Body shape concerns, sexual satisfaction, and associated factors among patients with polycystic ovarian syndrome

This study encourages healthcare providers to proactively query sexual apprehension among these patients. These findings may guide health caregivers, policymakers, and scholars in developing measures to improve the quality of life of women with PCOS.

Authors

Institutions

Publication Details

Journal
Saudi Medical Journal
Published
2025-01-01
DOI
https://doi.org/10.15537/smj.2025.46.1.20240797
Citations
3
Primary Topic
Sexual function and dysfunction studies
Type
article
Field-Weighted Citation Impact
4.41
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Body shape concerns, sexual satisfaction, and associated factors among patients with polycystic ovarian syndrome

Aseel Awad Alsaidan, Hani Hathath Alsulami, Ashokkumar Thirunavukkarasu
3 citations
Saudi Medical Journal
Sexual function and dysfunction studies
4.41
article

Body shape concerns, sexual satisfaction, and associated factors among patients with polycystic ovarian syndrome

Aseel Awad Alsaidan, Hani Hathath Alsulami, Ashokkumar Thirunavukkarasu
article en
3 citations

Abstract

This study encourages healthcare providers to proactively query sexual apprehension among these patients. These findings may guide health caregivers, policymakers, and scholars in developing measures to improve the quality of life of women with PCOS.

Saudi Medical JournalVol. 46(1)
Jouf University (SA), Maternity and Children's Hospital (SA)
Gender equality
Openalex Percentile: Top 7%
Sexual function and dysfunction studies
4.41
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.