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Impact of Prescribed and Self-Selected Music Interventions on Stress, Sleep, Heart Rate Variability, and Brain Connectivity in Surgeons Using 7-Tesla Functional Magnetic Resonance Imaging and Wearable Actigraphy: Multimodal Feasibility Randomized Controlled Trial

<strong>Background:</strong> Stress, sleep deprivation, and burnout are significant safety risks for acute care surgeons, negatively impacting performance, well-being, and clinical outcomes. <strong>Objective:</strong> This pilot randomized controlled trial aimed to measure neurophysiological effects of prescribed music (PM) and self-selected music (SSM) on surgeon stress, burnout, and neurophysiological responses using a multimodal protocol that integrated functional magnetic resonance imaging (fMRI), wearable biosensor monitoring, and psychological self-assessments. <strong>Methods:</strong> Full-time attending surgeons at a quaternary care hospital were invited to participate in a 3-armed trial (1:1:1 block allocation). Intervention groups were instructed to listen to 30 minutes (minimum 15 minutes) of either PM or SSM daily at bedtime for 6 weeks, reflecting real-world conditions. PM comprised original compositions based on elements promoting perceived relaxation from a prior study. The control arm avoided music in the 30 minutes before bed. Allocation was concealed from the recruiting investigator; the fMRI technicians, the statistician, and lead investigators were blinded until analyses were completed. Functional connectivity patterns were measured using fMRI at baseline and 6 weeks while participants listened to simulated intensive care unit noise, PM, and SSM. Secondary outcomes included continuous actigraphy for sleep quality and self-reported anxiety, sleep quality, and burnout using validated scales (State-Trait Anxiety Inventory, Pittsburgh Sleep Quality Index, and Maslach Burnout Inventory). <strong>Results:</strong> A total of 22 surgeons were assessed; demands of fMRI and data collection schedule led 3 to decline and 2 (allocated to PM) not to finish baseline measures; 6 PM, 5 SSM, and 6 controls received allocated intervention; 2 PM participants were withdrawn for nonadherence and missing follow-up data and 1 control missed follow-up collection due to scheduling (final analysis set after missing data: PM: n=4, SSM: n=5, control: n=5). One control participant experienced transient vertigo in fMRI. Trends in fMRI data indicated that both intervention groups experienced less negative emotional arousal and anxiety, with physical tension reduced in the PM group. The PM group exhibited reduced stress response in the frontal lobes when exposed to intensive care unit alarms, suggesting diminished attentional response to the high-stress auditory environment, compared to control. However, lack of statistical significance and baseline variability entail cautious interpretation. Observations of sleep quality were mixed, and no statistically significant differences in stress surveys were observed. <strong>Conclusions:</strong> Both music interventions trended toward positive changes in neurophysiological responses, suggesting potential benefits in reducing surgeon stress. However, due to the small sample, mixed or nonsignificant results, and the exploratory nature of this study, findings should be considered preliminary. Further research with larger, diverse cohorts is required to confirm trends, refine both the intervention approach and recruitment strategies, and determine whether objective compositional elements or personally selected music drive the mechanisms of potential positive effects. <strong>Trial Registration:</strong> ClinicalTrials.gov NCT05980429; https://clinicaltrials.gov/study/NCT05980429
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Exploring Influencing Factors of Medication Adherence Among Chinese Patients With Alzheimer Disease: Delphi Study Informing Future Artificial Intelligence–Supported Interventions

Background: Alzheimer disease (AD) affects cognition, treatment adherence, family connections, and health care resource allocation. Most patients with AD have low adherence to medication therapy due to the limitations associated with cognitive impairment. Therefore, increasing the involvement of patients and their family members in medication management is important to improve treatment outcomes and reduce the burden of care. Objective: This study explores the potential application of artificial intelligence (AI) in medication management for Chinese patients with early- to mid-stage AD focusing on enhancing medication adherence. The study first predicts and evaluates key factors through an online Delphi study, which provides a basis for their subsequent incorporation into the AI model as input variables to enable prediction of medication-taking behaviors. Since AI research in medication management for this population is still undeveloped, this paper further explores the multiple potentials of AI from a theoretical view, including drug dosage optimization, multidrug interaction detection, and family education support. It will provide a preliminary direction and theoretical basis for the development of an intelligent medication management system in the future. Methods: The exploratory online Delphi study with no modification predicted the key factors influencing medication adherence. Based on the results, the study confirmed the potential of AI to improve adherence. Participation by 12 experts in 3 rounds systematically assessed the core elements influencing patients’ adherence to their medication. Results: Family care, social support, environmental factors, emotional support, and patient behaviors were identified as the primary factors influencing medication adherence among Chinese patients with AD. These factors were validated and ranked through iterative Delphi rounds, with family care and social support receiving the highest importance scores. The Wilcoxon signed-rank test indicated no significant difference between rounds (=.06), supporting the stability of the consensus. These findings establish a foundational set of variables for AI systems that predict and enhance medication adherence. Conclusions: This study highlights the critical factors affecting medication adherence by Chinese patients with AD. It was designed as an exploratory online Delphi study to identify and prioritize key influencing factors, rather than to validate a specific AI-based system, and the findings provide a theoretical foundation for future AI-informed interventions. The results also indicate theoretical potential roles for AI in supporting medication management, such as optimizing drug dosage, detecting multidrug interactions, and enhancing family education.
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Development of iGET Living, a Digital Graded Exposure Intervention for Youth With Chronic Pain: Multiphase User-Centered Design and Pilot Study

Background: Pediatric chronic pain affects up to one-third of youth and is associated with significant disruptions in social, emotional, and behavioral functioning. Although behavioral treatments are effective, access remains limited due to geographic, financial, and systemic barriers. Digital behavioral health interventions offer a promising solution, but many lack user-centered design, iterative refinement, and implementation-informed development strategies that support usability and scalability. Objective: This study aimed to develop and iteratively refine iGET Living, a digital graded exposure intervention for youth with chronic pain, using a combined user-centered and implementation-informed framework, and to evaluate its preliminary acceptability, feasibility, and user-perceived success. Methods: Guided by the Consolidated Framework for Implementation Research (CFIR) and the mHealth (mobile health) Agile Development and Lifecycle model, intervention development proceeded through 3 phases. Phase 0 translated an evidence-based in-person graded exposure treatment (GET Living) into an initial digital prototype. Phase 1 involved iterative user-centered refinement across 3 cycles of qualitative development sessions with youth with chronic pain (n=15), incorporating think-aloud usability testing, Likert-rated feedback, and rapid qualitative analysis mapped to CFIR constructs to guide real-time modifications to content, design, and functionality. Phase 2 piloted the refined intervention with a new sample of youth (n=38, n=30 completers) recruited from a tertiary pediatric pain clinic to evaluate feasibility, acceptability, treatment credibility and expectancy, and user-perceived functional improvements. Quantitative outcomes were summarized descriptively, and qualitative exit interview data were analyzed using rapid qualitative analysis. Results: Across development cycles, youth feedback informed substantive refinements to the intervention, including reducing text density, incorporating animated educational videos, enhancing interactive features, and improving navigation and layout. These changes resulted in progressive improvements in clarity, satisfaction, and acceptability across prototypes. In the Phase 2 pilot study, participants reported moderate-to-high treatment credibility (mean of 19.71 out of 30) and expectancy (mean of 17.96 out of 30), as well as high satisfaction (mean of 46.12 out of 60). Acceptability ratings across domains of the Theoretical Framework of Acceptability were favorable. Qualitative exit interviews highlighted the interventions’ perceived role in helping youth re-engage in valued activities. Conclusions: Using a combined CFIR and agile development approach, iGET Living emerged as a feasible, acceptable, engaging digital graded exposure intervention for youth with chronic pain. These findings highlight the value of integrating implementation frameworks and participatory design early in digital intervention development and support further evaluation in a preliminary efficacy trial. Trial Registration: ClinicalTrials.gov NCT05079984; https://clinicaltrials.gov/study/NCT05079984 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2022-065997
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Cerebral blood flow and functional connectivity immediate changes following intradermal acupuncture in major depressive disorder

BackgroundAcupuncture has been increasingly applied as an adjunctive treatment for major depressive disorder (MDD), yet its central neurobiological mechanisms remain insufficiently understood. Cerebral blood flow (CBF) and functional connectivity strength (FCS) provide complementary perspectives on regional metabolic activity and large-scale functional integration, and their coupling may reflect neurovascular coordination relevant to depression.MethodsTwenty patients with MDD and twenty matched healthy controls (HC) underwent resting-state MRI. Patients received intradermal acupuncture (IA) and were scanned before and immediately after stimulation, while healthy controls were scanned once. Voxel-wise analyses of CBF, FCS, and their ratio (CBF/FCS) were performed to characterize acupuncture-related changes in neurovascular coupling. Group comparisons and pre–post acupuncture effects were assessed at the whole gray matter level.ResultsAcupuncture induced significant alterations in CBF/FCS coupling across widespread brain regions, including the bilateral precuneus, postcentral gyrus, superior temporal pole, superior frontal gyrus, occipital cortex, and cerebellum. These regions are primarily involved in sensorimotor processing, cognitive control, and emotional regulation. Overall, IA was associated with an immediate increase in CBF/FCS coupling, suggesting enhanced coordination between cerebral perfusion and functional network integration.ConclusionThis study provides evidence that intradermal acupuncture modulates neurovascular coupling in patients with MDD, offering neuroimaging-based insights into its antidepressant mechanisms. The findings support the notion that acupuncture may facilitate more efficient brain function by optimizing the balance between neural activity and metabolic supply.
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Effect of low-intensity focused ultrasound on hippocampus of alcohol addicted mice: a preliminary study

Alcohol addiction is a chronic relapsing brain disorder characterized by significant neurobiological changes, particularly within the hippocampus, which mediates emotional regulation and reward-seeking behavior. Previous studies have shown that alcohol-induced neuronal injury contributes to withdrawal-associated anxiety and persistent alcohol preference. This study investigated the therapeutic effects of low-intensity focused ultrasound (LIFU) on the hippocampus in a mouse model of alcohol addiction. Twenty-six male C57BL/6 mice were allocated to an alcohol-exposed group (n = 20) and a control group (n = 6). Following a 28-day modeling period, the alcohol group was randomly subdivided into a therapy group and a sham group. The therapy group received LIFU treatment, while the sham group underwent an identical procedure with the ultrasound transducer powered off. After seven days of treatment, the therapy group exhibited less severe anxiety symptoms upon alcohol withdrawal and a reduced preference for alcohol compared to the sham group. The brain-derived neurotrophic factor (BDNF) concentration was significantly lower in the therapy group than in the sham group, but did not differ significantly from the control group. Hippocampal HE staining revealed more pronounced degeneration and apoptosis of granule cells in the dentate gyrus (DG) region in the sham group relative to the therapy group. These preliminary findings suggest that LIFU may modulate alcohol addiction by mitigating hippocampal neuronal injury.
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The patterns of relapse and abstinence: using machine learning to identify a multidimensional signature of long-term outcome after inpatient alcohol withdrawal treatment

AimsA machine learning approach to identify a multidimensional signature associated with relapse and long-term outcome in alcohol dependence treatment.DesignIn this observational naturalistic study, inpatients with alcohol dependence received qualified detoxification plus CBT (Cognitive Behavioral Therapy) and were followed up 6-months after discharge to assess abstinence and drinking behavior. Cross-validated multivariate sparse partial least squares analysis (SPLS) was used to investigate the relationship between clinical features and four long-term outcome variables.SettingGermany.Participants152 patients (on average 47.8 years old, 72% male) with alcohol dependence, who received inpatient qualified detoxification plus CBT.Measurements35 clinical features were used to cover all three phases of inpatient treatment (pre-, within-, post-treatment). Among these, sociodemographic characteristics, ICD-10 psychiatric diagnoses, previous detoxification treatments, and somatic measurements as well as inpatient treatment setting such as withdrawal medication, liver ultrasound, further information about the patients´ stay, and post-inpatient care were assessed. The four outcome dimensions included: continuous abstinence, abstinence at follow up, daily alcohol consumption, and days of abstinence after discharge.FindingsSix months after withdrawal treatment 46% of the patients achieved continuous abstinence. Socioeconomic, clinical and somatic features across the treatment timeline were analyzed and summarized into a multivariate signature associated with long-term treatment outcome. Thereby, the SPLS algorithm identified regular completion of withdrawal treatment, higher education, and employment status to be most strongly associated with a positive outcome. Alcohol-related hepatic and hematopoietic damage, number of previous withdrawal treatments and living in a shelter were most profoundly associated with a negative outcome.ConclusionConceiving treatment outcome as a multidimensional signature and moving beyond simple binary classifications of relapse versus abstinence may improve the understanding of relapse pathways and support more individualized treatment strategies.
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Interoceptive dysfunction and its neural correlates in schizophrenia: protocol for a cross-sectional multimodal MRI study

BackgroundInteroception—the perception and integration of internal bodily signals—is fundamental to emotion regulation, bodily self-awareness, and predictive coding. Emerging evidence suggests that interoceptive disturbances may contribute to core psychopathological features of schizophrenia. Our research group recently conducted a systematic review and meta-analysis demonstrating significant impairments in interoceptive accuracy and sensitivity among individuals with schizophrenia. However, the neural mechanisms underlying these deficits remain unclear.MethodsThis cross-sectional protocol will recruit 30 individuals with schizophrenia and 30 age- and sex-matched healthy controls. Participants will complete (1) behavioral interoceptive assessment using the heartbeat counting task; (2) subjective interoceptive questionnaires, including the Multidimensional Assessment of Interoceptive Awareness (MAIA) and the Body Perception Questionnaire (BPQ); (3) clinical symptom ratings (PANSS, HAM-A, HAM-D); and (4) cognitive testing (TMT, animal fluency, DSST). All participants will undergo multimodal MRI scanning, including structural T1-weighted imaging, resting-state fMRI, and diffusion tensor imaging. Neuroimaging data will be preprocessed and analyzed using DPABISurf, SPM12, and GRETNA. Expected Results: We anticipate that individuals with schizophrenia will show reduced interoceptive accuracy, altered subjective interoceptive awareness, and abnormal intrinsic neural activity and connectivity within interoception-related circuits, including the anterior insula, anterior cingulate cortex, amygdala, and thalamus. Structural abnormalities within thalamo-cortical pathways are also expected. Interoceptive deficits are hypothesized to correlate with symptom severity and cognitive performance.ConclusionsThis study will provide an integrated characterization of interoceptive dysfunction and its neural correlates in schizophrenia. Findings may advance understanding of bodily self-disturbance and emotional dysregulation and support the development of future interoception-focused therapeutic approaches.Clinical trial registrationhttps://www.chictr.org.cn/, identifier ChiCTR2500110551.
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Anxiety among Chinese primary school teachers under the “double reduction” policy: prevalence and associated factors

ObjectivesThe implementation of the “Double Reduction” Policy in China has raised concerns about increased anxiety levels among primary school teachers. However, the prevalence of anxiety symptoms and the factors associated with them remain unclear. This study aims to investigate the prevalence and correlates of anxiety among primary school teachers under this policy.MethodsA cross-sectional survey was conducted from September to October 2022 among primary school teachers in 15 cities across China. Participants completed a series of questionnaires administered via WeChat to assess anxiety symptoms and potential related factors, including perceived stress, sociodemographic characteristics, and job-related variables. Anxiety and perceived stress were measured using the Generalized Anxiety Disorder-7 (GAD-7) and 10-item Perceived Stress Scale (PSS-10), respectively.ResultsOverall, 44.5% (1,423/3,199) of teachers reported at least mild anxiety symptoms. Among them, 56.43%, 25.30% and 18.27% had mild, moderate, and severe anxiety, respectively. In the final logistic regression model, five variables remained independently associated with anxiety: education level (master’s degree or above: OR = 2.781, 95% CI: 1.858–4.163), income dissatisfaction (OR = 1.487, 95% CI: 1.205–1.834), intermediate professional title (OR = 1.372, 95% CI: 1.084–1.738), younger age (OR = 0.979, 95% CI: 0.966–0.993), and perceived stress (OR = 1.489, 95% CI: 1.443–1.538).ConclusionAnxiety was prevalent among primary school teachers during the implementation of the “Double Reduction” Policy. Higher education level, income dissatisfaction, intermediate professional title, younger age, and elevated perceived stress were significant risk factors for anxiety. Therefore, interventions focusing on stress management and occupational support may help improve teachers’ mental well-being.