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Record W1974365400 · doi:10.1515/jpm.2010.011

Preferences of caregiver when experiencing nausea and vomiting during pregnancy

2010· article· en· W1974365400 on OpenAlexaff
Alon Shrim, Boaz Weisz, L. Gindes, Mordechay Dulitzki, Benny Almog

Bibliographic record

VenueJournal of Perinatal Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineNauseaVomitingPregnancyObstetricsAnesthesia

Abstract

fetched live from OpenAlex

AIM: To assess the preferences of pregnant women regarding the type of assistance desired to alleviate the consequences of nausea and vomiting of pregnancy (NVP). METHODS: Women with NVP were asked to complete an online survey of 12 questions assessing the extent of NVP and the perspective on the importance of different healthcare professionals for their improvement. RESULTS: A total of 121 pregnant women completed the survey. The median maternal age was 29 years and the average gestational age was 12.4+/-7.6 weeks. Sixty-four of the women (52.9%) had NVP in their previous pregnancy, which resulted in an average of 14.6+/-21.1 lost days of paid work. NVP necessitated admission to the emergency room in 36 (29.7%). When asked to rate (max 4 points) which healthcare professional would provide the best assistance for NVP, the physician was rated as the most important (average score of 3.56/4), followed by dietician (3.40/4), nurse (3.05/4) and social worker/psychologist as least important (1.77/4). CONCLUSION: Our findings illustrate women's perspective on NVP. According to our online survey, women perceive medically- and nutritionally-based care as most useful, whereas psychosocial factors are perceived to be less useful despite playing a central role in NVP.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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 designBench or experimental
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

Citations2
Published2010
Admission routes1
Has abstractyes

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