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# Cross-cultural data on romantic love and mate preferences from 117,293 participants across 175 countries

Marta Kowal et al. #

Psychological studies on close relationships have often overlooked cultural diversity, dynamic processes, and potentially universal principles that shape intimate partnerships. To address the limited generalizability of previous research and advance our understanding of romantic love experiences, mate preferences, and physical attractiveness, we conducted a large-scale cross-cultural survey study on these topics. A total of 404 researchers collected data in 45 languages from April to August 2021, involving 117,293 participants from 175 countries. Aside from standard demographic questions, the survey included valuable information on variables relevant to romantic relationships: intimate, passionate, and committed love within romantic relationships, physical-attractiveness enhancing behaviors, gender equality endorsement, collectivistic attitudes, personal history of pathogenic diseases, relationship quality, jealousy, personal involvement in sexual and/or emotional infidelity, relational mobility, mate preferences, and acceptance of sugar relationships. The resulting dataset provides a rich resource for investigating patterns within, and associations across, a broad range of variables relevant to romantic relationships, with extensive opportunities to analyze individual experiences worldwide.

## Background & Summary

Studies from the early 21st century have revealed a significant bias in social science research, with most studies conducted in WEIRD (Western, Educated, Industrialized, Rich, and Democratic) countries¹⁻³. Research on close relationships is no exception. To illustrate, Klein et al.⁴ analyzed five high-impact journals dedicated to sexuality and found that a substantial majority of studies (ranging from 68% to 88%) drew samples from WEIRD populations. Bode and Kowal⁵ reported similar results in their review of the biological underpinnings of passionate love: Only 11 out of 42 (26%) studies were conducted outside of WEIRD countries.

Fortunately, the situation is gradually improving⁶,⁷, with more researchers emphasizing the need to 'go beyond' WEIRD samples. Indeed, the number of studies in non-WEIRD countries published in high-impact journals is on the rise⁶, as is the number of cross-cultural studies covering multiple countries from various continents⁸. To contribute to this growing body of research, moving beyond WEIRD samples, and to improve the generalizability of research on close relationships, we conducted a large-scale cross-cultural study involving 404 researchers from 175 countries (see Fig. 1), focusing on pair bonds, their dynamics, and cultural and environmental factors that may potentially relate to such relationships.

Pair bonds are commonly defined as dyadic attachments between two reproductive partners which last more than one reproductive cycle⁹. Although pair bonding is considered one of the most crucial aspects of reproductive behavior for some species, it is also exceptionally rare across some taxa. While 90% of bird species exhibit features of monogamous pair bonding, monogamy is relatively rare in mammals (3% to 9%)¹⁰,¹¹. Among great apes, only humans engage in pair-bonding¹². Consequently, human pair-bonding has received scholarly attention across a variety of theoretical perspectives. For instance, evolutionary approaches highlight the importance of finding a suitable mate likely to invest in offspring¹³. Developmental psychology posits that

<footnote># A full list of authors and their affiliations appears at the end of the paper.</footnote>
<figure><img src="image_2.png" /><figcaption>Fig. 1 A schematic overview of the study flow.</figcaption></figure>

establishing an intimate romantic bond with a long-term partner is one of the key stages in human development¹⁴. Sociocultural theory underscores the societal importance of this phenomenon, suggesting that pair bonding is influenced by cultural norms that can shape the initiation, progression, and dynamics of romantic relationships¹⁵.

Given the profound impact of romantic relationships on individuals' lives, extensive research efforts have been dedicated to exploring the antecedents of forming committed partnerships. Many empirical studies have focused on mate preferences, identifying the traits that make individuals highly attractive in the mating market. The underlying logic is that certain characteristics—such as physical attractiveness, intelligence, honesty, health, and kindness—may enhance one's success in attracting potential partners¹³,¹⁶. Some have even suggested that a person's desirability on the mating market may be estimated mathematically¹⁷. Such statistical models might be tested on large datasets, for which the present dataset could be well suited.

Yet, possessing desirable traits does not guarantee that a person will be chosen as a life partner. The solution to this enigma might lie in 'a matter of heart'¹⁸ or, expressed in more scientific terms, in romantic love. Mate preferences and sexual drive toward particular individuals might stem from or lead to feelings of romantic love¹⁹. According to the commitment device hypothesis, romantic love evolved to foster commitment between partners, thereby enhancing their reproductive success²⁰. Previous research has provided evidence that although romantic love is a nearly universal human experience²¹⁻²³, there is substantial cultural and environmental variation in love experiences that reflect, for example, evolutionary legacy, modernization, collectivism, and average annual temperatures²⁴ (for a review, see²⁵). Such hypotheses might be further explored with the present cross-cultural dataset containing information on love experiences with measures that have already been cross-culturally validated²²,²⁶. Furthermore, once a romantic relationship is formed, numerous other affective phenomena emerge, including feelings of jealousy, relationship satisfaction, and commitment—all of which were also measured in the present dataset. In past research, these phenomena have been examined in isolation and primarily studied in a limited number of countries (for reviews, see²⁷,²⁸).

Here, to broaden the scope of close relationship research, we address the existing gap and offer a large-scale cross-cultural dataset. It consists of a comprehensive collection of variables on demographics, intimacy, passion, and commitment within romantic relationships, physical attractiveness enhancing behaviors, gender equality endorsement, collectivistic attitudes, personal history of pathogenic diseases, relationship quality, jealousy, infidelity, relational mobility, mate preferences, current mate ratings, self-ratings, and acceptance of sugar relationships. Furthermore, because our survey was translated into 45 languages, it provides a basis for validating various linguistic versions of the scales used (e.g.,²²,²⁶).

## Methods

When describing the following section, we used articles presenting social sciences data published in Scientific Data as blueprints²⁹⁻³¹.

**Ethical considerations.** The protocol for this study was approved by the Institutional Review Board (IRB) at the Institute of Psychology, University of Wrocław (number IPE0022). Data collection was conducted by team members in accordance with the ethical guidelines established by their respective IRBs, following either the Principal Investigator's IRB approval or the ethical clearances obtained from their local IRBs. Furthermore, all participants provided informed consent prior to their involvement in the study. Specifically, they confirmed that they were over 18 years old and acknowledged that their data, anonymized and stripped of any identifiable information, would be analyzed and disseminated in scientific reports and papers. Anonymity and confidentiality were guaranteed to participants as well as the voluntary nature of their participation.
<table><thead><tr><th colspan="3">SURVEY DESIGN</th></tr><tr><th>CATEGORY</th><th>SUBCATEGORY</th><th>VARIABLES</th></tr></thead><tbody><tr><td rowspan="18">SELF</td><td rowspan="10">Demographics</td><td>Language</td></tr><tr><td>Age</td></tr><tr><td>Gender</td></tr><tr><td>Sex at birth</td></tr><tr><td>Sexual orientation</td></tr><tr><td>Religious affiliation</td></tr><tr><td>Political views</td></tr><tr><td>Country of birth and residence (if different)</td></tr><tr><td>Time spent in country of birth (if different)</td></tr><tr><td>Employment status</td></tr><tr><td>Social status</td></tr><tr><td>Level of education</td></tr><tr><td>Number of children</td></tr><tr><td>Time spent on social media use</td></tr><tr><td>Time spent watching TV</td></tr><tr><td>Time spent on leisure activities</td></tr><tr><td rowspan="2">Attitudes</td><td>Individualistic attitudes</td></tr><tr><td>Attitudes toward gender equality</td></tr><tr><td rowspan="5">Perceptions</td><td>Perceived kindness</td></tr><tr><td>Perceived religiousness</td></tr><tr><td>Perceived financial prospects</td></tr><tr><td>Perceived physical health</td></tr><tr><td>Perceived physical attractiveness</td></tr><tr><td rowspan="5">Behaviors</td><td>Reproductive health behaviors (STDs)</td></tr><tr><td>Physical attractiveness-enhancing behaviors</td></tr><tr><td rowspan="10">PARTNER¹</td><td rowspan="4">Demographics</td><td>Age</td></tr><tr><td>Level of education</td></tr><tr><td>Social status</td></tr><tr><td>Political views</td></tr><tr><td rowspan="4">Perceptions</td><td>Perceived kindness</td></tr><tr><td>Perceived religiousness</td></tr><tr><td>Perceived financial prospects</td></tr><tr><td>Perceived physical health</td></tr><tr><td rowspan="2">PAIR</td><td rowspan="2">Love</td><td>Love feelings at present</td></tr><tr><td>Intensity of love feelings (if present)</td></tr><tr><td rowspan="5">Relationships</td><td>Passion, intimacy, commitment (if present)</td></tr><tr><td>Matrimonial directedness</td></tr><tr><td>Jealous feelings (in case of infidelity)</td></tr><tr><td>Relationship status</td></tr><tr><td>Relationship duration¹</td></tr><tr><td rowspan="5">BACKGROUND PROCEDURES</td><td rowspan="5">Metadata</td><td>Relationship duration¹</td></tr><tr><td>Relationship satisfaction¹</td></tr><tr><td>Long/short/term relationship preferences</td></tr><tr><td>Casual sexual experiences and preferences</td></tr><tr><td>Infidelity experiences and preferences</td></tr><tr><td rowspan="5">BACKGROUND PROCEDURES</td><td rowspan="5">Metadata</td><td>Acceptance of sugar relationships</td></tr><tr><td>Response date</td></tr><tr><td>Response completion</td></tr><tr><td>Response duration</td></tr><tr><td>Lab's ID</td></tr><tr><td rowspan="3">BACKGROUND PROCEDURES</td><td>Respondent's ID</td></tr><tr><td>Respondent's Consent</td></tr><tr><td>Attention check</td></tr></tbody></table>

Legend: ¹ Relevant to partnered participants

<caption>Fig. 2 A visual overview of the study's content (for detailed list of all variables, see Codebook).</caption>

**Survey.** The English version of the survey, along with all 45 translated linguistic versions, can be accessed on the Open Science Framework³². It contains the following sections (for the visual overview of the survey's content, see Fig. 2):

1. **Demographics:** Gender, sex at birth, age, country of birth and residence (if different), time spent in country of birth, relationship status, number of children, religious affiliation, sexual orientation, employment status, average daily time spent on social media, on TV, and time spent on leisure activities.

2. **Romantic love:** For partnered individuals: the Triangular Love Scale (TLS-15²²,³³), relationship length. For all individuals: Kephart's¹⁸ question on the importance of romantic love²⁰, being in love with anyone and the strength of these love feelings.
3. **Gender equality:** A subscale of the Gender Equitable Men Scale³⁴.

4. **Collectivistic attitudes:** A subscale of the Collectivism Scale³⁵.

5. **Personal Pathogen History:** Pathogen Prevalence Index³⁶.

6. **Physical Attractiveness-Enhancing Behaviors Scale:** Importance and time spent on eight types of physical-attractiveness enhancing behaviors²⁶.

7. **Long-term relationship preferences:** Six items adapted from the MPQ15¹⁷.

8. **Short-term relationship preferences:** Six items adapted from the MPQ15¹⁷.

9. **Preference Importance Measure:** 30 points allocated across six traits, including health, kindness, physical attractiveness, religiousness, financial prospects, and correct age, inspired by the budget allocation method used in Li *et al.*³⁷ and Conroy-Beam *et al.*¹⁷.

10. **Self-ratings:** Six items adapted from the MPQ15¹⁷.

11. **Mate ratings:** Six items adapted from the MPQ15¹⁷.

12. **Relationship satisfaction:** Six items from the 18-item Perceived Relationship Quality Components (PRQC³⁸).

13. **Jealousy Scale:** Two items adapted from Buss *et al.*³⁹.

14. **Sociosexual Attitudes Scale:** Three items from the revised Sociosexual Orientation Inventory (SOI-R⁴⁰).

15. **Infidelity Scale:** Two items assessing the perceived morality of sexual and emotional infidelity, developed based on findings from Carpenter's⁴¹ meta-analysis.

16. **Acceptance of Sugar Relationships:** Developed for younger companion providers (ASR-YWMS) and older resource providers (ASR-OMWS)⁴².

A detailed list of all items with their response ranges and codes can be found in the Codebook file titled "Codebook.xlsx" on the Open Science Framework, OSF³². The survey also included the Dance Perceptions Scale. However, this portion of the data is not included in the current dataset, as it is reserved for a forthcoming publication within the scope of a larger, long-term project on dance perceptions. These data will be made available upon the release of the final paper.

**Participants.** In total, we collected 119,781 responses. Excluding data from those who did not consent to participate in the study (n = 639), who previewed (n = 4) or tested the survey (n = 549) but did not complete it, who mistakenly doubled their submission (n = 21), who were recruited by one team member who collected data before asking their local IRB for approval, which violated the local IRB's rules, and thus was asked to withdraw the data (n = 244), and who failed the attention check (n = 1031) resulted in a final dataset of 117,293 participants from 175 countries. Out of these, 71,361 participants (61%) from 158 countries completed the whole survey, whereas 86,966 (74%) from 165 countries completed at least half of the survey.

Basic demographic characteristics of participants from the final dataset are presented in Table 1, whereas demographic characteristics across countries with at least 30 participants (k = 97) are given in the "Demographics across countries.xlsx" file on the OSF³². Figure 3 shows where the data were collected, colored according to the sample size.

**Translations.** The English version of the survey embedded in the HTML codes was pasted into 45 separate Google Spreadsheet files. Each of the 45 translation teams, consisting of bilingual collaborators, received a separate Google Spreadsheet file that consisted of four sheets. On the first sheet, there were instructions on how to perform the forward-back translation⁴³. The second sheet was intended for the forward-translation of the survey from English into a local language. The third sheet was intended for back-translation from the same local language into English. The final sheet was intended to prepare the final version of the survey in the local language. One or more native speakers performed the forward-translation, then other(s) performed the back-translation, and, finally, both forward- and back-translation teams discussed the differences, agreed on their resolution, and prepared the final linguistic version of the survey. Detailed instructions, along with a short video explaining the translation task, are presented in the "Instructions for translating teams.docx" file on the OSF³². All linguistic versions of the survey can be accessed in the "Translated survey - all languages.xlsx" file and "Translation Farsi.doc" file on the OSF³².

**Procedure.** After the translation process was completed, the study for that given language was launched, starting with English and Polish on April 8, 2021, to validate the Qualtrics survey and data protocols. Data collection was conducted over a span of five months, from April to August 2021. Data were collected primarily online via the Qualtrics website or related online platforms, except for two countries (i.e., Algeria and Morocco), where potential participants could not access the Qualtrics website for technical reasons. Therefore, the team members collected data from these two countries in person using a paper-and-pencil method. Moreover, due to difficulties accessing the Qualtrics website in Iran, we recreated the survey and collected data using Google Forms. Lastly, one Russian Collaborator collected data via the Toloka website (a crowdsourcing platform popular in Russia, similar to Prolific or Mechanical Turk). Collaborators strived to collect data from as diverse samples as possible, including inviting participants of various ages, genders, from various regions (including rural and urban areas), from the community and university samples, and so forth. While answering the survey, participants were also encouraged to share the link to the survey on their social media platforms with an already prepared invitation text (see the "Invitation text.docx" file on the OSF³²). Approximately 6% of the data were collected using outsourcing platforms (e.g., Prolific, MTurk, Toloka).
<table><caption>Table 1. Basic demographic characteristics of the final sample (N = 117,293).</caption><thead><tr><th>Variable</th><th></th><th>N/Mean</th><th>%/SD</th></tr></thead><tbody><tr><td>Gender</td><td></td><td></td><td></td></tr><tr><td>Women</td><td></td><td>71327</td><td>60.80%</td></tr><tr><td>Men</td><td></td><td>34864</td><td>29.70%</td></tr><tr><td>Non-binary</td><td></td><td>1089</td><td>0.90%</td></tr><tr><td>Prefer not to say</td><td></td><td>486</td><td>0.40%</td></tr><tr><td>N/A</td><td></td><td>9527</td><td>8.10%</td></tr><tr><td>Age</td><td></td><td>30.35</td><td>12.55</td></tr><tr><td>Number of children</td><td></td><td>0.50</td><td>0.97</td></tr><tr><td>Education</td><td></td><td></td><td></td></tr><tr><td>No formal education</td><td></td><td>275</td><td>0.20%</td></tr><tr><td>Primary school only</td><td></td><td>474</td><td>0.40%</td></tr><tr><td>Primary school through Secondary school</td><td></td><td>38763</td><td>33.00%</td></tr><tr><td>Primary school through High school or Technical college</td><td></td><td>19535</td><td>16.70%</td></tr><tr><td>Primary school through Bachelor's degree</td><td></td><td>18005</td><td>15.40%</td></tr><tr><td>Primary school through Master's degree</td><td></td><td>5473</td><td>4.70%</td></tr><tr><td>Primary school through PhD, MD, JD, or other advanced degree</td><td></td><td>5216</td><td>4.40%</td></tr><tr><td>N/A</td><td></td><td>29552</td><td>25.20%</td></tr><tr><td>Religious affiliation</td><td></td><td></td><td></td></tr><tr><td>Buddhism</td><td></td><td>2362</td><td>2%</td></tr><tr><td>Christianity</td><td></td><td>41486</td><td>35.40%</td></tr><tr><td>Hinduism</td><td></td><td>1033</td><td>0.90%</td></tr><tr><td>Islam</td><td></td><td>16820</td><td>14.30%</td></tr><tr><td>Judaism</td><td></td><td>1331</td><td>1.10%</td></tr><tr><td>None</td><td></td><td>40253</td><td>34.30%</td></tr><tr><td>Other</td><td></td><td>4106</td><td>3.50%</td></tr><tr><td>N/A</td><td></td><td>9902</td><td>8.40%</td></tr><tr><td>Sexual orientation</td><td></td><td></td><td></td></tr><tr><td>Asexual</td><td></td><td>1110</td><td>0.90%</td></tr><tr><td>Bisexual</td><td></td><td>7895</td><td>6.70%</td></tr><tr><td>Gay</td><td></td><td>2156</td><td>1.80%</td></tr><tr><td>Heterosexual</td><td></td><td>87043</td><td>74.20%</td></tr><tr><td>Lesbian</td><td></td><td>1455</td><td>1.20%</td></tr><tr><td>Other</td><td></td><td>1244</td><td>1.10%</td></tr><tr><td>Pansexual</td><td></td><td>1863</td><td>1.60%</td></tr><tr><td>Prefer not to say</td><td></td><td>4229</td><td>3.60%</td></tr><tr><td>N/A</td><td></td><td>10298</td><td>8.80%</td></tr></tbody></table>

**Data cleaning.** Most collaborators collected data via personalized Qualtrics links to the general survey (with a few exceptions, described in the Procedure paragraph). Moreover, due to certain collaborators' requests, connected with, for instance, adding personalized information within the survey, redirections to other websites, the need for better monitoring of data inflow, or collecting more information to grant course credits to students who helped with data collection, seven labs recruited participants through separate Qualtrics branches. All these datasets were merged into the final, ready-to-use dataset.

Data coming from outside of the general survey link were prone to minor coding mistakes. For instance, manually prepared datasets from Algeria and Morocco contained typos, such as doubled scores (e.g., a response of “44” on a 1–5 scale range). All these errors are addressed in the final dataset, the details for which are described in detail in the R script available on the OSF (see below).

**Data Records**

All materials associated with this large-scale, cross-cultural project can be found on the project's repository (comprising four folders) on the OSF³². The folder entitled “Dataset” contains the final, ready-to-use dataset (named “Final_dataset.csv”) and the Codebook of all variables with their response ranges (named “Codebook.xlsx”). The folder “R code” consists of a .txt file (named “R script.txt”) that was run to merge and clean raw datasets. Raw datasets are not shared because they may contain personal information about participants and collaborators (e.g., email addresses, student identification numbers, and detailed names of university groups and courses). The full anonymization code is available in the file “R Script.txt.” The folder “Survey” contains the .docx files “Instructions for translating teams.docx” and “Invitation text.docx”, which aimed to encourage participants to share the link to the survey with their friends, families, and on social media. The Survey folder also
<figure><img src="image_3.png" /><figcaption>**Fig. 3** A world map visualizing the number of participants across countries, with the color scale representing the sample size (the darker, the larger). *Note.* Gray areas represent countries not covered by the data.</figcaption></figure>

contains the .pdf file with the English version of the survey (named "Large_scale_project_English_with_codes.pdf"), the "README.txt" file which reminds users about any incongruence between the coding from the .pdf version of the survey and final coding in the dataset (as explained in the "Usage Notes" section), as well as .xlxs and .docx files with all translated versions of the survey (named "Translated survey - all languages.xlsx" and "Translation Farsi.docx"). The folder "R code" contains a .txt file (named "R code large-scale study.txt") with R code that was used to prepare the final dataset. Finally, the "Data description" folder contains the .xlxs file (named "Demographics across countries.xlsx") with demographic characteristics of participants for countries with at least 30 participants. It also contains the "Reliabilities across countries.xlsx" file containing information on the reliability of the multi-item scales across these countries, and the "Means across countries.xlsx" file with the means of the scales across these countries.

## Technical Validation

For technical validation, we examined the data quality (e.g., Cronbach's alpha scores, correlations) from 97 countries with at least 30 participants. Overall, 70 of these 97 countries (72%) had more than 200 participants, whereas 32 of them had more than 1,000 participants. The average age in this sample was similar to that of the whole sample, that is, 30.35 (SD = 12.54), but varied across the countries, ranging from 21.48 (SD = 5.06) in Thailand to 47.32 (SD = 16.86) in Argentina. The proportion of women in this sample was 66.30%, and again, this varied across countries, ranging from 5.4% in Ghana to 84% in Greece. The proportion of individuals who attained a tertiary level of education (i.e., Bachelor's degree or higher) was 58%, and also differed across countries, ranging from 6.1% in Ghana to 81.4% in Kenya. Although we cannot determine the representativeness of the included country populations, we believe that the data are still valuable in examining important research questions across a range of cultures varying widely in their norms surrounding relationships, sexual behavior, sexuality, and mate selection.

Despite variation in demographic variables across countries, the internal consistency of the scales ranged from good to excellent. For instance, Cronbach's alpha for the TLS-15 = 0.94, Intimacy = 0.90, Passion = 0.87, Commitment = 0.89²², gender equality = 0.85³⁴, collectivism = 0.76³⁵, Perceived Relationship Quality Components (PRQC) = 0.93, relationship satisfaction = 0.94, relationship commitment = 0.89³⁸, Acceptance of Sugar Relationships = 0.95, receiving subscale = 0.93, giving subscale = 0.93⁴². The "Reliabilities across countries.xlsx" file (accessible on the OSF³²) presents Cronbach's alphas for the scales across countries, with at least 30 participants answering the given scale. Basic descriptive statistics for these scales, including means and standard deviations, are presented in the "Means across countries.xlsx" file (accessible on the OSF³²).
For further validation of the data, we investigated correlations across variables that should correlate and those for which there are no expected associations. For example, we predicted high positive Pearson correlations between age and relationship length and age and the number of children¹⁰. Indeed, that is what we observed (r = 0.74 and r = 0.62, respectively). Similarly, we expected high positive correlations between subscales of the Triangular Love Scale (TLS-15²²) and relationship satisfaction³⁸: Intimacy r = 0.70, Passion r = 0.63, Commitment r = 0.63. In line with previous research⁴⁴, we also observed a high correlation between one's own and partner's age (r = 0.87). Conversely, we did not expect to see any significant links between subscales of love and time spent on social media, and, indeed, such correlations were marginal in effect size (Intimacy r = 0.04, Passion r = 0.07, Commitment r = 0.002).

## Usage Notes

The data are freely available, cleaned, and ready for analyses. We recommend that interested researchers first consult the codebook (“Codebook.xslx”) before using the final version of the dataset (available on OSF³²). The codebook presents all variables in the final dataset along with a brief explanation of both their scoring and what they represent. This is especially important because the original coding of some of the variables described in the .pdf version of the survey was recoded to be more intuitive. For example, there is a demographic question regarding the participant’s social class in the .pdf version of the survey, originally coded so that higher values represent lower social classes. In the final dataset, however, this item was reversed so that higher values represent higher social classes. In general, the naming of the variables follows the underlying logic so that higher scores represent “more” of the given psychological construct. Therefore, for instance, the “Gender_equality” items denote the participant’s agreement with more gender-equal views. Variables can be used individually or with the calculated average scores. To identify individuals from a specific country, the variables “CountryTOR” or “Country_Raised” should be used, depending on whether researchers wish to use participants’ country of residence, the country in which they were raised, or both.

Additionally, interested researchers should be cautious about using the mate budget allocation task, in which participants had to distribute 30 points across six potential traits (health, kindness, physical attractiveness, religiousness, financial prospects, correct age) in a romantic partner. When collecting data with the paper-and-pencil method in Algeria and Morocco, there was no validation of the total sum of allocated points. Consequently, the sum of allocated points exceeds 30 in almost 100 Algerian participants.

## Code availability

The R code for cleaning is available on the OSF³².

Received: 11 March 2025; Accepted: 6 June 2025;

Published online: 01 July 2025

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## Acknowledgements

This work is the result of the research project funded by the National Science Center, Poland (2019/33/N/HS6/00054). Marta Kowal was supported by the Foundation for Polish Science (FNP) START scholarship. Toivo Aavik was supported by the Estonian Research Council grant (PRG2190). The authors would like to thank the following scholars for their help with the translation: Christin-Melanie Vauclair Melanie, Catia Carvalho, Diogo Lamela, Elena Piccinelli, Anabela Caetano Santos, Patrícia Arriaga, and Isabel Pinto (Portuguese), Stanislava Stoyanova (Bulgarian), Vira Hrabchuk and Anne MacFarlane (Ukrainian). The authors would also like to thank the following organizations and individuals for their help with organizing data collection in El Salvador: the Escuela de Comunicacion Monica Herrera, Directora Nicole Paetz, asistente María Erlinda Avalos, Diego Infante, and Gabriela Quintanilla. Finally, the authors would like to thank all participants who devoted their time to answer the survey and to share the survey link with others.

## Author contributions

Contributions from all the authors are listed in the Supplementary Material (Figure S1).

## Competing interests

The authors declare no competing interests.

## Additional information

**Supplementary information** The online version contains supplementary material available at https://doi.org/10.1038/s41597-025-05365-2.

**Correspondence** and requests for materials should be addressed to M.K.

**Reprints and permissions information** is available at www.nature.com/reprints.
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© The Author(s) 2025

Marta Kowal ID1,*, Piotr Sorokowski², Biljana Gjoneska ID³, Katarzyna Pisanski ID2,4,5,
Gerit Pfuhl ID6, Leonardo Aguilar ID7, Steve M. J. Janssen ID8, Benjamin Gelbart9,
Patrícia Arriaga ID10, Jan Antfolk ID11, Katarina Zvončáková12,13, Linda H. Lidborg14,
Jorge Contreras-Garduño15, Mikhail V. Kozlov16, Taciano L. Milfont17, Marco A. C. Varella18,
Valerija Križanič19, Mahmoud Boussena ID20, Tina Kavčič21,22, Diana Ribeiro da Silva23,
Brahim Hamdaoui24, Fatima Zahra Sahli25, Karlijn Massar26, Eliane Deschrijver27,
Tatsunori Ishii ID28, Hakan Cetinkaya29, Oksana Senyk30, Farida Guemaz31, Koen Ponnet32,
Yahya Don33, Dušana Šakan34, Gyesook Yoo ID35, Ravit Nussinson36,37, Joaquín Ungaretti38,
Ali R. Can39, Izzet Duyar ID40, Jiří Čeněk ID41,42, Joao Carneiro43, Norbert Meskó ID44,
Luca Kozma ID45, Ellen K. Nyhus46, Mona Vintila47, Oulmann Zerhouni48,49, Farid Pazhoohi50,
Maja Zupančič21, Sinem Söylemez51, Austin H.-E. Wang52, Marietta Papadatou-Pastou53,
Irena Pavela Banai19, Pavol Prokop ID54,55, Mohd Sofian Omar Fauzee56, Reza Afhami ID57,
Jean C. Natividade ID58, Roberto Baiocco59, Mara Morelli60, Toivo Aavik61, Ezgi Toplu-
Demirtaş62, Singha Tulyakul63, Anna Wlodarczyk ID64, Razieh Chegeni65, Anabela C. Santos ID66,
Dmitry Grigoryev ID67, Dmitrii Dubrov ID67, Dimitri Chubinidze68, Gözde Ikizer ID69,
Nana Burduli70, Johanna Czamanski-Cohen ID71, Rizwana Amin ID72,73, Petros Roussos74,
Evgeniya Hristova75, Rūta Sargautytė ID76, Ekaterine Pirtskhalava77, Tenuunjargal Avirmed78,
Arooj Najmussaqib79, Abdelilah Charyate80, Shagufta Batool81, Tatiana Volkodav ID82,
Yoshihiko Kunisato83, Yuki Yamada ID84, Asako Toyama85, Mariia Perun86, Seda Dural ID87,
Tetyana Mandzyk86, Anna Studzinska ID88, Ognen Spasovski89, Felipe E. García90,
Caterina Grano ID91, Merve Boğa92, Mehmet Koyuncu93, Sangeeta Singh94, Ju Hee Park95,
Derya Atamtürk40, Samuel Lins ID43, Martin Pírko96, David Lacko ID12,42, Balazs Aczel ID97,
Ferenc Kocsor44, Ádám Putz98, Tobias Otterbring ID99, Pavol Kačmár ID100,
Efisio Manunta101,102, Théo Besson ID103, Nasim Ghahraman Moharrampour104,
Çağlar Solak51, Bojana M. Dinić105, Ignacio Estevan ID106, Merve Topcu Bulut107,
Nicolas Kervyn ID108, Moises Mebarak109, Jackson G. Lu ID110, Nejc Plohl111, Bojan Musil111,
Adil Samekin112, Kirill G. Miroshnik113,114, Clément Cornec5, Isabella Giammusso115,
Ulf-Dietrich Reips ID116, Maria Rosa Miccoli116, Miriam Parise117, Sabrina Stöckli118,119,
Tiago Marot120, Sibele D. Aquino ID58, Amanda Londero-Santos121, Antonio Chirumbolo122,
Aybegum Memisoglu-Sanli123, Jaroslava V. Valentova124, Cemre Karaarslan125,
Ivana Hromatko126, Kevin Sevag Kertechian127, Ogeday Çoker ID128, Matheus F. Ribeiro129,
Carlota Batres ID130, Ilker Dalgar ID123, Stephanie J. Eder ID131, Katarina Mišetić132,
Marios Argyrides133, Vita Mikuličiūtė76, Silvia Mari ID134, Elisabeth Oberzaucher ID135,136,137,
Kathrin Masuch ID135,137, Alan D. A. Mattiassi138, Salma S. Omar139, Elena Piccinelli ID140,
Eda Ermagan Caglar ID141, Diogo Lamela142, David A. Frederick143, Aleksander Kobylarek144,
Ma Criselda T. Pacquing145,146, Marc Eric S. Reyes145,146, Marcos Zumárraga-Espinosa147,
Feten Fekih-Romdhane148,149, Talía Gómez Yepes150,151, Edgardo Etchezahar150,152,
Katarzyna Galasinska153, Jan P. Röer ID154, Ayşegül Şahin40, Miguel Landa-Blanco155,
Izuchukwu L. G. Ndukaihe156, Arkadiusz Urbanek144, Chee-Seng Tan157, Rita Castro43,
Ksenija Cunichina76, Anna Krasnoděbska158, Daniel Conroy-Beam9, Franciszek Ostaszewski153,
Izabela Chałatkiewicz153, Beatriz Abad-Villaverde159, Bastien Trémolière160, Alexios
Arvanitis ID161, Gulmira T. Topanova162, William J. Chopik163, Grace Akello164,
Ariela F. Pagani165, Silvia Donato117, Peter Fedor54, Tomasz Frackowiak2, Simon Ozer ID166,
Marlon Mayorga-Lascano¹⁶⁷, Farah Khan¹⁶⁸, Maryanne L. Fisher¹⁶⁹, Princess Lovella G. Maturan¹⁷⁰, Tatiana Semenovskikh¹⁷¹, Sanjana Dutt¹⁷², William Tamayo-Agudelo¹⁷³, Gulnara Ismukhanova¹⁷⁴, Laith Al-Shawaf¹⁷⁵,¹⁷⁶,¹⁷⁷,¹⁷⁸, Luisa Angelucci¹⁷⁹,¹⁸⁰, Adam Bode¹⁸¹, Sercan Balim¹⁸², Jovi C. Dacanay¹⁸³, Chiemezie S. Atama¹⁸⁴, Kai A. D. Morgan Campbell¹⁸⁵, Tchilissila A. Simões¹⁸⁶, Barış Özener⁴⁰, Paula Błauciak¹⁸⁷ & Filipe Prazeres¹⁸⁸

¹IDN Being Human Lab - Institute of Psychology, University of Wrocław, Wrocław, Poland. ²Institute of Psychology, University of Wrocław, Wrocław, Poland. ³Macedonian Academy of Sciences and Arts, Skopje, North Macedonia.

⁴CNRS French National Centre for Scientific Research, DDL Dynamics of Language Laboratory, University of Lyon 2, Lyon, France. ⁵ENES Bioacoustics Research Lab, Jean Monnet University of Saint-Etienne, Saint-Etienne, France. ⁶Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway.

⁷School of Psychology, Central University of Venezuela, Caracas, Venezuela. ⁸School of Psychology, University of Nottingham Malaysia, Semenyih, Malaysia. ⁹Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, USA. ¹⁰Department of Psychology & CIS-Iscte, ISCTE - Instituto Universitário de Lisboa, Lisbon, Portugal. ¹¹Faculty of Arts, Psychology and Theology, Åbo Akademi University, Turku, Finland. ¹²Institute of Psychology, Czech Academy of Sciences, Brno, Czech Republic. ¹³Department of Psychology, Masaryk University, Brno, Czech Republic. ¹⁴Department of Psychology, Durham University, Durham, United Kingdom. ¹⁵Escuela Nacional de Estudios Superiores Unidad Morelia, Universidad Nacional Autónoma de México, Morelia, México. ¹⁶Department of Biology, University of Turku, Turku, Finland. ¹⁷School of Psychological and Social Sciences, University of Waikato, Tauranga, New Zealand. ¹⁸Department of Experimental Psychology, Institute of Psychology, University of São Paulo, São Paulo, Brazil. ¹⁹Department of Psychology, Faculty of Humanities and Social Sciences, J. J. Strossmayer University of Osijek, Osijek, Croatia. ²⁰Department of Psychology, University Mohamed lamine Debaghine Setif2, Setif, Algeria. ²¹Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia. ²²Faculty of Health Sciences, University of Ljubljana, Ljubljana, Slovenia. ²³CINEICC - Center for Research in Neuropsychology and Cognitive Behavioral Intervention, University of Coimbra, Coimbra, Portugal. ²⁴Departement of Sociology, Ibn Tofail University, Kénitra, Morocco. ²⁵Ibn Tofail University, Kenitra, Morocco. ²⁶Department of Work & Social Psychology, Maastricht University, Maastricht, The Netherlands. ²⁷School of Psychology, University of Sydney, Sydney, Australia. ²⁸Department of Psychology, Japan Women's University, Tokyo, Japan. ²⁹Department of Psychology, Yaşar University, Izmir, Turkey. ³⁰Department of Humanities and Social Sciences, WSB Merito University in Gdansk, Gdansk, Poland. ³¹Department of Psychology and Educational sciences and Orthophony, Mohamed Lamine Debaghine University Setif2, Setif, Algeria. ³²Faculty of Social Sciences, Ghent University, Ghent, Belgium. ³³School of Education (SoE), Universiti Utara Malaysia, Alor Setar, Malaysia. ³⁴Department of Psychology, Faculty of Legal and Business Studies dr Lazar Vrkatić, Novi Sad, Serbia. ³⁵Department of Child & Family Studies, Kyung Hee University, Seoul, Republic of Korea. ³⁶Department of Education and Psychology, The Open University of Israel, Raanana, Israel. ³⁷Institute for Information Processing and Decision Making, University of Haifa, Haifa, Israel. ³⁸Faculty of Education, Valencian International University, Valencia, Spain. ³⁹Department of Anthropology, Hatay Mustafa Kemal University, Hatay, Turkey. ⁴⁰Department of Anthropology, Istanbul University, Istanbul, Turkey. ⁴¹Department of Social Studies, Mendel University in Brno, Brno, Czechia. ⁴²Interdisciplinary Research Team on Internet and Society, Masaryk University, Brno, Czechia. ⁴³Department of Psychology, University of Porto, Porto, Portugal. ⁴⁴Institute of Psychology, University of Pécs, Pécs, Hungary. ⁴⁵Division of Psychology, University of the West of Scotland, Paisley, United Kingdom.
⁷⁷Department of Psychology, Ivane Javakhishvili Tbilisi State Univeristy, Tbilisi, Georgia. ⁷⁸Department of Sociology and Social Work, National University of Mongolia, Ulaanbaatar, Mongolia. ⁷⁹Independent Researcher, Independent Researcher, Islamabad, Pakistan. ⁸⁰Département des Sciences de l'éducation, Ecole Supérieure de l'éducation et de la Formation, Université Ibn Tofail, Kenitra, Maroc. ⁸¹Department of Psychology, Northeast Normal University, Changchun, China. ⁸²Department of Pedagogy and Psychology, Kuban State University, Krasnodar, Russia. ⁸³Department of Psychology, Senshu University, Kawasaki, Japan. ⁸⁴Faculty of Arts and Science, Kyushu University, Fukuoka, Japan. ⁸⁵Graduate School of the Humanities, Senshu University, Kawasaki, Japan. ⁸⁶Department of Psychology, Ivan Franko National University of Livv, Lviv, Ukraine. ⁸⁷Department of Psychology, Izmir University of Economics, Izmir, Turkey. ⁸⁸Humanities Department, Icam School of Engineering, Toulouse campus, Toulouse, France. ⁸⁹Department of Psychology, Ss. Cyril and Methodius University in Skopje, Skopje, North Macedonia. ⁹⁰Departamento de Psiquiatría y Salud Mental, Universidad de Concepción, Concepción, Chile. ⁹¹Department of Psychology, Sapienza University, Rome, Italy. ⁹²Department of Psychology, Erciyes University, Kayseri, Turkey. ⁹³Department of Psychology, Izmir Bakırçay University, Izmir, Turkey. ⁹⁴Department of Strategy, University of Agder, Kristiansand, Norway. ⁹⁵Department of Child and Family Studies, Yonsei University, Seoul, Republic of Korea. ⁹⁶Institute of Lifelong Learning, Mendel University in Brno, Brno, Czech Republic. ⁹⁷Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary. ⁹⁸Department of Cognitive and Evolutionary Psychology, University of Pécs, Pécs, Hungary. ⁹⁹Department of Management, University of Agder, Kristiansand, Norway. ¹⁰⁰Department of Psychology, University of Pavol Jozef Šafárik in Košice, Košice, Slovakia. ¹⁰¹CLLE, Université de Toulouse, Toulouse, France. ¹⁰²Department of Psychology, University of Limerick, Limerick, Ireland. ¹⁰³Laboratoire de Psychologie Sociale, Université Paris Cité, Boulogne-billancourt, France. ¹⁰⁴School of Psychological Sciences, University of Melbourne, Melbourne, Australia. ¹⁰⁵Department of Psychology, Faculty of Philosophy, University of Novi Sad, Novi Sad, Serbia. ¹⁰⁶Instituto de Fundamentos y Métodos en Psicología, Facultad de Psicología, Universidad de la República, Montevideo, Uruguay. ¹⁰⁷Department of Psychiatry, School of Medicine, Atılım University, Ankara, Turkey. ¹⁰⁸Louvain School of Management, Université Catholique de Louvain, Louvain La Neuve, Belgium. ¹⁰⁹Department of psychology, Universidad del Norte, Barranquilla, Colombia. ¹¹⁰MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, USA. ¹¹¹Department of Psychology, University of Maribor, Maribor, Slovenia. ¹¹²School of Liberal Arts, M. Narikbayev KAZGUU University, Astana, Kazakhstan. ¹¹³Department of Life Sciences, University of Trieste, Trieste, Italy. ¹¹⁴Department of Psychology, Saint Petersburg State University, Saint Petersburg, Russia. ¹¹⁵Department of Psychology, Educational Science and Human Movement, University of Palermo, Palermo, Italy. ¹¹⁶Department of Psychology, University of Konstanz, Konstanz, Germany. ¹¹⁷Department of Psychology, Università Cattolica del Sacro Cuore, Milano, Italy. ¹¹⁸Chair of Marketing, University of Zurich, Zurich, Switzerland. ¹¹⁹Bern University of Applied Sciences, Bern, Switzerland. ¹²⁰Department of Psychology, Federal Fluminense University, Campos Dos Goytacazes, Brazil. ¹²¹Department of Psychometric - Institute of Psychology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil. ¹²²Department of Psychology, Sapienza University of Rome, Rome, Italy. ¹²³Department of Psychology, Ankara Medipol University, Ankara, Turkey. ¹²⁴Department of Experimental Psychology, Institute of Psychology, University of Sao Paulo, São Paulo, Brazil. ¹²⁵Department of Psychology, Baskent University, Ankara, Turkey. ¹²⁶Department of Psychology, University of Zagreb, Zagreb, Croatia. ¹²⁷Department of Organization, Management, and Human Resource, ESSCA School of Management, Bouloge-Billancourt, France. ¹²⁸Psychology, Pamukkale University, Denizli, Turkey. ¹²⁹Department of Psychology, University of Uberaba, Uberaba, Brazil. ¹³⁰Department of Psychology, Franklin and Marshall College, Lancaster, USA. ¹³¹Department of Neurosciences and Developmental Biology, University of Vienna, Vienna, Austria. ¹³²Department of Psychology, University of Sarajevo, Sarajevo, Bosnia and Herzegovina. ¹³³Department of Psychology, Neapolis University Pafos, Paphos, Cyprus. ¹³⁴Department of Psychology, University of Milano-Bicocca, Milano, Italy. ¹³⁵Faculty of Life Sciences, University of Vienna, Vienna, Austria. ¹³⁶Cognitive Science Hub, University of Vienna, Vienna, Austria. ¹³⁷Urban Human, Vienna, Austria. ¹³⁸Department of Education, Literatures, Intercultural Studies, Languages and Psychology, University of Florence, Florence, Italy. ¹³⁹Department of Dermatology & Andrology, Alexandria University, Alexandria, Egypt. ¹⁴⁰CIS-Iscte, Instituto Universitário de Lisboa (Iscte-IUL), Lisbon, Portugal. ¹⁴¹Department of Psychology, Sakarya University, Sakarya, Turkey. ¹⁴²HEI-Lab, Lusófona University, Porto, Portugal. ¹⁴³Crean College of Health and Behavioral Sciences, Chapman University, Orange, USA. ¹⁴⁴Department of Pedagogy, University of Wrocław, Wrocław, Poland. ¹⁴⁵Department of Psychology, University of Santo Tomas, Manila, Philippines. ¹⁴⁶Research Center for Social Sciences and Education, University of Santo Tomas, Manila, Philippines. ¹⁴⁷Carrera de Psicología, Universidad Politécnica Salesiana (UPS), Quito, Ecuador. ¹⁴⁸Faculty of Medicine of Tunis, Tunis El Manar University, Tunis, Tunisia. ¹⁴⁹Department of Psychiatry Ibn Omrane, Razi Hospital, Manouba, Tunisia. ¹⁵⁰Department of Developmental and Educational Psychology, Universidad Autónoma de Madrid, Madrid, Spain. ¹⁵¹Faculty of Teacher Training and Education, Autonomous University of Madrid, Madrid, Spain. ¹⁵²Centro Interdisciplinario de Investigaciones en Psicología Matemática y Experimental, CONICET, Buenos Aires, Argentina. ¹⁵³Department of Psychology, SWPS University, Warsaw, Poland. ¹⁵⁴Department of Psychology and Psychotherapy, Witten/Herdecke University, Witten, Germany. ¹⁵⁵School of Psychological Sciences, National Autonomous University of Honduras, Tegucigalpa, Honduras. ¹⁵⁶Department of Psychology, Alex Ekwueme Federal University, Ndufu-alike, Nigeria. ¹⁵⁷School of Psychology, Wenzhou-Kean University, Wenzhou, China. ¹⁵⁸Administracja i Bezpieczeństwo Wewnętrzne, Uniwersytet WSB Merito Opole, Opole, Polska. ¹⁵⁹Faculty of Humanities and Education, Universidad Nacional Pedro Henríquez Ureña, Santo Domingo, Dominican Republic. ¹⁶⁰Department of Psychology, Université de Toulouse, Toulouse, France. ¹⁶¹Department of Psychology, University of Crete, Rethymno, Greece. ¹⁶²The Department of Theoretical and Practical Psychology, Информация Kazakh National Women's Teacher Training University, Almaty, Kazakhstan. ¹⁶³Department of Psychology, Michigan State University, East Lansing, MI, USA. ¹⁶⁴Department of Mental Health, Gulu University, Kampala, Uganda. ¹⁶⁵Department of Humanities, University of Urbino Carlo Bo, Urbino, Italy. ¹⁶⁶Department of Psychology and Behavioural Sciences, Aarhus University, Aarhus, Denmark. ¹⁶⁷Escuela de Psicología, Pontificia Universidad del
Ecuador- Ambato, Ambato, Ecuador. ¹⁶⁸Department of Education, Women University Mardan KP, Pakistan, Mardan, KP, Pakistan. ¹⁶⁹Department of Psychology, Saint Mary's University, Halifax, Canada. ¹⁷⁰Department of Psychology, University of the Philippines Diliman, Quezon City, Philippines. ¹⁷¹School of Education, Tyumen State University, Tyumen, Russia. ¹⁷²Faculty of Earth Sciences and Spatial Management, Nicolaus Copernicus University, Toruń, Poland. ¹⁷³Faculty of Psychology, Universidad Cooperativa de Colombia, Medellín, Colombia.

¹⁷⁴Department of Political Sciences and Political Technologies, al-Farabi Kazakh National University, Almaty, Kazakhstan. ¹⁷⁵Department of Psychology, University of Colorado, Colorado Springs, USA. ¹⁷⁶Center for Cognitive Archaeology, University of Colorado, Colorado Springs, USA. ¹⁷⁷Institute for Advanced Study in Toulouse (IAST), Toulouse, France. ¹⁷⁸Lyda Hill Institute or Human Resilience, University of Colorado, Colorado Springs, USA.

¹⁷⁹Psychology School, Universidad Católica Andrés Bello, Caracas, Venezuela. ¹⁸⁰Department of Behavioral Science and Technology, Universidad Simón Bolívar, Caracas, Venezuela. ¹⁸¹School of Archaeology and Anthropology, The Australian National University, Canberra, Australia. ¹⁸²Department of Psychology, Bursa Technical University, Bursa, Turkey. ¹⁸³School of Economics, University of Asia and the Pacific, Pasig, Philippines.

¹⁸⁴Department of Sociology & Anthropology, University of Nigeria, Nsukka, Nigeria. ¹⁸⁵Kultivating and Healing, KAHLE Journey, Kingston, Jamaica. ¹⁸⁶School of Psychology and Vision Sciences, University of Leicester, Leicester, United Kingdom. ¹⁸⁷Institute of Psychology, University College of Professional Education, Wrocław, Poland.

¹⁸⁸Departamento de Ciências Médicas, Universidade da Beira Interior, Covilhã, Portugal. e-mail: marta7kowal@gmail.com