Fathers' Involvement in the Developmental Care of Their Preterm Newborns and its Impact on the Bonding and Self-Efficacy: A Nonrandomized Clinical Trial
Bibliographic record
Abstract
Background: Premature birth and postpartum hospitalization can hurt the father-newborn bonding and self-efficacy.Aim: This study aimed to investigate the effect of fathers' involvement in premature newborns care on paternal-infant bonding and self-efficacy.Method: This nonrandomized clinical trial was conducted on 80 fathers of hospitalized newborns in the Neonatal Intensive Care Unit at Arash Hospital, Tehran University of Medical Sciences, Tehran, Iran, 2017. The samples were selected by the convenience sampling method and divided into two groups. Pre- and post-intervention outcomes were collected using the Parent-Infant Bonding Scale (originally the Mother-Infant Bonding Scale) and the Perceived Maternal Parenting Self-Efficacy tool. The gathered data were analyzed using independent t-test, paired t-test, repeated-measures ANOVA.Results: The mean±SD of the scores of the bonding score was reduced by 2.3±2.17 in the Control group and 5.27±2. 57 in the intervention group. A lower score represented a better bonding. The self-efficacy score increased in both groups; however, it was significantly higher in the intervention group, which was increased by 8.85±5.046, compared to 1.27±3.31 in the Control group.Implications for Practice: Developmental care by fathers can improve the father-infant bonding and increase the paternal self-efficacy for the care of the high-risk newborn.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".