Relationships between perceived measures of internal load and wellness status during overseas futsal training camps.

Exercise and sport practitioners frequently utilize rating of perceived exertion (RPE) to evaluate the players' psychophysiological strains during training sessions. The subjective rating of physical exertion level during sports training has been shown to have a reciprocal relationship with wellness status during periodic training or competitive seasons. However, the relationship between subjective physical exertions and wellness status during short-term overseas training camps (OTCs) has not been extensively investigated. This study aimed to examine the perceived responses of physical exertions [session-RPE (sRPE), training monotony, and training strain] and wellness status (fatigue, sleep, delayed onset muscle soreness, stress, and mood) measures in elite young adult futsal players from four separate OTCs with different training tasks. Twenty-seven U-20 male national team futsal players voluntarily participated in this study. The players recruited for OTCs were based on their performance during domestic training camps and the tactical demand of the team. The task of each OTCs was defined as: 1) 1st OTC = game-based camp (n = 14); 2) 2nd and 3rd OTC = training-based camp (n = 20 and n = 17, respectively); and 3) 4th OTC = pre-tournament camp (n = 14). The OTCs consisted of 11 training sessions (18.9 hours) and 16 friendly matches (23.8 hours). During daily training sessions and friendly matches, sRPE was used to quantify training load (TL). Additionally, a five-elements general wellness questionnaire was used to evaluate daily wellness status in the morning. The results demonstrated that the mean and sum sRPE in the game-based OTCs were significantly lower compared to the mean sRPE [p < 0.01, effect size (ES) = -4.8; p < 0.01, ES = -2.9] and sum sRPE in the training-based OTCs (p < 0.01, ES = -3.6; p < 0.01, ES = -3.1). The mean (p = 0.01; ES = -2.0) and sum sRPE (p < 0.01; ES = -3.4) in the game-based OTC were also lower than that in the pre-tournament OTC. Conversely, the wellness scores in the game-based OTC were higher compared to the training-based (p = 0.01; ES = 1.8) and the pre-tournament OTCs (p < 0.01; ES = 1.6). There was a negative relationship between mean and sum sRPE and all wellness scores (mean sRPE = r = -0.441 ~ -0.575, p < 0.001; sum sRPE = r = -0.41 ~ -0.559, p < 0.001). Our findings suggested that responses to training sessions, derived from mean and sum sRPE and wellness scores, are dependent upon the task-specific nature of OTCs among elite futsal players. Utilization of mean and sum sRPE and wellness measures to monitor the psychophysiological health during short-term OTCs is recommended.

Introduction

Futsal is a variant sport of soccer played indoors on either a wood or artificial floor surface within an area of 38–42 m (length) and 20–25 m (width). The game of futsal requires four field players and one goalkeeper on each team with no limit on the number of substitutions. The typical characteristics of futsal include vigorous game intensity, rapid decision-making, high physiological loads, psychological stress, and heightened emotional states [1, 2]. For example, Sarmento et al. [3] reported that the most common tactical actions to score in the Spanish Primera futsal league were the defense-to-offense transitions and positional play, which are characteristic of heavy workload through short-distance sprints and continuous running patterns during offensive plays. Furthermore, the locomotor demand during the futsal match consists of intermittent high frequency running, rapid change of direction, acceleration, and deceleration in field playing positions [4].

Integrating training and match load monitoring throughout a season is important for optimizing performance outcomes [5]. In professional futsal players, tactical demand, match fixtures, and ranking strategy are essential considerations for appropriate periodization during a season [6]. Conversely, identifying players’ competency via short-term training periods during training camps (TCs) is an essential process to ensure the readiness of national teams prior to major tournaments [7]. This period is a crucial stage for helping coaches and strength and conditioning practitioners tabulate the upcoming training program to optimize individual and team performance. One method commonly used to evaluate the strengths and weaknesses of a team’s performance during pre-tournament preparation is to conduct overseas training camps (OTCs) [8-10]. Furthermore, engagement in OTCs increases motivation and mental toughness from exposure to different opponents playing styles that are unavailable in domestic competitions [11]. However, most importantly, more matches during a congested international tournament may also contribute additional psychological and physiological strain, requiring players to develop greater resilience. Thus, OTCs provide opportunities for the players to be familiar with daily routines and psychophysiological demands typical of a tournament schedule. Through comprehensive monitoring of cycle changes in players (such as external load, internal load, wellness status, and readiness for training and match), coaches and practitioners can implement appropriate training programmes and recovery strategies in optimizing the team performance during the camps [12].

Quantification of perceived exertion in response to exercise engagement is one popular method of evaluating physiological strain during training/competition. To date, Borg CR-10 is extensively used to subjectively measure physical exertion during sports training due to its simplicity and accessibility [13]. Subsequently, the Borg CR-10 is used throughout a training bout to quantify the training experience regarding training intensity and duration, known as session-RPE (sRPE) [14]. The validity and reliability of the sRPE in sports training studies has been systematically reviewed by Haddad et al. [15].

Apart from training monitoring, utilizing assessments of stress, recovery, and sleep are also essential factors in understanding players’ health condition and wellness status [16, 17]. One common tool to evaluate these variables is the general wellness questionnaire modified by Hopper index [18, 19]. The validity and reliability of the wellness assessments during sports training has been demonstrated in both individual [20] and team sports [21] settings.

The intensity of TL and wellness status depends on the types of training and the objectives of the session [22]. The paradoxical relationship between internal load and wellness status has been reported throughout a season in both soccer [23, 24] and futsal players [8, 16]. We recently demonstrated a moderate effect size (ES) and negative correlation between external/internal TL and muscular perceptions [i.e. delayed onset muscle soreness (DOMS) and fatigue] during a 7-day short-term domestic TC in elite U-20 futsal players [16]. These findings seem to be workload-dependent. Conversely, Chen et al. [8] reported a poor relationship between TL and wellness scores during the first period of domestic TCs (consisting of physical and fitness examination, performance evaluation, etc.) and an international tournament in futsal players. However, the TL and wellness scores during domestic TCs, with a high accumulation of TL and invitational tournaments with congested schedules, were negatively correlated. Additionally, one of our previous reports demonstrated that a 5-day short-term OTC with game-based tasks had no negative impact on wellness status in senior futsal national team players [11].

In light of the abovementioned studies, there seems to be a scarcity of literature regarding TL and wellness status during futsal OTCs. Such information may help coaches and sports practitioners in proper decision-making for training and recovery strategies, even competition management. Consequently, coaches can focus the game tasks and match analysis in relation to individual and collective performance when these pre-match preparations are well organized [25, 26]. Therefore, the purpose of this study was twofold. Firstly, to identify characteristics of the perceived effect of training exertion and wellness status in elite young adult futsal players during different training tasks in OTCs. Secondly, the study aimed to examine the relationship between perceived responses of exercise engagement and the wellness status during OTCs. It was hypothesized that perceived exertion level during training and wellness status would vary from camp to camp. The secondary hypothesis was that there would be a negative relationship between all wellness indices and subjective physical exertion during exercise in OTCs.

Materials and methods

Experimental approach to the problem

This study was an observational study that aimed to examine the characteristics of perceived measures of internal TL and wellness status. Daily subjective measures of sRPE and general wellness questionnaire were implemented in four separate OTCs during pre-tournament preparation of a bi-annual continental tournament between July 2018- June 2019. The duration and number of players who participated in the OTC were: 1) 1st OTC (game-based task): 6 days, 14 players (July 28th–August 2nd 2018); 2) 2nd OTC (training-based task): 5 days, 20 players (November 19th–23rd 2018); 3rd OTC (training-based task): 6 days, 17 players (April 7th–12th 2019); 4th OTC (pre-tournament task): 10 days, 14 players (June 1st–10th 2019). Overall, the OTCs consisted of 11 training sessions (18.9 hours) and 16 friendly matches (23.8 hours). Over the data collection period, training load and wellness status were monitored daily. The training schedule is presented in Table 1.

Table 1

The training schedule of the overseas training camps.

Training camps	Day 1	Day 2	Day 3	Day 4	Day 5	Day 6	Day 7	Day 8	Day 9	Day 10
1st Camp (n = 14)	Travelling	Match	Match	Match	Match
Game-based camp	Training
July 28th–August 2nd 2018
2nd Camp (n = 20)	Travelling	Friendly Match	Friendly Match	Training	Friendly Match Travelling
Training-based camp
November 19th–23rd 2018
3rd Camp (n = 17)	Travelling	Friendly Match Training	Training	Friendly Match Training	Training	Friendly Match Travelling
Training-based camp	Training
April 7th–12th 2019	Friendly Match
4th Camp (n = 14)	Travelling	Training	Friendly Match	Training	Friendly Match	Training	Friendly Match	Rest	Friendly Match	Travelling
Pre-tournament camp	Friendly Match
June 1st–10th 2019

Participants

Twenty-seven (twenty-four outfield players and three goalkeepers) male futsal players voluntarily participated this study (age = 17.93 ± 0.87 yrs; height = 1.71 ± 0.07 m; body weight = 65.39 ± 9.39 kg; body fat = 12.54 ± 2.76%; maximal aerobic capacity = 51.98 ± 3.07 ml.kg-1.min-1). Player recruitment for the OTCs was based on their performance during domestic TC and the tactical demand of the team. In this study, the number of players who participated in the OTCs was ten players for all camps, one player for 3 camps, seven players for 2 camps, and nine players for 1 camp. Eligibility criteria for participation in this study were that the players did not miss more than two consecutive training sessions during the study period. The players signed written informed consent forms at the point of recruitment and were all familiarized with testing procedures. This study was approved by the Institution Board of Human Ethics Committee (UT-IRB-2018-068) and undertaken in accordance with the Declaration of Helsinki and its later amendments in 2013.

Design and procedure

The experimental procedure is described in our recent studies [8, 9]. The players stayed in a domestic hotel close to an airport one night before international travel. The individual RPE and general wellness questionnaire data were collected and assessed after traveling. For TL monitoring, the players reported their RPE scores to the team sports trainer face to face within 30 min after a training session and within 1-h after the friendly matches [27]. All players reported their wellness scores prior to breakfast. Individual RPE and general wellness scores were recorded in a customized excel spreadsheet via an iPad tablet computer (iPad Pro 9.7 a1673, Apple, CA, USA). The average of individual values in each training camp was used for subsequent data analysis. Collectively, 378 measures were recorded in this study.

Rating of perceived exertion

The subjective perceived exertion in training sessions and matches were assessed using the Borg CR10 scale (0 = nothing at all; 10 = extremely strong, almost maximum) [13]. The players were all familiarized with RPE assessment during their regular training sessions. After each training session, the team sports trainer asked the players, “how hard was your training session?” before the players reported an individual RPE score. The RPE score was then multiplied by the training session/match duration for sPRE (arbitrary units, a.u.) [14]. Furthermore, training monotony (mean of TL divided by its standard deviation) and training strain (sum of TL multiplied by training monotony during a single training camp) was calculated [15, 28, 29]. Testing procedures have been reported in our previous investigations [8, 16].

General wellness questionnaire

The general wellness questionnaire was used to assess the daily wellness conditions of players in this study. The questionnaire consists of cognitive perceptions of fatigue, sleep, DOMS, stress, and mood and requires players to answer via a five-point Likert Scale (1 –worst quality to 5 –best quality). The team’s sports trainer asked the players, “how do you feel about the level of fatigue status, sleep quality, muscle soreness, mental stress, and mood?” Afterward, the players reported the scores of each item individually. The sum of items, ranging from 5 to 25 points, was used to evaluate fatigue and wellness status [18]. The players reported their scores individually to avoid peer influence.

Data collection

Daily sRPE was collected for 5, 4, 5, and 8 days during the 1st, 2nd, 3rd, and 4th OTCs, respectively. Additionally, the wellness questionnaire was recorded for 5, 4, 6, and 9 days during the 1st, 2nd, 3rd, and 4th OTC, respectively.

Statistical analyses

Descriptive data of all variables were calculated as mean and standard deviation (SD). The average and coefficient of variation of measuring variables were used for comparisons. The normality of variables was examined with the Kolmogorov-Smirnov test. As there were different players who participated in OTCs in this study, inter-differences of TL and wellness scores to standard values were used for comparisons among the OTCs. Additionally, one-way analysis of variance (ANOVA) with Bonferroni adjustment was used to compare the variables across the OTCs. The qualitative magnitude was analyzed using Cohen’s d ES. The level of ES was interpreted as trivial (0.0–0.2), small (0.2–0.6), moderate (0.6–1.2), large (1.2–2.0), or very large (> 2.0) [30]. The relationships between TL variables and wellness scores were assessed by linear regression analysis. Statistical significance was set at p < .05 by using SPSS® Statistics version 25.0 (IBM, Armonk, NY, USA) and Microsoft Excel 2016 (Microsoft Corporation, Redmond, WA, USA).

Results

Rating of perceived exertion

One of the players failed to report wellness scores in the 1st OTC, leading to exclusion for statistical analysis. In Table 2, the results revealed significant differences in mean sRPE [F(3, 64) = 35.7, p < 0.01], sum sRPE [F(3, 64) = 36.6, p < 0.01], and training monotony [F(3, 64) = 10.5, p < 0.01] among the OTCs. The lowest mean and sum sRPE was found in the 1st OTC (335.4 ± 44.9 a.u.; 1676.8 ± 224.4 a.u.), whereas the highest mean and sum sRPE’s were found in the 3rd OTC (894.6 ± 247.6 a.u.) and 4th OTC (4509.8 ± 1136 a.u.), respectively. Very large ES of mean and sum sRPE was found when the 1st OTC was compared to the other OTCs. Furthermore, the lowest value of training monotony was found in the 2nd OTC (2.7 ± 0.4 a.u.), whereas the highest training monotony value was found in the 4th OTC (7.4 ± 3.1 a.u.). Very large ES was found between the 1st OTC and the 2nd OTC. In terms of training strain, the lowest value was found in the 2nd OTC (8932.5 ± 2096.2 a.u.), whereas the highest value was found in the 3rd OTC (14731.9 ± 15508.1 a.u.).

Table 2

Means of internal loads (session rating of perceived exertion, training monotony, and training strain) and wellness status (wellness, fatigue, delayed onset muscle soreness, sleep, stress, and mood) in four overseas training camps.

	Overseas training camps				P value (Effect size)
	1st camp (n = 14)	2nd camp (n = 20)	3rd camp (n = 17)	4th camp (n = 14)	1st vs 2nd	1st vs 3rd	1st vs 4th	2nd vs 3rd	2nd vs 4th	3 vs 4th
Mean sRPE (a.u.)	335.4 ± 44.9	826.9 ± 125.5	894.6 ± 247.6	596.9 ± 172.5	< 0.01** (-4.8 §)	< 0.01* * (-2.9 §)	0.01* (-2.0 §)	1 (-0.3 #)	0.01* (1.5 ‡)	< 0.01* (1.3 ‡)
Sum sRPE (a.u.)	1676.8 ± 224.4	3266.5 ± 536	3635.1 ± 791.8	4509.8 ± 1136	< 0.01** (-3.6 §)	< 0.01** (-3.1 §)	< 0.01** (-3.4 §)	0.80 (-0.5 #)	< 0.01* (-1.5 ‡)	0.01* (-0.9 †)
Monotony (a.u.)	7.4 ± 3.1	2.7 ± 0.4	3.9 ± 3.9	3.1 ± 0.8	< 0.01** (2.3 §)	0.02* (1.0 †)	< 0.01** (1.8 ‡)	0.90 (-0.4 #)	1 (-0.7 †)	1 (0.3 #)
Strain (a.u.)	12785.2 ± 6313.9	8932.5 ± 2096.2	14731.9 ± 15508.1	13971.2 ± 4994.3	1 (0.9 †)	1 (-0.2 *)	1 (-0.2 *)	0.31 (-0.5 #)	1 (-1.4 ‡)	1 (0.1 *)
Wellness (a.u.)	20.4 ± 2.5	16.9 ± 1.4	15.6 ± 3.1	16.3 ± 2.5	0.01* (1.8 ‡)	< 0.01** (1.6 ‡)	< 0.01** (1.6 ‡)	0.56 (0.5 #)	1 (0.3 #)	1 (-0.2 *)
Fatigue (a.u.)	3.7 ± 0.7	2.8 ± 0.3	2.8 ± 0.6	2.9 ± 0.6	< 0.01* (1.7 ‡)	< 0.01** (1.4 ‡)	0.02* (1.2 †)	1 (0 *)	1 (-0.2 *)	1 (-0.2 *)
Sleep (a.u.)	4.4 ± 0.4	3.9 ± 0.4	3.4 ± 0.7	3.7 ± 0.5	0.06* (1.2 †)	< 0.01** (1.7 ‡)	0.02* (1.5 ‡)	0.02* (0.9 †)	1 (0.4 #)	0.29 (-0.5 #)
DOMS (a.u.)	3.9 ± 0.6	3.0 ± 0.4	2.8 ± 0.8	2.8 ± 0.7	0.01* (1.8 ‡)	< 0.01** (1.5 ‡)	< 0.01** (1.6 ‡)	1 (0.3 #)	1 (0.4 #)	1 (-0.5 #)
Stress (a.u.)	4.0 ± 0.7	3.2 ± 0.4	3.1 ± 0.7	3.2 ± 0.6	0.01* (1.4 ‡)	< 0.01** (1.3 ‡)	0.02* (1.2 †)	1 (0.2 *)	1 (0 *)	1 (-0.1 *)
Mood (a.u.)	4.4 ± 0.5	4.0 ± 0.3	3.5 ± 0.8	3.6 ± 0.6	0.11 (1.0 †)	< 0.01** (1.3 ‡)	< 0.01** (1.4 ‡)	0.44 (0.8 †)	0.38 (0.9 †)	1 (-0.1 *)

Data are presented as mean and standard deviation or P value and effect size. DOMS = delayed onset muscle soreness.

p < 0.05 = *;

p < 0.01 = **.

The level of effect size was symbolled trivial (0–0.2) as *,

small (0.2–0.6) as #,

moderate (0.6–1.2) as †,

large (1.2–2.0) as ‡,

very large (> 2.0) as §.

There was a significant difference in mean sRPE among the OTCs [F(3, 64) = 9.9, p < 0.01] (Table 3). The coefficient of variation (CV) of mean sRPE was lowest in the 1st OTC (17.4 ± 10.7%) and largest in the 3rd OTC (39.8 ± 19.8%). The qualitative magnitude was very large when the 1st OTC was compared with the 2nd OTC, 3rd, and 4th OTC, respectively.

Table 3

Coefficient of variation of internal load (session rating of perceived exertion) and wellness status (wellness, fatigue, delayed onset muscle soreness, sleep, stress, and mood) in four overseas training camps.

	Overseas training camps				P value (Effect size)
	1st camp (n = 14)	2nd camp (n = 20)	3rd camp (n = 17)	4th camp (n = 14)	1st vs 2nd	1st vs 3rd	1st vs 4th	2nd vs 3rd	2nd vs 4th	3 vs 4th
Mean sRPE (%)	17.4 ± 10.7	37.5 ± 5.5	39.8 ± 19.8	34.2 ± 9.4	< 0.01** (-2.4 §)	< 0.01** (-1.3 ‡)	< 0.01** (-1.6 ‡)	1 (-0.2 *)	1 (0.4 #)	1 (0.3 #)
Wellness (%)	11.1 ± 6.5	9 ± 3.9	8.7 ± 4.9	11.8 ± 8.8	1 (0.4 #)	1 (0.4 #)	1 (-0.1 *)	1 (-0.4 #)	1 (-0.4 #)	0.98 (-0.4 #)
Fatigue (%)	22.2 ± 14	22 ± 7.9	16.6 ± 13.2	18.7 ± 12.4	1 (0.0 *)	1 (0.4 #)	1 (0.3 #)	1 (0.5 #)	1 (0.3 #)	1 (-0.2 *)
Sleep (%)	8 ± 7.1	10.6 ± 10.4	18.1 ± 11	14.9 ± 11.7	1 (-0.3 #)	0.05 (-1.0 †)	0.47 (-0.7 †)	0.19 (-0.7 †)	1 (-0.4 #)	1 (0.3 #)
DOMS (%)	16.5 ± 8	16.1 ± 12.1	19.3 ± 10.3	21.9 ± 11.4	1 (0.0 *)	1 (-0.3 #)	1 (-0.5 #)	1 (-0.3 #)	0.78 (-0.5 #)	1 (-0.2 *)
Stress (%)	15.3 ± 10.5	9 ± 11.7	19.3 ± 14.1	12.6 ± 14.6	0.96 (0.6 #)	1 (-0.3 #)	1 (0.2 *)	0.11 (-0.8 †)	1 (-0.3 #)	0.9 (0.5 #)
Mood (%)	6.8 ± 5.3	6 ± 7.8	20.6 ± 19.1	12.6 ± 11.7	1 (0.1 *)	0.02* (-0.9 †)	1 (-0.6 #)	< 0.01** (-1.0 †)	0.74 (-0.7 †)	0.47 (0.5 #)

Data are presented as mean and standard deviation or p value and effect size. DOMS = delayed onset muscle soreness.

p < 0.05 = *;

p < 0.01 = **.

The level of effect size was symbolled trivial (0–0.2) as *,

small (0.2–0.6) as #,

moderate (0.6–1.2) as = †,

large (1.2–2.0) as ‡,

very large (> 2.0) as §.

General wellness score

One-way ANOVA revealed a significant difference in wellness [F(3, 64) = 11.6, p < 0.01], fatigue [F(3, 64) = 8.6, p < 0.01], sleep [F(3, 64) = 9.6, p < 0.01], DOMS [F(3, 64) = 9.6, p < 0.01], stress [F(3, 64) = 5.7, p < 0.01], and mood [F(3, 64) = 9.2, p < 0.01]. Lowest wellness scores were found in the 3rd OTC (wellness = 15.6 ± 3.1 a.u.; fatigue = 12.8 ± 0.6 a.u.; sleep = 3.4 ± 0.7 a.u.; DOMS = 2.8 ± 0.8 a.u.; stress = 3.1 ± 0.7 a.u.; mood = 3.5 ± 0.8 a.u.) whereas largest wellness elements were found in the 1st OTC (wellness = 20.4 ± 2.5 a.u.; fatigue = 3.7 ± 0.7 a.u.; sleep = 4.4 ± 0.4 a.u.; DOMS = 3.9 ± 0.6 a.u.; stress = 4.0 ± 0.7 a.u.; mood = 4.4 ± 0.5 a.u.). Measures of magnitude demonstrated large ES in all wellness elements when the 1st OTC was compared with others OTC’s, except for fatigue and stress in the 1st OTC vs 4th OTC pairwise comparison and mood in the 1st OTC vs 2nd OTC pairwise comparison (Table 2).

There was also a significant difference in sleep [F(3, 64) = 3.0, p = 0.36] and mood [F(3, 64) = 5.2, p = 0.03]. The CV of wellness elements varied from camp to camp (wellness = 8.7 ± 4.9% ~ 11.8 ± 8.8%; fatigue = 16.6 ± 13.2% ~ 22.2 ± 14%; sleep = 8 ± 7.1 ~ 18.1 ± 11%; DOMS = 16.1 ± 12.1 ~21.9 ± 11.4%; stress = 9 ± 11.7 ~ 19.3 ± 14.1%; mood = 6 ± 7.8 ~ 20.6 ± 19.1%). The magnitude of ES varied from trivial to moderate among the comparisons (from 0 ~ -1.0) (Table 3).

Linear regression analysis

The mean and sum sRPE negatively correlated with all wellness elements (p < 0.001). The mean sRPE shows a range of r value from -0.575 (wellness score) to -0.439 (mood). Furthermore, the mean sRPE shows a ragne of r value from -0.559 (wellness score) to -0.410 (stress). However, training monotony (r = 0.034–0.216) and training strain (r = - 0.097–0.302) showed no relationship with all wellness elements, excepted training monotony vs fatigue (p = 0.042), training monotony vs fatigue (p = 0.046), training strain vs sleep (p = 0.007) (see Fig 1).

Fig 1

The linear regression analysis between perceived measures of internal loads and wellness status during futsal overseas training camps.

Columns illustrate relationships between mean session rating of perceived exertion/ sum session rating of perceived exertion/ training monotony/training strain (from most left column to most right column in the continuous sequence) and all wellness components: A) relationship with wellness scores, B) relationship with fatigue, C) relationship with sleep, D) relationship with delayed onset muscle soreness, E) relationship with stress, F) relationship with mood.

Discussion

The primary purpose of this study was to identify characteristics of the RPE-based measures and wellness status in elite futsal players during task-specific OTCs. The secondary purpose was to investigate the relationship between RPE-based measures and wellness status during futsal OTCs. Based on the observations in mean sRPE and sum sRPE, training monotony, training strain, and wellness scores during OTCs are task-dependent in elite futsal players. Additionally, the CV of sRPE is lower during game-based OTCs but larger during training-based and pre-tournament OTCs. The magnitude of CV of wellness variables ranged from trivial to moderate, indicating no large daily fluctuation in wellness status during futsal OTCs. These findings supported our first hypothesis. The secondary finding in the present study showed a significant negative relationship between mean and sum sRPE scores and all wellness components. Conversely, training monotony and training strain had no relationship with all wellness components. The later finding rejected our secondary hypothesis.

The primary finding in the present study showed a large variation of sRPE and training monotony across the OTCs. This observation indicates a characteristic of task-dependent TL during each OTC. The sRPE in the 1st OTC was significantly lower than that of 2nd, 3rd, and 4th OTC (1st OTC = 1680.47 ± 216.70 a.u. vs 2nd OTC = 3266.45 ± 536.01 a.u., 3rd OTC = 3635.06 ± 791.85 a.u., 4th OTC = 4509.29 ± 1135.97 a.u.). In this study, the sum sRPE scored in each OTC was related to the intensity of sessions/match and duration. The 1st OTC consisted mainly of game-based tasks to test the competitive level of the selected players. While, the 2nd and 3rd OTC focused on testing playing systems, fitness training, the strength of the bench depth for new players, and the implementation of team strategies. The 4th OTC was the final stage of pre-tournament preparation to simulate the competition environment and test game strategies before the final competition. Studies utilizing sRPE to quantify TL have reported ranges between 4–7 points for weekly mean RPE during a futsal preseason period [31]. However, the players’ RPE scores varied from camp to camp in our study (i.e. 1st OTC RPE = 2–5 points; 2nd OTC RPE = 3–7 points, 3rd OTC RPE = 2–9 points, 4th OTC RPE = 3–10 points). The discrepancies of RPE scores reported between the futsal preseason (consistency/progression of RPE) and the short-term futsal OTCs (variability of RPE) indicate the task-dependent characteristics of TL exhibited during each OTC.

Moreover, very large ES of mean and sum sRPE and training monotony were found when the 1st OTC was compared to the other OTCs. This discrepancy can be attributed to four consecutive matches held within the 1st OTC which were used to evaluate tactical plans for future matches. Therefore, only one training session was conducted in this OTC. Training monotony and training strain are variants of sRPE and help quantify weekly TL variability which is associated with the risk of injury and overtraining [29]. In professional soccer players, high intensity TL during the preseason period contributes to greater training monotony and training strain and is associated with the perceived measure of muscle fatigue and pain during the competitive season [32]. Furthermore, previous longitudinal studies assessed by accelerometry-based TL showed that decreasing training monotony is linked to an increase in training strain over a playing season in professional soccer players [24]. Training monotony and training strain (measured by GPS-derived accelerometer) tended to increase at the beginning and late stages of the season while decreasing during the middle portion of the season in professional soccer players [28]. In Futsal, Stochi de Oliveira and Borin [33] observed that Brazilian elite players demonstrated low training monotony (1.4–1.7 A.U.) and training strain (>5000 A.U.) during an entire futsal season, indicating a high degree of TL variability. In the present study, the extremely large training monotony and training strain during the 1st OTC (6 days) is related to the congested match schedule. In contrast, the 4th OTC (10 days) had only one scheduled match, followed by a rest/training day. The discrepancy of workload patterns between the professional season and national team TC highlights the influence of task-dependent profiles on TL. However, coaches should carefully consider such evidence since higher training monotony, and training strain levels may increase injury risk [29].

In this study, TL variability was detected in the CV estimations. The CV of sRPE was lower during the 1st OTC but was higher during the 2nd, 3rd, 4th OTCs. This phenomenon may be related to the same level of opponents played across matches in the 1st OTC. Intra-day variation of sRPE is a training marker to help understand fluctuations in individual TL responses. This finding is supported by the large training monotony found in the 1st OTC. As observed in the large SD in the 3rd OTC, a large intra-individual variation in TL may occur during intensive training-based camps. This intra-player variation should be considered in the weekly periodization of training stimuli since training intensity variability is one strategy to avoid monotony. Additionally, the impact of training intensity between players should be considered in future research to evaluate the acute responses to different levels of training stimuli.

As demonstrated in Tables 1 and 2, a larger ES of wellness scores was identified when the mean value was used to determine qualitative magnitude among the OTCs. On the other hand, trivial or small ES of wellness scores were found when CV was used for comparisons. These findings indicate that the daily fluctuation in wellness status was minor during futsal OTCs. Coincidentally, our previous observation found no change in daily wellness status and resting HR in senior national futsal players during a 5-day OTC with two friendly matches [11]. This suggests that although there exists a relationship between TL and wellness, other contextual factors and intra-personal behaviors may modulate wellness scores. In fact, a recent systematic review revealed a weak relationship between TL and wellness. This suggests that scores of wellness are influenced by many factors outside of just the TL imposed [22].

The linear regression analysis demonstrated a negative relationship between mean and sum sRPE and all wellness variables but not between training monotony and training strain. Our recent study supports these findings, which demonstrated a negative relationship between TL and wellness scores during invitation tournaments and training camps with high TL [8]. It is well known that TL and wellness status are primary factors that affect the psychophysiological health of athletes and the effectiveness of training adaptations [34]. Both measures can be used as a simple tool to examine the wellness conditions during TC [32, 35]. For example, higher TL and lower wellness scores are associated with lower cardiac-vagal tone and vice versa [36, 37].

There are three main limitations of the current study. Firstly, the traveling schedule was tabulated based on the convenience of flights. The discrepancy of traveling time among the OTC may have contributed to potential impacts on players’ psychometric status and circadian rhythm on the first day. Secondly, the training days varied from camp to camp. Although an elite coach took charge of the four OTCs, individual adaptation may vary among players [31]. Thirdly, the players experienced different playing times during friendly matches. This playing time variation may influence the reported TL scores on the friendly match day and vice versa.

Regarding practical implications, the negative association between sRPE and wellness status during short-term OTCs reflects the need to incorporate a measure of psychological exertion to wellness ratio in future investigations and training environments. Such implantations can help examine and track physical strain and wellbeing status during club/school days or domestic training camps prior to an OTC. Coaches and strength and conditioning practitioners are encouraged to utilize a comprehensive evaluation methods to monitor the daily fluctuation of psychophysiological responses during futsal OTCs.

For the future studies, it is recommended to futher explore the relationship between perceived measure of TL and wellness status during the match day and the day after the match during OTCs. Such information can advance our current understanding of managing individual variations of health status and players exposture to physical exertion during the micro-cycle of camps.

Conclusions

In conclusion, the perceived responses in training exertion and wellness scores are task-dependent during OTCs in elite futsal players. Utilizing mean/sum sRPE and wellness assessments to monitor psychophysiological health during short-term OTCs is recommended. The RPE-based training monotony and strain scores are independent markers of fatigue, DOMS, sleep, stress, and mood during futsal OTCs. Consequently, an integrated approach to using perceived measures of TL and assessments of wellness status provides efficient information in relation to training stress and wellness status in elite futsal players during OTCs.

(SAV)

Click here for additional data file.

(SAV)

Click here for additional data file.

31 Jan 2022

16 Feb 2022

Plos One

Manuscript number: PONE-D-21-37878

Title: Relationship between Relationships between perceived internal training loads and psychometric wellness during overseas futsal training camps

Dear Reviewers:

Thank you very much for your suggestions and the valuable comments. We have revised the manuscript according to the reviewers’ comments. We provide point-by-point responses (in RED color) to the reviewers’ comments below. Revision in responses to each question/concern raised by the reviewers are noted with tracked changes in the manuscript.

REVIEWER 1

ABSTRACT

Line 47: maybe consider rethinking the use of “training load”. I recommend reading the article “Misuse of the term ‘load’ in sport and exercise science” - https://www.sciencedirect.com/science/article/pii/S1440244021002127

Response: Thanks for your positive comments and support. We appreciate the need to correct the description to use training load in the revision after reading the reference. We have revised the description in the revision to highlight this issue. Please refer to revision for the changes. Thanks again to update the valuable information with us.

Line 50: recovery status – how the process will be monitored? Maybe more detail here.

Response: Thank you for your comment. We have revised and added further description in the sentence in Line 59-60.

Line 53: add the eligibility criteria for the included players

Response: Thank you for your valuable comment. We added a sentence in line 54-55.

Line 55: maybe add the details of the wellness questionnaire or the items assessed.

Response: Thank you for your suggestion. We have revised the sentence in line 59-61.

Lines 57-61: add statistical values to support the statements

Response: Thank you for your valuable comment. We have added ES and r value in the abstract as per your comment.

INTRODUCTION

Line 93: there is a perceived measure of internal training load? Or perceived effort/exertion? CR-10 Borg measure the perceived intensity and not load. https://www.sciencedirect.com/science/article/pii/S1440244021002127

Response: We fully agree with the reviewer’s comment, according to the statements reported by Staunton, et al. (2021) . We decided to revise all text related to the training load information throughout the manuscript to address the reviewer’s concerns.

Lines 93-94: support the statement about the cognitive awareness

Response: Thanks for your comments about this matter. To avoid confusing to reading, we removed the cognitive awareness in the revision.

Lines 94-96: Maybe some description about validity and reliability of the scale can be good.

Response: Thank you for your valuable comment. We have added additional information in the revision, line 107-108. Thanks.

Line 98: add examples of wellness questionnaires, validity and reliability. Which questionnaire?

Response: Thank you for your valuable comment. We have added a statement regarding validity and reliability to the revised manuscript. Line 112-113.

Lines 99-100: maybe consider this systematic review - Duignan, C., Doherty, C., Caulfield, B., & Blake, C. (2020). Single-Item Self-Report Measures of Team-Sport Athlete Wellbeing and Their Relationship With Training Load: A Systematic Review. Journal of Athletic Training, 55(9), 944-953.

Response: Thank you for your valuable comment. We have added a sentence “The intensity of TL and recovery status depends upon the types and objectives of the sessions.” to support the statement. The reference Duignan et al.,2020 was added as reference numbered 20. Line 114-115.

METHODS

Line 124: contextualize the periods of data collection (i.e., early season, mid season, end season) and the exact dates

Response: Thank for your point. We have added the exact dates of each training camp in the revision. Line 146-148.

Line 135: add the a priori sample size using G*Power or a similar software

Response: Thank you for your valuable comment. We agree with the reviewer that sample size estimation is critical to examine the power of the results. However, this study is an observational study, based on the training schedule and team preparation of a national team. This study was based on a sample of convenience and thus the number of players varied from camp to camp. We will keep this factor in mind for preparing overseas training camps in the future.

Line 144: how many times the same player participated in the OTC? Maybe a table with the N of sessions per each players would be important

Response: Thank you for your comments to improve the quality of the manuscript. The schedule of overseas training camps was tabulated in table 1. Please refer to information in line 160-162 of the revised manuscript.

Line 165: add the exact question made to the players prior to score is provided (example: how intense was the session?)

Response: Thank you for your valuable comment. We revised the sentence as “After each training session, the team sports trainer asked the players “how hard was your training session?” before the players reported an individual RPE score. Line 187-189.

Line 178: same as above (i.e., exact question) for the case of wellness.

Response: Thank you for your valuable comment. We added two sentences “The team sports trainer asked the players “how do you feel about the level of fatigue status, sleep quality, muscle soreness, mental stress, and mood?” Afterward, the players reported the scores of each item individually.”. Line 199-201.

RESULTS

Tables: add p-value as well and not the magnitude-based inference.

Response: Thank you for your this suggestion. We performed one-way ANOVA to compare the post-hoc analysis. The F ratio and p values have been added in the revisions. We also retained the effect size in the table due to unequal number of participants among the camps.

The figure has a low-resolution. Must be improved the quality.

Response: Thank you for your comment. We apologized for the low-resolution of figure 1 in the manuscript. After double checking, the figure 1 upload to the submission matches the resolution requirement of Plos One (300 dpi). However, our originally submission was a JPG file. We have converted to a TIFF file as the journal requires.

DISCUSSION

Generally well-written. I would like to suggest more discussion about further research and more practical recommendations for using not only in OTC contexts.

Response: Thank you for your positive comments and support. We have revised some sentences to improve the quality of discussion within the manuscript according to the reviewers point. Please see our revision.

REVIEWER 2

The study investigated the effects of different OTC on TL and well being measures as well as their relationships. The study is of interest and the authors did good job. There are some issues to be addressed, and a general English revision is required before the formal acceptance of the paper.

Response: Thank you very much for your supportive comment and valuable suggestions. We have improved the quality of the paper, according to the reviewers’ comments. Additionally, a native English speaker with good knowledge in sports sciences has provided feedback and proofread the revised manuscript.

Specific comments

Abstract

L49: the authors said that the relationship between TL and recovery status has not been established during short-term overseas training camps (OTC). However, previous study (Lu et al., 2018) has investigated such relationship during OTC? Any clarifications? Please remove it or just say that it was not extensively investigated to not neglect previous research.

Response: Thank you for the suggestion. We have now revised the sentence, according to your comments in lines 49-51.

- Please add effect size’s values for different comparisons and r values for correlations.

Response: Thank you for your valuable comment. We added ES and r value of correlation output in the abstract as per your comment.

Introduction

This part is well written by the authors.

Response: Thank for your positive comment.

Why the authors did not report that one previous study also investigated the relationship between TL and recovery state in OTC (https://www.termedia.pl/Training-load-and-recovery-status-during-a-short-term-overseas-training-camp-in-Taiwan-futsal-players,132,35932,0,0.html). I think it is important for your paper to clear for readers what is different from this one and this strengthens your rationale.

Response: Thank for your valuable comment. We added a sentence to address your concern. Line 125-127.

Materials and Methods

Participants

L138: “called up” may be appropriate to change to “recruited “

Response: Revised accordingly. Line 159.

- A sample size calculation is required here, please add it.

Response: Thank for your valuable comment. We agree with the reviewer that sample size estimation is critical to examine the power of the results. However, this study is an observational study, based on the training schedule and team preparation of a national team. This study was therefore based on a sample of convenience and thus the number of players varied from camp to camp. We will keep this factor in mind for preparing overseas training camps in the future.

- Please provide psychometric properties for measures used

Response: We apologize for the misleading statement for psychometric properties. To avoid the potential for confusion, we have remove the term “psychometric” and in its place inserted wellness status in the revision. Line 195-203.

Discussion

The discussion is written well.

Response: Thank you for your positive comment.

Figure

I would ask the authors to change the figure as it is not clear.

Response: Thank you for your comment. We apologized for the low-resolution of figure 1 in the manuscript. After double checking, the figure 1 upload to the submission matches the resolution requirement of Plos One (300 dpi). However, our originally submission was a JPG file. We have converted to a TIFF file as the journal requires.

Submitted filename: Authors responses to reviewers 2_PONE-D-21-37878.docx

Click here for additional data file.

18 Mar 2022

30 Mar 2022

Manuscript number: PONE-D-21-37878

Title: Relationships between perceived measures of internal load and wellness status during overseas futsal training camps

Dear Reviewers:

Thank you very much for your suggestions and the valuable comments in the second round of review. We have revised/improved the manuscript according to your comments. We provide point-by-point responses (in RED color) to the reviewers’ comments below. Revision in responses to each question/concern raised by the reviewers are noted with tracked changes in the manuscript.

REVIEWER 1

ABSTRACT

Line 49: detail the meaning of “recovery status”

Responses: The term “recovery status” was changed to “wellness status” throughout the manuscript.

Lines 51-52: would be better to add a description of the outcomes

Responses: Done.

Line 53: add the sample of training sessions and matches analyzed.

Responses: Done.

Lines 55-56: add the outcomes coming from the questionnaire.

Responses: We have revised the abstract entirely. We believe the current form is acceptable, according to your comment.

Lines 57-61: add statistical values to support the statements.

Responses: We have revised the abstract entirely. We believe the current form is acceptable, according to your comment.

INTRODUCTION

Lines 73-74: maybe add some details regarding the typical locomotor demands and intermittency of them.

Responses: This is a great point to enrich the statement. We added few sentences to this address this point. Please refer to line 90-92.

Lines 94-96: Borg’s scale does not allow measuring training load. In fact, is a measure of training intensity. Training load is a combination of intensity and volume.

Responses: Dear reviewer. We have corrected the statements in the first revision. We believe the paragraph between line 112-118 is fully compliant with your point here.

Lines 93-98: it would be important to strengthen the rationale of this paragraph with the Gabbett, T. J., Nassis, G. P., Oetter, E., Pretorius, J., Johnston, N., Medina, D., ... & Ryan, A. (2017). The athlete monitoring cycle: a practical guide to interpreting and applying training monitoring data. British Journal of Sports Medicine, 51(20), 1451-1452.

Responses: Added a sentence to strengthen the rationale of facilitating overseas training camps. Please refer to line 108-111.

The terms wellness and recovery status are not the same. Recovery status involves more than well-being measures, namely the functional status. I would like to suggest avoiding the term recovery status.

Responses: Thanks for your valuable comment to this point. We entirely changed the “recovery status” to “wellness status”.

The introduction section synthetizes the current state of the art. Nerveless, some references can help to better contextualizing these sections (e.g., Almeida, et. al. 2019.Coach decision-making in Futsal: from preparation to competition. International Journal of Performance Analysis in Sport.; Sarmento, H., Bradley, P., Travassos, B. (2015). The Transition from Match Analysis to Intervention: Optimising the Coaching Process in Elite Futsal. International Journal of Performance Analysis in Sport)

Responses: Thank for the suggestion to enrich the introduction. We added information in the last paragraph of the introduction, between line 141-144.

METHODS

Line 124: a timeline would be important adding information about the occurrence of the events.

Responses: The data of training camps has been descripted between line 158-.161. We added information for a time schedule in Table 1 for clarity.

Table 1: would be important to add information about how many training camps occurred for each type.

Responses: Done.

Line 122: sRPE was not introduced before

Responses: We moved the subsection Data Collection to line 220.

Lines 171 and 178: add the final main outcomes used for further data treatment. Moreover, add information about how statistical procedures were conducted (e.g., using average of training camps? Average of each day of training camps?)

Responses: We added a sentence “The average of individual values in each training camp was used for subsequent data analysis.” between line 196-197 for clarity.

Line 182: add the test to measure the homogeneity. Both were observed?

Responses: We did not included homogeneity test for one way ANOVA test. However, we used a post hoc test with Bonferroni adjustment for the pairwise comparison. We added this information in line 231 for clarity.

RESULTS

Figure 1. resolution of the figure is low.

Responses: We increase the resolution to 600 dpi.

Line 228: add in-text description of the information about statistical values associated with the linear regression.

Responses: Added accordingly. See line 280-285.

DISCUSSION

Generally well-written. However, future research should be described after the study limitations.

Responses: Done. Please refer to line 384-388 in the revision.

Dear Reviewer:

Thank you very much for your suggestions and the valuable comments.

REVIEWER 2

I congratulate the authors as they addressed almost of my comments satisfactorly. I recommend the paper to be accepted.

Responses: Thank you very much for your time and effort to improve the quality of the manuscript. Thanks again for your support.

Submitted filename: Authors responses to reviewers 2_PONE-D-21-37878_R2.docx

Click here for additional data file.

5 Apr 2022

Relationships between perceived measures of internal load and wellness status during overseas futsal training camps

PONE-D-21-37878R2

Dear Dr. Kuo,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Luca Paolo Ardigò, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Congratulations for the interesting work.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I would like to congratulate the authors by this revised version of the paper. All ny comments has been taking into account by the authors.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

8 Apr 2022

PONE-D-21-37878R2

Relationships between perceived measures of internal load and wellness status during overseas futsal training camps

Dear Dr. Kuo:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Luca Paolo Ardigò

Academic Editor

PLOS ONE