Objective:To analyze the development trajectory of sleep quality in patients with insomnia after cognitive behavioral therapy (CBT-I), and to explore the influencing factors of different development trajectories.Methods:A total of 418 patients with insomnia who received CBT-I at the Sleep Medicine Center of Xiamen Xianyue Hospital from February 2019 to June 2023 were recruited using convenience sampling. All patients completed the Pittsburgh sleep quality index (PSQI) at five time points: before CBT-I initiation (T1), at the end of treatment (T2), and at 3 months (T3), 6 months (T4), and 12 months (T5) post-treatment. At T1, all patients were evaluated by the insomnia severity index (ISI), Flinders fatigue scale (FFS), Beck depression inventory-Ⅱ (BDI-Ⅱ), Beck anxiety inventory (BAI), and dysfunctional beliefs and attitudes about sleep scale (DBAS). Latent class growth modeling (LCGM) was constructed and employed to analyze the development trajectories of sleep quality post-CBT-I using Mplus 8.0 software. Univariate analysis and Logistic regression analysis were conducted by SPSS 26.0 software to explore influencing factors of the sleep quality trajectories.Results:The PSQI scores of insomnia patients at T1, T2, T3, T4 and T5 were 15(12, 18), 8(6, 11), 5(3, 7), 5(3, 7) and 5(2, 7), respectively. Three distinct development trajectories were identified. Based on these trajectories, 418 patients were categorized into fluctuating development group ( n=44, 10.53%), slow improvement group ( n=193, 46.17%), and sustained improvement group ( n=181, 43.30%). Logistic regression analysis revealed that depressive symptom severity, anxiety symptom severity, family history of insomnia, and use of hypnotic medications were significant influencing factors for the sleep quality trajectories after CBT-I treatment (all P<0.05). Conclusion:The sleep quality of insomnia patients after CBT-I treatment shows different development trajectories, and its influencing factors are depression, anxiety, family history of insomnia and the use of hypnotic medications.

Objective:To analyze the development trajectory of sleep quality in patients with insomnia after cognitive behavioral therapy (CBT-I), and to explore the influencing factors of different development trajectories.Methods:A total of 418 patients with insomnia who received CBT-I at the Sleep Medicine Center of Xiamen Xianyue Hospital from February 2019 to June 2023 were recruited using convenience sampling. All patients completed the Pittsburgh sleep quality index (PSQI) at five time points: before CBT-I initiation (T1), at the end of treatment (T2), and at 3 months (T3), 6 months (T4), and 12 months (T5) post-treatment. At T1, all patients were evaluated by the insomnia severity index (ISI), Flinders fatigue scale (FFS), Beck depression inventory-Ⅱ (BDI-Ⅱ), Beck anxiety inventory (BAI), and dysfunctional beliefs and attitudes about sleep scale (DBAS). Latent class growth modeling (LCGM) was constructed and employed to analyze the development trajectories of sleep quality post-CBT-I using Mplus 8.0 software. Univariate analysis and Logistic regression analysis were conducted by SPSS 26.0 software to explore influencing factors of the sleep quality trajectories.Results:The PSQI scores of insomnia patients at T1, T2, T3, T4 and T5 were 15(12, 18), 8(6, 11), 5(3, 7), 5(3, 7) and 5(2, 7), respectively. Three distinct development trajectories were identified. Based on these trajectories, 418 patients were categorized into fluctuating development group ( n=44, 10.53%), slow improvement group ( n=193, 46.17%), and sustained improvement group ( n=181, 43.30%). Logistic regression analysis revealed that depressive symptom severity, anxiety symptom severity, family history of insomnia, and use of hypnotic medications were significant influencing factors for the sleep quality trajectories after CBT-I treatment (all P<0.05). Conclusion:The sleep quality of insomnia patients after CBT-I treatment shows different development trajectories, and its influencing factors are depression, anxiety, family history of insomnia and the use of hypnotic medications.

[Objective] To explore how to deal with the paternity test of complex adoption cases. [Method] Samples from 13 families, in which adoptive parents were suspected related to biological parents, were genotyped using "Identifder + Sinofder + Powerplex 16" combined system (D8S1179, D21S11, D7S820, CSFIPO, D3S1358, TH01, D13S317, D16S539, D2S1338, D19S433, VWA, TPOX, D18S51, D5S818, FGA, D6S1043, D12S391, PentaD, PentaE) followed by further statistical analysis. [Result] Among all 13 cases, 2 were completely accordance with the Mendel law, PI > 10 000. There found more than 3 inconsistent loci in 8 cases. And found 1～2 inconsistent loci in 3 cases, needed to test more STR loci until PI≥10 000. The half sibling index (HSI) was also calculated with ITO method. The adoptive parents of 2 cases were not excluded from a full sibling with biological parents. In addition, Y-STR loci were tested for 4 cases (father/son). Two adoptive fathers of them were not excluded from the paternal relationship with biological fathers. [Conclusion] The most (76.9%) of all (13) complex adoptive cases of paternity test could be drawn a definite conclusion with combined system of "Identifder + Sinefiler + Powerplexl6". Minority (23.1%) of them was not definite yet and needed testing more STIR loci. Meanwhile, we suggested adding Y-STR tests and providing HSI for reference.