MétaCan
Menu
Back to cohort
Record W4319068171 · doi:10.1080/07399332.2023.2172412

Pathways to social support: IVF patients’ motivation toward peers and selection preferences

2023· article· en· W4319068171 on OpenAlexaff
Natalie Dimitra Montgomery, Jenepher Lennox Terrion

Bibliographic record

VenueHealth Care For Women International · 2023
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversity of OttawaPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsPeer supportSocial supportInfertilityPeer reviewPsychologyTransparency (behavior)Social psychologyPeer groupMedicineDevelopmental psychologyClinical psychologyPsychiatryPregnancyPolitical scienceComputer scienceComputer security

Abstract

fetched live from OpenAlex

Infertility rates are increasing internationally, and its treatment, in-vitro fertilization (IVF) imposes stress on women as primary patients. In this study, led by a researcher with lived experience in infertility, we seek to uncover the pathways that lead IVF patients toward peer support; mainly what precipitates patients' decisions to seek peer support and how they select their peer. Having interviewed 23 IVF patients, we found that prior to disclosing to a peer, women reflect on information about their condition and their personal support needs and reconcile support gaps within their couple and social circles as they gauge their personal motivation to seek peer support. The demands of IVF compel patients to gravitate toward other women with shared experience. Prior to disclosure, patients consider diverse points of connection as well as desirable peer traits including previous IVF experience, other common ground and full transparency in a peer's communication style.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.340

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)0.0000.000

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 head0.055
GPT teacher head0.345
Teacher spread0.290 · 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 designObservational
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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHealth Care For Women InternationalSame topicReproductive Health and TechnologiesFrench-language works237,207