Short-Term Psychological and Physiological Effects of Varying the Volume of High-Intensity Interval Training in Healthy Men

Abstract

We assessed the short-term effects of varying the volume of high-intensity interval training (HIIT) on psychological and physiological responses of 23 healthy adult males (M = 21 years; M peak oxygen uptake [VO_2peak] = 47.2 ml·kg⁻¹·min⁻¹). Participants were randomly assigned to low- and very-low-volume HIIT groups and engaged in nine supervised exercise sessions over three weeks. The low-volume HIIT group performed 8-12 60-second work bouts on a cycle ergometer at the peak power output achieved during the incremental test, interspersed by 75 seconds of low-intensity active recovery. The very-low-volume HIIT performed 4-6 work bouts with the same intensity, duration, and rest intervals. During training, participants’ ratings of perceived exertion (Borg Category Ratio-10 scale) and their affective responses (Feeling Scale −5/+5) during the last 15 seconds of each work bout were recorded. Physiological data were VO_2peak, endurance, and anaerobic performance before and after the intervention. Throughout training, participants in the very-low-volume group (relative to the low-volume group) reported lower ratings of perceived exertion in Week 1 (M = 4.1 vs. M = 6.3; p < .01) and Week 3 (M = 4.0 vs. M = 6.2; p < .01), and higher affective response in these same two weeks (Week 1: M = 1.9 vs. M = 0.3; p = .04; Week 3: M = 2.1 vs. M = 0.9; p = .06). Regarding physical fitness, Wingate peak power increased significantly after training in the very-low-volume HIIT group (M = 1,049 W vs. M = 1,222 W; p < .05), but not in the low-volume HIIT group (M = 1,050 W vs. M = 1,076 W). No significant change was found after training in physiological variables of peak power output, VO_2peak, and endurance performance. In summary, in this short-term training period, the very-low-volume HIIT enhanced anaerobic capacity and was perceived as less strenuous and more pleasurable than low-volume HIIT.

Keywords

affective responses feeling states interval training perceived exertion aerobic fitness physiological responses

Introduction

Current physical activity guidelines advocate that healthy adults accumulate 150 minutes of moderate-intensity or 75 minutes of vigorous intensity physical activity per week to achieve fitness and health improvements (Garber et al., 2011). However, epidemiological research has found that many people fail to meet these recommendations (World Health Organization, 2011). The most commonly cited barrier to regular exercise participation is “lack of time” (Sequeira, Cruz, Pinto, Santos, & Marques, 2011, p. A19). Therefore, researchers and exercise professionals have focused on identifying the minimal dose of exercise required to gain favorable physiological adaptations to cardiovascular and metabolic systems (Gillen & Gibala, 2014). A recent development is an advocacy of sprint interval training (SIT), characterized by brief, intermittent bouts of supramaximal intensity interspersed with periods of active or passive recovery (Burgomaster et al., 2008). SIT has been demonstrated to induce physiological adaptations in aerobic fitness and skeletal muscle oxidative capacity similar to those elicited by traditional moderate-intensity continuous training (MICT), despite a substantially lower total training volume (Gillen & Gibala, 2014). Moreover, these improvements have occurred in healthy, athletic, and clinical populations and may, therefore, offer an effective alternative regime to traditional MICT (Rossow et al., 2010; Whyte, Ferguson, Wilson, Scott, & Gill, 2013).

Despite increasing evidence supporting the efficacy of SIT in improving fitness in a controlled laboratory environment, researchers have contended that due to the supramaximal nature of SIT, this modality is unlikely to be tolerated and followed by the general population (Biddle & Batterham, 2015; Hardcastle, Ray, Beale, & Hagger, 2014;Jung, Little, & Batterham, 2016). These limitations have inspired several attempts to increase tolerance for SIT (e.g., by decreasing exercise volume; Martins et al., 2016; Vollaard & Metcalfe, 2017; Zelt et al., 2014). Recently, Vollaard and Metcalfe (2017) proposed that “ … the focus of SIT research should be moved towards establishing acceptable and effective protocols that involve minimal sprint durations and repetitions” (p. 2443). This is based on the fact that SIT protocols with a reduced volume could elicit health and fitness benefits in a more time-efficient, less strenuous, and more tolerable way than the classic 4-6 repeated 30-second Wingate sprints (Vollaard & Metcalfe, 2017). For example, Gillen et al. (2016) showed that three 20-second “all out” sprints interspersed with two minutes of active recovery performed three times per week significantly improved aerobic fitness (i.e., peak oxygen uptake [VO_2peak]) by 19% in sedentary men, which was similar to traditional MICT, despite a fivefold lower exercise volume and time commitment.

However, even considering a reduced volume of sprint duration and repetition, the SIT protocols are still supramaximal. More practical and less strenuous models of interval training, termed low-volume high-intensity interval training (HIIT), have been developed, involving bouts of maximal or submaximal intensity (e.g., workload corresponding to the power at VO_2peak or peak power output (PPO) or ∼ 90% maximum heart rate [HR_max]), interspersed by shorter recovery periods (i.e., 60 seconds; Gibala, Little, Macdonald, & Hawley, 2012; Little, Safdar, Wilkin, Tarnopolsky, & Gibala, 2010). Based upon the newly proposed classification scheme for interval training (Weston, Taylor, Batterham, & Hopkins, 2014), SIT refers to protocols that involve “all out” or supramaximal efforts in contrast to HIIT that is characterized as protocols in which the training intensity is “near maximal.” Low-volume HIIT is used to describe short intervals bouts (i.e., ≤ 60 seconds) during a short exercise session duration, generally 20 minutes including the recovery periods (Gibala et al., 2012; Little et al., 2010).

Low-volume HIIT improves time trial performance and muscle oxidative potential (Hood, Little, Tarnopolsky, Myslik, & Gibala, 2011; Little et al., 2010) comparable with those shown by “all out” SIT protocols (Burgomaster et al., 2008). Because increases in skeletal muscle oxidative capacity and aerobic fitness are associated with improved metabolic health (Booth & Roberts, 2008), low-volume HIIT likely represents a useful strategy to enhance whole body physiological function and prevent metabolic disease (Vincent et al., 2015). However, while the previously mentioned findings are attractive from the perspective of human physiology, their translation into exercise recommendations for the general population remains a key challenge (Biddle & Batterham, 2015). For example, the commonly cited time-efficiency of low-volume HIIT is questioned. When accounting for the 5-minute warm-up, 10 60-second work bouts and interspersed recovery periods and cool down, total exercise time is at least 30 minutes. Even if low-volume HIIT is performed on fewer days than the current exercise guidelines (i.e., three versus nine days), individuals would still need to free up 30 minutes to participate regularly (Hardcastle et al., 2014). Consequently, time constraints may still pose a problem to exercise adherence. Therefore, it seems important to investigate whether HIIT protocols involving a reduced volume and time commitment elicit similar health and fitness benefits to those found with classic low-volume HIIT (i.e., 10 60-second work bouts at ∼90% of HR_max interspersed with 60 seconds of recovery).

Moreover, although low-volume HIIT is supported by much physiological evidence, it is reasonable to suggest that without concurrent psychological support it may be premature to translate HIIT into public health recommendations. Therefore, there is a growing interest in the ratings of perceived exertion (RPE) and affective responses to more practical models of HIIT (Frazão et al., 2016; Jung, Bourne, & Little, 2014; Kilpatrick & Greeley, 2014; Martinez, Kilpatrick, Salomon, Jung, & Little, 2015; Oliveira, Viana, Pires, Oliveira, & Santos, 2015; Saanijoki et al., 2015). Briefly, RPE is defined as the subjective perception of the intensity of effort, strain, or fatigue during exercise. The simplest and most primitive affective response is “basic affect,” which refers to the intrapersonal or experiential core of all valenced responses (i.e., positive or negative, pleasant or unpleasant). It should be noted that RPE describes what while affective responses emphasize how a person feels during exercise (Hardy & Rejeski, 1989). According to the hedonic theory of motivation (Ekkekakis, 2003), individuals who perceive exercise as pleasant are more likely to become and remain active for a long-term period. Almost all previous studies concerning RPE and affective responses to HIIT have examined only single sessions (Jung et al., 2014; Kilpatrick, Greeley, & Collins, 2015; Martinez et al., 2015; Oliveira et al., 2015). To our knowledge, only one previous study has examined affective responses to a short-term period (two weeks) of HIIT intervention as compared with MICT (Saanijoki et al., 2015). Given that adherence tends to deteriorate over time, and research has demonstrated a repeatedly negative association between RPE and exercise adherence (Bauman et al., 2002), it is important to explore perceived exertion and affective responses over time. The current study addresses this need.

Furthermore, the latest position of the American College of Sports Medicine (Garber et al., 2011) has recognized that exercise that is pleasant and enjoyable can improve a general population adoption and adherence to prescribed exercise programs, and that the use of tools to measure perceived pleasure during prescribed exercise should be considered. Thus, given that low-volume HIIT has been shown to be effective at improving health and fitness, it is relevant to know how individuals perceive this exercise psychologically over time and what aspects of it are related to exercise adherence (Rhodes & Kates, 2015). Clearly, there is a strong necessity to develop time-efficient exercise strategies to improve health and fitness of sedentary and insufficiently active individuals and to maintain these benefits in active individuals. However, these strategies should not be perceived as considerably effortful or aversive, if targeting adherence.

Therefore, this study aimed to examine the short-term effects of the classic low-volume HIIT protocol on psychological and physiological responses and to compare it with an alternative HIIT (i.e., a very-low-volume HIIT) protocol involving half as much volume of work bouts as are in the classic protocol in recreationally active men with no previous experience in HIIT. We hypothesized that participants in the alternative, very-low-volume HIIT intervention would improve fitness to the same extent, but with a lower RPE and a more positive affective response, compared with participants in the low-volume HIIT intervention.

Method

Study Design

We used a repeated measures design to compare psychological (RPE and affective responses) and physiological (heart rate [HR]) responses of individuals during bouts of low-volume and very-low-volume HIIT. A pre/postintervention parallel groups design was used to measure the physiological and fitness effects of the interventions. Before and after the 3-week training period, each participant undertook the following test procedures: (a) initial screening and physical evaluation; (b) maximal incremental exercise test; (c) constant load test at 80% PPO to volitional exhaustion; and (d) Wingate anaerobic test. We familiarized participants with these procedures before any experimental testing began. Each exercise test was separated by at least 48 hours. Participants were asked to avoid vigorous physical activity, caffeinated products, and alcohol consumption 24 hours before the exercise tests and before all HIIT sessions during the 3-week training study and to maintain a good sleeping pattern and normal dietary habits. Participants were permitted to continue with light-to-moderate-intensity activities (i.e., walking), but they were requested not to undertake any formal cardiovascular or strength training activities outside the HIIT training. In addition, two weeks after the end of the training period, participants responded to a questionnaire designed to assess their attitudes, intentions, confidence, and perceived behavioral control (PBC) to participate in HIIT. This study design is summarized in Figure 1.

Figure 1.

Study design and training protocols. HIIT = high-intensity interval training; PPO = peak power output achieved during the incremental test.

Participants

Twenty-three healthy, recreationally active males (M = 21, SD = 1 years; M VO_2peak = 47.2, SD = 2.3 ml·kg⁻¹·min⁻¹) volunteered to participate in the study. We recruited participants via lectures in the university setting. Following baseline testing, participants were assigned to two groups: low-volume HIIT (n = 12) and very-low-volume HIIT (n = 11). Considering that the baseline characteristics of the participants would impact on the outcomes of the research, we used a stratified randomization approach to achieve a balance between groups in terms of baseline characteristics. Thus, we stratified participants according to VO_2peak and Wingate mean power after baseline assessment, and then, we performed a simple randomization (https://www.randomizer.org/) to assign participants into the low-volume and very-low-volume HIIT groups. A no-training control group was not included considering that meta-analytical research has consistently found improvements in aerobic fitness with HIIT (Weston et al., 2014), including superior results compared with traditional MICT (Costa et al., 2018; Milanović, Sporiš, & Weston, 2015). Further, participants recruited for this study were physically active, and it would be unethical require them to stop exercising.

All participants completed a medical history questionnaire before entering the study. The following were the inclusion criteria: (a) classified as apparently healthy by the Physical Activity Readiness Questionnaire; (b) no experience in HIIT; (c) injury-free at the time of this study. The following were the exclusion criteria: (a) any diagnosis of cardiovascular, metabolic, and orthopedic disease; (b) any other contraindications for physical activity; (c) injury during the training period. Participants were informed about all procedures of the study, and all participants gave written informed consent. The study was approved by the University’s Institutional Human Research Ethics Committee, and all participants were informed of the benefits and risks of the investigation prior to signing an informed consent to participate. Six participants dropped out of the study (three from each group) due to either lack of time or injury not related to the training protocol (see Figure 1).

Fitness Testing (Physiological Variables)

Participants performed an incremental test to volitional exhaustion on an electronically braked cycle ergometer (Schoberer Rad Messtechnik, SRM, Germany) to determine VO_2peak using an online gas collection system (Metalyzer® Sport, Metasoft® Studio v.3.9, Cortex Biophysik GmbH, Leipzig, Germany). Power output (W) was measured and recorded at a frequency of one Hz (SRM, 6.40.07, Germany). Participants began pedaling at 50 W for five minutes, and the workload increased by five W every 12 seconds thereafter until volitional fatigue or at the point where pedal cadence fell below 70 rpm for more than five seconds. HR was recorded throughout the test (Accurex+, Polar Electro, Oy, Kempele, Finland). VO_2peak was defined as the highest average oxygen uptake over a 30-second period. PPO was calculated as the average power output (W) over the last minute of the test. Handlebar and seat height were recorded and kept constant throughout baseline and posttesting.

After at least 48 hours recovery, participants performed a constant load time to exhaustion test (TTE) at 80% PPO (McLellan, Cheung, & Jacobs, 1995) on the SRM cycle ergometer. Pedaling was maintained at 80 rpm with no physiological or temporal feedback, and the test was terminated when cadence fell below 70 rpm for < five seconds despite verbal encouragement. The TTE (seconds) was defined as the duration of cycling. Participants reported their RPE by pointing their index finger at the scale, and HR was recorded at 1-minute intervals. Posttesting was performed at the same load (i.e., 80% of PPO at baseline).

On a separate day with at least 48-hour interval, a Wingate anaerobic test was performed starting with a 5-minute warm-up at 50 W, and then participants performed a 30-second Wingate test against a constant braking force of 0.075 kg per kg of body mass, on a computer-controlled cycle ergometer (Monark, Ergomedic, 894 E, Germany). Peak power was calculated as the highest absolute (W) and relative (W·kg⁻¹) power output was recorded during the test. Mean power was calculated as the average absolute (W) and relative (W·kg⁻¹) power output (W) over the 30-second test.

Exercise Training Protocols

Exercise training consisted of nine supervised HIIT sessions over a 3-week period. Participants were requested to complete three sessions per week. Exercise sessions were performed individually on alternate days at the same time of the day to avoid circadian variation on physiological or psychological outcomes. Both protocols began with a 5-minute warm-up at 50 W. HIIT was modeled according to Little et al. (2010), consisting of eight 60-second work bouts at the PPO in the maximal incremental test, interspersed by 75 seconds of low-intensity (50 W) active recovery. Participants in the low-volume HIIT group performed eight, 10, and 12 work bouts in the three sessions of the first, second, and third week of training, respectively. Participants in the very-low-volume HIIT group performed the same protocol, however, with half the volume of work bouts of the low-volume HIIT group (i.e., four, five, and six work bouts in the three sessions of the first, second, and third week of training, respectively). Figure 1 displays the study design and training protocols. All training was performed on Monark cycle ergometers. Measurements of HR, RPE, and affective response were recorded during the final 15 seconds of each 60-second work bout.

Rating of Perceived Exertion (Psychological Variable)

Perceived exertion was defined as the subjective intensity of effort, strain, or fatigue that an individual feels during exercise. Before the maximal incremental exercise test, the meaning of perceived exertion was explained to participants. The Borg Category Ratio (CR-10) scale (Borg, 1998) was used to assess perceived exertion. The Borg CR-10 scale has shown good reliability and validity on healthy individuals against physiological measures, such as HR, blood lactate, oxygen uptake, ventilation, and respiratory rate (Chen, Fan, & Moe, 2002). The low and high perceptual anchors for the RPE scale were established during the maximal exercise test. A rating of 0 (low anchor, nothing at all) was assigned to the lowest exercise intensity, while a rating of 10 (high anchor, very, very hard) was assigned to the highest exercise intensity. RPE values were recorded during the last 15 seconds of each 60-second work bout. Participants were asked to rate what they felt at that moment, pointing their index finger over the number representing their RPE.

Affective Responses (Psychological Variable)

The participants’ affective responses to exercise were assessed using the 11-point bipolar Feeling Scale (FS; Hardy & Rejeski, 1989). Seven verbal anchors are provided, ranging from very good (+5) to very bad (−5) to measure the basic affective response (i.e., pleasure/displeasure) during exercise. This scale presents the following verbal anchors: −5 = very bad; −3 = bad; −1 = fairly bad; 0 = neutral; +1 = fairly good; +3 = good; and +5 = very good. The FS presented correlations ranging from .51 to .88 with the valence scale of the Self-Assessment Manikin and from .41 to .59 with the valence scale of the Affect Grid (Van Landuyt, Ekkekakis, Hall, & Petruzzello, 2000). The intraclass correlation coefficient of the FS during the exercise was .83 (Unick et al., 2015). Participants were familiarized with standard instruction before the incremental test using standard instructions (Agricola et al., 2016). Affective responses were recorded during the last 15 seconds of each 60-second work bout. Participants were asked to rate how they felt at that moment, pointing their index finger over the number representing their affective response.

Attitudes, Intentions, Confidence, and PBC to Participate in HIIT

Two weeks following the end of the training program, participants completed a brief theory of planned behavior (Ajzen, 1991) questionnaire that assessed their intentions, attitudes, confidence, and PBC to participate in HIIT training in the following two weeks, based on previously established measures with acceptable validity and reliability (Armitage & Conner, 1999; Bagozzi & Kimmel, 1995; Manstead & Van Eekelen, 1998; Terry & O’Leary, 1995). The purpose of the questionnaire was to explore whether attitudes toward HIIT, confidence, control, and intentions to perform HIIT differed according to dose of HIIT training experienced during the intervention. The questionnaire was constructed following recent guidelines (Ajzen, 2013). The attitude was assessed via response to the statement “For me, participating in HIIT over the next two weeks would be …” This statement was then paired with six bipolar, 7-point adjective scales to assess both instrumental (useless – useful, worthwhile – not worthwhile, important – unimportant) and affective attitudes (enjoyable – unenjoyable, pleasant – unpleasant, satisfying – unsatisfying; Armitage & Conner, 2001).These items are established and reliable measures of attitude (Babbie, 2001). Three items with a 6-point Likert scale were used to measure intention, PBC, and confidence; for adequate internal consistency (Armitage & Conner, 2001), the mean of the respective three items was used for the analysis. For example: (a) “I intend to participate in HIIT at least three times per week in the next fortnight” (Agree very strongly – Disagree very strongly); (b) “How much personal control do you feel you have in doing HIIT at least three times per week over the next two weeks?” (Very little control – Complete control; Armitage & Conner, 2001); (c) “How conﬁdent are you over the next two weeks that you could participate in HIIT at least three times per week if you wanted to do so?” (Very unconﬁdent – Very conﬁdent; Armitage & Conner, 2001).

Statistical Analyses

A Shapiro–Wilk test confirmed the normal distribution of the data. We reported descriptive data as means and standard deviations unless otherwise stated. To minimize the number of data points, we aggregated the affective, RPE, and %HR_max responses per week (Weeks 1, 2, and 3), which included three HIIT sessions in each one. The last three responses (affective, RPE, and HR) of each HIIT session were considered for statistical analyses, given that the affect felt at the end of the exercise is important for building affective memories respective to the exercise experience (Decker & Ekkekakis, 2017; Zenko, Ekkekakis, & Ariely, 2016). Thus, the data of each week included the averaged responses of the last three work bouts of each HIIT session, over three sessions. To compare the affective, RPE, and HR responses between participants in the two groups during each week, as well as participant attitudes, intentions, confidence, and control two weeks following the end of the training program, we used the independent samples t test. We calculated the effect size (ES) using Hedges’ g and interpreted as follows: 0.20 = small; 0.50 = moderate; 0.80 = large. The effect of training volume on changes on VO_2peak, TTE, and Wingate test power output was analyzed using a Mixed Model 2 (group: low- vs. very-low-volume) × 2 (time: pre vs. post) analysis of variance (ANOVA), with Bonferroni’s post hoc testing applied as needed. Partial eta squared (η_p²) was used as a measure of the ES for the ANOVA.

A Pearson product-moment correlation coefficient was used to examine the possible relationship between affective, RPE, and %HR_max responses in both groups. A power analysis was conducted to detect differences in affect or RPE by one unit for each variable. The power analysis indicated that a repeated measures ANOVA would detect a large ES (f = .45) 80% of the time at .05 alpha level if the total sample size of the study comprised 20 participants (10 in each group). The data were analyzed using SPSS® 20.0 (SPSS, Inc., Chicago, IL), and the significance level was set at p ≤ .05.

Results

Participants of the very-low-volume HIIT group and the low-volume HIIT group were not statistically different in age (M = 21.4, SD = 0.8 years vs. M = 21.1, SD = 1.4 years); height (M = 178.5, SD = 5.6 cm vs. M = 182.5, SD = 8.9 cm); body mass (M = 77.9, SD = 9.3 kg vs. M = 77.7, SD = 11.4 kg); and BMI (M = 24.4, SD = 2.0 kg/m² vs. M = 23.2, SD = 1.8 kg/m²; p > .05). The attendance rate for the training sessions was 97.8% and 97.2% for the low and very-low-volume HIIT groups, respectively. Regarding the completion of the prescribed training protocol, as displayed in Table 1, more work bouts were missed in the low-volume group compared with the very-low-volume group, possibly indicating issues of tolerability/adherence to this volume of training (i.e., lower number of work bouts performed vs. prescribed).

Table 1.

Number of Work Bouts Performed Compared With the Number of Work Bouts Prescribed Over the 3-Week Training Protocol.

	Low-volume HIIT	Very-low-volume HIIT
Week 1	211/216	96/96
Week 2	257/270	120/120
Week 3	284/324	130/144
Total	752/810 (92.8%)	346/360 (96.1%)

Note. Number of repetitions = Number of participants × Number of training sessions per week (3) × Number of work bout for a given week. HIIT = high-intensity interval training.

Figure 2 displays RPE, affective responses, and HR responses over the 3-week training protocol. Participants in the very-low-volume HIIT program experienced lower RPE in Weeks 1 (g = 1.64) and 3 (g = 1.88) and showed a trend toward significance in Week 2 (p = .08; g = 0.81) with a large ES, in comparison with those in the low-volume HIIT program (Figure 2(a)). Likewise, participants in the very-low-volume HIIT group reported more positive affect with a large ES in Week 1 (g = 1.02) and a trend toward significance in Week 3 (p = .06; g = 0.71; Figure 2(b)). However, there was no significant difference in Week 2 despite a moderate ES (p = .14; g = 0.62). The %HR_max was lower in the very-low-volume HIIT group with a large ES in Week 1 (g = 1.32), with similar HR responses (∼86% of HR_max) in Weeks 2 (g = 0.56) and 3 (g = 0.57; Figure 2(c)).

Figure 2.

Rating of perceived exertion (RPE; a), affective responses (b), and heart rate (c) in the very-low-volume (VLV HIIT) and low-volume high-intensity interval training (LV HIIT) groups over 3-week training program. Data are expressed as mean (thick = LV HIIT; dashed = VLV HIIT) and individual data points. * = Difference between groups (p ≤ .05).

In addition, we performed an ancillary analysis using the grand average of the three weeks of training, which showed that participants in the very-low-volume HIIT group, compared with low-volume HIIT, displayed higher affective responses (M = 1.97, SD = 1.62 vs. M = 0.43, SD = 1.52; p = .05; g = 0.93); lower RPE (M = 4.21, SD = 1.35 vs. M = 6.10, SD = 1.06; p = .004; g = 1.50); and similar HR (M = 165.8, SD = 6.7 vs. M = 165.1, SD = 9.6; p = .86; g = 0.08), respectively. We found a large negative correlation between affective response and RPE (r = −.74; p < .01). Interestingly, we did not observe a significant correlation between affective response and HR (r = −.38; p = .12).

Table 2 summarizes the effect of low and very-low-volume HIIT on physical fitness. There was a significant group by time interaction on Wingate absolute, F(1, 16) = 4.28, p = .05; η_p²= 0.21, and relative, F(1, 16) = 4.08, p = .05; η_p²= 0.06, peak power. Post hoc testing showed that only participants in the very-low-volume HIIT program improved their Wingate absolute and relative peak power with a large ES. No other main effect or interaction was statistically significant.

Table 2.

Baseline, Follow-Up Mean (SEM), and Mean Change Measures for Physiological Outcomes.

Variables	Low-volume HIIT (n = 9)				Very-low-volume HIIT (n = 8)
Variables	Baseline	Posttraining	Δ (mean [95% CI])	g	Baseline	Posttraining	Δ (mean [95% CI])	g
Maximum power (W)	283 (14)	304 (13)	18.7 [2.35, 35.0]	1.48	259 (16)	290 (15)	0.75 [−16.3, 17.8]	1.90
VO_2peak (ml·kg⁻¹·min⁻¹)	47.2 (2.2)	48.7 (2.2)	1.86 [−1.67, 5.38]	0.65	47.1 (2.4)	45.5 (2.5)	−2.18 [−6.65, 2.29]	0.62
Wingate PP (W)	1,050 (61)	1,076 (78)	41.2 [−28.5, 110.9]	0.35	1,049 (70)	1,222 (88)*	154.3 [41.7, 266.8]	2.06
Wingate PP (W·kg⁻¹)	14.3 (0.7)	14.6 (0.8)	0.45 [−0.37, 1.27]	0.38	13.5 (0.8)	15.5 (0.9)*	1.74 [0.43, 3.05]	2.22
Wingate MP (W)	678 (38.7)	657.0 (42.0)	−11.3 [−44.5, 22.0]	0.50	713 (44)	729.9 (47.6)	18.2 [−7.4, 43.8]	0.35
Wingate MP (W·kg⁻¹)	9.2 (0.2)	8.9 (0.7)	−0.20 [−0.61, 0.22]	0.56	9.1 (0.2)	10.2 (0.7)	0.93 [−1.03, 2.88]	2.02
Time to exhaustion (s)	649 (51)	781 (98)	226.9 [−90.7, 544.5]	1.61	599 (57)	595 (111)	−3.29 [−208.8, 202.2]	0.04

Note. Hedges’ g was used as a measure of the effect size. HIIT = high-intensity interval training; VO_2peak = peak oxygen uptake; PP = peak power; MP = mean power; Δ = posttraining− pretraining difference; 95%CI = 95% confidence interval. * = Different from baseline (p = .05).

Finally, two weeks following the end of the training period, there was no difference between the very-low-volume and low-volume HITT groups for psychological variables of attitudes, intentions, confidence, and perceived behavioral toward participation in their respective training protocols (Table 3).

Table 3.

Psychological Variables Following a 3-Week HIIT With Different Volume in Recreationally Active Males.

Variable	Low-volume HIIT (n = 9)	Very-low-volume HIIT (n = 8)	g	p
Variable	M (SD)	M (SD)	g	p
Instrumental attitudes	2.62 (0.57)	2.75 (0.64)	0.20	.68
Affective attitudes	3.33 (0.85)	3.33 (0.73)	0.00	1.0
Intentions to engage	3.56 (1.78)	3.25 (1.59)	0.19	.71
Confidence to engage	3.41 (1.37)	2.71 (0.93)	0.59	.24
Perceived behavioral control	3.04 (1.55)	2.54 (1.38)	0.32	.50

Note. Hedges’ g was used as a measure of the effect size. HIIT = high-intensity interval training.

Discussion

We investigated the short-term (three weeks, nine sessions) effects of low- and very-low-volume HIIT on perceived exertion, affective response, and fitness outcomes in active men with no previous experience in HIIT. Our main findings were (a) participants who received the very-low-volume HIIT program reported lower RPE and more positive affective response, compared with participants who were assigned to the low-volume HIIT program; (b) there was a large negative correlation between affective response and RPE over the training period in both groups; (c) there were no significant differences between groups in intentions, attitudes, confidence, and PBC to participate in HIIT in the weeks following cessation of the intervention; (d) there were no improvements in most fitness outcomes, but participants who received very-low-volume HIIT program improved Wingate peak power.

As previously hypothesized, the very-low-volume HIIT group presented lower RPE and higher affective responses over this short-term training period. Overall, participants of the very-low-volume HIIT group reported an RPE equivalent to “somewhat hard” (i.e., 4 on the Borg’s CR-10 scale) and an affective response between “fairly good” and “good” (i.e., +1 to +3 on the FS) in the last three work bouts. However, the low-volume HIIT group reported an RPE between “hard” and “very hard” (i.e., 5 to 7 on the Borg’s CR-10 scale) and an affective response equivalent to “neutral” (i.e., 0 on the FS). Previously, we found similar RPE and affective response in healthy recreationally active men during a single session of low-volume HIIT (10 60-second work bouts at 85%–90% HR_max, 60 s active recovery; Frazão et al., 2016). A total of 98%, 85%, and 59% of these participants reported positive/neutral affective response during the 1st to 3rd, 4th to 7th, and 8th to 10th work bouts in the low-volume HIIT session, respectively (Frazão et al., 2016). In contrast, while the frequency of positive/neutral affective responses during the 1st to 3rd work bouts reported by inactive men was similar (i.e., 91%) to the active group, the rate of positive/neutral affective responses was significantly lower during the 4th to 7th and 8th to 10th work bouts (i.e., 40% and 22%, respectively). Therefore, our current results obtained in a short-term training period confirmed our previous findings with a single session, namely, HIIT with a lower volume of work bouts was perceived as less strenuous and more pleasant.

During HIIT, participants performed repeated work bouts close to 90% HR_max, which generate a cumulative fatigue and exacerbate the stress imposed on the participant (i.e., internal load) over time. Previous researchers have reported an increase in VO₂, HR, blood lactate concentration, and RPE over the work bouts during different HIIT protocols (Tucker, Sawyer, Jarrett, Bhammar, & Gaesser, 2015; Wood et al., 2016). Given that the low-volume HIIT group performed more work bouts, it is reasonable to think that the participants from this group had a higher internal load, probably mediated by a more pronounced metabolic stress (i.e., blood lactate accumulation and pH disturbance), than participants from the very-low-volume HIIT group. In addition, a recent study showed that low-volume high-intensity interval exercise generates a mild delayed-onset muscle soreness 24 hours after exercise, similar to moderate continuous exercise in untrained healthy males (Farias Junior et al., 2017). This result suggests that the very-low-volume HIIT may have even lower delayed-onset muscle soreness, which is particularly important for inexperienced/untrained individuals in HIIT.

Possibly, over the additional work bouts in the low-volume HIIT group, the afferent interoceptive signals from the body to the brain areas related to the generation of the affective response (i.e., prefrontal cortex [PFC] and subcortical areas) may have been intensified. The neural basis of the dual-mode model states that during high-intensity exercise (i.e., above the ventilatory threshold), the functional capacity of the PFC becomes challenged by the intensified interoceptive cues (Ekkekakis, Parfitt, & Petruzzello, 2011). This induces a deregulation of the PFC, resulting in a negative affective response, mainly driven by subcortical areas (i.e., amygdala; Ekkekakis et al., 2011). Recently, Tempest, Eston, and Parfitt (2014) confirmed the limited functional capacity of the PFC at respiratory compensation point and at exhaustion during an incremental test in healthy individuals, coinciding with participants reporting displeasure at these points. Despite the differences between an incremental test and a HIIT session, these findings (Tempest et al., 2014) may, at least in part, explain our results. However, we highlight that the dual-mode model was initially proposed and tested using continuous exercise protocols and maximal exercise test (Ekkekakis et al., 2011), and the extrapolation of the dual-mode model to HIIT has been recently questioned (Biddle & Batterham, 2015; Jung et al., 2016). Therefore, future work ought to test the dual-mode model in HIIT considering its differences from continuous exercise protocols and maximal exercise testing.

Another interesting finding of our study was the strong negative correlation between affective response and RPE in both groups, while a nonsignificant negative correlation of small magnitude was found between basic affect and HR. Oliveira et al. (2015) showed that RPE, but not HR or VO₂, predicted affective response during continuous and high-intensity interval exercise. The authors suggested that the pattern of affective response seemed to be modulated not only by the intensity of exercise but mostly by how the individuals perceived the intensity. More recently, we observed a negative correlation between RPE and affective response during low-volume HIIT in active (r = −.74) and inactive individuals (r = −.51; Frazão et al., 2016). Our results support these findings, given that the individuals who reported higher RPE presented lower affective response. Thus, from a practical point of view, the RPE should be considered a valuable tool in the prescription and monitoring of the exercise intensity during HIIT when the main goal is to promote improvements in affective response and to avoid aversive feelings related to this type of training (Oliveira et al., 2015).

To date, few studies have investigated the affective responses to HIIT (Vollaard, Metcalfe, & Williams, 2017), with some of them showing negative (Oliveira, Slama, Deslandes, Furtado, & Santos, 2013; Saanijoki et al., 2015; Wood et al., 2016) while others found positive affective responses (Jung et al., 2014; Martinez et al., 2015) during different HIIT protocols. However, based on previous studies (Jung et al., 2014; Kilpatrick et al., 2015; Martinez et al., 2015) and the present findings, it seems to be clear that HIIT protocols with fewer work bouts at intensities between 80% and 100% of HR_max with shorter lengths (∼60 s or less) may be perceived as less strenuous and more pleasant for both active and inactive individuals (Frazão et al., 2016; Jung et al., 2014; Kilpatrick et al., 2015; Martinez et al., 2015), especially in the end of the training session. The fact that a lower volume of HIIT is perceived as more pleasant is of particular interest considering that the affective responses to exercise has been demonstrated in two recent systematic reviews to predict future exercise behavior in both aerobic exercise (Rhodes & Kates, 2015) and resistance exercise (Rhodes, Lubans, Karunamuni, Kennedy, & Plotnikoff, 2017). For instance, Williams et al. (2008) found that the affective response to aerobic exercise of moderate intensity predicted physical activity at six and 12 months later. The authors showed that for each additional positive point in the FS individuals performed 38 and 41 more minutes of physical activity per week at six and 12 months, respectively. Thus, improved affective and perceived exertion responses with very-low-volume HIIT protocols may likely foster adherence in the long term. However, we highlight that perceived confidence to engage in HIIT in a lab setting with supervision and encouragement from exercise physiologists does not necessarily translate into confidence to undertake such exercise independently (Hardcastle et al., 2014). This may be more problematic when less active participants with no previous experience in HIIT perform protocols with several work bouts or work bouts with longer lengths.

Review-level evidence has confirmed the positive relationship between affective responses during exercise and future participation in physical activity (Rhodes & Kates, 2015). However, although positive affect was higher and RPE was lower in the very-low-volume HIIT group in the present study, there was no difference between groups in intentions, attitudes, confidence, and PBC to participate in future HIIT training. It is important to note that although exercise intentions may translate into exercise participation, it is not clear whether or to what extent these intentions are translated into future exercise participation. For instance, it has been demonstrated that stronger intentions to do exercise in young adults (18–25 years) was not associated with exercise behavior (Poobalan, Aucott, Clarke, & Smith, 2012). In addition, the failure to find group differences in behavior, attitudes, and confidence may be because both groups consisted of active young men who generally enjoyed physical activity and had high motivation to participate in the high-intensity exercise.

Interestingly, our study was the first to find that a short-term HIIT program with a very-low-volume and submaximal stimulus (i.e., 4–6 60-second work bouts at ∼90% of HR_max) improved these HIIT beginners’ Wingate peak power, while there was no change in Wingate peak power for the low-volume group. While the reasons for this failure to find a Wingate peak power change in the low volume group are unknown, a very recent meta-analysis regarding SIT, including 34 studies with 418 participants, concluded that improvement in aerobic fitness is not attenuated with lower volume (Vollaard et al., 2017). On the contrary, aerobic fitness could be improved with even a lower number of sprints (i.e., −1.2% decrease in VO_2peak for every two additional sprints; Vollaard et al., 2017). The present results give some support to that meta-analysis, respective to the improvement in anaerobic capacity with fewer work bouts, even though the underlying mechanisms for these results are unclear. Future studies in this field are certainly warranted. Nonetheless, in our study, neither low- nor very-low-volume HIIT was sufficient to induce significant improvements in maximal power output during the incremental test, VO_2peak, TTE with a constant load, and Wingate mean power over the 3-week training period. These results were unexpected as we hypothesized that both the very-low-volume HIIT participants and the low-volume HIIT group would achieve similar improvements in aerobic and anaerobic fitness. Considering that our participants had no prior experience with HIIT, we expected the implementation of this new stimulus in their training routine would improve their aerobic fitness in the short term, as it has been previously observed (Gibala et al., 2012). One possible explanation is that our sample was composed of active men with good physical fitness, as these participants have had little room for change, especially considering the short training period. Thus, a ceiling effect cannot be ruled out. In addition, the typical duration of HIIT protocols normally ranges from 8 to 16 weeks (Costa et al., 2018; Weston et al., 2014), although some studies use shorter durations (e.g., 2-4 weeks). Hence, it is possible that a longer intervention protocol could have presented significant improvements in the fitness measures.

Strengths of this study and its main contribution to scientific knowledge center around our exploration of psychological responses (perceived exertion, affective state, attitudes, intentions, confidence, and perceived control) toward HIIT protocols with different volumes, both during training and over time, rather than from a single bout of exercise as has been the research record to date. The main limitations of this study include the absence of a no-training control group, our failure to monitor participants’ physical activities, sleep, and dietary patterns outside the HIIT program and our restricted small sample of healthy, young, and physically active men. Researchers should consider these limitations when conducting future investigations. Further, measurement of blood lactate or gas analyses to evaluate whether the higher contribution of the anaerobic metabolism, mainly in the last work bouts, may be exacerbating the RPE in the participants from of the low-volume HIIT group is warranted. Also, future studies should test whether very-low-volume HIIT would result in lower delayed-onset muscle soreness, compared with the low-volume HIIT. Finally, the psychological and physiological responses in the long term of varying the volume of HIIT are of special interest.

In conclusion, we found that three weeks of very-low-volume HIIT of 4-6 60-second work bouts at ∼90%HR_max elicited participant’s perceptions of the exercise as less strenuous and more pleasant than the classic low-volume HIIT of 8-12 60-second work bouts at ∼90%HR_max in young active men with no previous HIIT experience. Despite the improvement in anaerobic capacity (i.e., Wingate peak power) among very-low-volume HIIT participants, both training programs failed to induce significant changes in most aerobic and anaerobic fitness outcomes over this 3-week training period. As the affective and RPE responses were more favorable to exercise adherence during the very-low-volume HIIT program, it would be interesting to further investigate whether this protocol is sufficient to induce improvements in aerobic and anaerobic fitness outcomes over a longer training period. Moreover, further studies should investigate whether the very-low-volume HIIT can be successfully implemented and maintained in real-life settings with less active participants and to better understand what health- and fitness-related changes may stem from this exercise. From a practical perspective, coaches may consider very-low-volume HIIT as an alternative training method for enhancing affective responses, perceived exertion, and anaerobic fitness in active individuals, especially when they have limited time for exercise. It remains a concern that even very-low-volume HIIT still involves strenuous work that, on a sustained basis, may challenge an individual’s exercise preference for and tolerance of exercise intensity.

Footnotes

Article Notes

References

Agricola

P. M. D.

da Silva Machado

D. G.

de Farias Junior

L. F.

do Nascimento Neto

L. I.

Fonteles

A. I.

da Silva

S. K. A.

Okano

A. H.

(2016) Slow down and enjoy: The effects of cycling cadence on pleasure. Perceptual and Motor Skills 0(0): 1–15. doi:10.1177/0031512516672774.

Ajzen

(1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes 50(2): 179–211. doi:10.1016/0749-5978(91)90020-T.

Ajzen, I. (2013). Theory of planned behaviour questionnaire. Measurement instrument database for the social science. Retrieved from http://www.midss.org/content/theory-planned-behaviour-questionnaire.

Armitage

C. J.

Conner

(1999) The theory of planned behaviour: Assessment of predictive validity and ‘perceived control’. British Journal of Social Psychology 38: 35–54. doi:10.1348/014466699164022.

Armitage

C. J.

Conner

(2001) Efficacy of the theory of planned behaviour: A meta-analytic review. British Journal of Social Psychology 40: 471–499. doi:10.1348/014466601164939.

Babbie, E. (2001). The practice of social research. The practice of social research (9th ed.). Wadsworth/Thomson Learning.

Bagozzi

R. P.

Kimmel

S. K.

(1995) A comparison of leading theories for the prediction of goal directed behaviours. British Journal of Social Psychology 34(4): 437–461. doi:10.1111/j.2044-8309.1995.tb01076.x.

Bauman

A. E.

Sallis

J. F.

Dzawaltowski

D. A.

Owen

Dzewaltowski

D. A.

Owen

(2002) Toward a better understanding of the influences on physical activity: The role of determinants, correlates, causal variables, mediators, moderators, and confounders. American Journal of Preventive Medicine 23(2 Suppl): 5–14. doi:10.1016/S0749-3797(02)00469-5.

Biddle

S. J. H.

Batterham

A. M.

(2015) High-intensity interval exercise training for public health: A big HIT or shall we HIT it on the head? International Journal of Behavioral Nutrition and Physical Activity 12(95): 1–8. doi:10.1186/s12966-015-0254-9.

10.

Booth

F. W.

Roberts

C. K.

(2008) Linking performance and chronic disease risk: Indices of physical performance are surrogates for health. British Journal of Sports Medicine 42(12): 950–952. doi:10.1136/bjsm.2008.052589.

11.

Borg

G. A.

(1998) Borg’s perceived exertion and pain scales, Champaign, IL: Human Kinetics.

12.

Burgomaster, K. A., Howarth, K. R., Phillips, S. M., Rakobowchuk, M., MacDonald, M. J., McGee, S. L., & Gibala, M. J. (2008). Similar metabolic adaptations during exercise after low volume sprint interval and traditional endurance training in humans. The Journal of Physiology, 586(1), 151–160. doi:10.1113/jphysiol.2007.142109.

13.

Chen

M. J.

Fan

Moe

S. T.

(2002) Criterion-related validity of the Borg ratings of perceived exertion scale in healthy individuals: A meta-analysis. Journal of Sports Sciences 20(11): 873–899. doi:10.1080/026404102320761787.

14.

Costa

E. C.

Hay

J. L.

Kehler

D. S.

Boreskie

K. F.

Arora

R. C.

Umpierre

Duhamel

T. A.

(2018) Effects of high-intensity interval training versus moderate-intensity continuous training on blood pressure in adults with pre- to established hypertension: A systematic review and meta-analysis of randomized trials. Sports Medicine 48(9): 2127–2142. doi:10.1007/s40279-018-0944-y.

15.

Decker

E. S.

Ekkekakis

(2017) More efficient, perhaps, but at what price? Pleasure and enjoyment responses to high-intensity interval exercise in low-active women with obesity. Psychology of Sport and Exercise 28: 1–10. doi:10.1016/j.psychsport.2016.09.005.

16.

Ekkekakis

(2003) Pleasure and displeasure from the body: Perspectives from exercise. Cognition Emotion 17(2): 213–239. doi:10.1080/02699930244000282.

17.

Ekkekakis

Parfitt

Petruzzello

S. J.

(2011) The pleasure and displeasure people feel when they exercise at different intensities: Decennial update and progress towards a tripartite rationale for exercise intensity prescription. Sports Medicine (Auckland, N.Z.) 41(8): 641–671. doi:10.2165/11590680-000000000-00000.

18.

Farias Junior

L. F.

Browne

R. A. V.

Frazão

D. T.

Dantas

T. C. B.

Silva

P. H. M.

Freitas

R. P. A.

Costa

E. C.

(2017) Effect of low-volume high-intensity interval exercise and continuous exercise on delayed-onset muscle soreness in untrained healthy males. Journal of Strength and Conditioning Research. . Advance online publication. doi:10.1519/JSC.0000000000002059.

19.

Frazão

D. T.

De Farias

L. F.

Dantas

T. C. B.

Krinski

Elsangedy

H. M.

Prestes

Costa

E. C.

(2016) Feeling of pleasure to high-intensity interval exercise is dependent of the number of work bouts and physical activity status. PLoS One 11(3): 1–16. doi:10.1371/journal.pone.0152752.

20.

Garber

C. E.

Blissmer

Deschenes

M. R.

Franklin

B. A.

Lamonte

M. J.

Lee

I.-M.

Swain

D. P.

(2011) Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Medicine & Science in Sports & Exercise 43(7): 1334–1359. doi:10.1249/MSS.0b013e318213fefb.

21.

Gibala

M. J.

Little

J. P.

Macdonald

M. J.

Hawley

J. A.

(2012) Physiological adaptations to low-volume, high-intensity interval training in health and disease. Journal of Physiology 590(5): 1077–1084. doi:10.1113/jphysiol.2011.224725.

22.

Gillen

J. B.

Gibala

M. J.

(2014) Is high-intensity interval training a time-efficient exercise strategy to improve health and fitness? Applied Physiology, Nutrition, and Metabolism 39(3): 409–412. doi:10.1139/apnm-2013-0187.

23.

Gillen

J. B.

Martin

B. J.

MacInnis

M. J.

Skelly

L. E.

Tarnopolsky

M. A.

Gibala

M. J.

(2016) Twelve weeks of sprint interval training improves indices of cardiometabolic health similar to traditional endurance training despite a five-fold lower exercise volume and time commitment. PLoS One 11(4): 1–14. doi:10.1371/journal.pone.0154075.

24.

Hardcastle

S. J.

Ray

Beale

Hagger

M. S.

(2014) Why sprint interval training is inappropriate for a largely sedentary population. Frontiers in Psychology 5: 1505.. doi:10.3389/fpsyg.2014.01505.

25.

Hardy

C. J.

Rejeski

W. J.

(1989) Not what, but how one feels: The measurement of affect during exercise. Journal of Sport & Excercise Psychology 11: 304–317.

26.

Hood

M. S.

Little

J. P.

Tarnopolsky

M. A.

Myslik

Gibala

M. J.

(2011) Low-volume interval training improves muscle oxidative capacity in sedentary adults. Medicine and Science in Sports and Exercise 43(10): 1849–1856. doi:10.1249/MSS.0b013e3182199834.

27.

Jung

M. E.

Bourne

J. E.

Little

J. P.

(2014) Where does HIT fit? An examination of the affective response to high-intensity intervals in comparison to continuous moderate- and continuous vigorous-intensity exercise in the exercise intensity-affect continuum. PLoS One 9(12): 1–18. doi:10.1371/journal.pone.0114541.

28.

Jung

M. E.

Little

J. P.

Batterham

A. M.

(2016) Commentary: Why sprint interval training is inappropriate for a largely sedentary population. Frontiers in Psychology 6: 1999.. doi:10.3389/fpsyg.2015.01999.

29.

Kilpatrick

M. W.

Greeley

S. J.

(2014) Exertional responses to sprint interval training: A comparison of 30sec. and 60-sec. conditions. Psychological Reports 114(3): 854–865. doi:10.2466/06.15.PR0.114k27w8.

30.

Kilpatrick

M. W.

Greeley

S. J.

Collins

L. H.

(2015) The impact of continuous and interval cycle exercise on affect and enjoyment. Research Quarterly for Exercise and Sport 86(3): 244–251. doi:10.1080/02701367.2015.1015673.

31.

Little

J. P.

Safdar

Wilkin

G. P.

Tarnopolsky

M. A.

Gibala

M. J.

(2010) A practical model of low-volume high-intensity interval training induces mitochondrial biogenesis in human skeletal muscle: Potential mechanisms. The Journal of Physiology 588(Pt 6): 1011–1022. doi:10.1113/jphysiol.2009.181743.

32.

Manstead

A. S. R.

Van Eekelen

S. A. M.

(1998) Distinguishing between perceived behavioral control and self-efficacy in the domain of academic achievement intentions and behaviors. Journal of Applied Social Psychology 28(15): 1375–1392. doi:10.1111/j.1559-1816.1998.tb01682.x.

33.

Martinez

Kilpatrick

M. W.

Salomon

Jung

M. E.

Little

J. P.

(2015) Affective and enjoyment responses to high-intensity interval training in overweight-to-obese and insufficiently active adults. Journal of Sport and Exercise Psychology 37(2): 138–149. doi:10.1123/jsep.2014-0212.

34.

Martins

Kazakova

Ludviksen

Mehus

Wisloff

Kulseng

King

(2016) High-intensity interval training and isocaloric moderate-intensity continuous training result in similar improvements in body composition and fitness in obese individuals. International Journal of Sport Nutrition and Exercise Metabolism 26(3): 197–204. doi:10.1123/ijsnem.2015-0078.

35.

McLellan

T. M.

Cheung

S. S.

Jacobs

(1995) Variability of time to exhaustion during submaximal exercise. Canadian Journal of Applied Physiology = Revue Canadienne de Physiologie Appliquee 20(1): 39–51. doi:10.1139/h95-003.

36.

Milanović

Sporiš

Weston

(2015) Effectiveness of high-intensity interval training (HIT) and continuous endurance training for VO2max improvements: A systematic review and meta-analysis of controlled trials. Sports Medicine 45(10): 1469–1481. doi:10.1007/s40279-015-0365-0.

37.

Oliveira

B. R. R.

Slama

F. A.

Deslandes

A. C.

Furtado

E. S.

Santos

T. M.

(2013) Continuous and high-intensity interval training: Which promotes higher pleasure? PLoS One 8(11): e79965.. doi:10.1371/journal.pone.0079965.

38.

Oliveira

B. R. R.

Viana

B. F.

Pires

F. O.

Oliveira

M. J.

Santos

T. M.

(2015) Prediction of affective responses in aerobic exercise sessions. CNS & Neurological Disorders Drug Targets 14(9): 1214–1218. doi:10.2174/1871527315666151111121924.

39.

Poobalan

A. S.

Aucott

L. S.

Clarke

Smith

W. C. S.

(2012) Physical activity attitudes, intentions and behaviour among 18-25 year olds: A mixed method study. BMC Public Health 12(1): 1,. doi:10.1186/1471-2458-12-640.

40.

Rhodes

R. E.

Kates

(2015) Can the affective response to exercise predict future motives and physical activity behavior? A systematic review of published evidence. Annals of Behavioral Medicine 49(5): 715–731.

41.

Rhodes

R. E.

Lubans

D. R.

Karunamuni

Kennedy

Plotnikoff

(2017) Factors associated with participation in resistance training: A systematic review. British Journal of Sports Medicine 51(20): 1466–1472. doi:10.1136/bjsports-2016-096950.

42.

Rossow

Yan

Fahs

C. A.

Ranadive

S. M.

Agiovlasitis

Wilund

K. R.

Fernhall

(2010) Postexercise hypotension in an endurance-trained population of men and women following high-intensity interval and steady-state cycling. American Journal of Hypertension 23(4): 358–367. doi:10.1038/ajh.2009.269.

43.

Saanijoki, T., Nummenmaa, L., Eskilinen, J.-J., Savolanen, A. M., Vahlberg, T., Kalliokoski, K. K., & Hannukainen, J. C. (2015). Affective responses to repeated sessions of high-intensity interval training. Medicine & Science in Sports & Exercise, 47(12), 2604–2611. doi:10.1249/MSS.0000000000000721.

44.

Sequeira

Cruz

Pinto

Santos

Marques

(2011) Prevalence of barriers for physical activity in adults according to gender and socioeconomic status. British Journal of Sports Medicine 45(15): A18–A19. doi:10.1136/bjsports-2011-090606.59.

45.

Tempest

G. D.

Eston

R. G.

Parfitt

(2014) Prefrontal cortex haemodynamics and affective responses during exercise: A multi-channel near infrared spectroscopy study. PLoS One 9(5): 1–9. doi:10.1371/journal.pone.0095924.

46.

Terry

D. J.

O’Leary

J. E.

(1995) The theory of planned behaviour: The effects of perceived behavioural control and self-efficacy. British Journal of Social Psychology 34(2): 199–220. doi:10.1111/j.2044-8309.1995.tb01058.x.

47.

Tucker

W. J.

Sawyer

B. J.

Jarrett

C. L.

Bhammar

D. M.

Gaesser

G. A.

(2015) Physiological responses to high-intensity interval exercise differing in interval duration. Journal of Strength and Conditioning Research 29(12): 3326–3335. doi:10.1519/JSC.0000000000001000.

48.

Unick

J. L.

Strohacker

Papandonatos

G. D.

Williams

O’Leary

K. C.

Dorfman

Wing

R. R.

(2015) Examination of the consistency in affective response to acute exercise in overweight and obese women. Journal of Sport and Exercise Psychology 37(5): 534–546. doi:10.1123/jsep.2015-0104.

49.

Van Landuyt

L. M.

Ekkekakis

Hall

E. E.

Petruzzello

S. J.

(2000) Exercise psychology throwing the mountains into the lakes: On the perils of nomothetic conceptions of the exercise-affect relationship. Journal of Sport & Exercise Psychology 22(3): 208–234.

50.

Vincent

Lamon

Gant

Vincent

P. J.

MacDonald

J. R.

Markworth

J. F.

Hickey

A. J. R.

(2015) Changes in mitochondrial function and mitochondria associated protein expression in response to 2-weeks of high intensity interval training. Frontiers in Physiology 6: 1–8. doi:10.3389/fphys.2015.00051.

51.

Vollaard

N. B.

Metcalfe

R. S. S.

Williams

(2017) Effect of number of sprints in a SIT session on change in VO2max: A meta-analysis. Medicine and Science in Sports and Exercise 49: 1147–1156. doi:10.1249/MSS.0000000000001204.

52.

Vollaard

N. B. J.

Metcalfe

R. S.

(2017) Research into the health benefits of sprint interval training should focus on protocols with fewer and shorter sprints. Sports Medicine 47(12): 2443–2451. doi:10.1007/s40279-017-0727-x.

53.

Weston

Taylor

K. L.

Batterham

A. M.

Hopkins

W. G.

(2014) Effects of low-volume high-intensity interval training (HIT) on fitness in adults: A meta-analysis of controlled and non-controlled trials. Sports Medicine 44(7): 1005–1017. doi:10.1007/s40279-014-0180-z.

54.

Whyte

L. J.

Ferguson

Wilson

Scott

R. A.

Gill

J. M. R.

(2013) Effects of single bout of very high-intensity exercise on metabolic health biomarkers in overweight/obese sedentary men. Metabolism: Clinical and Experimental 62(2): 212–219. doi:10.1016/j.metabol.2012.07.019.

55.

Williams

D. M.

Dunsiger

Ciccolo

J. T.

Lewis

B. A.

Albrecht

A. E.

Marcus

B. H.

(2008) Acute affective response to a moderate-intensity exercise stimulus predicts physical activity participation 6 and 12 months later. Psychology of Sport and Exercise 9(3): 231–245. doi:10.1016/j.psychsport.2007.04.002.

56.

Wood

K. M.

Olive

LaValle

Thompson

Greer

Astorino

T. A.

(2016) Dissimilar physiological and perceptual responses between sprint interval training and high-intensity interval training. Journal of Strength and Conditioning Research 30(1): 244–250. doi:10.1519/JSC.0000000000001042.

57.

World Health Organization (2011) World health statistics 2011, Geneva, Switzerland: Author.

58.

Zelt

J. G. E.

Hankinson

P. B.

Foster

W. S.

Williams

C. B.

Reynolds

Garneys

Gurd

B. J.

(2014) Reducing the volume of sprint interval training does not diminish maximal and submaximal performance gains in healthy men. European Journal of Applied Physiology 114(11): 2427–2436. doi:10.1007/s00421-014-2960-4.

59.

Zenko

Ekkekakis

Ariely

(2016) Can you have your vigorous exercise and enjoy it too? Ramping intensity down increases postexercise, remembered, and forecasted pleasure. Journal of Sport & Excercise Psychology 38: 149–159.