Dear Dr. Rodas,

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.

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ACADEMIC EDITOR: -->--> -->-->Thank you very much for your submission. The reviewer has raised important concerns and I have as well reviewed the manuscript, requiring several revisions to improve the clarity and methodological robustness. I would welcome a revised version of the manuscript subject to incorporating the revisions suggested by the reviewer and myself.

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Please submit your revised manuscript by Feb 21 2026 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.. 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.

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We look forward to receiving your revised manuscript.

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Ioannis G. Katsantonis, PhD, MPhil

Academic Editor

PLOS One

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Additional Editor Comments:

The manuscript addresses an important issue with appropriate data and methods, but requires conceptual clarification, methodological justification, and interpretative moderation before it is suitable for publication. With these revisions, the study has the potential to make a solid contribution to the psychometric literature on anxiety assessment.

The sample size is large and appropriate for the analyses presented. That being said, the use of convenience sampling via online dissemination should be discussed more explicitly as a limitation, particularly in relation to the representativeness to the wider Ecuadorian population, potential overrepresentation of younger, urban, and more educated participants, and possible response-style effects associated with online self-report administration.

I have several questions on the psychometric strategy selected. Did the authors use separet subsamples for EFA/CFA? It is generally recommended to split the sample and run the analyses in separate subsamples.

I would like to see a more thorough justification for the method factor. Please explain why this factor was specified as orthogonal and why alternative specifications (e.g., bifactor modelling) have not been tested.

I find it problematic that multiple items show loadings below .40 on the general anxiety factor. While this is reported, its implications are underdeveloped. The authors should clarify more the implications of this.

In the measurement invariance analyses, please report effect sizes for the latent mean differences. Also, try to clarify whether these differences align with prior epidemiological evidence.

I found several typographical issues inside the manuscript. Additionally, several concepts should be clarifed and should be used consistently, such as “methodological artefact,” “confounding construct,” and “positive affect”.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #1: Yes

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

Reviewer #1: No

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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: Yes

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

Reviewer #1: Yes

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Reviewer #1: Overall evaluation

Strengths:

Clear and relevant research question (factor structure and sex invariance of the STAI in Ecuador).

Large sample (n=1,244) with reasonable age range and sex balance.

Use of EFA, CFA/SEM, DWLS for ordinal data, and stepwise measurement invariance (configural–metric–scalar–residual–latent means) following standard guidelines.

Main concerns:

Conceptual framing of the “method factor” vs “positive affect/anxiety-free” factor is not fully coherent with the presented evidence.

Some methodological decisions and descriptions need clarification (sampling, handling of non-normality, model comparison, item-level behavior).

The Discussion and Conclusion occasionally overstate the implications (especially “not supporting use of the STAI in research”).

Structure and style require tightening (repetitions, some language issues, and small inconsistencies).

Given this, the manuscript has potential but requires a deeper revision of introduction, methods justification, results reporting, and interpretation.

Major points to revise

1. Clarify the theoretical model and aim

The introduction alternates between three ideas: (a) STAI factor structure problems, (b) reverse-worded items as method effects, and (c) reverse-worded items as reflecting a positive/anxiety-free construct.

Explicitly state at the end of the Introduction whether the second factor is hypothesized to be:

a pure method factor,

a substantive “positive affect/anxiety-free” factor,

or a mixture of both.

Align this hypothesis with the analytic plan (e.g., why the methods factor is specified as uncorrelated, and why all items still load on the general anxiety factor).

Clearly define specific hypotheses:

H1: A two-factor model (anxiety + reversed/method factor) will fit better than a unidimensional model for state and trait scales.

H2: The STAI will show configural, metric, and scalar invariance by sex.

H3: Women will present higher latent anxiety levels than men.

Stating these explicitly will make the Results and Discussion more focused.

2. Sampling and generalizability

Describe the recruitment channels in more detail (type of social media groups, institutional networks, etc.) and discuss how convenience online sampling and age distribution (mean 27.65 years) may limit generalizability to the Ecuadorian adult population.

Clarify the exclusion criteria regarding “no prior diagnosis of psychiatric disorders”: was this self-reported? Were any specific screening questions used?

Given the concentration in certain cities (e.g., Guayaquil), add a short paragraph in the Discussion recognizing regional and socio-economic limitations.

3. Methods: analytic details and reporting

Internal consistency:

Report α and ω for each subscale (state and trait) in the main text and in a table (currently mostly in text and Table 1 for ω-if-item-deleted).

Briefly justify the use of ω alongside α (e.g., less dependent on tau-equivalence).

EFA:

Specify the extraction method (e.g., principal axis factoring vs maximum likelihood) and the software used.

Justify the number of factors (were eigenvalues, scree plot, and/or parallel analysis considered, beyond KMO/Bartlett?).

Provide a table with EFA loadings for state and trait scales (even if also represented in a figure) so readers can see loadings and cross-loadings numerically.

SEM/CFA:

Clarify the estimator used in SEM (DWLS / WLSMV) and software (lavaan/R, Mplus, etc.).

Explain why the method factor is set as uncorrelated with the general anxiety factor, even though you later interpret it as possibly a substantive “positive state” dimension. If you suspect substantive overlap, a correlated method factor or bifactor model might be more consistent with the theoretical position.

Present all main fit indices for each model (χ², df, RMSEA + 90% CI, CFI, TLI, SRMR) in a table for state and trait scales, for one-factor vs two-factor models, to facilitate comparison.

Measurement invariance:

Report the invariance model sequence clearly (configural, metric, scalar, residual, latent means) and for each level provide ΔCFI and ΔRMSEA, not only Δχ². This aligns with current recommendations and softens the focus on χ² sensitivity to sample size.

Clarify whether invariance was tested on the two-factor model (anxiety + method factor) and whether both factors’ loadings/intercepts were constrained across sex.

4. Results: sharpen and structure

Internal consistency:

Add the actual α/ω values for each subscale in the first paragraph of Results (state α = …, ω = …; trait α = …, ω = …; briefly indicate “excellent” or “good” according to common benchmarks).

Factor structure:

In the SEM section, distinguish clearly between state and trait results with subtitles or opening sentences.

When noting that some items have loadings < 0.40 on the general anxiety factor, discuss whether they nevertheless have strong loadings on the method factor, and how that supports your interpretation.

Consider including a brief note on modification indices, if they were inspected and if any cross-loadings or correlated residuals were allowed or rejected.

Measurement invariance:

Make it explicit that scalar invariance was achieved while latent means differed (women higher anxiety), and quantify these differences (latent mean differences or effect sizes, if available).

5. Discussion and conclusions: moderate claims and improve coherence

Strengthen linkage to your own data:

When citing Bieling, Delgado, Ortuño-Sierra, Bados, etc., make explicit whether your pattern (reverse items forming a separate factor, some items with low loadings) is theoretically closer to “method effects”, “positive affect”, or “general negative affect”.

Consider whether a three-component interpretation may be needed: anxiety, positive/anxiety-free affect, and general negative affect—without overstating beyond your models.

Moderate strong statements:

The statement that “our results do not support the use of the STAI in research aiming to obtain purer measures of anxiety” is very strong considering that:

A strong general factor is still present.

You used the full 40-item version without testing alternative scoring (e.g., removing reversed items or using only the negative items).

Reframe this as: the presence of a strong secondary factor and method effects suggests that researchers who require highly specific, unidimensional anxiety measures should consider using alternative instruments or modified STAI scoring (e.g., excluding reversed items) and should report these limitations.

Clinical vs research utility:

If you wish to maintain that STAI remains useful clinically, ground that claim in your findings (e.g., high reliability, clear general factor, scalar invariance) while acknowledging that fine-grained research on pure anxiety constructs might prefer more focused instruments.

Limitations and future directions:

Expand limitations to include:

Use of a single measure (no convergent/discriminant validity tests with depression or other anxiety scales).

Cross-sectional design.

Potential self-selection bias of online volunteers.

Suggest future research:

Testing bifactor models and alternative short forms (e.g., removing reversed items).

Including additional measures to separate anxiety, depression, and positive affect in Ecuadorian samples.

6. Presentation, style, and small issues

Language and style:

There are several minor issues (e.g., “calmn”, “confortable”, some long sentences, and occasional tense inconsistencies). A thorough language edit will improve readability.

Remove repeated text fragments originating from the submission system (e.g., detailed PLOS forms and instructions appearing in the PDF) from the manuscript body if not required.

Structure:

Consider shortening the general “Assessing Anxiety” section, focusing more quickly on STAI-specific controversies and Ecuadorian context.

Ensure all figures and supplementary tables are referenced in the main text in the correct order and with consistent labels (Fig 1, Table S1, Table S2).

Ethical and data statements:

The ethics and data availability statements are clear and in line with journal expectations; only minor wording harmonization with PLOS templates may be needed.

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Reviewer #1: No

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Dear Dr. Rodas,

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.

==============================

ACADEMIC EDITOR:-->-->Dear authors,-->-->thank you for submitting your revised version. I believe that the revised manuscript has nearly addressed all initial comments and is now closer to publication. However, I found a minor inconsistency that needs to be clarified before further processing of the manuscript.-->-->==============================

Please submit your revised manuscript by Apr 09 2026 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.. 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.

• A 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 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 . 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,

Ioannis G. Katsantonis, PhD, MPhil

Academic Editor

PLOS One

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Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

I thank the authors for their reply to my comments. The only outstanding issues that the WLSMV estimator was used to estimate measurement invariance, yet the authors mention inside the manuscript that for scalar invariance the intercepts were found to be equal. However, in ordinal data measurement invariance with WLSMV assumes that intercepts are not defined; instead, item thresholds are estimated in WLSMV measurement invariance. Hence, I invite the authors to explain the measurement invariance steps in greater detail or revise the invariance analyses if thresholds were not held equal and intercepts were estimated.

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Underlying Structure and Measurement Invariance by Sex of the State Trait Anxiety Inventory: A Psychometric Analysis in Ecuador

PONE-D-25-53829R2

Dear Dr. Rodas,

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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Ioannis G. Katsantonis, PhD, MPhil

Academic Editor

PLOS One

Additional Editor Comments (optional):

The authors have done an excellent job in addressing sufficiently and in detail all comments. The manuscript can now be published.

Reviewers' comments: