A Qualitative Exploration of Factors That Affect Sexual Desire Among Men Aged 30 to 65 in Long-Term Relationships
Bibliographic record
Abstract
Few empirical studies have explored men's experiences of sexual desire, particularly in the context of long-term relationships. The objective of the current study was to investigate the factors that elicit and inhibit men's sexual desire. Semistructured interviews were conducted with 30 men between the ages of 30 and 65 (average age 42.83 years) currently in long-term heterosexual relationships (average duration 13 years 4 months). Analysis was conducted using grounded theory methodology from the interpretivist perspective. A total of 14 themes and 23 subthemes were identified to capture men's descriptions of eliciting and inhibiting factors of their sexual desire. The six most integral themes are presented in the current article, all of which reflect the perspectives of the majority of participants, regardless of age or relationship duration, specifically (a) feeling desired, (b) exciting and unexpected sexual encounters, (c) intimate communication, (d) rejection, (e) physical ailments and negative health characteristics, and (f) lack of emotional connection with partner. The findings suggest that men's sexual desire may be more complex and relational than previous research suggests. Implications for researchers and therapists are discussed.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".