MétaCan
Menu
Back to cohort
Record W4416396281 · doi:10.1177/10748407251392877

“Fathers Are Not Mothers” Nurses’ Experiences of Practicing With Fathers When Providing Care to Their Children: A Qualitative Systematic Review

2025· article· en· W4416396281 on OpenAlexafffund
Francine de Montigny, Caroline René, Isabelle Landry, Anne Brødsgaard, Naiara Barros Polita, Cynthia A. Danford, Debbie Sheppard-LeMoine, Mari Ikeda, Lucila Castanheira Nascimento, Suja Somanadhan, Willyane de Andrade Alvarenga, Christine Gervais

Bibliographic record

VenueJournal of Family Nursing · 2025
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of WindsorUniversité du Québec à Trois-RivièresUniversité du Québec en Outaouais
FundersFonds de Recherche du Québec-Société et Culture
KeywordsThematic analysisQualitative researchInclusion (mineral)PerceptionIntervention (counseling)Qualitative property

Abstract

fetched live from OpenAlex

This qualitative review aims to synthesize the evidence on nurses' experience of intervening with fathers when providing care to their young children. Five databases were searched. Inclusion criteria were (a) nurses' experience, (b) intervention with fathers, (c) written in English or French. Data were extracted by two independent reviewers. Qualitative thematic synthesis of 17 peer-reviewed studies was performed by 12 family nurse researchers from six countries. Three analytical themes were identified: "Conceiving of the father's role in terms of his involvement within the family"; "Working with fathers based on the nurse's individual conception of the paternal role"; and "Developing a sense of efficacy in working with fathers." The results highlight the importance of raising family nurses' awareness of fathers' individual realities. Training in this regard makes it possible to modify nurses' perceptions of the paternal role and to promote the adoption of father inclusive practices within the family.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.384
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Family NursingSame topicMaternal Mental Health During Pregnancy and PostpartumFrench-language works237,207