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Record W4411230415 · doi:10.1177/1097184x251351628

Reimagining Caregiving Roles and Challenging Gender Norms: A Husband’s Experience with Caring for Wife Living with Dementia

2025· article· en· W4411230415 on OpenAlexafffund
Shreemouna Gurung, Katherine Bertoni, Lucy Kervin, Kishore Seetharaman, Koushambhi Basu Khan, Jennifer Baumbusch

Bibliographic record

VenueMen and Masculinities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsUniversity of British ColumbiaUniversity of VictoriaSimon Fraser University
FundersCanadian Institutes of Health Research
KeywordsWifePsychologyDementiaGender studiesDevelopmental psychologyGerontologySocial psychologySociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

Spousal care is a prominent support for persons living with dementia, yet the experiences of men who provide spousal care are understudied. This research explored the experiences of husbands caring for wives with progressive dementia in a community setting. In this paper, the experience of a 63-year-old retired man caring for his wife diagnosed with early onset dementia was explored using a longitudinal qualitative case study approach. Reflexive thematic analysis of interview and narrative diary data produced two themes: (1) The Practical Realities of Caregiving, underscoring the everyday challenges of caregiving and (2) The Emotional Landscape of Caregiving, highlighting the complex emotional journey of caregivers. Findings emphasize the emotional challenges faced by men caregivers and highlight the need for supports that are tailored to men's unique experiences and emotional needs.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.011
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.267
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes2
Has abstractyes

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