OBJECTIVE:This study aimed to clarify the independent and joint associations of loneliness and social isolation with subjective cognitive decline (SCD) among perimenopausal women. METHODS:This cross-sectional study was conducted between March and September 2024 and comprised 903 perimenopausal women. Subjective perceived loneliness, objective social isolation, and severity of SCD were measured using a set of self-reported online questionnaires. Latent class analysis was employed to determine the high-risk SCD groups among perimenopausal women, and restricted cubic spline model and logistic regression models were further utilized to investigate the independent and joint associations of loneliness and social isolation with SCD. RESULTS:The mean SCD score across all participants was 3.77 (SD=2.99). Latent class analysis categorized the participants into a "mild SCD group" (47.8%) and "severe SCD group" (52.2%). Logistic regression analysis revealed that both loneliness and social isolation were independently associated with SCD. Notably, joint analysis revealed that compared with participants without loneliness and social isolation, those with moderate to severe loneliness and social isolation exhibited the highest odds of severe SCD. Furthermore, significant additive and multiplicative interactions were observed between moderate to severe loneliness and social isolation. CONCLUSION:In perimenopausal populations, loneliness and social isolation were not only independently associated with SCD but also exhibited a joint relationship. These findings offer deeper insights into understanding the relationship between social connections and SCD, and provide empirical evidence for developing psychosocial interventions aimed at preserving cognitive health in perimenopausal women.

Depression is prevalent among colorectal cancer (CRC) survivors. Although various physical activity intensities are differentially associated with depressive symptoms, the underlying mediator and moderator involving interoception and mindfulness, remain unclear. This study aims to examine whether interoceptive accuracy differentially mediates the relationship between various physical activity intensities and depressive symptoms and whether mindfulness moderates these pathways. In this multicenter cross-sectional study, 395 CRC survivors completed validated questionnaires assessing depressive symptoms, physical activity participation, interoceptive accuracy, and mindfulness. Mediation and moderated mediation analyses via PROCESS version 4.1 for SPSS tested whether interoceptive accuracy mediated associations between light and moderate-to-vigorous physical activity (LPA vs. MVPA) and depressive symptoms, and whether mindfulness moderated these pathways. Both LPA and MVPA are negatively associated with depressive symptoms (p < 0.001). Interoceptive accuracy significantly mediated these associations, accounting for 49.09

BACKGROUND:Nurses are required to manage their emotional expressions to meet professional standards and provide optimal support. Emotional labor has become an inevitable part of their daily professional lives. Understanding the relationships between emotional labor and its antecedents is crucial for guiding nurses to adopt beneficial emotional labor strategies, thereby enhancing their well-being and the quality of care. AIM:To examine the interdependence among emotional labor strategies, emotional display rules, emotional intelligence, and perceived organizational support among clinical nurses using network analysis, and to identify central and bridge components that may inform future nursing management research. METHODS:A secondary analysis was conducted using cross-sectional data from 2996 nurses across eight cities in Shandong Province, China. Data on emotional labor, emotional display rules, emotional intelligence, and perceived organizational support were collected. We estimated an undirected network using a Gaussian graphical model (GGM) and employed Bayesian network analysis to infer potential directional associations, visualized as a directed acyclic graph (DAG). RESULTS:The undirected network identified "Use of emotion" and "Deep acting" as the nodes with the highest expected influence, indicating their strong connectivity with other components of the emotional labor network. "Positive display rules" exhibited the highest bridge expected influence, functioning as a link between the organizational norms and individual emotion regulation. Additionally, in the estimated DAG, "Self-emotion appraisal" occupied a relatively upstream structural position, providing an exploratory indication of potential directional organization. CONCLUSIONS:This study provides preliminary insights into the network structure linking emotional labor, emotional display rules, emotional intelligence, and perceived organizational support among clinical nurses in Shandong Province, China. "Use of emotion," "Self-emotion appraisal," and "Positive display rules" emerged as structurally important components that warrant further examination in longitudinal and intervention studies. The findings may be most applicable to clinical nurses working in similar Chinese tertiary hospital contexts. IMPLICATIONS FOR NURSING MANAGEMENT:In similar Chinese tertiary hospital contexts, nursing managers may consider fostering supportive work environments and developing flexible, noncoercive positive display norms that support adaptive emotional regulation and the appropriate expression of naturally felt emotions. Emotional utilization and self-emotion appraisal may also represent relevant areas for future management programs; however, these implications are based on exploratory cross-sectional evidence and require confirmation in longitudinal or intervention studies.

Patients with gastrointestinal cancer frequently encounter a myriad of sleep disorders, and these disturbances can profoundly exacerbate their psychological distress, particularly anxiety and depression. Elucidating the intricate relationship between sleep disorders and psychological disturbances holds paramount significance in enhancing the therapeutic efficacy and improving the survival outcomes for these patients. A cross-sectional study including 352 participants from two hospitals was conducted. Insomnia symptoms and psychological distress were assessed. Pearson correlation analysis and network analysis were used to determine the association between insomnia and psychological distress components. In this study, the prevalence of psychological distress was recorded at 45.2

Mindfulness interventions have demonstrated significant effectiveness in alleviating perioperative symptoms, but how they impact the interconnected symptom network and hospital outcomes remains unclear. This study explored the effect of Perioperative Mindfulness Intervention (PMI) on symptom networks and hospital-related outcomes of patients with gastrointestinal cancer. A sample of 328 patients with gastrointestinal cancer was randomly allocated to the intervention (n = 164) or control group (n = 164). The PMI, delivered via WeChat, comprised seven sessions during the perioperative period, integrating health education and mindfulness practice through multimedia content. The main measurement tools included the M.D. Anderson Symptom Inventory-Gastrointestinal Cancer Module, the Quality of Recovery-15, and the Stress Response Questionnaire. We conducted assessments before (T0, 2 days before surgery), during (T1, 2 days after surgery and T2, 6 days after surgery), immediately after (T3, 10 days after surgery), and 4 days after the mindfulness intervention (T4, 14 days after surgery). The main methods included the Network Comparison Test (NCT) and Network Intervention Analysis (NIA). The NCT revealed differences in network structure, global strength, and the centrality of certain nodes between the two symptom networks. The NIA identified the targets of mindfulness intervention during the perioperative period including dry mouth, sleep disturbances, and pain. Moreover, there were differences in recovery quality (t(326) = − 3.23, p = 0.001, Cohen’s d = − 0.36), adaptation status (t(322.61) = 4.92, p < 0.001, Cohen’s d = 0.54), and length of hospital stay (t(311.33) = 2.63, p = 0.009, Cohen’s d = 0.30) between the two groups. This research was expected to not only enhance patients’ recovery quality and adaptation, shorten hospital stays, but also improve medical service quality. The trial was prospectively registered at the Chinese Clinical Trial Registry (ChiCTR2100044752) on March 26, 2021.

PURPOSE:To examine the co-occurrence of social isolation and loneliness among colorectal cancer patients with a permanent stoma and its associated factors based on the ICF framework. METHODS:A convenience sample of 469 patients was recruited from three tertiary Grade A hospitals in Shandong Province between November 2023 and December 2024. Data were collected using questionnaires on demographics, social isolation, loneliness, social participation, stigma, motivation for social connectedness, and family functioning. Multinomial logistic regression was used to identify factors associated with the co-occurrence patterns of social isolation and loneliness. RESULTS:Social isolation and loneliness were reported by 59.2% and 47.8% of patients, respectively. Four co-occurrence patterns were identified: no social isolation and no loneliness (Class 1, 28.3%), social isolation but no loneliness (Class 2, 23.9%), no social isolation but loneliness (Class 3, 12.4%), and both social isolation and loneliness (Class 4, 35.4%). Higher social participation was associated with lower odds of belonging to all three vulnerable groups. Greater stigma increased the likelihood of belonging to the no social isolation but loneliness and coexistence groups. Higher motivation for social connection reduced the likelihood of belonging to the social isolation but no loneliness and coexistence groups. Better family functioning was associated with lower odds of belonging to the no social isolation but loneliness and coexistence groups. CONCLUSION:Coexisting social isolation and loneliness was the most common pattern. The findings suggest that future assessment and supportive care should consider the heterogeneity of social isolation-loneliness patterns, with attention to social participation, stigma, motivation for social connectedness, and family functioning.

Background Depressive symptoms are prevalent and influenced by various protective factors among university students. While meaning in life (MIL), particularly the presence of MIL, has emerged as a core psychological construct associated with depression, its precise position within the network of interconnected psychological resources remains unclear. This study aimed to understand how psychological resources of mental health interact and to explore statistically compatible directional pathways associated with depressive symptoms. Method A cross-sectional study was conducted among 2216 Chinese university students. Outcome measures included depression, MIL, mindfulness, self-control, social support, and resilience. Psychological network analysis was employed to estimate associations among variables, with additional directed acyclic graphs (DAGs) used to explore directional structures compatible with the observed data. Results The network showed the presence of MIL as the central, highest-bridging node, strongly connecting a cluster of protective factors negatively to depression. DAG-based modeling suggested that family support, mindfulness, and self-discipline were directionally associated with the presence of MIL, which, in turn, was linked to lower depression both directly and indirectly via resilience, with a potential mediating role. Conclusion The findings highlight the presence of MIL as a central and modifiable factor within the psychological resources network against depression among university students. The results generate testable hypotheses suggesting that MIL interventions, integrated with mindfulness, social support, and self-control, may be promising directions for alleviating depression, with a need for testing in future longitudinal and experimental research.

Interoceptive accuracy (IAcc), the objective capacity to sense internal bodily signals, declines with aging, yet its underlying neural mechanisms remain unclear. This study utilized functional near-infrared spectroscopy (fNIRS) to investigate age-related differences in cortical activation and functional connectivity of cortical regions during interoceptive tasks to uncover neural mechanisms that may explain age-related differences in IAcc. This study recruited 29 young adults (M age =23.76) and 25 older adults (M age =64.32) to undertake a breath-focused interoceptive task and a resting-state scan. IAcc was assessed by the heartbeat perception task. This study showed that young adults exhibited significantly greater activation in the supplementary motor cortex (SMC), prefrontal cortex (PFC), inferior frontal gyrus (IFG), left primary somatosensory cortex (S1-L), and right primary motor cortex (M1-R) during the interoceptive task compared to older adults. Critically, higher IAcc was positively correlated with the IFG-L activation. Older adults demonstrated significantly stronger functional connectivity between S1-L and IFG-R, PFC-R, as well as PFC-L during the interoceptive task relative to the resting state. Importantly, between-group comparisons revealed a trend enhanced functional connectivity in older adults for M1-L/M1-R, S1-L/IFG-R and PFC networkers before the FDR correction for multiple comparisons. These findings suggest that age-related cortical changes may compromise the neural efficiency of interoceptive networks. This research provides novel insights into the age-specific neural patterns underlying IAcc decline, highlighting potential biomarkers for early identification of interoceptive decline risks and informing the development of targeted interventions to mitigate age-related changes in interoceptive function.

Objective Fear of progression (FoP), anxiety, and depression are common emotional distresses for parents of children with cancer, but yet these concerns often lack attention. This study explored the network connections between FoP, anxiety, and depression in parents of children with malignant solid tumors. Methods This study that included 447 parents of children with malignant solid tumors. All participants completed the Fear of Progression Questionnaire-parent version (FoP-Q-SF/PR), the 2-item Generalize Anxiety Disorder Scale (GAD-2) and the 2-item Patient Health Questionnaire (PHQ-2). We estimated two network models: regularized partial correlation network and Bayesian Directed Acyclic Graph (DAG). Results The regularized partial correlation network demonstrated a correlation between FoP, anxiety, and depressive symptoms, with a stronger association observed between anxiety and depression. The results of the Network Centrality Indicator showed that the top three symptoms in terms of expected impact (EI) were “fear of major treatment”, “life anxiety”, and “feeling tense, anxious, or eager”. The DAG showed that the symptoms of FoP activated each other, which in turn activated anxiety and depressive symptoms. In particular, “fear of major treatment” was at the top of the DAG and therefore has the highest predictive priority in the network.Conclusion: “Fear of major treatment” was a core symptom in the regularized partial correlation network and an upstream symptom in the DAG. The findings suggest that strengthening health education, building confidence in overcoming the disease, and reinforcing positive coping may help to improve negative emotions in parents of children with malignant solid tumors.

Purpose:Depression is well-known to be transmitted across generations, whereas the focus has often been on mother-child dyads. Little is known about the role of fathers and some inherited temperaments of adolescents, especially in Chinese families. This study is the first to explore the moderated mediation transmission mechanism of depressive symptoms, in which (i) the role of fathers was compared to that of mothers, and (ii) how adolescent perceptual sensitivity worked was particularly elucidated. Participants and Methods:A total of 738 Chinese adolescents (M age = 12.80 ± 1.58 years; 47.2% girls) who were companied with one of their primary caregivers (mothers or fathers) were recruited, constituting two subsamples of mother-child (N = 508) versus father-child dyads (N = 230), respectively. Path models and the regions of significance approach were used to analyze the moderated mediation mechanisms. Results:Mothers and fathers both transmitted depressive symptoms to adolescents via their rejection parenting (indirect effect = 0.14, SE = 0.02, p < 0.001). However, adolescent perceptual sensitivity moderated the second half path of this mediation pathway among mother-child dyads (b = 0.09, SE = 0.04, p = 0.011), but not among father-child dyads (b = -0.05, SE = 0.06, p = 0.348), and worked in a manner of diathesis-stress. Adolescent sex did not moderate this transmission mechanism (χ2 = 6.52, df = 3, p = 0.089). Conclusion:These findings suggest similarities and differences in the roles of mothers and fathers in the transmission risk of depressive symptoms in contemporary Chinese families, and highlight a diathesis-stress like moderation effect of adolescent perceptual sensitivity.

ObjectiveThis study aims to develop and validate a machine learning model for identifying individuals within the nursing population experiencing severe subjective cognitive decline (SCD) during the menopause transition, along with their associated factors.MethodsA secondary analysis was performed using cross-sectional data from 1,264 nurses undergoing the menopause transition. The data set was randomly split into training (75%) and validation sets (25%), with the Bortua algorithm employed for feature selection. Seven machine learning models were constructed and optimized. Model performance was assessed using area under the receiver operating characteristic curve, accuracy, sensitivity, specificity, and F1 score. Shapley Additive Explanations analysis was used to elucidate the weights and characteristics of various factors associated with severe SCD.ResultsThe average SCD score among nurses in the menopause transition was (5.38 +/- 2.43). The Bortua algorithm identified 13 significant feature factors. Among the seven models, the support vector machine exhibited the best overall performance, achieving an area under the receiver operating characteristic curve of 0.846, accuracy of 0.789, sensitivity of 0.753, specificity of 0.802, and an F1 score of 0.658. The two variables most strongly associated with SCD were menopausal symptoms and the stage of menopause.ConclusionsThe machine learning models effectively identify individuals with severe SCD and the related factors associated with severe SCD in nurses during the menopause transition. These findings offer valuable insights for the management of cognitive health in women undergoing the menopause transition.

AIMS:This study aimed to develop and evaluate the psychometric properties of the Stoma Acceptance and Valuable Actions Scale (SAVAS), which measures the degree of stoma acceptance and the extent of personal actions aligned with values among colorectal cancer (CRC) patients with permanent stomas. BACKGROUND:Acceptance of a stoma and the enactment of actions consistent with personal values are crucial for psychosocial adaptation following stoma formation. However, these aspects have not been adequately explored, largely due to the lack of valid and reliable measurement tools. DESIGN:This is an instrument development and validation study with a cross-sectional design. METHODS:Items were created through a literature review and guided by Acceptance and Commitment Therapy (ACT) theory. Content validity was evaluated using two rounds with a consensus panel of 12 experts. The psychometric properties of the SAVAS were tested using two separate convenience samples (Ns = 201 and 213). Key aspects assessed included content validity, internal consistency, test-retest reliability, convergent validity, discriminant validity and concurrent validity. RESULTS:The content validity of the SAVAS was high at 0.921, and a two-factor solution emerged from the final 12 items: stoma acceptance and valuable actions. The Cronbach's alpha for the overall scale and its factors was strong (0.888 for the total scale, 0.879 for stoma acceptance and 0.872 for valuable actions). Acceptable test-retest reliability was demonstrated, with values of 0.939, 0.872 and 0.864, respectively. The study also confirmed good convergent, concurrent and discriminant validity for the SAVAS. CONCLUSION:The SAVAS demonstrated good validity and reliability for assessing stoma acceptance and valuable actions among CRC patients with permanent stomas. Future observational and interventional studies are needed to further assess and refine the psychometric properties of the SAVAS.

Growth differentiation factor 11 (GDF11), a member of the transforming growth factor β (TGF-β) superfamily, exhibits great neurological and mental diseases modulating potential. However, its specific effects on microglia, which are the primary immune cells of the nervous system, remain unclear. To investigate the mechanism by which GDF11 affects BV2 microglial cells in vitro and to elucidate its regulatory mechanisms, we carried out a systematic examination of how GDF11 affects the various functions of lipopolysaccharide (LPS)-induced BV2 microglial cells and found that endogenous GDF11 could significantly inhibit cell proliferation, apoptosis, and migration. Specifically, GDF11 inhibited the polarization of BV2 cells to the proinflammatory M1 phenotype and promoted their polarization to the anti-inflammatory M2 phenotype, precipitating a reduction in the expression of CD86 and nitric oxide synthase 2 (NOS2), and an increase in the expression of CD206 and arginase-1. Additionally, RNA-seq and Western blotting experiments revealed that GDF11 activated the p38 MAPK (mitogen-activated protein kinase) pathway, mediating its effects on BV2 cells. Taken together, GDF11 could crucially regulate microglial responses and promote an anti-inflammatory microglial phenotype through the p38 MAPK signaling axis, which may have potential therapeutic implications in neuroinflammatory diseases.

Colorectal cancer (CRC) survivors with permanent stomas may commonly suffer from social withdrawal and subsequently experience loneliness. However, the relationship between social withdrawal and loneliness may vary depending on the individual’s psychological flexibility based on Acceptance and Commitment Therapy (ACT) theory. The present study thus examined the association between social withdrawal and loneliness by focusing on the potential moderating roles of psychological flexibility among CRC survivors with permanent stomas. A cross-sectional sample of 289 CRC survivors with permanent stomas completed the social withdrawal subscales, the stoma acceptance and valuable actions scale, and the 6-item revised UCLA Loneliness scale. Moderation analysis using the PROCESS macro in SPSS was conducted to examine the moderating effects of psychological flexibility and its two components, stoma acceptance and valuable actions. The results indicated that social withdrawal was positively associated with loneliness (r = 0.423, P < 0.001). The moderating analyses showed that psychological flexibility significantly moderated the association of social withdrawal with loneliness (interaction term = − 0.017, P = 0.006). Further exploratory analyses found that the moderating effect of valuable actions was significant (interaction term = − 0.028, P = 0.005), while the stoma acceptance was not. Psychological flexibility, as well as valuable actions, may serve as a protective factor in the potential effects of social withdrawal on loneliness among CRC survivors with permanent stomas.

The patterns of respiratory pathogens have undergone significant changes, underscoring the critical need for accurate pathogen identification to guide targeted treatment. This study aimed to investigate the positive rates of common respiratory pathogens over the past two years using the multiplex molecular testing in clinical settings. This study evaluated respiratory pathogens in 7861 hospitalized patients at Qilu Hospital of Shandong University from March 2022 to February 2024. Pathogen detection was performed using multiplex RT-PCR combined with capillary electrophoresis technology, targeting influenza A virus (Flu-A), influenza A virus H1N1 (H1N1), influenza A virus H3N2 (H3N2), influenza B virus (Flu-B), parainfluenza virus (PIV), adenovirus (ADV), human Metapneumovirus (HMPV), human Coronavirus (HCOV), Mycoplasma pneumoniae (MP), respiratory syncytial virus (RSV), parainfluenza virus (PIV), Boca virus (Boca), human Rhinovirus (HRV), and Chlamydia (Ch). A comparative analysis of epidemiological patterns was conducted between the period during and after implementation of COVID-19 control policies. The overall pathogen detection rate was significantly higher at 65.79% (3786/5754) post COVID-19 pandemic compared to 30.36% (640/2107) during COVID-19 pandemic. With the relaxation of COVID-19 control policies, the positive rates of viruses such as Flu-A, Flu-B, PIV, RSV, and HCOV increased significantly. In contrast, there were no significant differences in the positive rates of HRV and Boca between the two periods. Notably, the positive rate of RSV was significantly higher across all age groups in the post-pandemic COVID-19 period, expect among individuals aged 14-18 and 19-40 years. MP was identified as the predominant pathogen in patients aged 4-13 years. Seasonal variation was evident in the detection rates of respiratory pathogens, ranging from 18.27% in 2022 to 77.79% in 2023. Flu-A H1N1 subtype infections were detected throughout spring, autumn and winter of 2023, peaking in spring and declining gradually in subsequent months. Additionally, MP infections fist emerged in May 2023 and increased monthly, reaching the peak in October of the same year. The findings illustrate the progressive re-emergence and considerable epidemiological importance of multiple respiratory pathogens among hospitalized patients across different age groups and seasons during the two-year surveillance period. Utilizing a multiplex molecular approach for respiratory pathogen surveillance enables accurate assessment of prevalence trends, especially in hospitalized patients with more severe clinical presentations, which can help clinicians to take necessary measures in the management of prevention, control, and precise therapy.

AIM:To combine the Job Demand-Resource (JD-R) model with machine learning (ML) techniques to identify the key factors affecting job burnout (JB) among Chinese nurses. DESIGN:A Cross-Sectional Study. METHODS:This study utilised a stratified sampling method to recruit 3449 eligible nurses from eight cities in Shandong Province between June and December 2021. After data cleaning, 2998 valid samples were retained. The dataset was randomly split into a training set (75%) and a test set (25%). The Boruta algorithm was used to select relevant variables for model construction. Six-millilitre models were compared using cross-validation, with mean absolute error (MAE), root mean square error (RMSE) and R-squared (R2) used to select the best model. The Shapley Additive Explanation (SHAP) method was used to identify key predictors of JB. RESULTS:The average JB score among nurses was (32.88 ± 11.45). Among the 20 variables, 17 were identified by the Boruta algorithm as strongly associated with JB, including 7 job demand-related variables and 10 job resource-related variables. After comparing 6-ml models, the Random Forest was identified as the optimal model (MAE = 6.56, RMSE = 8.86, R2 = 0.63). SHAP analysis further revealed the importance ranking of these 17 variables and identified four key predictors: psychological distress (SHAP = 4.07), perceived organisational support (SHAP = 2.03), emotional intelligence (SHAP = 1.81) and D-type personality (SHAP = 1.73). CONCLUSION:By integrating the JD-R model framework, ML algorithms proved effective in identifying critical predictors of nurses' JB. SHAP analysis identified four primary determinants: psychological distress, perceived organisational support, emotional intelligence and D-type personality. These findings provide novel insights for nursing administrators to optimise intervention strategies. IMPACT:Not applicable. PATIENT OR PUBLIC INVOLVEMENT:This study did not include patient or public involvement in its design, conduct or reporting.

BACKGROUND:Recent studies have identified interoceptive dysfunction as a critical biomarker for emotional disorders. It is well-established that aging correlates with a deterioration in interoceptive capabilities, which consequently affects emotional processing dynamics. METHODS:This study performed a systematic review and meta-analysis to evaluate the associations between interoceptive variants and mental health in middle-aged and elderly adults. Three English databases, including PubMed, Web of Science, and Medline (via EBSCO), were electronically searched from inception through December 2023. The study quality and meta-analysis were performed using the MMAT and RevMan 5.4 software. RESULTS:A total of 21 studies were included in this systematic review, and data from 14 studies were used in the meta-analysis. Favorable associations were seen between interoception and depression (pooled r = -0.11 (95CI%: -0.19 to -0.03), z = 2.72, p = 0.006, I2= 0 %), alexithymia (pooled r = -0.25 (95CI%: -0.35 to -0.16), z = 4.84, p < 0.001, I2= 31 %), and emotion regulation (pooled r = 0.30 (95CI%: 0.18-0.41), z = 4.63, p < 0.001, I2= 33 %). Interoception showed no significant correlation with other mental health outcomes. CONCLUSION:This systematic review and meta-analysis underscore the importance of interoception in understanding the underlying neural mechanisms of depression, alexithymia, and emotion regulation in middle-aged and older adults. Interoceptive training could also potentially serve as an effective strategy for promoting mental health within this demographic.

Background Premenstrual syndrome (PMS) is a public health problem with widespread impact, influenced by the multiple factors. Young adult women, as a high-risk group for PMS, can benefit from early identification of key factors related to PMS. This study aimed to construct a machine learning model for identifying PMS among young adult women and explore the complex relationships between associated factors and PMS. Method A secondary analysis was performed using cross-sectional data from 3447 young adult women. Using a score of 6 points on the Premenstrual Syndrome Scale (PSS) as the cutoff, all participants were divided into the PMS group and the non-PMS group. The dataset was randomized into a training set and a validation set in 75% and 25% proportions. Five machine learning algorithms were used to develop models and the output of performed-best model was interpreted using SHapley Additiveex Planations (SHAP). Results There were 1474 women in PMS group and 1973 women in non-PMS group. Among five machine learning models, the random forest model performed best, with an AUC of 0.782. Neuroticism was most strongly associated with PMS, followed by mindfulness, history of dysmenorrhea, emotional abuse, and use of analgesic. Conclusion The results suggested that the random forest model was an effective tool for identifying PMS among young adult women, and neuroticism could serve as a crucial predictive indicator. Furthermore, interventions such as mindfulness training, dysmenorrhea management, and addressing early trauma may hold significant potential in preventing and managing PMS.

Symptom networks can provide empirical evidence for developing personalized and precise symptom management strategies. However, the network structure and temporal stability of perioperative symptoms among gastrointestinal cancer patients remain unknown. This study aims to explore the dynamic connections between symptoms and accurately identify core symptoms to support clinical decision-making. The measurement points included T0 (2 days before surgery), T1 (2 days after surgery), T2 (6 days after surgery), T3 (10 days after surgery), and T4 (14 days after surgery). Measurement tools included M.D. Anderson Symptoms Inventory-Gastrointestinal Cancer Module (MDASI-GI). A Multilevel Vector Autoregressive Model (mlVAR) was used to build the temporal and contemporaneous networks. A total of 241 gastrointestinal cancer participants were recruited, primarily with colorectal cancer type. In the temporal network, sadness had the strongest predictive effect on appetite change, with a value of -0.231. Additionally, dry mouth was identified as the core symptom with the highest outward strength centrality (1.234) and positively predicted pain, sadness, difficulty swallowing, distress, and fatigue (EW = 0.157 0.230, Ps < 0.001). In the contemporaneous network, depression was a core symptom with the highest strength centrality (1.001). The strongest correlation was found between distress and sadness (EW = 0.645, Ps < 0.05), followed by dry mouth and difficulty swallowing (EW = 0.363, Ps < 0.05). At five time points, the core symptoms within the perioperative symptom network encompassed appetite loss (at T0, with a value of 0.943), distress (at T1, with a value of 1.225; at T2, with a value of 1.057; and at T3, with a value of 0.858), and sadness (at T4, with a value of 1.238). There exist a prevalent occurrence of positive predictive and associative effects among symptoms. Moreover, emotional and gastrointestinal symptoms, particularly depression and dry mouth, hold significant positions in the perioperative symptom network and should be prioritized in symptom management strategies. This study uncovers the underlying patterns of widespread positive predictive and associative effects among symptoms, and provides targeted clinical guidance for managing core symptoms such as dry mouth in perioperative care for cancer patients.