Knowledge, attitudes, and practices of patients with diminished ovarian reserve regarding traditional Chinese medicine treatment: structural equation modelling analysis

This study assessed the knowledge, attitudes, and practices (KAP) of patients with diminished ovarian reserve (DOR) regarding Traditional Chinese medicine (TCM) treatments. A cross-sectional study was conducted from November 2023 to August 2024 among patients with DOR to assess their KAP regarding TCM treatments. Data on characteristics and KAP scores were collected via a self-designed questionnaire. Structural equation modelling (SEM) was employed to assess the relationships among the KAP dimensions. A total of 439 valid responses from patients with DOR were included in the final analysis (effective response rate 82.2%). Patients with DOR had a moderate level of knowledge (median [IQR]: 7.00 [5.00–8.00]), generally positive attitudes (median [IQR]: 27.00 [25.00–28.00]), and suboptimal practices (median [IQR]: 31.00 [28.00–33.00]). SEM showed that knowledge had a direct effect on attitude (β = 0.183, P < 0.001) and practice (β = 0.199, P < 0.001), attitude had a direct effect on practice (β = 0.267, P < 0.001), and knowledge indirectly affected practice through attitude (β = 0.049, P = 0.001). Patients with DOR had inadequate TCM knowledge but positive attitudes. Low practice engagement highlights a need for better education to convert attitudes into effective TCM use for managing ovarian decline.

Authors

Institutions

Publication Details

Journal
Human Fertility
Published
2026-10-15
DOI
https://doi.org/10.1080/14647273.2026.2741540
Primary Topic
Complementary and Alternative Medicine Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Knowledge, attitudes, and practices of patients with diminished ovarian reserve regarding traditional Chinese medicine treatment: structural equation modelling analysis

Juan Zheng, Jiali CAI, Jingzhen Hong, Fan Jiang et al.
Human Fertility
Complementary and Alternative Medicine Studies
article

Knowledge, attitudes, and practices of patients with diminished ovarian reserve regarding traditional Chinese medicine treatment: structural equation modelling analysis

Juan Zheng, Jiali CAI, Jingzhen Hong, Fan Jiang, Lin Su
article en

Abstract

This study assessed the knowledge, attitudes, and practices (KAP) of patients with diminished ovarian reserve (DOR) regarding Traditional Chinese medicine (TCM) treatments. A cross-sectional study was conducted from November 2023 to August 2024 among patients with DOR to assess their KAP regarding TCM treatments. Data on characteristics and KAP scores were collected via a self-designed questionnaire. Structural equation modelling (SEM) was employed to assess the relationships among the KAP dimensions. A total of 439 valid responses from patients with DOR were included in the final analysis (effective response rate 82.2%). Patients with DOR had a moderate level of knowledge (median [IQR]: 7.00 [5.00–8.00]), generally positive attitudes (median [IQR]: 27.00 [25.00–28.00]), and suboptimal practices (median [IQR]: 31.00 [28.00–33.00]). SEM showed that knowledge had a direct effect on attitude (β = 0.183, P < 0.001) and practice (β = 0.199, P < 0.001), attitude had a direct effect on practice (β = 0.267, P < 0.001), and knowledge indirectly affected practice through attitude (β = 0.049, P = 0.001). Patients with DOR had inadequate TCM knowledge but positive attitudes. Low practice engagement highlights a need for better education to convert attitudes into effective TCM use for managing ovarian decline.

Human FertilityVol. 29(1)
Xiamen University (CN), Zhangzhou Municipal Hospital of Fujian Province (CN)
Good health and well-being
Openalex Percentile: Top 9%
Complementary and Alternative Medicine Studies
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.