obtained from 85% of subjects initially allocated to groups; 6 = all subjects for whom outcome measures were available received the treatment or control condition as allocated or, where this was not the case, data for at least 1 key outcome were analysed by “intention to treat”; 7 = the results of between-group statistical comparisons are reported for at least 1 key outcome; 8= the study provides both point measures and measures of variability for at least 1 key outcome

Level of Evidence and Quality of the Studies

Ten of the seventeen included studies had a level of evidence 1b (good quality randomized control trials). The 7 remaining studies had a level of evidence of 2b (individual cohort studies). Also, the mean score in the PEDro scale was 6.47 ± 0.87, with values ranging from 5 to 7 (Table 1).

Characteristics of the Participants

Participants were characterized as experienced or well-trained athletes due to their training experience or their one repetition maximum (the maximum amount of weight that a person is able to lift for one repetition). A summary of participants´ characteristics is presented in Table 2. The total number of participants was 279 (253 men, 6 women and 20 unknown).

Included studies

StudyNumber (M/F)Age (years)RT experience (years)Main Outcome
Andrews et al. (2016)14 (8/6)M 21.3 21.2 ± ± 1.8 0.4 / F≥ 2Unilateral PAP and fatigue
Comyns et al. (2007)12 (12/0)23.3 ± 2.51RM ≥ 2x bodyweightOptimal resistive load and PAP
Dello Iacono (2019) et al.26 (26/0)23.2 ± 5.1≥ 2Traditional sets sets PAP PAP vs cluster
Do Carmo et al. (2018)12 (12/0)25.4 ± 3.6≥ 3PAP rest interval
Gilbert and Lees (2007)15 (15/0)24.3 ±3.3unknownChanges in force development
Golas et al. (2017)16 (16/0)18-35≥ 5Used PAP load magnitude
Kilduff et al. (2008)20 (Unknown)25.4 ± 4.83.1 ± 1.6Recovery time and PAP
Kobal et al. (2019)18 (18/0)25.42 ± 3.583Different volume and PAP
Krzysztofik et al. (2020a)12 (12/0)25.2 ± 2.13PAPE and training volume
Krzysztofik et al. (2020b)32 (32/0)28.4 ± 4.53Eccentric and concentric PAP
Krzysztofik et al. (2020c)13 (13/0)25.7 ±1.96.5 ± 2.2Eccentric PAP
Krzysztofik and Wilk (2020)24 (24/0)24.5 ± 2.66.3 ± 2.5Plyometric PAP protocol
Lowery et al. (2012)13 (13/0)21 ± 33PAP stimuli and recovery time
Mina et al. (2019)15 (15/0)21.7 ± 1.1≥ 5PAP: free resistance weight vs variable
Poulos et al. (2018)15 (15/0)24.3 ± 2.6≥ 2Back Squat intensity and PAP
Reardon (2014)11 (11/0)25.18 ± 3.601RM ≥ 2x bodyweightMuscle architecture and PAP
Thomas et al. (2015)11 (11/0)23 ± 4≥ 2PAP and neuromuscular function

PAP = post activation potentiation; M = male; F = female; RT = resistance training

Studies matching volume load

Five of the included 17 studies matched the volume load in the protocols used. From these five studies, three compared different intensity protocols (Dello Iacono et al., 2019; Lowery et al., 2012; Mina et al., 2019) and two the optimal rest interval (do Carmo et al., 2018; Kilduff et al., 2008).

Mina et al. (2019) performed a study comparing free weight back squats and variable resistance back squats (elastic bands were used to generate the 35% of the total load at the upper part of the squat). Under the free weight condition, no significant changes were found in jump height, peak power or a normalized (to body weight) rate of force development (RFD) compared to pre-intervention performance. On the other hand, under the variable resistance condition, statistically significant increases (p < 0.05) in CMJ height were observed at 30 s (5.9 ± 1.2%), 4 min (5.6 ± 1.8%), 8 min (6.5 ± 2.6%) and 12 min (5.3 ± 2.5%) compared to pre-intervention. In addition, statistically significant increases (p < 0.05) were evident in peak power at 30 s (4.7 ± 1.2%), 4 min (5.9 ± 1.3%), 8 min (4.4 ± 1.7%) and 12 min (4.8 ± 1.7%) time points. These changes in CMJ height and peak power were also significantly different from the free weight condition group (p < 0.05).

Dello Iacono et al. (2019) compared the effect of two protocols using the individualized optimal power load with traditional and clusterset configuration in a randomized cross-over design. Although both protocols increased jump height 4 and 8 min post-intervention, the cluster set configuration reached significantly better results by 1.33 cm (95% CI, 1.02 to 1.65 cm) and 1.64 cm (95% CI, 1.41 to 1.88 cm), respectively. Additionally, cluster set configuration was able to maintain 10% higher power output (95% CI, 8 to 12%) relative to their relative mean propulsive power.

Lowery et al. (2012) studied the effects of three different loads (light, 56% 1RM; medium, 70% 1RM; and heavy, 93% 1RM) on vertical jump height. Vertical jumps after the light load protocol did not reach statistically significant differences. Moderate and high load protocols decreased vertical jump performance right after the conditioning activity (p < 0.05; ESmedium loaded = -2.45, large; ESheavy loaded = -2.87, large). Additionally, a medium loaded protocol reached a significant performance increase at 4 min in the post activation training protocol (p < 0.05; ES = 1.46, large) and a high loaded protocol reached statistically significant improvements at both 4 and 8 min post protocol (p < 0.05; ES4min = 1.34, large; ES8min = 1.48, large).

Kilduff et al. (2008) attempted to set the optimal recovery time for a complex training session. Participants performed 3 sets of 3 repetitions at 87% 1RM back squats before an explosive activity. They reported a statistically significant (p < 0.05) decrease at 15 s post conditioning activity and a statistically significant (p < 0.05) increase at 8 min post conditioning activity for power output and for jump height. A statistically significant (p < 0.05) increase in the RFD 8 min post conditioning activity was also reported. Additionally, Do Carmo et al. (2018) suggested that self-selected rest intervals were better than a fixed rest interval in order to dissipate the fatigue created by the conditioning activity. They conducted a study and no significant changes were observed after the conditioning activity in the fixed rest interval group (38.0 ± 5 cm vs. 37.7 ± 5.1 cm; p = 0.4; ES = 0.04) nor in the self-selected rest interval group from pre- to post-test (38.2 ± 4.6 cm vs. 40.5 ± 4.4 cm).

Studies not matching volume load

The remaining twelve of the included 17 studies did not match the volume load in the protocols used. Four of these studies (Comyns et al., 2007; Gilbert and Lees, 2005; Krzysztofik et al., 2020b, 2020c) support the relationship between a higher volume load and potentiation stimuli. Of the remaining 8 studies, one analysed the neuromuscular function (Thomas et al., 2017), compared PAP in exercised and contralateral legs (Andrews et al., 2016), compared the relationship between PAP and time under tension (Krzysztofik et al., 2020a) and another studied the effects of plyometric PAP in bench press throw (Krzysztofik and Wilk, 2020). The remaining 4 reported contradictory results (Golas et al., 2017; Kobal et al., 2019; Poulos et al., 2018; Reardon et al., 2014).

Four studies (Comyns et al., 2007; Gilbert and Lees, 2005; Krzysztofik et al., 2020b, 2020c) support the notion of higher volume loads as better potentiation stimuli. These three studies compared different intensities and volumes ranging from 65% 1 RM to 130% 1 RM. Gilbert and Lees (2005) found statistically significant increases in the isometric RFD in the 1RM group at 15 min (p = 0.021) and 20 min (p = 0.006), with a peak increase of 11.8%. In the optimal power load group, a statistically significant increase (p = 0.038) in the isometric RFD was found at 2 min, with a peak increase of 6.7%. Comyns et al. (2007) found that contact time showed a statistically significant reduction (p < 0.05) and vertical leg spring stiffness indicated a significant increase (p < 0.05) for the heavy loaded protocol (93% 1RM). However, there were significantly (p < 0.01) shorter flight times for all the protocols. Krzysztofik et al. (2020b) compared the differences between a classic PAP protocol (2 sets of 2 repetitions of the concentric bench press at 90% 1-RM) and eccentric protocols (2 sets of 2 repetitions of either only eccentric 90% 1-RM, only eccentric 110% 1-RM or only eccentric 130% 1-RM bench press). The study reported better potentiation results with eccentric only protocols, achieving greater peak velocity (η2 = 0.441; p = 0.019) and greater mean velocity (η2 = 0.011; p = 0.041) after the 110% 1-RM eccentric only protocol and greater peak velocity after the 130% 1-RM eccentric only protocol (η2 = 0.323; p = 0.037). In another study by Krzysztofik et al. (2020c) with the same eccentric protocols, the bench press throw with a load of 30% 1-RM improved peak power by 10.5 ± 6.0% ( effect size = 0.34) and by 9.9 ± 8.1% (effect size = 0.33) for the 110 and 130% 1-RM conditions, respectively. Peak velocity increased by 5.9 ± 5.5% (effect size = 0.4) and by 6.1 ± 6.1% (effect size 0.43) for the 100 and 130% 1-RM protocols, respectively. Since sets and repetitions remained the same through protocols, the differences in volume load were a result of the different intensities.

Four studies (Golas et al., 2017; Kobal et al., 2019; Poulos et al., 2018; Reardon et al., 2014) showed conflicting results. In the study by Poulos et al. (2018) both protocols (10 sets of 3 or 5 repetitions with 87% 1RM vs. 65% 1RM respectively) enhanced jump height (65% 1RM: +3.3 ± 2.2% [CI: 1.0 to 5.6]; 87% 1RM +2.6% ± 1.9% [CI: 0.7 to 4.5]) after 10 sets. Nevertheless, there was a larger chance of jump height improvement when CMJs were performed across the 10 sets of squats in the protocol of 87% 1RM. Golas et al. (2017) compared five different protocols and they observed statistically significant (p = 0.01) differences in the RFD and the rate of power development (RPD) (p = 0.02) in the medium volume load group (80% 1RM) compared to the other conditions. Additionally, Kobal et al. (2019) found that a lower volume load with a higher intensity (100% 1RM) protocol induced similar results to a higher volume load and lighter load protocol (93% 1RM and 87% 1RM). Reardon et al. (2014) found no performance improvement in any of their protocols (3 sets of either 10 or 3 repetitions with 75% 1RM vs. 90% 1RM).

Thomas et al. (2017) analysed neuromuscular function using EMG during a PAP protocol. Countermovement jump height increased significantly (p = 0.008) from pre- to post-potentiation (from 41.0 ± 4.3 cm to 44.7 ± 4.1 cm). Neuromuscular function was measured before the first CMJ and after the last CMJ. A small and statistically non-significant decrease in the maximum voluntary contraction (MVC) (p = 0.142) and in voluntary activation (p = 0.06) was observed, but potentiated twitch force was significantly (p < 0.001) reduced after strength training (235 ± 65 N to 185 ± 51 N) in comparison to the control group.

Andrews et al. (2016) studied the effect of unilateral squats potentiation in the exercised leg and in the contralateral leg using a low fatigue protocol. The results showed no statistically significant differences at 1, 5 and 10 min in comparison to pre-test values for the drop jump contact time or the drop jump reactive strength index. Regarding the CMJ, a condition x time interaction indicated that the exercised leg exhibited significant but small to trivial magnitude jump height increases of 4.0% (p = 0.02; d = 0.36), 0.9% (p = 0.06; d = 0.08) and 1.6% (p = 0.04; d = 0.15) at 1, 5 and 10min post-intervention, respectively. The contralateral leg, on the other hand, had trivial CMJ deficits post intervention: 1.3% (p = 0.23; d = 0.12), 0.9% (p = 0.09; d = 0.10) and 1.7% (p = 0.03; d = 0.19) at 1, 5 and 10min postintervention, respectively.

Krzysztofik and Wilk (2020) showed that 3 sets of 5 repetitions of plyometric push ups with 1 min rest intervals improved bench press peak velocity (p < 0.01) and mean velocity (p < 0.01) compared to a control group. In addition, Krzysztofik et al. (2020a) also found that a PAP protocol consisting of 3 sets of 3 repetitions at 85% 1-RM achieved higher training volume based on time under tension at the end of the training session (p < 0.01) when compared to a control group, despite completing the same number of repetitions.

Discussion

The main finding of this systematic review is that the volume load plays an important role in performance enhancement after a conditioning activity. Four studies firmly support that the volume load is the main conditioning factor to achieve an optimal potentiation effect (Comyns et al., 2007; Gilbert and Lees, 2005; Krzysztofik et al., 2020b, 2020c), while four showed contradictory results (Gołas et al., 2017; Kobal et al., 2019; Poulos et al., 2018; Reardon et al., 2014). This systematic review also shows that when the total volume is low, intensity seems to be decisive (Andrews et al., 2016; Poulos et al., 2018).

Recruitment of type II fibers is needed to achieve potentiation, which is the result of combining volume and intensity (Bawa et al., 2014; Bompa and Haff, 2009; Henneman et al., 1974; Maloney et al., 2014). As stated by Schoenfeld (2010), in order to recruit high order motor units, light loads are not as effective as heavy loads. In the four studies (Comyns et al., 2007; Gilbert and Lees, 2005; Krzysztofik et al., 2020b, 2020c) firmly supporting our hypothesis, high intensities were used (up to 130% 1 RM) to achieve higher volume loads. However, potentiation can be achieved using lower volume loads as well (Gołas et al., 2017; Kobal et al., 2019). Gołas et al. (2017) and Kobal et al. (2019) performed between 3 and 5 sets with different loads ranging from 60% 1 RM to 100% 1-RM with a fixed rest interval. Considering that fatigue is especially evident when training is performed close to 1-RM or to failure (Dankel et al., 2017; Zajac et al., 2015), the better potentiation achieved in these studies with lower volume loads may rely on the rest-time between the conditioning activity and the re-test. Although according to Do Carmo et al. (2018) a self-selected rest may be sufficient to improve performance, other studies suggest that potentiation values peak after 8 min or longer resting periods (Gilbert and Lees, 2005; Kilduff et al., 2008).

The second finding is that a minimum effective intensity is needed to achieve potentiation. However, intensity should be understood as the amount of repetitions in reserve and not as the percentage of 1-RM. In order to achieve potentiation, we can either use light loads with high volumes or high intensities with low volumes (Bompa and Haff, 2009). Thus, when leaving at least 2 repetitions in reserve, performing multiple sets leads to potentiation without accumulating excessive fatigue (Andrews et al., 2016; Poulos et al., 2018). However, although lowering intensity during the conditioning activity may lead to lesser fatigue (Mina et al., 2019), leaving too many repetitions in reserve may not provide enough stimuli to elicit potentiation (Helms et al., 2016; Reardon et al., 2014). On the other hand, leaving too few repetitions in reserve (between 0 and 1) may lead to excessive fatigue and impaired performance after the conditioning activity (Helms et al., 2016; Reardon et al., 2014). In this way, the higher the intensity, the longer the rest interval the athlete needs to dissipate fatigue (do Carmo et al., 2018; Gilbert and Lees, 2005).

We also found different time-potentiation profiles for high- and medium-load protocols. In the study by Lowery et al. (2012), heavy and medium protocols peaked at the same time point, but potentiation achieved with the heavy loaded protocol was maintained for a longer time. These findings are in line with those of Gilber and Lees (2005), who reported different time-potentiation profiles; while the optimal power load group peaked earlier, the heavy loaded protocol group peaked later but with a higher potentiation effect (6.7% vs. 11.8%, respectively). These findings are in line with those by Krzysztofik and Wilk (2020) who observed the greater increase in peak velocity and mean velocity of the bench press in the first set after the plyometric push ups protocol. Thus, the time-potentiation profiles seem to be determined by the intensity of the stimuli and the resting time (fatigue-potentiation relationship). Fatigue in resistance training, as suggested by Zajac et al. (2015), is produced by post-exercise intramuscular perturbations (i.e., decrease in phosphocreatine, glycogen, ATP stores and augmentation of phosphate and hydrogen ions) and modulation of central motor drive during exercise by nociceptive afferent input (III and IV muscle afferents). These changes are especially evident when training sessions are close to 1-RM. During submaximal contractions, the closer to failure, the more motor units are recruited, but also the higher the metabolite accumulation, which contributes to fatigue (Dankel et al., 2017). This may partially explain the differences in the potentiation protocols leaving too many (Andrews et al., 2016) or too little (Reardon et al., 2014) repetitions in reserve during submaximal efforts.

We have to acknowledge several limitations. These include the lack of raw data for a deeper analysis. The main purpose of the review was to summarize the evidence so far and, if possible, to analyse differences in used protocols based on the volume load. While the most recent studies included raw data, the oldest ones did not. This limited our intention to compare the volume load of different protocols as we could not calculate it for 2 of the 13 studies. Another important limitation was related to the heterogeneity of the protocols used. Finally, the results of this review cannot be extrapolated to the general population as it only analysed trained subjects and almost all subjects were men. All these limitations imply that the conclusions of this review should be interpreted with caution.

Conclusions

Although different protocols can be used to achieve post-activation potentiation, it seems that higher intensities induce better performance enhancement. Our results indicate that potentiation effect exists as long as minimum intensity and sufficient rest intervals are provided. More precisely, the results of this study highlight the following:

Experienced athletes benefit more from a higher volume potentiation bout (1-3 sets), especially when the optimal power load is used.

Intensities of 65% 1RM are valid with high volumes, but higher potentiation effects can be achieved with 85% - 90% 1RM intensities. Higher intensities are useful, but they need longer rest intervals.

Repetitions to failure or almost to failure are not recommended because of the fatigue generated (2-3 repetitions in reserve).

Around 7-8 minutes of rest should be allowed in order to dissipate fatigue. Self-selected rest intervals are valid too, as they adjust quite precisely.

Due to major sensitivity of type II fibres to calcium concentration, athletes with a higher percentage of type II fibres will benefit more from heavy loads and longer rest intervals after PAP protocols (Blazevich and Babault, 2019).

Plyometric protocols combined with short or medium rest intervals are useful postactivation protocols for the bench press.

Figure 1

Flow chart of search strategy and selection of articles.
Flow chart of search strategy and selection of articles.

Physiotherapy Evidence Database (PEDro) ratings and Oxford evidence levels of the included studies.

Study12345678TotalEvidence level
Andrews et al. (2016)Yes111111171b
Comyns et al. (2007)Yes111111171b
Dello Iacono et al. (2019)Yes111111171b
Do Carmo et al. (2018)Yes111111172b
Gilbert & Lees (2007)Yes111111171b
Golas et al. (2017)Yes111111152b
Kilduff et al. (2008)Yes001111152b
Kobal et al. (2019)Yes001111152b
Krzysztofik et al. (2020a)Yes111111171b
Krzysztofik et al. (2020b)Yes111111171b
Krzysztofik et al. (2020c)Yes111111171b
Krzysztofik and Wilk (2020)Yes111111171b
Lowery et al. (2012)Yes111111172b
Mina et al. (2019)Yes111011161b
Poulos et al. (2018)Yes111111171b
Reardon et al. (2014)Yes111111172b
Thomas et al. (2015)Yes100111152b

Included studies

StudyNumber (M/F)Age (years)RT experience (years)Main Outcome
Andrews et al. (2016)14 (8/6)M 21.3 21.2 ± ± 1.8 0.4 / F≥ 2Unilateral PAP and fatigue
Comyns et al. (2007)12 (12/0)23.3 ± 2.51RM ≥ 2x bodyweightOptimal resistive load and PAP
Dello Iacono (2019) et al.26 (26/0)23.2 ± 5.1≥ 2Traditional sets sets PAP PAP vs cluster
Do Carmo et al. (2018)12 (12/0)25.4 ± 3.6≥ 3PAP rest interval
Gilbert and Lees (2007)15 (15/0)24.3 ±3.3unknownChanges in force development
Golas et al. (2017)16 (16/0)18-35≥ 5Used PAP load magnitude
Kilduff et al. (2008)20 (Unknown)25.4 ± 4.83.1 ± 1.6Recovery time and PAP
Kobal et al. (2019)18 (18/0)25.42 ± 3.583Different volume and PAP
Krzysztofik et al. (2020a)12 (12/0)25.2 ± 2.13PAPE and training volume
Krzysztofik et al. (2020b)32 (32/0)28.4 ± 4.53Eccentric and concentric PAP
Krzysztofik et al. (2020c)13 (13/0)25.7 ±1.96.5 ± 2.2Eccentric PAP
Krzysztofik and Wilk (2020)24 (24/0)24.5 ± 2.66.3 ± 2.5Plyometric PAP protocol
Lowery et al. (2012)13 (13/0)21 ± 33PAP stimuli and recovery time
Mina et al. (2019)15 (15/0)21.7 ± 1.1≥ 5PAP: free resistance weight vs variable
Poulos et al. (2018)15 (15/0)24.3 ± 2.6≥ 2Back Squat intensity and PAP
Reardon (2014)11 (11/0)25.18 ± 3.601RM ≥ 2x bodyweightMuscle architecture and PAP
Thomas et al. (2015)11 (11/0)23 ± 4≥ 2PAP and neuromuscular function

Andrews SK, Horodyski JM, Macleod DA, Whitten J, Behm DG. The interaction of fatigue and potentiation following an acute bout of unilateral squats. J Sport Sci Med, 2016; 15: 625–32AndrewsSKHorodyskiJMMacleodDAWhittenJBehmDGThe interaction of fatigue and potentiation following an acute bout of unilateral squatsJ Sport Sci Med20161562532Search in Google Scholar

Bawa PNS, Jones KE, Stein RB. Assessment of size ordered recruitment. J Hum Kinet, 2014; 49: 159–69BawaPNSJonesKESteinRBAssessment of size ordered recruitmentJ Hum Kinet20144915969Search in Google Scholar

Baz-Valle E, Fontes-Villalba M, Santos-Concejero J. Total number of sets as a training volume quantification method for muscle hypertrophy: a systematic review. J Strength Cond Res, 2018; 00: 1–9Baz-ValleEFontes-VillalbaMSantos-ConcejeroJTotal number of sets as a training volume quantification method for muscle hypertrophy: a systematic reviewJ Strength Cond Res20180019Search in Google Scholar

Blazevich AJ, Babault N. Post-activation Potentiation Versus Post-activation Performance Enhancement in Humans: Historical Perspective, Underlying Mechanisms, and Current Issues. Front Physiol, 2019; 10, DOI: 10.3389/fphys.2019.01359BlazevichAJBabaultNPost-activation Potentiation Versus Post-activation Performance Enhancement in Humans: Historical Perspective, Underlying Mechanisms, and Current IssuesFront Physiol20191010.3389/fphys.2019.01359Open DOISearch in Google Scholar

Bompa TO, Haff GG. Periodization: theory and methodology of training (5th edition). 2009BompaTOHaffGGPeriodization: theory and methodology of training (5th edition)2009Search in Google Scholar

do Carmo EC, De Souza EO, Roschel H, Kobal R, Ramos H, Gil S, Tricoli V. Self-Selected Rest Interval Improves Vertical Jump Post-Activation Potentiation. J Strength Cond Res, 2018: 1doCarmo ECDeSouza EORoschelHKobalRRamosHGilSTricoliVSelf-Selected Rest Interval Improves Vertical Jump Post-Activation PotentiationJ Strength Cond Res20181Search in Google Scholar

Comyns TM, Harrison AJ, Hennessy L, Jensen RL. Identifying the optimal resistive load for complex training in male rugby players. Sport Biomech, 2007; 6: 59–70ComynsTMHarrisonAJHennessyLJensenRLIdentifying the optimal resistive load for complex training in male rugby playersSport Biomech200765970Search in Google Scholar

Dankel SJ, Mattocks KT, Jessee MB, Buckner SL, Mouser JG, Loenneke JP. Do metabolites that are produced during resistance exercise enhance muscle hypertrophy? Eur J Appl Physiol, 2017; 117: 2125–35DankelSJMattocksKTJesseeMBBucknerSLMouserJGLoennekeJPDo metabolites that are produced during resistance exercise enhance muscle hypertrophy?Eur J Appl Physiol2017117212535Search in Google Scholar

Gilbert G, Lees A. Changes in the force development characteristics of muscle following repeated maximum force and power exercise. Ergonomics, 2005; 48: 1576–84GilbertGLeesAChanges in the force development characteristics of muscle following repeated maximum force and power exerciseErgonomics200548157684Search in Google Scholar

Gołas´ A, Wilk M, Stastny P, Maszczyk A, Pajerska K, Zajac A. Optimizing half squat postactivation potential load in squat jump training for eliciting relative maximal power in ski jumpers. J Strength Cond Res, 2017; 31: 3010–7Gołas´AWilkMStastnyPMaszczykAPajerskaKZajacAOptimizing half squat postactivation potential load in squat jump training for eliciting relative maximal power in ski jumpersJ Strength Cond Res20173130107Search in Google Scholar

Gołaś A, Maszczyk A, Zajac A, Mikołajec K, Stastny P. Optimizing post activation potentiation for explosive activities in competitive sports. J Hum Kinet, 2016; 52: 95–106GołaśAMaszczykAZajacAMikołajecKStastnyPOptimizing post activation potentiation for explosive activities in competitive sportsJ Hum Kinet20165295106Search in Google Scholar

Helms ER, Cronin J, Storey A, Zourdos MC. Application of the Repetitions in Reserve-Based Rating of Perceived Exertion Scale for Resistance Training. Strength Cond J, 2016; 38: 42–9HelmsERCroninJStoreyAZourdosMCApplication of the Repetitions in Reserve-Based Rating of Perceived Exertion Scale for Resistance TrainingStrength Cond J201638429Search in Google Scholar

Henneman E, Ckamann PH, Gillies DJ, Skinner RD. Rank order of motoneurons within a pool: law of combination. J Neurophysiol, 1974; 37: 1338–49HennemanECkamannPHGilliesDJSkinnerRDRank order of motoneurons within a pool: law of combinationJ Neurophysiol197437133849Search in Google Scholar

Dello Iacono A, Beato M, Halperin I. The Effects of Cluster-Set and Traditional-Set Postactivation Potentiation Protocols on Vertical Jump Performance. Int J Sports Physiol Perform, 2019: 1–6DelloIacono ABeatoMHalperinIThe Effects of Cluster-Set and Traditional-Set Postactivation Potentiation Protocols on Vertical Jump PerformanceInt J Sports Physiol Perform201916Search in Google Scholar

Dello Iacono A, Padulo J, Seitz LD. Loaded hip thrust-based PAP protocol effects on acceleration and sprint performance of handball players: Original Investigation. J Sports Sci, 2018; 36: 1269–76DelloIacono APaduloJSeitzLDLoaded hip thrust-based PAP protocol effects on acceleration and sprint performance of handball players: Original InvestigationJ Sports Sci201836126976Search in Google Scholar

Kilduff LP, Owen N, Bevan H, Bennett M, Kingsley MIC, Cunningham D. Influence of recovery time on post-activation potentiation in professional rugby players. J Sports Sci, 2008; 26: 795–802KilduffLPOwenNBevanHBennettMKingsleyMICCunninghamDInfluence of recovery time on post-activation potentiation in professional rugby playersJ Sports Sci200826795802Search in Google Scholar

Kobal R, Pereira LA, Kitamura K, Paulo AC, Ramos HA, Carmo EC, Roschel H, Tricoli V, Bishop C, Loturco I. Post-Activation Potentiation: Is there an Optimal Training Volume and Intensity to Induce Improvements in Vertical Jump Ability in Highly-Trained Subjects? J Hum Kinet, 2019; 66: 195–203KobalRPereiraLAKitamuraKPauloACRamosHACarmoECRoschelHTricoliVBishopCLoturcoIPost-Activation Potentiation: Is there an Optimal Training Volume and Intensity to Induce Improvements in Vertical Jump Ability in Highly-Trained Subjects?J Hum Kinet201966195203Search in Google Scholar

Krzysztofik M, Wilk M. The Effects of Plyometric Conditioning on Post-Activation Bench Press Performance. J Hum Kinet, 2020; 74: 7-20KrzysztofikMWilkMThe Effects of Plyometric Conditioning on Post-Activation Bench Press PerformanceJ Hum Kinet202074720Search in Google Scholar

Krzysztofik M, Wilk M, Filip A, Zmijewski P, Zajac A, Tufano JJ. Can post-activation performance enhancement (PAPE) improve resistance training volume during the bench press exercise? Int J Environ Res Public Health, 2020a; 17: 2554KrzysztofikMWilkMFilipAZmijewskiPZajacATufanoJJCan post-activation performance enhancement (PAPE) improve resistance training volume during the bench press exercise?Int J Environ Res Public Health2020a172554Search in Google Scholar

Krzysztofik M, Wilk M, Golas A, Lockie RG, Maszczyk A, Zajac A. Does Eccentric-only and Concentric-only Activation Increase Power Output? Med Sci Sports Exerc, 2020b; 52: 484–9KrzysztofikMWilkMGolasALockieRGMaszczykAZajacADoes Eccentric-only and Concentric-only Activation Increase Power Output?Med Sci Sports Exerc2020b524849Search in Google Scholar

Krzysztofik M, Wilk M, Lockie RG, Golas A, Zajac A, Bogdanis GC. Postactivation Performance Enhancement of Concentric Bench Press Throw After Eccentric-Only Conditioning Exercise. J Strength Cond Res, 2020c; Epub ahead of printKrzysztofikMWilkMLockieRGGolasAZajacABogdanisGCPostactivation Performance Enhancement of Concentric Bench Press Throw After Eccentric-Only Conditioning ExerciseJ Strength Cond Res2020cEpub ahead of printSearch in Google Scholar

Lowery RP, Duncan NM, Loenneke JP, Sikorski EM, Naimo MA, Brown LE, Wilson FG, Wilson JM. The Effects of Potentiating Stimuli Intensity Under Varying Rest Periods on Vertical Jump Performance and Power. J Strength Cond Res, 2012; 26: 3320–5LoweryRPDuncanNMLoennekeJPSikorskiEMNaimoMABrownLEWilsonFGWilsonJMThe Effects of Potentiating Stimuli Intensity Under Varying Rest Periods on Vertical Jump Performance and PowerJ Strength Cond Res20122633205Search in Google Scholar

Maher CG, Sherrington C, Herbert RD, Moseley AM, Elkins M. Reliability of the PEDro Scale for Rating Quality of Randomized Controlled Trials. Phys Ther, 2003; 83: 713–21MaherCGSherringtonCHerbertRDMoseleyAMElkinsMReliability of the PEDro Scale for Rating Quality of Randomized Controlled TrialsPhys Ther20038371321Search in Google Scholar

Maloney SJ, Turner AN, Fletcher IM. Ballistic Exercise as a Pre-Activation Stimulus: A Review of the Literature and Practical Applications. Sport Med, 2014; 44: 1347–59MaloneySJTurnerANFletcherIMBallistic Exercise as a Pre-Activation Stimulus: A Review of the Literature and Practical ApplicationsSport Med201444134759Search in Google Scholar

Mina MA, Blazevich AJ, Tsatalas T, Giakas G, Seitz LB, Kay AD. Variable, but not free-weight, resistance back squat exercise potentiates jump performance following a comprehensive task-specific warm-up. Scand J Med Sci Sports, 2019; 29: 380–92MinaMABlazevichAJTsatalasTGiakasGSeitzLBKayADVariable, but not free-weight, resistance back squat exercise potentiates jump performance following a comprehensive task-specific warm-upScand J Med Sci Sports20192938092Search in Google Scholar

Morin J, Edouard P, Samozino P. Technical Ability of Force Application as a determinant factor of sprint performance. Med Sci Sport Exerc, 2010; 43: 1680–8MorinJEdouardPSamozinoPTechnical Ability of Force Application as a determinant factor of sprint performanceMed Sci Sport Exerc20104316808Search in Google Scholar

de Morton NA. The PEDro scale is a valid measure of the methodological quality of clinical trials: a demographic study. Aust J Physiother, 2009; 55: 129–33deMorton NAThe PEDro scale is a valid measure of the methodological quality of clinical trials: a demographic studyAust J Physiother20095512933Search in Google Scholar

OCEBM Levels of Evidence Working Group. Home - CEBM. “The Oxford 2011 Levels Evidence” Oxford Cent Evidence-Based Med, 2011OCEBM Levels of Evidence Working Group. Home - CEBM“The Oxford2011Levels Evidence” Oxford Cent Evidence-Based Med2011Search in Google Scholar

Poulos N, Chaouachi A, Buchheit M, Slimani D, Haff GG, Newton RU, Germain PS. Complex training and countermovement jump performance across multiple sets: Effect of back squat intensity. Kinesiology, 2018; 50: 75–89PoulosNChaouachiABuchheitMSlimaniDHaffGGNewtonRUGermainPSComplex training and countermovement jump performance across multiple sets: Effect of back squat intensityKinesiology2018507589Search in Google Scholar

Reardon D, Hoffman JR, Mangine GT, Gonzalez AM, Wells AJ, Fukuda DH, Fragala MS, Stout JR. Do Acute Changes In Muscle Architecture Affect Post-Activation Potentiation? Med Sci Sport Exerc, 2014; 46: 354ReardonDHoffmanJRMangineGTGonzalezAMWellsAJFukudaDHFragalaMSStoutJRDo Acute Changes In Muscle Architecture Affect Post-Activation Potentiation?Med Sci Sport Exerc201446354Search in Google Scholar

Schoenfeld BJ. The mechanisms of muscle hypertrophy and their application to resistance training. J Strength Cond Res, 2010; 24: 2857–72SchoenfeldBJThe mechanisms of muscle hypertrophy and their application to resistance trainingJ Strength Cond Res201024285772Search in Google Scholar

Thomas K, Toward A, West DJ, Howatson G, Goodall S. Heavy-resistance exercise-induced increases in jump performance are not explained by changes in neuromuscular function. Scand J Med Sci Sport, 2017; 27:3 5–44ThomasKTowardAWestDJHowatsonGGoodallSHeavy-resistance exercise-induced increases in jump performance are not explained by changes in neuromuscular functionScand J Med Sci Sport2017273544Search in Google Scholar

Zajac A, Chalimoniuk M, Gołas̈ A, Lngfort J, Maszczyk A. Central and peripheral fatigue during resistance exercise - A critical review. J Hum Kinet, 2015; 49: 159–69ZajacAChalimoniukMGołas̈ALngfortJMaszczykACentral and peripheral fatigue during resistance exercise - A critical reviewJ Hum Kinet20154915969Search in Google Scholar

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