Exploring the Psychological Well-being of Stay-at-Home Fathers
Bibliographic record
Abstract
This study aims to explore the psychological well-being of stay-at-home fathers (SAHFs), focusing on their self-identity and role perception, the challenges they face, and the coping mechanisms they employ. A qualitative research design was employed, utilizing semi-structured interviews to gather data from 24 SAHFs. Participants were selected through purposive sampling to ensure a diverse representation. The interviews were conducted either in-person or via video conferencing, lasting between 45 to 90 minutes. Data were transcribed verbatim and analyzed using NVivo software. Thematic analysis was used to identify key themes and patterns in the data, providing an in-depth understanding of the participants' experiences. The study identified three main themes: Identity and Role Perception, Challenges and Coping Mechanisms, and Social Support and Relationships. SAHFs experienced significant shifts in self-identity, moving from career-focused to fatherhood-centered roles. They faced various emotional challenges, including stress, anxiety, and social isolation, exacerbated by time management and financial pressures. Social support from spouses, peers, and community involvement played a crucial role in mitigating these challenges. The importance of robust support networks and community engagement was underscored, highlighting the need for tailored interventions to enhance the well-being of SAHFs. The psychological well-being of SAHFs is influenced by a complex interplay of identity shifts, societal perceptions, and the challenges of managing daily responsibilities. Social support emerges as a critical factor in promoting mental health and reducing feelings of isolation. This study contributes to the understanding of SAHFs' experiences and underscores the need for targeted support systems and policies to address their unique challenges. Future research should expand on these findings with larger, more diverse samples and explore the long-term impacts of being a SAHF.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".