PONE-D-24-25633Effect of Emotional Regulation on Performance of Shooters during Competition: an Ecological Momentary  Assessment StudyPLOS ONE

Dear Dr. Hua,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Editor comment. I was fortunate to receive feedback from three reviewers, all of whom are top experts. They found the paper well-written and the topic interesting, but there are some important issues to address. R1 mentioned the need for more clarity, especially in the abstract and the way you interpret your findings, along with how you operationalise "flexibility" in emotion regulation. R1 also suggested adding some further analyses to deepen your insights. R2 pointed out the need for more transparency around your statistical methods, including clearer explanations of the software and models you used, and asked for more detailed reporting of the regression equations and coefficients. The most significant concerns came from R3, who raised concerns about the validity of the items used to measure emotion regulation strategies (especially whether single items can be used from the context of the ensemble of the questionnaire) and noted that the time factor was not incorporated in your longitudinal analysis, which R3 argues is essential. These are critical points that will require careful revision. I thereby invite you to submit a revised manuscript that includes a point-by-point response to all of the reviewers' comments.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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: Partly

Reviewer #2: Partly

Reviewer #3: No

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

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5. 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: In this study, the authors assessed emotion regulation strategies in female and male shooters at both first-level and national-level using longitudinal ecological momentary assessment (EMA). They aimed to predict the impact of these strategies on shooting performance. The results revealed differences in emotion regulation based on gender and skill level, and their relation to shooting performance.

The study is compelling, with the use of EMA enhancing the ecological validity of the findings. However, the manuscript lacks clarity in several sections. Additional analyses could better address the research questions posed by the authors. While the discussion provides sufficient explanations for many results, it overlooks some key points. Therefore, I recommend a major revision of the manuscript.

See below for detailed feedback Unfortunately, the authors did not provide page or line numbers. Therefore, I will refer to section headings in my feedback:

1. In the Abstract, you state: “Inaccurate perception of situational demands and difficulty in using engagement strategies are the main emotion regulation processes that affect athletic performance.” However, this conclusion appears to be unsupported by the presented results. The study does not seem to assess the accuracy of athletes' perception of situational demands. Moreover, this statement does not align with the primary findings of your paper, which focus on the differences in emotion regulation strategies between male and female athletes, as well as between first-level and national-level competitors. Consider revising the Abstract to more accurately reflect the key points and results of your research.

2. You refer to the flexibility in the usage of emotion regulation strategies. However, it is unclear which results of your study indicate high or low flexibility. Is it the sum score of the usage of all strategies? Conclusions regarding overall flexibility would require calculating a variable that numerically captures this construct. I am not sure if your data can provide information on emotional flexibility. Additionally, interpreting this in absolute terms would be difficult, as you would require a non-athlete control group to determine if your sample is indeed less flexible in their usage of emotional control strategies. Therefore, I suggest that you only interpret differences between your subgroups (gender and skill level). If you cannot operationalize the flexibility in emotional regulation, please avoid jumping to conclusions (e.g., “Athletes had low flexibility in emotion regulation …” [Abstract], “Low-level athletes have lower emotional regulation flexibility compared to high-level athletes, and they demonstrate inflexibility in both situational demands and specific” [4. Limitations], etc.).

3. You use some terminology from shooting sports that laypeople (such as myself) might find difficult to understand. Specifically, please elaborate on the outcomes of your models:

- What is the “proportion of good ten rings” [2.4 Analysis] exactly?

- What is meant by “speed of grip force” [Section 1.1] and how is it related to shooting performance?

- What exactly is meant by “slow the production of force” [Section 3.2] and again, how does this relate to performance?

Additionally, in Section 1.3 you refer to “rapidly changing competitive sports situations.” What do you mean by that? How is this related to shooting (i.e., what are the changing situations in a shooting competition)?

4. Regarding your power analysis: If I am not mistaken, gPower is not able to perform power analyses for multilevel linear models. It appears that you computed a power analysis for a linear multiple regression with 4 predictors, resulting in the reported detectable effect sizes of f²=0.20 (I assume that you refer to the effect size parameter f², please make so explicitly). However, a power analysis based on a (non-hierarchical) linear regression is not suitable for a multilevel analysis.

Please conduct a suitable power analysis (for example, using a simulation-based approach) or use another method of justification for your sample size. You may find the following resource helpful:

https://online.ucpress.edu/collabra/article/8/1/33267/120491/Sample-Size-Justification https://shiny.ieis.tue.nl/sample_size_justification/

5. Please report how many surveys were completed and the extent of dropout you experienced. Additionally, specify if you had any exclusion criteria for the data, such as excluding participants with a survey completion rate below a certain threshold.

6. Please provide all survey questions asked in the 2.2 Measures section. The questions for the triggering event and the emotional intensity are missing.

7. Please report the nationalities of the athletes.

8. The main effect models are interesting, but what about Level 1 interactions? At least two-way interactions might yield interesting results, especially in light of the literature, which has shown that engagement strategies are most effective in low-intensity emotional contexts, while disengagement strategies are more effective in high-intensity emotional contexts. You make several remarks regarding such an interaction:

- “Strategies that require more participation and effort, such as cognitive reappraisal, may be most effective in regulating low-intensity emotions, whereas strategies that involve disengagement from stimuli, such as distraction, may be most effective in regulating high-intensity emotions” [Section 1.3]

-“In addition, engagement strategies are more effective at regulating low-intensity emotions, but require a greater allocation of cognitive resources” [Section 3.2]

Exploring these interactions in your models could provide a deeper understanding of how emotion regulation strategies function under varying emotional intensities. I would thus suggest to include a fourth model which encapsulates all two-way interactions of level 1 variables. I would thus suggest including a fourth model that encapsulates all two-way interactions of Level 1 variables. This additional analysis could provide a deeper understanding of how different emotion regulation strategies function under varying emotional intensities and contexts.

9. To strengthen the analysis, I suggest performing a model comparison analysis. Since Model 1 is not nested within Model 2, using an Information Criterion like the Akaike Information Criterion (AIC) and/or the Bayesian Information Criterion (BIC) would be appropriate. These criteria allow for the comparison of non-nested models by evaluating the trade-off between model fit and complexity.

10. At the moment, you only report the random intercept. Could you also report the random effects of gender and (skill-)level?

11. I noticed some inconsistencies in your descriptives, specifically in Table 1: The average ring value is approximately 10, or exactly 10.00 for male athletes. Isn’t this the highest possible value achievable, meaning that they shot the center of the target almost every time (I apologize, I am a layperson regarding shooting)? Is this correct? Could there be a ceiling effect in accuracy? Additionally, how does this align with the ten-ring ratio being approximately 35%? Shouldn’t this be close to 100% if the average ring value was 10? Please clarify these points and explain the potential discrepancy between the average ring value and the ten-ring ratio.

Also, please add some context regarding the highest achievable score in the average ring value. If these numbers are indeed correct, you should discuss these near-perfect performances of the athletes and the possible ceiling effects. This context will help readers better understand the skill level of the athletes and the implications for your study's findings.

12. “National-level athletes have higher performance levels and significant differences in emotional experience and use of regulatory strategies, which may account for the significant differences in shooting performance.” [Section 3.1] This conclusion is likely confounded with athlete experience and habituation. National-level athletes have probably competed in many competitions and might have habituated to the emotional distress experienced during competition. Their experience might also be a reason for the better performance, raising the question of whether emotion regulation strategies are indeed the primary reason behind their greater success. Please discuss these results more carefully.

13. The discussion of gender differences in Section 3.1 is somewhat brief. Please elaborate further on the differing results for females compared to males. What are the implications of these findings, and why do these differences exist?

14. “However, the intensity and controllability of emotions are averaged, making it difficult to examine the variability and degree of adaptation of emotional regulation strategies under different situational demands.” [Section 4. Limitations] I do not understand this limitation. You used a hierarchical model for your analysis, so you did not average over intensity and controllability of emotions, correct?

15. Please discuss the limitations in more detail. For instance, you relied solely on retrospective self-reported data. This requires athletes to a) remember their emotions and strategies thoroughly and b) be able to clearly identify their used strategy, a task that is arguably even hard for mental health practitioners. Also, you did not assess physiological data, which might be crucial to understand in light of the shooting performance. Additionally, the lack of preregistration is a significant limitation, as preregistration is considered part of good scientific practice. Please reflect on these and any other limitations in your study.

16. A Conclusion section at the end of your discussion would round off the paper nicely.

17. The manuscript would benefit from increased clarity in certain sections. For instance:

• “Expressive suppression is the most commonly used strategy by athletes in intense competition with limited time （Beatty & Janelle，2016）, but the effective time is short, and the negative experience caused by high intensity may disrupt the movement structure.” [Section 1.1] Could you please elaborate on the statement “and the negative experience caused by high intensity may disrupt the movement structure”? This phrase would benefit from further explanation to clarify its meaning and implications

• “The prerequisite for effective emotion regulation strategies is the context that triggers emotional changes.” [Section 1.1] Unfortunately, I do not understand what you mean. Could you clarify this?

• “Previous studies have focused on exploring regulation strategies or patterns that are applicable to sport situations, and compared to life situations, sport situations are constantly changing, and the applicability of specific regulation strategies is challenged.” [Section 1.1] What do you mean by “compared to life situations, sport situations are constantly changing”? It's debatable whether sport situations are inherently more dynamic than everyday life scenarios, which can also be highly variable and unpredictable. Could you please elaborate on this comparison and provide evidence or specific examples to support your assertion?

• “The ability-based model suggests that emotional clarity, emotional tolerance, and emotional regulation flexibility are the potential for individuals to regulate emotions.” [Section 1.2] Please clarify what you mean by “are the potential for individuals to regulate emotions”

• “Rumination (disengagement with a tendency to avoid difficulties) is also classified as a disengagement strategy （Goodman，2021)”I don’t understand what is meant by “disengagement with a tendency to avoid difficulties”, please clarify. [Section 1.2]

• “However, in rapidly changing competitive sports situations, the effects of specific emotion regulation strategies are not stable, and athletes need to flexibly choose and use different strategies based on changes in the situation to achieve good results.” [Section 1.3] What do you mean by “rapidly changing competitive sports situations”. How does this specifically relate to shooting?

• “…the second-level variables were individual differences among participants (level, gender)” At this point in the manuscript, it was unclear to me, what “level” means. Maybe re-label it to “skill-level” or something more comprehendible.

• “Model 2: A regression model with mean as the outcome variable is used to conduct […]” [Section 3.2] Please clarify which mean (of what?) is used as an outcome

18. Your manuscript sometimes uses inconsistent terminology which impairs flow and understandability:

• You define “the proportion of good ten rings” [2.4 Analysis] as one of the outcomes. However, you refer to this outcome as “Ten-ring Rations” [Table 1 to Table 3], or “proportion of perfect scores” [Section 3.2].

• You refer to one type of emotion regulation strategies as “engagement strategies” but you refer to this as “participation strategy” in Section 3.2

19. Some statements in your manuscript require literature references:

• “It can be seen that the effect of specific emotion regulation strategies is not stable.” [Section 1.1]

• “Regulation strategies that successfully regulate emotions or tolerate aversive emotions are better suited for athletes to achieve their goal of enhancing sport performance than regulation strategies that are more adaptable to individual psychological health development.” [Section 1.2]

• “Compared to male athletes, female athletes use six emotional regulation strategies more frequently, which is consistent with findings from studies of college students that show stable gender differences in the emotional regulation process.” [Section 3.1]

• “This may be because females have more complex emotions than males.” [Section 3.2] This is a strong claim and urgently needs a reference!

• “Women are more sensitive to situational demands and use more regulatory strategies.” [Section 3.2]

• “In addition, engagement strategies are more effective at regulating low-intensity emotions, but require a greater allocation of cognitive resources.” [Section 3.2]

20. There seems to be a citation error in Section 3.2:

• “In contrast to suppressing emotional experiences, suppressing physiological responses to emotions can improve performance（18）.” (no author or year provided)

Reviewer #2: The authors aimed to examine the effect of emotion regulation on

shooting performance in shooting athletes. I have a few questions regarding the methodology.

1. The authors mentioned that they used statistical software for data processing. However, the explanation lacked detail, such as which menus or features were utilized. This level of detail was necessary to allow other researchers to replicate the study described in this manuscript. As a suggestion, researchers could consider using statistical analysis with programming languages to facilitate easier replication.

2. In the manuscript, the authors mentioned the term 'ACC' but never explained its meaning. This could make it difficult for general readers to understand its significance.

3. The authors developed three regression models. In the first model, a two-level approach was used. In the second model, no predictors were included at the second level. Why did the authors choose not to use a standard multiple regression model? It appears there is no significant difference. Please explain.

4. In the second model, the authors coded gender as 1 for males and 2 for females. Why did not the authors use 0 for males and 1 for females, given that gender was nominal and not ordinal? Please explain.

5. The researchers should consider providing the equation form of all the models generated, including the value of each coefficient and intercept. This will allow readers to visually assess the influence of each predictor on the target.

The manuscript has the potential to be published. However, certain aspects, particularly in the methodology, require a more detailed explanation regarding how the conclusions were reached.

Reviewer #3: Introduction

The introduction is written quite well.

Method

Unfortunately, I regret to say that the work contains some serious problems.

- The problem of the origin of the items:

- The authors point out that they largely chose items from other questionnaires to measure emotion regulation strategies, e.g. for cognitive reappraisal the item chosen was: ‘I tried to think about the situation differently.’ from the ‘reappraisal subscale’ of the Emotion Regulation Questionnaire (ERQ) by Gross, John (2003). The item ‘I made sure not to express what I was feeling’ according to the authors was selected from the same questionnaire (ERQ) to determine the Expressive suppression strategy. The ERQ questionnaire is very well known. Although the authors' items are somewhat related in content to the items in the questionnaire, I did not find items in the ERQ with the same content as presented by the authors (see Gross, John 2003, Table 2 - 1-reappraisal factor, 2-suppression factor).

- The authors indicate that ‘Acceptance was measured with an item derived from acceptance and mindfulness measures (Baer et al., 2004), “I tried to notice my thoughts and feelings without thinking of them as good or bad”. In the questionnaire in the source given, I also did not find an item with such content as indicated by the authors (see Baer et al., 2004 - Table 1 - Kentucky Inventory of Mindfulness Skills). There is instead a item such as: ‘I make judgments about whether my thoughts are good or bad’.

- The authors also indicate that ‘Rumination was measured with an item derived from rumination measures (Treynor et al., 2003), “I kept thinking about and dwelling on my anxiety.”. I did not find such an item in the scale provided in the literature either (see Treynor et al., 2003 - Table 1 - Ruminative Responses Scale).

It is therefore difficult to know where the items presented come from, and if they are related to the content of items from other questionnaires, what modifications they have undergone.

- methodological problem:

Authors used single items with unknown validity and reliability to measure emotion regulation strategies. Even if we assume that a single item was selected from a validated and standardised questionnaire, the validity and reliability of a single item is unknown. Short versions of questionnaires are often used, but these require full re-validation (regardless of the original version). On the other hand, shortening a subscale of a questionnaire to a single item, which in addition has been chosen arbitrarily, is an oversimplification. Unfortunately, a scale consisting of a single item is often too short to be reliable, and the use of a single item is particularly discouraged when measuring such broad constructs as personality or emotional processes. The authors further pointed out, for example, that a specific question was used to measure emotional intensity. When it comes to emotional process, it is very difficult to even assess the reliability of such a single-question scale (test-retest), as this phenomenon is very dynamic. To measure emotion regulation strategies, I would suggest using a short, but recognised, standardised and validated questionnaire or constructing and validating your own questionnaire where the subscale consists of more than one item.

- The authors further write: ‘These strategies include cognitive appraisal, acceptance, problem solving, emotional suppression, rumination, and avoidance. The first three are categorised as engagement strategies, while the latter three are categorised as disengagement strategies'. - The authors selected some items and created new subscales from them as they saw fit. The authors then also analysed the results in the proposed subscales. This approach is also methodologically questionable. Combining selected questions into new subscales or questionnaires would have required theoretical analysis and psychometric re-validation, which unfortunately the authors did not do. In order to create new subscales from the questions used, it would have been necessary to first provide a theoretical perspective on the rationale for their creation, and then perform a psychometric analysis to verify the validity of the approach used.

- In addition, some questions, unfortunately, need to be more explicit, e.g., the item on intensity of emotion would require clarification of what emotion is meant, e.g., positive, negative, etc.

- The authors further indicate” The number of participants required to compute the multilevel linear model with four predictor variables and two-tailed tests using Gpower3.1 was over 42, which provides sufficient power (i.e., greater than .80) to detect effect sizes ≥ .20.” Unfortunately, there are many more than 4 predictors in the model presented. In the final model presented in Table 3, there are as many as 8 expressions for fixed effects, and even before interaction effects, single predictors (without interaction) should still be included, resulting in a much larger number of predictors. Besides, the sample size should be determined for a specific effect size, among other things. It is not known what the name of the effect proposed in the paper is, and hence, among other things, it is difficult to assess its strength so as to determine the sample size. On another note, it is not known how the sample size was determined for such advanced models taking into account both fixed and random effects using Gpower3.1 software.

Results

- The authors indicate that: “Using ecological momentary assessment, we followed 57 athletes during competitions for a period of 6 days before the competition and 2 days during the competition” and then write that a multilevel linear model was used to analyze the longitudinal data. The main purpose of longitudinal research and analysis is to analyze changes over time in relation to various variables. Unfortunately, the authors did not model the time factor, and the data was analyzed as if it had been collected at one time. So I suggest including time factor as a fundamental element in the analysis of longitudinal studies. A good source for longitudinal analysis in multilevel modeling is a widely available textbook: Heck, R. H., Thomas, S. L., & Tabata, L. N. (2013). Multilevel and longitudinal modeling with IBM SPSS. Routledge.

- In addition, the models presented are problematic from a statistical point of view. The authors only presented interaction effects in fixed effects in final model 3, and they should estimate and present all terms (including also effects for single variables without interaction).

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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PONE-D-24-25633R1Effect of Emotional Regulation on Performance of Shooters during Competition: an Ecological Momentary  Assessment StudyPLOS ONE

Dear Dr. Hua,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Editor comments. The same reviewers have provided additional feedback on your manuscript. R1 and R2 are satisfied with the revisions and recommend acceptance, whereas R3 remains dissatisfied, raising significant concerns that they feel have not been adequately addressed. Consequently, R3 recommends rejection and does not support the manuscript in its current form. Given these conflicting recommendations, I must make a difficult decision. While I cannot accept the manuscript at this stage due to R3’s unresolved concerns, I believe that a further round of revision could potentially address or mitigate these issues. I am therefore inviting you to submit another revision of your manuscript. If you feel able to address the raised issues, please provide a detailed point-by-point response to all remaining comments from R3. Wherever feasible, incorporate additional analyses or clarifications. For issues that cannot be directly addressed, explicitly discuss and acknowledge these limitations. I hope this further opportunity enables you to resolve the outstanding issues and advance your manuscript, but see my detailed comments below.

Please submit your revised manuscript by Jan 12 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Michael B. Steinborn, PhD

Section Editor

PLOS ONE

Additional Editor Comments:

In the following, I will provide (co-)comments on the raised issues and specific aspects of your work, offering feedback from the perspective of an interested reader who is not directly involved in your specific field of study. My comments are intended to support you in revising the manuscript. Given that some issues appear fundamentally unresolvable without new data collection or substantial reworking of the analysis, I aim to provide guidance on how these might be addressed in a way that strengthens the paper. The feedback focuses primarily on objectively identifiable issues rather than engaging in internal theoretical or methodological debates within the field. My intention is to assist in improving the manuscript, not to criticise your work.

(-1-) Origin of items.

R3 has raised concerns about discrepancies between the questionnaire items used in this study and the original validated scales. While modifications do not inherently invalidate an instrument, their appropriateness depends on item content and face validity. I recommend providing justification to ensure theoretical and psychometric soundness. To address this, it may be helpful to detail the origin of the chosen measures, the rationale for modifications, and any supporting theoretical or empirical evidence. If items were adapted to fit the context of this study (e.g., because brief measures were needed to avoid extending testing time unduly), you might explain how these changes align with the construct being measured. I further suggest acknowledging deviations from the original scales and discussing why alternative validated instruments were not used. If evidence, such as pilot testing, supports the validity of these items, I suggest referring to these literature sources, where such evidence is unavailable, however, acknowledging limitations and outlining strategies to mitigate them would enhance transparency. A clear summary of the modifications and their rationale is likely to address R3's concerns and improve methodological rigour.

(-2-) Use of Single-Item Measures.

Single-item measures, though often criticised, are not inherently invalid solely due to the absence of aggregation. From a measurement theory perspective, statistical aggregation typically enhances reliability. However, the validity and reliability of single-item measures depend heavily on their content. For instance, a single-item measure for a straightforward construct like body height in centimetres is likely reliable because individuals vary sufficiently to produce distinguishable values and because it is likely that they will report consistent results in test-retest scenarios (because persons typically know what their height is). This means, whether the choice of items can be justified likely depends on content validity, that is, of how well the items chosen represent the concept being measured. I am not an expert on the specific case at hand, but as a rule of thumb, some constructs are clear and self-evident, making single-item measures potentially justifiable. However, I agree with R3 that complex umbrella concepts, such as emotion regulation strategies, are relatively complicated to represent using single item scores. This is because these constructs encompass numerous dimensions and are not easily captured in a few items, and indeed, even multi-item scales may struggle to fully represent such constructs, as their definitions are context-dependent, thus can vary and encompass a wide range of aspects. Since (as it seems to me) collecting new data is likely not possible or feasible, I recommend more deeply analysing the content validity of the existing items (what do they mean, actually) to evaluate their appropriateness and effectiveness. Such an analysis could address R3’s concerns, at least a bit.

To best support you in the review process, I recommend consulting the abovementioned works, as their methodologies and discussions offer valuable insights relevant to R3’s concerns. While not directly addressing performance anxiety in shooters, they provide a range of specific guidance that is broadly relevant and potentially helpful across topics. This relevance is why I suggest referring to these studies. For instance, Deng et al. (2022) proposed a systematic seven-step plan for evaluating measurement accuracy, covering molecular to molar aspects. I believe this comprehensive approach could serve as a narrative model for elaborating on psychometric aspects of your measures, particularly pertaining to creating new subscales and the use of single-item measures (doi: 10.1016/j.actpsy.2022.103789; doi:10.3389/fpsyg.2022.946626). Implementing this framework may help address R3’s concerns about the psychometric soundness of your instruments. Steghaus and Poth (2024) offer an in-depth analysis of the significance of context and content validity in selecting items for state and trait measurements, directly addressing issues raised about item origin and single-item measures. Aligning your item selection and measurement strategies with their principles could strengthen the theoretical justification for your methods. Similarly, Kärtner et al. (2021) also theorises on the importance of context in measurement and the need for thorough validation when adapting instruments. While not directly related to emotion regulation in shooting competitions, their methodological rigour can inform your approach to justifying item modifications and creating new subscales. Drawing on their validation processes may help reinforce your methodological framework. Incorporating these studies’ methodologies and discussions into your manuscript can provide a solid foundation to address R3’s concerns, demonstrating rigorous measurement practices and clear justifications for your choices, thereby enhancing the validity and credibility of your findings.

Deng, Y. et al. (2022). The effect of mind wandering on cognitive flexibility is mediated by boredom. Acta Psychologica, 231, 103789. doi:10.1016/j.actpsy.2022.103789

Steghaus, S., & Poth, C. H. (2024). Feeling tired versus feeling relaxed: Two faces of low physiological arousal. PLoS One, 19(9), e0310034. doi:10.1371/journal.pone.0310034

Kärtner, L. et al. (2021). Positive expectations predict improved mental-health outcomes linked to psychedelic microdosing. Scientific Reports(1941). doi:10.1038/s41598-021-81446-7

(-3-) Creation of New Subscales

The reviewer raises concerns about the creation of new subscales by combining selected items, emphasising that this approach requires a clear theoretical rationale and psychometric re-validation, which they feel has not been adequately addressed. Their point suggests that items may not reliably measure the intended construct when removed from their original context, as the contextual embedding could influence their meaning. While I cannot be certain of the extent to which this applies in the current study, I recommend that you carefully consider and provide evidence or reasoning to demonstrate that the selected items appropriately measure the intended constructs. For example, a detailed theoretical justification for the combination of items could strengthen the argument for the new subscales, even if re-validation is not feasible. Additionally, clarifying potentially vague items (e.g., emotional intensity) and discussing the limitations of single-item measures explicitly within the manuscript could improve transparency. Providing references to support the decision to use single-item measures in cases where multi-item scales are not practical may also help address this concern. If possible, supplementary analyses or validations could further enhance the reliability of the measures used.

(-4-) Statistical Issues.

There is one issue that R3 raised, which concerns the inclusion of the time factor as a key variable in the multilevel model, suggesting that its omission undermines the longitudinal nature of the data. R3 also recommend presenting all terms in the model, including main effects and interaction effects, rather than focusing solely on interactions. To be honest, I cannot fully assess this issue myself, given that I am not the ultimate expert here, and also as R1 and R2 found the modelling satisfactory and even commended it. However, R3 has provided arguments that seem also plausible to me, and given his expertise in this area, I am inclined to trust his judgment. Therefore, I would tentatively suggest that you carefully consider how the time factor might be incorporated into the model, if feasible. If it is not possible or does not make sense (in your opinion) to include this variable, then providing a clear justification for its exclusion would be good. In any case, acknowledging any limitations and explicitly discussing why certain recommendations cannot be implemented could also help to address R3’s concerns effectively.

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: No

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Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Thank you very much for your thorough response to my comments. I believe the manuscript has improved considerably and is now ready for acceptance. However, I was unable to access the data via the provided URL. Please ensure that the data is accessible.

Reviewer #2: The manuscript demonstrates a high level of scholarly contribution and is well-prepared for publication. The authors have meticulously addressed all necessary concerns raised, providing comprehensive explanations and ensuring that the content meets the expected standards of rigor and clarity.

Reviewer #3: Unfortunately, the authors did not sufficiently address my main comments. No validity and reliability measures were presented for the questions used to assess emotion regulation strategies. Nor was a psychometric analysis presented for the distinction between engagement strategies and disengagement strategies.

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Reviewer #1: Yes:  Julian Gutzeit

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Reviewer #3: No

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Effect of Emotional Regulation on Performance of Shooters during Competition: an Ecological Momentary  Assessment Study

PONE-D-24-25633R2

Dear Dr. Hua,

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.

Final editor comment.

The authors have thoroughly addressed all comments and significantly improved the manuscript, which is now well-elaborated and in excellent shape. While the fundamental critiques raised by R3 remain partially unresolved, addressing them would require new data collection. However, it remains unclear what specific additional data would sufficiently resolve these concerns, leaving the matter open to interpretation. Within these constraints, the authors have made every effort to address the concerns as comprehensively as possible. After careful consideration, I conclude that the manuscript is now ready for publication in its present form.

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