Examining Factor Structure and Validating the Persian Version of the Pregnancy's Worries and Stress Questionnaire for Pregnant Iranian Women
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Pregnant women tend to experience anxiety and stress when faced with the changes to their biology, environment and personal relationships. The identification of these factors and the prevention of their side effects are vital for both mother and fetus. The present study was conducted to validate and to examine the factor structure of the Persian version of the Pregnancy's Worries and Stress Questionnaire. MATERIALS AND METHODS: The 25-item PWSQ was first translated by specialists into Persian. The questionnaire's validity was determined using face, content, criterion and construct validity and reliability of questionnaire was examined using Cronbach's alpha. Confirmatory factor analysis was performed in AMOS and SPSS 21. Participants included healthy Iranian pregnant women (8-39 weeks) who refer to selected hospitals for prenatal care. Hospitals included private, social security and university hospitals and selected through the random cluster sampling method. FINDINGS: The results of validity and reliability assessments of the questionnaire were acceptable. Cronbach's alpha calculated showed a high internal consistency of 0.89. The confirmatory factor analysis using the c2, CMIN/DF, IFI, CFI, NFI and NNFI indexes showed the 6-factor model to be the best fitted model for explaining the data. CONCLUSION: The questionnaire was translated into Persian to examine stress and worry specific to Iranian pregnant women. The psychometric results showed that the questionnaire is suitable for identifying Iranian pregnant women with pregnancy-related stress.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".