MétaCan
Menu
Back to cohort
Record W4392468322 · doi:10.5539/ijps.v16n2p1

The Lived Experience of Seeking Pregnancy in a Woman with a History of Cancer

2024· article· en· W4392468322 on OpenAlexafffundvenue
Tsorng-Yeh Lee

Bibliographic record

VenueInternational Journal of Psychological Studies · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsYork University
FundersYork University
KeywordsPsychologyCancerPregnancyLived experienceDevelopmental psychologyPsychoanalysisMedicine

Abstract

fetched live from OpenAlex

Myelodysplastic syndromes (MDS) are a rare form of cancer that affects the bone marrow's ability to produce mature blood cells. Several treatments are available, including chemotherapy using anticancer or cytotoxic drugs, blood or platelet transfusions, and stem cell transplants. In this study, a 33-year-old woman shares her experience of attempting to conceive while undergoing treatment for myelodysplastic syndromes. The study aimed to explore the psychosocial difficulties women with a history of cancer treatment may encounter when trying to get pregnant. Semi-structured qualitative interviews were undertaken, recorded, and transcribed verbatim. The transcript was analyzed by narrative analysis. Four themes were identified: 1) Support from loved ones, 2) Challenges in conceiving, 3) Emotional ups and downs during pregnancy, and 4) The joy of motherhood. A cancer diagnosis can devastate young women, primarily if the treatment affects their fertility. These women must have the support of their husbands. Fortunately, many methods are available to assist women in successfully conceiving, although the journey can be difficult and emotional. The ups and downs of the process are inevitable, but the desire to become a mother makes it all worth it in the end. Cancer treatment for myelodysplastic syndromes and related conditions can profoundly impact childbearing women. Such women may face significant challenges if they plan to have a child after treatment. Hence, further research with more women with the diagnosis of MDS is imperative in this critical area.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.111

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 head0.137
GPT teacher head0.460
Teacher spread0.323 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Psychological StudiesSame topicCancer Risks and FactorsFrench-language works237,207