PONE-D-24-46988

Validation of the Multidimensional Social-Sexual Orientation Inventory (SOI-M) in the Chilean population

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Reviewer 1: I would like to thank the authors for giving me the opportunity to review this work, which I found very interesting and intriguing. The research is well structured and addresses an important topic: the validation of the Sociosexual Orientation Inventory-Multidimensional (SOI-M) in the Chilean population. The strengths of the study are numerous, particularly the methodological approach, which combines exploratory and confirmatory analyses, making the results solid and well supported by evidence.

Strengths:

Robust methodological approach: data analysis with a significant sample (865 participants) and the use of advanced statistical methods such as exploratory factor analysis (EFA), exploratory structural equation modelling (ESEM) and confirmatory factor analysis (CFA) are appropriate choices for testing the validity of the model.

Convergent and Divergent Validity: The results confirm that the SOI-M inventory effectively measures sociosexuality, with strong evidence of both convergent and divergent validity.

Reasoning behind the model reduction: the decision to reduce the initial model from 20 to 15 items by eliminating redundancy and improving the model's fit was well justified, leading to a more parsimonious version of the inventory.

Sexual invariance: the analysis of metric and scalar invariance confirmed that the reduced model is valid for comparisons between men and women, strengthening the generalisability of the results.

Suggested changes:

Line 13:

Current: ‘We used the Multidimensional Sociosexual Orientation Inventory (SOI-M) initially developed by Jackson and Kirkpatrick (2007) for validation in the Chilean population.’

Suggested change: ’We used the Multidimensional Sociosexual Orientation Inventory (SOI-M) developed by Jackson and Kirkpatrick (2007) for validation in the Chilean population.’

Line 33:

Current: ‘We tested the psychometric properties of the instrument on a final sample of 865 subjects (247 women and 616 men) aged between 18 and 55 (M = 23.56; SD = 5.52).’

Suggested change: ‘We tested the psychometric properties of the instrument on a final sample of 865 subjects (247 women and 616 men) aged between 18 and 55 (M = 23.56; SD = 5.52).’

Line 72:

Current: ‘We tested and verified the convergent and divergent validity of the instrument.’

Suggested change: ‘We tested and verified the convergent and divergent validity of the instrument.’

Line 143:

Current version: ’Finally, we verified the psychometric properties of the inventory, which demonstrates that we are measuring the construct of same-sex attraction as described by the authors of the original instrument.’

Suggested edit: ‘Finally, we verified the psychometric properties of the inventory, confirming that we are measuring the construct of sociosexuality as described by the authors of the original instrument.’

I recommend citing the following article, which could further enrich the discussion on psychometric properties and measurement invariance in different cultural contexts:

Diotaiuti, P., Valente, G., Mancone, S., Grambone, A., & Chirico, A. (2021). Metric Goodness and Measurement Invariance of the Italian Brief Version of Interpersonal Reactivity Index: A Study With Young Adults. Frontiers in Psychology, 12, 773363. https://doi.org/10.3389/fpsyg.2021.773363.

How and where to cite:

I suggest including this citation in the paragraph discussing the validity of psychometric tools, particularly when discussing evidence of convergent and divergent validity. A possible integration could be:

Introduction or discussion: ‘Previous studies, such as those by Diotaiuti et al. (2021), have explored the validity of short versions of interpersonal reactivity instruments, providing a useful framework for understanding metric properties and measurement invariance in different cultural contexts’.

Including this citation will help contextualise the findings within a broader body of research on psychometric testing and measurement invariance.

Reviewer 2: In their manuscript, Oriana Figueroa and colleagues validated the multidimensional inventory of socio-sexual orientation (Jason and Kirkpatrick, 2007) for the Chilean sample. To this end, they translated and administered this instrument to a large sample from Chile and provided evidence of its structural validity through exploratory factor analyses (EFAs), confirmatory factor analyses (CFAs) and exploratory structural equation modelling (ESEM).

Overall, I believe the study is sound and makes a valuable contribution to the literature. However, the authors should address some important issues.

My first concern is about the validity of the measurement content: I am not convinced that long-term pairing orientation, and therefore the items that reflect this construct, is a manifestation of sociosexuality. I see it rather as a construct that relates to OS and should definitely belong to its nomological network, but I am not sure that the search for a long-term relationship is, in itself, a form of sociosexuality that is unlimited as opposed to limited. However, if an instrument, albeit multidimensional, refers to a construct (sociosexuality, in this case), then its subscales would to some extent reflect that latent variable and therefore should be highly correlated. This is not only a theoretical consideration that concerns the substantial evidence in favour of the validity of the instrument, which should therefore be thoroughly discussed. It is also an empirical issue that should be taken into consideration when examining the structural evidence. The authors are not very clear about which models they are testing in their CFAs and ESEMs, but I would certainly like to see a comparison between a one-dimensional model, a three-factor model with correlated factors, and a bifactorial model (as in Ciocca et al., 2024). The latter model would also help to break down the total reliability (total omega) into reliability that depends on the general (hierarchical) factor and on specific factors (group omega). In addition, authors can have a nuanced assessment of how much the one-dimensionality - and therefore the calculation of a total score - is supported by the data through the omega evaluation, following the recommendations of Reise et al. (2013), values of ωh > 0.70, ECV > 0.60 and PUCs > 0.80. Ultimately, it would certainly be useful to add the values of these models together with the standardised loads.

My second concern relates to their overall analytical strategy. It is quite clear to me that they aim to test a measurement model – and perhaps compare it with other theoretically valid models such as those mentioned above – and therefore I would have expected to start with a CFA and, in case of a mismatch, an exploratory strategy would have been justified. The authors seem to justify their decision by noting that no CFA was conducted in the original validation paper. However, it is quite clear to me that they theoretically have three different latent variables in mind (SOTM, LOTM and sociosexual behaviour) that are reflected in specific items. Therefore, a more sensible approach would be to randomly split their combined samples in two, conduct a CFA - and ideally compare more competitive CFA models - and then, in case of misfit, explore the causes of the misfits (e.g., by examining modification indices) and explore other solutions through ESEM (especially to identify and remove cross-loading elements) and, if ESEM fails to achieve good fit, perform EFA to understand if the structure has been identified incorrectly. Then, once you arrive at a new valid model, you can test the model through another CFA on the cross-validation sample.

My third concern is about the way the authors verify the validity of the external tests in terms of convergent and discriminant validity. A better approach would be to do this within a CFA framework and check whether the latent variables, rather than the observed scores, are correlated and to what extent they are. This could allow them to check for discriminant validity as recommended by Ronkko and Cho (2022).

My fourth concern is about the huge heterogeneity of their samples in terms of results. The authors should think harder about why they find huge differences in sex differences in sociosexual behaviour between samples. This is another reason why I strongly advise against splitting the data according to the analysis conducted. Perhaps a better approach would be to merge all the datasets and then randomly split the merged sample, as suggested above.

One last important concern is that the authors often omit some important details (see my point-by-point comments below) that could help the reader assess the quality of their evidence.

Here the authors can find other point-by-point comments:

- Page 6: the authors do not cite Ciocca et al. (2024) for the Italian validation of the SOI-R

- Page 11: the translation process should be described in more detail. How did they handle forward translation? Did they also perform a reverse translation? And how was it handled?

- Page 14, Table 1: There are notable differences between the samples. The most notable is the much wider gender difference in the ESM/CFA sample compared to the EFA sample and, even more striking, and somewhat contrary to the literature, the difference in socio-sexual behaviour.

- Page 15: I would like to see more detail on the determination of the number of factors, and it would be useful to provide more detail. Was it conducted through PCA or PAF? Did they also evaluate the scree plot and eigenvalues? And an evaluation of the simple structure? This procedure would have helped to identify the cross-loafing elements in the EFA.

- Page 23: it is not clear why the relationship between attractiveness and intrasexual competitiveness with SOTM should not be relevant for women as well.

- Page 24: ‘In this sense, the evidence shows that the self-perception of attractiveness is not necessarily correlated with more objective measures, such as the evaluation of attractiveness by third parties (Greitemeyer, 2020)’. I would suggest that the authors explore the presumed underlying mechanism.

Minor points:

- Page 20: The degrees of freedom do not apply to the r coefficient itself, but rather to the statistical test used to evaluate its significance

- . Pearson's r coefficient is a descriptive statistic and the test on r could be conducted either through a t-test (with N-2 dfs) or through a z-test. Therefore, I would report, together with the r coefficient, the t statistic together with the relative dfs).

Page 23: ‘Furthermore, physical attractiveness was also positively associated with sociosexual behaviour. For women, physical attractiveness was positively correlated with sociosexual behaviour’. It is not clear whether this is a repetition or whether the first sentence was intended to refer to men.

References

Ciocca, G., Giorgini, R., Petrocchi, L., Origlia, G., Occhiuto, G., Aversa, A., & Liuzza, M. T. (2024). Psychometric characteristics of the Italian version of the revised Sociosexual Orientation Inventory. Archives of Sexual Behavior, 53(8), 3267–3283. https://doi.org/10.1007/s10508-024-02882-w

Reise, S. P., Bonifay, W. E., & Haviland, M. G. (2013). Scoring and modelling psychological measures in the presence of multidimensionality. Journal of Personality Assessment, 95(2), 129–140.

Ronkko., M., & Cho, E. (2022). An updated guideline for assessing discriminant validity. Organizational Research Methods, 25(1), 6–14

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Reviewer 1: Yes: Pierluigi Diotaiuti

Reviewer 2: Yes: Marco Tullio Liuzza

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Validation of the Multidimensional Sociosexual Orientation Inventory (SOI-M) in the Chilean population

PONE-D-24-46988R1

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Vincenzo Auriemma

Academic Editor

PLOS ONE

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