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Prenatal education for mothers with disabilities

2000· article· en· W2087968701 on OpenAlexafffundabout
Karen A. Blackford, Heather Richardson, S Grieve

Bibliographic record

VenueJournal of Advanced Nursing · 2000
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsLaurentian UniversityCanadian Mennonite UniversityCanadian Centre on Disability StudiesCanadian Science Centre for Human and Animal Health
FundersUniversity of British Columbia
KeywordsNursingExploratory researchPrenatal careVariety (cybernetics)MedicineQualitative researchContent analysisPregnancyPsychologyFamily medicinePopulation

Abstract

fetched live from OpenAlex

Prenatal nurse educators are well prepared to meet the learning needs of many expectant mothers. But how prepared are they to meet the learning needs of mothers with disabilities? To answer this question, eight mothers with various chronic illnesses located in north-eastern Ontario, Canada were asked to describe their maternity experiences. Given the small convenience sample and exploratory nature of the study, a qualitative content analysis was done. The mothers' reports described interaction with a variety of health professionals. This analysis focuses on findings specific to nurses who provide prenatal education. In general, mothers reported they had received insufficient, inappropriate information, especially about their pregnancy and chronic illnesses. The mothers thought that nurses doubted the ability of women with disabilities to be decision-makers or responsible and 'proper' mothers. Suggestions by disabled mothers for quality care in prenatal education are described. A more emancipatory approach to preparing nurses for practice as prenatal educators is recommended. Such an approach can reduce the barriers associated with power differences between women with disabilities as 'learners' and their nurse 'teachers'.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.389
Teacher spread0.362 · 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 designOther design
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

Citations55
Published2000
Admission routes3
Has abstractyes

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