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Record W2023743495 · doi:10.1177/1074840709331643

Men Family Caregivers' Experience of Nonsupportive Interactions

2009· article· en· W2023743495 on OpenAlexaff
Anne Neufeld, Kaysi Eastlick Kushner

Bibliographic record

VenueJournal of Family Nursing · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyDementiaFamily caregiversPerceptionThematic analysisSocial supportDevelopmental psychologyQualitative researchSocial psychologyGerontologyMedicineDiseaseNeuroscience

Abstract

fetched live from OpenAlex

Men's involvement as family caregivers has grown as the prevalence of dementia has increased. Men rely on support from others for caregiving but also experience nonsupportive interactions. The purpose of this ethnographic study of 34 men (24 spouses and 10 sons) caring for a relative with dementia, 5 assisting caregivers, and 15 professionals was to identify primary caregivers' perceptions of nonsupportive and supportive interactions in relationships with kin and friends as well as professionals. Thematic analysis of transcribed data generated from interviews, diaries, and focus group discussions revealed the nature of men's caregiving journeys, the characteristics of their social networks, and their expectations of supportive interactions. The nonsupportive interactions men caregivers experienced included a lack of orientation to the caregiving situation, an unsatisfactory linkage to support sources, insufficient support, and hurtful interactions. Information about nonsupportive interactions can sensitize kin and friends as well as professionals to the complexity of men's experience and potentially avoid unintended negative consequences of support efforts.

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)0.000
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.351
Teacher spread0.327 · 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

Citations36
Published2009
Admission routes1
Has abstractyes

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