The Forgotten Caregivers: A Qualitative Study Exploring the Experiences of Fathers of Children With Medical Complexity
Bibliographic record
Abstract
AIM(S): To explore the caregiving experiences and support needs of fathers of children with medical complexity in Canada. DESIGN: A qualitative study guided by interpretive description methodology and informed by a Gender-Based Analysis Plus (GBA+) lens. METHODS: Data were collected through 60-min semi-structured interviews with seven fathers of children with medical complexity and analyzed using thematic analysis. The study followed the COREQ guidelines and checklist. RESULTS: Thematic analysis identified fathers' key roles as financial providers, hands-on caregivers, and as playing a key role in supporting their partners emotionally with the challenges of caregiving. Fathers prioritised the need for peer support, flexible workplace policies and improved access to mental health services. CONCLUSION: The findings indicate that there is a critical need for more inclusive and flexible support systems and workplace policies that acknowledge and accommodate the important caregiving roles of fathers of children with medical complexity. RELEVANCE TO CLINICAL PRACTICE: The implications for healthcare professionals include actively involving fathers in care planning and providing targeted support services that recognise their roles to enhance child and family outcomes. PATIENT OR PUBLIC CONTRIBUTION: We worked closely with our community advisory team, comprised of a physician, social worker and community organisation leader, who contributed to the study design, supported participant recruitment, and assisted in disseminating the findings back to the community, helping to ensure the research was grounded in and responsive to the needs of families of children with medical complexity.
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".