Reviewer Comments

Evidence of Responses Added

1. Limitations of BMI: The article acknowledges that BMI is not the best tool for assessing athletes' body composition, as it cannot distinguish between muscle mass and fat mass. However, it does not sufficiently discuss how this limitation impacts the study’s findings. For instance, the article mentions that baseball players tend to have higher BMI, but their FMS scores are not necessarily lower. This could be attributed to baseball players typically having greater muscle mass.

Location of Evidence: See lines 107-119 of the “Introduction” section; final paragraph of this section found on page 5 of the document.

*Comment addressed on the third page of the Introduction section (final paragraph) and again in the “Discussion of Results” section. For the content addressed within the “Conclusion” section, see lines 33-71 under the “Discussion of Results” section found on pages 13 and 14 of the document.

Content was added to discuss how BMI does not limit the outcomes of this study since the focus was on comparing body mass to movement patterns. There is no evidence from clinical trials to support how the precise measurements of lean versus fat mass have a direct impact on movement outcomes. Research only supports the impact of body fat percentage on health outcomes not related to functional movement in collegiate athletes.  The implications of BMI suggest that higher scores in some athletic populations, such as baseball players, would likely have higher muscle mass. However, athletic populations with larger athletes competing, such as American football, was not involved in this study. Therefore, it is difficult to assume if larger mass due to both muscle and fat would result in the same outcomes. Further investigation is needed on this topic relating to athletes with larger mass in general. 

2. Sample Representativeness: The sample consists of only 85 collegiate athletes from six sports, which may not adequately represent the entire collegiate athlete population. Athletes from different sports, genders, and competitive levels may have varying BMI and FMS scores.

Location of Evidence: See lines 15-23 of the “Limitations” section found on page 15 of the document.

*Comment was addressed on the second-to-last page of this document under the “Limitations” section (just before the “Practical Applications” section).

Content was added to discuss the diversity of the athletes used in this study. While not all collegiate sports were represented, there was fairly equal representation between genders. Further investigation needs to be made regarding the population of athletes competing in sports that were not included in this study. Likewise, comparisons should be made of athletes competing at various levels of college athletics, which could include community college, NAIA, NCAA DI and DIII levels. This study assessed NCAA DII athletes, which is only one of the many collegiate levels of competitive athletics offered nationwide.

3. Inter-Rater and Intra-Rater Reliability: While the article mentions that FMS scoring might be influenced by inter-rater and intra-rater reliability; it does not explain how these factors were controlled. It should clarify how the two certified FMS raters were trained and evaluated to ensure scoring consistency.

Location of Evidence: See lines 56-84 under the “Introduction” title; specific content can be found on page 4 of the document.

Addressed on the second page of the “Introduction” section as well as the “Limitations” section on page 14 of the document. *Content within the “Limitations” was added in the first paragraph; see lines 7-14 under the “Limitations” title.

Content was added to discuss the role of the two FMSC raters. Both certified raters assessed each participant using the suggested angles of analysis for each exercise. Both raters scored the movements using the FMS score sheet and took the lower of the two scores, which is the suggested protocol (Cook et al., 2013; Shultz et al., 2013). Both raters were unfamiliar with the participants involved in the study to avoid bias on reporting results. This process helped to control the effect of inter-rater reliability since two non-bias raters were used to collaborate on FMS scores for each participant. Prior to participation, each participant was asked about his/her knowledge of the FMS testing protocol (Minick et al., 2010). None of the participants used in this study had prior knowledge or experience with the FMS protocol, which helped to control the intra-rater reliability (Gribble et al., 2011). Likewise, the proper testing protocols for executing each exercise involved in the FMS were followed using the handout provided, which ensures that the raters do not “coach” athletes through the testing protocol (Beardsley & Contreras, 2014: Cook et al., 2011). This ensures that the outcomes of each movement are natural and not adjusted for the sake of performing a higher score (Kraus et al., 2014).

4. Participants’ Familiarity with FMS: The article suggests that participants’ familiarity with FMS may influence the screening results but does not explain how this factor was controlled. It should specify whether participants were familiar with the FMS test beforehand and how the study minimized the impact of this familiarity on the results.

Location of Evidence: See lines 65-84 under the “Introduction” title; specific content can be found on page 4 of the document.

*Comment was addressed on the second page of the “Introduction” section following the inter- and intra-rater content (of which was updated as well).

Content was added to discuss the impact of participant knowledge of the FMS testing protocol and the effect of intra-rater reliability as a result.  As stated above… Prior to participation, each participant was asked about his/her knowledge of the FMS testing protocol. None of the participants used in this study had prior knowledge or experience with the FMS protocol, which helped to control the intra-rater reliability. Likewise, the proper testing protocols for executing each exercise involved in the FMS were followed using the handout provided, which ensures that the raters do not “coach” athletes through the testing protocol (Beardsley & Contreras, 2014: Cook et al., 2011). This ensures that the outcomes of each movement are natural and not adjusted for the sake of performing a higher score (Cook et al., 2013).

5. Additional Participant Information: More information about the participants, such as their age, years of training, and competitive level, should be provided. Conclusion This article offers valuable insights into the relationship between BMI and FMS but requires several revisions to enhance its academic rigor and readability.

Location of Evidence: See lines 1-15 following the “Participants and Instrumentation” title at the bottom of page 5 of the document.

*Comment was addressed within the “Participants and Instrumentation” section as well as the “Demographics Statistics” section under “Results” found on page 8 of the document.

Content was added to discuss the specific details of the participants involved in this study. Participants ages ranged from 18-24 with a mean age of 21. Each participant involved in this study was a current student athlete competing at an NCAA DII collegiate program with experience levels ranging from freshman (first year) through senior (final year). The training status of each athlete varied based on competitive season and time spent training and competing at the DII collegiate level. Every participant disclosed his/her fitness and ability to perform movement pattern exercises. No participants involved in this study reported any current or recent injuries that would limit his/her ability to perform any of the exercises involved in the FMS testing protocol.

*Note: the participant demographics on age and sport status was also included in the Demographic Statistics section under the Results content. See lines 9-15 following the “Results” title on page 8 of the document.