BACKGROUND: This study aimed to identify the developmental trajectories of loneliness in Chinese children and examine the predictive roles of domain-specific environmental factors (i.e., family dysfunction and satisfaction of relatedness needs at school), personality factors (i.e., neuroticism and extraversion), and their interactions in these developmental trajectories.
METHODS: A total of 702 Chinese children (Mage = 8.95, SD = 0.76; 54.1 % boys) participated in assessments at six time points over three years at six-month intervals. Growth mixture modeling (GMM) was used to estimate trajectory classes for loneliness, followed by multivariate logistic regression analyses exploring associations between these classes and predictors.
RESULTS: GMM analyses identified three distinct trajectories of loneliness: \"low-stable\" (81.5 %), \"moderate-increasing\" (9.4 %), and \"high-decreasing\" (9.1 %). Multivariate logistic regression analyses revealed that family dysfunction and neuroticism served as risk factors for adverse loneliness trajectories, while satisfaction of relatedness needs at school and extraversion acted as protective factors. Furthermore, the interaction between family dysfunction and extraversion indicated that extraversion did not mitigate the adverse effects of high family dysfunction on children\'s loneliness, emphasizing the vital need to support positive family functioning among all children.
CONCLUSIONS: This study did not incorporate biological variables (e.g., genetics), which are crucial in the evolutionary theory of loneliness.
CONCLUSIONS: The identification of three distinct trajectory groups of children\'s loneliness, along with key environmental and personality predictors, suggests that interventions should be tailored to each group\'s unique characteristics.

BACKGROUND: Surgical resection is the primary treatment for gastrointestinal (GI) cancers, but postoperative skeletal muscle loss (SML) is common and linked to poor prognosis. This study aims to identify patterns of muscle change, examine its association with quality of life (QoL), and explore predictors of SML in the first 3 months.
METHODS: A prospective cohort study was conducted on patients newly diagnosed with GI cancer and undergoing surgery in China between September 2021 and May 2022. Skeletal muscle mass (SMM) and QoL were assessed at admission, 7 days, 1 month, and 3 months post-surgery. Demographic, clinical data, and biomarkers were collected. Missing data were imputed using multiple imputation. Data were analyzed using growth mixture modelling, bivariate analyses, and logistic regression.
RESULTS: A total of 483 patients completed baseline assessment. Of the 242 patients with complete muscle assessments, 92% experienced SML. Three distinct patterns of muscle change were identified: 57% had normal preoperative SMM with mild postoperative SML, 16% had low preoperative SMM with moderate SML, and 27% had normal preoperative mass but severe postoperative SML. Moderate/severe SML was associated with more postoperative complications, poorer health, and higher symptom burden. Independent predictors included advanced age, preoperative sarcopenia, advanced cancer stage, and low prognostic nutrition index (PNI ≤ 45). The results did not change when using imputed values.
CONCLUSIONS: Although SML is prevalent, patterns of muscle change are heterogeneous among patients. Advanced age, preoperative sarcopenia, advanced cancer stage, and cancer-related inflammation are predictors for moderate/severe SML, highlighting the need for early detection and management.

BACKGROUND: Neuropsychiatric symptoms are common after traumatic brain injury (TBI) and often resolve within 3 months post-injury. However, the degree to which individual patients follow this course is unknown. We characterized trajectories of neuropsychiatric symptoms over 12 months post-TBI. We hypothesized that a substantial proportion of individuals would display trajectories distinct from the group-average course, with some exhibiting less favorable courses.
METHODS: Participants were level 1 trauma center patients with TBI (n = 1943), orthopedic trauma controls (n = 257), and non-injured friend controls (n = 300). Trajectories of six symptom dimensions (Depression, Anxiety, Fear, Sleep, Physical, and Pain) were identified using growth mixture modeling from 2 weeks to 12 months post-injury.
RESULTS: Depression, Anxiety, Fear, and Physical symptoms displayed three trajectories: Stable-Low (86.2-88.6%), Worsening (5.6-10.9%), and Improving (2.6-6.4%). Among symptomatic trajectories (Worsening, Improving), lower-severity TBI was associated with higher prevalence of elevated symptoms at 2 weeks that steadily resolved over 12 months compared to all other groups, whereas higher-severity TBI was associated with higher prevalence of symptoms that gradually worsened from 3-12 months. Sleep and Pain displayed more variable recovery courses, and the most common trajectory entailed an average level of problems that remained stable over time (Stable-Average; 46.7-82.6%). Symptomatic Sleep and Pain trajectories (Stable-Average, Improving) were more common in traumatically injured groups.
CONCLUSIONS: Findings illustrate the nature and rates of distinct neuropsychiatric symptom trajectories and their relationship to traumatic injuries. Providers may use these results as a referent for gauging typical v. atypical recovery in the first 12 months post-injury.

This study aimed to identify different symptom trajectories based on the severity of depression symptoms within a 2-month follow-up, and to explore predictive factors for different symptom trajectories. Three hundred and ninety-two adults diagnosed with major depressive disorder (MDD) were recruited from two longitudinal cohorts. Patients received antidepressant treatment as usual, and the depression symptoms were evaluated by the 17-item Hamilton depression rating scale (HAMD-17) at baseline, two weeks, and eight weeks. Based on the HAMD-17 scores, different trajectories of symptom change were distinguished by applying Growth Mixture Modeling (GMM). Furthermore, the baseline sociodemographic, clinical, and cognitive characteristics were compared to identify potential predictors for different trajectories. Through GMM, three unique depressive symptom trajectories of MDD patients were identified: (1) mild-severity class with significant improvement (Mild, n = 255); (2) high-severity class with significant improvement (High, n = 39); (3) moderate-severity class with limited improvement (Limited, n = 98). Among the three trajectories, the Mild class had a relatively low level of anxiety symptoms at baseline, whereas the High class had the lowest education level and the worst cognitive performance. Additionally, participants in the Limited class exhibited an early age of onset and experienced a higher level of emotional abuse. MDD patients could be categorised into three distinct latent subtypes through different symptom trajectories in this study, and the characteristics of these subtype patients may inform identifications for trajectory-specific intervention targets.

Understanding longitudinal cognitive performance in individuals at ultra-high risk for psychosis (UHR) is important for informing theoretical models and treatment. A vital step in this endeavor is to determine whether there are UHR subgroups that have similar patterns of cognitive change over time. The aims were to: i) identify latent class trajectories of cognitive performance over 12-months in UHR individuals, ii) identify baseline demographic and clinical predictors of the resulting classes, and iii) determine whether trajectory classes were associated with transition to psychosis or functional outcomes. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia (BACS) at baseline, 6- and 12-months (N = 288). Using Growth Mixture Modeling, a single unimpaired improving trajectory class was observed for motor function, speed of processing, verbal fluency, and BACS composite. A two-class solution was observed for executive function and working memory, showing one unimpaired and a second impaired class. A three-class solution was found for verbal learning and memory: unimpaired, mildly impaired, and initially extremely impaired, but improved (\"caught up\") to the level of the mildly impaired. IQ, omega-3 index, and premorbid adjustment were associated with class membership, whereas clinical variables (symptoms, substance use), including transition to psychosis, were not. Working memory and verbal learning and memory trajectory class membership was associated with functioning outcomes. These findings suggest there is no short-term progressive cognitive decline in help-seeking UHR individuals, including those who transition to psychosis. Screening of cognitive performance may be useful for identifying UHR individuals who may benefit from targeted cognitive interventions.

BACKGROUND: Data-driven classification of long-term psychotic symptom trajectories and identification of associated risk factors could assist treatment planning and improve long-term outcomes in psychosis. However, few studies have used this approach, and knowledge about underlying mechanisms is limited. Here, we identify long-term psychotic symptom trajectories and investigate the role of illness-concurrent cannabis and stimulant use.
METHODS: 192 participants with first-episode psychosis were followed up after 10 years. Psychotic symptom trajectories were estimated using growth mixture modeling and tested for associations with baseline characteristics and cannabis and stimulant use during the follow-up (FU) period.
RESULTS: Four trajectories emerged: (1) Stable Psychotic Remission (54.2 %), (2) Delayed Psychotic Remission (15.6 %), (3) Psychotic Relapse (7.8 %), (4) Persistent Psychotic Symptoms (22.4 %). At baseline, all unfavorable trajectories (2-4) were characterized by more schizophrenia diagnoses, higher symptom severity, and longer duration of untreated psychosis. Compared to the Stable Psychotic Remission trajectory, unstable trajectories (2,3) showed distinct associations with cannabis/stimulant use during the FU-period, with dose-dependent effects for cannabis but not stimulants (Delayed Psychotic Remission: higher rates of frequent cannabis and stimulant use during the first 5 FU-years; Psychotic Relapse: higher rates of sporadic stimulant use throughout the entire FU-period). The Persistent Psychosis trajectory was less clearly linked to substance use during the FU-period.
CONCLUSIONS: The risk for an adverse long-term course could be mitigated by treatment of substance use, where particular attention should be devoted to preventing the use of stimulants while the use reduction of cannabis may already yield positive effects.

High utilization by a minority of patients accounts for a large share of health care costs, but the dynamics of this utilization remain poorly understood. We sought to characterize longitudinal trajectories of hospitalization among adult patients at an academic medical center from 2017 to 2023. Among 3404 patients meeting eligibility criteria, following an initial \"rising-risk\" period of 3 hospitalizations in 6 months, growth mixture modeling discerned 4 clusters of subsequent hospitalization trajectories: no further utilization, low chronic utilization, persistently high utilization with a slow rate of increase, and persistently high utilization with a fast rate of increase. Baseline factors associated with higher-order hospitalization trajectories included admission to a nonsurgical service, full code status, intensive care unit-level care, opioid administration, discharge home, and comorbid cardiovascular disease, end-stage kidney or liver disease, or cancer. Characterizing hospitalization trajectories and their correlates in this manner lays groundwork for early identification of those most likely to become high-need, high-cost patients.

UNASSIGNED: Children and adolescents with elevated internalizing symptoms are at increased risk for depression, anxiety, and other psychopathology later in life. The present study examined the predictive links between two bioecological factors in early childhood-parental hostility and socioeconomic stress-and children\'s internalizing symptom class outcomes, while considering the effects of child sex assigned at birth on internalizing symptom development from childhood to adolescence.
UNASSIGNED: The study used a sample of 1,534 children to test the predictive effects of socioeconomic stress at ages 18 and 27 months; hostile parenting measured at child ages 4-5; and sex assigned at birth on children\'s internalizing symptom latent class outcomes at child ages 7-9, 10-12, 13-15, and 16-19. Analyses also tested the mediating effect of parenting on the relationship between socioeconomic stress and children\'s symptom classes. Other covariates included parent depressive symptoms at child ages 4-5 and child race and ethnicity.
UNASSIGNED: Analyses identified three distinct heterogenous internalizing symptom classes characterized by relative symptom levels and progression: low (35%); moderate and increasing (41%); and higher and increasing (24%). As anticipated, higher levels of parental hostility in early childhood predicted membership in the higher and increasing symptom class, compared with the low symptom class (odds ratio (OR) = .61, 95% confidence interval (CI) [.48,.77]). Higher levels of early childhood socioeconomic stress were also associated with the likelihood of belonging to the higher-increasing symptom class compared to the low and moderate-increasing classes (OR = .46, 95% CI [.35,.60] and OR = .56, 95% CI [.44,.72], respectively). The total (c = .61) and direct (c\' = .57) effects of socioeconomic stress on children\'s symptom class membership in the mediation analysis were significant (p <.001).
UNASSIGNED: Study findings suggest that intervening on modifiable bioecological stressors-including parenting behaviors and socioeconomic stressors-may provide important protective influences on children\'s internalizing symptom trajectories.

OBJECTIVE: To investigate the trajectories and potential categories of changes in the sense of coherence (SOC) in patients after colorectal cancer surgery and to analyze predictive factors.
METHODS: From January to July 2023, 175 patients with colorectal cancer treated at a tertiary Grade A oncology hospital in Jiangsu Province were selected as the study subjects. Prior to surgery, SOC-13 scale, Patient-Generated Subjective Global Assessment (PG-SGA), Brief Illness Perception Questionnaire (BIPQ), and Social Support Rating Scale (SSRS) were used to survey the patients. SOC levels were measured multiple times at 1 week, 1 month, and 3 months post-surgery. Growth Mixture Modeling (GMM) was applied to fit the trajectory changes of SOC in patients after colorectal cancer surgery. Multinomial logistic regression was used to analyze the predictive factors of SOC trajectory changes.
RESULTS: The SOC scores of patients at points T1-T4 were (65.27 ± 9.20), (63.65 ± 10.41), (63.85 ± 11.84), and (61.56 ± 12.65), respectively. Multinomial logistic regression results indicated that gender, employment status, disease stage, household monthly income, intestinal stoma, nutritional status, illness perception, and social support were predictors of SOC trajectory changes (P < 0.05).
CONCLUSIONS: There is heterogeneity in the trajectory changes of SOC in patients after colorectal cancer surgery. Healthcare professionals should implement early precision interventions based on the patterns of changes and predictive factors in each trajectory category.

A large body of research has documented racial/ethnic disparities in childhood obesity in the United States (US) but less work has sought to understand differences within racial groups. Longitudinal studies are needed to describe BMI trajectories across development, particularly for Black children from immigrant families who have been underrepresented in childhood obesity research. The current study utilizes BMI data collected longitudinally from ages 5 to 8 years and growth mixture modeling to (1) identify and visualize growth patterns among Black children from primarily Caribbean immigrant families, and (2) to compare these patterns to growth trajectories among Black children from US-born families. First, we identified four classes or trajectories of growth for Black children from immigrant families. The largest trajectory (70% of the sample) maintained non-overweight throughout the study period. A second trajectory developed overweight by age 8 (25%). Two small trajectory groups demonstrated high rates of moderate and severe obesity-i.e., specifically, a trajectory of accelerated weight gain ending in moderate/severe obesity (3%), and a trajectory of early severe obesity with BMI decreasing slightly with age (2%). We identified a very similar four class/trajectory model among Black children from US-born families, and compared the model to the one for children from immigrant families using multi-group growth mixture modeling. We found that the patterns of growth did not differ significantly between the populations, with two notable exceptions. Among Black children from immigrant families, ∼ 5% were classified into the two heavier BMI trajectories, compared to ∼ 11% of children from US-born families. Additionally, among children with an accelerated weight gain trajectory, children from immigrant families had lower BMIs on average at each time point than children from US-born families. These findings describe the multiple trajectories of weight gain among Black children from immigrant families and demonstrate that although these trajectories are largely similar to those of Black children from US-born families, the differences provide some evidence for lower obesity risk among Black children from immigrant families compared to Black children from US-born families. As this study is the first to describe BMI trajectories for Black children from immigrant families across early and middle childhood, future work is needed to replicate these results and to explore differences in heavier weight trajectories between children from immigrant and US-born families.