MétaCan
Menu
Back to cohort
Record W4387358223 · doi:10.1210/jendso/bvad114.1611

FRI418 A 6-month Lifestyle Intervention Program Improves Quality Of Life And Motivation In Women With Obesity And Infertility

2023· article· en· W4387358223 on OpenAlexaff
Kathryne Brûlé, Alexandra Thibodeau, Daniel Maillet, Matea Bélan, Farrah Jean-Denis, Marie-Hélène Pesant, Belina Carranza‐Mamane, Jean‐Patrice Baillargeon

Bibliographic record

VenueJournal of the Endocrine Society · 2023
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsFertilityInfertilityMedicineObesityBody mass indexQuality of life (healthcare)Intervention (counseling)Polycystic ovaryGynecologyPregnancyPhysical therapyGerontologyPopulationEnvironmental healthInternal medicineNursing

Abstract

fetched live from OpenAlex

Abstract Disclosure: K. Brûlé: None. A. Thibodeau: None. D. Maillet: None. M. Belan: None. F. Jean-Denis: None. M. Pesant: None. B. Carranza-Mamane: None. J. Baillargeon: Grant Recipient; Self; Ferring Pharmaceuticals. Introduction Infertility is the incapacity to conceive after 12 months of regular and unprotected sexual intercourse, affecting 11 to 16% of couples. Obesity affects fertility, increases fertility treatment costs, diminishes their efficacy, predisposes to many complications during pregnancy and presents risks for the offspring. To prevent those consequences, many organizations recommend that women with obesity be assisted in adopting healthy lifestyle habits before conception and maintain them during pregnancy. Also, women with infertility and those living with obesity score lower on the quality of life (QoL) scales. Therefore, our objective was to assess the impact of a lifestyle intervention on QoL and stages of change (based on the transtheoretical model) in women with obesity and seeking fertility treatments. Methods Women 18-40 years old with infertility and obesity (body mass index (BMI) ≥ 30 kg/m2 or BMI ≥ 27 kg/m2 for those with polycystic ovary syndrome), consulting at the fertility clinic of an academic center, were enrolled and randomized to usual fertility care (control group, CG) or the intervention program (lifestyle group, LSG) alone for 6 months and then combined to usual care. The lifestyle program focused on improving physical activity and nutrition and was based on motivational communication. It involved individual follow-ups with a nutritionist and a kinesiologist at weeks 0, 3, 6 and then every 6 weeks for 18 months. Also, participants needed to attend 12 group sessions, including workshops and physical activities. QoL scores from the SF-6D and FertiQol, levels of conviction (visual analog scales on 100), and stages of change were collected at baseline and at 6 months. Proportions were compared by Pearson chi-square tests and means by Student’s t tests or ANCOVA (correcting for the baseline value of the result). Results Among 127 women, 85 had available data at 6 months (CG=43, LSG=42). After 6 months, and compared to the CG, women in the LSG improved more their SF-6D (+0.029 ± 0.076 vs -0.017 ± 0.082, p = 0.009, p ANCOVA <0.001) and FertiQoL total score (+0.35 ± 6.85 vs -2.70 ± 11.80, p = 0.18, p ANCOVA = 0.02). A higher proportion of women in LSG improved their stage of change by ≥2 categories compared to CG (40.0% vs 13.2%, p=0.008). They better maintained their level of conviction about the need to improve their food habits (+4.0 ± 13.4 vs -2.7 ± 17.7, p ANCOVA=0.02) or their physical activity (+2.5 ± 10.2 vs -5.1 ± 13.8, p=0.006, p ANCOVA=0.01). Conclusion A lifestyle program targeting women with obesity and infertility significantly helped maintain or increase their QoL, levels of conviction for food habits and physical activity, and stages of change regarding lifestyle habits compared to usual fertility care. These results suggest that such lifestyle intervention can contribute to the well-being and maintenance of lifestyle changes in women with obesity who seek fertility treatments. Presentation: Friday, June 16, 2023

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)0.001
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 score0.009
Threshold uncertainty score0.172

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.018
GPT teacher head0.298
Teacher spread0.280 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Endocrine SocietySame topicOvarian function and disordersFrench-language works237,207