Objective:To explore the status of psychological resilience in female infertility patients and analyze its influencing factors, providing a basis for developing effective intervention measures in clinical practice.Methods:A convenient sampling method was used to select female infertility patients who visited the Reproductive Medicine Center of the First Affiliated Hospital of the University of South China from March to October 2024 as the research objects. A cross-sectional survey was conducted using the General Data Questionnaire, Connor-Davidson Resilience Scale, Herth Hope Index, the Infertility Stigma Scale, Family Resilience Scale and Perceived Social Support Scale. The random forest algorithm was used to rank the importance of variables, Lasso regression was used to further screen variables, and the selected variables were included in multiple stepwise regression analysis to analyze the influencing factors.Results:Ultimately, 322 female infertility patients aged (30.40 ± 4.50) were included. The psychological resilience score was (64.29 ± 10.05) points, which was above the medium level. The top 6 influential factors in the importance of variables were stigma, family resilience, age, social support, infertility cause and hope level. Multiple stepwise regression analysis showed that age, infertility cause, hope level, stigma, family resilience and social support were the main influencing factors of mental resilience of female infertility patients ( t values were -8.32 to 6.85, all P<0.05). Conclusions:The psychological resilience of female infertility patients is above the medium level, and the psychological resilience of infertile women is affected by many factors such as individual characteristics, family environment and social support. Medical staff should take targeted intervention measures to improve the psychological resilience of female infertility patients.

Objective:To explore the status of psychological resilience in female infertility patients and analyze its influencing factors, providing a basis for developing effective intervention measures in clinical practice.Methods:A convenient sampling method was used to select female infertility patients who visited the Reproductive Medicine Center of the First Affiliated Hospital of the University of South China from March to October 2024 as the research objects. A cross-sectional survey was conducted using the General Data Questionnaire, Connor-Davidson Resilience Scale, Herth Hope Index, the Infertility Stigma Scale, Family Resilience Scale and Perceived Social Support Scale. The random forest algorithm was used to rank the importance of variables, Lasso regression was used to further screen variables, and the selected variables were included in multiple stepwise regression analysis to analyze the influencing factors.Results:Ultimately, 322 female infertility patients aged (30.40 ± 4.50) were included. The psychological resilience score was (64.29 ± 10.05) points, which was above the medium level. The top 6 influential factors in the importance of variables were stigma, family resilience, age, social support, infertility cause and hope level. Multiple stepwise regression analysis showed that age, infertility cause, hope level, stigma, family resilience and social support were the main influencing factors of mental resilience of female infertility patients ( t values were -8.32 to 6.85, all P<0.05). Conclusions:The psychological resilience of female infertility patients is above the medium level, and the psychological resilience of infertile women is affected by many factors such as individual characteristics, family environment and social support. Medical staff should take targeted intervention measures to improve the psychological resilience of female infertility patients.

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Objective:Based on the pathological model of acceptance and commitment therapy(ACT), to explore the correlation between cognitive fusion and resting-state spontaneous brain activity amplitude of low frequency fluctuation in patients with major depressive disorder(MDD).Methods:Patients with MDD ( n=19) and healthy controls (HCs, n=19)matched with gender, age, and years of education were enrolled from August 2022 to May 2023 in Hangzhou Seventh People's Hospital. 17-item Hamilton depression rating scale(HAMD-17) and cognitive fusion questionnaire(CFQ) were used to estimate the depressive symptoms and cognitive fusion of the participants. The amplitude of low frequency fluctuation(ALFF) data were collected on a 1.5 T-GE scanner. Based on DPABI v7.0 software of MATLAB 7.11.0 (R2018b), two independent sample t-test was used to compare the ALFF of the MDD group and HC group. ALFF values and the cognitive fusion scale scores were investigated by Pearson correlation analysis. Results:Compared with HCs, ALFF in patients with MDD was decreased relatively in the left triangular part of the inferior frontal gyrus(MNI: x, y, z=-36, 24, 21; t=-2.107, P=0.042), the right cuneus(CUN; MNI: x, y, z=12, -87, 24; t=-8.635, P<0.001) as well as the left calcarine fissure and surrounding cortex(MNI: x, y, z=-18, -57, 6; t=-14.188, P<0.001), while increased relatively in left superior occipital gyrus(MNI: x, y, z=-21, -72, 33; t=-7.253, P<0.001). There was a significant negative correlation between cognitive fusion and ALFF values of abnormal activity in left IFGtriang (belonging to ECN)( r=-0.57, P<0.05). Conclusion:There is a correlation between cognitive fusion and resting-state spontaneous brain activity ALFF in patients with MDD. Both cognitive fusion and depressive symptoms may affect patients' cognitive control deficits through multiple sources.

Objective:To investigate the protective effect of warning at different time points on eyewitness memory during repeated memory retrieval.Methods:A pilot test and artificial intelligence technology were used to develop a set of witness memory experiment procedures applicable to Chinese people. A total of 46 healthy participants were included in the pilot test and 101 healthy participants were included in the formal experiment. A mixed 3 (group of warning) ×4 (memory test time points) design was applied to this study and SPSS 23.0 software was used for data analysis.The memory of 101 healthy participants (33 in the pre-warning group, 30 in the no-warning group, and 38 in the post-warning group) using two-factor repeated measure ANOVA. The memory accuracy rate, memory misleading rate and confidence of the three groups in different memory test time points were taken as dependent variables, and the group of warning and the test time points were taken as independent variables to analyze the differences in memory among the groups in different test time points.Results:(1)In the early two repeated memory tests, the accuracy of memory in pre-warning group ((0.67±0.11), (0.67±0.12)) were significantly higher than those in no warning group ((0.58±0.15), (0.60±0.15)) (both P<0.05); at the third repeat memory test, the accuracy of post-warning group (0.63±0.12) and no warning group (0.60±0.13) were significantly lower than that of pre-warning group (0.69±0.12) (both P<0.05). (2)In the three repeated memory tests, the memory misleading rates of the pre-warning group (0.25(0.13, 0.38), 0.25(0.13, 0.38), 0.25(0.13, 0.38)) and the post-warning group (0.25(0.13, 0.38), 0.25(0.13, 0.38), 0.25(0.13, 0.38)) were significantly lower than those of the no warning group (0.63(0.34, 0.78), 0.63(0.34, 0.75), 0.63(0.25, 0.75)) (all P<0.05). (3)There were no significant difference in the answer confidence between any pair of groups at any corresponding memory test (both P>0.05). Conclusion:The protective effect of warning before misleading information is better than the warning after misleading information, and the protection of the two warnings are still working.