A Series of Acute Psychological Priming Interventions Assessing Changes in Hormonal and Physical Performance Measures During Resistance Training

Abstract

Psychological “priming” strategies such as music, self-talk, imagery, and audience effects are commonly used by athletes, yet their acute influence on resistance training performance and underlying endocrine responses is unclear. We conducted three crossover studies in collegiate adults (n = 64) examining self-selected music (SSM), motivational self-talk with imagery (MSTI) or without (MST), and observation either in-person (OE) or via social media (SM) compared with control (CON). Performance tests included a 3-repetition maximum (3RM) back squat, four sets of a 4RM bench press, and a 65% 1RM back squat to failure. Salivary testosterone (T) and cortisol (C) concentrations were assessed to explore potential mechanisms. Across studies, no condition yielded statistically significant differences versus CON (p > 0.05); however, small-to-moderate effect sizes suggested practically relevant improvements. For example, 3RM back squat load increased under SSM (g = 0.26) and MSTI (g = 0.22), while SM observation improved repetitions to failure (g = 0.33) and produced a moderate rise in T (g = 0.79). Several priming strategies also favourably altered the T:C ratio. These findings suggest that although group-level changes were subtle, individualized responses may allow athletes to benefit from simple, free interventions that could accumulate into meaningful performance gains when applied repeatedly in training. Future work with larger samples and long-term training designs is warranted to confirm these effects and whether changes in T and C are modulating the priming response.

1. Introduction

The importance of physically warming up to increase preparedness for athletic performance has been widely accepted in the scientific literature [1,2,3]. Jeffreys [1] designed a protocol called the “RAMP” warm-up to “raise” body temperature, “activate” and “mobilize” muscles and joints, in order to then “potentiate” the effectiveness of the subsequent performance task. However, the mental aspect of warming up appears to lack a similar protocol, and structured psychological techniques appear to be less routinely applied [4]. A mental warm-up aims to psychologically increase and enhance an athlete’s readiness for sports performance [4]. To reach the ideal mental state, elite athletes have used techniques such as imagery, goal setting, relaxation, attentional focusing, and emotional control [4]. These methods are often referred to as “priming.” When “primed,” performance is potentially improved through increased load lifted when resistance training, or in a sporting performance context, through 40 m sprint time for example. When athletes are without a coach or sports psychologist, the implementation of formalized priming is possibly absent altogether, likely due to a lack of knowledge, perceived value, and protocols [5]. Therefore, a sustainable and easily adhered-to protocol would be beneficial for athletes and reduce the need to rely on others for its consistent integration.

Many athletes instinctively “psych” themselves up prior to training and competition. A systematic review of 53 studies showed increased muscular strength of 61–75% after implementing cognitive psyching-up strategies [6]. Further to this, in a survey of 90 athletes, Collins et al. [7] reported that 89% implemented some form of psychological priming, with 38% reporting improvements in motivation, with music being the most popular priming tool (27%). Music is often used to elicit positive psychological effects in interventions and is simple to implement and effortlessly absorbed by the listener [8]. This is because music is a non-cognitive technique, as there is no conscious mental component [9]. Karageorghis [10] reported that music could enhance emotional arousal, motivation, task engagement, and enjoyment. The effects reported have primarily been derived from studies using aerobic exercise [11,12]. However, Bartolomei et al. [13] reported that when self-selected music was listened to in 31 resistance-trained men, a significant increase (t-test p = 0.03, 5.8%) in bench press was noted when repetitions were performed to failure at 60% one repetition maximum (1RM). Moss et al. [11] support this by reporting that compared to a control group, squat and bench press performances increased in 16 resistance-trained males when performing repetitions to failure at 60% 1RM (Cohen’s d = 1.05 and d = 0.71, respectively), while listening to music at a minimum of 120 beats per minute.

The second most popular priming tool reported by Collins et al. [7] was self-talk (24%). Self-talk has been defined as “self-addressed verbalizations that can serve both instructional and motivational functions” [14] (p. 999). It has been proposed to enhance sporting performance by increasing attentional focus, confidence, and motivation, regulating effort, and controlling emotional and cognitive reactions [15,16,17]. Research has classified self-talk into two categories: instructional and motivational. Hardy et al. [18] report that instructional self-talk may be more effective for tasks requiring timing and precision, whereas motivational self-talk is better considered for tasks requiring strength and endurance. For example, Theodorakis et al. [19] reported that in 72 male youth soccer players, instructional self-talk significantly (mixed-model ANOVA p < 0.01) improved a soccer accuracy test of passing the ball into 12 one-yard-wide goals compared to motivational self-talk (7.1 goals vs. 4.6 goals, respectively). They also performed a badminton service test of serving the shuttlecock into a small area and found that instructional self-talk significantly (mixed-model ANOVA p < 0.02) improved serve accuracy compared to motivational self-talk (36 serves vs. 29.5 serves, respectively). Additionally, Blanchfield et al. [14] reported the effects of motivational self-talk on 24 recreationally trained participants, cycling at 80% peak power output to exhaustion. Both ratings of perceived effort (Cohen’s d = 0.80, independent t-test p < 0.05) and time to exhaustion (Cohen’s d = 0.69, independent t-test p < 0.05) showed significant improvement compared to the control condition. Another widely used cognitive priming technique is imagery, which is suggested to be the link between physical and imagined movements [20,21]. In a meta-analysis of 55 studies by Simonsmeier et al. [22], imagery was found to be effective at enhancing motor learning and various sport-specific performance outcomes (Cohen’s d = 0.43). Hardy et al. [23] postulate that the effects of imagery may be enhanced when combined with self-talk, as self-talk may help to improve the quality of the imagery. For example, in 33 skilled tennis players, during match play conditions, the percentage of successful first serves significantly (repeated measures ANOVA p < 0.05) increased after implementing imagery and self-talk together (η2p = 0.66), compared to imagery alone (η2p = 0.28) [24]. This result may indicate the potential effects of implementing both motivational priming strategies together. However, there is a dearth of literature researching the effects of both priming strategies together, particularly in relation to measures of athletic performance and resistance training. Therefore, further investigations are warranted to corroborate this theory.

Finally, many professional athletes are observed during competition, which may also act as a primer. Tennie et al. [25] suggest that when being observed, a form of reputation management occurs, which requires a behavioural response dependent on the given task and who is observing. This is supported by Chen et al. [26], who suggest that the presence of peers heightens feelings for reward, which motivates changes in behavioural decision-making. This is known as the “audience effect theory” [27]. Therefore, being observed also has the potential to improve athletic performance. This was noted when 51 college students significantly increased loads lifted in a 1RM bench (women: 1.5 kg and men: 1.8 kg, ANOVA p < 0.05) and leg press (women: 4.1 kg and men: 8.5 kg, ANOVA p < 0.05) when being observed by two individuals of the opposite gender [28]. However, Zajonc [27] suggests that increased arousal due to an audience effect may affect performance positively or negatively depending on the context of the task in question. Easily performed or well-rehearsed tasks will produce better outcomes than challenging or new tasks, where performance was found to worsen. Therefore, being observed could be an efficacious primer, potentially enhancing performance in simple training exercises.

Despite the widespread use and recognition of many of the aforementioned psychological priming methods, there appears to be a paucity of literature examining and explaining the underpinning mechanisms. Walter et al. [29] suggest that a priming intervention may affect psychological and cognitive processing. Changes in the hormone testosterone have been associated with altering these aspects through changes in motivation, power, risk-taking, competition, violence, dominance, seeking status, social and sexual interaction, increased risk-taking, and reduced fear [30,31,32,33]. Ishak et al. [34] report that endocrine changes occur when music is listened to, with alterations in testosterone, cortisol, and oxytocin concentration levels, which may induce the positive effects noted, along with alterations in salivary immunoglobulin A, heart rate, and blood pressure levels. Our desire to seek status when being observed serves our primitive drives and can, in part, be explained by a “Biosocial Model of Status” [30,35]. This model also suggests that endocrine changes occur with testosterone, which motivate competitive behaviours that serve to increase status. This is supported in an imagery intervention by Schultheiss et al. [36], who reported the association between imagining being successful with a significant increase in testosterone in 42 male students (r = 0.77, ANOVA p < 0.001). Therefore, testosterone could potentially be the underpinning mechanism being altered with psychological priming strategies, including affecting the catecholamines adrenaline and noradrenaline.

Wang et al. [37] note that testosterone may modulate adrenaline release from the adrenal gland. In turn, catecholamines stimulate the central motor system, secretion of growth hormone and IGF-1, muscular enzyme activity, promote energy availability, and augment vascular dilation by modulating blood pressure and modulating the redistribution of blood. These act to alter contractile qualities of skeletal muscle leading to an increase in instantaneous recruitment of muscle mass and subsequently muscular strength [38,39,40]. Additionally, a rise in catecholamine levels before exercise is referred to as the “anticipatory” response, and the magnitude of the rise equates to the anticipated intensity [38]. Jezová et al. [41] also report a significant (ANOVA p < 0.05) correlation (r = 0.82) between plasma testosterone, adrenaline, and noradrenaline during exercise. Of note, however, testosterone is produced via the hypothalamus-pituitary axis, which consists of a dual hormone relationship; cortisol is considered to act as an antagonist to testosterone, inhibiting its production [42,43,44]. Increases in cortisol occur in response to physical or psychological stress [43]. Therefore, the modulation of cortisol may be just as significant as priming testosterone. For example, Cook and Crewther [45] reported that 12 professional rugby players produced their worst match performance (as rated by the head coach) when cortisol was significantly higher (17.6%, ANOVA p < 0.01) and testosterone lower (−0.7%) compared to baseline. In contrast, the best performance ratings occurred when testosterone was significantly higher (12.5%, ANOVA p < 0.001) and cortisol was lower (1.0%) compared to baseline.

Therefore, the overall aim of this study was to investigate the aforementioned psychological priming interventions and their effects on resistance training performance, and to determine if the T and the T:C ratio was modulating any observed changes. To achieve this aim, three individual studies were implemented, with each priming technique compared to a control condition. Study 1 consisted of listening to self-selected music (SSM) or engaging in motivational self-talk with imagery (MSTI) and its subsequent effect on a 3RM back squat (3RM). Study 2 investigated listening to SSM, or motivational self-talk (MST), and its effects on bench press performance over four sets of four repetitions at a four-repetition maximum (4RM) intensity. Finally, study 3 implemented being observed through social media (SM) or being viewed in-person (OE), and its effect on a 65% one RM (1RM) back squat exercise to repetition (rep) failure.

2. Methods

2.1. Participants

All studies were conducted in a randomized crossover design using a convenience sampling method, whereby a total of 64 participants undertook performance tests. Participants partook in only one intervention, where upper and lower body maximal strength and endurance were measured, thus determining its effect on resistance training volume load. Study 1 consisted of 17 collegiate adult males (25.94 ± 6.81 years, 170.80 ± 4.84 cm tall, and a mass of 82.94 ± 8.11 kg mean and standard deviation, respectively) and 11 collegiate adult females (28.36 ± 9.75 years, 163.97 ± 12.41 cm tall, and a mass of 68.47 ± 11.88 kg). Study 2 had 15 collegiate adult males (23.9 ± 3.8 years of age, 177.6 ± 3.3 cm tall, and a mass of 78.7± 8.6 kg) and seven collegiate adult females (21.1 ± 2.0 years of age, 173.3 ± 3.5 cm tall, and a mass of 67.9 ± 4.3 kg). Study 3 had nine collegiate adult males (22.3 ± 2.9 years of age, 176.1 ± 5.7 cm tall, and a mass of 80.0 ± 5.8 kg) and five collegiate adult females (22.4 ± 3.2 years of age, 173.0 ± 3.9 cm tall, and a mass of 70.0 ± 4.8 kg). All participants who volunteered to participate in this study were recruited via advertisements placed on the university grounds. To participate, the individuals must be in good health and free from injury and have at least three years of resistance training experience. Participants were classed as recreational, attending the gym at least twice weekly. Participants were excluded if they did not meet the above criteria. All participants provided written informed consent, with study procedures meeting Middlesex University’s ethical approval.

2.2. Procedures

On arrival at the testing facility, participants provided a saliva sample (protocol outlined later) before engaging in one of the priming interventions for five minutes, or, excluding the peer observation study, sitting passively in a sterile room (control condition). They then undertook a standardized warm-up consisting of a 15 min “RAMP” protocol, including inchworms (10), front lunges (10 on each side), “world’s greatest stretch” (10 on each side), and single-leg glute bridges (10 on each side). At the conclusion of the warm-up or following peer observation, they provided a second saliva sample. The time of day of the testing session was standardized to account for the daily circadian rhythm with natural fluctuations in T and C [46]. At least 72 h separated each condition tested. Before testing, all participants had a familiarization session, which enabled the determination of back squat and bench press loads and aided in determining the music playlist (for the self-selected music condition) and engagement in self-talk with imagery.

2.3. Saliva Sampling

Participants were asked to refrain from eating or drinking for two hours before arriving at the laboratory. Participants were asked to place a sterile swab in their mouth and allow saliva to soak in for two minutes. The swab was removed, placed into salivate collection tubes (Sarstedt, Leicester, UK), and stored at −80 °C. Before biochemical analysis, samples were thawed and centrifuged at 3000 rpm for three minutes to obtain clear saliva with low viscosity. Salivary testosterone and cortisol levels were determined by employing a commercially available enzyme-linked immunosorbent assay (ELISA, IBL, Hamburg, Germany) with limits of detection of 20 and 0.4 nmol/L, respectively. Stanton [47] advises that an intra- and inter-assay coefficient of variation (CV) of less than 10% is considered good; therefore, for this study, the intra- and inter-assay CV were set to <10%.

2.4. Motivational Self-Talk with Imagery

Participants were given a script containing positive motivational statements [15], which was followed by external coaching cues [48] consisting of phrases: “I WILL push the floor away,” “I CAN push this barbell up,” and “I WILL explode up.” If participants had a phrase they preferred to use that was not listed, this was allowed and, during the familiarization session, was refined. For the imagery component, participants were given an imagery script containing elements of the PETTLEP (physical, environmental, task, timing, learning, emotion, and perspective) imagery framework [20] and guided to imagine a positive emotion while visualizing themselves performing the subsequent tests successfully, either as though they were watching themselves on television or looking through their own eyes. This procedure is classified as motivational-general and cognitive-specific imagery, with participants reciting to themselves their motivational statements while positively feeling and seeing themselves performing a successful task [49,50].

2.5. Self-Selected Music

The psychological effect of music can be very individualized, with influences on emotions, mood, behaviour, attitudes, and cognition affecting everyone differently [51,52]. Therefore, participants self-selected the music of their choice rather than implementing pre-selected music. However, rhythm and tempo have been shown to prompt physical reactions to enhance performance [51]. Therefore, in line with Karageorghis [10], participants were asked to listen to songs in a playlist from Spotify called “125 bpm songs,” which contained songs with beats per minute (BPM) at 125. Participants used their headphones with their smartphone and were asked to play the music at the highest, comfortable audio level.

2.6. Observer Effect and Social Media

In recent years, social media platforms have enabled a virtual observer effect. Sherman et al. [53] reported increased neural responses in the medial prefrontal cortex and hippocampus in adolescent participants when observing their photographs. Also, increased activity in the nucleus accumbens, responsible for feelings of reward, occurred when viewing positive feedback on their pictures. This links back to our primitive desire to seek status, explained in the “Biosocial Model of Status” [30,35]. Therefore, a novel approach was implemented; as the participants warmed up, they were continuously observed with a mounted iPhone 12 camera (Cupertino, CA, USA). The mounted camera was known to the participants, and they were told that the film was to be uploaded to the University’s social media platforms. For the in-person observation, ten strangers whom the participants did not know and were masters-level college students, would stand on the edge of the room observing the participants throughout the whole intervention. To blind the participants, they were told the students happened to be in the facility by chance.

2.7. Back Squat

Before performing a 3RM or a 65% 1RM back squat to repetition failure, a potentiating warm-up was undertaken consisting of a back squat set of 10 reps at 20 kilograms (kg) at a controlled tempo, with a 1 min rest, followed by three sets of five reps with an increased load of 14–18 kg each set, with a 2 min rest [54]. The tests were then undertaken 4 min after the final warm-up set. If the attempt failed, a 3 min rest was given before their next attempt with a 3 kg reduced load. This process was replicated until an attempt had been completed. Depth was calculated whereby the thigh descended to a parallel position with the head of the femur in the same horizontal plane as the superior border of the patella [55]. A box was positioned posteriorly to the participant at the aforementioned height as they performed the exercise, controlling the individualized depth across all trials. Barbell load was recorded in kg using an IWF weightlifting competition Olympic barbell and plates (Eleiko; Halmstad, Sweden). A “push band” (Push Inc., Toronto, ON, Canada) accelerometer training device was attached to the barbell to determine velocity (m/s) for all repetitions. No verbal encouragement from the researcher was provided.

2.8. 4RM Bench Press

Before performing a 4-set of a 4-rep bench press test, a potentiating warm-up was undertaken, consisting of 10 reps at 20 kg, followed by eight and five reps at a self-selected weight, with two-minute rest between each set. The protocol was standardized, with all participants told to lie supine on a bench with eyes below a racked bar. Both hands were pronated and positioned slightly wider than shoulder-width apart so that the elbows were at a 90-degree angle at the bottom of the movement, whereby the bar touches the chest [56]. A 4RM load was investigated as strength is a key athletic characteristic; therefore, participants could be primed to a level whereby they could overcome their previous best effort. The load lifted was recorded in kg using the same barbells and plates as the back squat. The accelerometer training device was again attached to the barbell to determine velocity. The researchers provided no verbal encouragement. Reps not completed were classified as failed and recorded as 0 kg.

2.9. Statistical Analysis

Statistical analysis, including intraclass correlation coefficient and standard error of measurement (SEM) to measure reliability, were completed using Microsoft Excel and IBM SPSS Statistics 27. Endocrine markers, bench press and back squat loads, and barbell velocity were analyzed using repeated measures ANOVA with Bonferroni Post hoc analysis. Repeated measures ANOVA tests are robust to violations of normality [57], which are likely when measuring salivary testosterone and cortisol outside of highly trained athletes [58,59]. It has been reported that elite athletes’ hormone responses can differ considerably from lesser-trained non-elite individuals, as they are more sensitive to stress due to their bodies not being efficient at regulating stress responses. Physical exercise stabilizes hormonal responses through repeated exposure and adaptation, becoming more resilient to fluctuations [60]. Statistical significance was set at an alpha level of p < 0.05. Practical differences were examined using effect size analysis (Hedges’ g) with magnitudes of difference interpreted according to Cohen [61], whereby <0.20 = trivial; 0.20–0.49 = small; 0.5–0.79 = moderate; >0.8 = large. Ninety-five percent confidence intervals (CI) were also calculated per Hedge and Olkin [62]. Effect sizes and 95% CI were calculated using Microsoft Excel. Data for T and C were analyzed as a percentage change (±SEM) from each testing day’s baseline, and barbell load and velocity were assessed as a percentage change (±SEM) from the control condition. An individual case study analysis was also undertaken to identify individual responses to the interventions to highlight within-group variability and if interventions need to be personalized based on stimulus and outcome.

3. Results

3.1. Study 1

No statistically significant differences were noted during post hoc analysis in 3RM (p = 0.61), T (p = 0.28), or C (p = 0.89) markers compared to CON. However, there were small effect size increases in 3RM back squat load lifted in the MSTI and SSM conditions 96 ± 23 kg, g = 0.22 (95% CI −0.10, 0.54), 5.5%, and 97 ± 25 kg, g = 0.26 (95% CI −0.23, 0.75), 6.6%, respectively, compared to CON 91 ± 22 kg (Figure 1). Salivary testosterone concentrations were increased by MSTI 113 ± 38% (g = 0.39, 95% CI −0.27, 1.06), SSM 120 ± 35% (g = 0.66, 95% CI −0.06, 1.37), and CON 100 ± 22%. The T:C ratio (p = 0.68) resulted in the CON 9 ± 45%, MSTI 20 ± 48%, and SSM 22 ± 35%, equating to small effect sizes of MSTI g = 0.23 (95% CI −0.41, 0.87) and SSM g = 0.31 (95% CI −0.34, 0.96) (Figure 2). Intra-assay CV was 8.1%.

3.2. Study 2

No statistically significant differences were noted across any intervention 4RM (p = 0.06), C (p = 0.89), and T (p = 0.28), only practical differences. In total volume load (VL) lifted, a trivial difference occurred with SSM 1092.81 ± 360.67 kg, g = 0.09 (95% CI −0.42, 0.59), as did MST 1083.11 ± 341.46 kg, g = 0.06 (95% CI −0.45, 0.57) compared to CON 1061.55 ± 360.56 kg (Figure 3). Average barbell velocity across the strength training session demonstrated a trivial increase when comparing MST 0.32 ± 0.10 m/s, g = 0.15 (95% CI −0.36, 0.65) to CON 0.30 ± 0.08 m/s, and a trivial decrease comparing SSM 0.29 ± 0.08 m/s, g = −0.14 (95% CI −0.65, 0.37) to CON. Testosterone demonstrated a large increase after MST 135.07 ± 35.91%, g = 1.04 (95% CI 0.50, 1.58) and SSM 122.14 ± 21.10%, g = 0.85 (95% CI 0.32, 1.38) compared to control 103.65 ± 21.58%. The T:C ratio resulted in a small difference between CON and SSM 22%, g = −0.48 (95% CI −1.00, 0.03), a trivial difference between CON and MST 10%, g = −0.19 (95% CI −0.70, 0.32) (Figure 4). Intra-assay CV was 7.8%.

3.3. Study 3

No statistically significant differences were noted in total reps (p = 0.13), T (p = 0.07), and C (p = 0.70); however, practical differences were. The SM condition produced the most reps performed at 17.33 ± 6.14 reps, g = 0.38 (95% CI −0.27, 1.03), with OE at 17.50 ± 6.72 reps, g = 0.43 95% (CI −0.22, 1.08), compared to CON 14.83 ± 5.91 reps (Figure 5). Average barbell velocity incurred a small difference in both interventions, SM 0.49 ± 0.09 m/s, g = 0.27 (95% CI −0.37, 0.92), and the OE 0.49 ± 0.09 m/s, g = 0.28 (95% CI −0.37, 0.92), compared to CON 0.47 ± 0.08 m/s. A moderate increase in T occurred in SM 113.29 ± 40.76%, g = 0.79 (95% CI −0.12, 1.46), but only a trivial difference in OE 85.76 ± 30.20%, g = 0.06 (95% CI −0.58, 0.71) compared to CON 83.74 ± 31.45%. T:C ratio noted a moderate decrease in OE −19 ± 0.44%, g = 0.10 (95% CI −0.55, 0.74), and CON −23 ± 0.42%, with SM increasing by 2 ± 0.43% g = 0.58 (95% CI −0.08, 1.24) (Figure 6). Intra-assay CV was 8.5%.

Figure 7, Figure 8 and Figure 9 and

Table 1. Summary of effects across three priming studies.

Study	Primer	Performance Test	Performance Outcome vs. CON	Performance Change	T Change	T:C Change	Interpretation
1	SSM	3RM Back Squat	↑ 6.6% load	g = 0.26 (−0.23, 0.75)	g = 0.66	g = 0.31	Small ↑
1	MSTI	3RM Back Squat	↑ 5.5% load	g = 0.22 (−0.10, 0.54)	g = 0.39	g = 0.23	Small ↑
2	SSM	4 × 4RM Bench Press	↑ 31.26 kg VL	g = 0.09 (−0.42, 0.59)	g = 0.85	g = −0.4	Trivial
2	MST	4 × 4RM Bench Press	↑ 21.56 kg VL	g = 0.06 (−0.45, 0.57)	g = 1.04	g = −0.19	Trivial
3	SM	65% 1RM Squat to Failure	↑ 2.5 reps	g = 0.33 (−0.35, 1.02)	g = 0.79	g = 0.58	Moderate ↑
3	OE	65% 1RM Squat to Failure	↑ 2.67 reps	g = 0.28 (−0.40, 0.95)	g = 0.06	g = 0.10	Small ↑

Key: ↑ indicates an increase, self-selected music (SSM), motivational self-talk with imagery (MSTI) or without (MST), and observation either in-person (OE) or via social media (SM), repetition maximum (RM), testosterone (T), cortisol (C), Hedges g (g), volume load (VL), and control (CON).

summarize the findings across the three cross-over studies. While the point estimates suggest positive trivial to moderate increases in resistance training performance across priming methods, the 95% CI suggest some participants may experience large positive effects while others moderate negative effects (Figure 7). Across the three interventions, T appears to be consistently higher than control, and again, based on 95% CI, changes could be expected to be between a large positive change and a moderate negative decrease (Figure 8). For T:C, results are more varied (Figure 9).

4. Discussion

The present study investigated the priming capability of various psychological interventions on physical performance tests. No statistically significant results were reported across any intervention. However, small and moderate effect size differences were noted in repetitions completed, load lifted, barbell velocity, testosterone, cortisol, and the T:C ratio. Although small, these changes, over time, may equate to notable differences, as noted by the 95% confidence intervals reported, potentially leading to improvements in performance markers. Furthermore, we would encourage those engaging in resistance training to adopt priming strategies, as they are free and simple to implement. However, given responses are subject-specific, individuals should trial them to discover which is the most efficacious for them.

4.1. Study 1

Both MSTI and SSM strategies produced an improved 3RM back squat by 5 ± 2 kg (5.8%, g = 0.22, 95% CI −0.10, 0.54) and 6 ± 4 kg (7.1%, g = 0.26, 95% CI −0.23, 0.75), respectively, with T increasing by 12.5% (g = 0.39, 95% CI −0.27, 1.06) and 19.9% (g = 0.66, 95% CI −0.06, 1.37), respectively. These findings are similar to those of Cook and Crewther [45], who reported that psychological strategies could prime the 3RM back squat. When T concentration levels are increased, they can increase the release of catecholamine neurotransmitters adrenaline, noradrenaline, and dopamine, which can lead to instantaneous recruitment of muscle mass, an increase in intracellular calcium levels, and subsequent muscular strength [38,39,40]. In support, Crewther et al. [63] reported a correlation of r = 0.92 between T and a 1RM back squat; however, West and Phillips [64] reported no association between acute T secretion and leg press strength. Although the practical differences in our findings are small to moderate, collectively, these changes throughout a training programme could potentially lead to meaningful improvements in performance over time for these participants. Additionally, 95% CI analysis suggests that some individuals may experience large positive changes while others may have small detrimental changes and thus, an individualized approach is required, or more formal training is needed to capitalize on these forms of priming.

4.2. Study 2

This investigation sought to build on previous literature by identifying priming strategies that can be used to “psych-up” athletes before a resistance training session through the effect it has on salivary T and C concentration. Analysis of the CI indicates that some individuals experienced large positive changes, while others experienced small negative changes. A large increase in T levels occurred in MST and SSM by 35% and 18%, respectively, compared to the CON. While changes in total VL from four sets of four reps bench press were not statistically or practically significant (CON 1061.55 ± 360.56 kg, SSM 1092.81 ± 360.67 kg, MST 1083.11 ± 341.46 kg), examination of the raw data revealed that the MST and SSM groups had small individual increases in barbell load of 1.25–10 kg, or performed an extra rep within one or two of the sets. Therefore, potentially, these changes, over time, may equate to notable differences. Future research should utilize lighter loads (>6RM) to enable the detection of small changes. For example, participants reported attempting extra repetitions but failing. Thus, these attempts were not recorded, albeit recognized within average velocity. Presumably, using lighter loads would be more sensitive to any extra work performed and thus prove more sensitive to identifying additional repetitions subsequent to a priming effect, should one exist.

Weakley et al. [65] reported that barbell velocity for a four-repetition effort should be approximately 0.42 m/s. The average barbell velocity in this study was mixed in the intervention groups compared to the CON. MST velocity was 0.32 m/s, and SSM was 0.29 m/s, compared to CON at 0.30 m/s. This potentially suggests that subjects either chose loads that were too heavy due to their primed state and thus were willing to be more effortful, or they may have felt tired or demotivated (i.e., negatively primed) and therefore, applied less force to each rep. Interestingly, barbell velocity was slower when comparing SSM to MST, suggesting that music may have provided a greater intrinsic drive to work towards failure. Compared to the CON conditions, T demonstrated a large increase following SSM of 18% (d = 0.84, 95% CI 0.24, 1.43) and MST of 35% (d = 1.05, 95% CI 0.41, 1.70), which may, in part, explain the lower velocities under these conditions due to more load being lifted. Furthermore, MST demonstrated a small increase in T compared to the SSM condition (d = 0.44, 95% CI −0.09, 0.97).

4.3. Study 3

This study sought to add to the limited literature on priming healthy collegiate adults during their warm-up via the use of the OE, both in-person and virtually via SM. A moderate increase in salivary T concentration levels was noted in the SM condition of 113.2% (g = 0.79, 95% CI = −0.12, 1.46), compared to the trivial OE response of 85.7% (g = 0.06, 95% CI −0.58, 0.71) and control of 83.7%. An increase in total reps completed and barbell velocity in the back squat exercise may have occurred due to the increase in the endocrine marker, particularly in the SM condition with 17.50 reps (g = 0.43, 95% CI −0.22, 1.08), compared to OE condition with 17.33 reps (g = 0.38, 95% CI −0.27, 1.03), and CON with 14.83 reps. Bar velocity also improved in the SM condition, 0.49 m/s (g = 0.27, 95% CI −0.37, 0.92) and OE condition, 0.49 m/s (g = 0.28, 95% CI −0.37, 0.92), compared to the CON, 0.47 m/s. These results are in line with Cook et al. [66], who reported a correlation of free T levels before training in 15 men to self-selected back squat and bench press workloads (r = 0.81, p < 0.001). Cook and Crewther [45], Cook and Beaven [67], and Crewther et al. [63] support these findings by correlating back squat performance with T levels (r = 0.85, r = 0.67, and r = 0.92, respectively). Interestingly, Alexander et al. [68] did not make any associations between total T and hand grip strength in 716 women. This result may have occurred due to the exercise testing maximal strength rather than repetitions. Therefore, because these back squat performance improvements are mirrored by moderate increases in T and moderate increases in the TC ratio (SM 102%, g = 0.58, 95% CI −0.08, 1.24; OE 81%, g = 0.10, 95% CI −0.55, 0.74; CON 77%), we speculate that with these participants a priming strategy whereby T is modulated through behaviour and motivation through what they perceive to be a status-seeking opportunity can be used to maximize performance.

This study provides a meaningful contribution to sport and exercise science by implementing a novel approach of integrating psychological priming strategies with physiological and performance outcomes in resistance training. It is among the first to examine how these distinct priming strategies, of self-selected music, motivational self-talk with and without imagery, and social observation, can elicit measurable improvements in strength and hormonal responses in the population studied. The inclusion of confidence intervals strengthens the interpretation of practical significance by emphasizing individual variability. Therefore, this study advances understanding of how psychological and endocrine mechanisms may interact to influence physical performance and support more personalized mental preparation approaches.

5. Limitations

While the overall sample size was 63, each study may have benefited with larger samples given their non-elite status and thus more variable responses to priming and the release of T and C; this may also have enabled us to examine sex differences. These studies only utilized a 3RM, 65% 1RM back squat, and 4RM bench press tests; therefore, we cannot correlate the changes noted here to other measures of athletic performance, such as during jumping and sprinting. Lastly, a coefficient of variation of 9% in hormonal changes may be too large to signal subtle changes in the hormonal status.

6. Conclusions

In summary, while the acute effects of priming strategies were small and variable, the consistent positive trends across studies with these participants indicate that such techniques may serve as low-cost, accessible tools to enhance resistance training performance. Importantly, the observed individual differences suggest that no single strategy will be universally effective, and individuals may benefit most from experimenting with different approaches to identify their optimal method. Over time, the accumulation of small performance gains and favourable hormonal profiles could contribute to meaningful long-term adaptations. Future research should therefore prioritize larger, more diverse samples and chronic training designs to determine whether these acute responses translate into sustained improvements in strength and performance.