Association of Depression and Resilience with Fertility Quality of Life among patients presenting to the infertility Centre for treatment in Karachi, Pakistan
Bibliographic record
Abstract
Abstract Background In Pakistan there is dire need to explore the quality of life among infertile males and females and their undesirable psychological outcomes. Thus, the aim of this study was; 1. To compare the QoL of males and females presenting to the infertility centre for treatment, 2. To assess the association of QoL with resilience, depression and other soico-demographic factors among males and females presenting to infertility clinic for treatment Methods An Analytical Cross Sectional study was conducted and study participants were recruited from Australian Concept Infertility Medical Center Karachi (ACIMC) Pakistan. A non-probability (purposive) sampling strategy was used to recruit the participants. The sample size was 668. Data was analyzed using STATA version 12. Results After adjusting for the covariates we observed that males who were less resilient their QoL was 8.47 units significantly lower and those who were depressed their QoL was 17.849 units significantly lower as compared to their counterparts. . Formal education, low monthly income and friends were significantly associated with QoL among males . Similarly, females who were less resilient their QoL was 8.606 units lower and those who were depressed their QoL was 19.387 units significantly lower as compared to their counterparts.. Formal education and low monthly income had a significant association with QoL among females.Conclusion Fertility related QoL of men and women has a significant association with no formal education, number of friends, income, depression and resilience. Therefore, health care professionals in the field of infertility must be adequately trained to respond to the needs of individuals going through these psychological problems.
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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 | 0.001 | 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".