Yajing Wang

Objective: To investigate the effects of sleep quality, sleep deprivation, and napping on facial emotion recognition (FER) accuracy and speed. Methods: This research included a cross-sectional study (102 qualified participants) and a randomized controlled study (26 in the napping group and 24 in the control group). The stimuli for the FER task were obtained from the Chinese Facial Affective Picture System (CFAPS). Four facial expressions (fearful, disgusted, sad, and angry) were used. The Pittsburgh Sleep Quality Index (PSQI), Self-Rating Anxiety Scale, and Self-Rating Depression Scale were used to measure participants’ sleep quality and psychological conditions. In Study 1, FER ability was compared between good and poor sleepers. In Study 2, all participants were sleep-deprived for one night, and completed the FER task before and after sleep deprivation. After different interventions (ie, napping for one hour, or walking around for ten minutes), the participants completed the third FER task. Results: Study 1: Poor sleepers were able to recognize sad expressions more accurately compared with good sleepers. Study 2: 30-h sleep deprivation had no significant effect on the accuracy (ACC). Napping after sleep deprivation improved the FER ACC of upper-face expressions and marginally significantly improved the FER ACC of disgusted expressions. Conclusion: Better sleep quality was linked to lower FER accuracy, particularly in recognizing sad expressions, while no significant differences in recognition speed were observed. Additionally, 30 hours of sleep deprivation did not affect FER accuracy, but napping after sleep deprivation improved accuracy for upper-face and marginally for disgusted expressions.

Purpose This study explored the relationship between naps and memory among habitual nappers in China. Methods Medical college students participated and were divided into 30-min, 60-min, and 90-min time-in-bed groups. To evaluate declarative and procedural memory performance, A–B and A–C interfering word pair and interfering finger tapping tasks were employed. Results Among 60 students, a significant decrease in the correct recall rate in the declarative task after having a nap was found only in the 30-min group (p = 0.005). After learning interference (A-C word pairs), the correct recall rate for the declarative task decreased significantly in all interference tests (ps < 0.001). In the procedural task, the speed of sequence A in the retests increased after having a nap in all three groups (ps < 0.048), with a significant decrease in accuracy only in the 30-min group (p = 0.042). After learning interference (sequence B) in the procedural task, the speed of sequence A increased in the 60-min group after 1 h (p = 0.049), and both the 60-min and 90-min groups showed increased speed after one night (ps < 0.022). No significant improvement in speed was found in the 30-min group (ps > 0.05), and this group showed the lowest accuracy for sequence A (ps < 0.16). Conclusion A habitual nap time-in-bed of 60 or 90 min had better effects on declarative and procedural memory consolidation and better memory resistance against interference in procedural memory.

Military personnel live in operating environments in which poor sleep is common. In this cross-temporal meta-analysis (CTMA), 100 studies (144 data sets, N = 75,998) were identified to examine changes in sleep quality among Chinese active service personnel from 2003 to 2019. Participants were divided into three groups: the navy, the non-navy, and the unknown service. The Pittsburgh Sleep Quality Index (PSQI) was used as the measure of sleep quality; it contains a global score and seven component scores, with higher scores indicative of poorer sleep. Among all active military personnel, the PSQI global and seven component scores decreased from 2003 to 2019. In examining the results by military type, the PSQI global and seven component scores increased in the navy group. Conversely, both the non-navy and unknown-service groups showed decreased PSQI global scores over time. Similarly, all PSQI component scores decreased over time for both the non-navy and unknown service groups, except for the use of sleeping medication (USM), which increased in the non-navy group. In conclusion, the sleep quality of Chinese active service personnel showed a positive trend. Further research should focus on improving the navy’s sleep quality.

Purpose: Previous epidemiological and psychological studies have assessed the effects of napping on individual performance and health. However, these studies did not distinguish between spontaneous and passive napping due to sleep disorders. Therefore, this study aimed to explore the potential motivation for napping among Chinese college students and to assess the relationship between different nap motivations and sleep. Patients and Methods: This cross-sectional study was conducted at a university in Shanghai in March 2021 using convenience sampling. A total of 564 Chinese college students with self-reported napping habits participated in this study. Exploratory factor analysis (EFA) was employed to analyze 34 self-rated motivations for napping to derive a potential structural model of napping motivation. Correlation and multiple linear regression analyses were performed to determine the influence of nap motivation on sleep behavior. Results: Chinese college students mainly take naps to reduce fatigue, usually in the form of frequent and long naps (6.25 ± 1.24 days; 64.62 ± 23.70 min). A structural model of nap motivation named the I-DREAM model was proposed, consisting of six factors: restorative, induced, mindful, appetitive, dysregulative, and exercise naps. There were also sex differences in nap motivation, as women preferred restorative naps and appetitive naps, while men preferred exercise naps (p < 0.01, p < 0.05). Furthermore, there was a significant correlation between nap motivation on nap duration, frequency and nighttime sleep quality (R²= 2.70– 18.9%). Conclusion: The proposed I-DREAM model implies that there are population differences in napping motivation. Different motivations also have different relationships with napping patterns and nighttime sleep. In understanding the relationship between naps and health status, nap motivation may be an extremely important influencing factor.

The therapeutic effect of antidepressants has been demonstrated for anhedonia in patients with depression. However, antidepressants may cause side‐effects, such as cardiovascular dysfunction. Although physical activity has minor side‐effects, it may serve as an alternative for improving anhedonia and depression. We sought to investigate whether physical activity reduces the level of anhedonia in individuals with depression. Fifty‐six university students with moderate depressive symptoms (Beck Depression Inventory total score > 16) were divided into three training groups: the Running Group (RG, n = 19), the Stretching Group (SG, n = 19), and the Control Group (n = 18). We employed the Monetary Incentive Delay (MID) task and the Temporal Experience of Pleasure Scale (TEPS) to evaluate hedonic capacity. All participants in the RG and SG received 8 weeks of jogging and stretching training, respectively. The RG experienced an increase in the level of arousal during anticipation of a future reward and recalled less negativity towards the loss condition. The SG exhibited enhanced scores on the Anticipatory and Consummatory Pleasure subscales of the TEPS after training. Moreover, in the RG, greater improvements in anticipatory arousal ratings for pleasure and remembered valence ratings for negative affect were associated with longer training duration, lower maximum heart rate, and higher consumed calories during training. To conclude, physical activity is effective in improving anticipatory anhedonia in individuals with depressive symptoms.

Background: Patients with lung cancer (LC) have a poor quality of life (QoL) and easily suffer from psychological diseases. Previous studies focused less on the relationship between genetic factors and QoL, depression, and anxiety status in LC patients. The current study is intended to explore the relationship between SNPs and haplotypes of ERCC1 and ERCC2 and the QoL, depression and anxiety status of patients with LC. Methods: QoL, depression and anxiety status were assessed in 291 LC patients using the European Organization for Research and Treatment of Cancer (EORTC) Core Quality of Life Questionnaire (QLQ-C30), EORTC Quality of Life Questionnaire-Lung Cancer 13 (QLQ-LC13), SDS and SAS. Nine tag SNPs of ERCC1 and ERCC2 were detected using an improved multiplex ligation detection reaction (iMLDR) technique. Haplotype analysis was conducted using the software Haploview 4.2. The association between SNPs or haplotypes and QoL or depression or anxiety in LC patients was analyzed by regression analysis. Results: ERCC1 rs11615 was associated with emotional functioning (P = 0.027), and ERCC1 rs3212986 was associated with anxiety scores (P = 0.018). ERCC1 rs762562-rs3212986 haplotype was associated with cognitive function (P = 0.029), somatic function (P = 0.014) and dysphagia (OR = 3.32, P = 0.044). Patients with ERCC1 rs3212986-rs11615 AG haplotype had worse cognitive function (adjusted Beta = − 5.42) and somatic function (adjusted Beta = − 6.55) and had severer symptoms of loss of appetite (adjusted OR = 1.67) and dysphagia (adjusted OR = 4.43) (All adjusted P < 0.05). ERCC2 rs13181-rs3916874-rs238416 haplotype was associated with emotional functioning (P = 0.035), pain at other sites (OR 1.88, P = 0.014), chest pain (OR 0.42, P = 0.02), dysphagia (OR 2.82, P = 0.048), and anxiety status (OR 0.23, P = 0.009). Conclusion: After adjustment for environmental factors, SNPs and haplotypes of ERCC1 and ERCC2 were associated with different domains of QoL, depression and anxiety in LC patients.