Determinants of Sexual Health and Sexual Quality of Life after Cardiovascular Surgeries: An Integrative Review
Bibliographic record
Abstract
BACKGROUND AND AIM: Sexual health and sexual quality of life are key components of psychosocial adjustment after cardiac surgeries and are often linked with improving the general quality of life. Reviews have been conducted to highlight the associations between cardiovascular diseases and sexual dysfunctions, but no review reported determinants of sexual health and sexual quality of life in patients after cardiovascular surgeries. We aimed to comprehensively examine the determinants of sexual health and sexual quality of life among individuals with cardiovascular surgeries. METHODS: Literature was searched within PubMed, CINAHL, Scopus, Web of Science, and OVID databases. In total, 816 records were identified from database searches, 279 records were screened, and 11 empirical studies were included for review. Relevant data were extracted using literature summary tables and synthesised using an inductive approach. RESULTS: The core determinants of sexual health and sexual quality of life were type of surgery and comorbidities, fears and uncertainties regarding sexual activity, sexual health education and counselling, spousal relationship and communication, and demographic factors such as advanced age and literacy levels. Major surgeries performed were coronary artery bypass grafting (CABG) and heart valve surgeries. The data collection tools used to collect data for sexual health and sexual quality of life were the International Erectile Function Questionnaire (IEFQ), International Index of Erectile Function (IIEF), Female Sexual Function Index (FSFI), Sexual Knowledge CABG Scale (SKS-CABG), Sexual Quality of Life Questionnaire (SQOL), SKS-Myocardial Infarction Scale (SKS-MI), and Couple Communication Scale (CCS). CONCLUSIONS: Despite their importance, sexual health and quality of life are frequently overlooked during patient rehabilitation after cardiovascular surgeries. The lack of adequate education and counselling from healthcare professionals frequently leads to increased fear and uncertainties among individuals and their partners. Therefore, more person-centred educational and counselling approaches should be developed to address the sexual concerns of individuals and their partners.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".