Postpartum Depression Experience Among Jordanian Mother With Hospitalized Infant in Neonatal Intensive Care Unit: Incidence and Associated Factors
Bibliographic record
Abstract
Postpartum depression (PPD) is a global mental health problem that affects about 13% to 19% of mothers who have recent given birth. This problem increases if the infant is admitted to the intensive care unit (NICU). The aims of this study were to examine the prevalence and risk factors of postpartum depression among mothers with hospitalized infant on NICU and to explore mothers experience after admitting their infants to the NICU. A varied methods research design were undertaken in two hospitals in Jordan. The Edinburgh Postpartum Depression Scale (EPDS) was used to survey 188 Jordanian mothers with infants in the NICU, it deals with semi-structured in-depth interviews to identify the themes that characterize mothers PPD experience in the NICU. The quantitative results of this study showed that the mothers with hospitalized infant in NICU experienced high level of PPD with the mean score was 20.81 (SD = 4.92). With regard to qualitative results, two major themes with nine subthemes : the first one is Postpartum Depression Experience and the second theme was sources that influence postpartum depression. In conclusion, the mothers with hospitalized infant in NICU experience PPD. the PPD mothers experience many manifestations during this situation such as : shock, surprise, crying, Anhedonia,hopelessness and thinking about harming themselves or their babies after admission of their infants to the NICU, Also there are many sources that influence postpartum depression such as baby gender, lack of knowledge, social support, mother role, mother infant attachment, stigma and shame.
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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 | 0.000 |
| 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) | 0.001 | 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".