Emotional Intelligence Profiles and Cyber-Victimization in Secondary School Students: A Multilevel Analysis

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The attached file notes a very few edits that are typos and not content based. I found the article to note the data collected and compared with other studies to be succinct and appropriate for the topic. I have no substantive comments to make as the article spoke for itself.

Comments for author File: Comments.pdf

Author Response

Title: Emotional Intelligence Profiles and Cyber-victimization in Secondary School Students: A Multilevel Analysis

(Title has been modified at the suggestion of reviewer 2)

Comments 1: The attached file notes a very few edits that are typos and not content based. I found the article to note the data collected and compared with other studies to be succinct and appropriate for the topic. I have no substantive comments to make as the article spoke for itself.

Response 1: Dear Reviewer. Sincerely. Thank you very much for your time and effort.

I think the main value of this paper is not so much the results obtained, but the procedure used. I hope it can be useful.

Comments 2: Page 4: Line 123: “. . . that allows you to replicate. . .”    

Response 2: Modified

Comments 3:  Page 8: Line 179: “. . . that make it up, but it does . . .”

Response 3: Modified

Comments 4: Page 8: Line 180: Do you mean global emotional intelligence?

Response 4: Modified

Comments 5: Page 13: Line 286: “. . . possible to consider”. . .

Response 5: Modified

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The title is clear and descriptive but could be more concise. Consider: "Emotional Intelligence Profiles and Cyber-victimization in Secondary School Students: A Multilevel Analysis."

The abstract provides a good summary but could be more concise. Avoid excessive details about the sample simulation and focus on the main findings and their implications.

The introduction offers a thorough background but can be more concise. Highlight the gap in the literature more clearly to justify the study. The objectives are clear, but the hypotheses could be explicitly stated for better clarity.

The literature review is comprehensive but somewhat dense. Summarize key points more succinctly to improve readability. Ensure smooth transitions between topics to maintain coherence. Include more recent references to highlight the current relevance of the study.

Participants: Clearly describe the original and simulated samples separately. The rationale for using a simulated sample is well explained but could be simplified.

Procedure: Provide a step-by-step account of the data collection and simulation process. Ensure clarity and avoid overly technical language.

Measures: Describe the measures (e.g., TMMS-24) in more detail, including their reliability and validity.

Present the results in a clear and structured manner. Use tables and figures effectively to summarize key findings. Provide more explanation of the multilevel analysis and its appropriateness for the study. Ensure that non-experts can understand the statistical methods used.

Discuss the implications of the findings in relation to the hypotheses and existing literature. Highlight the novel contributions of the study. Acknowledge the limitations of using a simulated sample and suggest how future research can address these issues. Emphasize the practical implications for educators and policymakers.

Use clear and concise language throughout the manuscript. Avoid jargon where possible.

Comments on the Quality of English Language

Use clear and concise language throughout the manuscript. Avoid jargon where possible. Ensure consistency in terminology and formatting.

Author Response

Title: Emotional Intelligence Profiles and Cyber-victimization in Secondary School Students: A Multilevel Analysis.

Dear reviewer. Thank you for your time and effort.

I hope that the changes made to the text respond to your suggestions for improvement.

Thank you for your contribution to the improvement of this work.

Comments 1: The title is clear and descriptive but could be more concise. Consider: "Emotional Intelligence Profiles and Cyber-victimization in Secondary School Students: A Multilevel Analysis."

Response 1: MODIFIED

Title: Emotional Intelligence Profiles and Cyber-victimization in Secondary School Students: A Multilevel Analysis.

Comments 2: The abstract provides a good summary but could be more concise. Avoid excessive details about the sample simulation and focus on the main findings and their implications.

Response 2: Dear reviewer, thank you for your advice.

The findings have been very interesting.

The main value of this work may not be so much the results obtained.

I think that the most novel aspects of the work are the techniques of generating a simulated sample, stratification through concatenation (intersectional stratification) and multilevel analysis.

This is not a procedure that I have been able to document in previous works.

Comments 3: Highlight the gap in the literature more clearly to justify the study.

Response 3: Thank you for your insightful advice.

The TMMS-24 is widely used to measure Emotional Intelligence in Spain and Latin America.

In much of the literature on the use of the TMMS-24, a global score is used, but as indicated on page 3 (Line 66-68):

It is not designed to provide an overall score, but for each of its component factors (attention, clarity, and emotional regulation), with their levels of measurement (low, adequate, and excessive).

Comments 4: The objectives are clear, but the hypotheses could be stated explicitly for greater clarity.

Response 4: MODIFIED

The following hypotheses were started:

(1) The variability of average cybervictimization across EI-strata is significant and non-zero. Different emotional intelligence profiles imply different levels of cybervictimization risk.

(2) This difference can be explained by the individual characteristics of the subjects. According to previous evidence, it was expected that:

(2.1) Inadequate levels of emotional intelligence increase the probability of cyber-victimization [25].

(2.2) Gender is related to the degree of cyber-victimization [35].

(2.3) Cybervictimization increases when gender orientation is nonheterosexual [36].

(2.4) Between the ages of 11 and 18, older youth are more likely to be cyber-victims.

(2.5) Low self-esteem increases the risk of cybervictimization

(2.6) High social anxiety increases risk of getting cybervictimized

(2.7) The risk of cyber victimization increases with risky Internet behavior.

(2.8) Low parental control increases likelihood of cyber victimization

Comments 5: The literature review is comprehensive but somewhat dense. Summarize key points more succinctly to improve readability. Ensure smooth transitions between topics to maintain coherence. Include more recent references to highlight the current relevance of the study.

Response 5: MODIFIED

Number of references between 2015 and 2024

2015:  5

2016: 1

2017: 3

2018: 4

2019: 3

2020; 11

2021: 13

2022: 5

2023: 7

2024: 1

Comments 6: Participants: Clearly describe the original and simulated samples separately. The rationale for using a simulated sample is well explained but could be simplified.

Response 6:

MODIFIED

Dear reviewer, thank you for your feedback.

A typo in table 1 has been corrected.

 

Original: 1908 students (50.7% girls) of Compulsory Secondary Education (CSE) from Almeria (Spain), between 11 and 18 years, participated in the study (M=13.65; SD: 1.36).

They belonged to 4 Educational Centers selected according to their convenience, based on having agreed to participate in the study.

Regarding the level of education, 28.2% (539) were in the first year, 28.8% (550) in the sec-ond year, 22.1% (422) in the third year, and 20.8% (397) in the fourth year of secondary education. In terms of sexual orientation, 4.9% of respondents identified themselves as non-heterosexual.

The simulated sample consisted of 50,000 cases representative of a population aged 11 to 18 years (mean: 13.65; SD: 1.36), divided into 23,905 boys and 24,095 girls.

 

You can find the exhaustive description of the two samples (original and simulated) in table 1.

The statistics presented allow us to describe the data distribution for each of the variables for the two samples. The simulation objective is to generate data that respect the characteristics of the original distribution.

In the case of categorical variables, the reference provided is frequency and percentage. The objective of comparing both samples is that the percentage differences are not significant.

Both samples are described for the variables:

1. Age
2. Peer bullying
3. Parentals-controls
4. Self-esteem
5. School vict.
6. Training- support
7. Shyness-Soc. anxiety 8. Risk behaviors 9. Academic-Performance 10. CBV-Average 11. Gender 12. Sexual orientation 13. TMMS Attention 14. TMMS Clarity 15. TMMS Regulation 16. CBV Severity

This is the comparison of the descriptive values of the two samples.

The inferential description of the two samples:

1) You can find the comparison of the differences in means in table 3,

2) You can find the comparison of the regression equations for the two samples, in relation to each of the variables, in table 4

Comments 7: Procedure: Provide a step-by-step account of the data collection and simulation process. Ensure clarity and avoid overly technical language.

Response 7: Dear Reviewer, Thank you for your feedback-

MODIFIED.

You can find the description of the procedure followed for:

1. a) Data collection:

1908 students (50.7% girls) of Compulsory Secondary Education (CSE) from Almeria (Spain), between 11 and 18 years, participated in the study (M=13.65; SD: 1.36).

They belonged to 4 Educational Centers selected according to their convenience, based on having agreed to participate in the study.

Regarding the level of education, 28.2% (539) were in the first year, 28.8% (550) in the second year, 22.1% (422) in the third year, and 20.8% (397) in the fourth year of secondary education. In terms of sexual orientation, 4.9% of respondents identified themselves as non-heterosexual. The information was collected during the months of January and February 2024. All CSE students who provided parental consent were evaluated at each participating center. The tests were administered during class time. Teachers were present.

1. b) Data simulation procedure:

b.1. The Simulate Active Dataset utility generated a simulation plan that allows you to repli-cate the process of constructing simulated data from empirical data using SPSS (File > Open > Empirical Dataset > Analyze > Simulation > Open a Simulation Plan).

It was later verified that both samples were statistically equivalent. To assess data quality, the distributions of the observed and imputed data were compared [38]. For scale varia-bles, means, standard deviations, and maximum and minimum values were compared, and for categorical variables, percentages of each category were compared (Table 1).

b.2. The difference of typed means was calculated for the scale variables and the difference of percentages for the categorical variables (Table 2).

b.3. In both mean differences (scale variables) and percentage differences (categorical varia-bles), the values were close to zero and in all cases the confidence intervals contained the null value (no significant differences) (Table 3).

b.4. To ensure sampling equivalence, the two-dimensional distribution of the relationship between the dependent variable (mean cyber-victimization) and the different independent variables was compared through their regression coefficients (slope and constant) (Table 4). Bivariate correlation analysis was performed on the slopes and intercepts of the pri-mary and simulate sample, with a Pearson correlation of .948 (Sig. .000) for slopes and .999 (Sig. .000) for intercepts. Each sample is statistically equivalent.

Comments 8: Measures: Describe the measures (e.g., TMMS-24) in more detail, including their reliability and validity.

Response 8: MODIFIED

It consists of three factors:

1. a) Emotional awareness (perception) (8 items: 1 to 8). This refers to the ability to experience ad communicate emotions appropriately. That is, it involves a deep understanding of one´s own emotions, identifying feelings and understanding their meaning (α= .86).
2. b) Emotional clarity (understanding) (8 items: 9 to 16). This means understanding the emotional state. It involves recognizing and understanding emotions, distinguishing between them, understanding how they change over time, and integrating them coherently into thinking (α= .84).
3. c) Emotional regulation (8 items: 17 to 24). This is the ability to effectively manage emotional states. It means the ability to regulate and maintain control over positive and negative emotions (α= .83).

[…]

The Pearson correlation value for the test-retest after four weeks was found to be between 0.60 and 0.83 [29]

Comments 9: Present the results in a clear and structured manner. Use tables and figures effectively to summarize key findings. Provide more explanation of the multilevel analysis and its appropriateness for the study. Ensure that non-experts can understand the statistical methods used.

Response 9: Dear reviewer. Thank you for your advice.

The results section is the reference to facilitate the reproducibility of the work. It is necessary to consult the referenced texts for each aspect discussed. I must admit that statistically this is a very complex work.

It combines intersectional analysis techniques with statistical analysis techniques such as a complete multilevel analysis, multiple regression analysis for each of the strata, and data mining techniques. An attempt has been made to present an organized sequence of analyses, the results of the statistical analyses performed, and their interpretation.

Comments 10: Discuss the implications of the findings in relation to the hypotheses and existing literature. Highlight the novel contributions of the study. Acknowledge the limitations of using a simulated sample and suggest how future research can address these issues. Emphasize the practical implications for educators and policymakers.

Response 10: Dear reviewer, Thank you for your feedback.

The review of the consistency of the work (identification of research hypotheses, analysis techniques to be used for their verification, results and discussion of each research hypothesis) appears to be complete.

Practical implications for educators and policy makers:

It was evident that each profile or emotional intelligence stratum had its own peculiarities in terms of predisposition to cyber-victimization and the weight that the variables gender, sexual orientation, academic-performance, or risk-factors had in cyber-victimization, and that in general they presented levels excessive interpersonal attention and low emotional regulation are predictors of cyber-victimization [2, 64].

It is necessary to propose actions aimed at protecting non-heterosexual people from cyber-victimization [65], especially in the case of girls, considering the need to strengthen self-esteem and emotional regulation.

In general, protective measures against cyber-victimization should warn about the risk of Internet use, avoid paternalistic behaviors by adults to protect minors, and reduce rumination behaviors or excessive attention to the opinion that others have of us [66].

Author Response File: Author Response.pdf