The Relationship between Inclination for Conscious Movement Monitoring and Control and Stopping a Golf Stroke
有意识运动监测和控制的倾向与停止高尔夫击球之间的关系

Introduction 介绍

Athletes pursue optimal performance during competition. Interestingly, many elite athletes indicate that they typically do not or pay only little conscious attention toward the execution of movements, that is, on how movements should unfold in space and time, when performing optimally (Toner & Moran, Citation2011). In fact, increased conscious investment in monitoring and control of movement is often associated with suboptimal performance (Beilock & Carr, Citation2001; Masters, Citation1992; Maxwell et al., Citation2006; Toner & Moran, Citation2011). For example, when expert golf players were instructed to turn attention inwards to the ongoing putting movement and (afterwards) reported which part of the putter face contacted the ball, their performance worsened in comparison to a condition without instruction (Toner & Moran, Citation2011). A similar phenomenon is thought to underpin break downs of performance in high pressure situations. These lead to increased conscious monitoring and control of normally automatized movement control, which may disrupt performance, especially in skilled athletes (Beilock & Carr, Citation2001, Masters & Maxwell, Citation2008).
运动员在比赛中追求最佳表现。有趣的是，许多精英运动员表示，他们通常不会或很少有意识地关注动作的执行，即在最佳表现时动作应如何在空间和时间上展开（Toner & Moran， Citation 2011 ）。事实上，增加对运动监测和控制的有意识投资通常与次优表现相关（Beilock & Carr， Citation 2001 ；Masters， Citation 1992 ；Maxwell 等人， Citation 2006 ；Toner & Moran， Citation 2011 ）。例如，当专业高尔夫球手被指示将注意力转向正在进行的推杆运动并（随后）报告推杆面的哪一部分接触球时，与没有指导的情况相比，他们的表现会恶化（Toner & Moran， Citation 2011） ）。人们认为，类似的现象会导致高压情况下的表现下降。这些导致对通常自动运动控制的有意识监视和控制的增加，这可能会扰乱表现，特别是对于技术熟练的运动员（Beilock＆Carr， Citation 2001 ，Masters＆Maxwell， Citation 2008 ）。

Yet, some researchers have suggested that increased conscious investment in movement can also be accommodating, particularly when a movement suddenly needs to be stopped or inhibited (Beilock & Gray, Citation2012; Park et al., Citation2020). Abruptly stopping or profoundly changing an ongoing or planned action is especially necessitated in the unpredictable dynamics of sporting environments (Gray, Citation2009). For example, in soccer, the penalty kicker may interrupt the planned action and opt instead to kick to the side opposite of the initially intended side because of the goalkeeper’s actions (Morya et al., Citation2003; van der Kamp, Citation2006). Or in baseball, the batter may stop the swing at the latest moment when it appears that the trajectory of the oncoming ball is different from what was initially perceived (Gray, Citation2009). Therefore, to stop or inhibit planned or ongoing movements quickly and (just) in time can be crucial to successful sport performance. Increased conscious movement monitoring and control has been suggested to speed up inhibition (Beilock & Gray, Citation2012; Park et al., Citation2020). Beilock and Gray (Citation2012) recruited novices and skilled golfers and required them to stop golf putting strokes in response to an auditory stop-signal. They reported that novices had shorter stopping time and distances compared to the skilled golfers when the stop-signal appeared during the downswing. Novices thus seemed more proficient in inhibiting the golf swing compared to experienced golfers. Since novices compared to skilled performers typically show increased conscious engagement in movement behavior, Beilock and Gray (Citation2012) proposed that skilled golfers were slower in stopping because they first had to (re-)direct attention to the movement. By contrast, novices could forego this step since they were already consciously attending inward.
然而，一些研究人员认为，增加对运动的有意识投资也可以起到调节作用，特别是当运动突然需要停止或抑制时（Beilock & Gray， Citation 2012 ；Park et al.， Citation 2020 ）。在不可预测的动态运动环境中，突然停止或深刻改变正在进行或计划的动作尤其必要（Gray， Citation 2009 ）。例如，在足球中，由于守门员的行为，点球手可能会打断计划的动作并选择踢到与最初预期一侧相反的一侧（Morya 等人， Citation 2003 ；van der Kamp， Citation 2006 ）。或者在棒球中，当即将到来的球的轨迹与最初感知的不同时，击球手可能会在最后一刻停止挥杆（Gray， Citation 2009 ）。因此，快速、及时地停止或抑制计划中或正在进行的运动对于成功的运动表现至关重要。有人建议增加有意识的运动监测和控制来加速抑制（Beilock & Gray，引文2012 ；Park 等人，引文2020 ）。 Beilock 和 Gray（引文2012 ）招募了新手和熟练的高尔夫球手，并要求他们在听到停止信号时停止高尔夫推杆。 他们报告说，与熟练的高尔夫球手相比，当下杆期间出现停止信号时，新手的停止时间和距离更短。因此，与经验丰富的高尔夫球手相比，新手似乎更擅长抑制高尔夫挥杆。由于与熟练的高尔夫球手相比，新手通常会表现出更多的有意识地参与运动行为，Beilock 和 Gray（引文2012 ）提出，熟练的高尔夫球手停下来的速度较慢，因为他们首先必须（重新）将注意力转移到运动上。相比之下，新手可以放弃这一步，因为他们已经有意识地向内关注。

The degree of conscious movement investment not only differentiates novices and skilled performers but is also considered a disposition that explains interindividual differences (i.e., within a level of skill) in the degree to which performers lean toward conscious investment in movement monitoring and control. This disposition can be measured with the Movement Specific Reinvestment Scale (MSRS, Malhotra et al., Citation2015; Masters & Maxwell, Citation2008; Masters et al., Citation1993, Citation2005). Movement reinvestment is used as an umbrella term merging different ways of how consciousness engages in movement (Masters & Maxwell, Citation2008). The original MSRS consisted of two factors, named conscious motor processing (CMP) and movement self-consciousness (MS-C, Masters et al., Citation2005). CMP reflects an individual’s inclination to consciously regulate or apply explicit movement rules in the ongoing movements, for instance, by actively adjusting movement form or speed in response to instructions. MS-C refers to an individual’s concern or attention to the ‘style’ of movement, for instance, when trying to make a good impression in public (Masters et al., Citation2005; Masters & Maxwell, Citation2008). Recently, however, Malhotra et al. (Citation2015) reinterpreted the MS-C to generally reflect the conscious monitoring of movement without necessarily having the intention to actively intervene in its execution. This reading followed from their observations that both CMP and MS-C were associated with novices’ golf putting performance during early practice, higher scores for CMP and MS-C were related to better performance. Malhotra et al. (Citation2015, p. 6) argued that “it is difficult to comprehend how being self-conscious about movements or being concerned about the ‘style’ of movement manifests in more proficient performance in practice”. Instead, they argued, MS-C would be more appropriately taken to represent a conscious monitoring or paying attention to one’s movements without actively intervening in them. In fact, Malhotra et al. (Citation2015) proposed, following an earlier lead by Jackson et al. (Citation2006), that the two factors of MSRS draw a distinction between conscious movement control and movement monitoring. We are sympathetic to this proposal, and thus interpret the CMP and MS-C factors of the MSRS to measure an individual’s inclination to consciously control and monitor one’s movements, respectively. Skilled athletes with a higher inclination for conscious movement control and monitoring are more likely to show performance break downs in high pressure situations (Chell et al., Citation2003; Jackson et al., Citation2006; Citation2013; Tang et al., Citation2023), presumably because they reinvest conscious attention in already automatized movement behaviors. Also, without contingencies such as high pressure, the MSRS is shown to be sensitive to individual differences in the degree movements to which they tend to consciously attend to and control movements. For example, novices with higher CMP and MS-C scores, and therefore a higher inclination for conscious movement investment, showed higher performance of golf putting (Malhotra et al., Citation2015).
有意识的动作投入程度不仅区分新手和熟练的表演者，而且还被认为是解释表演者倾向于有意识地投入运动监控和控制的程度的一种倾向（即在技能水平内）。这种处置可以通过运动特定再投资量表来衡量（MSRS，Malhotra 等人，引文2015 ；Masters & Maxwell，引文2008 ；Masters 等人，引文1993 ，引文2005 ）。运动再投资被用作一个涵盖性术语，融合了意识参与运动的不同方式（Masters & Maxwell， Citation 2008 ）。最初的 MSRS 由两个因素组成，称为有意识运动处理（CMP）和运动自我意识（MS-C，Masters 等人， Citation 2005 ）。 CMP反映了个体在正在进行的运动中有意识地调节或应用明确的运动规则的倾向，例如，根据指令主动调整运动形式或速度。 MS-C 指的是个人对运动“风格”的关注或注意，例如，当试图在公共场合留下好印象时（Masters 等人， Citation 2005 ；Masters & Maxwell， Citation 2008 ）。然而，最近，Malhotra 等人。 （引文2015 ）重新解释了 MS-C，一般反映了对运动的有意识监控，而不一定有主动干预其执行的意图。这一读数是根据他们的观察得出的，即 CMP 和 MS-C 都与新手在早期练习中的高尔夫推杆表现相关，CMP 和 MS-C 得分越高，表现越好。马尔霍特拉等人。 （引文2015 ，第 6 页）认为“很难理解对动作的自我意识或对动作‘风格’的关注如何在实践中体现出更熟练的表现”。相反，他们认为，MS-C 更适合代表有意识地监控或关注一个人的动作，而不主动干预它们。事实上，马尔霍特拉等人。 ( Citation 2015 ) 是在 Jackson 等人的早期领导下提出的。 ( Citation 2006 )，MSRS 的两个因素区分了有意识的运动控制和运动监控。我们赞同这一提议，因此解释了 MSRS 的 CMP 和 MS-C 因子，以分别衡量个体有意识地控制和监控自己的运动的倾向。更倾向于有意识的运动控制和监测的熟练运动员更有可能在高压情况下表现出表现下降（Chell 等人，引用2003 年；Jackson 等人，2003 年）。，引文2006 ；引文2013 ； Tang 等人，引用2023 ），大概是因为他们将有意识的注意力重新投入到已经自动化的运动行为中。此外，在没有高压等意外情况的情况下，MSRS 对运动程度的个体差异很敏感，他们倾向于有意识地关注和控制运动。例如，具有较高 CMP 和 MS-C 分数的新手，因此更倾向于有意识的运动投资，表现出更高的高尔夫推杆表现（Malhotra 等人，引文2015 ）。

Recently, Park et al. (Citation2020) directly examined the relationship between the ability to inhibit simple movements and the inclination for conscious movement investment. They hypothesized that participants who showed more proficient inhibition would have a low inclination for conscious movement investment (Park et al., Citation2020). They had participants complete the MSRS and perform a computerized Go/No-Go Task to measure inhibition. In the Go/No-Go Task participants respond to the prevalent go-stimulus but withhold that response when the less frequent no-go stimulus appears. Park et al. (Citation2020) found a negative correlation between MSRS score and the variability in the go response time. However, there was no significant correlation between MSRS score and the number of false responses to the no-go stimuli (i.e., commission errors), which is the primary indicator of inhibition in the Go/No-Go Task. If anything, this suggests that individuals with a high inclination to consciously invest in movement monitoring and control, have more proficient inhibition ability, which contradicts Park et al.’s hypothesis. Yet, this finding does seem to (partly) corroborate Beilock and Gray (Citation2012) observations. Possibly, the association observed in Park et al. (Citation2020) in the simple button press tasks is even more pronounced for more complex movements involving multiple degrees of freedom.
最近，帕克等人。 （引文2020 ）直接检验了抑制简单运动的能力与有意识运动投资的倾向之间的关系。他们假设表现出更熟练抑制的参与者对有意识运动投资的倾向较低（Park 等人，引文2020 ）。他们让参与者完成 MSRS 并执行计算机化的 Go/No-Go 任务来测量抑制。在“进行/不进行”任务中，参与者对普遍的“进行”刺激做出反应，但当出现不太频繁的“不进行”刺激时，则不会做出反应。帕克等人。 （引文2020 ）发现 MSRS 分数与 go 响应时间的变异性之间存在负相关。然而，MSRS 分数与对不进行刺激的错误反应数量（即委托错误）之间没有显着相关性，而这是进行/不进行任务中抑制的主要指标。如果说有什么不同的话，那就是，这表明，高度倾向于有意识地投资于运动监测和控制的个体，具有更熟练的抑制能力，这与 Park 等人的假设相矛盾。然而，这一发现似乎确实（部分）证实了 Beilock 和 Gray（引文2012 ）的观察结果。 Park 等人可能观察到这种关联。 （引文2020 ）在简单的按钮按下任务中，对于涉及多个自由度的更复杂的运动来说更加明显。

Typically, the conscious monitoring and control of movement is understood in the context of cognitive theories that hold that internal representations or motor programs underpin movement behavior (Masters & Maxwell, Citation2008). The key argument follows from early work by Fitts and Posner (Citation1967), Keele (Citation1968) that novices consciously control or monitor their movements, but that with learning the explicit knowledge that they have accumulated becomes internalized into motor programs. Once the program is acquired, executive conscious monitoring and control is superfluous and, consequently, the movement normally runs off automatically or unconsciously (Schneider & Shiffrin, Citation1977; Willingham, Citation1999). It follows that conscious control and monitoring of movement is beneficial for beginners, but degrades movement performance among skilled performers, because it interferes with the already automatized control (Beilock et al., Citation2002; Beilock & Carr, Citation2001; Maxwell et al., Citation2006; Perkins-Ceccato et al., Citation2003). For example, Beilock et al. (Citation2002) reported that novice soccer players dribbled faster when they were instructed to report whether they touched the ball with the outside or inside of their foot on hearing a loud a tone compared to when they had to identify a target word from a list of words spoken on a tape-recorder. In other words, the novices performed better when consciously monitoring their movements, (i.e., referred to as skill-focus attention by Beilock et al., Citation2002), presumably because it enhances their normal continuous conscious step-by-step control of movements. However, skilled soccer players showed the opposite pattern. They performed better when conscious attention was directed away from the movements (i.e., distributed attention), strengthening the noninterference in automatic movement control.
通常，有意识地监测和控制运动是在认知理论的背景下理解的，该理论认为内部表征或运动程序支撑着运动行为（Masters & Maxwell，引文2008 ）。关键论点源自 Fitts 和 Posner（ Citation 1967 ）、Keele（ Citation 1968 ）的早期研究，即新手有意识地控制或监控自己的动作，但通过学习他们所积累的显性知识，他们会内化到运动程序中。一旦获得了程序，执行意识的监视和控制就是多余的，因此，运动通常会自动或无意识地运行（Schneider＆Shiffrin， Citation 1977 ；Willingham， Citation 1999 ）。由此可见，有意识地控制和监测运动对初学者来说是有益的，但会降低熟练表演者的运动表现，因为它会干扰已经自动化的控制（Beilock 等人，引文2002 ；Beilock 和 Carr，引文2001 ；Maxwell 等人，2002）。 ，引文2006 ；Perkins-Ceccato 等人，引文2003 ）。例如，贝洛克等人。 ( Citation 2002 ) 报道称，与必须从一系列单词中识别目标单词时相比，当新手足球运动员被指示在听到响亮的声音时报告是用脚的外侧还是内侧触球时，他们的运球速度更快。录音机上所说的话。换句话说，新手在有意识地监控自己的动作时表现得更好（即 Beilock 等人称为技能集中注意力，引文2002 ），大概是因为它增强了他们正常的连续有意识的逐步控制动作。然而，熟练的足球运动员却表现出相反的模式。当有意识的注意力远离运动（即分散注意力）时，他们表现得更好，从而加强了自动运动控制的不干扰性。

Although we do not intend to directly compare theoretical approaches, we prefer to conceptualize conscious movement monitoring and control from a nonrepresentational theory that combines the perspectives of ecological psychology (Gibson, Citation1979) and dynamic systems theory (Kugler et al., Citation1980). In this approach, it is argued that adaptive movement emerges or self-organizes from the interactions of various constraints imposed upon the performer-environment system, rather than being prescribed by internal representations or programs (Davids et al., Citation2013; Newell, Citation1986; Warren, Citation2006). In this respect, Bernstein (Citation1967) argued that for a movement to be adapted to the dynamic environment, a performer’s movement system’s many independent degrees of freedom need to be temporally organized or coordinated. The number of actively controlled degrees of freedom is then defined by the constraints on the movement system. In this respect, Newell and Ranganathan (Citation2010) argued that instructions that shift a person’s conscious attention to the unfolding movement, act as a (additional) constraint on the movement system. Importantly, in this understanding a constraint does not cause or prescribe a movement, but functions to channel the search for an adaptive movement (Kugler et al., Citation1980). Consequently, within this perspective conscious movement monitoring and control can be considered a way to temporally reduce the number of degrees of freedom. Indeed, some studies have shown that conscious movement monitoring and control is associated with a freezing or reducing of the degrees of freedom (Higuchi et al., Citation2002; Lohse et al., Citation2010; van Ginneken et al., Citation2018). For example, van Ginneken et al. (Citation2018) showed that in a throwing task, increased conscious movement monitoring and control was associated with more similar, less variable movements. It can be proposed, therefore, that in less skilled performers conscious movement monitoring and control simplifies movement control. However, in more proficient performers, who show more distributed movement control, adding an additional constraint through conscious interference may reduce the degrees of freedom and thus hamper adaptive movement flexibility. This may lead to the typically observed performance disruptions associated with conscious movement monitoring and control in skilled performers (Beilock et al., Citation2002; Beilock & Gray, Citation2012; Gray, Citation2004, Citation2006). In this respect, Hervault et al. (Citation2021) found that movements involving multiple degrees of freedom (i.e., swiping) show longer time to inhibit compared to movements with less degrees of freedom (i.e., button press). The authors suggested that the speed of movement inhibition scales with the number of degrees of freedom being controlled. Because with more complex movements, control is distributed over a larger number of degrees of freedom, more time is needed to disassemble or undo control in the case of sudden inhibition. In sum, our working hypothesis is that conscious investment in the monitoring and control of movement can act as a constraint that reduces the number of degrees of freedom to be controlled. Following the arguments of Hervault et al. (Citation2021), these consciously controlled movements would be inhibited faster than movements for which control is distributed over a larger number of degrees of freedom.
尽管我们不打算直接比较理论方法，但我们更喜欢从结合了生态心理学（Gibson， Citation 1979 ）和动态系统理论（Kugler et al.， Citation 1980 ）视角的非表征理论来概念化有意识运动监测和控制。 。在这种方法中，有人认为适应性运动是从施加在表演者环境系统上的各种约束的相互作用中出现或自组织的，而不是由内部表征或程序规定（Davids et al., Citation 2013 ; Newell, Citation） 1986 年；沃伦，引文2006 ）。在这方面，伯恩斯坦（ Citation 1967 ）认为，为了使动作适应动态环境，表演者的动作系统的许多独立自由度需要在时间上进行组织或协调。然后，主动控制的自由度的数量由运动系统的约束来定义。在这方面，Newell 和 Ranganathan（引文2010 ）认为，将人的意识注意力转移到展开的运动上的指令，充当了对运动系统的（附加）约束。重要的是，在这种理解中，约束不会导致或规定运动，而是用于引导对适应性运动的搜索（Kugler 等人，引文1980 ）。 因此，从这个角度来看，有意识的运动监控和控制可以被认为是暂时减少自由度数量的一种方法。事实上，一些研究表明，有意识的运动监测和控制与自由度的冻结或降低有关（Higuchi 等人，引文2002 ；Lohse 等人，引文2010 ；van Ginneken 等人，引文2018 ） 。例如，范吉内肯等人。 （引文2018 ）表明，在投掷任务中，增加有意识的运动监控和控制与更相似、更少变化的运动相关。因此，可以提出，对于技术较差的表演者来说，有意识的运动监测和控制可以简化运动控制。然而，对于表现出更分散的运动控制的更熟练的表演者来说，通过有意识的干扰添加额外的约束可能会降低自由度，从而妨碍自适应运动的灵活性。这可能会导致熟练表演者通常观察到的与有意识运动监控和控制相关的表现中断（Beilock 等人，引文2002 ；Beilock & Gray，引文2012 ；Gray，引文2004 ，引文2006 ）。在这方面，赫沃等人。 （引文2021 ）发现涉及多个自由度的运动（即与自由度较小的运动（即按下按钮）相比，滑动、滑动）显示出更长的抑制时间。作者认为，运动抑制的速度与受控制的自由度的数量成正比。因为对于更复杂的运动，控制分布在更多的自由度上，所以在突然抑制的情况下需要更多的时间来分解或撤消控制。总之，我们的工作假设是，有意识地对运动的监视和控制进行投资可以充当限制，减少要控制的自由度的数量。根据 Hervault 等人的论点。 （引文2021 ），这些有意识控制的运动将比控制分布在更多自由度上的运动受到更快的抑制。

As reviewed above, the evidence supporting the relationship between conscious movement investment and inhibition is still weak. Beilock and Gray (Citation2012) indeed presented evidence supporting a relationship based on a comparison between participants of different skill level, but their evidence would have been strengthened had they shown that the participating novice performers indeed were more strongly inclined to and/or consciously attending to the golf movements. Park et al. (Citation2020) evidence is less direct and limited in the sense that the key press response in the Go/No-Go Task seemingly does not require much conscious movement monitoring or control. Hence, we further explore the relationship between conscious movement monitoring and control and inhibition by combining both methodologies. Specifically, we adopted the experimental task introduced by Beilock and Gray (Citation2012) and asked novice golf players to stop a golf putting stroke in response to an auditory signal. We assessed participants’ inclination for conscious movement investment using the MSRS. As elaborated on in the above, previous studies have shown that the MS-C and CMP factors that make up the MSRS, seem to differently relate to performance by manifesting themselves more strongly in the monitoring and control of movement, respectively (Malhotra et al., Citation2014; Citation2015). Because the MSRS measures an individual’s inclination for conscious movement investment and not the actual degree of conscious involvement in monitoring and control in the ongoing movement, we also estimated the amount of declarative knowledge that participants invested by using a post-experimental verbal knowledge protocol (Beilock & Carr, Citation2001). Novice performers with high MSRS scores, indicating a high inclination for conscious movement monitoring and control tend to accumulate more explicit movement rules than performers with low MSRS scores (Maxwell et al., Citation2000). We predicted more proficient inhibition (i.e., higher stopping rate and shorter stopping time) for participants with a stronger inclination for conscious movement monitoring and control (i.e., as reflected in higher MS-C and CMP scores, respectively) and/or with more invested declarative knowledge.
如上所述，支持有意识运动投入与抑制之间关系的证据仍然薄弱。 Beilock 和 Gray（引文2012 ）确实提供了基于不同技能水平的参与者之间的比较来支持关系的证据，但如果他们表明参与的新手表演者确实更强烈地倾向于和/或有意识地参加，他们的证据将会得到加强到高尔夫动作。帕克等人。 （引文2020 ）证据不太直接和有限，因为 Go/No-Go 任务中的按键响应似乎不需要太多有意识的运动监控或控制。因此，我们结合这两种方法进一步探讨有意识运动监测和控制与抑制之间的关系。具体来说，我们采用了 Beilock 和 Gray 提出的实验任务（引文2012 ），并要求新手高尔夫球手响应听觉信号停止高尔夫推杆击球。我们使用 MSRS 评估了参与者对有意识运动投资的倾向。如上所述，之前的研究表明，构成 MSRS 的 MS-C 和 CMP 因素似乎与表现有不同的关系，分别在运动的监测和控制中表现得更强烈（Malhotra 等，2017）。 ，引文2014 ；引文2015 ）。 由于 MSRS 衡量的是个体对有意识运动投资的倾向，而不是有意识地参与持续运动的监测和控制的实际程度，因此我们还使用实验后言语知识协议（Beilock）估计了参与者投入的陈述性知识量＆Carr，引文2001 ）。具有高 MSRS 分数的新手表演者，表明有意识运动监控和控制的高倾向，往往比具有低 MSRS 分数的表演者积累更明确的运动规则（Maxwell 等人， Citation 2000 ）。我们预测，对于有意识的运动监测和控制倾向更强（即，分别反映在较高的 MS-C 和 CMP 分数）和/或投入更多的参与者，抑制效果会更熟练（即，更高的停止率和更短的停止时间）。陈述性知识。

Method 方法

Apparatus, Materials, and Tasks
设备、材料和任务

Questionnaire 问卷调查

Movement Specific Reinvestment Scale (MSRS): The MSRS comprises ten items loading on two factors (Masters et al., Citation2005). Five items assess movement self-consciousness (MS-C), while the other five items assess conscious motor processing (CMP). Following Malhotra et al. (Citation2015; see also Jackson et al., Citation2006), we interpret MS-C and CMP to measure an individual’s inclination to consciously invest in movement monitoring and movement control, respectively. Each item is rated on 6-point Likert scale, range from 1 (strongly disagree) to 6 (strongly agree), with cumulative scores on each factor ranging from 5 to 30. The higher the score, the stronger the inclination for conscious movement investment. The English version of the MSRS was used in this study. All participants were fluent in English.
运动特定再投资量表 (MSRS)： MSRS 包括十个项目，加载两个因素（Masters 等人，引文2005 ）。五个项目评估运动自我意识（MS-C），而其他五个项目评估有意识的运动处理（CMP）。继 Malhotra 等人之后。 （引文2015 ；另见 Jackson 等人，引文2006 ），我们将 MS-C 和 CMP 解释为分别衡量个人有意识地投资于运动监测和运动控制的倾向。每个项目均采用 6 点李克特量表评分，范围从 1（强烈不同意）到 6（强烈同意），每个因素的累积分数范围从 5 到 30。分数越高，有意识运动投资的倾向越强。本研究使用英文版 MSRS。所有参与者都能说流利的英语。

Verbal Knowledge Protocols: Following Beilock and Carr (Citation2001), a verbal knowledge protocol (Appendix A) was used to assess the number of movement rules that participants used when performing the golf putting strokes. The participants gave their responses in writing.
言语知识协议：继 Beilock 和 Carr（引文2001 ）之后，使用言语知识协议（附录 A ）来评估参与者在进行高尔夫推杆击球时使用的运动规则的数量。参与者以书面形式给出了答复。

Indoor Putting Green 室内果岭

An indoor putting green was used (
使用了室内果岭（Figure 1 图1). A red square-shaped target with a red dot inside was used as the target (0.045*0.045m) and four white starting lines with a red dot were used as four different starting locations. The starting lines were at 1.22, 1.83, 2.44, or 3.05 m distance from the red square-shaped target and numbered 1 to 4, respectively, to instruct participants on the starting location. Beilock and Carr (Citation2001, study 1) demonstrated that participants quickly adapted to a golf putting task when only one distance was used, reducing conscious movement engagement. Hence, to increase the contrast in conscious movement investment between participants with a high or low inclination for conscious movement monitoring and control, we followed Beilock and Gray (Citation2012) and included four distances. Standard balls and putter were used.
）。靶子采用一个内有红点的红色方形靶子（0.045*0.045m），4条带红点的白色起始线作为四个不同的起始位置。起始线距红色方形目标1.22、1.83、2.44或3.05 m，分别编号为1至4，以指示参与者的起始位置。 Beilock 和 Carr（引文2001 ，研究 1）证明，当仅使用一个距离时，参与者很快就适应了高尔夫推杆任务，从而减少了有意识的运动参与。因此，为了增加有意识运动监测和控制倾向高或低的参与者之间有意识运动投资的对比，我们遵循 Beilock 和 Gray（引文2012 ）并包括四个距离。使用标准球和推杆。

FIGURE 1. Schematic representation of the golf setting. Note. Numbers 1 to 4 represents the starting lines at 1.22, 1.83, 2.44 and 3.05 m from the target, respectively. The red square with a red dot inside represents the target. The black rectangle indicates the photographed area. The radius from the smallest circle to the next larger circle is 0.15, 0.30, and 0.45 m, respectively. The dashed lines were drawn for analyses purpose and not visible to participants.
图 1.高尔夫球场景示意图。笔记。数字 1 至 4 分别代表距离目标 1.22、1.83、2.44 和 3.05 m 的起始线。里面有红点的红色方块代表目标。黑色矩形表示拍摄区域。从最小圆到下一个较大圆的半径分别为 0.15、0.30 和 0.45 m。虚线是出于分析目的而绘制的，参与者看不到。

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Kinematic Recordings 运动记录

Optorak 3020 was used to record the x-, y-, and z-coordinates of a LED mounted on the shaft of the putter at 200 Hz, with the y-coordinate referring to the ball-driven plane (i.e., the x-coordinate referred to the direction perpendicular to the y-coordinate, and the z-coordinate referred to the vertical direction). The Laboratory Virtual Instrument Engineering Workbench (LabVIEW) was used to generate and synchronize the auditory signals to the kinematic recordings. The experimenter triggered a go-signal (i.e., a man’s voice saying ‘go’, lasting 500 ms), which concurrently initiated the kinematic recordings. A custom-made LabVIEW routine used positional data of the LED to calculate velocity, acceleration and jerk in the y-direction in real time. A stop-signal (i.e., 150 ms tone at 500 Hz) appeared either 50 ms after the end of backswing (i.e., at the start of the downswing) or 100–250 ms after the ball-putter contact. The end of the backswing was defined as the velocity equaling zero after the initial increase in velocity (i.e., start of the backswing), while the ball-putter contact was detected as follows: (1) the jerk suddenly changed from a low value (i.e., < −1000 m/s³) to a high value (i.e., > 1000 m/s³), (2) the acceleration was less than −10 m/s², and (3) to prevent a false detection of ball-putter contact (e.g., because the club touches the ground during the downswing), the LED must have crossed its initial position.
Optorak 3020 用于以 200 Hz 频率记录安装在推杆轴上的 LED 的 x、y 和 z 坐标，其中 y 坐标指的是球驱动平面（即 x 坐标）指垂直于 y 坐标的方向，z 坐标指垂直方向）。实验室虚拟仪器工程工作台 (LabVIEW) 用于生成听觉信号并将其同步到运动学记录。实验者触发了一个“开始”信号（即，一个男人的声音说“开始”，持续 500 毫秒），同时启动运动学记录。定制的 LabVIEW 例程使用 LED 的位置数据来实时计算 y 方向的速度、加速度和加加速度。停止信号（即 500 Hz 的 150 ms 音调）在上杆结束后 50 毫秒（即下杆开始时）或球推杆接触后 100-250 毫秒出现。后摆结束定义为速度初始增加后（即后摆开始）为零，同时检测球推杆接触如下：（1）急动度突然从低值变化（ (即 < -1000 m/s ³ ) 到高值 (即 > 1000 m/s ³ )，(2) 加速度小于 -10 m/s ² ，以及 (3) 防止误检测球推杆接触（例如，因为球杆在下挥杆过程中接触地面），LED 一定已经越过其初始位置。

Camera 相机

A digital camera (Sony RX100IV or Sony Rx10III) was used to record the final position of the ball relative to the target. The highest resolution (5472 × 3648 pixels), the widest lens aperture (f/1.8 for Sony RX100IV, f/2.4 for Sony Rx10III) and the date/time function were used. The camera was mounted on a frame 1.46 m above the target. A bubble level attached to the camera ensured the lens was positioned parallel to the green. Before each experimental session, a tape measure (in mm) was placed on the green for calibration purposes (Neumann & Thomas, Citation2008).
使用数码相机（Sony RX100IV 或 Sony Rx10III）记录球相对于目标的最终位置。使用了最高分辨率（5472 × 3648 像素）、最宽的镜头光圈（索尼 RX100IV 为 f/1.8，索尼 Rx10III 为 f/2.4）和日期/时间功能。相机安装在目标上方 1.46 m 的框架上。相机上安装的气泡水平仪确保镜头与果岭平行。在每次实验之前，将卷尺（以毫米为单位）放在果岭上以进行校准（Neumann & Thomas，引文2008 ）。

Go Task (without Stop-Signals)
执行任务（无停止信号）

We followed Beilock and Gray (Citation2012) by starting the experiment with a Go Task (
我们遵循 Beilock 和 Gray（引文2012 ），通过 Go 任务开始实验（Figure 2a 图2a) in which no stop trials were given. This allowed us to determine whether randomly interspersing go trials with stop trials, as in the Stop-Signal Task (see below) affects putting accuracy and kinematics. At the start of the Go Task, participants were presented with an image showing the starting posture of a golf putt, and they were asked to emulate the starting posture on the image before making a putt. The image was posted on the wall so that participants could see it anytime they wanted. No additional guidance regarding putting technique was given, except for one experimenter instructing them that putting involved first moving the club backward and then forward to strike the ball. This was only done once at the beginning of the Go Task, without cueing attention to other aspects of the putting movements. The Go Task consisted of one practice block of eight trials (i.e., two trials per distance in randomized order) and one test block of thirty-two trials (i.e., eight trials per distance in randomized order). The practice block allowed participants to familiarize with the putting technique and experimental procedure. On each trial, participants were instructed about the putting distance and asked to post themselves at the corresponding starting line. After the participants informed the experimenter that they were ready to putt, the experimenter clicked on the mouse to generate the go-signal and start the kinematic recording. After hearing the go-signal, the participants started to make a putt and try to roll the ball into the target. They were told that the nearer the ball would stop to the target the better the performance. After the ball stopped rolling, a second experimenter took a photograph if the ball ended in the photographed area or took a photograph of a paper noting either ‘too soft’ or ‘too hard’ when the ball did not end in the photographed area. Then, the ball was returned to the participant to prepare for the next trial. The final position of the ball was visible to participants, but no other feedback was given.
），其中没有进行停止试验。这使我们能够确定随机散布的围棋试验与停止试验是否会影响推杆准确性和运动学，如停止信号任务（见下文）。在围棋任务开始时，参与者会看到一张显示高尔夫推杆起始姿势的图像，并要求他们在推杆之前模仿图像上的起始姿势。该图像被贴在墙上，以便参与者可以随时查看。除了一位实验者指导他们，推杆包括首先向后移动球杆，然后向前移动球杆来击球之外，没有给出有关推杆技术的额外指导。这仅在围棋任务开始时完成一次，没有提示人们注意推杆动作的其他方面。围棋任务包括一个包含八项试验的练习块（即，每个距离按随机顺序进行两项试验）和一个包含三十二项试验的测试块（即每个距离按随机顺序进行八项试验）。练习区让参与者熟悉推杆技术和实验程序。在每次试验中，参与者都被告知推杆距离，并被要求站在相应的起跑线上。当参与者通知实验者他们准备好推杆后，实验者点击鼠标生成开始信号并开始运动学记录。听到开始信号后，参与者开始推杆并尝试将球滚入目标。他们被告知，球停得越接近目标，表现就越好。 球停止滚动后，如果球结束在拍摄区域，第二位实验者会拍一张照片；如果球没有结束在拍摄区域，则拍摄一张纸的照片，注明“太软”或“太硬”。然后，球被归还给参与者，为下一次试验做准备。参与者可以看到球的最终位置，但没有给出其他反馈。

FIGURE 2. Flowchart of two tasks. Note. (a) Go Task. (b) Stop-Signal Task (SST).
图 2.两项任务的流程图。笔记。 (a) 执行任务。 (b) 停止信号任务（SST）。

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Stop-Signal Task (SST) 停止信号任务 (SST)

The SST ( 海温（Figure 2b 图2b) consisted of go trials, stop trials and filler trials. Go trials were identical to the trials in the Go Task, that is, participants were asked to make a putt and try to roll the ball into the target after hearing the go-signal. Stop and filler trials were different from go trials. On stop trials, besides the go-signal, a second auditory signal (i.e., the stop-signal) was presented 50 ms after reaching the end of the backswing. This instant in time was used because: (1) Beilock and Gray (Citation2012) found that the differences in stopping performance between experts and novices were only found when a stop-signal was presented during the downswing; (2) our pilot study showed that some participants were unable to stop when the stop-signal occurred longer than 50 ms after the end of the backswing. On filler trials, in addition to the go-signal, a second auditory signal was presented 100–250 ms after ball-putter contact rather than 50 ms after reaching the end of backswing. Filler trials were to ensure that participants did not anticipate stopping at the end of the backswing (Beilock & Gray, Citation2012). In the SST, participants were instructed to stop the putt movement as fast as possible after the stop-signal was presented during the downswing (i.e., stop trials), but they were also instructed to finish the putt and try to roll the ball into the target when no stop-signal occurred (i.e., go trials) or when the stop-signal was after ball-putter contact (i.e., filler trials). It was emphasized that they would make the putt movement in a similar way as they did in Go Task and not to wait for the stop-signal. Participants completed two test blocks of thirty-two trials with short breaks between blocks. Each block comprised of sixteen go trials (i.e., four trials per distance), twelve stop trials (i.e., three trials per distance) and four filler trials (i.e., one trial per distance). The trial type and putting distance were randomized within blocks. Before the test blocks, participants performed a practice block of sixteen trials to familiarize with the procedures. This included two go trials, one stop trial and one filler trial for each distance. Irrespective of performance, the second experimenter took a photograph after participants completed a trial. For go trials and filler trials, the same procedure was followed as in the Go Task. For the stop trials, a photograph was taken from the empty area if participants successfully stopped, otherwise, a photograph of a paper noting “no stop” was taken. We also manually wrote down the outcome of each stop trial. Again, the final position of the ball was visible to participants, but no other feedback was given.
）包括继续试验、停止试验和填充试验。围棋试验与围棋任务中的试验相同，即参与者被要求在听到“围棋”信号后进行推杆并尝试将球滚入目标。停止和填充试验与​​继续试验不同。在停止试验中，除了开始信号之外，在到达后摆结束后 50 毫秒还会出现第二个听觉信号（即停止信号）。使用这个时间点是因为：（1）Beilock 和 Gray（引文2012 ）发现，专家和新手之间的停止表现差异只有在下杆过程中出现停止信号时才会出现； (2) 我们的试点研究表明，当后摆结束后 50 毫秒内出现停止信号时，一些参与者无法停止。在填充试验中，除了启动信号之外，在推杆接触后 100-250 毫秒（而不是到达后挥杆结束后 50 毫秒）出现第二个听觉信号。填充物试验是为了确保参与者不会预期在后摆结束时停止（Beilock & Gray，引文2012 ）。在SST中，参与者被要求在下杆过程中出现停止信号后尽快停止推杆运动（即停止试验），但他们也被要求完成推杆并尝试将球滚入球内。当没有停止信号发生时（即，继续试验）或当停止信号发生在球推杆接触之后（即，填料试验）时，目标。他们强调，他们将以与 Go Task 中类似的方式进行推杆动作，而不是等待停止信号。 参与者完成了三十二项试验中的两个测试块，测试块之间有短暂的休息。每个块由十六个走试验（即每个距离四次试验）、十二个停止试验（即每个距离三个试验）和四个填充试验（即每个距离一个试验）组成。试验类型和推杆距离在区块内随机进行。在测试块之前，参与者进行了十六次试验的练习块以熟悉程序。这包括每个距离的两次试行试验、一次停站试验和一次填充试验。无论表现如何，第二位实验者都会在参与者完成试验后拍照。对于 go 试验和填充试验，遵循与 Go 任务中相同的程序。对于停止试验，如果参与者成功停止，则从空白区域拍摄一张照片，否则，拍摄一张注明“禁止停止”的纸的照片。我们还手动记下每次停止试验的结果。同样，参与者可以看到球的最终位置，但没有给出其他反馈。

Results 结果

The paired-t test revealed that the putting score was significantly higher in the SST than in the Go Task, t(66) = 2.32, p = 0.02, d = 0.28 (SST: 2.3 ± 0.3, Go Task: 2.2 ± 0.3). To also assess performance changes within the two tasks, a 2 (task: Go Task, SST) by 2 (block: first, last) ANOVA with repeated measures on both factors was conducted, which revealed that the putting score differed significantly between tasks, F(1,66) = 10.39, p = 0.002, η_p² = 0.14, and blocks, F(1,66) = 6.86, p = 0.011, η_p² = 0.09. Importantly, an interaction between block and task was also found, F(1,66) = 12.09, p < 0.001, η_p² = 0.16 (
配对 t 检验显示，SST 中的推杆得分显着高于 Go 任务，t(66) = 2.32， p = 0.02， d = 0.28（SST：2.3 ± 0.3，Go Task：2.2 ± 0.3） 。为了评估这两项任务中的表现变化，我们对这两个因素进行了 2（任务：Go 任务、SST）乘 2（块：第一个、最后一个）方差分析，并重复测量这两个因素，结果表明任务之间的推杆分数存在显着差异， F(1,66) = 10.39， p = 0.002， η _p ² = 0.14，并且块，F(1,66) = 6.86， p = 0.011， η _p ² = 0.09。重要的是，还发现了块和任务之间的交互作用，F(1,66) = 12.09, p < 0.001, η _p ² = 0.16 (Figure 3 图3). Post hoc comparisons indicated that the putting score in the first block of the Go Task was significantly lower than in the last block of the Go Task, and in the first and last block of the SST. The first and last block of the SST did not differ.
）。事后比较表明，Go 任务的第一个区块的推杆得分显着低于 Go 任务的最后一个区块以及 SST 的第一个和最后一个区块。 SST 的第一个和最后一个块没有区别。

FIGURE 3. The putting score on go trials in the first and last block of the Go Task and Stop-Signal Task (SST). Note. Error bar represents the standard error of the mean. *** p < 0.001.
图 3.围棋任务和停止信号任务 (SST) 的第一个和最后一个区块的围棋试验推杆得分。笔记。误差条代表平均值的标准误差。 *** p < 0.001。

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Table 2 表2 shows the outcomes of the Pearson’s correlation analyses. The significant correlations were limited to the MS-C factor. A significant positive correlation was found between MS-C score and stopping rate (p = 0.02), indicating that higher MS-C scores were associated with more successful stopping. In addition, a significant positive correlation between MS-C score and stopping time was found (p = 0.016Footnote³), indicating that higher MS-C scores were associated with longer stopping time. We did not find significant positive or negative correlations between CMP score and stopping rate (p = 0.23) and stopping time (p = 0.47), respectively. Additionally, no positive or negative correlations were revealed between the amount of verbal knowledge and stopping rate (p = 0.45) and stopping time (p = 0.36), respectively. Finally, Pearson’s correlation analysis also did not discern positive correlations between the amount of verbal knowledge and MS-C score (p = 0.17), CMP score (p = 0.47).
显示 Pearson 相关分析的结果。显着相关性仅限于 MS-C 因子。 MS-C 评分与停止率之间存在显着正相关性 ( p = 0.02)，表明 MS-C 评分越高，停止成功率越高。此外，还发现 MS-C 评分与停止时间之间存在显着正相关（ p = 0.016脚注³ ），表明较高的 MS-C 评分与较长的停止时间相关。我们没有发现 CMP 分数与停止率 ( p = 0.23) 和停止时间 ( p = 0.47) 之间分别存在显着的正相关或负相关。此外，言语知识量与停止率（ p = 0.45）和停止时间（ p = 0.36）之间没有显示出正相关或负相关。最后，Pearson 的相关分析也没有发现言语知识量与 MS-C 分数（ p = 0.17）、CMP 分数（ p = 0.47）之间的正相关性。

Although we found a significant correlation between MS-C score and stopping time, the direction was not as we expected. In other words, although participants with higher MS-C score, which is interpreted as having a higher inclination for conscious movement monitoring, were found to have higher stopping rates, they did not show shorter stopping time. In addition, we had not anticipated that more successful, higher stopping rates would be associated with longer stopping time, but we found that a higher stopping rate was significantly correlated with longer stopping time (p < 0.001). To further explore these findings, we considered two possible explanations. First, participants may have intentionally adjusted the stroke kinematics in the SST in response to the stopping requirement. In particular, they may have slowed down the time for downswing to gain more time to ensure successful stopping in the SST compared to the Go Task. Alternatively, rather than intentionally adjusting the stroke kinematics in the SST, some participants may have swing kinematics that hinder stopping, while swing kinematics of other participants may facilitate stopping. In other words, the inherent swing kinematics may have indirectly affected inhibition. In particular, participants who show a shorter downswing time have less time to successfully stop in the SST than participants who show a longer downswing time.
尽管我们发现 MS-C 分数和停止时间之间存在显着相关性，但方向并不像我们预期的那样。换句话说，虽然 MS-C 分数较高（被解释为有意识运动监测倾向较高）的参与者被发现具有较高的停止率，但他们并没有表现出较短的停止时间。此外，我们没有预料到更成功、更高的停止率会与更长的停止时间相关，但我们发现更高的停止率与更长的停止时间显着相关（ p <0.001）。为了进一步探讨这些发现，我们考虑了两种可能的解释。首先，参与者可能有意调整 SST 中的划水运动学以响应停止要求。特别是，与 Go 任务相比，他们可能会减慢下杆的时间，以获得更多的时间来确保在 SST 中成功停止。或者，一些参与者可能具有阻碍停止的摆动运动学，而其他参与者的摆动运动学可能有助于停止，而不是有意地调整SST中的击球运动学。换句话说，固有的摆动运动学可能间接影响了抑制作用。特别是，与表现出较长下摆时间的参与者相比，表现出较短下摆时间的参与者在 SST 中成功停止的时间更少。

To find out which explanation is more likely, we firstly submitted downswing time to a 2 (task: Go Task, SST) by 2 (block: first, last) ANOVA with repeated measures on both factors. If the first explanation is correct, then we would expect to find longer downswing time in the SST compared to the Go Task, and especially in comparison with the last block of the Go Task (as performance was not yet stabilized in the first block of the Go Task, see above). This pattern was not found. Instead, two-way repeated measures ANOVA for the downswing time did show a significant effect of task, F(1,66) = 5.71, p = 0.02, η_p² = 0.08 and a significant interaction between task and block, F(1,66) = 11.75, p = 0.001, η_p² = 0.15. Post hoc comparisons indicated that the downswing time in the last block of the SST (0.34 ± 0.08s) was significantly shorter (not longer) than in the last block of the Go Task (0.36 ± 0.09s). No other differences were found.
为了找出哪种解释更有可能，我们首先将下降时间提交给 2（任务：Go Task，SST）乘 2（块：第一个，最后一个）方差分析，并对这两个因素进行重复测量。如果第一个解释是正确的，那么我们预计与 Go 任务相比，SST 中会出现更长的下降时间，特别是与 Go 任务的最后一个块相比（因为在第一个块中性能尚未稳定）执行任务，见上文）。没有找到这个模式。相反，下降时间的双向重复测量方差分析确实显示了任务的显着影响，F(1,66) = 5.71， p = 0.02， η _p ² = 0.08，以及任务和块之间的显着交互作用，F(1 ,66) = 11.75， p = 0.001， η _p ² = 0.15。事后比较表明，SST 最后一个块的下摆时间（0.34±0.08s）明显短于（不是更长）Go Task 最后一个块的下摆时间（0.36±0.09s）。没有发现其他差异。

If the second explanation is correct, then the relations between MS-C score and stopping rate and stopping time would be mediated by the downswing time in the SST. The Model 4 of PROCESS Macro for SPSS was used to conduct a mediation analysis, which estimates indirect effects using a non-parametric bootstrapping method (Hayes, Citation2017). If the bootstrap confidence intervals (CI) of the indirect effect do not include zero, the indirect effect is significant.
如果第二种解释是正确的，那么 MS-C 分数与停止率和停止时间之间的关系将由 SST 的下降时间来调节。 SPSS PROCESS Macro 的模型 4 用于进行中介分析，该分析使用非参数引导方法估计间接影响（Hayes，引文2017 ）。如果间接效应的自举置信区间 (CI) 不包括零，则间接效应显着。Figure 4(a) 图4(a) shows the unstandardized regression coefficients of the mediation model for predicting the effect of MS-C score on stopping rate via downswing time. As can be seen in
显示了中介模型的非标准化回归系数，用于预测 MS-C 分数通过下杆时间对停止率的影响。可以看出Figure 4(a) 图4(a), the MS-C score was positively correlated with downswing time, that is, the higher the MS-C score, the longer the downswing time (B = 0.005, p = 0.019). And the downswing time was positively correlated with stopping rate, indicating that the longer the downswing time, the higher stopping rate (B = 322.334, p < 0.001). The total effect of MS-C score on stopping rate was significant (p = 0.047, 95% CI = 0.026 to 3.197). The bootstrap CI based on 5000 bootstrap resamples was entirely above zero, 95% CI = 0.176 to 2.907, indicating that the indirect effect of MS-C score on stopping rate was significant. In addition, no direct effect of the MS-C score on stopping rate was found (B = 0.071, p = 0.886, 95% CI = −0.916 to 1.058). These results suggest that individuals with a higher MS-C, indicating a higher inclination for conscious movement monitoring, showed longer downswing time, which, in turn, increased the stopping rate.
，MS-C得分与下挥杆时间呈正相关，即MS-C得分越高，下挥杆时间越长（ B = 0.005， p = 0.019）。并且下降时间与停止率呈正相关，表明下降时间越长，停止率越高（ B = 322.334， p < 0.001）。 MS-C 评分对停止率的总影响显着（ p = 0.047，95% CI = 0.026 至 3.197）。基于 5000 个 bootstrap 重采样的 bootstrap CI 完全高于零，95% CI = 0.176 至 2.907，表明 MS-C 评分对停止率的间接影响显着。此外，未发现 MS-C 评分对停止率有直接影响（ B = 0.071， p = 0.886，95% CI = -0.916 至 1.058）。这些结果表明，MS-C 较高的个体（表明有意识运动监测的倾向较高）表现出较长的下杆时间，这反过来又增加了停止率。

FIGURE 4. Mediation models illustrating the impact of MS-C score on stopping performance via the downswing time (s) in the Stop-Signal Task (SST). Note. (a) The mediation model of the impact of MS-C score on stopping rate (%) via the downswing time. (b) The mediation model of the impact of MS-C score on stopping time (ms) via the downswing time. The numbers refer to unstandardized coefficients (see also text); ***p < 0.001, *p < 0.05.
图 4.中介模型通过停止信号任务 (SST) 中的下挥杆时间说明 MS-C 分数对停止性能的影响。笔记。 (a) MS-C 分数通过下杆时间影响停止率 (%) 的中介模型。 (b) MS-C 分数通过下杆时间影响停止时间 (ms) 的中介模型。这些数字指的是非标准化系数（另见文本）； *** p < 0.001，* p < 0.05。

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Similarly,  相似地，Figure 4(b) 图4(b) shows the unstandardized regression coefficients of the mediation model for predicting the effect of the MS-C score on stopping time via downswing time in the SST. It again shows that MS-C score was associated with downswing time, indicating that the higher MS-C score, the longer the downswing time (B = 0.004, p = 0.042). It also shows that the downswing time was associated with stopping time, which implies that the longer the downswing time, the longer the stopping time (B = 924.782, p < 0.001). The total effect of MS-C score on stopping time was significant, p = 0.028, 95% CI = 0.520 to 8.928. The bootstrap CI based on 5000 bootstrap resamples included zero, 95% CI = −0.100 to 7.808, indicating that there was no indirect effect of MS-C score on stopping time. In addition, the direct effect of MS-C score on stopping time was not significant, B = 0.981, p = 0.388, 95% CI = −1.276 to 3.237. These results indicate that the individuals with higher MS-C score, indicating higher inclination for conscious investment in movement monitoring, showed longer stopping time in the SST, but no mediation effect of downswing time was found.
显示了中介模型的非标准化回归系数，用于通过SST 中的下降时间来预测 MS-C 分数对停止时间的影响。再次表明，MS-C 得分与下杆时间相关，表明 MS-C 得分越高，下杆时间越长（ B = 0.004， p = 0.042）。它还表明，下摆时间与停止时间相关，这意味着下摆时间越长，停止时间就越长（ B = 924.782， p < 0.001）。 MS-C 评分对停止时间的总影响显着， p = 0.028，95% CI = 0.520 至 8.928。基于 5000 个 bootstrap 重采样的 bootstrap CI 包括零、95% CI = -0.100 至 7.808，表明 MS-C 评分对停止时间没有间接影响。此外，MS-C评分对停止时间的直接影响并不显着， B = 0.981， p = 0.388，95% CI = -1.276至3.237。这些结果表明，MS-C 得分较高的个体，表明在运动监测方面有意识投入的倾向较高，在 SST 中表现出较长的停止时间，但没有发现下杆时间的中介作用。

Discussion 讨论

Increased levels of conscious investment in movement monitoring and control have typically been shown to impair motor performance in sports (Beilock & Carr, Citation2001; Masters, Citation1992; Maxwell et al., Citation2006). Notably, however, two recent studies have reported discordant findings with respect to inhibition: persons that are more likely to consciously invest in movement monitoring and control demonstrate better and faster stopping of movement (Beilock & Gray, Citation2012; Park et al., Citation2020). The present study set out to further explore this association. We reasoned, grounded in ecological psychology and dynamic systems approaches, that the observed association emerges because conscious investment in movement monitoring and control acts to reduce the number of individual degrees of freedom to be controlled (Lohse et al., Citation2010; van Ginneken et al., Citation2018), thereby allowing faster inhibition compared to when movement control is distributed over a larger number of degrees of freedom (Hervault et al., Citation2021). Consistent with our hypothesis, we found that individuals with higher scores on the MS-C factor of the MSRS, which following earlier proposals by Malhotra et al. (Citation2015, see also Jackson et al., Citation2006) can be associated with higher inclinations for conscious investment in the monitoring of movement without actively interfering in its execution, displayed higher stopping rate. However, we also found that individuals who stopped more often showed longer stopping time, while shorter stopping time were expected. By contrast, no associations were found for the CMP factor, which is associated with the inclination for conscious movement control (Jackson et al., Citation2006; Malhotra et al., Citation2015), and stopping variables, and also the amount of verbal knowledge did not predict stopping performance. Additional exploration of movement kinematics suggested that participants with a low MS-C score or a low inclination for conscious movement monitoring made relatively fast downswings, which were less often successfully stopped, but if they were successfully inhibited then the stopping time were necessary short. Conversely, individuals with a high MS-C score or a high inclination for conscious movement monitoring tended to make slower downswings, which granted more successful stopping.
增加对运动监测和控制的有意识投入通常会损害运动中的运动表现（Beilock & Carr， Citation 2001 ；Masters， Citation 1992 ；Maxwell 等人， Citation 2006 ）。然而，值得注意的是，最近的两项研究报告了关于抑制的不一致的结果：更有可能有意识地投资于运动监测和控制的人表现出更好更快的停止运动（Beilock & Gray， Citation 2012 ；Park et al.， Citation） 2020 ）。本研究旨在进一步探讨这种关联。基于生态心理学和动态系统方法，我们推断，所观察到的关联的出现是因为有意识地投资于运动监测和控制，从而减少了受控制的个体自由度的数量（Lohse 等人，引文2010 ；van Ginneken 等人）等人，引文2018 ），从而与运动控制分布在更大数量的自由度上时相比，可以实现更快的抑制（Hervault 等人，引文2021 ）。与我们的假设一致，我们发现在 MSRS 的 MS-C 因子上得分较高的个体，这遵循 Malhotra 等人的早期提议。 （引文2015 ，另见 Jackson 等人，2015 年），引文2006 ）可能与有意识地投资于运动监控而不主动干预其执行的更高倾向相关，显示出更高的停止率。然而，我们还发现，经常停车的人表现出更长的停车时间，而预期的停车时间更短。相比之下，没有发现 CMP 因素的关联，该因素与有意识运动控制的倾向有关（Jackson 等人， Citation 2006 ；Malhotra 等人， Citation 2015 ）、停止变量以及言语量。知识并不能预测停止表现。对运动运动学的进一步探索表明，MS-C 分数较低或有意识运动监测倾向较低的参与者会做出相对较快的下挥杆，成功停止的情况较少，但如果成功抑制，则停止时间必须很短。相反，MS-C 分数高或有意识运动监测倾向高的人往往下杆速度较慢，从而更成功地停止。

These findings provide partial support for our original hypothesis. We anticipated that probable higher levels of conscious movement investment would promote inhibition or stopping rate, because it would promote shorter stopping time. Yet, we found that individuals with higher inclination for conscious movement monitoring (but not control) managed to stop more often but tended to have longer stopping time. One possible cause for this paradoxical result would be that these individuals prolonged the duration of the downswing to have more time to stop. Yet, no clear adjustments and certainly no lengthening occurred in the temporal characteristics of the downswing in the block with stop trials (i.e., SST) relative to the block without stop trials (i.e., Go Task), making a strategic adjustment in swing kinematics unlikely. Rather, the observed mediation effect of the kinematic characteristics of the downswing (i.e., downswing time) on the relation between MS-C score and stopping rate, indicate that individuals with a lower inclination for conscious movement monitoring show kinematic features in their downswing that make it harder to stop the putt successfully. We suspect that a high inclination for conscious movement monitoring perhaps invites a putting style with a relatively slow downswing (which perhaps is more apt for monitoring). Such a strategy would be consistent with previous studies. For example, novice golfers exhibited a longer time interval between start of downswing and peak acceleration when they consciously focusing on gripping the club and the position of elbows compared to when they are focusing on the target (Pelleck & Passmore, Citation2017). In this respect, other studies confirm that an internal focus of attention toward movement execution increases conscious movement monitoring and control relative to an external focus of attention (e.g., Poolton et al., Citation2006). It is also reminiscent of previous observations by Malhotra et al. (Citation2014), who showed that individuals with higher inclination for conscious movement monitoring performed more slowly on novel and well-practiced laparoscopic tasks. Importantly, this explanation implies that (the inclination for) conscious movement monitoring (and control) does not directly affect inhibition performance. Instead, the association would largely be indirect, which is partially confirmed by the mediation analyses. Increased conscious movement monitoring may induce movement styles that make it easier to halt the movement.
这些发现为我们最初的假设提供了部分支持。我们预计，可能更高水平的有意识运动投资将促进抑制或停止率，因为它会缩短停止时间。然而，我们发现，更倾向于有意识的运动监测（而不是控制）的人能够更频繁地停下来，但往往有更长的停止时间。造成这种矛盾结果的一个可能原因是这些人延长了下风期的持续时间，以便有更多的时间停止。然而，相对于没有停止试验的区块（即Go Task），有停止试验的区块（即SST）的下挥杆的时间特征没有发生明显的调整，当然也没有发生延长，这使得挥杆运动学的策略调整不太可能。相反，观察到的下挥杆运动学特征（即下挥杆时间）对 MS-C 得分和停止率之间关系的中介作用表明，意识运动监测倾向较低的个体在下挥杆时表现出运动学特征，这使得更难成功地停止推杆。我们怀疑，有意识的运动监控的高度倾向可能会导致下挥杆相对缓慢的推杆风格（这可能更适合监控）。这样的策略与之前的研究是一致的。例如，新手高尔夫球手在有意识地专注于握杆和肘部位置时，与专注于目标时相比，在下杆开始和峰值加速之间表现出更长的时间间隔（Pelleck & Passmore，引文2017 ）。 在这方面，其他研究证实，相对于外部注意力焦点，对运动执行的内部注意力焦点增加了有意识的运动监控和控制（例如，Poolton等人，引文2006 ）。这也让人想起 Malhotra 等人之前的观察。 （引文2014 ），他表明，更倾向于有意识运动监测的个体在新颖且熟练的腹腔镜任务中表现得更慢。重要的是，这种解释意味着有意识的运动监测（和控制）（的倾向）并不直接影响抑制表现。相反，这种关联很大程度上是间接的，中介分析部分证实了这一点。增加有意识的运动监测可能会诱发更容易停止运动的运动方式。

Our results differed from those of Beilock and Gray (Citation2012), who observed that novices, who presumably have increased levels of conscious investment in movement monitoring and control (i.e., novices), had reduced stopping time compared to skilled golf players. They did not report differences in stopping rate. It is not immediately clear why the relation between conscious movement investment and stopping time appears opposite in the two studies, but it may stem from methodological differences. Most importantly, Beilock and Gray (Citation2012) refer to differences between novices to skilled players when referring to a decrease in stopping time, while we refer to differences within a group of novice players. Also, Beilock and Gray (Citation2012) had the stop-signal in both the backswing and downswing phases, while we had restricted the stop-signal to the downswing phase only.
我们的结果与 Beilock 和 Gray 的结果不同（引文2012 ），他们观察到，与熟练的高尔夫球手相比，新手可能在运动监控和控制方面有意识地投入更多（即新手），因此减少了停止时间。他们没有报告停止率的差异。目前尚不清楚为什么两项研究中有意识的运动投入和停止时间之间的关系看起来相反，但这可能源于方法论上的差异。最重要的是，Beilock 和 Gray（ Citation 2012 ）在提到停止时间的减少时提到了新手与熟练玩家之间的差异，而我们则指的是一组新手玩家之间的差异。此外，Beilock 和 Gray（ Citation 2012 ）在上杆和下杆阶段都有停止信号，而我们仅将停止信号限制在下杆阶段。

Beforehand, we anticipated similar associations with inhibition for conscious movement monitoring and conscious movement control. However, unlike for conscious movement monitoring (as measured by the MS-C factor of the MSRS), no relationships were found between the inclination for conscious movement control (i.e., as measured by the CMP factor) and the inhibition performance, and not with the downswing time either. We can only speculate about the absence of these relationships (e.g., conscious movement control might manifest itself more strongly in the planning before rather than during the stroke, Beilock & Gray, Citation2012), but it may be consistent with the nonappearance of any relationship with the amount of declarative knowledge reported by the participants. Yet, this lack of association with the amount of declarative knowledge in itself needs careful interpretation, because only a subsample of participants filled out the verbal knowledge protocol. Additionally, since the final trial before completing the verbal knowledge protocol could also be a stop trial, we asked participants to recall how in general they made the putting movement rather than during the final trial, as is typically done in this protocol. Accordingly, participants may have tended to recall generic knowledge of putting strokes instead of the episodic knowledge that more directly reflects actual investment of conscious movement control (Beilock & Carr, Citation2001).
之前，我们预计有意识运动监测和有意识运动控制与抑制存在类似的关联。然而，与有意识运动监测（通过 MSRS 的 MS-C 因子测量）不同，在有意识运动控制倾向（即通过 CMP 因子测量）和抑制性能之间没有发现任何关系，并且与抑制性能没有关系。下风期也一样。我们只能推测这些关系是否不存在（例如，有意识的运动控制可能在中风之前而不是中风期间的计划中表现得更强烈，Beilock & Gray， Citation 2012 ），但这可能与任何关系的不出现一致以及参与者报告的陈述性知识量。然而，这种与陈述性知识量本身缺乏关联的情况需要仔细解释，因为只有一小部分参与者填写了口头知识协议。此外，由于完成口头知识协议之前的最终试验也可能是停止试验，因此我们要求参与者回忆他们一般如何进行推杆动作，而不是像本协议中通常所做的那样在最终试验期间进行。因此，参与者可能倾向于回忆击球的一般知识，而不是更直接反映有意识运动控制的实际投入的情景知识（Beilock＆Carr， Citation 2001 ）。

Conclusion 结论

In the current study, we further investigated the purported relationship between conscious movement monitoring and control and inhibition in a more complex putting task, where conscious movement investment is more likely to occur (Beilock & Gray, Citation2012). The current study, however, did not provide further evidence that probable increased levels of conscious movement monitoring and control goes to together with better inhibition performance. Instead, the present findings suggest that the relationship is more indirect, with individuals that are more likely to consciously monitor movement possibly producing slower movements that are easier to stop or inhibit.
在当前的研究中，我们进一步研究了在更复杂的推杆任务中，有意识的运动监测和控制与抑制之间的关系，在该任务中更有可能发生有意识的运动投入（Beilock＆Gray，引文2012 ）。然而，目前的研究没有提供进一步的证据来证明有意识运动监测和控制水平的提高可能与更好的抑制表现有关。相反，目前的研究结果表明，这种关系更为间接，更有可能有意识地监控运动的个体可能会产生更慢的运动，更容易停止或抑制。