PONE-D-19-15440

Evaluating the higher-order structure of emotional competence using the Profile of Emotional Competence (PEC): Confirmatory factor analysis and Bayesian structural equation modeling

PLOS ONE

Dear Dr. Nozaki,

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.

Please try to address each of the issues commented by both reviewers. I feel the manuscript may be remarkably improved if done like this.

We would appreciate receiving your revised manuscript by Sep 20 2019 11:59PM. When you are 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.

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We look forward to receiving your revised manuscript.

Kind regards,

Juan Carlos Perez-Gonzalez, Ph.D.

Academic Editor

PLOS ONE

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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: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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

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

Reviewer #1: No

Reviewer #2: Yes

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

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

Reviewer #1: Yes

Reviewer #2: 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: Thank-you for the opportunity to review your manuscript. I approach this review from the perspective of an Emotional Intelligence researcher, with experience testing models of factor structure of EI constructs using MPlus (but not Bayesian SEM). I am very passionate about the field so was thrilled to have the opportunity to review your work, and I do hope my comments are of benefit to you for this project.

To explain my responses to the set questions, some of the code and data are in a private OSF page which I cannot currently access. As for Q1, please see comments below regarding scale vs construct.

My major concern with this manuscript is that there is a little conflation of measure and construct. The theoretical clarity of EI has often been questioned, and so when you suggest EI and EC are interchangeable terms on p2/3 I think this has more scope for causing confusion than clarity. For example, some researchers differentiate between cognitive ability (emotional intelligence), trait (affect-related personality) and behaviour (e.g. emotion regulation). It could be clearer exactly how you expect the competency perspective to fit in/around these other domains. This concern is furthered by the critique of competencies as atheoretical/ambiguous both within the EI domain, and much broader. The lack of theoretical position on competencies means there are some areas of ambiguity throughout the manuscript. For example, why would dimensions be excluded for not representing both ability and trait approaches – why would this matter if they were something different to these perspectives, or only related to one? As a result of these sorts of concerns, I think this paper would be much more valuable if it represented a discussion on the structure of the scale, rather than claiming for a definitive model of competencies.

Your detailing, presentation and analysis of the models looks pretty clear although some further details would be of benefit. For example, the justification for MLR over WLSMV is only convincing if you make the argument that the indicators provide additional value in model discrimination. I don’t have any experience with BSEM, although I am familiar with the principles, and so found some of the analysis section a little tricky to follow. My main problem with this is that it can be easy to miss errors or make subjective decisions which are difficult to follow. As such, I believe the analyses are robust but some of the more technical notes could be made a little easier to follow.

Your discussion is mostly clear, although I have two comments here. Firstly, the speculation for previous findings on lines 365-370 I would not encourage. Secondly, the fact that utilization-self did not load in the BSEM results is not a limitation of the current research- this finding should be discussed in the results or discussion section more substantively. You make an interesting line of argument around it not being include in factor structures of ability (e.g. see also Fan et al.) however again this links back to my first substantive comment about theoretical ambiguity.

As a whole, I really enjoyed reading this manuscript and found it in the most part to represent clear communication of a substantive contribution to the field. However, due to the issues around theory, I would encourage this paper to be re-orientated towards the measure rather than the construct. I do hope this is all clear and helps, I am very happy to elaborate wherever of value. Thank-you for the opportunity to read your work!

Reviewer #2: Manuscript PONE –D-19-15440

Full title: Evaluating the higher-order structure of emotional competence using the Profile of Emotional Competence (PEC): Confirmatory factor analysis and Bayesian structural equation modeling.

The study represents an important attempt to integrate previous findings into a model of Emotional Competences that goes beyond the traditional emotional intelligence paradigms. The authors utilize advanced statistical techniques to demonstrate that the five factor structure of Emotional Competences is relatively stable across cultures and show that the model distinguishing between intrapersonal and interpersonal domains fit the data best. Findings from this study can assist researchers and EI program developers who would like to base their implementations on a solid and evidence-based model of EC.

There is tremendous value in investigating systematically the higher order structure of Emotional Competence in different cultures, and findings from this study would be very helpful for the design of future EI implementation programs on EI.

The authors successfully introduce a complex theoretical distinction and clarify terminology issues, which have been a problem during decades of emotional intelligence research. The use of very relevant and up-to-date references is noticeable.

At the end of the description of the PEC the authors refer to the fact that the modification of the Likert scale for one of their samples did not affect the main results. It would be helpful if they could clarify this sentence and indicate how they reached this conclusion. In addition, it would be advisable to incorporate examples of items in the PEC illustrating every component of the test.

Some demographic variables seem to be quite different across samples (e.g., main age), as well as the questionnaire administration conditions (through data collection company online for the Japanese data only), so it would be advisable to identify clearly how the authors dealt with these differences.

The authors made great efforts in interpreting the results regarding interpersonal and intrapersonal EC. In order to further enhance this discussion, the authors could refer to how these findings could inform future implementation programs aiming to develop EC in particular, and Emotional Education in general (see Perez-Gonzalez & Qualter, 2018).

As for the recommendations for future research, specific comments on future validation of the model could be made (content validity, discriminatory power, etc.). Also, the authors could elaborate on previous validation work using the PEC earlier on in the manuscript.

Overall, this is a coherent and solid research paper, which adds to the existent literature on emotional intelligence. I definitely recommend its publication in PlosOne

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Reviewer #1: No

Reviewer #2: Yes: Maria-Jose Sanchez-Ruiz

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PONE-D-19-15440R1

Evaluating the higher-order structure of emotional competence using the Profile of Emotional Competence (PEC): Confirmatory factor analysis and Bayesian structural equation modeling

PLOS ONE

Dear Dr. Nozaki,

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 for one of the two reviewers.

As Academic Editor, this time I feel the required minor changes will bring the manuscript direct to final acceptance if you follow the reviewer' guidelines. I frankly agree with the reviewer's observations and I believe that his observations can significantly strengthen the theoretical robustness of the paper, providing a necessary refinement.

We would appreciate receiving your revised manuscript by Nov 18 2019 11:59PM. When you are 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.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

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). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Juan-Carlos Perez-Gonzalez, Ph.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

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

Reviewer #1: Thank-you for the opportunity to re-review this work. I believe this work is of high-quality and makes an interesting contribution to the field. Many of my comments have been addressed and the paper as a whole reads very well. Excluding a few minor comments highlighted below, my main concerns surrounding the framing of the introduction remain.

You have done a good job at reframing the work to be about the scale rather than the construct, however your introduction still presents a slightly confused review of EI theory. For example, you conflate EC with trait EI (p3) – particularly in the second paragraph (starting “Research conducted over the last two decades…”) where you cite mostly trait EI research, however some may argue that your central argument that EC is malleable to training is much less true for trait EI. Furthermore, this becomes slightly further confused when suggesting the PEC is built upon the Mayer and Salovey model (p4) which itself is an ability EI framework. I would recommend you take a clearer stance on this – this could be done in a number of different ways – you could argue that EC is different to ability EI and trait EI, you could argue that trait EI and EC are in essence the same, you could argue that competencies are the behavioural outcomes of ability EI (hence the Mayer and Salovey framework) and trait EI (hence self-report behavioural measure), or take it in a different way. Whichever way, framing it more clearly and acknowledging the consequences of this decision is vital. As it stands this is the major obstacle to publication for this work is this theoretical clarity which frames the whole paper.

Minor changes/recommendations/thoughts:

• Remove ‘emotional competence using’ from the title

• P3. Trait EI… is TYPICALLY measured using self-report. It’s worth adding this conditional statement as there has been a body of research considering other-rated trait EI/competencies

• P13 there are two ‘that’ in the sentence – that that

• P13 your lack of convergence sounds like a Heywood case. Is that the case and if so did you attempt any resolution?

• P26 you link the findings to emotional education as requested by the second reviewer – I would encourage you to expand on this just a little more in context of the theoretical approach adopted. I.e. if you take a trait or competency approach, what is the evidence that such individual differences can be trained, and what would you expect to improve from understanding the factor structure differentiating between interpersonal and intrapersonal?

• P27 you discuss the utilisation branch and acknowledge in other factor analytic work that this does not emerge. Could you provide just a little more detail about your findings in this area i.e. do loadings or relationships to other factors seem higher than the others etc.

In sum, there is some great work presented and I fully support the publication of this work, but the theoretical grounding to the constructs discussed needs refinement. Other (minor) recommendations and thoughts are provided to further refine the manuscript. I do hope these help!

Reviewer #2: The authors have successfully answered all the comments raised and I recommend this manuscript for publication in PLOSONE.

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

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

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

Reviewer #1: No

Reviewer #2: Yes: Maria-Jose Sanchez-Ruiz

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Evaluating the higher-order structure of the Profile of Emotional Competence (PEC): Confirmatory factor analysis and Bayesian structural equation modeling

PONE-D-19-15440R2

Dear Dr. Nozaki,

Great work! We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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With kind regards,

Juan-Carlos Pérez-González, Ph.D.

Academic Editor

PLOS ONE

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