The rural-oriented tuition-waived medical education program in China, started in 2010, provides free medical education to students committed to serving in rural areas to address medical staff shortages. Despite its success in training and deploying graduates, retaining them post-obligation remains challenging. This study explores the mechanisms behind the turnover intentions of rural-oriented medical students in Western China, offering insights for their retention.

Semi-structured interviews were conducted with 47 rural-oriented medical students and 30 health clinic directors in Nanning City. Interview data were analysed using grounded theory, and open, axial and selective coding was applied.

Through three levels of coding analysis, 34 tree nodes, 13 sub-categories and 3 main categories were identified from the interviews with rural-oriented medical students and health clinic directors. 3 main categories were Subjective Norms, Behavioural Attitudes, and Perceived Behavioural Control.

A model of turnover intention among rural-oriented medical students was developed. This model can serve as a valuable reference for future policy optimization concerning China’s rural order-directed medical students.

The emotion regulation network (ERN) in the brain provides a framework for understanding the neuropathology of affective disorders. Although previous neuroimaging studies have investigated the neurobiological correlates of the ERN in major depressive disorder (MDD), whether patients with MDD exhibit abnormal functional connectivity (FC) patterns in the ERN and whether the abnormal FC in the ERN can serve as a therapeutic response signature remain unclear.

A large functional magnetic resonance imaging dataset comprising 709 patients with MDD and 725 healthy controls (HCs) recruited across five sites was analyzed. Using a seed-based FC approach, we first investigated the group differences in whole-brain resting-state FC of the 14 ERN seeds between participants with and without MDD. Furthermore, an independent sample (45 MDD patients) was used to evaluate the relationship between the aforementioned abnormal FC in the ERN and symptom improvement after 8 weeks of antidepressant monotherapy.

Compared to the HCs, patients with MDD exhibited aberrant FC between 7 ERN seeds and several cortical and subcortical areas, including the bilateral middle temporal gyrus, bilateral occipital gyrus, right thalamus, calcarine cortex, middle frontal gyrus, and the bilateral superior temporal gyrus. In an independent sample, these aberrant FCs in the ERN were negatively correlated with the reduction rate of the HAMD17 score among MDD patients.

These results might extend our understanding of the neurobiological underpinnings underlying unadaptable or inflexible emotional processing in MDD patients and help to elucidate the mechanisms of therapeutic response.

In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.

To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.

Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.

This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.

High-risk Human Papillomavirus (HPV) infections are a leading cause of cervical diseases among Han Chinese women of reproductive age. Despite studies like Mai et al. (2021) addressing HPV prevalence in Southern China, awareness remains low, especially in Southwest China. Our study addresses this gap.

This hospital-based, retrospective study analyzes the prevalence of high-risk HPV and its association with cervical intraepithelial neoplasia (CIN) among Han Chinese women of reproductive age in Southwest China.

Data were collected from 724 women undergoing routine health exams from December 2022 to April 2023. A total of 102 women with high-risk HPV infections were identified. A survey assessed HPV awareness, CIN incidence, and socio-demographic factors influencing awareness.

Of the 724 women, 102 (14.1%) were diagnosed with high-risk HPV, with HPV-16 being the most common subtype (22.5%). Awareness was significantly lower among unmarried women (OR: 6.632, p = 0.047), those with high school education or less (OR: 20.571, p = 0.003), and rural residents (OR: 19.483, p = 0.020). HPV-16 was detected in 54.55% of women with high-grade CIN.

There is an urgent need for targeted education and HPV vaccination in Southwest China, particularly for women with lower education, rural residents, and older individuals. Subtype-specific strategies are essential for preventing and managing CIN.

Coronary artery aneurysms have been considered the most serious complication of Kawasaki disease. However, some coronary artery aneurysms do regress. Therefore, the ability to predict the expected time of coronary artery aneurysm regression is critical. Herein, we have created a nomogram prediction system to determine the early regression (<1 month) among patients with small to medium coronary artery aneurysms.

Seventy-six Kawasaki disease patients identified with coronary artery aneurysms during the acute or subacute phase were included. All the patients who met inclusion criteria demonstrated regression of coronary artery aneurysms within the first-year post Kawasaki disease diagnosis. The clinical and laboratory parameters were compared between the groups of coronary artery aneurysms regression duration within and beyond 1 month. Multivariate logistic regression analysis was used to identify the independent parameters for early regression based on the results from the univariable analysis. Then nomogram prediction systems were established with associated receiver operating characteristic curves.

Among the 76 included patients, 40 cases recovered within 1 month. Haemoglobin, globulin, activated partial thromboplastin time, the number of lesions, location of the aneurysm, and coronary artery aneurysm size were identified as independent factors for early regression of coronary artery aneurysms in Kawasaki disease patients. The predictive nomogram models revealed a high efficacy in predicting early regression of coronary artery aneurysms.

The size of coronary artery aneurysms, the number of lesions, and the location of aneurysms presented better predictive value for predicting coronary artery aneurysms regression. The nomogram system created from the identified risk factors successfully predicted early coronary artery aneurysm regression.

Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous neurodevelopmental disorder defined by characteristic behavioral and cognitive features. Abnormal brain dynamic functional connectivity (dFC) has been associated with the disorder. The full spectrum of ADHD-related variation of brain dynamics and its association with behavioral and cognitive features remain to be established.

We sought to identify patterns of brain dynamics linked to specific behavioral and cognitive dimensions using sparse canonical correlation analysis across a cohort of children with and without ADHD (122 children in total, 63 with ADHD). Then, using mediation analysis, we tested the hypothesis that cognitive deficits mediate the relationship between brain dynamics and ADHD-associated behaviors.

We identified four distinct patterns of dFC, each corresponding to a specific dimension of behavioral or cognitive function (r = 0.811–0.879). Specifically, the inattention/hyperactivity dimension was positively associated with dFC within the default mode network (DMN) and negatively associated with dFC between DMN and the sensorimotor network (SMN); the somatization dimension was positively associated with dFC within DMN and SMN; the inhibition and flexibility dimension and fluency and memory dimensions were both positively associated with dFC within DMN and between DMN and SMN, and negatively associated with dFC between DMN and the fronto-parietal network. Furthermore, we observed that cognitive functions of inhibition and flexibility mediated the relationship between brain dynamics and behavioral manifestations of inattention and hyperactivity.

These findings document the importance of distinct patterns of dynamic functional brain activity for different cardinal behavioral and cognitive features related to ADHD.

Although aberrant brain regional responses are reported in social anxiety disorder (SAD), little is known about resting-state functional connectivity at the macroscale network level. This study aims to identify functional network abnormalities using a multivariate data-driven method in a relatively large and homogenous sample of SAD patients, and assess their potential diagnostic value.

Forty-six SAD patients and 52 demographically-matched healthy controls (HC) were recruited to undergo clinical evaluation and resting-state functional MRI scanning. We used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra-/inter-network functional network connectivity (FNC). Furtherly, we explored the associations of FNC abnormalities with clinical characteristics, and assessed their ability to discriminate SAD from HC using support vector machine analyses.

SAD patients showed widespread intra-network FNC abnormalities in the default mode network, the subcortical network and the perceptual system (i.e. sensorimotor, auditory and visual networks), and large-scale inter-network FNC abnormalities among those high-order and primary RSNs. Some aberrant FNC signatures were correlated to disease severity and duration, suggesting pathophysiological relevance. Furthermore, intrinsic FNC anomalies allowed individual classification of SAD v. HC with significant accuracy, indicating potential diagnostic efficacy.

SAD patients show distinct patterns of functional synchronization abnormalities both within and across large-scale RSNs, reflecting or causing a network imbalance of bottom-up response and top-down regulation in cognitive, emotional and sensory domains. Therefore, this could offer insights into the neurofunctional substrates of SAD.

Persistent psychological distress associated with the coronavirus disease 2019 (COVID-19) pandemic has been well documented. This study aimed to identify pre-COVID brain functional connectome that predicts pandemic-related distress symptoms among young adults.

Baseline neuroimaging studies and assessment of general distress using the Depression, Anxiety and Stress Scale were performed with 100 healthy individuals prior to wide recognition of the health risks associated with the emergence of COVID-19. They were recontacted for the Impact of Event Scale-Revised and the Posttraumatic Stress Disorder Checklist in the period of community-level outbreaks, and for follow-up distress evaluation again 1 year later. We employed the network-based statistic approach to identify connectome that predicted the increase of distress based on 136-region-parcellation with assigned network membership. Predictive performance of connectome features and causal relations were examined by cross-validation and mediation analyses.

The connectome features that predicted emergence of distress after COVID contained 70 neural connections. Most within-network connections were located in the default mode network (DMN), and affective network-DMN and dorsal attention network-DMN links largely constituted between-network pairs. The hippocampus emerged as the most critical hub region. Predictive models of the connectome remained robust in cross-validation. Mediation analyses demonstrated that COVID-related posttraumatic stress partially explained the correlation of connectome to the development of general distress.

Brain functional connectome may fingerprint individuals with vulnerability to psychological distress associated with the COVID pandemic. Individuals with brain neuromarkers may benefit from the corresponding interventions to reduce the risk or severity of distress related to fear of COVID-related challenges.

The coronavirus disease 2019 (COVID-19) pandemic is a major threat to the public. However, the comprehensive profile of suicidal ideation among the general population has not been systematically investigated in a large sample in the age of COVID-19.

A national online cross-sectional survey was conducted between February 28, 2020 and March 11, 2020 in a representative sample of Chinese adults aged 18 years and older. Suicidal ideation was assessed using item 9 of the Patient Health Questionnaire-9. The prevalence of suicidal ideation and its risk factors was evaluated.

A total of 56,679 participants (27,149 males and 29,530 females) were included. The overall prevalence of suicidal ideation was 16.4%, including 10.9% seldom, 4.1% often, and 1.4% always suicidal ideation. The prevalence of suicidal ideation was higher in males (19.1%) and individuals aged 18–24 years (24.7%) than in females (14.0%) and those aged 45 years and older (11.9%). Suicidal ideation was more prevalent in individuals with suspected or confirmed infection (63.0%), frontline workers (19.2%), and people with pre-existing mental disorders (41.6%). Experience of quarantine, unemployed, and increased psychological stress during the pandemic were associated with an increased risk of suicidal ideation and its severity. However, paying more attention to and gaining a better understanding of COVID-19-related knowledge, especially information about psychological interventions, could reduce the risk.

The estimated prevalence of suicidal ideation among the general population in China during COVID-19 was significant. The findings will be important for improving suicide prevention strategies during COVID-19.

Intimate partner violence (IPV) is an important risk factor for perinatal depression (PND). But IPV's impact on the natural prognosis of PND symptoms is not well understood. We tested two hypotheses: (1) pregnant women with IPV experiences will exhibit more severe PND symptoms than women without IPV experience; (2) IPV experience will impede the recovery prognosis of PND. We also explored the contribution of IPV to PND comparing with other risk factors.

The sample is comprised of 813 pregnant women followed through perinatal period in Hunan, China. We assessed IPV experience using items from the Short Form of the Revised Conflict Tactics Scale (CTS2S), and PND symptoms via the Edinburgh Postnatal Depression Scale (EPSD). We conducted Linear Mixed-effects Model to compare the trajectories of PND symptoms between victims and non-victims and a multistage Generalised Estimating Equations Model to explore salient factors on the trajectory of PND symptoms.

There were 90 participants (11.07%) who reported IPV experience in the past 12 months. With respect to physical, psychological and sexual violence, the prevalence was 4.55% (37/813), 9.23% (75/813) and 2.34% (19/813). Victims reported more severe PND symptoms (t = 5.30, p < 0.01) and slower decreasing slope of trajectories (t = 28.89, p < 0.01). The PND trajectory was associated with IPV experience (OR = 3.78; 95% CI 1.39–10.26), social support (OR = 0.93; 95% CI 0.88–0.97), positive coping strategies (OR = 0.85; 95% CI 0.80–0.91), negative coping strategies (OR = 1.25; 95% CI 1.14–1.37) and monthly income of $0.15–$298.36 (compared to no income, OR = 0.0075; 95% CI 0.00052–0.11).

The findings suggest the reported prevalence of IPV is lower in Hunan than most of the previous studies during perinatal period in other provinces of China, and IPV victimisation is associated with increased severity and slowed prognosis of PND symptoms. Future studies that screen for victimisation and establish its explicit mechanism to the poorer prognosis of PND symptoms would benefit the prevention and treatment of PND.