Fathers’ Involvement: Mothers’ Perceived Benefits of Promoting Paternal Involvement Through a WhatsApp-Based Preventive Intervention for Postpartum Depression
Bibliographic record
Abstract
Introduction: Despite the social and cultural changes of the recent decades, the tasks associated with childcare continue to be assumed mainly by women, increasing stress and, in some cases, negatively affecting maternal mental health. The “m-What were we thinking” (m-WWWT) intervention seeks to reduce the risk of developing postpartum depression and anxiety symptoms in women by increasing self-efficacy in caring for a newborn and perceived social support, with a special focus on the partner's role. The objective of this study was to describe the mothers’ perception of how this intervention facilitated the father's parenting involvement. Methods: Sixty-four text messages from 25 first-time mothers participating in the m-WWWT program were analyzed using the Grounded Theory open and axial coding criteria. Results: There are four subjective themes linked to fathers and parenthood. The first refers to the loss of the previous balance and increased stress with the arrival of the first child; the second, to the importance of watching the intervention videos together; the third, to the possibility of communicating regarding what is happening; and the fourth, to the shared conceptualization of parenting among the couples. Conclusion: These findings suggest that m-WWWT positively influences paternal involvement in the postpartum period, which is a relevant factor to promote maternal and infant well-being.
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 | 0.001 | 0.002 |
| 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) | 0.003 | 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".