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Record W4362558527 · doi:10.3390/healthcare11071026

Assisted Reproductive Treatments, Quality of Life, and Alexithymia in Couples

2023· article· en· W4362558527 on OpenAlexaboutno aff
Alessia Renzi, Fabiola Fedele, Michela Di Trani

Bibliographic record

VenueHealthcare · 2023
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaSpouseQuality of life (healthcare)PsychologyFertilityPsychological interventionAffect (linguistics)InfertilityClinical psychologyPromotion (chess)Developmental psychologyMedicinePsychiatryPregnancyPsychotherapistPopulationEnvironmental health

Abstract

fetched live from OpenAlex

Infertility and related treatments can negatively affect a couple's wellbeing. The aim of this study was to evaluate couples starting assisted reproductive treatment, differences in alexithymia and quality of life levels between partners, and the association of these psychological dimensions within the couple's members. Data was collected in two fertility centres in Rome; 47 couples completed the Fertility Quality of Life (FertiQoL), the 20-item Toronto Alexithymia Scale (TAS-20), and a socio-demographic questionnaire. Data analysis showed a worsened quality of life in women compared with their partners, as well as higher externally oriented thinking in men compared with their spouses. Associations between alexithymia and quality of life levels between women and men emerged. According to the regression analysis, a better quality of life in women was predicted by a greater partner's capabilities in identifying and describing emotion as well as by a better partner's quality of life, whereas for men, a better quality of life was predicted by their spouse's higher levels of quality of life. This study highlights the protective role that couples can play in the perception of the negative impact that infertility can have on their partner's quality of life. Further investigations are needed for the development of specific therapeutic interventions for the promotion of the couples' wellbeing.

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)0.002
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 score0.029
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.152
GPT teacher head0.418
Teacher spread0.266 · 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

Citations17
Published2023
Admission routes1
Has abstractyes

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