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Record W2153794718 · doi:10.1177/1049732307313768

Advocacy of Women Family Caregivers: Response to Nonsupportive Interactions With Professionals

2008· article· en· W2153794718 on OpenAlexaff
Anne Neufeld, Margaret J. Harrison, Moira Stewart, Karen D. Hughes

Bibliographic record

VenueQualitative Health Research · 2008
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyFeelingThematic analysisNegotiationMental healthQualitative researchHealth professionalsService providerService (business)Social psychologyHealth carePsychotherapistSociology

Abstract

fetched live from OpenAlex

Support from health and social service professionals assists women in caring for a relative with a chronic condition. However, nonsupportive interactions coexist with supportive interactions and might have unanticipated consequences. The purpose of this ethnographic study was to examine advocacy as a proactive response to nonsupportive interactions with professionals among women family caregivers in four caregiving situations. Data generation included in-depth interviews with 34 women. Interviews were tape-recorded, transcribed verbatim, and analyzed using thematic and constant comparative analysis techniques. As a consequence of nonsupportive interactions women experienced negative feelings, a lack of trust, powerlessness, and challenges in their caregiving situations that were catalysts for advocacy involving assertively taking charge in a relationship with a health professional. As advocates women employed strategies of monitoring their relative's condition, educating themselves or others, negotiating or fighting for resources, or campaigning for change. There were stress and fatigue involved in becoming an advocate, but the women also described the experience as one of personal growth. This research provided insight into the role of nonsupportive interactions with professionals as a catalyst for the development of individual-level advocacy initiatives.

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)0.023
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.725
GPT teacher head0.670
Teacher spread0.055 · 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.

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

Citations34
Published2008
Admission routes1
Has abstractyes

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