Self-regulation in High-level Ice Hockey Players : An Application of the MuSt Theory

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Self-regulation in High-level Ice Hockey Players : An Application of the MuSt Theory © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Published version Ruiz, Montse C.; Luojumäki, Reko; Karvinen, Samppa; Bortoli, Laura; Robazza, Claudio Ruiz, M. C., Luojumäki, R., Karvinen, S., Bortoli, L., & Robazza, C. (2021). Self-regulation in Highlevel Ice Hockey Players : An Application of the MuSt Theory. International Journal of Environmental Research and Public Health, 18(24), Article 13317. https://doi.org/10.3390/ijerph182413317 2021 International Journal of Environmental Research and Public Health Article Self-Regulation in High-Level Ice Hockey Players: An Application of the MuSt Theory Montse C. Ruiz 1,* , Reko Luojumäki 1, Samppa Karvinen 1, Laura Bortoli 2and Claudio Robazza 2   Citation: Ruiz, M.C.; Luojumäki, R.; Karvinen, S.; Bortoli, L.; Robazza, C. Self-Regulation in High-Level Ice Hockey Players: An Application of the MuSt Theory. Int. J. Environ. Res. Public Health 2021,18, 13317. https://doi.org/10.3390/ ijerph182413317 Academic Editor: Paul B. Tchounwou Received: 5 December 2021 Accepted: 16 December 2021 Published: 17 December 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Faculty of Sport and Health Sciences, University of Jyväskylä, 40014 Jyväskylä, Finland; [email protected] (R.L.); [email protected] (S.K.) 2BIND-Behavioral Imaging and Neural Dynamics Center, Department of Medicine and Aging Sciences, “G. d’Annunzio” University of Chieti-Pescara, 66013 Chieti, Italy; [email protected] (L.B.); [email protected] (C.R.) *Correspondence: montse.r[email protected] Abstract: The purpose of the study was to examine the validity of core action elements and feeling states in ice hockey players in the prediction of performance. A second aim of the study was to explore the effectiveness of a 30-day program targeting action and emotion regulation. Participants were male ice hockey players drawn from two teams competing at the highest level of the junior Finnish ice hockey league. They were assigned to a self-regulation (n= 24) and a control (n= 19) group. The self-regulation program focused on the recreation of optimal execution of core action elements and functional feeling states. Separate repeated measures MANOVAs indicated significant differences in ratings of perceived control and execution accuracy ratings of self-selected visual and behavioral components of the action (critical for optimal performance) and psychobiosocial (feeling) states across recalled best and worst games. Results support the use of both action- and emotioncentered strategies for performance enhancement. Future research including psychophysiological markers is warranted. Keywords: psychobiosocial states; action components; emotion; performance; MuSt theory 1. Introduction Substantial literature indicates that athletes’ subjective experiences influence their performance [ 1 – 5 ], and that they use several strategies to regulate emotions in order to attain sporting achievements [ 6 , 7 ]. Emotion regulation refers to the processes by which individuals manage the type, intensity, or duration of emotions they experience [ 8 ]. However, emotion regulation is only one part of the self-regulatory process by which individuals modify or modulate their thoughts, feelings, and behaviors to attain goals [ 9 , 10 ]. Thus, intervention programs aimed to help athletes reach and maintain optimal performance that combine emotion- and action-centered regulation strategies are assumed to be more effective than focusing on each of them in isolation [9,11]. A novel theoretical framework that considers both emotion- and action-regulation is the multi-states (MuSt) theory [ 1 ]. Similar to previous theoretical frameworks [ 12 , 13 ], the MuSt theory acknowledges the importance of athletes’ evaluation of their interaction with the environment, which determines their experiences and the perceived functional impact on performances. Extending previous frameworks, the MuSt theory accounts for the multiple performance states of athletes which derive from the interaction between valence (pleasant–unpleasant) and functionality (functional–dysfunctional) of their subjective experiences, and the level of attention monitoring/control they exert on task execution. High level performance can be characterized by a pleasant experience, and a low level of action monitoring, leading to ‘flow’ states [ 14 ]. High level performance can also be characterized by unpleasant experiences and high action monitoring, a more effortful ‘clutch’ state than flow [ 15 ]. In this case, directing one’s attention only to relevant key elements of the action Int. J. Environ. Res. Public Health 2021,18, 13317. https://doi.org/10.3390/ijerph182413317 https://www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2021,18, 13317 2 of 12 may help prevent excessive conscious control of movement, or a wrong focus of attention. Poor performance is typically typified by focus on irrelevant aspects, lack of energy, and dysfunctional states. Self-regulation is a process that involves awareness, acceptance, and goal-directed actions [ 9 , 16 ]. A requisite of successful regulation involves athletes’ awareness of the type of experiences they have, and how these may influence their performance. Athletes’ experiences are usually characterized by several interrelated aspects, including psychological (i.e., affective, cognitive, motivational, and volitional), biological (i.e., bodily and motor–behavioral), and social (i.e., operational and communicative) components, which together form the so-called psychobiosocial states [ 17 ]. According to the MuSt theory, functional psychobiosocial states (pleasant or unpleasant) are those that are energizing, and reflect a task-relevant focus or effortless action monitoring. Conversely, dysfunctional psychobiosocial states (pleasant or unpleasant) are those that reflect a lack of energy, or an athlete’s struggle to channel energy appropriately, thus, resulting in distraction from the task at hand, or excessive conscious control over processes that would require little attention. This multi-component conceptualization of athletes’ feeling states has been supported in several studies involving athletes of different sports and competitive levels [4]. Athletes’ acceptance of their experiences is the next necessary step prior to the implementation of regulation strategies. Awareness and acceptance are also common core elements in other intervention modalities, such as the mindfulness–acceptance-based approaches [ 18 , 19 ]. However, though these approaches do not seek to change the content of athletes’ experiences [ 19 ], self-regulation involves deliberate behaviors aimed to downregulate dysfunctional experiences, or up-regulate or maintain functional experiences [ 9 ]. Some of the strategies that athletes can use to regulate their emotions include relaxation (e.g., focus on breathing), imagery [ 20 ], music [ 21 , 22 ], or mindfulness–acceptance-based approaches [ 23 ]. Based on these self-regulation strategies the athletes often use spontaneously, during the intervention, we combined somatic techniques (i.e., paced breathing and relaxation) and mental imagery of challenging competitive situations to help players experience and mentally strengthen the optimal conditions for performance. Deep, rhythmic, abdominal breathing at approximately six breaths per minute is recommended to increase heart rate variability (HRV), which refers to changes in the time intervals between heartbeats. When individuals face stressful events in high HRV conditions, they are better able to respond, react, and adapt [24]. Thus, HRV training has been used to increase the athlete’s ability to self-regulate and, consequently, to improve sport performance [ 25 ]. Additional benefits associated with HRV training may come from greater self-awareness of physical and mental states, as well as a better understanding of the mind–body connection [26]. Beyond regulation of their own experiences for successful performance, athletes are also required to shift the focus of attention appropriately from internal feelings to task execution [ 27 ]. In line with MuSt theory assumptions, a task-focused attentional monitoring underlies automatic processes, and is associated with good performance, whereas an excessive self-focused attention results in controlled processes and impaired performances. Study Purpose and Hypotheses Framed within the MuSt theory [ 1 ], and following the principles of self-regulation [ 9 ], the purpose of this study was to examine the effectiveness of an intervention program on the self-regulation of core action components and psychobiosocial states of ice hockey players. We also examined the predictive validity of a whole profile including action elements and feeling states. We hypothesized that core action components and psychobiosocial states would differentiate between best and worst performances (H1). We also expected that the intervention would be effective in helping players self-regulate their core action components and psychobiosocial states (H2), which would be reflected in improved perceived performance (H3). Int. J. Environ. Res. Public Health 2021,18, 13317 3 of 12 2. Materials and Methods 2.1. Participants A priori power analysis for multivariate analysis of variance (MANOVA) design (within-subjects main effect), with an anticipated medium effect size (f = 0.30), statistical power set at 0.80, α level of 0.05 (correlation among repeated measures = 0.5), and three measurements, suggested a minimum sample size of 22 (G*Power 3.1.9.6 software) [ 28 ]. We recruited 43 Finnish male ice hockey players with a mean age of 19.98 years ( SD = 0.95 ). The criterion for participation in the study was having a minimum of 8 years of playing experience. Participants were drawn from two teams competing at the highest level of the Finnish A-junior ice hockey league. Their playing experience ranged from 8 to 18 years (M= 13.70, SD = 2.18). The participants were non-smokers, did not report any sleep disturbances, heart or respiratory conditions, and had not previously participated in any structured self-regulation interventions. 2.2. Measures 2.2.1. Core Action Components Players identified two visual and two behavioral core components of the action (ice hockey task-execution) following a stepwise profiling procedure [ 11 ]. First, players were asked to identify a challenging situation occurring during game where their performance would be likely subjected to high variability. The key question was: “Imagine yourself performing in a mental or physical nonoptimal state, for example when you are under distress or fatigue, or after a mistake or a poor execution, or when you have to deal with unexpected events. What are the actions or behaviours that you would need to control intentionally in order to execute in a consistent and accurate manner, and thus attain good performance?” For example, a player may identify several elements within the faceoff situation (e.g., going to the circle, opponent’s positioning, opponent’s blade, own teammates positioning, own positioning, grip of the stick, own blade’s angle, reaction to the puck drop). Participants were then asked to identify two most important visual cues (e.g., opponent’s positioning, opponent’s blade) and two behavioral cues (e.g., own positioning, own blade’s angle) of the action that would be most important to regulate. Then, they were asked to assess the perceived accuracy and control levels of execution of each component on the modified Borg scale [ 29 ]. To avoid floor and ceiling effects, the following verbal anchors were used: 0 (nothing at all), 0.5 (very, very little), 1 (very little), 2 (little), 3 (moderate), 5 (much), 7 (very much), 10 (very, very much), and • (maximal possible, 11 score is attributed to maximal possible). 2.2.2. Psychobiosocial States Individualized Profiling of Psychobiosocial States (IPPS) [ 17 ] was used to assess several aspects of the players’ performance related experiences (i.e., emotional, cognitive, motivational, volitional, bodily, motor–behavioral, operational, and communicative). The IPPS consists of 20 rows of items, including in total 74 descriptors (3–4 per row). Functionality (functional, dysfunctional) and hedonic tone (pleasant, unpleasant) distinctions were used in the development of the items assessing the emotional modality, which is assessed on six items (i.e., functional pleasant states, dysfunctional pleasant states, functional anxiety, dysfunctional anxiety, functional anger, and dysfunctional anger). The functionality distinction alone was used to categorize the items assessing cognitive, motivational, volitional, bodily, motor–behavioral, operational, and communicative aspects of the psychobiosocial states. For example, the bodily modality is assessed on two items, one describing functional bodily aspects (e.g., vigorous, energetic, physically charged), and one describing dysfunctional bodily aspects (e.g., physically tense, jittery, tired, exhausted). Participants are asked to select one adjective per item to describe how they are feeling. Then, they rate the intensity of their states on a scale ranging from 0 (nothing at all) to 4 (very much). High reliability and sound factorial structure for a two-factor solution (functional, dysfunctional) in a sample of Finnish athletes has been reported [30]. Int. J. Environ. Res. Public Health 2021,18, 13317 4 of 12 2.2.3. Imagery Ability Participants’ imagery ability was measured on the Sport Imagery Ability Measure (SIAM) [ 31 ]. The 48-item SIAM consists of four sport-related scenarios. Participants receive detailed descriptions of each scenario, after which they are given one minute to imagine each scenario. Then, they are asked to complete twelve items to assess their imagery on five dimensions (i.e., vividness, control, duration, ease, and speed of generation), six senses ( i.e., visual, auditory, olfactory, gustatory, tactile, and kinesthetic), and the experience of emotion. Each item (e.g., “How clear was the image”) is rated on a 100 mm visual analogue scale (e.g., “no image” to “perfectly clear image”). Adequate internal reliability and sound factorial validity for hard copy and web-based versions of the SIAM have been reported [32]. 2.2.4. Heart Rate Variability Cardiac vagal activity was measured as beat-to-beat intervals using the Firstbeat Bodyguard 2 (Firstbeat Technologies Ltd. Jyväskylä, Finland). The device is attached to the body with two built-in electrodes, one to be placed under the collarbone, and the second one on the rib cage. The sampling frequency is 12.5 Hz. Measurement starts automatically when the device is attached. Very high beat detection rate (i.e., 99.95%) has been reported [ 33 ]. The root mean square of successive differences (RMSSD) was used as reliable and stable measure of HRV [34,35]. 2.2.5. Performance Perceived overall performance was measured on the modified Borg scale [ 29 ]. The range was similar to the assessment of core elements; however, only two verbal anchors were included, thus, perceived performance ranged from 0 (extremely poor) to • (excellent). A score of 11 was attributed to excellent. In addition, participants’ actual ice hockey performance was video recorded from a bird’s eye perspective, where half of the performance platform is visible at a time, with a dynamic center to the puck (broadcast view of the ice hockey rink). 2.2.6. Feedback and Evaluation A brief semi-structured interview was conducted to assess participants’ involvement and evaluation of the study. Participants were asked to reflect about their involvement in the study, frequency and easiness following the breathing and imagery instructions, and overall perception of the program. The purpose of the interview was to serve as a manipulation check to determine the compliance with the intervention proposed, and to capture participants’ experiences about the self-regulation program. 2.3. Procedure Ethical approval for the study was granted from the local institution’s ethics committee. The study was conducted in accordance with the Declaration of Helsinki. Managers and coaches of two ice hockey teams were contacted, and the purpose of the study was explained to them, after which they granted permission to contact the participants. Participants were informed about the purpose of the study, procedures, confidentiality of results, and voluntary nature of study participation. They signed an informed consent form prior to commencement of the study, and were requested to create a code to ensure anonymity. Phase one: Recalled game situations. This phase consisted of the initial assessments of core components of the action, psychobiosocial states, and imagery ability, as well as the description of the study procedures. The assessments were carried out individually or in small groups in a quiet place nearby training facilities. Specifically, participants were requested to identify the most relevant core components of the action. The players were asked to access video recordings via personal electronic devices to identify their best game. They could watch the whole game or shorter individualized performance situations as many times as they wanted. After watching video recordings, participants were asked to as- Int. J. Environ. Res. Public Health 2021,18, 13317 5 of 12 sess the level of control and perceived accuracy of the previously selected core components of the action, as well as to identify and rate the intensity level of psychobiosocial states when thinking of their best performance. Previous research has shown that video-assisted recall is useful for an accurate assessment of emotions related to performance [ 36 ]. Then, participants assessed their core components of the action and how they felt in relation to their recalled worst game. Moreover, the players assessed their imagery ability on the SIAM. Finally, they were instructed about how to attach Firstbeat Bodyguard 2 chest belts to themselves. They were also requested to wear the devices for two days, to follow their normal sleep routine, and to record their sleep and waking time. Initial assessment took place a few weeks after the season had started to ensure that participants had experience and awareness of relevant aspects of their performance and feelings. Phase two: Actual game situations. Participants were contacted before an actual game. They were asked to wear the Firstbeat Bodyguard 2 chest belts, and to record their HRV during the two days prior to the game. A day after the game, with the aid of video-assisted recall, the players were asked to assess the level of control and perceived accuracy of their core action components and psychobiosocial states. They also assessed their perceived overall game performance. Phase three: Paced breathing and self-regulation protocols. Participants from one team were assigned to a self-regulation condition (SR group), whereas participants from the second team were assigned to a control condition (C group). SR group players were instructed to follow a video including a breathing pacer and guidelines for slow-paced breathing (6 cycles/min; 4.5 s inhale and 5.5 s exhale) for 15 min. At the end of the 15 min , they received the following instructions: “Now you can breathe at your own pace. Imagine the challenging situation you have previously identified. You may close your eyes if you feel more comfortable. Imagine yourself performing optimally in your challenging situation. While performing optimally in your challenging situation, pay attention to your core action components. Imagine yourself performing these core components accurately. You feel in control of the situation. Experience the emotions and feelings you felt when you have performed your challenging situation optimally. Pay attention to how you feel yourself, your muscles, and your whole body. Now, you can continue imagining your core components, the emotions, and experiences you had while performing your challenging situation optimally.” C group players were instructed to follow a video including a breathing pacer and guidelines for a close to normal breathing rhythm (12 cycles/min; 2.2 s inhale and 2.8 s exhale) for 15 min. At the end of the 15 min, they received the following instructions: “Now you can breathe at your own pace. Imagine yourself at the ice rink . . . You may close your eyes if you feel more comfortable. Now, imagine yourself executing your usual routine in preparation for a practice session. You put on your hockey equipment, shin guards, socks, pants, skates, shoulder pads, elbow pads, jersey, helmet, globes . . . Focus on how the equipment feels like, what you see around, who is there with you. Once you are ready, imagine you warm-up to prepare for a normal practice session.” SR and C group players were asked to follow the video instructions (paced breathing and imagery) for one month. Daily reminders were sent to all participants inviting them to follow the instructions. HRV, ratings about self-selected action elements, and feeling states were assessed in relation to actual games and post-intervention. Specifically, all participants measured their HRV (for the two consecutive days prior to the game). With the aid of video recordings, they also assessed their core action components, psychobiosocial states, and perceived performance (after the game). Phase four: Evaluation and feedback. Finally, one/two weeks after the intervention, participants were individually interviewed inquiring about their involvement in the study. They were asked to provide information about compliance with the program, and to reflect on the perceived effectiveness. Int. J. Environ. Res. Public Health 2021,18, 13317 6 of 12 2.4. Data Analysis Data was screened for missing values, distribution, and possible outliers. A series of repeated measures MANOVAs was used to investigate the differences on the dependent variables (core action components, psychobiosocial states, performance, HRV). The independent variables were group (SR group vs. C group), context (best performance vs. worst performance), and time (pre-, post-intervention). Pair-wise comparisons of means were then calculated to ascertain sources of significant effects. 3. Results Three cases had missing data (missingness > 5%), and were thus deleted. An individual profile including ratings for the self-selected core action elements and intensities of feeling states is depicted in Figure 1. Descriptive statistics for core action elements and feeling states identified in recalled best and worst games at group level is presented in Table 1. Figure 1. Ice hockey player’s individual profile of psychobiosocial states and core components of the action in best, worst, and current games. As expected, significant differences were found in the ratings of the action components across context (recalled best and worst games), Wilks’ λ= 0.071 ,F(8, 34) = 55.463, p< 0.001 , ηp2 = 0.929. Post hoc analysis indicated that there were significant differences in all action elements (p< 0.001, ηp2 values ranged from 0.630 to 0.888). There were no significant differences in the ratings of action components in recalled best and worst games across groups. Significant differences were found in the intensities of psychobiosocial states across recalled best and worst games, Wilks’ λ = 0.098, F(20, 20) = 9.227, p< 0.001, ηp2 = 0.902. Post hoc analysis indicated that there were significant differences in all modalities of psychobiosocial states (p< 0.001, ηp2 values ranged from 0.382 to 0.759), excluding the Pleasant ( − ) modality. There were no significant differences in the intensities of feeling states across groups. There were no significant differences across SR and C group players in the ratings of selected action elements at pre-intervention assessment in an actual game, Wilks’ λ= 0.652 , F(8, 24) = 1.604, p= 0.176, ηp2 = 0.348. Similarly, no significant differences emerged in the intensities of psychobiosocial states at the baseline actual game assessment, Wilks’ λ= 0.472, F(20, 12) = 0.670, p= 0.793, ηp2= 0.528. Int. J. Environ. Res. Public Health 2021,18, 13317 7 of 12 Participants’ mean scores in the imagery ability subscales at phase one (pre-intervention) are depicted in Figure 2. There were no significant differences in the imagery ability subscale scores across SR and C group players, Wilks’ λ = 0.483, F(12, 18) = 1.604, p= 0.107, ηp2= 0.517. Their imagery ability was deemed sufficient to follow the study protocols. Table 1. Descriptive statistics for players’ psychobiosocial states and core action components in recalled best and worst games for participants in the self-regulation and control groups. Self-Regulation Group (n= 24) Control Group (n= 19) Best Games Worst Games Best Games Worst Games Variables M SD SK K M SD SK K M SD SK K M SD SK K Core action components Visual 1 Control 7.46 2.26 − 1.17 0.62 3.83 3.01 0.70 − 0.43 6.95 2.34 − 0.74 − 1.06 2.32 1.10 − 0.32 − 0.95 Visual 1 Accuracy 8.08 1.84 − 1.73 4.23 2.96 2.27 0.68 − 0.53 8.26 1.59 − 2.05 6.12 3.05 2.20 1.65 3.02 Behavioral 1 Control 7.96 2.07 − 0.96 0.51 3.08 2.50 0.79 − 0.22 8.53 1.39 − 2.08 5.71 4.21 2.46 0.43 0.06 Behavioral 1 Accuracy 8.58 1.91 − 2.08 5.57 2.63 2.22 0.95 − 0.03 8.68 1.25 − 1.62 3.20 2.58 1.38 − 0.18 − 1.13 Visual 2 Control 7.69 2.62 − 1.32 1.11 3.96 3.18 0.53 − 1.07 7.58 2.29 − 0.44 − 0.99 2.53 1.43 − 0.31 − 0.69 Visual 2 Accuracy 8.04 2.10 − 2.13 4.97 2.92 2.61 1.11 1.01 8.58 1.68 − 1.06 0.15 1.84 1.05 0.15 − 0.51 Behavioral 2 Control 8.75 1.65 − 1.15 1.64 3.10 2.56 1.12 0.56 8.11 2.62 − 1.76 4.16 3.42 2.41 1.44 2.24 Behavioral 2 Accuracy 8.79 1.56 − 1.87 4.02 2.21 1.50 0.66 − 0.53 8.32 2.71 − 1.97 4.21 1.89 1.23 0.10 − 0.85 Psychobiosocial States Pleasant (+) 3.50 0.59 − 0.69 − 0.40 1.42 1.21 0.37 − 0.86 3.53 0.51 − 0.11 − 2.24 1.63 1.01 0.50 0.42 Anxiety (+) 1.25 0.99 0.04 − 1.15 2.38 1.10 − 0.19 − 0.49 1.16 0.83 − 0.32 − 1.49 2.42 1.07 0.23 − 1.10 Anger (+) 3.00 0.83 − 0.49 − 0.17 1.83 1.17 0.53 − 0.43 2.74 1.15 − 0.90 0.37 2.00 1.05 0.00 − 0.81 Cognitive (+) 3.25 0.94 − 1.90 5.09 1.25 1.15 0.77 − 0.10 3.11 0.66 − 0.11 − 0.39 1.11 0.88 0.34 − 0.46 Motivational (+) 3.13 1.08 − 1.41 1.92 1.58 1.18 0.04 − 0.82 3.37 0.60 − 0.31 − 0.55 1.74 1.10 0.59 − 0.84 Volitional (+) 3.21 0.83 − 1.41 2.56 1.35 1.27 0.89 − 0.16 3.05 0.62 − 0.03 0.02 1.37 1.21 0.66 − 0.43 Bodily (+) 2.96 1.04 − 1.17 1.56 1.00 1.06 0.71 − 0.70 3.00 1.00 − 0.75 − 0.31 1.84 1.07 − 0.27 − 1.27 Motor–behavioral (+) 2.96 0.86 − 0.37 − 0.53 1.50 1.14 0.00 − 1.39 3.05 0.91 − 0.60 − 0.39 1.47 1.12 0.47 − 0.11 Operational (+) 3.04 0.95 − 1.40 3.16 1.13 1.19 0.75 − 0.28 2.89 0.81 − 0.50 0.30 1.32 1.11 0.66 0.35 Communicative (+) 2.13 1.19 − 0.43 − 0.70 0.96 1.04 0.84 − 0.36 1.95 0.85 − 0.50 − 0.01 1.26 1.19 0.74 − 0.11 Pleasant (−) 1.50 1.22 0.32 − 0.97 1.04 1.23 0.98 − 0.11 1.37 1.26 0.71 − 0.64 0.84 1.01 0.70 − 0.96 Anxiety (−) 0.46 0.78 1.96 4.02 1.87 1.18 0.46 − 0.50 0.53 0.70 1.00 − 0.09 1.79 1.18 0.45 − 0.50 Anger (−) 0.25 0.53 2.13 4.14 1.79 1.28 0.02 − 1.07 0.89 0.74 0.17 − 1.00 2.26 0.87 − 0.01 − 0.70 Cognitive (−) 0.75 1.15 1.65 2.01 2.83 0.96 − 0.28 − 0.88 0.58 0.69 0.81 − 0.37 2.63 0.83 − 0.47 0.04 Motivational (−) 0.25 0.85 4.16 18.34 1.13 1.15 0.48 − 1.26 0.11 0.32 2.71 5.98 1.26 1.10 0.82 0.68 Volitional (−) 0.17 0.38 1.91 1.79 2.04 1.30 0.05 − 1.03 0.42 0.51 0.35 − 2.11 2.26 0.93 − 0.13 − 1.10 Bodily (−) 0.79 1.06 1.64 2.71 2.78 1.17 − 0.67 − 0.23 1.05 0.78 0.69 0.98 2.89 0.99 − 0.53 − 0.61 Motor–behavioral (−) 0.46 0.93 2.07 3.33 2.38 1.06 − 0.12 − 0.18 0.21 0.54 2.66 6.88 2.05 0.85 − 0.72 0.37 Operational (−) 0.21 0.41 1.53 0.38 2.04 1.55 − 0.08 − 1.46 0.16 0.50 3.34 11.19 2.11 0.88 − 0.22 1.46 Communicative (−) 0.38 0.71 2.46 7.34 1.50 1.41 0.60 − 0.99 0.32 0.58 1.77 2.54 1.74 0.81 − 0.17 − 0.16 Note. (+) denotes functional modalities of psychobiosocial states, (−) denotes dysfunctional modalities of psychobiosocial states. Figure 2. Mean and standard deviations of ice hockey players’ imagery ability subscale scores at phase one. Int. J. Environ. Res. Public Health 2021,18, 13317 8 of 12 Repeated measures MANOVAs yielded significant differences by group for RMSSD mean scores recorded during sleep at pre- and post-training assessments, Wilks’ λ = 0.542, F(2, 15) = 6.345, p= 0.010, ηp2 = 0.458. Post hoc analysis indicated significant differences in the RMSSD values prior to the commencement of the training program, with a significant increase in variability for SR participants (see also Figure 3). Figure 3. Root mean square of successive differences between RR intervals (RMSSD) for heart rate variability during sleep at the beginning and the end of the training program. MANOVA could not be calculated to examine differences in the ratings of the action components and intensities of feeling states at pre- and post-intervention across groups due to the high attrition, with 19 participants providing data at both times. Separate independent samples Mann–Whitney U tests indicated that there were no significant differences by groups in the ratings of the action components (pvalues > 0.289) or in the intensities of psychobiosocial states (p> 0.056) across pre-and post-intervention. Contrary to our third hypothesis, independent samples Mann–Whitney U tests did not yield significant differences by groups in the ratings of perceived overall performance in actual games played pre- and post-intervention (p= 0.643). Participants reported high compliance with the program. SR group participants reported following the video instructions three to seven times per week (M= 5.00; SD = 1.44 ), whereas C group participants followed them from two to seven times per week (M= 5.00; SD = 1.86). Overall, players perceived the program to be beneficial, rating its benefit on average 3.77 (SD = 0.49), with 5 being highest rating, and an average of 3.67 (SD = 0.61) for participants in the control group. Qualitative feedback indicated that the self-regulation program was beneficial. For example, “I noticed that the more I practiced the better it went, it was more natural, and I calmed down and felt more relaxed. I got such a good and relaxed feeling, that. ..I could have done anything after that.” “I relaxed. It’s not often in everyday life that you can relax like that, in such a comprehensive way. If the day was a bit hectic, this was incredibly helpful.” The participants also reported their involvement in the study helped them gain awareness, as the following quotes illustrate: “I hadn’t thought so much about how one can influence his own feelings. So now that I think about it, the feelings are different when it goes well, compared to when goes badly. If it goes well, then you are inside the game. If you are not absorbed in the game, then the focus goes away, you are not focused on the puck . . . ” “Thinking about your feelings, and after a situation that is very important, thinking about your feelings, because they have big influence in that, and then you are able to modify and change for the next situation.” They also reported the program was helpful