Assessment Scales, Associated Factors and the Quality of Life Score in Pregnant Women in Iran
Bibliographic record
Abstract
Women experience physical, chemical, endocrine gland and organ changes during pregnancy that limit their activities and reduce their quality of life. The present study was conducted to investigate the quality of life in pregnant women in Iran, the assessment scales used to measure this variable and the factors associated with it. The present study searched databases including Science Direct, PubMed, Scopus, SID, Iranmedex, Mahiran, IranDoc and Google Scholar using keywords such as pregnant women, Iran, quality of life, pregnancy and prenatal and their Persian equivalents to find relevant articles conducted in Iran and ultimately found 20 articles to review without any regard for their time, language and publication site. Studies conducted in Iran to assess the quality of life in pregnant women have used four tools, including the SF-36, the WHOQOL-BRIEF, the SF-12 and the Nausea and Vomiting of Pregnancy-Specific Health-Related Quality of Life Questionnaire. The mean quality of life score obtained using these different tools varied from 61.18±13.21 to 66.48±15.57. Social support, socioeconomic status, the pregnancy being wanted, satisfaction with life and sexual function were related directly to the quality of life, while prenatal mental disorders, the severity of pregnancy nausea and vomiting and sleep disorders were related inversely to it. Given the lack of a specific tool designed to assess the quality of life in pregnant women, general tools were used for its assessment. Further studies are thus required to design a specific localized tool and to also assess the relationship between the quality of life and its associated factors.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".