Patterns of Sexuality, Adjustment to Aging and Satisfaction with Life: A Cluster Analysis of Adults Across the Lifespan
Bibliographic record
Abstract
Abstract Sexual satisfaction, adjustment to aging, and satisfaction with life are relevant dimensions of overall well-being across the life cycle. Through cluster analysis procedures, this study aims to describe the specific profile of adjustment to aging, sexual satisfaction and satisfaction with life of adults across the life span. This cross-sectional study involved a community-based sample of 619 Portuguese individuals, aged between 18 and 92 years old (M = 47.53 SD = 18.34) evaluated using a two-step cluster analysis. Fours clusters emerged. The most adjusted participants were mostly of a younger age, women and had a high education. The least adjusted participants globally presented low education, poor perceived health, and poor engagement in leisure activities. Well-being focused participants were mostly women of older age, with high education and spirituality. Finally, moderately satisfied participants were mostly men of older age, had a lower education, and presented poor reported health. Complementary comparative analysis among the identified subgroups was performed. The most adjusted participants had the highest perceived overall sexual well-being, sexual attractiveness, sexual openness and communication, and sexual satisfaction. These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed a combining adjustment to aging, satisfaction with life and sexual satisfaction for tailored interventions to the specific needs of populations across the lifespan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".