Predictors of sexual satisfaction among Social Security and National Insurance Trust pensioners in the Greater Accra Region of Ghana
Bibliographic record
Abstract
The population of pensioners remains on the rise in Ghana coupled with an intrinsic need for sexual activity and satisfaction. However, data on factors associated with sexual satisfaction among pensioners are limited in Ghana. The aim of this study was to examine the predictors of sexual satisfaction among Social Security and National Insurance Trust pensioners in the Greater Accra Region of Ghana. We employed a cross-sectional survey design in this study. Participants were recruited using cluster and stratified sampling techniques. Our analytical sample was 410 participants. Ordinal logistic regressions were employed to determine predictors of sexual satisfaction among the participants. The significance of the test was set at a p-value ≤ 0.05. The results showed that participants who were household head (AOR: 1.874, 95% CI: 1.037-3.388), who did not incur any expenditure on their household in a month (AOR: 6.290, 95% CI: 1.758-22.511) and those who undertake daily exercises were significantly (AOR: 1.981, 95% CI: 1.276-3.075) more likely to fall in one of the higher categories of sexual satisfaction compared to their counterparts. Also, the study revealed that those with secondary education (AOR:.503, 95% CI:.253-.0.999), who were in the public sector (AOR:.449, 95% CI:.237 -.850), who were very dissatisfied with health service access/use (AOR:.032, 95% CI:.002-.421) and not able to determine whether they were satisfied or dissatisfied with their health status (AOR:.518, 95% CI:.329-.816) were significantly less likely to fall in one of the higher categories of sexual satisfaction. Findings of this study suggest that household headship, education level, employment sector, expenditure on household, satisfaction with health services/use, daily exercises intake and satisfaction with health status were associated with sexual satisfaction among the participants. In relation to our findings, the implications for policy, practice and future research have been discussed for the attention of policy makers and researchers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".