Underneath the Sheets: a Cross-Cultural Cluster Analysis of Older Adults’ Patterns of Aging and Sexual Well-Being in Portugal and Mexico
Bibliographic record
Abstract
Abstract This study aims to assess the patterns of life satisfaction with life (SwL), sexual satisfaction, and adjustment to aging (AtA), of older adults in Mexico and Portugal. A sample of 658 older adults, aged 65 years-old and older, from Mexico and Portugal were recruited for this cross-cultural study. The following measures were applied: (a) Adjustment to Aging Scale (ATAS); (b) Satisfaction with Life Scale (SwLS); (c) New Sexual Satisfaction Scale (NSSS); (d) Mini-Mental State Exam; and (e) Sociodemographic, health and lifestyle questionnaire. Clusters were identified and characterized by using K-means cluster analysis, encompassing SwL, AtA, and sexual satisfaction. Sexual well-being differences among clusters were analyzed with One-way ANOVAs. Findings indicated three clusters, which explained 76.4% (R-sq = 0.764) of the total variance: Cluster #1: “Moderately adjusted older adults” (n = 355, 53.9%), Cluster #2: “Moderately fulfilled older adults” (n = 265, 40.3%), and Cluster 3: “Well adjusted and satisfied older adults” (n = 38, 5.8%). Participants in Cluster #1 were mostly Mexican, with moderate levels of AtA and reduced sexual satisfaction and SwL. Conversely, Cluster #2 predominantly consisted of Portuguese participants with moderate sexual satisfaction and SwL, and lower levels of AtA. Participants from Cluster #3 were mostly Portuguese with high levels of AtA, sexual satisfaction, and SwL. This innovative study explored the intricate relationship between sexual well-being, the ability to adjust to aging, and overall SwL, in two different cultural contexts. Findings contributed to the understanding of the relationship between these three variables and for developing tailored future interventions and service planning with older adults in different cultures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".