Cross-cultural Validation of the Arizona Sexual Experience Scale (ASEX) in 42 Countries and 26 Languages
Bibliographic record
Abstract
Abstract Introduction The Arizona Sexual Experiences Scale (ASEX) is a brief questionnaire that evaluates five major aspects of sexual function: sex drive, arousal, erectile function/vaginal lubrication, ability to reach orgasm, and satisfaction with orgasm. An advantage of the ASEX is its simplicity and brevity (five items), making it suitable for the screening of sexual function problems in healthcare contexts and large-scale studies. The main objective of this study was to examine the psychometric properties of the ASEX in a multi-national sample, as well as to explore sexual function according to countries, genders, and sexual orientations. Methods The psychometric examination of the ASEX was conducted with a sample of 82,243 participants (women = 57.02%; men = 39.59%; gender-diverse = 3.38%; M age = 32.39 years; SD = 12.52) from 42 different countries speaking 26 languages. Results The CFA supported a one-factor solution. Multigroup CFAs supported configural, metric, partial scalar, and residual invariance across countries, languages, genders, and sexual orientations. Furthermore, the ASEX showed good internal consistency (ω = .85) and convergent validity (e.g., significant negative associations with masturbation and sexual intercourse frequency). Finally, individuals in Eastern countries, women, and asexual participants reported higher levels of sexual function issues. Conclusions and Policy Implications The findings supported the use of the ASEX as a tool to screen for sexual function problems across diverse populations in multi-cultural settings. This scale may be used to improve our knowledge on the cross-cultural differences on the expression of sexual function, serving as the basis for the development of culturally tailored interventions for the improvement of this basic aspect of well-being.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".