First-Time Father’s Risk Factors of Paternal Perinatal Psychological Distress: A Scoping Review
Bibliographic record
Abstract
Fathers can experience psychological distress during the paternal perinatal period. The effects of paternal perinatal psychological distress (PPPD) are multileveled. Little research is available about PPPD in first-time fathers. The purpose of this review is to explore the literature on risk factors contributing to PPPD in first-time fathers. The Arksey & O'Malley framework was used to guide this scoping review. The Population, Concept, and Context (PCC) framework was used for answering the review question "What evidence is available about factors contributing to PPPD in first-time fathers?" Five databases (CINAHL, EMBASE, MEDLINE, PsycINFO, and PubMed) were used to retrieve relevant, full-text, English references from January 01, 2020, to January 04, 2023. A data extraction tool was developed to identify risk factors assessed in the included studies. The Socio-Ecological Model (SEM) was used for analyzing the extracted data according to the four socio-ecological levels, i.e., individual, relationship, community, and societal. A total of 18 references reporting on 16 studies were included in the review. Fifty-six tools were used for assessing the risk factors contributing to PPPD in first-time fathers. Limited understanding was established about risk factors because tools lacked gender sensitivity. Risk factors aligned with 12 domains (e.g., psychological, relationship, social, and physical). Most domains corresponded with the individual level of SEM. Only two domains corresponded with the societal level of SEM. The literature indicates there are few studies about PPPD experienced by first-time fathers. This scoping review adds to the literature on the mental health care gaps for this population. Further research on measuring PPPD may improve individual and family functioning during the perinatal period.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".