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Record W4292059309 · doi:10.1177/0192513x221087724

Perceived Injustice and Psychological Well-Being in Couples Seeking Fertility Treatment

2022· article· en· W4292059309 on OpenAlexaff
Frédérique Bourget, Sawsane El Amiri, Audrey Brassard, Katherine Péloquin

Bibliographic record

VenueJournal of Family Issues · 2022
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversité de SherbrookeUniversité de Montréal
Fundersnot available
KeywordsInjusticeFertilityInfertilityPsychologyAnxietyDistressQuality of life (healthcare)Clinical psychologyMedicineSocial psychologyPsychiatryPsychotherapistPregnancyPopulation

Abstract

fetched live from OpenAlex

Infertility and its treatment are associated with a host of negative emotions, including perceived injustice. However, no quantitative study has examined the link between perceived injustice and psychological difficulties in couples seeking fertility treatment. This study examined the associations between perceived injustice and both partners’ psychological well-being and investigated possible differences in perceived injustice based on sex or cause of infertility. Both partners of 103 couples seeking fertility treatment completed the Injustice Experience Questionnaire—Infertility, the Hospital Anxiety and Depression Scale, and the Fertility Quality of Life Tool. Perceived injustice was associated with one’s own and one’s partner’s higher depressive symptoms and lower infertility-related quality of life, as well as one’s own higher anxiety symptoms. Women also perceived more injustice than men. The cause of infertility was unrelated to perceived injustice. Findings suggest that perceived injustice could represent an intervention target to reduce psychological distress in infertile couples.

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)0.001
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 score0.136
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.079
GPT teacher head0.390
Teacher spread0.311 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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